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|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
4efa4f577a65b005da3b33e71203cf0431e9f05f
|
caa95ce8dbc1f48cfa0f605226688239359ded33
|
/examples/continuous/CMCEditted_SmartStart_DDPG_Baselines_experimenter.py
|
b32e2e6b82358dee0314a43a966d67433e0dbe61
|
[] |
no_license
|
darren-huang/SmartStartContinuous
|
6ae9c9240a6a8686295689e553ff5e1cfe0c11c7
|
07b80e01a5a4590ee2fd88a344cd89be8688ca3d
|
refs/heads/master
| 2020-03-26T12:10:47.623766
| 2018-08-25T23:14:46
| 2018-08-25T23:14:46
| 144,879,450
| 2
| 0
| null | 2018-08-25T22:37:59
| 2018-08-15T16:53:22
|
Python
|
UTF-8
|
Python
| false
| false
| 13,083
|
py
|
import gym
import random
from environments.continuous_mountain_car_editted import Continuous_MountainCarEnv_Editted
from smartstart.RLAgents.DDPG_Baselines_agent import DDPG_Baselines_agent
from smartstart.smartexploration.smartexplorationcontinuous import SmartStartContinuous
from smartstart.reinforcementLearningCore.rlTrain import rlTrain
from smartstart.utilities.experimenter import run_experiment, create_experimeter_info_txt
from smartstart.utilities.utilities import set_global_seeds, get_default_data_directory
def task_run_ss_ddpg_baselines_mc(params):
import tensorflow as tf
print("\n\nprocess " + str(params['id']) + " has started" + "-"*200 + "\n")
noGpu = params['noGpu']
render = False
replay_buffer = None
# random seed each time
random.seed()
RANDOM_SEED = random.randint(0, 2**32 - 1)
# Overall Options
episodes = params['episodes']
dir_name = params['dir_name']
#naming function
get_extra_name = params['get_extra_name']
# configuring environment
env = Continuous_MountainCarEnv_Editted.make_timed_env(params['power_scalar'],
max_episode_steps=params['max_episode_steps'],
max_episode_seconds=params['max_episode_seconds'])
if noGpu:
tfConfig = tf.ConfigProto(device_count={'GPU': 0})
else:
tfConfig = None
with tf.Graph().as_default() as graph:
with tf.Session(config=tfConfig, graph=graph) as sess:
# with tf.Session() as sess:
# Reset the seed for random number generation
set_global_seeds(RANDOM_SEED)
env.seed(RANDOM_SEED)
# Initialize agent, see class for available parameters
base_agent = DDPG_Baselines_agent(env, sess,
replay_buffer=replay_buffer,
buffer_size=params['buffer_size'],
batch_size = params['batch_size'],
num_train_iterations = params['num_train_iterations'],
num_steps_before_train = params['num_steps_before_train'],
ou_epsilon = params['ou_epsilon'],
ou_min_epsilon = params['ou_min_epsilon'],
ou_epsilon_decay_factor = params['ou_epsilon_decay_factor'],
ou_mu = params['ou_mu'],
ou_sigma = params['ou_sigma'],
ou_theta = params['ou_theta'],
actor_lr = params['actor_lr'],
actor_h1 = params['actor_h1'],
actor_h2 = params['actor_h2'],
critic_lr = params['critic_lr'],
critic_h1 = params['critic_h1'],
critic_h2 = params['critic_h2'],
gamma = params['gamma'],
tau = params['tau'],
layer_norm = params['layer_norm'],
normalize_observations = params['normalize_observations'],
normalize_returns = params['normalize_returns'],
critic_l2_reg = params['critic_l2_reg'],
enable_popart = params['enable_popart'],
clip_norm = params['clip_norm'],
reward_scale = params['reward_scale'],
lastLayerTanh = params['lastLayerTanh'],
finalizeGraph=False
)
smart_start_agent = SmartStartContinuous(base_agent, env, sess,
buffer_size=params['buffer_size'],
exploitation_param = params['exploitation_param'],
exploration_param = params['exploration_param'],
eta = params['eta'],
eta_decay_factor = params['eta_decay_factor'],
n_ss = params['n_ss'],
print_ss_stuff=True,
# sigma=params['sigma'],
# smart_start_selection_modified_distance_function=params['smart_start_selection_modified_distance_function'],
nnd_mb_final_steps = params['nnd_mb_final_steps'],
nnd_mb_steps_per_waypoint = params['nnd_mb_steps_per_waypoint'],
nnd_mb_mean_per_stepsize = params['nnd_mb_mean_per_stepsize'],
nnd_mb_std_per_stepsize = params['nnd_mb_std_per_stepsize'],
nnd_mb_stepsizes_in_waypoint_radii = params['nnd_mb_stepsizes_in_waypoint_radii'],
nnd_mb_gamma = params['nnd_mb_gamma'],
nnd_mb_horizontal_penalty_factor = params['nnd_mb_horizontal_penalty_factor'],
nnd_mb_horizon = params['nnd_mb_horizon'],
nnd_mb_num_control_samples = params['nnd_mb_num_control_samples'],
nnd_mb_path_shortcutting= params['nnd_mb_path_shortcutting'],
nnd_mb_steps_before_giving_up_on_waypoint=params['nnd_mb_steps_before_giving_up_on_waypoint'],
nnd_mb_load_dir_name = params['nnd_mb_load_dir_name'],
nnd_mb_load_existing_training_data = params['nnd_mb_load_existing_training_data'],
nnd_mb_num_fc_layers = params['nnd_mb_num_fc_layers'],
nnd_mb_depth_fc_layers = params['nnd_mb_depth_fc_layers'],
nnd_mb_batchsize = params['nnd_mb_batchsize'],
nnd_mb_lr = params['nnd_mb_lr'],
nnd_mb_nEpoch = params['nnd_mb_nEpoch'],
nnd_mb_fraction_use_new = params['nnd_mb_fraction_use_new'],
nnd_mb_num_episodes_for_aggregation = params['nnd_mb_num_episodes_for_aggregation'],
nnd_mb_make_aggregated_dataset_noisy = params['nnd_mb_make_aggregated_dataset_noisy'],
nnd_mb_make_training_dataset_noisy = params['nnd_mb_make_training_dataset_noisy'],
nnd_mb_noise_actions_during_MPC_rollouts = params['nnd_mb_noise_actions_during_MPC_rollouts'],
nnd_mb_verbose = params['nnd_mb_verbose'])
sess.graph.finalize()
# Train the agent, summary contains training data
summary = rlTrain(smart_start_agent, env, render=render,
render_episode=False,
print_steps=False,
print_results=False,
num_episodes=episodes,
print_time=False,
progress_bar=True,
id=params['id'],
num_ticks=params['num_ticks']) # type: Summary
summary.add_params_to_param_dict(zz_RANDOM_SEED=RANDOM_SEED, zz_episodes=episodes, noGpu=noGpu)
fp = summary.save(get_default_data_directory(dir_name), last_name_section=True,
extra_name_append= get_extra_name(params))
print("\n\nprocess " + str(params['id']) + " has finished" + "!" * 200 + "\n")
# train_writer = tf.summary.FileWriter(fp[:-35])
# train_writer.add_graph(sess.graph)
# Define the task function for the experiment
def task_print(params):
# print(sorted(params.items(), key=lambda x: x[0]))
print(params['get_extra_name'](params))
def get_extra_name(params):
exploration_param_str = "_explorP-" + str(params['exploration_param'])
eta_decay_str = "_etaDecay-" + str(params['eta_decay_factor'])
wp_give_up_str = "_wpGiveUp-" + str(params['nnd_mb_steps_before_giving_up_on_waypoint'])
return exploration_param_str + eta_decay_str + wp_give_up_str
if __name__ == "__main__":
experiment_task = task_run_ss_ddpg_baselines_mc
#changeable parameter
num_exp_per_param = 50
episodes = 1000
noGpu = True
lastLayerTanh = True
#naming / display
num_ticks = 200 #ticks to display while the process is running
decaying_noise = True #must be the case that these match the parameters
dir_name = 'smart_start_continuous_summaries/ddpg_baselines/good_params_cont_mc_editted'
paramsGrid = {
'task' : experiment_task,
'num_exp' : num_exp_per_param,
'num_ticks' : [num_ticks],
'episodes' : [episodes],
'decayingNoise' : [decaying_noise],
'dir_name' : [dir_name],
'noGpu' : [noGpu],
'power_scalar': [.4], # CONSTANT
'max_episode_steps': [1000],
'max_episode_seconds': [None],
'buffer_size': [100000],
'batch_size': [64],
'num_train_iterations': [1],
'num_steps_before_train': [1],
'ou_epsilon': [1.0],
'ou_min_epsilon': [0.01],
'ou_epsilon_decay_factor': [.99],
'ou_mu': [0.4],
'ou_sigma': [0.6],
'ou_theta': [.15],
'actor_lr': [0.001], # these are the optimal critic and actor sizes : )
'actor_h1': [64],
'actor_h2': [32],
'critic_lr': [0.001],
'critic_h1': [64],
'critic_h2': [32],
'gamma': [0.99],
'tau': [0.001],
'layer_norm': [False],
'normalize_observations': [False],
'normalize_returns': [False],
'critic_l2_reg': [0],
'enable_popart': [False],
'clip_norm': [None],
'reward_scale': [1.],
'lastLayerTanh': [lastLayerTanh],
'exploitation_param': [1.],
'exploration_param': [2.], # CONSTANT
'eta': [0.5],
'eta_decay_factor': [.99, .995], # NOT CONSTANT
'n_ss': [2000],
'nnd_mb_final_steps': [10],
'nnd_mb_steps_per_waypoint': [1],
'nnd_mb_mean_per_stepsize': [1],
'nnd_mb_std_per_stepsize': [1],
'nnd_mb_stepsizes_in_waypoint_radii': [1],
'nnd_mb_gamma': [.75],
'nnd_mb_horizontal_penalty_factor': [.5],
'nnd_mb_horizon': [4],
'nnd_mb_num_control_samples': [5000],
'nnd_mb_path_shortcutting' : [True],
'nnd_mb_steps_before_giving_up_on_waypoint' : [5], # CONSTANT
'nnd_mb_load_dir_name': ["default"],
'nnd_mb_load_existing_training_data': [True],
'nnd_mb_num_fc_layers': [1],
'nnd_mb_depth_fc_layers': [32],
'nnd_mb_batchsize': [512],
'nnd_mb_lr': [0.001],
'nnd_mb_nEpoch': [30],
'nnd_mb_fraction_use_new': [0.9],
'nnd_mb_num_episodes_for_aggregation': [4],
'nnd_mb_make_aggregated_dataset_noisy': [True],
'nnd_mb_make_training_dataset_noisy': [True],
'nnd_mb_noise_actions_during_MPC_rollouts': [True],
'nnd_mb_verbose': [False],
'get_extra_name' : [get_extra_name]
}
noGpu_str = "_NoGPU" if noGpu else ""
llTanh_str = "_LLTanh" if lastLayerTanh else ""
decayingNoise_str = "_decayingNoise" if decaying_noise else ""
if len(paramsGrid['nnd_mb_num_fc_layers']) == 1 and len(paramsGrid['nnd_mb_depth_fc_layers']) == 1:
fc_layer_str = "_fcLayer-" + str(paramsGrid['nnd_mb_num_fc_layers'][0]) + "lyrs-" + str(paramsGrid['nnd_mb_depth_fc_layers'][0]) +"dpth"
else:
fc_layer_str = ""
create_experimeter_info_txt(paramsGrid, get_default_data_directory(dir_name),
name_append= "_MountainCarContEditted_" + str(episodes) + "ep" + noGpu_str + llTanh_str + decayingNoise_str + fc_layer_str)
run_experiment(paramsGrid, n_processes=-1)
|
[
"darren.y.huang@berkeley.edu"
] |
darren.y.huang@berkeley.edu
|
7fabf8240dcacb728f45fa30c16f1d86b565d56c
|
07cbae096598c6bd3c18626b0525960d6641bff5
|
/kafka/producer.py
|
eaa130093bc195a04848b2ce63185c8510d450c6
|
[] |
no_license
|
wangshoujunnew/tensorflow_learn
|
337852be27350d45346d982f20ad48430c3836cf
|
cf4b627a39b2cf9a8d79cedf3825aa3cfef5d1e2
|
refs/heads/master
| 2020-04-08T16:09:01.818340
| 2018-12-24T02:22:18
| 2018-12-24T02:22:18
| 159,506,289
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 384
|
py
|
#encoding=utf-8
from kafka import KafkaClient, KafkaProducer, KafkaConsumer
# 给kafka集群发送数据,生产者
cluster_host = '172.31.11.221:9092,172.31.11.222:9092,172.31.11.223:9092'
topic = 'test_topic'
group_id = 'test-python-test_topic'
producter = KafkaProducer(bootstrap_servers=cluster_host)
producter.send(topic=topic, value='from shoujunw test ... ')
producter.flush()
|
[
"noreply@github.com"
] |
wangshoujunnew.noreply@github.com
|
12889c1e3f168a30b0fa49c05210b3d362812643
|
eaf976115834853cc1372ac5501978899381a24d
|
/rich/measure.py
|
35af5a0b0736c4330aeb0630415cd82ad8492b6e
|
[
"MIT"
] |
permissive
|
JettChenT/rich
|
01812de0822ba9d1847198bf564d2a4a121a092a
|
bd98aafb68273847e01b32a38f11461e59f472e4
|
refs/heads/master
| 2022-12-07T18:49:24.610192
| 2020-08-24T11:31:14
| 2020-08-24T11:31:14
| 285,136,370
| 0
| 0
|
MIT
| 2020-08-24T11:31:15
| 2020-08-05T00:40:26
| null |
UTF-8
|
Python
| false
| false
| 3,884
|
py
|
from operator import itemgetter
from typing import Iterable, NamedTuple, TYPE_CHECKING
from . import errors
from .protocol import is_renderable
if TYPE_CHECKING:
from .console import Console, RenderableType
class Measurement(NamedTuple):
"""Stores the minimum and maximum widths (in characters) required to render an object."""
minimum: int
"""Minimum number of cells required to render."""
maximum: int
"""Maximum number of cells required to render."""
@property
def span(self) -> int:
"""Get difference between maximum and minimum."""
return self.maximum - self.minimum
def normalize(self) -> "Measurement":
"""Get measurement that ensures that minimum <= maximum and minimum >= 0
Returns:
Measurement: A normalized measurement.
"""
minimum, maximum = self
minimum = min(max(0, minimum), maximum)
return Measurement(max(0, minimum), max(0, max(minimum, maximum)))
def with_maximum(self, width: int) -> "Measurement":
"""Get a RenderableWith where the widths are <= width.
Args:
width (int): Maximum desired width.
Returns:
RenderableWidth: new RenderableWidth object.
"""
minimum, maximum = self
return Measurement(min(minimum, width), min(maximum, width))
@classmethod
def get(
cls, console: "Console", renderable: "RenderableType", max_width: int = None
) -> "Measurement":
"""Get a measurement for a renderable.
Args:
console (~rich.console.Console): Console instance.
renderable (RenderableType): An object that may be rendered with Rich.
max_width (int, optional): The maximum width available, or None to use console.width.
Defaults to None.
Raises:
errors.NotRenderableError: If the object is not renderable.
Returns:
Measurement: Measurement object containing range of character widths required to render the object.
"""
_max_width = console.width if max_width is None else max_width
if isinstance(renderable, str):
renderable = console.render_str(renderable)
renderable = getattr(renderable, "__rich__", renderable)
if is_renderable(renderable):
get_console_width = getattr(renderable, "__rich_measure__", None)
if get_console_width is not None:
render_width = (
get_console_width(console, _max_width)
.normalize()
.with_maximum(_max_width)
)
return render_width.normalize()
else:
return Measurement(1, _max_width)
else:
raise errors.NotRenderableError(
f"Unable to get render width for {renderable!r}; "
"a str, Segment, or object with __rich_console__ method is required"
)
def measure_renderables(
console: "Console", renderables: Iterable["RenderableType"], max_width: int
) -> "Measurement":
"""Get a measurement that would fit a number of renderables.
Args:
console (~rich.console.Console): Console instance.
renderables (Iterable[RenderableType]): One or more renderable objects.
max_width (int): The maximum width available.
Returns:
Measurement: Measurement object containing range of character widths required to
contain all given renderables.
"""
get_measurement = Measurement.get
measurements = [
get_measurement(console, renderable, max_width) for renderable in renderables
]
measured_width = Measurement(
max(measurements, key=itemgetter(0)).minimum,
max(measurements, key=itemgetter(1)).maximum,
)
return measured_width
|
[
"willmcgugan@gmail.com"
] |
willmcgugan@gmail.com
|
a1cf71010db2976eef6025ea85ec14e2a6a9ce8b
|
b721a2744096c5cc44d22eb303e0fc288c8c3679
|
/account/urls.py
|
0dc7c8d992b8d387fc203ea80c1fbfd0d8617ae2
|
[] |
no_license
|
Rasel120/Python-blog-project
|
91cacdb12834bbcfea2b9b3a64153952d94d5d04
|
20e1561d06eb9ab6144bb50101b061acf9680914
|
refs/heads/main
| 2023-06-05T08:22:25.509881
| 2021-06-17T09:21:04
| 2021-06-17T09:21:04
| 375,974,709
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 352
|
py
|
from django.urls import path
from .import views
urlpatterns = [
path('', views.authlogin, name='login'),
path('logout/', views.authlogout, name='logsout'),
path('register/', views.authregister, name='registration'),
path('forgot/', views.authforgot, name='forgotpass'),
path('profile/', views.authprofile, name='userprofile'),
]
|
[
"raselhossain120@gmail.com"
] |
raselhossain120@gmail.com
|
beeeb4805e5fc65df1730bbc7329a1679c1c8d3f
|
b78798473c39a4348a4bd4dfb94a00427f03e57a
|
/portfolio/urls.py
|
223830f008a714f02a7e7d75e30ecd4089c0299f
|
[] |
no_license
|
Limenation/portfolio
|
bd466cca2fa313b08fe4965ae36e5caf417664e0
|
a42cd4a09b1d5b7650826afae11d590e5f5f87bd
|
refs/heads/master
| 2020-07-03T07:25:01.635322
| 2019-08-13T07:01:50
| 2019-08-13T07:01:50
| 201,836,870
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,031
|
py
|
"""portfolio URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/2.2/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based views
1. Add an import: from other_app.views import Home
2. Add a URL to urlpatterns: path('', Home.as_view(), name='home')
Including another URLconf
1. Import the include() function: from django.urls import include, path
2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))
"""
from django.contrib import admin
from django.urls import include, path
from . import views
from django.conf.urls.static import static
from django.conf import settings
urlpatterns = [
path('admin/', admin.site.urls),
path('', views.home),
# path('blog/', blog.views.blog_page),
path('blog/', include('blog.urls')),
] + static(settings.MEDIA_URL,document_root=settings.MEDIA_ROOT)
|
[
"1448918377@qq.com"
] |
1448918377@qq.com
|
03fa372373be0909afbda2455c14a4b31e28297a
|
a46d135ba8fd7bd40f0b7d7a96c72be446025719
|
/packages/python/plotly/plotly/validators/densitymapbox/_text.py
|
d6acb8ce9d54edebc2f8c5d7d89393b3ac169a33
|
[
"MIT"
] |
permissive
|
hugovk/plotly.py
|
5e763fe96f225d964c4fcd1dea79dbefa50b4692
|
cfad7862594b35965c0e000813bd7805e8494a5b
|
refs/heads/master
| 2022-05-10T12:17:38.797994
| 2021-12-21T03:49:19
| 2021-12-21T03:49:19
| 234,146,634
| 0
| 0
|
MIT
| 2020-01-15T18:33:43
| 2020-01-15T18:33:41
| null |
UTF-8
|
Python
| false
| false
| 444
|
py
|
import _plotly_utils.basevalidators
class TextValidator(_plotly_utils.basevalidators.StringValidator):
def __init__(self, plotly_name="text", parent_name="densitymapbox", **kwargs):
super(TextValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
array_ok=kwargs.pop("array_ok", True),
edit_type=kwargs.pop("edit_type", "calc"),
**kwargs
)
|
[
"noreply@github.com"
] |
hugovk.noreply@github.com
|
4163953d53f7282f91a3283b78bcd99bd93f92e4
|
d1df2f274304101ea8ebcf083f54433b70b8756d
|
/ch1/types.py
|
e85000f0736c8d84920e877578ca920372867bdd
|
[] |
no_license
|
baykier/deep-leaning-from-scratch
|
76f737335f96b0a045320f9e52a0b46f2ac3a1f8
|
e315ee29c0a74e8f40c11f372fafb59debfce044
|
refs/heads/master
| 2020-05-19T16:29:36.872167
| 2019-05-10T08:18:41
| 2019-05-10T08:18:41
| 185,110,317
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 368
|
py
|
# coding: utf-8
# int
num = 10
print(type(num))
# float
float_num = 10.3
print(type(float_num))
# str
str_var = ' this is a str'
str_var2 = "this is anothor str"
print(type(str_var), type(str_var2))
# bool
true_var = True
print(type(true_var))
# list
list_var = [1, 23, '444']
print(type(list_var))
# list loop
for m in list_var:
print(m,type(m))
|
[
"1035666345@qq.com"
] |
1035666345@qq.com
|
4589e114dd1b638453c2633b3541962c9d1cc69b
|
b1977f6e68564dd02a41631d51653db90b174185
|
/Gupta.py
|
d6d0086ad074d1e537ee9f1584a5309379b35425
|
[] |
no_license
|
eliwchen/ISZPVRPTW
|
c9593c9219f02af5d4463c28ada93bfe044ee473
|
33335d2750239f1297a8f8672e4aafcf5f2e568a
|
refs/heads/master
| 2021-07-15T03:31:14.919998
| 2021-06-17T13:23:20
| 2021-06-17T13:23:20
| 249,741,672
| 2
| 1
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,401
|
py
|
# -*- coding:utf-8 -*-
import numpy as np
import time
from tool import makespan_value
class Gupta:
def cals(self, data):
s = np.zeros([2, data.shape[1]])
s[0] = data[0]
for j in range(data.shape[1]):
temp = []
c = 1
if data[-1, j] > data[1, j]:
c = -1
for m in range(data.shape[0] - 1):
temp.append(np.sum([data[m, j], data[m + 1, j]]))
s[1, j] = c / np.min(temp)
return s
def sort(self, data, s):
col = np.array(s[:, np.argsort(s[1])][0], dtype=int) - 1
data_gupta = data[:, col][0]
return data_gupta
def gupta(data,transfer_time, draw=0):
"""
:param data:3行，工序编号，机器1加工时间，机器2加工时间
:return:
"""
data = data[:, np.argsort(data[0])]
new = Gupta()
start_time = time.time()
s = new.cals(data)
data_gupta = new.sort(data, s)
end_time = time.time()
# print("Gupta// Time used: %s" % (end_time - start_time))
# print("Gupta// The minimum makespan: %s" % makespan_value(data[:, data_gupta - 1]))
if draw:
import matplotlib.pyplot as plt
from tool import gatt
gatt(data[:, data_gupta - 1])
plt.show()
return data_gupta,makespan_value(data[:, data_gupta - 1],transfer_time)
|
[
"noreply@github.com"
] |
eliwchen.noreply@github.com
|
1d094e0d228f9630176cdaa4cf7b1db608649010
|
60a831fb3c92a9d2a2b52ff7f5a0f665d4692a24
|
/IronPythonStubs/release/stubs.min/System/Diagnostics/__init___parts/CorrelationManager.py
|
e850a4823b372a076124dfa139e458c43873f4ed
|
[
"MIT"
] |
permissive
|
shnlmn/Rhino-Grasshopper-Scripts
|
a9411098c5d1bbc55feb782def565d535b27b709
|
0e43c3c1d09fb12cdbd86a3c4e2ba49982e0f823
|
refs/heads/master
| 2020-04-10T18:59:43.518140
| 2020-04-08T02:49:07
| 2020-04-08T02:49:07
| 161,219,695
| 11
| 2
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,080
|
py
|
class CorrelationManager(object):
""" Correlates traces that are part of a logical transaction. """
def StartLogicalOperation(self,operationId=None):
"""
StartLogicalOperation(self: CorrelationManager)
Starts a logical operation on a thread.
StartLogicalOperation(self: CorrelationManager,operationId: object)
Starts a logical operation with the specified identity on a thread.
operationId: An object identifying the operation.
"""
pass
def StopLogicalOperation(self):
"""
StopLogicalOperation(self: CorrelationManager)
Stops the current logical operation.
"""
pass
ActivityId=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Gets or sets the identity for a global activity.
Get: ActivityId(self: CorrelationManager) -> Guid
Set: ActivityId(self: CorrelationManager)=value
"""
LogicalOperationStack=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Gets the logical operation stack from the call context.
Get: LogicalOperationStack(self: CorrelationManager) -> Stack
"""
|
[
"magnetscoil@gmail.com"
] |
magnetscoil@gmail.com
|
e5a727919954194e5eb42a5a0667882dba607a25
|
d01823353eb061355068bac9964bb9747495dee5
|
/liblearn/loss/lossbase_.py
|
8129ee80387cf6c0d59810be1ab64eb45d058764
|
[] |
no_license
|
fulQuan/ift6266h15
|
57eb97e6054cb5bc1936382defdf11c5955cd19e
|
3e2780963f061484c938090419001149fff04182
|
refs/heads/master
| 2021-01-18T18:20:18.411096
| 2015-04-17T19:32:10
| 2015-04-17T19:32:10
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 119
|
py
|
# -*- coding: utf-8 -*-
"""
Created on Tue Feb 24 15:01:11 2015
@author: francis
"""
class lossbase(object):
pass
|
[
"francisquintallauzon@gmail.com"
] |
francisquintallauzon@gmail.com
|
a5ba66337b1d2cdf5e0bedf267c86604f72d7545
|
471477500808e6d7195b33852113e454bbad0e48
|
/Wiki/GoogleRedirect.py
|
23e8dadd04a265fdd532075e94639e7b435cb0c3
|
[
"MIT"
] |
permissive
|
RogerNi/2019_AAU_Web-NLP_Utils-Ex
|
0bd35b1a5febf24b62b04819b05a10cb8e194dcb
|
0b727647e09b5cded97b0625b535fa7a35fe807c
|
refs/heads/master
| 2020-06-03T00:25:19.958238
| 2019-06-11T15:04:07
| 2019-06-11T15:04:07
| 191,360,193
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,218
|
py
|
'''
@Author: NI Roger
@LastEditors: NI Roger
@LastEditTime: 2019-06-11 12:42:30
@Description: Using Google searching result to redirect Wikipedia page
'''
from requests_html import HTMLSession
session = HTMLSession()
def getWikiKeyWordFromGoogle(entry):
'''Return Wiki Keyword from Google Searching result
This function first gets the searching result from Google. Then it picks up the wiki links from the
searching result and choose the most appropriate one.
Arg:
entry: Keyword to search
Return:
One keyword for Wikipedia that is expected to the most suitable one for the input keyword
Note:
Frequent HTML requests to Google may cause temporary ban of your IP address from furthur Google
search. Also, the strategies to pick up appropriate Wikipedia keyword to choose the minimum-length
keyword from all, which is not correct in some situations.
'''
responde = session.get("https://www.google.com/search?q="+entry)
links = responde.html.links
wikiLinks = [x for x in links if "wikipedia.org" in x]
wikiKeywords = [x.split("/")[-1] for x in wikiLinks]
return min(wikiKeywords,key=len)
|
[
"noreply@github.com"
] |
RogerNi.noreply@github.com
|
a4c25541c52d27a7bce05e9b2d6e2660b94be563
|
c1cadf7816acbe2c629dfdf5bfe8f35fa14bfd57
|
/engish/readanno/Utils/Utils.py
|
3b883c76d63bb3a1a20536146fea5532e30b561e
|
[] |
no_license
|
luochengleo/timeperception
|
39c5eb0b0cedf16a02867e6a67e2befc4a118c71
|
6c27ceb51e219d9f18898918d4f3158c94836ff4
|
refs/heads/master
| 2021-01-21T04:46:45.315679
| 2016-07-21T14:34:04
| 2016-07-21T14:34:04
| 43,635,809
| 0
| 1
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,491
|
py
|
__author__ = 'luocheng'
def str2numseq(s,splitter):
return [int(item) for item in s.strip().split(splitter)]
def numseq2str(numseq,splitter):
return [splitter.join([str(item) for item in numseq])]
from django.db import transaction, models
import re
from readanno.models import *
patterns = {key: re.compile('%s=(.*?)\\t' % key) for key in ['TIME', 'USER', 'JOBID','ACTION']}
info_patterns = re.compile('INFO:\\t(.*?)$')
click_info_patterns = {key: re.compile('%s=(.*?)\\t' % key) for key in ['type', 'result', 'page', 'rank']}
click_info_patterns['src'] = re.compile('src=(.*?)$')
def fromString(line):
studentID = patterns['USER'].search(line).group(1)
jobid = patterns['JOBID'].search(line).group(1)
action = patterns['ACTION'].search(line).group(1)
logObj = Log.objects.create(studentid=studentID,
jobid=jobid,
action=action,
content=line)
return logObj
# @transaction.commit_manually
def insertMessageToDB(message):
try:
for line in message.split('\n'):
fout = open('data/all.log','a')
fout.write(line+'\n')
print line
if line == '':
continue
log = fromString(line)
log.save()
except Exception as e:
print e
print 'insert exception'
# transaction.rollback()
else:
print 'commit()'
# transaction.commit()
|
[
"luochengleo@gmail.com"
] |
luochengleo@gmail.com
|
9b46ba4719d7f278f861f5db639e3faead3a4cb5
|
de5be7e4d9e20bbfda3ce8697afc3433a3ccf55d
|
/python_tutorial/excercise_3/looping_in_list.py
|
55baa5d9ed37a214eb2ca2ffb7502363bf5236cd
|
[] |
no_license
|
poojataksande9211/python_data
|
42a88e0a0395f383d4375000a3d01b894bd38e62
|
64c952d622abfa77f2fdfd737c210014fce153c5
|
refs/heads/main
| 2023-04-16T10:24:27.213764
| 2021-04-27T16:34:32
| 2021-04-27T16:34:32
| 360,673,774
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 227
|
py
|
#looping in list
fruits=["anar","banana","apple","kiwi","orange","papaya","pinaple"]
# for i in fruits:
# print(i)
#..................................................
i=0
while i<len(fruits):
print(fruits[i])
i=i+1
|
[
"amitganvir6@gmail.com"
] |
amitganvir6@gmail.com
|
2814486884b96d9ebaf788e56bff7cd00778b883
|
0f38731054bb79200959725f8ee0ba74291c6e47
|
/profile_url_scraper.py
|
f0b8f104a545aa1066849429be52d659dac9a1c0
|
[] |
no_license
|
Project-Based-Learning-IT/linkedin-scraper
|
f34e378466fa6f29ed8d363fcf714ecd09f78cde
|
67ded49501c9c0aa58cf79b9fd7d5a46d5f0190a
|
refs/heads/main
| 2023-07-18T18:17:09.105435
| 2021-09-15T17:26:24
| 2021-09-15T17:26:24
| 405,339,543
| 1
| 1
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,056
|
py
|
from selenium import webdriver
from parsel import Selector
import csv
urlArray = []
chromedriver = '/home/sid/Downloads/chromedriver_linux64/chromedriver'
_DRIVER_CHROME = webdriver.Chrome(chromedriver)
_DRIVER_CHROME.get('https://www.linkedin.com/uas/login')
elementID = _DRIVER_CHROME.find_element_by_id('username')
elementID.send_keys('maatsisipbl@gmail.com')
elementID = _DRIVER_CHROME.find_element_by_id('password')
elementID.send_keys('project@123')
elementID.submit()
for i in range(1, 100):
_DRIVER_CHROME.get('https://www.linkedin.com/search/results/people/?origin=FACETED_SEARCH&page={}&schoolFilter=%5B%22246006%22%5D&sid=b33'.format(i))
selector = Selector(text=_DRIVER_CHROME.page_source)
urls = selector.xpath('//a[@class="app-aware-link" and @aria-hidden="false"]/@href').extract()
for i in range(0, len(urls)):
urls[i] = urls[i].split('?')[0]
urlArray.extend(urls)
print(urlArray)
with open('profile_urls.csv', 'w', encoding='UTF8', newline='') as f:
writer = csv.writer(f)
for url in urlArray:
writer.writerow([url])
|
[
"realsiddheshko@gmail.com"
] |
realsiddheshko@gmail.com
|
779eada9da3ae4912ac01d4f8d5d8b1879026927
|
9ef2a6ead84931997ae925140f010d0ec4f81f3b
|
/mysite/mysite/settings.py
|
08fb602c0eae4cb43f996fa67d460a3831a99bc7
|
[
"MIT"
] |
permissive
|
dalonlobo/Django11Polls
|
fbfed91b601c5ce33a150ae4b5f6103273c737ca
|
89e93dcec61274a46bbec10a872234512b113158
|
refs/heads/master
| 2021-01-02T09:18:59.251668
| 2017-09-05T14:58:06
| 2017-09-05T14:58:06
| 99,192,235
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 3,161
|
py
|
"""
Django settings for mysite project.
Generated by 'django-admin startproject' using Django 1.11.3.
For more information on this file, see
https://docs.djangoproject.com/en/1.11/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/1.11/ref/settings/
"""
import os
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/1.11/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = ')40k4cly018(!0ts86xrq4glhvc70a7sf5trl6e&!ch9n-*u-+'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
INSTALLED_APPS = [
'polls.apps.PollsConfig',
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'mysite.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [os.path.join(BASE_DIR, 'templates')],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'mysite.wsgi.application'
# Database
# https://docs.djangoproject.com/en/1.11/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
}
}
# Password validation
# https://docs.djangoproject.com/en/1.11/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/1.11/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/1.11/howto/static-files/
STATIC_URL = '/static/'
|
[
"dalonlobo@gmail.com"
] |
dalonlobo@gmail.com
|
c88e25a8187fa6eeb3b35e16b4b5ad0563ff166a
|
b6f4e527154b82f4e3fa48f06ca53fc15bf08283
|
/Day06/function6.py
|
9ad8987713d947369211aa8882890d4323c7d7f1
|
[] |
no_license
|
Light-City/Python-100-Days
|
74118e36c658db6c897f847e7e554311af036b9d
|
1fe049a1fe1e64082752d2d32cb75c1a4349cded
|
refs/heads/master
| 2020-03-18T12:44:53.191512
| 2018-05-24T09:49:22
| 2018-05-24T09:49:22
| 134,741,794
| 3
| 1
| null | 2018-05-24T16:29:02
| 2018-05-24T16:29:02
| null |
UTF-8
|
Python
| false
| false
| 346
|
py
|
"""
作用域问题
Version: 0.1
Author: 骆昊
Date: 2018-03-05
"""
# 局部作用域
def foo1():
a = 5
foo1()
# print(a) # NameError
# 全局作用域
b = 10
def foo2():
print(b)
foo2()
def foo3():
b = 100 # 局部变量
print(b)
foo3()
print(b)
def foo4():
global b
b = 200 # 全局变量
print(b)
foo4()
print(b)
|
[
"jackfrued@126.com"
] |
jackfrued@126.com
|
f2219cf699a60372c8109d14de0b1a2190cfe346
|
b7b8a8e1d41159a636a0e243056941bdf57856b5
|
/fianl exam/main.py
|
82352cb2a0b905f0b9013c1b6c8ac399cf277ef8
|
[] |
no_license
|
fjucs/107-VideoProcessing
|
0afc97a958e12f38637d0f2cc7cc9a4f9586ca65
|
364904da89009ea0107e64a1611f67cfe4eddaa3
|
refs/heads/master
| 2020-09-06T00:01:55.233541
| 2019-11-07T14:13:46
| 2019-11-07T14:13:46
| 220,251,680
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,149
|
py
|
import cv2
import numpy as np
import pygame
from color_manip import *
from bar import *
from utils import *
cap = cv2.VideoCapture(0)
pygame.init()
pygame.display.set_caption(u"clown")
screen = pygame.display.set_mode((800, 600))
clock = pygame.time.Clock()
class Clown:
def __init__(self, x, y, img):
self.x = x
self.y = y
self.img = img
self.wear = False
def update(self, now, faces):
if not now:
return
nx, ny = now
x = self.x
y = self.y
if x <= nx and nx <= x+200 and y <= ny and ny <= y+200:
self.wear = True
if self.wear:
for fx, fy, fw, fh in faces:
self.x = fx + 65
self.y = fy - 100
def draw(self):
screen.blit(self.img, (self.x, self.y))
# t = TrackBar('1', 'b')
a = Clown(10, 10, pygame.transform.scale(pygame.image.load("1.png"), (200, 200)))
b = Clown(300, 10, pygame.transform.scale(pygame.image.load("2.png"), (200, 200)))
c = Clown(590, 10, pygame.transform.scale(pygame.image.load("3.png"), (200, 200)))
hat = [a, b, c]
GAME_PLAY = 1
GAME_WIN = 2
gm = GAME_PLAY
running = True
while running:
for event in pygame.event.get():
# 離開遊戲.
if event.type == pygame.QUIT:
running = False
# update
## opencv
ret, frame = cap.read()
frame = flip(frame, 1)
## color detect
_, mask, _ = color_detect(frame, (0, 0, 255), 50)
cent = get_color_pos(mask)
cv2.imshow('1', mask)
# cv2.imshow('2', inv)
## face detect
faces = face_detect(frame)
## game logic
for i in hat:
i.update(cent, faces)
# win
wear_cnt = 0
for i in hat:
if i.wear:
wear_cnt += 1
if wear_cnt == 3:
gm = GAME_WIN
# draw
back = cvimage_to_pygame(frame)
back = pg_resize(back, 800, 600)
screen.blit(back, (0,0))
for i in hat:
i.draw()
if gm == GAME_WIN:
showFont(screen, "You Win", 300, 250, 'simhei', 50, (255, 0, 0))
pygame.display.update()
clock.tick(60)
cap.release()
cv2.destroyAllWindows()
|
[
"a82611141@gmail.com"
] |
a82611141@gmail.com
|
820ba9667ca39c6dfe6a225fce1cd4ebbbf82bbb
|
41935d3be8b0f8722133d5b21470feddcb9793b5
|
/PythonWS-S14/begin.py
|
17b0de8b09ddcc3e357ba4437a53f6d1187fcde5
|
[] |
no_license
|
ga98442w/mypydevrepoongit
|
118c797f8193ca51e14a3f258ea70568f6480ef4
|
cf238295750ed27ff4f46f0c27e18951d48b6987
|
refs/heads/master
| 2021-01-04T22:32:35.366768
| 2015-02-06T21:10:55
| 2015-02-06T21:10:55
| 30,433,462
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 247
|
py
|
__author__ = 'GilbertAlipui'
# Prompt the user to enter a radius
radius = eval(input("Enter a value for radius: "))
#Compute area
area = radius * radius * 3.14159
#Display results
print("The area for the circle of radius ", radius, "is ", area)
|
[
"98ab50f1@opayq.com"
] |
98ab50f1@opayq.com
|
6b1f08084a9b1cbda2335c4a9356745284920465
|
7442a9088d41bbb900e767b7eb6d85ac6a300df0
|
/Controlador/app.py
|
550cdfd9e1a81f2e369ff26bb61138c0e6a5dde2
|
[] |
no_license
|
AdrianGOT/InstantSecurity
|
aa3bc544b2b9680469cef188bec556e47dc37e26
|
00e4ddc56e66fe6d2cef525ecd2639cb81f4a87a
|
refs/heads/main
| 2023-01-22T10:03:51.731279
| 2020-12-02T15:49:42
| 2020-12-02T15:49:42
| 317,891,786
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 6,488
|
py
|
from flask import Flask, render_template, redirect
from flask import jsonify, request, url_for
from flask import session
import requests
import random
import json
app = Flask(__name__)
url_cliente = 'http://127.0.0.1:5001/clientes/'
url_producto = 'http://127.0.0.1:5002/producto/'
url_factura = 'http://127.0.0.1:5003/factura/'
app.secret_key="lalocura123456789"
# Función que buscar un solo producto
def buscar_un_producto(name):
response = requests.get(url_producto + name)
return json.loads(response.text)
# Función que buscar un solo cliente
def buscar_un_cliente(id):
response = requests.get(url_cliente + str(id))
return json.loads(response.text)
# Función que busca todos los productos
def buscar_productos():
response = requests.get(url_producto)
return json.loads(response.text)
# Función que busca todas las facturas
def buscar_facturas():
response = requests.get(url_factura)
return json.loads(response.text)
# Función que agrega datos del cliente a la session
def registroSesion(todo):
session['nombre'] = todo['nombre']
session['cc'] = todo['CC']
print(session['cc'])
@app.route('/')
def index():
return redirect(url_for('all_products'))
# Guardar cliente
@app.route('/guardar', methods = ['POST'])
def save_client():
data = {
'nombre' : request.form['nombre'],
'apellido' : request.form['apellido'],
'CC': request.form['CC'],
'celular':request.form['celular'],
'email' : request.form['email'],
'direccion':request.form['direccion']
}
registroSesion(data)
requests.post(url_cliente, json = data)
return redirect(url_for('index'))
# Actualizar la información del cliente
@app.route('/actualizar', methods = ['POST'])
def update():
data = {
'name' : request.form['nombre'],
'apellido' : request.form['apellido'],
'Celular':request.form['celular'],
'email' : request.form['email']
}
requests.put(url_cliente + request.form['CC'], json = data)
return redirect(url_for('index'))
# Obtiene todos los prodcutos
@app.route('/obtener_productos/', methods=['GET', 'POST'])
def all_products():
todo = buscar_productos()
comprobante = False
n = 'Desconocido'
cc = 'Desconocido'
if "nombre" in session:
comprobante = True
n = session['nombre']
cc = session['cc']
return render_template('index.html', productos = todo['result'], title='InstantSecurity', c = comprobante, n = n)
return render_template('index.html', productos = todo['result'], title='InstantSecurity', c = comprobante, n = n)
# Registro e Inicio de sesión
@app.route('/Inicio_de_sesión', methods=['GET','POST'])
def inicioSesion():
if request.method == 'POST':
todo = buscar_un_cliente(request.form['CC'])
registroSesion(todo['result'])
return redirect(url_for('all_products'))
return render_template('inicioSesion.html', title='Iniciar sesión')
@app.route('/Registrarse', methods=['GET','POST'])
def registro():
return render_template('registrarse.html', title='Registro')
# Creación de la factura
@app.route('/factura/<productName>', methods=['GET','POST'])
def facturacion(productName):
if "nombre" in session:
comprobante = True
producto = buscar_un_producto(productName)
cliente = buscar_un_cliente(str(session['cc']))
factura = {
'Nombre': cliente['result']['nombre'],
'Identificacion': cliente['result']['CC'],
'Direccion del cliente': cliente['result']['direccion'],
'Nombre del producto o servicio': producto['result']['name'],
'Precio': producto['result']['price'],
'Número de telefono': cliente['result']['celular']
}
if request.method == 'POST':
n = random.randint(0,100000000)
data_check={
'numero_factura':n,
'direccion': factura['Direccion del cliente'],
'precio': factura['Precio'],
'nombre_producto':factura['Nombre del producto o servicio'],
'nombre_cliente':factura['Nombre'],
'CC_cliente':factura['Identificacion']
}
requests.post(url_factura, json=data_check)
return render_template('resultado.html', num = n)
return render_template('factura.html', Factura = factura,
n=session['nombre'], title = 'Factura')
# Perfil del usuario
@app.route('/obtener_productos/perfil', methods=['GET','POST'])
def perfil():
if "cc" in session:
info = buscar_un_cliente(str(session['cc']))
f = buscar_facturas()
return render_template('perfil.html', title=session['nombre'], n=session['nombre'], info = info['result'], facturas = f['result'])
else:
return redirect(url_for('index'))
# Elimiar factura
@app.route('/Elimar_factura/<numero>', methods = ['GET','POST'])
def eliminar_factura(numero):
requests.delete(url_factura + numero)
return redirect(url_for('perfil'))
# Editar Cuenta
@app.route('/Editar_cuenta/<cc>', methods=['GET', 'POST'])
def editar_cuenta(cc):
if request.method == 'POST':
new_data={
'name':request.form['nombre'],
'apellido':request.form['apellido'],
'Celular':request.form['celular'],
'email':request.form['email'],
'direccion':request.form['direccion']
}
requests.put(url_cliente + str(cc), json=new_data)
return redirect(url_for('perfil'))
todo = buscar_un_cliente(session['cc'])
return render_template('editarPerfil.html', title="Editar Perfil", info=todo['result'])
# Eliminar Cuenta
@app.route('/eliminar_cuenta/<int:cc>', methods=['GET', 'POST'])
def eliminar_cuenta(cc):
if 'nombre' in session:
requests.delete(url_cliente + str(cc))
return redirect(url_for('logout'))
return redirect(url_for('index'))
# Cerrar sesión
@app.route('/Cerrar Session')
def logout():
session.pop('nombre',None)
session.pop('cc',None)
return redirect(url_for('all_products'))
|
[
"noreply@github.com"
] |
AdrianGOT.noreply@github.com
|
3dd66015f4809417e4adb64f640b1c8d56acb3e0
|
b5522ba428e1faa2e6661ac2a7051e76673e71b2
|
/P0/Task3.py
|
c11e00a8198d703d7c4401532277e195767b5bcc
|
[] |
no_license
|
jeyansaran620/DSA_Udacity
|
6fdf535425e32dd5792ba7c1d90be899acebde23
|
cd59411b5de62c5764a7d82d2673524e30d783c9
|
refs/heads/master
| 2022-07-13T22:26:44.579387
| 2020-05-13T15:19:31
| 2020-05-13T15:19:31
| 263,665,703
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,568
|
py
|
"""
Read file into texts and calls.
It's ok if you don't understand how to read files.
"""
import csv
codes=set()
total_calls=0
bang_calls=0
with open('calls.csv', 'r') as f:
reader = csv.reader(f)
calls = list(reader)
for call in calls:
call1=call[0].split(")")
if call1[0][0]=='(':
if call1[0].split("(")[1] =="080":
total_calls+=1
call2=call[1].split(")")
if call2[0][0]=='(':
codes.add(call2[0].split("(")[1])
if call2[0].split("(")[1]=="080":
bang_calls+=1
call22=call[1].split(" ")
if call22[0][0]=='7' or call22[0][0]=='8' or call22[0][0]=='9':
codes.add(call22[0][:4])
if call22[0][:3]=="140":
if "140" not in codes:
codes.add('140')
print("The numbers called by people in Bangalore have codes:")
for key in sorted(codes):
print(key)
print(str("%.2f" %(bang_calls*100/total_calls))+" percent of calls from fixed lines in Bangalore are calls to other fixed lines in Bangalore.")
"""
TASK 3:
(080) is the area code for fixed line telephones in Bangalore.
Fixed line numbers include parentheses, so Bangalore numbers
have the form (080)xxxxxxx.)
Part A: Find all of the area codes and mobile prefixes called by people
in Bangalore.
- Fixed lines start with an area code enclosed in brackets. The area
codes vary in length but always begin with 0.
- Mobile numbers have no parentheses, but have a space in the middle
of the number to help readability. The prefix of a mobile number
is its first four digits, and they always start with 7, 8 or 9.
- Telemarketers' numbers have no parentheses or space, but they start
with the area code 140.
Print the answer as part of a message:
"The numbers called by people in Bangalore have codes:"
<list of codes>
The list of codes should be print out one per line in lexicographic order with no duplicates.
Part B: What percentage of calls from fixed lines in Bangalore are made
to fixed lines also in Bangalore? In other words, of all the calls made
from a number starting with "(080)", what percentage of these calls
were made to a number also starting with "(080)"?
Print the answer as a part of a message::
"<percentage> percent of calls from fixed lines in Bangalore are calls
to other fixed lines in Bangalore."
The percentage should have 2 decimal digits
"""
|
[
"noreply@github.com"
] |
jeyansaran620.noreply@github.com
|
087879df2af5993db7367abe2d8b8e60ad037c0b
|
bb7d0ec68afabd53f81b9e6f8823bc65566778d9
|
/stdplugins/squ.py
|
5549e5c1211cd2ce35d92f22a86d5a72ef36a7da
|
[
"Apache-2.0"
] |
permissive
|
IshwaranRudhara/PepeBot
|
b992cd7233ff5ef42c9ef124c1fa8c0c42147369
|
5c0bd4c19e076bee73cf62a4dc804681045754d3
|
refs/heads/master
| 2021-05-20T08:37:05.954697
| 2020-06-19T10:23:30
| 2020-06-19T10:23:30
| 252,200,694
| 2
| 3
|
Apache-2.0
| 2020-04-30T08:36:54
| 2020-04-01T14:36:26
|
Python
|
UTF-8
|
Python
| false
| false
| 3,367
|
py
|
# BY @STARKTM1
from telethon import events
import asyncio
@borg.on(events.NewMessage(pattern=r"\.squ", outgoing=True))
async def _(event):
if event.fwd_from:
return
await event.edit("╔═══════════════════╗ \n \n╚═══════════════════╝")
await asyncio.sleep(1)
await event.edit("╔═══════════════════╗ \n \t░ \n╚═══════════════════╝")
await asyncio.sleep(1)
await event.edit("╔═══════════════════╗ \n ░ \t░ \n╚═══════════════════╝")
await asyncio.sleep(1)
await event.edit("╔═══════════════════╗ \n ░ ░ ░ \n╚═══════════════════╝")
await asyncio.sleep(1)
await event.edit("╔═══════════════════╗ \n ░ ░ ░ ░ \n╚═══════════════════╝")
await asyncio.sleep(1)
await event.edit("╔═══════════════════╗ \n ░ ░ ░ ░ ░ \n╚═══════════════════╝")
await asyncio.sleep(1)
await event.edit("╔═══════════════════╗ \n ░ ░ ░ ░ ░ ░ \n╚═══════════════════╝")
await asyncio.sleep(1)
await event.edit("╔═══════════════════╗ \n ░ ░ ░ ░ ░ ░ ░ \n╚═══════════════════╝")
await asyncio.sleep(1)
await event.edit("╔═══════════════════╗ \n ░ ░ ░ ░ ░ ░ ░ ░ \n╚═══════════════════╝")
await asyncio.sleep(1)
await event.edit("╔═══════════════════╗ \n ░ ░ ░ ░ ░ ░ ░ ░ ░ \n╚═══════════════════╝")
await asyncio.sleep(1)
await event.edit("╔═══════════════════╗ \n ░ ░ ░ ░ ░ ░ ░ ░ ░ ░ \n╚═══════════════════╝")
await asyncio.sleep(1)
await event.edit("╔═══════════════════╗ \n ░ ░ ░ ░ ░ ░ ░ ░ ░ ░ ░ \n╚═══════════════════╝")
await asyncio.sleep(1)
await event.edit("╔═══════════════════╗ \n ░ ░ ░ ░ ░ ░ ░ ░ ░ ░ ░ ░ \n╚═══════════════════╝")
await asyncio.sleep(1)
await event.edit("╔═══════════════════╗ \n ░ ░ ░ ░ ░ ░ ░ ░ ░ ░ ░ ░ ░ \n╚═══════════════════╝")
await asyncio.sleep(1)
await event.edit("╔═══════════════════╗ \n ░ ░ ░ ░ ░ ░ ░ ░ ░ ░ ░ ░ ░ ░ \n╚═══════════════════╝")
await asyncio.sleep(6)
|
[
"55076817+prono69@users.noreply.github.com"
] |
55076817+prono69@users.noreply.github.com
|
9e18921acde56458b273c44ee0e1f1783c047e29
|
04eb04b945713d067d5f1bf5643e0e25ffbe876a
|
/target/dist/cs3280_project5-1.0.dev0/setup.py
|
984726c899b521091737fb4a8a6c500f9de1fce9
|
[] |
no_license
|
twhaley1/cs3280_project5
|
a9748415d40d81b8def01048569c16bf23bc4022
|
b521cd0312ce24e6e3aaa67c2e1031a5a9c22c49
|
refs/heads/master
| 2020-09-15T13:20:04.863652
| 2019-11-23T00:10:36
| 2019-11-23T00:10:36
| 223,457,062
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,415
|
py
|
#!/usr/bin/env python
from setuptools import setup
from setuptools.command.install import install as _install
class install(_install):
def pre_install_script(self):
pass
def post_install_script(self):
pass
def run(self):
self.pre_install_script()
_install.run(self)
self.post_install_script()
if __name__ == '__main__':
setup(
name = 'cs3280_project5',
version = '1.0',
description = 'Project for CS3280 : Scans ports',
long_description = ' Takes an ip address and a port or a pair\n of ports and determines whether there the \n port is listening or not. ',
author = 'Thomas Whaley',
author_email = 'twhaley1@my.westga.edu',
license = '',
url = '',
scripts = [],
packages = [],
namespace_packages = [],
py_modules = [
'portscan',
'simpleservers'
],
classifiers = [
'Development Status :: 3 - Alpha',
'Programming Language :: Python'
],
entry_points = {},
data_files = [],
package_data = {},
install_requires = [],
dependency_links = [],
zip_safe = True,
cmdclass = {'install': install},
keywords = '',
python_requires = '',
obsoletes = [],
)
|
[
"twhaley1@my.westga.edu"
] |
twhaley1@my.westga.edu
|
946b2f7c4dda23e138459b3f7d75952d0601e0a9
|
085a41aa8cf80c3c64783b15459fb37f5d067aac
|
/cups.py
|
a59a14d4509cbdb9c57a99fcfa22ab01c47c892d
|
[] |
no_license
|
CamilleSalvinien/OpenKattis
|
25155e352d689387fe63f2352181805e0d07309b
|
d8c4b0898022d664039fc8135141ffc40c5fe95b
|
refs/heads/main
| 2023-04-30T16:00:33.571115
| 2021-05-09T18:20:33
| 2021-05-09T18:20:33
| 327,402,396
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 304
|
py
|
n = int(input())
cups = {}
for i in range (n):
a, b = input().split()
if a.isnumeric():
number = int(int(a)/2)
color = b
else:
number = int(b)
color = a
cups[color]=number
for w in sorted(cups, key=cups.get, reverse=False):
print(w)
|
[
"noreply@github.com"
] |
CamilleSalvinien.noreply@github.com
|
25f57380ce9bc585649b6037352bcbc1e84ee69a
|
65f78f7d50b2cbce8be821db26cd3b49e7861f08
|
/backend/location/vector.py
|
f11fff67a074483f9c7e7adef13070eb1997d58a
|
[] |
no_license
|
adamallaf/FriendLocation
|
c3f194de632d4695d5981e6cee3893856af47a09
|
4095e66fe62af13bba588f04d79627cd10f9efc0
|
refs/heads/master
| 2021-03-12T19:09:39.110438
| 2017-08-11T11:33:43
| 2017-08-11T11:33:43
| 91,455,444
| 1
| 0
| null | 2017-05-16T12:24:15
| 2017-05-16T12:24:15
| null |
UTF-8
|
Python
| false
| false
| 1,326
|
py
|
class Vector:
# a vector consists of two points
def __init__(self, point1, point2):
self.p1 = point1
self.p2 = point2
# checks if two numbers have different signs
@staticmethod
def _diff_sign(a,b):
return ((a > 0) and (b < 0) or ((a <0) and (b >0)))
# equation in general form a*x + b*y +c = 0 of an infinite line that goes
# through vector self
# evaluates the generated equation with the longitude and latitude of point
# returns a number
def _to_eq(self, point):
# Delta Y
a = self.p2.latitude - self.p1.latitude
# - Delta X
b = self.p1.longitude - self.p2.longitude
c = self.p2.longitude * self.p1.latitude - self.p1.longitude * self.p2.latitude
return a * point.longitude + b * point.latitude + c
# checks if self intersects with vector self
def intersects(self, vec):
# if the d1 and d2 have different signs, they are on different sides of the
# vector self
d1 = self._to_eq(vec.p1)
d2 = self._to_eq(vec.p2)
# we must check again, but otherwise
d3 = vec._to_eq(self.p1)
d4 = vec._to_eq(self.p2)
# will return true if the vectors do intersect, false if they don't
return (self._diff_sign(d1,d2) and self._diff_sign(d3,d4))
|
[
"adam.allaf@gigaset.com"
] |
adam.allaf@gigaset.com
|
5fbae611d9c4fdb92550ad1b70f2539ba8a9cfda
|
9fbe2b3a0c992f4348c480b0c06a131cb42847f3
|
/深度学习与TensorFlow入门实战-源码和PPT/lesson13-前向传播（张量）-实战/forward.py
|
3e0b0d6a62c22bff758b2b6690162c11903ba91e
|
[] |
no_license
|
SunYanCN/TensorFlow
|
60efc11c69a40986a56c5847ea9e1572f947157a
|
5b8800d6ff1aca4a0f05c251a0f81bb2b8755b57
|
refs/heads/master
| 2020-06-02T00:11:45.159401
| 2019-06-05T15:51:41
| 2019-06-05T15:51:41
| 190,974,442
| 2
| 2
| null | 2019-06-09T06:58:09
| 2019-06-09T06:58:09
| null |
UTF-8
|
Python
| false
| false
| 2,457
|
py
|
import os
import tensorflow as tf
from tensorflow.python.keras import datasets
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
# x: [60k, 28, 28],
# y: [60k]
(x, y), _ = datasets.mnist.load_data()
# x: [0~255] => [0~1.]
x = tf.convert_to_tensor(x, dtype=tf.float32) / 255.
y = tf.convert_to_tensor(y, dtype=tf.int32)
print(x.shape, y.shape, x.dtype, y.dtype)
print(tf.reduce_min(x), tf.reduce_max(x))
print(tf.reduce_min(y), tf.reduce_max(y))
train_db = tf.data.Dataset.from_tensor_slices((x, y)).batch(128)
train_iter = iter(train_db)
sample = next(train_iter)
print('batch:', sample[0].shape, sample[1].shape)
# [b, 784] => [b, 256] => [b, 128] => [b, 10]
# [dim_in, dim_out], [dim_out]
w1 = tf.Variable(tf.random.truncated_normal([784, 256], stddev=0.1))
b1 = tf.Variable(tf.zeros([256]))
w2 = tf.Variable(tf.random.truncated_normal([256, 128], stddev=0.1))
b2 = tf.Variable(tf.zeros([128]))
w3 = tf.Variable(tf.random.truncated_normal([128, 10], stddev=0.1))
b3 = tf.Variable(tf.zeros([10]))
lr = 1e-3
for epoch in range(10): # iterate db for 10
for step, (x, y) in enumerate(train_db): # for every batch
# x:[128, 28, 28]
# y: [128]
# [b, 28, 28] => [b, 28*28]
x = tf.reshape(x, [-1, 28 * 28])
with tf.GradientTape() as tape: # tf.Variable
# x: [b, 28*28]
# [b, 784]@[784, 256] + [256] => [b, 256] + [256] => [b, 256] + [b, 256]
# h1 = x @ w1 + tf.broadcast_to(b1, [x.shape[0], 256])
h1 = x @ w1 + b1
h1 = tf.nn.relu(h1)
# [b, 256] => [b, 128]
h2 = h1 @ w2 + b2
h2 = tf.nn.relu(h2)
# [b, 128] => [b, 10]
out = h2 @ w3 + b3
# compute loss
# out: [b, 10]
# y: [b] => [b, 10]
y_onehot = tf.one_hot(y, depth=10)
# mse = mean(sum(y-out)^2)
# [b, 10]
loss = tf.square(y_onehot - out)
# mean: scalar
loss = tf.reduce_mean(loss)
# compute gradients
grads = tape.gradient(loss, [w1, b1, w2, b2, w3, b3])
# print(grads)
# w1 = w1 - lr * w1_grad
w1.assign_sub(lr * grads[0])
b1.assign_sub(lr * grads[1])
w2.assign_sub(lr * grads[2])
b2.assign_sub(lr * grads[3])
w3.assign_sub(lr * grads[4])
b3.assign_sub(lr * grads[5])
if step % 100 == 0:
print(epoch, step, 'loss:', float(loss))
|
[
"li1191863273@hotmail.com"
] |
li1191863273@hotmail.com
|
fdcbb54e8a2910def38de933332d9505ff1eb7d0
|
8e47f970e089e33f75e4cbaad087c68daf1bf955
|
/example2/9.ciclos.py
|
7434f59aa9d347b63daef4336b5396b1906472d5
|
[] |
no_license
|
jjmirandaa86/learn_Python
|
a53800278954246b5490a2c9980ef3ce33b5009d
|
5ab6557373c3b367c5abdc80eb2b6ad62bb1bdd8
|
refs/heads/master
| 2023-04-07T20:32:00.139129
| 2021-04-03T12:23:27
| 2021-04-03T12:23:27
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 249
|
py
|
#While
variable = 0
while variable < 10:
variable += 1
print(variable)
if variable == 5:
print("llego al 5")
continue
if variable == 8:
print("llego al 8 y terminara")
break
else:
print("termino")
|
[
"jefferson_miranda@hotmail.es"
] |
jefferson_miranda@hotmail.es
|
baaba701cc5aefbc2ff2786e1a8ca4520c39bbca
|
d83339f639c678f2ccc601d4b6a4b738cf7c55bc
|
/regex/regular_expression.py
|
aa4e79b41932c16e81fd2a8fe7e25179e6e8c1d3
|
[] |
no_license
|
evgeniikotliarov/python_example
|
fd734ec3252cef4ae51a43f73d5432336c35391a
|
65cd59eebfc78ee4cd5a3eb64c99137502a582d0
|
refs/heads/master
| 2021-01-19T14:40:45.601630
| 2017-06-20T06:23:38
| 2017-06-20T06:23:38
| 88,182,904
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,165
|
py
|
import re
#
# input_filename = "../regex/text.txt"
# result_file = "../regex/results.txt"
#
# inputfile = open(input_filename, mode='r', encoding='UTF8')
# resultfile = open(result_file, mode='w', encoding='UTF8')
# mytext = inputfile.read()
# inputfile.close()
lookfor = {'\d':"[0-5]"}
for k, v in lookfor.items():
print(re.sub(k, lambda x: lookfor[x.replace(v)], v))
# results = re.findall(lookfor, mytext)
# for item in results:
#
# resultfile.write(item)
# print(item)
# resultfile.close()
# print("Total: " + str(len(results)))
PASSWORD_REGEX_STR = "^(?=.*[A-Za-z])(?=.*\\d)(?=.*[$@#$!%*?&=])[A-z\\d$@#$!%*?&=]{8,}$"
PIN_REGEX_STR = "\d{4}"
CODE_REGEX_STR = "\d+"
PROFILE_ID_REGEX = "\d{9}"
EXP_DATE_REGEX = "\d{4}"
CVV_REGEX = "\d{3}"
AMOUNT_REGEX = "\d{3}"
PHONE_REGEX_STR = "^\+996(55|77|70)[0-9]\\d{6}$"
EMAIL_REGEX_STR = '[^@]+@[^@]+\.[^@]+'
REGEX = ".*"
FIO_REGEX_STR = ".*"
def get_regex_date_format():
return r'\w{3},\s\d{2}\s\w{3}\s\d{4}\s\d{2}:\d{2}:\d{2}\s[A-Z]{3}'
def get_request_regex():
methods = r'\w+'
host_symbols = r"[\w\.\-\d/:'0-9]"
space = r'\s'
query = r'(?:[?&][^\s&]+)*'
protocol = r'HTTP/.*'
request_regex = "(({methods}){space}+({host_symbols}+)({query}){space}+({protocol}))".format(
methods=methods,
space=space,
host_symbols=host_symbols,
query=query,
protocol=protocol
)
return request_regex.encode()
def get_boundary_regex():
return b'boundary=(.+)'
def get_content_disposition_regex():
r = br'Content-Disposition:\s?(.*)\r\n'
return r
def get_content_type_regex():
r = br'Content-Type:\s?(.*)\r\n'
return r
def get_multipart_body_regex():
r = br'Content-Disposition:\s?.*(?:[\r\n]{0,1}Content-Type:\s?.*[\r\n]{0,1})?.*[\r\n]*([\s\S]*)'
return r
def get_disposition_name_regex():
r = br'name="(.*?)"'
return r
def get_session_regex():
r = br'session=(.*)\s?'
return r
def get_template_tokenizer_regex():
CONTROL = "{%.*?%}"
EXPRESSIONS = "{{.*?}}"
r = "(?s)({control}|{expressions})".format(control=CONTROL, expressions=EXPRESSIONS)
return r
|
[
"kotlyarov.ev@gmail.com"
] |
kotlyarov.ev@gmail.com
|
e8d8ce3147bbcc2b2b76f268cde4eeba8e7dce9e
|
a6d9feb6c532471ec6968b19c6147c7c7143cdca
|
/Sentiment Analysis/NLTK_Intro.py
|
d1d58c9cc82175e4971fa221639f037ca24d7204
|
[] |
no_license
|
brandontip/algoTradeUdemy
|
983bd976b5c8687c54469fc929ecf8da3c61f7f0
|
7dfc8283a0b64ca0cf469b9ecce685b8282d2179
|
refs/heads/master
| 2022-12-22T19:28:29.799099
| 2020-09-28T05:54:51
| 2020-09-28T05:54:51
| 277,447,531
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,280
|
py
|
# -*- coding: utf-8 -*-
"""
Created on Fri Jul 17 16:41:34 2020
@author: Bran
"""
import nltk
# run this to download necessary files
#nltk.download()
#nltk.download('punkt')
from nltk.tokenize import word_tokenize
#from nltk.stem import WordNetLemmatizer
from nltk.stem import PorterStemmer
text = "If you set your goals ridiculously high and it's a failure, you will fail above everyone else's success."
# Tokenization
# this parses the string into units (usually words)
tokens = word_tokenize(text)
print(tokens)
# Lemmatization
# attempts to convert words into root word
# effectiveness can be reduced when using
# lemmatization or stemming
# we're not going to download wordnet for this
#lemmatizer = WordNetLemmatizer()
#tokens=[lemmatizer.lemmatize(word) for word in tokens]
# Stemming
# attempts to convert words into root word
#tokens=word_tokenize(text.lower())
ps = PorterStemmer()
tokens=[ps.stem(word) for word in tokens]
print(tokens)
# Stop words
stopwords = nltk.corpus.stopwords.words('english')
print(stopwords)
tokens_new = [j for j in tokens if j not in stopwords]
# this is the result of only tokenizing and removing sopt words
#['If', 'set', 'goals', 'ridiculously', 'high', "'s", 'failure', ',', 'fail', 'everyone', 'else', "'s", 'success', '.']
|
[
"54258128+brandontip@users.noreply.github.com"
] |
54258128+brandontip@users.noreply.github.com
|
d8f070143e2464ad9f56813856e939e75527d0b5
|
6fca61fe5c317cefdd95aa5fa507177d4a9c1160
|
/dictionarynumbers.py
|
740c3a9b2f8139152b8008159b01a38c271c88c3
|
[] |
no_license
|
Shadyaobuya/100daysofCodepython
|
4ed5df1cf3fbfbc6b754665d5028f6719c548278
|
8f4beaad5a541feced11b905f05e8f354a6a5579
|
refs/heads/master
| 2023-04-15T08:13:42.425950
| 2021-04-27T05:02:04
| 2021-04-27T05:02:04
| 350,864,077
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 327
|
py
|
numbers=input("Enter any number from 0-10 to see how it's read in Swahili: ")
conversion={
"1":"Moja",
"2":"Mbili",
"3":"Tatu",
"4":"Nne",
"5":"Tano",
"6":"Sita",
"7":"Saba",
"8":"Name",
"9":"Tisa",
"10":"Kumi",
"0":"Sufuri"
}
for number in numbers:
print(conversion.get(number))
|
[
"shadyaobuyagard@gmail.com"
] |
shadyaobuyagard@gmail.com
|
1024d2e59aa23e5ba8c257b5bebb70e45f4ca0b6
|
16609d71ee627729af9d14ca73e606fcaed7d165
|
/invenio_previewer/api.py
|
5fa0b6e1640307175a1935491c382843cd1faf72
|
[
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] |
permissive
|
inveniosoftware/invenio-previewer
|
39214993c82c176b44b9ef712c5dfe9bfdb9e8b8
|
d8582637e34cccd44054be1f28aaeb236d7d9c80
|
refs/heads/master
| 2023-08-24T19:32:43.096635
| 2023-08-17T14:53:19
| 2023-08-17T15:33:54
| 40,646,712
| 5
| 60
|
MIT
| 2023-09-13T15:32:40
| 2015-08-13T08:09:01
|
JavaScript
|
UTF-8
|
Python
| false
| false
| 1,754
|
py
|
# -*- coding: utf-8 -*-
#
# This file is part of Invenio.
# Copyright (C) 2016-2019 CERN.
#
# Invenio is free software; you can redistribute it and/or modify it
# under the terms of the MIT License; see LICENSE file for more details.
"""File reader utility."""
from __future__ import absolute_import, print_function
from os.path import basename, splitext
from flask import url_for
class PreviewFile(object):
"""Preview file default implementation."""
def __init__(self, pid, record, fileobj):
"""Initialize object.
:param file: ObjectVersion instance from Invenio-Files-REST.
"""
self.file = fileobj
self.pid = pid
self.record = record
@property
def size(self):
"""Get file size."""
return self.file['size']
@property
def filename(self):
"""Get filename."""
return basename(self.file.key)
@property
def bucket(self):
"""Get bucket."""
return self.file.bucket_id
@property
def uri(self):
"""Get file download link.
.. note::
The URI generation assumes that you can download the file using the
view ``invenio_records_ui.<pid_type>_files``.
"""
return url_for(
'.{0}_files'.format(self.pid.pid_type),
pid_value=self.pid.pid_value,
filename=self.file.key)
def is_local(self):
"""Check if file is local."""
return True
def has_extensions(self, *exts):
"""Check if file has one of the extensions."""
file_ext = splitext(self.filename)[1].lower()
return file_ext in exts
def open(self):
"""Open the file."""
return self.file.file.storage().open()
|
[
"lars.holm.nielsen@cern.ch"
] |
lars.holm.nielsen@cern.ch
|
37f06f5f1ab8d42558fc8283d5595e8c109a3a78
|
62a4afb5ccc6c391ebe36032a83ec6fb8b3b48ac
|
/greatest num.py
|
1fd8ee7b39c5c9e2f3c2713daee0445a07493672
|
[] |
no_license
|
Pavila98/python
|
d42ef282a7b37aee1a592969ade12b8c4bdcc93d
|
06c8fe373cf4269849e5f93d76cdcf5fdd54c5fc
|
refs/heads/master
| 2020-03-10T00:42:15.302513
| 2018-05-01T04:39:41
| 2018-05-01T04:39:41
| 129,088,468
| 0
| 1
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 241
|
py
|
num1=input("enter a number")
num2=input("enter a number")
num3=input("enter a number")
if (num1>num2 and num1>num3):
print("num1 is greater")
elif(num2>num1 and num2>num3):
print("num2 is greater")
else:
print("num3 is greater")
|
[
"noreply@github.com"
] |
Pavila98.noreply@github.com
|
2c3c6083c292e6a8e74d423af6ccf461c5805058
|
1cd9fb9466b0225575575091545cd9188fec539c
|
/tensorflow_probability/python/distributions/probit_bernoulli_test.py
|
fc7cbe257d528bbae156d92d904c2f9c046a71e1
|
[
"Apache-2.0"
] |
permissive
|
ibozkurt79/probability
|
16f4fa9b773486a5f21617be3a4163079ac3aa61
|
2522dec61de0584a9d51850ccc2b7a13857b562c
|
refs/heads/master
| 2020-08-31T12:45:34.262934
| 2019-10-30T23:43:15
| 2019-10-30T23:44:21
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 13,055
|
py
|
# Copyright 2018 The TensorFlow Probability Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
"""Tests for the ProbitBernoulli distribution."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
# Dependency imports
import numpy as np
from scipy import special as sp_special
import tensorflow.compat.v1 as tf1
import tensorflow.compat.v2 as tf
import tensorflow_probability as tfp
from tensorflow_probability.python.internal import special_math
from tensorflow_probability.python.internal import tensorshape_util
from tensorflow_probability.python.internal import test_util as tfp_test_util
from tensorflow.python.framework import test_util # pylint: disable=g-direct-tensorflow-import
tfd = tfp.distributions
def make_bernoulli(batch_shape, dtype=tf.int32):
p = np.random.uniform(size=list(batch_shape))
p = tf.constant(p, dtype=tf.float32)
return tfd.ProbitBernoulli(probs=p, dtype=dtype)
def entropy(p):
q = 1. - p
return -q * np.log(q) - p * np.log(p)
@test_util.run_all_in_graph_and_eager_modes
class ProbitBernoulliTest(tfp_test_util.TestCase):
def testP(self):
p = [0.2, 0.4]
dist = tfd.ProbitBernoulli(probs=p)
self.assertAllClose(p, self.evaluate(dist.probs))
def testProbits(self):
probits = [-42., 42.]
dist = tfd.ProbitBernoulli(probits=probits)
self.assertAllClose(probits, self.evaluate(dist.probits))
self.assertAllClose(
sp_special.ndtr(probits), self.evaluate(dist.probs_parameter()))
p = [0.01, 0.99, 0.42]
dist = tfd.ProbitBernoulli(probs=p)
self.assertAllClose(
sp_special.ndtri(p), self.evaluate(dist.probits_parameter()))
def testInvalidP(self):
invalid_ps = [1.01, 2.]
for p in invalid_ps:
with self.assertRaisesOpError('probs has components greater than 1'):
dist = tfd.ProbitBernoulli(probs=p, validate_args=True)
self.evaluate(dist.probs_parameter())
invalid_ps = [-0.01, -3.]
for p in invalid_ps:
with self.assertRaisesOpError('x >= 0 did not hold'):
dist = tfd.ProbitBernoulli(probs=p, validate_args=True)
self.evaluate(dist.probs_parameter())
valid_ps = [0.0, 0.5, 1.0]
for p in valid_ps:
dist = tfd.ProbitBernoulli(probs=p)
self.assertEqual(p, self.evaluate(dist.probs)) # Should not fail
def testShapes(self):
for batch_shape in ([], [1], [2, 3, 4]):
dist = make_bernoulli(batch_shape)
self.assertAllEqual(batch_shape,
tensorshape_util.as_list(dist.batch_shape))
self.assertAllEqual(batch_shape, self.evaluate(dist.batch_shape_tensor()))
self.assertAllEqual([], tensorshape_util.as_list(dist.event_shape))
self.assertAllEqual([], self.evaluate(dist.event_shape_tensor()))
def testDtype(self):
dist = make_bernoulli([])
self.assertEqual(dist.dtype, tf.int32)
self.assertEqual(dist.dtype, dist.sample(5).dtype)
self.assertEqual(dist.dtype, dist.mode().dtype)
self.assertEqual(dist.probs.dtype, dist.mean().dtype)
self.assertEqual(dist.probs.dtype, dist.variance().dtype)
self.assertEqual(dist.probs.dtype, dist.stddev().dtype)
self.assertEqual(dist.probs.dtype, dist.entropy().dtype)
self.assertEqual(dist.probs.dtype, dist.prob(0).dtype)
self.assertEqual(dist.probs.dtype, dist.prob(0.5).dtype)
self.assertEqual(dist.probs.dtype, dist.log_prob(0).dtype)
self.assertEqual(dist.probs.dtype, dist.log_prob(0.5).dtype)
dist64 = make_bernoulli([], tf.int64)
self.assertEqual(dist64.dtype, tf.int64)
self.assertEqual(dist64.dtype, dist64.sample(5).dtype)
self.assertEqual(dist64.dtype, dist64.mode().dtype)
def testFloatMode(self):
dist = tfd.ProbitBernoulli(probs=.6, dtype=tf.float32)
self.assertEqual(np.float32(1), self.evaluate(dist.mode()))
def _testPmf(self, **kwargs):
dist = tfd.ProbitBernoulli(**kwargs)
# pylint: disable=bad-continuation
xs = [
0,
[1],
[1, 0],
[[1, 0]],
[[1, 0], [1, 1]],
]
expected_pmfs = [
[[0.8, 0.6], [0.7, 0.4]],
[[0.2, 0.4], [0.3, 0.6]],
[[0.2, 0.6], [0.3, 0.4]],
[[0.2, 0.6], [0.3, 0.4]],
[[0.2, 0.6], [0.3, 0.6]],
]
# pylint: enable=bad-continuation
for x, expected_pmf in zip(xs, expected_pmfs):
self.assertAllClose(self.evaluate(dist.prob(x)), expected_pmf)
self.assertAllClose(self.evaluate(dist.log_prob(x)), np.log(expected_pmf))
def testPmfCorrectBroadcastDynamicShape(self):
p = tf1.placeholder_with_default([0.2, 0.3, 0.4], shape=None)
dist = tfd.ProbitBernoulli(probs=p)
event1 = [1, 0, 1]
event2 = [[1, 0, 1]]
self.assertAllClose(
[0.2, 0.7, 0.4], self.evaluate(dist.prob(event1)))
self.assertAllClose(
[[0.2, 0.7, 0.4]], self.evaluate(dist.prob(event2)))
def testPmfInvalid(self):
p = [0.1, 0.2, 0.7]
dist = tfd.ProbitBernoulli(probs=p, validate_args=True)
with self.assertRaisesOpError('must be non-negative.'):
self.evaluate(dist.prob([1, 1, -1]))
with self.assertRaisesOpError('Elements cannot exceed 1.'):
self.evaluate(dist.prob([2, 0, 1]))
def testPmfWithP(self):
p = [[0.2, 0.4], [0.3, 0.6]]
self._testPmf(probs=p)
self._testPmf(probits=sp_special.ndtri(p))
def testPmfWithFloatArgReturnsXEntropy(self):
p = [[0.2], [0.4], [0.3], [0.6]]
samps = [0, 0.1, 0.8]
self.assertAllClose(
np.float32(samps) * np.log(np.float32(p)) +
(1 - np.float32(samps)) * np.log(1 - np.float32(p)),
self.evaluate(
tfd.ProbitBernoulli(probs=p, validate_args=False).log_prob(samps)))
def testBroadcasting(self):
probs = lambda p: tf1.placeholder_with_default(p, shape=None)
dist = lambda p: tfd.ProbitBernoulli(probs=probs(p))
self.assertAllClose(np.log(0.5), self.evaluate(dist(0.5).log_prob(1)))
self.assertAllClose(
np.log([0.5, 0.5, 0.5]), self.evaluate(dist(0.5).log_prob([1, 1, 1])))
self.assertAllClose(np.log([0.5, 0.5, 0.5]),
self.evaluate(dist([0.5, 0.5, 0.5]).log_prob(1)))
def testPmfShapes(self):
probs = lambda p: tf1.placeholder_with_default(p, shape=None)
dist = lambda p: tfd.ProbitBernoulli(probs=probs(p))
self.assertEqual(
2, len(self.evaluate(dist([[0.5], [0.5]]).log_prob(1)).shape))
dist = tfd.ProbitBernoulli(probs=0.5)
self.assertEqual(2, len(self.evaluate(dist.log_prob([[1], [1]])).shape))
dist = tfd.ProbitBernoulli(probs=0.5)
self.assertEqual((), dist.log_prob(1).shape)
self.assertEqual((1), dist.log_prob([1]).shape)
self.assertEqual((2, 1), dist.log_prob([[1], [1]]).shape)
dist = tfd.ProbitBernoulli(probs=[[0.5], [0.5]])
self.assertEqual((2, 1), dist.log_prob(1).shape)
def testBoundaryConditions(self):
dist = tfd.ProbitBernoulli(probs=1.0)
self.assertAllClose(np.nan, self.evaluate(dist.log_prob(0)))
self.assertAllClose([np.nan], [self.evaluate(dist.log_prob(1))])
def testEntropyNoBatch(self):
p = 0.2
dist = tfd.ProbitBernoulli(probs=p)
self.assertAllClose(self.evaluate(dist.entropy()), entropy(p))
def testEntropyWithBatch(self):
p = [[0.1, 0.7], [0.2, 0.6]]
dist = tfd.ProbitBernoulli(probs=p, validate_args=False)
self.assertAllClose(
self.evaluate(dist.entropy()),
[[entropy(0.1), entropy(0.7)], [entropy(0.2),
entropy(0.6)]])
def testSampleN(self):
p = [0.2, 0.6]
dist = tfd.ProbitBernoulli(probs=p)
n = 100000
samples = dist.sample(n)
tensorshape_util.set_shape(samples, [n, 2])
self.assertEqual(samples.dtype, tf.int32)
sample_values = self.evaluate(samples)
self.assertTrue(np.all(sample_values >= 0))
self.assertTrue(np.all(sample_values <= 1))
# Note that the standard error for the sample mean is ~ sqrt(p * (1 - p) /
# n). This means that the tolerance is very sensitive to the value of p
# as well as n.
self.assertAllClose(p, np.mean(sample_values, axis=0), atol=1e-2)
self.assertEqual(set([0, 1]), set(sample_values.flatten()))
# In this test we're just interested in verifying there isn't a crash
# owing to mismatched types. b/30940152
dist = tfd.ProbitBernoulli(np.log([.2, .4]))
x = dist.sample(1, seed=tfp_test_util.test_seed())
self.assertAllEqual((1, 2), tensorshape_util.as_list(x.shape))
def testNotReparameterized(self):
p = tf.constant([0.2, 0.6])
_, grad_p = tfp.math.value_and_gradient(
lambda x: tfd.ProbitBernoulli(probs=x).sample(100), p)
self.assertIsNone(grad_p)
def testSampleDeterministicScalarVsVector(self):
p = [0.2, 0.6]
dist = tfd.ProbitBernoulli(probs=p)
n = 1000
def _maybe_seed():
if tf.executing_eagerly():
tf1.set_random_seed(42)
return None
return 42
self.assertAllEqual(
self.evaluate(dist.sample(n, _maybe_seed())),
self.evaluate(dist.sample([n], _maybe_seed())))
n = tf1.placeholder_with_default(np.int32(1000), shape=None)
sample1 = dist.sample(n, _maybe_seed())
sample2 = dist.sample([n], _maybe_seed())
sample1, sample2 = self.evaluate([sample1, sample2])
self.assertAllEqual(sample1, sample2)
def testMean(self):
p = np.array([[0.2, 0.7], [0.5, 0.4]], dtype=np.float32)
dist = tfd.ProbitBernoulli(probs=p)
self.assertAllEqual(self.evaluate(dist.mean()), p)
def testVarianceAndStd(self):
var = lambda p: p * (1. - p)
p = [[0.2, 0.7], [0.5, 0.4]]
dist = tfd.ProbitBernoulli(probs=p)
self.assertAllClose(
self.evaluate(dist.variance()),
np.array([[var(0.2), var(0.7)], [var(0.5), var(0.4)]],
dtype=np.float32))
self.assertAllClose(
self.evaluate(dist.stddev()),
np.array([[np.sqrt(var(0.2)), np.sqrt(var(0.7))],
[np.sqrt(var(0.5)), np.sqrt(var(0.4))]],
dtype=np.float32))
def testProbitBernoulliProbitBernoulliKL(self):
batch_size = 6
a_p = np.array([0.6] * batch_size, dtype=np.float32)
b_p = np.array([0.4] * batch_size, dtype=np.float32)
a = tfd.ProbitBernoulli(probs=a_p)
b = tfd.ProbitBernoulli(probs=b_p)
kl = tfd.kl_divergence(a, b)
kl_val = self.evaluate(kl)
kl_expected = (a_p * np.log(a_p / b_p) + (1. - a_p) * np.log(
(1. - a_p) / (1. - b_p)))
self.assertEqual(kl.shape, (batch_size,))
self.assertAllClose(kl_val, kl_expected)
def testParamTensorFromProbits(self):
x = tf.constant([-1., 0.5, 1.])
d = tfd.ProbitBernoulli(probits=x, validate_args=True)
self.assertAllClose(
*self.evaluate([special_math.ndtri(d.prob(1.)),
d.probits_parameter()]),
atol=0,
rtol=1e-4)
self.assertAllClose(
*self.evaluate([d.prob(1.), d.probs_parameter()]), atol=0, rtol=1e-4)
def testParamTensorFromProbs(self):
x = tf.constant([0.1, 0.5, 0.4])
d = tfd.ProbitBernoulli(probs=x, validate_args=True)
self.assertAllClose(
*self.evaluate([special_math.ndtri(d.prob(1.)),
d.probits_parameter()]),
atol=0,
rtol=1e-4)
self.assertAllClose(
*self.evaluate([d.prob(1.), d.probs_parameter()]), atol=0, rtol=1e-4)
@test_util.run_all_in_graph_and_eager_modes
class ProbitBernoulliFromVariableTest(tfp_test_util.TestCase):
def testGradientProbits(self):
x = tf.Variable([-1., 1])
self.evaluate(x.initializer)
d = tfd.ProbitBernoulli(probits=x, validate_args=True)
with tf.GradientTape() as tape:
loss = -d.log_prob([0, 1])
g = tape.gradient(loss, d.trainable_variables)
self.assertLen(g, 1)
self.assertAllNotNone(g)
def testGradientProbs(self):
x = tf.Variable([0.1, 0.7])
self.evaluate(x.initializer)
d = tfd.ProbitBernoulli(probs=x, validate_args=True)
with tf.GradientTape() as tape:
loss = -d.log_prob([0, 1])
g = tape.gradient(loss, d.trainable_variables)
self.assertLen(g, 1)
self.assertAllNotNone(g)
def testAssertionsProbs(self):
x = tf.Variable([0.1, 0.7, 0.0])
d = tfd.ProbitBernoulli(probs=x, validate_args=True)
self.evaluate(x.initializer)
self.evaluate(d.entropy())
with tf.control_dependencies([x.assign([0.1, -0.7, 0.0])]):
with self.assertRaisesOpError('x >= 0 did not hold'):
self.evaluate(d.entropy())
if __name__ == '__main__':
tf.test.main()
|
[
"gardener@tensorflow.org"
] |
gardener@tensorflow.org
|
9fcf128a1978a85ebd97a6e38aa48846a658c2f6
|
215fc7c88d816e93199167823a97530e777f9466
|
/core/migrations/0003_url_redirect_count.py
|
224d7d7bbe8f7e4d46ffd2c5ed3eabea2654ce65
|
[] |
no_license
|
lliricheskiuu/orm_auth_urlShortener
|
957d39e395097626701e3b604931cffb53d0acf0
|
8cbe711af4c215e8cd9b34bd0a2fceaf07f81d28
|
refs/heads/master
| 2023-07-10T01:27:40.051582
| 2021-08-15T11:19:47
| 2021-08-15T11:19:47
| 394,743,094
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 416
|
py
|
# Generated by Django 3.2.3 on 2021-08-15 10:59
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('core', '0002_alter_url_key'),
]
operations = [
migrations.AddField(
model_name='url',
name='redirect_count',
field=models.IntegerField(default=0),
preserve_default=False,
),
]
|
[
"kzarrr4@gmail.com"
] |
kzarrr4@gmail.com
|
9705c634ccb676f51e5e6f5c9b8aa64820268883
|
abfdac5a34895cb747995e21542556a96fb55bd1
|
/tree.py
|
7c14531fda378468753c7155b4b2fb451fab5d81
|
[] |
no_license
|
KatherineCG/Algorithm
|
74db0ba7eef0c1fb38eaea13722e126d1bd93ec7
|
697f5524d18eabe7566a81c6f35e3320469a55f2
|
refs/heads/master
| 2020-03-26T19:57:27.000672
| 2018-08-19T11:08:13
| 2018-08-19T11:08:13
| 145,295,654
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 3,820
|
py
|
import Queue
class TreeNode:
def __init__(self, data):
self.val = data
self.left = None
self.right = None
class BinaryTree:
def PreOrder(self, tree, res):
if not tree:
return []
res.append(tree.val)
self.PreOrder(tree.left, res)
self.PreOrder(tree.right, res)
return res
def InOrder(self, tree, res):
if not tree:
return []
self.InOrder(tree.left, res)
res.append(tree.val)
self.InOrder(tree.right, res)
return res
def PostOrder(self, tree, res):
if not tree:
return []
self.PostOrder(tree.left, res)
self.PostOrder(tree.right, res)
res.append(tree.val)
return res
def preorder(self, bintree):
if not bintree:
return []
res = []
tree = []
p = bintree
while p or tree:
while p:
tree.append(p)
res.append(p.val)
p = p.left
if tree:
p = tree.pop()
p = p.right
return res
def inorder(self, bintree):
if not bintree:
return []
res = []
tree = []
p = bintree
while p or tree:
while p:
tree.append(p)
p = p.left
if tree:
p = tree.pop()
res.append(p.val)
p = p.right
return res
def postorder(self, bintree):
if not bintree:
return []
tree = []
res = []
tree.append(bintree)
while tree:
p = tree.pop()
res.insert(0, p.val)
if p.left:
tree.append(p.left)
if p.right:
tree.append(p.right)
return res
def traverse(self, tree):
if not tree:
return []
res = []
q = Queue.Queue()
q.put(tree)
while not q.empty():
level = []
length = q.qsize()
for i in range(length):
p = q.get()
level.append(p.val)
if p.left:
q.put(p.left)
if p.right:
q.put(p.right)
res.append(level)
return res
def CreateBinaryTree(self, data, n):
if len(data) > 0:
flag = False
for i in range(n, len(data)):
if data[i] != '#':
flag = True
break
if flag:
l = 2 * n + 1
r = 2 * n + 2
j = n + 1
if j < len(data):
while data[j] == '#':
if data[j:] == ['#' for x in range(j, len(data))]:
break
data.insert(l + 2 * (j - n), '#')
data.insert(r + 2 * (j - n), '#')
j += 1
if data[n] != '#':
pRoot = TreeNode(data[n])
pRoot.left = self.CreateBinaryTree(data, l)
pRoot.right = self.CreateBinaryTree(data, r)
return pRoot
else:
return None
else:
return None
else:
return None
test = BinaryTree()
treeinput = [1,2,3,4,5,6,7]
tree = test.CreateBinaryTree(treeinput, 0)
print test.traverse(tree)
print test.PreOrder(tree, [])
print test.preorder(tree)
print test.InOrder(tree, [])
print test.inorder(tree)
print test.PostOrder(tree, [])
print test.postorder(tree)
|
[
"noreply@github.com"
] |
KatherineCG.noreply@github.com
|
f22aa844e4a1abb8405742a55991017dd9c5e6e3
|
8f54f227e28d7c0c1a11af0c9d0ec09cf679dc3c
|
/김노은/[List] 1244.py
|
6b903c08cc5788a47ef5b9dbad60a45ff05807e5
|
[] |
no_license
|
bellaria19/2020-Spring-Jookgorithm
|
0325e58f1cf6b46a0a1b441ce75d37424924b6f8
|
5044acfd78b86728769f94a03806ef94ceb1a920
|
refs/heads/master
| 2022-12-04T09:51:58.815174
| 2020-08-25T11:45:55
| 2020-08-25T11:45:55
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 930
|
py
|
import sys
switch_num = int(input())
switch_status = [0] + list(map(int, sys.stdin.readline().split()))
student_numum = int(input())
student_info = [list(map(int, sys.stdin.readline().split())) for i in range(student_numum)]
for info in student_info:
if info[0] == 1:
for i in range(1, switch_num//info[1] + 1):
switch_status[i * info[1]] = int(not switch_status[i * info[1]])
else:
switch_status[info[1]] = int(not switch_status[info[1]])
move = 1
while (info[1]-move) > 0 and (info[1]+move) <= switch_num and switch_status[info[1] - move] == switch_status[info[1] + move]:
switch_status[info[1] - move] = int(not switch_status[info[1] - move])
switch_status[info[1] + move] = int(not switch_status[info[1] + move])
move += 1
for i in range(1, len(switch_status)):
print(switch_status[i], end= ' ')
if i%20 == 0:
print()
|
[
"noelleland@naver.com"
] |
noelleland@naver.com
|
9ce91c8561fffd158ba88da040dd06fd990376b3
|
8c0640716b86f759478b0b83e3973707d763b887
|
/lib/scan.py
|
1b58a1762041653d4e2fc7f72783d6ec309a4f22
|
[] |
no_license
|
Kevin-sa/SSRF_ex
|
6583f84788a93763189b8f91e55ac2064018fb39
|
7bae64aeba95dd4a5d1aec5ece7209a4c80af0bd
|
refs/heads/master
| 2020-03-15T16:53:33.926289
| 2018-07-04T16:12:43
| 2018-07-04T16:12:43
| 132,245,489
| 7
| 1
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 5,551
|
py
|
#encoding : utf-8
from lib.common import get_requests
import time,requests, hashlib, threading,queue
from lib.config import logging, out_put
#scan open ports
#22 port ssh-sevice, 80 port http-server, 445 port smtp-server, 3306 port-server, 6379 port redis-server, 7001 port weblogic-console, 8080 port tomcat\jobss-server, 11211 port memcache-server
#try use conn_time to judge
'''
class Scan(object):
def __init__(self,target,parameter):
self.target = target
self.parameter = parameter
self.ports = [22,80,445,3306,6379,7001,8080,11211]
#self.ports = [22,80]
self.open_port = []
#self.time_out = self._time_limit()
def _time_limit(self):
url = "{url}?{query}=ftp://127.0.0.1:80".format(url=self.target,query=self.parameter)
r = requests.get(url)
time_out = float(r.elapsed.microseconds)
print(time_out)
return time_out
def _port_open(self):
time_out = 66522.0
for port in self.ports:
payload = "{url}?{query}=dict://127.0.0.1:{port}".format(url=self.target, query=self.parameter, port=port)
print(payload)
request_time = requests.get(payload).elapsed.microseconds
print("port:{} time:{}".format(port, request_time))
if request_time <= time_out:
self.open_port.append(port)
return list(set(self.open_port))
'''
#use hash of content to judge
class Scan(object):
def __init__(self, target, parameter,ip='',queue=''):
self.target = target
self.parameter = parameter
self.ports = [22, 80, 445, 3306, 6379, 7001, 8080, 11211]
self.hash = hashlib.md5()
self.ip = ip
self.queue = queue
#when the port is not exist,use dict protocol to get the hash of content
def hash_limit(self):
payload = "{url}?{query}=dict://127.0.0.1:{port}".format(url=self.target, query=self.parameter, port=0)
limit_conn = get_requests(payload).text
if limit_conn:
self.hash.update(limit_conn.encode('utf-8'))
return self.hash.hexdigest()
else:
return False
#judge the open port,default is host
def _open_port(self,ip=''):
hash_judge = []
open_port = []
if ip:
pass
else:
ip = '127.0.0.1'
logging.info("Starting detect open ports in ip:{}.....".format(ip))
for port in self.ports:
hash_values = {}
payload = "{url}?{query}=dict://{ip}:{port}".format(url=self.target, query=self.parameter, ip=ip, port=port)
#print(payload)
port_conn = get_requests(payload).text
if port_conn:
self.hash.update(port_conn.encode('utf-8'))
hash_values['port'] = port
hash_values['hash'] = self.hash.hexdigest()
hash_judge.append(hash_values)
else:
pass
#print(hash_judge)
hash_limit_value = self.hash_limit()
if hash_limit_value:
for i in hash_judge:
if hash_limit_value != i['hash']:
open_port.append(i['port'])
else:
for j in hash_judge:
open_port.append(j['port'])
return list(set(open_port))
def host_port(self):
while True:
if self.queue.empty():
break
try:
ip = self.queue.get_nowait()
ip_port = self._open_port(ip=ip)
if ip_port:
out_put(self.target,'host_port.log',ip_port)
logging.info("the {} found open port is: {}".format(self.ip, ip_port))
except requests.exceptions.ReadTimeout:
pass
except requests.exceptions.ConnectTimeout:
pass
except Exception as e:
break
def run(target,parameter,ip_c=''):
threads_count = 20
threads = []
Queue = queue.Queue()
open_port = Scan(target, parameter)._open_port()
out_put(target, 'host_port.log', open_port)
logging.info("127.0.0.1 host found open port is: {}".format(open_port))
if ip_c:
logging.info("Starting to detct the other ip ....")
for d in range(105,106):
ip = '{0}.{1}'.format(ip_c, d)
Queue.put(ip)
for i in range(threads_count):
t = threading.Thread(target=Scan(target, parameter, queue=Queue).host_port())
t.start()
t.join()
'''
threads.append(Scan(target, parameter, queue=Queue).host_port())
for t in threads:
t.start()
for t in threads:
t.join()
'''
#use file to get file content
def file_reader(target,parameter):
content = []
get_file = []
paths = ['/etc/rsyslog.conf','/etc/syslog.conf','/etc/passwd','/etc/shadow','/etc/group','/etc/anacrontab','/etc/networks','/etc/hosts']
logging.info("Use the protocol to get the contents of the file.....")
for path in paths:
payload = "{url}?{query}=file://{path}".format(url=target, query=parameter, path=path)
file_content = get_requests(payload)
if file_content:
content.append(file_content.text.strip())
get_file.append(path)
else:
pass
if content:
logging.info("Save file content: {}".format(get_file))
out_put(target,'file_content.log',list(set(content)))
|
[
"kevinsa@gmail.com"
] |
kevinsa@gmail.com
|
80e43533a78587cad0cea97fc52d873dd7b725b2
|
d51b719092f3baee00771785fda848f6a4f31c53
|
/cyber/api/views/DebateViewSet.py
|
dc8bb2647a0ff2c13316223a7d0ac9d77b998a27
|
[] |
no_license
|
Ang98/cyberdemo
|
0bca22924e969c18925edfe97926357b09f06ad8
|
81041d9e263a87ae7c3dfdb6a0a7418021b7e86a
|
refs/heads/master
| 2023-07-31T07:30:25.558851
| 2020-05-05T03:54:04
| 2020-05-05T03:54:04
| 237,125,073
| 0
| 0
| null | 2021-09-22T18:48:09
| 2020-01-30T02:33:20
|
Python
|
UTF-8
|
Python
| false
| false
| 572
|
py
|
from django.shortcuts import render
# CYBER
from rest_framework import viewsets
from rest_framework.permissions import IsAuthenticated
from ..serializer.DebateSerializer import *
from ..models.Debate import *
class DebateViewSet(viewsets.ModelViewSet):
serializer_class = DebateSerializer
permission_classes = (IsAuthenticated,)
def get_queryset(self):
queryset = Debate.objects.all()
usuario = self.request.user
if usuario.is_administrador:
return queryset
return ['Usuario no es administrador']
|
[
"angelcayatopa98@gmail.com"
] |
angelcayatopa98@gmail.com
|
bb7b405aa848fd021f45afb15843edddd21c69dd
|
c4cc9a7406ebf2e46535cd29080f302cf2f6c01d
|
/scanner.py
|
ff0b2f00a377539720a6b863681ce00eddce60c7
|
[
"MIT"
] |
permissive
|
OscarEReyes/Modding-Tool
|
64660aa0348072ae97b01bab3828b65cd9e72645
|
2edcb6d3423f22b8720d5cb135043d72af31c44f
|
refs/heads/master
| 2021-01-17T14:17:11.181533
| 2016-12-20T00:45:34
| 2016-12-20T00:45:34
| 51,173,694
| 0
| 1
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 3,291
|
py
|
from softwareModClasses import Feature
from Categories import Categories
line_tags = [
'Name',
'Description',
'Unlock',
'NameGenerator',
'Popularity',
'TimeScale',
'Retention',
'Iterative'
]
def scan(tree, c_combo_box, f_combo_box):
"""
* Parameter: tree (etree root element)
* Parameter: c_combo_box (Qt combobox object)
* Parameter: f_combo_box (Qt combobox object)
* Look for 'Categories tag in tree, store it, and
* If it is not None execute look_for_categories method
*
* Look for 'Features' tag in tree and store it
* Execute look_for_features method
"""
categories = tree.find('Categories')
if categories is not None:
search_categories(categories, c_combo_box)
features = tree.find('Features')
search_features(features, f_combo_box)
def search_categories(categories, combobox):
"""
* Parameter: categories (etree element -Tag- 'Categories)
* Parameter: combobox (Qt Combobox object)
* Create Categories object -Note- Pass opt parameter Scan as True
* Iterate over category (etree element tag 'Category) in categories
* Get name of category (attrib 'Name')
* Execute add_category method for each category (Category Object)
"""
categories_object = Categories.add(categories.getparent(), combobox, True)
for category in categories:
name = category.attrib["Name"]
categories_object.add_category(name, True)
def search_features(features, combobox):
"""
* Parameter: features (etree element -Tag- 'Features')
* Iterate over feature elements (etree elements) in features
* Look for tag 'Name' in feature and store its text in var name
* Create Feature Object for each feature
* Execute look_for_dependencies method for each Feature Object
"""
for feature in features:
name = feature.find('Name').text
f = Feature.add(features, name, combobox, True)
search_dep(feature, f)
search_soft_categ(feature, f)
def search_dep(feature, f):
"""
* Parameter: feature (etree Element -Tag- 'Feature')
* Parameter: f (Feature object)
* Iterate over feature's elements (etree elements)
* Look for tag 'Dependency' in feature and store its text in var
* Get element attribute 'Software' and store it in a var
* Add dependency object to f
"""
for element in feature:
if element.tag == 'Dependency':
dependency = element.text
software = element.attrib["Software"]
f.scan_special_tag('f', software, dependency)
def search_soft_categ(feature, f):
"""
* Parameter: feature(etree Element -Tag- 'Feature')
* Parameter: f (Feature object)
* Iterate over feature's elements (etree elements)
* Look for tag 'Dependency' in feature and store its text in var
* Get element attribute 'Software' and store it in a var
* Add dependency object to f
"""
for attribute in feature:
if attribute.tag == 'SoftwareCategory':
unlock = attribute.text
category = attribute.attrib["Category"]
f.scan_software_category('sc', category, unlock)
|
[
"noreply@github.com"
] |
OscarEReyes.noreply@github.com
|
9c2ffe8c7c3cb51ce4ce7379e0b0eda58bc2928a
|
fae9e054b1232b72ccc2a36d9f13184ed54fe06a
|
/PayController/wechatAppletOrderPay.py
|
58835f8c4883f7dfb16fa3b37e849b758d51978a
|
[] |
no_license
|
Ronald122013/API_test
|
66f719f0c75c93b69dfe5f3ae7951838e93fd120
|
898b5afdcda7fb211bb58e922e82a6c20bb43299
|
refs/heads/master
| 2022-11-25T06:23:47.185645
| 2020-07-30T05:38:41
| 2020-07-30T05:38:41
| 283,679,438
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,946
|
py
|
#小程序调用支付
#!usr/bin/env python
# -*- coding:utf-8 -*-
import logging
logging.basicConfig(level=logging.DEBUG,format=' %(asctime)s - %(levelname)s- %(message)s')
# logging. disable(logging.CRITICAL) # 禁用日志
logging.debug('>>>>>>Start of program<<<<<<')
import unittest
import json
import requests
from assertpy import assert_that
from commonApp import getDomain as c
from commonApp import getStatusCode as s
domain = c.Get_Domain().Domain('156')
class wechatAppletOrderPay(unittest.TestCase):
def setUp(self):
#self.url = domain + '/toBRegister'
#self.headers = {"Content-Type":"application/json;charset=UTF-8"}
print(">>>>>>BEGIN toBRegister TEST<<<<<<")
def test_wechatAppletOrderPay(self):
self.url = domain + '/toBRegister'
self.headers = {"Content-Type":"application/json;charset=UTF-8"}
with open('./PayController/wechatAppletOrderPay.json','r',encoding='utf-8') as f:
data = json.load(f)
self.form = data
#print(data) #调试用
#开始发数据
r = requests.post(self.url,json = self.form,headers = self.headers)
print(r.text) #打印返回参数
print('接口响应时间：',r.elapsed.total_seconds()) #打印接口响应时间
null = None #兼容
dic = eval(r.text) #str转化为dict
code = dic["code"] #提取status里面的code值
s.getStatusCode(code) #打印code值
try:
assert_that(code).is_equal_to(200) #当前值判断接口返回状态
except AssertionError as e:
raise AssertionError(e)
if __name__ == '__main__':
#unittest.main()
runTest = wechatAppletOrderPay()
runTest.test_wechatAppletOrderPay()
logging.debug('>>>>>>End of program<<<<<<')
|
[
"18529533960@163.com"
] |
18529533960@163.com
|
5902145d39bd706e85af337bfb580ade6d6c4b63
|
990c11e2caed3b3f797bcc40e1e5f2ebf1da6d99
|
/9_Iterator_mode/coroutine_prac.py
|
d4eb481d8f52fcf1ebb50971bc7e99a92b71d71d
|
[] |
no_license
|
KindleHsieh/OOP_book_practice
|
72c1cc0c8558ac6f3bf149b39a15ee0a7c13dd1f
|
a3c6db3f403be6943469c3eed40d868009ff5f96
|
refs/heads/main
| 2023-09-04T00:36:31.644596
| 2021-11-01T23:17:12
| 2021-11-01T23:17:12
| 407,589,515
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,864
|
py
|
# -*- coding: utf-8 -*-
# author: Kindle Hsieh time: 2021/10/21
def tally():
score = 0
while True:
increase = yield score
score += increase
# Create teams.
white_sox = tally()
blue_jay = tally()
# initial game.
next(white_sox)
next(blue_jay)
# Add score.
white_sox.send(1)
blue_jay.send(3)
max_point_team = tally()
next(max_point_team)
for i in white_sox, blue_jay:
if i.send(0) > max_point_team.send(0):
max_point_team = i
print(max_point_team.__name__, max_point_team.send(0))
'''
coroutine.(協程)
建立後，要利用next()做初始化，第一次推動他。
之後只能使用send(val)將參數傳進去。
協程無法單獨取得函式內的參數，也無法print結果(例如這邊的score)。
如果有顯示接收他的結果，就要使用send()才能讓yield回傳。
'''
##################
# log Analyze. #
##################
import re
# search all rows and pass the row related with regex.
def match_regex(filename, regex):
with open(filename) as file:
lines = file.readlines()
for line in reversed(lines):
match = re.match(regex, line)
if match:
regex = yield match.groups()[0]
# Interactive with first def and suggest the right regex.
def get_serials(filename):
ERROR_RE = 'XFS ERROR (\[sd[a-z]\])'
matcher = match_regex(filename, ERROR_RE)
device = next(matcher)
while True:
print('-'*36)
bus = matcher.send(
f'(sd \S+) {re.escape(device)}'
)
print(f'bus: {bus}')
serial = matcher.send(
f'{bus} \(SERIAL=([^)]*)\)'
)
print(f'serial: {serial}')
yield serial
device = matcher.send(ERROR_RE)
for serial_number in get_serials('/Users/kindlemac/PycharmProjects/OOP_book_practice/9_Iterator_mode/EXAMPLE_LOG.log'):
print(serial_number)
|
[
"mom1puppy@gmail.com"
] |
mom1puppy@gmail.com
|
67f96bfcb80546fa39f2adb18c8ce52b22aee45a
|
7673aefcb43950a281085501dccc2a25e6fbda3a
|
/websocket_example.py
|
8cce9c67a4ab9686936214b27e0d085e2cc39758
|
[] |
no_license
|
xikouxi/okex-hc
|
31a6d63a974bdac81b63f77946cf100a1b0dedeb
|
e435652ffa97ae607eaf60f1b5d74371d2d69872
|
refs/heads/master
| 2023-04-16T13:16:50.583924
| 2021-04-25T10:23:19
| 2021-04-25T10:23:19
| 361,396,425
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 18,261
|
py
|
import asyncio
import websockets
import json
import requests
import dateutil.parser as dp
import hmac
import base64
import zlib
import datetime
def get_timestamp():
now = datetime.datetime.now()
t = now.isoformat("T", "milliseconds")
return t + "Z"
def get_server_time():
url = "https://www.okex.win/api/general/v3/time"
response = requests.get(url)
if response.status_code == 200:
return response.json()['iso']
else:
return ""
def server_timestamp():
server_time = get_server_time()
parsed_t = dp.parse(server_time)
timestamp = parsed_t.timestamp()
return timestamp
def login_params(timestamp, api_key, passphrase, secret_key):
message = timestamp + 'GET' + '/users/self/verify'
mac = hmac.new(bytes(secret_key, encoding='utf8'), bytes(message, encoding='utf-8'), digestmod='sha256')
d = mac.digest()
sign = base64.b64encode(d)
login_param = {"op": "login", "args": [api_key, passphrase, timestamp, sign.decode("utf-8")]}
login_str = json.dumps(login_param)
return login_str
def inflate(data):
decompress = zlib.decompressobj(
-zlib.MAX_WBITS # see above
)
inflated = decompress.decompress(data)
inflated += decompress.flush()
return inflated
def partial(res, timestamp):
data_obj = res['data'][0]
bids = data_obj['bids']
asks = data_obj['asks']
instrument_id = data_obj['instrument_id']
# print(timestamp + '全量数据bids为：' + str(bids))
# print('档数为：' + str(len(bids)))
# print(timestamp + '全量数据asks为：' + str(asks))
# print('档数为：' + str(len(asks)))
return bids, asks, instrument_id
def update_bids(res, bids_p, timestamp):
# 获取增量bids数据
bids_u = res['data'][0]['bids']
print(timestamp + '增量数据bids为：' + str(bids_u))
# print('档数为：' + str(len(bids_u)))
# bids合并
for i in bids_u:
bid_price = i[0]
for j in bids_p:
if bid_price == j[0]:
if i[1] == '0':
bids_p.remove(j)
break
else:
del j[1]
j.insert(1, i[1])
break
else:
if i[1] != "0":
bids_p.append(i)
else:
bids_p.sort(key=lambda price: sort_num(price[0]), reverse=True)
# print(timestamp + '合并后的bids为：' + str(bids_p) + '，档数为：' + str(len(bids_p)))
return bids_p
def update_asks(res, asks_p, timestamp):
# 获取增量asks数据
asks_u = res['data'][0]['asks']
print(timestamp + '增量数据asks为：' + str(asks_u))
# print('档数为：' + str(len(asks_u)))
# asks合并
for i in asks_u:
ask_price = i[0]
for j in asks_p:
if ask_price == j[0]:
if i[1] == '0':
asks_p.remove(j)
break
else:
del j[1]
j.insert(1, i[1])
break
else:
if i[1] != "0":
asks_p.append(i)
else:
asks_p.sort(key=lambda price: sort_num(price[0]))
# print(timestamp + '合并后的asks为：' + str(asks_p) + '，档数为：' + str(len(asks_p)))
return asks_p
def sort_num(n):
if n.isdigit():
return int(n)
else:
return float(n)
def check(bids, asks):
# 获取bid档str
bids_l = []
bid_l = []
count_bid = 1
while count_bid <= 25:
if count_bid > len(bids):
break
bids_l.append(bids[count_bid-1])
count_bid += 1
for j in bids_l:
str_bid = ':'.join(j[0 : 2])
bid_l.append(str_bid)
# 获取ask档str
asks_l = []
ask_l = []
count_ask = 1
while count_ask <= 25:
if count_ask > len(asks):
break
asks_l.append(asks[count_ask-1])
count_ask += 1
for k in asks_l:
str_ask = ':'.join(k[0 : 2])
ask_l.append(str_ask)
# 拼接str
num = ''
if len(bid_l) == len(ask_l):
for m in range(len(bid_l)):
num += bid_l[m] + ':' + ask_l[m] + ':'
elif len(bid_l) > len(ask_l):
# bid档比ask档多
for n in range(len(ask_l)):
num += bid_l[n] + ':' + ask_l[n] + ':'
for l in range(len(ask_l), len(bid_l)):
num += bid_l[l] + ':'
elif len(bid_l) < len(ask_l):
# ask档比bid档多
for n in range(len(bid_l)):
num += bid_l[n] + ':' + ask_l[n] + ':'
for l in range(len(bid_l), len(ask_l)):
num += ask_l[l] + ':'
new_num = num[:-1]
int_checksum = zlib.crc32(new_num.encode())
fina = change(int_checksum)
return fina
def change(num_old):
num = pow(2, 31) - 1
if num_old > num:
out = num_old - num * 2 - 2
else:
out = num_old
return out
# subscribe channels un_need login
async def subscribe_without_login(url, channels):
l = []
while True:
try:
async with websockets.connect(url) as ws:
sub_param = {"op": "subscribe", "args": channels}
sub_str = json.dumps(sub_param)
await ws.send(sub_str)
while True:
try:
res_b = await asyncio.wait_for(ws.recv(), timeout=25)
except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed) as e:
try:
await ws.send('ping')
res_b = await ws.recv()
timestamp = get_timestamp()
res = inflate(res_b).decode('utf-8')
print(timestamp + res)
continue
except Exception as e:
timestamp = get_timestamp()
print(timestamp + "正在重连……")
print(e)
break
timestamp = get_timestamp()
res = inflate(res_b).decode('utf-8')
print(timestamp + res)
res = eval(res)
if 'event' in res:
continue
for i in res:
if 'depth' in res[i] and 'depth5' not in res[i]:
# 订阅频道是深度频道
if res['action'] == 'partial':
for m in l:
if res['data'][0]['instrument_id'] == m['instrument_id']:
l.remove(m)
# 获取首次全量深度数据
bids_p, asks_p, instrument_id = partial(res, timestamp)
d = {}
d['instrument_id'] = instrument_id
d['bids_p'] = bids_p
d['asks_p'] = asks_p
l.append(d)
# 校验checksum
checksum = res['data'][0]['checksum']
# print(timestamp + '推送数据的checksum为：' + str(checksum))
check_num = check(bids_p, asks_p)
# print(timestamp + '校验后的checksum为：' + str(check_num))
if check_num == checksum:
print("校验结果为：True")
else:
print("校验结果为：False，正在重新订阅……")
# 取消订阅
await unsubscribe_without_login(url, channels, timestamp)
# 发送订阅
async with websockets.connect(url) as ws:
sub_param = {"op": "subscribe", "args": channels}
sub_str = json.dumps(sub_param)
await ws.send(sub_str)
timestamp = get_timestamp()
print(timestamp + f"send: {sub_str}")
elif res['action'] == 'update':
for j in l:
if res['data'][0]['instrument_id'] == j['instrument_id']:
# 获取全量数据
bids_p = j['bids_p']
asks_p = j['asks_p']
# 获取合并后数据
bids_p = update_bids(res, bids_p, timestamp)
asks_p = update_asks(res, asks_p, timestamp)
# 校验checksum
checksum = res['data'][0]['checksum']
# print(timestamp + '推送数据的checksum为：' + str(checksum))
check_num = check(bids_p, asks_p)
# print(timestamp + '校验后的checksum为：' + str(check_num))
if check_num == checksum:
print("校验结果为：True")
else:
print("校验结果为：False，正在重新订阅……")
# 取消订阅
await unsubscribe_without_login(url, channels, timestamp)
# 发送订阅
async with websockets.connect(url) as ws:
sub_param = {"op": "subscribe", "args": channels}
sub_str = json.dumps(sub_param)
await ws.send(sub_str)
timestamp = get_timestamp()
print(timestamp + f"send: {sub_str}")
except Exception as e:
timestamp = get_timestamp()
print(timestamp + "连接断开，正在重连……")
print(e)
continue
# subscribe channels need login
async def subscribe(url, api_key, passphrase, secret_key, channels):
while True:
try:
async with websockets.connect(url) as ws:
# login
timestamp = str(server_timestamp())
login_str = login_params(timestamp, api_key, passphrase, secret_key)
await ws.send(login_str)
# time = get_timestamp()
# print(time + f"send: {login_str}")
res_b = await ws.recv()
res = inflate(res_b).decode('utf-8')
time = get_timestamp()
print(time + res)
# subscribe
sub_param = {"op": "subscribe", "args": channels}
sub_str = json.dumps(sub_param)
await ws.send(sub_str)
time = get_timestamp()
print(time + f"send: {sub_str}")
while True:
try:
res_b = await asyncio.wait_for(ws.recv(), timeout=25)
except (asyncio.TimeoutError, websockets.exceptions.ConnectionClosed) as e:
try:
await ws.send('ping')
res_b = await ws.recv()
time = get_timestamp()
res = inflate(res_b).decode('utf-8')
print(time + res)
continue
except Exception as e:
time = get_timestamp()
print(time + "正在重连……")
print(e)
break
time = get_timestamp()
res = inflate(res_b).decode('utf-8')
print(time + res)
except Exception as e:
time = get_timestamp()
print(time + "连接断开，正在重连……")
print(e)
continue
# unsubscribe channels
async def unsubscribe(url, api_key, passphrase, secret_key, channels):
async with websockets.connect(url) as ws:
# login
timestamp = str(server_timestamp())
login_str = login_params(str(timestamp), api_key, passphrase, secret_key)
await ws.send(login_str)
# time = get_timestamp()
# print(time + f"send: {login_str}")
res_1 = await ws.recv()
res = inflate(res_1).decode('utf-8')
time = get_timestamp()
print(time + res)
# unsubscribe
sub_param = {"op": "unsubscribe", "args": channels}
sub_str = json.dumps(sub_param)
await ws.send(sub_str)
time = get_timestamp()
print(time + f"send: {sub_str}")
res_1 = await ws.recv()
res = inflate(res_1).decode('utf-8')
time = get_timestamp()
print(time + res)
# unsubscribe channels
async def unsubscribe_without_login(url, channels, timestamp):
async with websockets.connect(url) as ws:
# unsubscribe
sub_param = {"op": "unsubscribe", "args": channels}
sub_str = json.dumps(sub_param)
await ws.send(sub_str)
print(timestamp + f"send: {sub_str}")
res_1 = await ws.recv()
res = inflate(res_1).decode('utf-8')
print(timestamp + f"recv: {res}")
api_key = ""
secret_key = ""
passphrase = ""
url = 'wss://real.okex.com:8443/ws/v3'
# url = 'wss://real.okex.com:8443/ws/v3?brokerId=9999'
# 现货
# 用户币币账户频道
channels = ["spot/account:USDT"]
# 用户杠杆账户频道
# channels = ["spot/margin_account:BTC-USDT"]
# 用户委托策略频道
# channels = ["spot/order_algo:BTC-USDT"]
# 用户交易频道
# channels = ["spot/order:BTC-USDT"]
# 公共-Ticker频道
# channels = ["spot/ticker:BTC-USDT"]
# 公共-K线频道
# channels = ["spot/candle60s:BTC-USDT"]
# 公共-交易频道
# channels = ["spot/trade:BTC-USDT"]
# 公共-5档深度频道
# channels = ["spot/depth5:BTC-USDT"]
# 公共-400档深度频道
# channels = ["spot/depth:BTC-USDT"]
# 公共-400档增量数据频道
# channels = ["spot/depth_l2_tbt:BTC-USDT"]
# 交割合约
# 用户持仓频道
# channels = ["futures/position:BTC-USD-200327"]
# 用户账户频道
# channels = ["futures/account:BTC"]
# 用户交易频道
# channels = ["futures/order:BTC-USD-200626"]
# 用户委托策略频道
# channels = ["futures/order_algo:BTC-USD-200327"]
# 公共-全量合约信息频道
# channels = ["futures/instruments"]
# 公共-Ticker频道
# channels = ["futures/ticker:BTC-USD-200626"]
# 公共-K线频道
# channels = ["futures/candle60s:BTC-USD-200626"]
# 公共-交易频道
# channels = ["futures/trade:BTC-USD-200117"]
# 公共-预估交割价频道
# channels = ["futures/estimated_price:BTC-USD-200228"]
# 公共-限价频道
# channels = ["futures/price_range:BTC-USD-200327"]
# 公共-5档深度频道
# channels = ["futures/depth5:BTC-USD-200327"]
# 公共-400档深度频道
# channels = ["futures/depth:BTC-USD-200327"]
# 公共-400档增量数据频道
# channels = ["futures/depth_l2_tbt:BTC-USD-200327"]
# 公共-标记价格频道
# channels = ["futures/mark_price:BTC-USD-200327"]
# 永续合约
# 用户持仓频道
# channels = ["swap/position:BTC-USD-SWAP"]
# 用户账户频道
# channels = ["swap/account:BTC-USD-SWAP"]
# 用户交易频道
# channels = ["swap/order:BTC-USD-SWAP"]
# 用户委托策略频道
# channels = ["swap/order_algo:BTC-USD-SWAP"]
# 公共-Ticker频道
# channels = ["swap/ticker:BTC-USD-SWAP"]
# 公共-K线频道
# channels = ["swap/candle60s:BTC-USD-SWAP"]
# 公共-交易频道
# channels = ["swap/trade:BTC-USD-SWAP"]
# 公共-资金费率频道
# channels = ["swap/funding_rate:BTC-USD-SWAP"]
# 公共-限价频道
# channels = ["swap/price_range:BTC-USD-SWAP"]
# 公共-5档深度频道
# channels = ["swap/depth5:BTC-USD-SWAP"]
# 公共-400档深度频道
# channels = ["swap/depth:BTC-USDT-SWAP"]
# 公共-400档增量数据频道
# channels = ["swap/depth_l2_tbt:BTC-USD-SWAP"]
# 公共-标记价格频道
# channels = ["swap/mark_price:BTC-USD-SWAP"]
# 期权合约
# 用户持仓频道
# channels = ["option/position:BTC-USD"]
# 用户账户频道
# channels = ["option/account:BTC-USD"]
# 用户交易频道
# channels = ["option/order:BTC-USD"]
# 公共-合约信息频道
# channels = ["option/instruments:BTC-USD"]
# 公共-期权详细定价频道
# channels = ["option/summary:BTC-USD"]
# 公共-K线频道
# channels = ["option/candle60s:BTC-USD-200327-11000-C"]
# 公共-最新成交频道
# channels = ["option/trade:BTC-USD-200327-11000-C"]
# 公共-Ticker频道
# channels = ["option/ticker:BTC-USD-200327-11000-C"]
# 公共-5档深度频道
# channels = ["option/depth5:BTC-USD-200327-11000-C"]
# 公共-400档深度频道
# channels = ["option/depth:BTC-USD-200327-11000-C"]
# 公共-400档增量数据频道
# channels = ["option/depth_l2_tbt:BTC-USD-200327-11000-C"]
# ws公共指数频道
# 指数行情
# channels = ["index/ticker:BTC-USD"]
# 指数K线
# channels = ["index/candle60s:BTC-USD"]
# WebSocket-获取系统升级状态
# channels = ["system/status"]
loop = asyncio.get_event_loop()
# 公共数据 不需要登录（行情，K线，交易数据，资金费率，限价范围，深度数据，标记价格等频道）
loop.run_until_complete(subscribe_without_login(url, channels))
# 个人数据 需要登录（用户账户，用户交易，用户持仓等频道）
# loop.run_until_complete(subscribe(url, api_key, passphrase, secret_key, channels))
loop.close()
|
[
"wanghaohao@hkincus.com"
] |
wanghaohao@hkincus.com
|
be3437aa9fa367b840821d66be4aed2a3752a683
|
c77704211d7c0534d760e0245f3b27c1a6b34153
|
/Scripts/taxaID.py
|
98fb28cd500b21cb7a3b5bf2dc0488ae5b440ace
|
[
"Apache-2.0"
] |
permissive
|
Junyu25/PCAS
|
400ca22828d64a50e8705c363b6aba41214c9842
|
436c6405563a1cd486ab06d3a13a29dc07235dd3
|
refs/heads/master
| 2020-12-23T11:29:04.601293
| 2020-09-25T11:03:08
| 2020-09-25T11:03:08
| 237,137,039
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 627
|
py
|
# -*- coding: utf-8 -*-
"""
Created on Thu Sep 19 15:23:47 2019
#Extract the ID and taxa information from the original full align fasta file.
#Usage:
#python taxaID.py file.fasta
#Input file: full align fasta file e.g. SILVA_132_LSURef_tax_silva_trunc.fasta
#Output file: file.fasta.csv which contains the ID and taxa columns
@author: Junyu
"""
import sys
import pandas as pd
from Bio import SeqIO
file = sys.argv[1]
print(file)
f = pd.DataFrame()
seqdict = {}
for seq in SeqIO.parse(file, "fasta"):
f = f.append({'ID':seq.id, "taxa":seq.description}, ignore_index=True)
f.to_csv(file +".csv", encoding = "utf-8")
|
[
"chenjunyu2016@email.szu.edu.cn"
] |
chenjunyu2016@email.szu.edu.cn
|
71479ef289bc7903e1075aa7f29f77eaf6cb43c8
|
0a691220c5e2c2a9b99d20b2ac62baa1a1f95ca3
|
/djangoimposter/users/migrations/0002_auto_20201207_2230.py
|
14cd67ebb2b2aee631a51bbacc92ec18d56df661
|
[] |
no_license
|
beasyx0/djangoimposter
|
a1fc945e09148a8cf2ae41d3f96f4c4565a5b94d
|
b7e06dfe972306179d42b6595e64a461979d32b1
|
refs/heads/main
| 2023-02-27T10:49:48.087627
| 2021-02-08T18:54:27
| 2021-02-08T18:54:27
| 334,469,294
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 409
|
py
|
# Generated by Django 3.0.11 on 2020-12-08 03:30
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('users', '0001_initial'),
]
operations = [
migrations.AlterField(
model_name='user',
name='name',
field=models.CharField(blank=True, max_length=255, verbose_name='Full Name'),
),
]
|
[
"b_easyx@protonmail.com"
] |
b_easyx@protonmail.com
|
68135f8b97c4ebc7b5ebc08b53c005435de072a0
|
ff68cb9fac6f942c571013cedd3cbc45bf79e081
|
/Mooc-Exercise/HannoTower.py
|
ba672729dd87018726edd3e4b5e0357f413bf80c
|
[] |
no_license
|
MiniFullC/PythonCode
|
1459f7251326938c4c51f322980e375cb9aed4d5
|
e17d8fb399748adee0cc786d87142a6f33feaa74
|
refs/heads/master
| 2020-03-21T15:44:29.208565
| 2018-07-23T06:32:17
| 2018-07-23T06:32:17
| 138,729,885
| 4
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 319
|
py
|
count = 0
def hanoi(n, src, dst, mid):
global count
if n == 1:
print("{}:{}->{}".format(1, src,dst))
count += 1
else:
hanoi(n-1, src, mid, dst)
print("{}:{}->{}".format(n, src, dst))
count += 1
hanoi(n-1, mid, dst, src)
hanoi(3, "A", "C", "B")
print(count)
|
[
"1414273510@qq.com"
] |
1414273510@qq.com
|
d7bef716820e0bde57cdc9f38137cd3b8605c116
|
93527a65b070e6ede1f482edd707ff86547ff67f
|
/URIonlinejudge/1036 - Bhaskara's Formula.py
|
84722cb22aae01097a1dcc991ba054a3414b0096
|
[
"MIT"
] |
permissive
|
MahmudX/Algorithms
|
9f32d26aaf3a469bafc9bb192aeb6e30d99643d7
|
df498929b5d3fc0f0d558b3369c2aa9804c292f1
|
refs/heads/master
| 2021-03-13T23:58:52.275060
| 2020-03-28T22:02:19
| 2020-03-28T22:02:19
| 246,722,181
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 328
|
py
|
import math as math
inp = list(map(float, input().split()))
A = inp[0]
B = inp[1]
C = inp[2]
D = ((B**2) - 4 * A*C)
if A == 0 or D <= 0:
print("Impossivel calcular")
else:
D = math.sqrt(D)
E = (2 * A)
R1 = (-B + D) / E
R2 = (-B - D) / E
print("R1 = %.5f" % R1)
print("R2 = %.5f" % R2)
|
[
"noreply@github.com"
] |
MahmudX.noreply@github.com
|
ccfa1b8dd0406647d78867773c7b33c3b179aee3
|
bc178ffc6636d543002032e8e47590de85b4ddb4
|
/app/models.py
|
15f3a0e95b2d3152735c25d32f1e85b9629969ac
|
[] |
no_license
|
Dave0921/logsBackend
|
df2593c28fecd48aa6359c7a145b44b507e7a1e4
|
2117da2ef61978ebca6a50363a5db5aa93237ed9
|
refs/heads/master
| 2022-04-19T02:13:52.042892
| 2020-04-14T05:23:51
| 2020-04-14T05:23:51
| 255,504,961
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,060
|
py
|
from . import db
### Models
class Action(db.Model):
__tablename__ = 'action'
id = db.Column(db.Integer, primary_key=True)
logType = db.Column(db.String(20), nullable=False)
userId = db.Column(db.Integer, db.ForeignKey("user.id"), nullable=False)
user = db.relationship("User", backref=db.backref("user", uselist=False))
sessionId = db.Column(db.String(100), nullable=False)
properties = db.Column(db.JSON, nullable=False)
date = db.Column(db.DateTime, nullable=False)
def __init__(self, logType: str, userId: int, sessionId: int, properties: str, date: str):
self.logType = logType
self.userId = userId
self.sessionId = sessionId
self.properties = properties
self.date = date
class User(db.Model):
# TODO: Add password, email, names, and other user-related attributes
__tablename__ = 'user'
id = db.Column(db.Integer, primary_key=True)
username = db.Column(db.String(100), nullable=False)
def __init__(self, username: str):
self.username = username
|
[
"sdave0921@gmail.com"
] |
sdave0921@gmail.com
|
c4d54fb98b26af71e58379df29a737a65da6cdca
|
1834fe8dd2636d4fab7c162300399229d7c6e7db
|
/fsplit/tar.py
|
0c786d5e2ada823411b0d8c1799227e3d36f042d
|
[
"MIT"
] |
permissive
|
leosartaj/fsplit
|
780acdfbaf9df657e504bfec5a9f10f2b9e59d54
|
c2a4c09153c10550f13f8bf0fc3db20c9d7afb0b
|
refs/heads/master
| 2022-10-21T07:09:38.436902
| 2022-08-25T11:02:13
| 2022-08-25T11:02:13
| 28,518,946
| 1
| 4
|
MIT
| 2022-10-15T20:29:21
| 2014-12-26T19:10:37
|
Python
|
UTF-8
|
Python
| false
| false
| 2,118
|
py
|
#!/usr/bin/env python2
##
# fsplit
# https://github.com/leosartaj/fsplit.git
#
# Copyright (c) 2014 Sartaj Singh
# Licensed under the MIT license.
##
"""
Tar related functionality
"""
import tarfile, os
import oswrapper as osw
import exce
def isTar(fName):
"""
checks whether a file is a tarfile or not
"""
return tarfile.is_tarfile(fName)
def createTar(fName, dest=None):
"""
Converts a file into tar
"""
basename, dirname = osw.basename(fName), osw.dirname(fName)
if not osw.fileExists(basename, dirname):
raise OSError('file \'%s\' does not exist' %(fName))
if not dest:
dest = osw.getpath(dirname, '')
dest = osw.getpath(dest, basename + '.tar.gz')
with tarfile.open(dest, 'w:gz') as tar:
tar.add(fName, arcname=basename)
def createTarAll(dire=osw.pDir(), dest=None):
"""
Creates tar of all the files in a directory
removes the files
"""
if not osw.dirExists(dire):
raise OSError('directory \'%s\' does not exist' %(dire))
for file in os.listdir(dire):
path = osw.getpath(dire, file)
createTar(path, dest)
os.remove(path)
def extractTar(tarname, dest=None):
"""
Extracts a tarfile to the destination
"""
basename, dirname = osw.basename(tarname), osw.dirname(tarname)
if not osw.fileExists(basename, dirname):
raise OSError('file \'%s\' does not exist' %(tarname))
if not isTar(tarname):
raise exce.NotTarError("Not a valid tarfile \'%s\'" %(tarname))
if not dest:
dest = osw.getpath(dirname, '')
with tarfile.open(tarname, 'r|gz') as tar:
tar.extractall(dest)
def extractTarAll(dire=osw.pDir(), dest=None):
"""
Extracts all tarfiles to the destination
removes the tarfiles
"""
status = False
if not osw.dirExists(dire):
raise OSError('directory \'%s\' does not exist' %(dire))
for file in os.listdir(dire):
path = osw.getpath(dire, file)
if isTar(path):
status = True
extractTar(path, dest)
os.remove(path)
return status
|
[
"singhsartaj94@gmail.com"
] |
singhsartaj94@gmail.com
|
a8f097242b7e1cefbd268bbfd9ecabca3d892e23
|
ccca5cf1e544cd30eaabe54d3a53b875538f873e
|
/rob_onboarding/stores/__init__.py
|
310ab6a6616036e2ec38e0b558514bca34673151
|
[] |
no_license
|
rh-glob/rob_onboarding
|
4b4edcbd5acabf9984f5c958fabf1942c21013da
|
78a7a91f5686288227bf542d757e4a3d8aebcfae
|
refs/heads/master
| 2020-08-30T22:16:44.900882
| 2019-11-05T16:45:18
| 2019-11-05T16:45:18
| 218,504,825
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 275
|
py
|
from rob_onboarding.stores.order_event_store import OrderEventStore # noqa
from rob_onboarding.stores.order_store import OrderStore # noqa
from rob_onboarding.stores.pizza_store import PizzaStore # noqa
from rob_onboarding.stores.topping_store import ToppingStore # noqa
|
[
"rob.hand@globality.com"
] |
rob.hand@globality.com
|
74d686d79d4895d92e74380c3d87714c7ee5db10
|
aa773f14572b99c1da25bd02d25308314d401aee
|
/coincap_ticker_specific.py
|
b8aa4a054f0be2916d009b2f5d9f8576585bbdde
|
[] |
no_license
|
mrzacsmith/coinmarketcap
|
b99094a892c2450d50141a2f3f02a570a83d0cca
|
59dda6d9dda350c14de3c01e97c76edffa99aa94
|
refs/heads/master
| 2020-04-08T20:54:36.009459
| 2018-11-30T00:27:13
| 2018-11-30T00:27:13
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,381
|
py
|
import json
import requests
convert = 'USD'
listings_url = 'https://api.coinmarketcap.com/v2/listings/'
url_end = '?structure=array&convert=' + convert
request = requests.get(listings_url)
results = request.json()
# print(json.dumps(results, sort_keys=True, indent=4))
data = results['data']
ticker_url_pairs = {}
for currency in data:
symbol = currency['symbol']
url = currency['id']
ticker_url_pairs[symbol] = url
# print(ticker_url_pairs)
while True:
print
choice = input("Enter the ticker symbol of a cryptocurrency: ")
choice = choice.upper()
print(choice)
ticker_specific_url = 'https://api.coinmarketcap.com/v2/ticker/' + str(ticker_url_pairs[choice]) + '/' + url_end
request = requests.get(ticker_specific_url)
results = request.json()
# print(json.dumps(results, sort_keys=True, indent=4))
currency = results['data'][0]
rank = currency['rank']
name = currency['name']
symbol = currency['symbol']
circulating_supply = int(currency['circulating_supply'])
total_supply = int(currency['total_supply'])
quotes = currency['quotes'][convert]
market_cap = int(quotes['market_cap'])
hour_change = quotes['percent_change_1h']
day_change = quotes['percent_change_24h']
week_change = quotes['percent_change_7d']
price = quotes['price']
volume = quotes['volume_24h']
volume_string = '{:,}'.format(volume)
market_cap_string = '{:,}'.format(market_cap)
circulating_supply_string = '{:,}'.format(circulating_supply)
total_supply_string = '{:,}'.format(total_supply)
print
print(str(rank) + ': ' + name + ' (' + symbol + ')' )
print('Market cap: \t\t$' + market_cap_string)
print('Price: \t\t\t$' + str(price))
print('24h Volume: \t\t$' + volume_string)
print('Hour change: \t\t' + str(hour_change) + '%')
print('Day change: \t\t' + str(day_change) + '%')
print('Week change: \t\t' + str(week_change) + '%')
print('Total supply: \t\t' + total_supply_string)
print('Circulating supply: \t' + circulating_supply_string)
print('Percentage of coins in circulation: ' + str(float(circulating_supply / total_supply * 100)))
print
print('~~~~~~~~~~~~~~~~~~~~~~~~~~')
choice = input('Run again? (y/n) ')
if choice == 'n':
break
|
[
"zrs3141592@gmail.com"
] |
zrs3141592@gmail.com
|
e301f382000c5f9365d80c0fbe4735d1bb96b5ea
|
7ced16cc717dce6f7356499c4e160e56c735e111
|
/code/src/add_method.py
|
b7fcf2f45ae437036a5763499979e4d710e255dd
|
[] |
no_license
|
Sofiaxue/Chinese_electronic_medical_record_NER
|
6d963098e7ca9e1fcff9862305eedd996fee090e
|
cdb8a389b15e59e937bd3dc9e086883ee751602a
|
refs/heads/master
| 2021-10-08T14:21:00.904835
| 2018-12-13T06:12:17
| 2018-12-13T06:12:17
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,288
|
py
|
# coding:utf-8
import sys
import os
import codecs
import imp
#datadir = "./data"
def ReadFile(file):
f = open(file,'r')
lines = f.readlines()
f.close()
return [line.rstrip('\r\n') for line in lines]
def ReadFileUTF8(file):
f = codecs.open(file,'r', 'utf8')
lines = f.readlines()
f.close()
return [line.rstrip() for line in lines]
def SaveFeatures(features, file, linetag="\n"):
imp.reload(sys)
# sys.setdefaultencoding('utf8')
f = open(file, "w")
for [token,tag] in features:
f.write(token + " " + tag)
f.write(linetag)
f.flush()
f.close()
def AddTrain(features, file, linetag="\n"):
imp.reload(sys)
#sys.setdefaultencoding('utf8')
f = open(file, "a")
for [token,tag2] in features:
f.write(token + " " + tag2)
f.write(linetag)
f.flush()
f.close()
def AddTest(features, file, linetag="\n"):
imp.reload(sys)
#sys.setdefaultencoding('utf8')
f = open(file, "w")
for token in features:
f.write(token)
f.write(linetag)
f.flush()
f.close()
"""if __name__ == '__main__':
lines = ReadFileUTF8(datadir+'/病史特点/病史特点-1.txtoriginal.txt');
for line in lines:
print(line)
"""
|
[
"17633700633@163.com"
] |
17633700633@163.com
|
f61a39d8625dcea53b66e2920dc1e1861875ce5f
|
309d17b81cea038713ba67bee72a41d2df4d6869
|
/Python/Python A.prasert/args.py
|
ec3d35542045871f9be09f04a40f8b53c06d08bc
|
[] |
no_license
|
Bongkot-Kladklaen/Programming_tutorial_code
|
ac07e39da2bce396e670611884436b360536cdc5
|
cda7508c15c3e3d179c64b9aac163b6173ef3519
|
refs/heads/master
| 2023-06-20T13:14:17.077809
| 2021-07-18T04:41:04
| 2021-07-18T04:41:04
| 387,081,622
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 313
|
py
|
# print(3,5,10)
# print(3,10)
# print(2, 'two',1)
def avg(*args):
total = 0
for i in args:
total += i
return total / len(args)
def print_bullet(*items, bullet="\u2022"):
for e in items:
print("{} {}".format(bullet, e))
# print(avg(2,3,5,6))
print_bullet('lily','rose','jasmine')
|
[
"bongkot.klad@gmail.com"
] |
bongkot.klad@gmail.com
|
35e94527390de65d607e55d930d377b659e81384
|
9cc41b6848e1bb7d3a62c3d4775f2b7512ef29c4
|
/DjangoPractical/chapter8/bookmark/models.py
|
227d51e407b304d58a495aff4c9c5c0f1bddf96a
|
[] |
no_license
|
Hyeon-Goo/python-web-programming-practice-part
|
5b49ef2ebd1804243ab06ca27322997016823778
|
84c1d25cbc727a427266e44c7ea1487ab48b61a0
|
refs/heads/master
| 2023-04-26T01:16:10.839256
| 2021-05-14T05:06:58
| 2021-05-14T05:06:58
| 360,438,286
| 0
| 0
| null | 2021-05-10T12:23:42
| 2021-04-22T07:58:37
|
Python
|
UTF-8
|
Python
| false
| false
| 250
|
py
|
from django.db import models
# Create your models here.
class Bookmark(models.Model):
title = models.CharField('TITLE', max_length=100, blank=True)
url = models.URLField('URL', unique=True)
def __str__(self):
return self.title
|
[
"wizardhk@naver.com"
] |
wizardhk@naver.com
|
0cff46c8ae1951bd02beb0ad049bd94fca416dce
|
d06eac41b0920d1c50cacd8e99513a4b233ebc68
|
/cap8/ex175_recursive_decimal_to_binary.py
|
fcd3cfa4e73e14a7b523be4d4efca0b01b90fe5a
|
[] |
no_license
|
RobRoger97/test_tomorrowdevs
|
81cff72e4e7aafafa32a3de8b84868add3946d58
|
2691174740fe7c647396c536c472db608605b727
|
refs/heads/main
| 2023-01-13T23:44:40.964483
| 2020-11-15T20:05:34
| 2020-11-15T20:05:34
| 304,426,984
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 629
|
py
|
#define a recursive function to convert a non-negative
#integer entered by the user from decimal to binary.
def decimal_to_binary(lis,n):
if n==1:
return 1
elif n==0:
return 0
else:
c=n%2
q=n//2
lis=str(c)
return lis + str(decimal_to_binary(lis,q))
#define the main function
def main():
#read a non-negative decimal number from the user
line = int(input("Enter a non-negative decimal number: "))
if line<0:
print("That's not a non-negative decimal number!")
else:
print(decimal_to_binary('',line)[::-1])
#call the main function
main()
|
[
"RobertaRuggiero_97@hotmail.it"
] |
RobertaRuggiero_97@hotmail.it
|
2732c7bbb0a9870594da2add13048f64309ad5c0
|
940d7b93fb27e8eead9b6e52bc5c7444666744dd
|
/python/src/Lib/test/test_transformer.py
|
909cda51837cad3bbf574a62593bb8211bb6c47d
|
[
"Apache-2.0",
"GPL-1.0-or-later",
"LicenseRef-scancode-other-copyleft",
"Python-2.0",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-python-cwi"
] |
permissive
|
pilotx45/sl4a
|
d446531d310cc17d93f24aab7271a0813e8f628d
|
150e3e46b5103a9b9a391034ef3fbc5bd5160d0f
|
refs/heads/master
| 2022-03-24T19:48:30.340479
| 2022-03-08T16:23:58
| 2022-03-08T16:23:58
| 277,016,574
| 1
| 0
|
Apache-2.0
| 2022-03-08T16:23:59
| 2020-07-04T01:25:36
| null |
UTF-8
|
Python
| false
| false
| 1,028
|
py
|
import unittest
from test import test_support
from compiler import transformer, ast
from compiler import compile
class Tests(unittest.TestCase):
def testMultipleLHS(self):
""" Test multiple targets on the left hand side. """
snippets = ['a, b = 1, 2',
'(a, b) = 1, 2',
'((a, b), c) = (1, 2), 3']
for s in snippets:
a = transformer.parse(s)
assert isinstance(a, ast.Module)
child1 = a.getChildNodes()[0]
assert isinstance(child1, ast.Stmt)
child2 = child1.getChildNodes()[0]
assert isinstance(child2, ast.Assign)
# This actually tests the compiler, but it's a way to assure the ast
# is correct
c = compile(s, '<string>', 'single')
vals = {}
exec c in vals
assert vals['a'] == 1
assert vals['b'] == 2
def test_main():
test_support.run_unittest(Tests)
if __name__ == "__main__":
test_main()
|
[
"damonkohler@gmail.com"
] |
damonkohler@gmail.com
|
7180a6535820ae9ce9bfd769a1e6a1813a6dc687
|
6e22c9bc6dd2bb442345a1c6759249fc3211322b
|
/venv/lib/python3.8/site-packages/django/core/management/commands/inspectdb.py
|
4fdcf74a72de1b4733c36b48ec765e3a3d63afdd
|
[] |
no_license
|
Sankalpa830/NHPE
|
b4ba283f602b15a2ae53afaeb06ed11354879f76
|
ac2615f218d35bd0d8a24b06abb37ef77d321a72
|
refs/heads/main
| 2023-07-14T20:58:14.639187
| 2021-09-01T08:03:27
| 2021-09-01T08:03:27
| 401,979,352
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 13,985
|
py
|
import keyword
import re
from django.core.management.base import BaseCommand, CommandError
from django.db import DEFAULT_DB_ALIAS, connections
from django.db.models.constants import LOOKUP_SEP
class Command(BaseCommand):
help = "Introspects the database tables in the given database and outputs a Django model module."
requires_system_checks = False
stealth_options = ('table_name_filter',)
db_module = 'django.db'
def add_arguments(self, parser):
parser.add_argument(
'table', nargs='*', type=str,
help='Selects what tables or views should be introspected.',
)
parser.add_argument(
'--database', default=DEFAULT_DB_ALIAS,
help='Nominates a database to introspect. Defaults to using the "default" database.',
)
parser.add_argument(
'--include-partitions', action='store_true', help='Also output models for partition tables.',
)
parser.add_argument(
'--include-views', action='store_true', help='Also output models for database views.',
)
def handle(self, **options):
try:
for line in self.handle_inspection(options):
self.stdout.write(line)
except NotImplementedError:
raise CommandError("Database inspection isn't supported for the currently selected database backend.")
def handle_inspection(self, options):
connection = connections[options['database']]
# 'table_name_filter' is a stealth option
table_name_filter = options.get('table_name_filter')
def table2model(table_name):
return re.sub(r'[^a-zA-Z0-9]', '', table_name.title())
with connection.cursor() as cursor:
yield "# This is an auto-generated Django model module."
yield "# You'll have to do the following manually to clean this up:"
yield "# * Rearrange models' order"
yield "# * Make sure each model has one field with primary_key=True"
yield "# * Make sure each ForeignKey and OneToOneField has `on_delete` set to the desired behavior"
yield (
"# * Remove `managed = False` lines if you wish to allow "
"Django to create, modify, and delete the table"
)
yield "# Feel free to rename the models, but don't rename db_table values or field names."
yield 'from %s import models' % self.db_module
known_models = []
table_info = connection.introspection.get_table_list(cursor)
# Determine types of tables and/or views to be introspected.
types = {'t'}
if options['include_partitions']:
types.add('p')
if options['include_views']:
types.add('v')
for table_name in (options['table'] or sorted(info.name for info in table_info if info.type in types)):
if table_name_filter is not None and callable(table_name_filter):
if not table_name_filter(table_name):
continue
try:
try:
relations = connection.introspection.get_relations(cursor, table_name)
except NotImplementedError:
relations = {}
try:
constraints = connection.introspection.get_constraints(cursor, table_name)
except NotImplementedError:
constraints = {}
primary_key_column = connection.introspection.get_primary_key_column(cursor, table_name)
unique_columns = [
c['columns'][0] for c in constraints.values()
if c['unique'] and len(c['columns']) == 1
]
table_description = connection.introspection.get_table_description(cursor, table_name)
except Exception as e:
yield "# Unable to inspect table '%s'" % table_name
yield "# The error was: %s" % e
continue
yield ''
yield ''
yield 'class %s(models.Model):' % table2model(table_name)
known_models.append(table2model(table_name))
used_column_names = [] # Holds column names used in the table so far
column_to_field_name = {} # Maps column names to names of model fields
for row in table_description:
comment_notes = [] # Holds Field notes, to be displayed in a Python comment.
extra_params = {} # Holds Field parameters such as 'db_column'.
column_name = row.name
is_relation = column_name in relations
att_name, params, notes = self.normalize_col_name(
column_name, used_column_names, is_relation)
extra_params.update(params)
comment_notes.extend(notes)
used_column_names.append(att_name)
column_to_field_name[column_name] = att_name
# Add primary_key and unique, if necessary.
if column_name == primary_key_column:
extra_params['primary_key'] = True
elif column_name in unique_columns:
extra_params['unique'] = True
if is_relation:
if extra_params.pop('unique', False) or extra_params.get('primary_key'):
rel_type = 'OneToOneField'
else:
rel_type = 'ForeignKey'
rel_to = (
"self" if relations[column_name][1] == table_name
else table2model(relations[column_name][1])
)
if rel_to in known_models:
field_type = '%s(%s' % (rel_type, rel_to)
else:
field_type = "%s('%s'" % (rel_type, rel_to)
else:
# Calling `get_field_type` to get the field type string and any
# additional parameters and notes.
field_type, field_params, field_notes = self.get_field_type(connection, table_name, row)
extra_params.update(field_params)
comment_notes.extend(field_notes)
field_type += '('
# Don't output 'id = meta.AutoField(primary_key=True)', because
# that's assumed if it doesn't exist.
if att_name == 'id' and extra_params == {'primary_key': True}:
if field_type == 'AutoField(':
continue
elif field_type == 'IntegerField(' and not connection.features.can_introspect_autofield:
comment_notes.append('AutoField?')
# Add 'null' and 'blank', if the 'null_ok' flag was present in the
# table description.
if row.null_ok: # If it's NULL...
extra_params['blank'] = True
extra_params['null'] = True
field_desc = '%s = %s%s' % (
att_name,
# Custom fields will have a dotted path
'' if '.' in field_type else 'models.',
field_type,
)
if field_type.startswith(('ForeignKey(', 'OneToOneField(')):
field_desc += ', models.DO_NOTHING'
if extra_params:
if not field_desc.endswith('('):
field_desc += ', '
field_desc += ', '.join('%s=%r' % (k, v) for k, v in extra_params.items())
field_desc += ')'
if comment_notes:
field_desc += ' # ' + ' '.join(comment_notes)
yield ' %s' % field_desc
is_view = any(info.name == table_name and info.type == 'v' for info in table_info)
is_partition = any(info.name == table_name and info.type == 'p' for info in table_info)
yield from self.get_meta(table_name, constraints, column_to_field_name, is_view, is_partition)
def normalize_col_name(self, col_name, used_column_names, is_relation):
"""
Modify the column name to make it Python-compatible as a field name
"""
field_params = {}
field_notes = []
new_name = col_name.lower()
if new_name != col_name:
field_notes.append('Field name made lowercase.')
if is_relation:
if new_name.endswith('_id'):
new_name = new_name[:-3]
else:
field_params['db_column'] = col_name
new_name, num_repl = re.subn(r'\W', '_', new_name)
if num_repl > 0:
field_notes.append('Field renamed to remove unsuitable characters.')
if new_name.find(LOOKUP_SEP) >= 0:
while new_name.find(LOOKUP_SEP) >= 0:
new_name = new_name.replace(LOOKUP_SEP, '_')
if col_name.lower().find(LOOKUP_SEP) >= 0:
# Only add the comment if the double underscore was in the original name
field_notes.append("Field renamed because it contained more than one '_' in a row.")
if new_name.startswith('_'):
new_name = 'field%s' % new_name
field_notes.append("Field renamed because it started with '_'.")
if new_name.endswith('_'):
new_name = '%sfield' % new_name
field_notes.append("Field renamed because it ended with '_'.")
if keyword.iskeyword(new_name):
new_name += '_field'
field_notes.append('Field renamed because it was a Python reserved word.')
if new_name[0].isdigit():
new_name = 'number_%s' % new_name
field_notes.append("Field renamed because it wasn't a valid Python identifier.")
if new_name in used_column_names:
num = 0
while '%s_%d' % (new_name, num) in used_column_names:
num += 1
new_name = '%s_%d' % (new_name, num)
field_notes.append('Field renamed because of name conflict.')
if col_name != new_name and field_notes:
field_params['db_column'] = col_name
return new_name, field_params, field_notes
def get_field_type(self, connection, table_name, row):
"""
Given the database connection, the table name, and the cursor row
description, this routine will return the given field type name, as
well as any additional keyword parameters and notes for the field.
"""
field_params = {}
field_notes = []
try:
field_type = connection.introspection.get_field_type(row.type_code, row)
except KeyError:
field_type = 'TextField'
field_notes.append('This field type is a guess.')
# Add max_length for all CharFields.
if field_type == 'CharField' and row.internal_size:
field_params['max_length'] = int(row.internal_size)
if field_type == 'DecimalField':
if row.precision is None or row.scale is None:
field_notes.append(
'max_digits and decimal_places have been guessed, as this '
'database handles decimal fields as float')
field_params['max_digits'] = row.precision if row.precision is not None else 10
field_params['decimal_places'] = row.scale if row.scale is not None else 5
else:
field_params['max_digits'] = row.precision
field_params['decimal_places'] = row.scale
return field_type, field_params, field_notes
def get_meta(self, table_name, constraints, column_to_field_name, is_view, is_partition):
"""
Return a sequence comprising the lines of code necessary
to construct the inner Meta class for the model corresponding
to the given database table name.
"""
unique_together = []
has_unsupported_constraint = False
for params in constraints.values():
if params['unique']:
columns = params['columns']
if None in columns:
has_unsupported_constraint = True
columns = [x for x in columns if x is not None]
if len(columns) > 1:
unique_together.append(str(tuple(column_to_field_name[c] for c in columns)))
if is_view:
managed_comment = " # Created from a view. Don't remove."
elif is_partition:
managed_comment = " # Created from a partition. Don't remove."
else:
managed_comment = ''
meta = ['']
if has_unsupported_constraint:
meta.append(' # A unique constraint could not be introspected.')
meta += [
' class Meta:',
' managed = False%s' % managed_comment,
' db_table = %r' % table_name
]
if unique_together:
tup = '(' + ', '.join(unique_together) + ',)'
meta += [" unique_together = %s" % tup]
return meta
|
[
"88698739+Sankalpa830@users.noreply.github.com"
] |
88698739+Sankalpa830@users.noreply.github.com
|
d8ebe9f96b8861612109f607cda8efcac6488540
|
6f9cb82b54a537e8d328c91527f14e9b1a77a0a2
|
/pg_xlsx_pg/xlsx2db.py
|
3daeed8aaf85eb4cb81e5b0e4a6fc97d7a4a5532
|
[] |
no_license
|
godsfear/py
|
c22f93581a900436fe7ce08829af14822dd228a4
|
b0510a729342953181df2bc69f2da5d2cca959bf
|
refs/heads/master
| 2020-05-27T19:52:50.119385
| 2019-10-17T09:25:06
| 2019-10-17T09:25:06
| 188,767,580
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,537
|
py
|
#!/python
from openpyxl import load_workbook
import sys
import os
import json
import re
import time
import progressbar
import glob
from db_api import *
if __name__ == '__main__':
fname = 'xlsx2db.json'
if len(sys.argv) > 1 and not ((sys.argv[1] == "") or (sys.argv[1] is None)):
fname = sys.argv[1]
if os.path.exists(fname):
with open(fname,'r',encoding='utf-8') as f:
try:
cfg = json.load(f)
except IOError:
print ("Could not read file:",fname)
sys.exit(1)
else:
print("File not exist:",fname)
sys.exit(1)
conn = connect(cfg["destination"])
if cfg["execute"] != "" and cfg["execute"] != None:
if os.path.exists(cfg["execute"]):
with open(cfg["execute"],'r',encoding='utf-8') as f:
try:
query(conn,f.read())
except IOError:
print ("Could not read file:",cfg["execute"])
sys.exit(1)
else:
print("File not exist:",cfg["execute"])
sys.exit(1)
k = 1
with progressbar.ProgressBar(max_value=len(cfg["files"])) as bar:
for xfile in (cfg["files"]):
for fn in glob.glob(xfile["name"]):
wb = load_workbook(fn)
j = 0
for row in (wb[xfile["query"]["page"]]):
j += 1
if j < xfile["begin_row"]:
continue
val = re.split(',',xfile["query"]["values"])
typ = re.split(',',xfile["query"]["type"])
i = 0
values = ""
for v in (val):
z = str(row[int(v) - 1].value)
if typ[i] == 'date':
z = z.split(" ")[0]
z.replace(",","\\,")
z.replace('"','\\"')
z.replace("'","\\'")
if typ[i] == 'varchar' or typ[i] == 'date':
z = "'" + z + "'"
z = z + "::" + typ[i]
if values == "":
values = z
else :
values += "," + z
i += 1
insert(conn,xfile["query"]["table"],xfile["query"]["fields"],values)
bar.update(k)
k += 1
if conn is not None:
conn.close()
|
[
"44734149+godsfear@users.noreply.github.com"
] |
44734149+godsfear@users.noreply.github.com
|
e5486b8d06884487a9f8627990bbdd51bc3ce273
|
86813bf514f3e0257f92207f40a68443f08ee44b
|
/1047 删除字符串中的所有相邻重复项/1047 删除字符串中的所有相邻重复项.py
|
bf028b0fd7a93d4a5ee6c4ef9b7c9d614fc710aa
|
[] |
no_license
|
Aurora-yuan/Leetcode_Python3
|
4ce56679b48862c87addc8cd870cdd525c9d926c
|
720bb530850febc2aa67a56a7a0b3a85ab37f415
|
refs/heads/master
| 2021-07-12T13:23:19.399155
| 2020-10-21T03:14:36
| 2020-10-21T03:14:36
| 212,998,500
| 4
| 1
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,116
|
py
|
#label: stack difficulty: easy
"""
思路一：
直接循环，空间复杂度低，但时间复杂度高
"""
class Solution(object):
def removeDuplicates(self, S):
"""
:type S: str
:rtype: str
"""
flag = 1
while 1:
original_l = len(S)
i = 0
while i < len(S) - 1:
if i >= 0 and S[i] == S[i + 1]:
S = S[:i] + S[i + 2:]
i -= 2
i += 1
if original_l == len(S):
return S
“”“
思路二：
我们可以用字符串自带的替换函数，由于字符串仅包含小写字母，因此只有 26 种不同的重复项。
将 aa 到 zz 的 26 种重复项放入集合中；
遍历这 26 种重复项，并用字符串的替换函数把重复项替换成空串。
注意，在进行过一次替换之后，可能会出现新的重复项。例如对于字符串 abbaca，如果替换了重复项 bb，字符串会变为 aaca，出现了新的重复项 aa。
因此，上面的过程需要背重复若干次，直到字符串在一整轮替换过程后保持不变（即长度不变）为止。
”“”
from string import ascii_lowercase
class Solution:
def removeDuplicates(self, S: str) -> str:
# generate 26 possible duplicates
duplicates = {2 * ch for ch in ascii_lowercase}
prev_length = -1
while prev_length != len(S):
prev_length = len(S)
for d in duplicates:
S = S.replace(d, '')
return S
“”“
思路三：
栈。我们可以用栈来维护没有重复项的字母序列：
若当前的字母和栈顶的字母相同，则弹出栈顶的字母；
若当前的字母和栈顶的字母不同，则放入当前的字母。
”“”
class Solution:
def removeDuplicates(self, S: str) -> str:
output = []
for ch in S:
if output and ch == output[-1]:
output.pop()
else:
output.append(ch)
return ''.join(output)
|
[
"noreply@github.com"
] |
Aurora-yuan.noreply@github.com
|
cb2a744a2359e92619b1478436292d694371171c
|
7df76ba9ce259073358b8a6478bb641ea6e50509
|
/src/code/attacks/evasion.py
|
30f16677e2b8ab4cf8bc3bcdbf1d524ffe57ea44
|
[] |
no_license
|
SONG-WONHO/attack_correlation2
|
ed261daef89fbe3c211a714948dadc6aeadaf682
|
142e229fa28880ca8391749dcc6ed2491fe0ce96
|
refs/heads/master
| 2023-07-06T00:41:54.786069
| 2021-08-12T10:43:49
| 2021-08-12T10:43:49
| 389,508,920
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 30,237
|
py
|
import torch
import numpy as np
import warnings
from tqdm import tqdm
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
warnings.filterwarnings("ignore")
def clip_eta(eta, norm, eps):
"""
PyTorch implementation of the clip_eta in utils_tf.
:param eta: Tensor
:param norm: np.inf, 1, or 2
:param eps: float
"""
if norm not in [np.inf, 1, 2]:
raise ValueError("norm must be np.inf, 1, or 2.")
avoid_zero_div = torch.tensor(1e-12, dtype=eta.dtype, device=eta.device)
reduc_ind = list(range(1, len(eta.size())))
if norm == np.inf:
eta = torch.clamp(eta, -eps, eps)
else:
if norm == 1:
raise NotImplementedError("L1 clip is not implemented.")
norm = torch.max(
avoid_zero_div,
torch.sum(torch.abs(eta), dim=reduc_ind, keepdim=True)
)
elif norm == 2:
norm = torch.sqrt(
torch.max(
avoid_zero_div,
torch.sum(eta ** 2, dim=reduc_ind, keepdim=True)
)
)
factor = torch.min(
torch.tensor(1.0, dtype=eta.dtype, device=eta.device), eps / norm
)
eta *= factor
return eta
def optimize_linear(grad, eps, norm=np.inf):
"""
Solves for the optimal input to a linear function under a norm constraint.
Optimal_perturbation = argmax_{eta, ||eta||_{norm} < eps} dot(eta, grad)
:param grad: Tensor, shape (N, d_1, ...). Batch of gradients
:param eps: float. Scalar specifying size of constraint region
:param norm: np.inf, 1, or 2. Order of norm constraint.
:returns: Tensor, shape (N, d_1, ...). Optimal perturbation
"""
red_ind = list(range(1, len(grad.size())))
avoid_zero_div = torch.tensor(1e-12, dtype=grad.dtype, device=grad.device)
if norm == np.inf:
# Take sign of gradient
optimal_perturbation = torch.sign(grad)
elif norm == 1:
abs_grad = torch.abs(grad)
sign = torch.sign(grad)
red_ind = list(range(1, len(grad.size())))
abs_grad = torch.abs(grad)
ori_shape = [1] * len(grad.size())
ori_shape[0] = grad.size(0)
max_abs_grad, _ = torch.max(abs_grad.view(grad.size(0), -1), 1)
max_mask = abs_grad.eq(max_abs_grad.view(ori_shape)).to(torch.float)
num_ties = max_mask
for red_scalar in red_ind:
num_ties = torch.sum(num_ties, red_scalar, keepdim=True)
optimal_perturbation = sign * max_mask / num_ties
# TODO integrate below to a test file
# check that the optimal perturbations have been correctly computed
opt_pert_norm = optimal_perturbation.abs().sum(dim=red_ind)
assert torch.all(opt_pert_norm == torch.ones_like(opt_pert_norm))
elif norm == 2:
square = torch.max(
avoid_zero_div,
torch.sum(grad ** 2, red_ind, keepdim=True)
)
optimal_perturbation = grad / torch.sqrt(square)
# TODO integrate below to a test file
# check that the optimal perturbations have been correctly computed
opt_pert_norm = (
optimal_perturbation.pow(2).sum(dim=red_ind, keepdim=True).sqrt()
)
one_mask = (square <= avoid_zero_div).to(
torch.float) * opt_pert_norm + (
square > avoid_zero_div
).to(torch.float)
assert torch.allclose(opt_pert_norm, one_mask, rtol=1e-05, atol=1e-08)
else:
raise NotImplementedError(
"Only L-inf, L1 and L2 norms are " "currently implemented."
)
# Scale perturbation to be the solution for the norm=eps rather than
# norm=1 problem
scaled_perturbation = eps * optimal_perturbation
return scaled_perturbation
def fast_gradient_method(model, x, eps=0.3, norm=np.inf,
clip_min=None, clip_max=None, y=None, targeted=False,
sanity_checks=False):
"""
PyTorch implementation of the Fast Gradient Method.
:param model: a callable that takes an input tensor and returns the model logits.
:param x: input tensor.
:param eps: epsilon (input variation parameter)
:param norm: Order of the norm (mimics NumPy). Possible values: np.inf, 1 or 2.
:param clip_min: (optional) float. Minimum float value for adversarial example components.
:param clip_max: (optional) float. Maximum float value for adversarial example components.
:param y: (optional) Tensor with true labels. If targeted is true, then provide the
target label. Otherwise, only provide this parameter if you'd like to use true
labels when crafting adversarial samples. Otherwise, model predictions are used
as labels to avoid the "label leaking" effect. Default is None.
:param targeted: (optional) bool. Is the attack targeted or untargeted?
Untargeted, the default, will try to make the label incorrect.
Targeted will instead try to move in the direction of being more like y.
:param sanity_checks: bool, if True, include asserts (Turn them off to use less runtime /
memory or for unit tests that intentionally pass strange input)
:return: a tensor for the adversarial example
"""
asserts = []
# If a data range was specified, check that the input was in that range
if clip_min is not None:
assert_ge = torch.all(
torch.ge(x, torch.tensor(clip_min, device=x.device, dtype=x.dtype)))
asserts.append(assert_ge)
if clip_max is not None:
assert_le = torch.all(
torch.le(x, torch.tensor(clip_max, device=x.device, dtype=x.dtype)))
asserts.append(assert_le)
x = x.clone().detach().to(torch.float).requires_grad_(True)
if y is None:
# Using model predictions as ground truth to avoid label leaking
_, y = torch.max(model(x)[0], 1)
# Compute loss
loss_fn = torch.nn.CrossEntropyLoss()
loss = loss_fn(model(x)[0], y)
# If attack is targeted, minimize loss of target label rather than maximize loss of correct label
if targeted:
loss = -loss
# Define gradient of loss wrt input
loss.backward()
optimal_perturbation = optimize_linear(x.grad, eps, norm)
# Add perturbation to original example to obtain adversarial example
adv_x = x + optimal_perturbation
# If clipping is needed, reset all values outside of [clip_min, clip_max]
if (clip_min is not None) or (clip_max is not None):
if clip_min is None or clip_max is None:
raise ValueError(
"One of clip_min and clip_max is None but we don't currently support one-sided clipping")
adv_x = torch.clamp(adv_x, clip_min, clip_max)
if sanity_checks:
assert np.all(asserts)
return adv_x
def basic_iterative_method(
model,
x,
y=None,
targeted=False,
eps=0.15,
eps_iter=0.01,
n_iter=50,
clip_max=None,
clip_min=None):
x = x.clone().detach().to(torch.float).requires_grad_(True)
if y is None:
# Using model predictions as ground truth to avoid label leaking
_, y = torch.max(model(x)[0], 1)
eta = torch.zeros(x.shape).to(x.device)
for i in range(n_iter):
out = model(x + eta)[0]
loss = F.cross_entropy(out, y)
if targeted:
loss = -loss
loss.backward()
eta += eps_iter * torch.sign(x.grad.data)
eta.clamp_(-eps, eps)
x.grad.data.zero_()
x_adv = x + eta
if (clip_min is not None) or (clip_max is not None):
if clip_min is None or clip_max is None:
raise ValueError(
"One of clip_min and clip_max is None but we don't currently support one-sided clipping")
x_adv.clamp_(clip_min, clip_max)
return x_adv.detach()
INF = float("inf")
def carlini_wagner_l2(
model_fn,
x,
n_classes,
y=None,
targeted=False,
lr=5e-3,
confidence=0,
clip_min=0,
clip_max=1,
initial_const=1e-2,
binary_search_steps=5,
max_iterations=1000,
):
"""
This attack was originally proposed by Carlini and Wagner. It is an
iterative attack that finds adversarial examples on many defenses that
are robust to other attacks.
Paper link: https://arxiv.org/abs/1608.04644
At a high level, this attack is an iterative attack using Adam and
a specially-chosen loss function to find adversarial examples with
lower distortion than other attacks. This comes at the cost of speed,
as this attack is often much slower than others.
:param model_fn: a callable that takes an input tensor and returns
the model logits. The logits should be a tensor of shape
(n_examples, n_classes).
:param x: input tensor of shape (n_examples, ...), where ... can
be any arbitrary dimension that is compatible with
model_fn.
:param n_classes: the number of classes.
:param y: (optional) Tensor with true labels. If targeted is true,
then provide the target label. Otherwise, only provide
this parameter if you'd like to use true labels when
crafting adversarial samples. Otherwise, model predictions
are used as labels to avoid the "label leaking" effect
(explained in this paper:
https://arxiv.org/abs/1611.01236). If provide y, it
should be a 1D tensor of shape (n_examples, ).
Default is None.
:param targeted: (optional) bool. Is the attack targeted or
untargeted? Untargeted, the default, will try to make the
label incorrect. Targeted will instead try to move in the
direction of being more like y.
:param lr: (optional) float. The learning rate for the attack
algorithm. Default is 5e-3.
:param confidence: (optional) float. Confidence of adversarial
examples: higher produces examples with larger l2
distortion, but more strongly classified as adversarial.
Default is 0.
:param clip_min: (optional) float. Minimum float value for
adversarial example components. Default is 0.
:param clip_max: (optional) float. Maximum float value for
adversarial example components. Default is 1.
:param initial_const: The initial tradeoff-constant to use to tune the
relative importance of size of the perturbation and
confidence of classification. If binary_search_steps is
large, the initial constant is not important. A smaller
value of this constant gives lower distortion results.
Default is 1e-2.
:param binary_search_steps: (optional) int. The number of times we
perform binary search to find the optimal tradeoff-constant
between norm of the perturbation and confidence of the
classification. Default is 5.
:param max_iterations: (optional) int. The maximum number of
iterations. Setting this to a larger value will produce
lower distortion results. Using only a few iterations
requires a larger learning rate, and will produce larger
distortion results. Default is 1000.
"""
def compare(pred, label, is_logits=False):
"""
A helper function to compare prediction against a label.
Returns true if the attack is considered successful.
:param pred: can be either a 1D tensor of logits or a predicted
class (int).
:param label: int. A label to compare against.
:param is_logits: (optional) bool. If True, treat pred as an
array of logits. Default is False.
"""
# Convert logits to predicted class if necessary
if is_logits:
pred_copy = pred.clone().detach()
pred_copy[label] += -confidence if targeted else confidence
pred = torch.argmax(pred_copy)
return pred == label if targeted else pred != label
def arctanh(x):
return 0.5 * torch.log((1 + x) / (1 - x))
if y is None:
# Using model predictions as ground truth to avoid label leaking
pred = model_fn(x)[0]
y = torch.argmax(pred, 1)
# Initialize some values needed for binary search on const
lower_bound = [0.0] * len(x)
upper_bound = [1e10] * len(x)
const = x.new_ones(len(x), 1) * initial_const
o_bestl2 = [INF] * len(x)
o_bestscore = [-1.0] * len(x)
x = torch.clamp(x, clip_min, clip_max)
ox = x.clone().detach() # save the original x
o_bestattack = x.clone().detach()
# Map images into the tanh-space
x = (x - clip_min) / (clip_max - clip_min)
x = torch.clamp(x, 0, 1)
x = x * 2 - 1
x = arctanh(x * 0.999999)
# Prepare some variables
modifier = torch.zeros_like(x, requires_grad=True).to(x.device)
y_onehot = torch.nn.functional.one_hot(y, n_classes).to(torch.float)
# Define loss functions and optimizer
f_fn = lambda real, other, targeted: torch.max(
((other - real) if targeted else (real - other)) + confidence,
torch.tensor(0.0).to(real.device),
)
l2dist_fn = lambda x, y: torch.pow(x - y, 2).sum(list(range(len(x.size())))[1:])
optimizer = torch.optim.Adam([modifier], lr=lr)
# Outer loop performing binary search on const
for outer_step in range(binary_search_steps):
# Initialize some values needed for the inner loop
bestl2 = [INF] * len(x)
bestscore = [-1.0] * len(x)
# Inner loop performing attack iterations
for i in tqdm(range(max_iterations), leave=False):
# One attack step
new_x = (torch.tanh(modifier + x) + 1) / 2
new_x = new_x * (clip_max - clip_min) + clip_min
logits = model_fn(new_x)[0]
real = torch.sum(y_onehot * logits, 1)
other, _ = torch.max((1 - y_onehot) * logits - y_onehot * 1e4, 1)
optimizer.zero_grad()
f = f_fn(real, other, targeted)
l2 = l2dist_fn(new_x, ox)
loss = (const * f + l2).sum()
loss.backward()
optimizer.step()
# Update best results
for n, (l2_n, logits_n, new_x_n) in enumerate(zip(l2, logits, new_x)):
y_n = y[n]
succeeded = compare(logits_n, y_n, is_logits=True)
if l2_n < o_bestl2[n] and succeeded:
pred_n = torch.argmax(logits_n)
o_bestl2[n] = l2_n
o_bestscore[n] = pred_n
o_bestattack[n] = new_x_n
# l2_n < o_bestl2[n] implies l2_n < bestl2[n] so we modify inner loop variables too
bestl2[n] = l2_n
bestscore[n] = pred_n
elif l2_n < bestl2[n] and succeeded:
bestl2[n] = l2_n
bestscore[n] = torch.argmax(logits_n)
# Binary search step
for n in range(len(x)):
y_n = y[n]
if compare(bestscore[n], y_n) and bestscore[n] != -1:
# Success, divide const by two
upper_bound[n] = min(upper_bound[n], const[n])
if upper_bound[n] < 1e9:
const[n] = (lower_bound[n] + upper_bound[n]) / 2
else:
# Failure, either multiply by 10 if no solution found yet
# or do binary search with the known upper bound
lower_bound[n] = max(lower_bound[n], const[n])
if upper_bound[n] < 1e9:
const[n] = (lower_bound[n] + upper_bound[n]) / 2
else:
const[n] *= 10
return o_bestattack.detach()
def projected_gradient_descent(
model_fn,
x,
eps,
eps_iter,
nb_iter,
norm,
clip_min=None,
clip_max=None,
y=None,
targeted=False,
rand_init=True,
rand_minmax=None,
sanity_checks=True,
):
"""
This class implements either the Basic Iterative Method
(Kurakin et al. 2016) when rand_init is set to False. or the
Madry et al. (2017) method if rand_init is set to True.
Paper link (Kurakin et al. 2016): https://arxiv.org/pdf/1607.02533.pdf
Paper link (Madry et al. 2017): https://arxiv.org/pdf/1706.06083.pdf
:param model_fn: a callable that takes an input tensor and returns the model logits.
:param x: input tensor.
:param eps: epsilon (input variation parameter); see https://arxiv.org/abs/1412.6572.
:param eps_iter: step size for each attack iteration
:param nb_iter: Number of attack iterations.
:param norm: Order of the norm (mimics NumPy). Possible values: np.inf, 1 or 2.
:param clip_min: (optional) float. Minimum float value for adversarial example components.
:param clip_max: (optional) float. Maximum float value for adversarial example components.
:param y: (optional) Tensor with true labels. If targeted is true, then provide the
target label. Otherwise, only provide this parameter if you'd like to use true
labels when crafting adversarial samples. Otherwise, model predictions are used
as labels to avoid the "label leaking" effect (explained in this paper:
https://arxiv.org/abs/1611.01236). Default is None.
:param targeted: (optional) bool. Is the attack targeted or untargeted?
Untargeted, the default, will try to make the label incorrect.
Targeted will instead try to move in the direction of being more like y.
:param rand_init: (optional) bool. Whether to start the attack from a randomly perturbed x.
:param rand_minmax: (optional) bool. Support of the continuous uniform distribution from
which the random perturbation on x was drawn. Effective only when rand_init is
True. Default equals to eps.
:param sanity_checks: bool, if True, include asserts (Turn them off to use less runtime /
memory or for unit tests that intentionally pass strange input)
:return: a tensor for the adversarial example
"""
if norm == 1:
raise NotImplementedError(
"It's not clear that FGM is a good inner loop"
" step for PGD when norm=1, because norm=1 FGM "
" changes only one pixel at a time. We need "
" to rigorously test a strong norm=1 PGD "
"before enabling this feature."
)
if norm not in [np.inf, 2]:
raise ValueError("Norm order must be either np.inf or 2.")
if eps < 0:
raise ValueError(
"eps must be greater than or equal to 0, got {} instead".format(eps)
)
if eps == 0:
return x
if eps_iter < 0:
raise ValueError(
"eps_iter must be greater than or equal to 0, got {} instead".format(
eps_iter
)
)
if eps_iter == 0:
return x
assert eps_iter <= eps, (eps_iter, eps)
if clip_min is not None and clip_max is not None:
if clip_min > clip_max:
raise ValueError(
"clip_min must be less than or equal to clip_max, got clip_min={} and clip_max={}".format(
clip_min, clip_max
)
)
asserts = []
# If a data range was specified, check that the input was in that range
if clip_min is not None:
assert_ge = torch.all(
torch.ge(x, torch.tensor(clip_min, device=x.device, dtype=x.dtype))
)
asserts.append(assert_ge)
if clip_max is not None:
assert_le = torch.all(
torch.le(x, torch.tensor(clip_max, device=x.device, dtype=x.dtype))
)
asserts.append(assert_le)
# Initialize loop variables
if rand_init:
if rand_minmax is None:
rand_minmax = eps
eta = torch.zeros_like(x).uniform_(-rand_minmax, rand_minmax)
else:
eta = torch.zeros_like(x)
# Clip eta
eta = clip_eta(eta, norm, eps)
adv_x = x + eta
if clip_min is not None or clip_max is not None:
adv_x = torch.clamp(adv_x, clip_min, clip_max)
if y is None:
# Using model predictions as ground truth to avoid label leaking
_, y = torch.max(model_fn(x)[0], 1)
i = 0
while i < nb_iter:
adv_x = fast_gradient_method(
model_fn,
adv_x,
eps_iter,
norm,
clip_min=clip_min,
clip_max=clip_max,
y=y,
targeted=targeted,
)
# Clipping perturbation eta to norm norm ball
eta = adv_x - x
eta = clip_eta(eta, norm, eps)
adv_x = x + eta
# Redo the clipping.
# FGM already did it, but subtracting and re-adding eta can add some
# small numerical error.
if clip_min is not None or clip_max is not None:
adv_x = torch.clamp(adv_x, clip_min, clip_max)
i += 1
asserts.append(eps_iter <= eps)
if norm == np.inf and clip_min is not None:
# TODO necessary to cast clip_min and clip_max to x.dtype?
asserts.append(eps + clip_min <= clip_max)
if sanity_checks:
assert np.all(asserts)
return adv_x
def spsa(
model_fn,
x,
eps,
nb_iter,
norm=np.inf,
clip_min=-np.inf,
clip_max=np.inf,
y=None,
targeted=False,
early_stop_loss_threshold=None,
learning_rate=0.01,
delta=0.01,
spsa_samples=128,
spsa_iters=1,
is_debug=False,
sanity_checks=True,
):
"""
This implements the SPSA adversary, as in https://arxiv.org/abs/1802.05666
(Uesato et al. 2018). SPSA is a gradient-free optimization method, which is useful when
the model is non-differentiable, or more generally, the gradients do not point in useful
directions.
:param model_fn: A callable that takes an input tensor and returns the model logits.
:param x: Input tensor.
:param eps: The size of the maximum perturbation, measured in the L-infinity norm.
:param nb_iter: The number of optimization steps.
:param norm: Order of the norm (mimics NumPy). Possible values: np.inf, 1 or 2.
:param clip_min: If specified, the minimum input value.
:param clip_max: If specified, the maximum input value.
:param y: (optional) Tensor with true labels. If targeted is true, then provide the
target label. Otherwise, only provide this parameter if you'd like to use true
labels when crafting adversarial samples. Otherwise, model predictions are used
as labels to avoid the "label leaking" effect (explained in this paper:
https://arxiv.org/abs/1611.01236). Default is None.
:param targeted: (optional) bool. Is the attack targeted or untargeted? Untargeted, the
default, will try to make the label incorrect. Targeted will instead try to
move in the direction of being more like y.
:param early_stop_loss_threshold: A float or None. If specified, the attack will end as
soon as the loss is below `early_stop_loss_threshold`.
:param learning_rate: Learning rate of ADAM optimizer.
:param delta: Perturbation size used for SPSA approximation.
:param spsa_samples: Number of inputs to evaluate at a single time. The true batch size
(the number of evaluated inputs for each update) is `spsa_samples *
spsa_iters`
:param spsa_iters: Number of model evaluations before performing an update, where each
evaluation is on `spsa_samples` different inputs.
:param is_debug: If True, print the adversarial loss after each update.
:param sanity_checks: bool, if True, include asserts (Turn them off to use less runtime /
memory or for unit tests that intentionally pass strange input)
:return: a tensor for the adversarial example
"""
if y is not None and len(x) != len(y):
raise ValueError(
"number of inputs {} is different from number of labels {}".format(
len(x), len(y)
)
)
if y is None:
y = torch.argmax(model_fn(x)[0], dim=1)
# The rest of the function doesn't support batches of size greater than 1,
# so if the batch is bigger we split it up.
if len(x) != 1:
adv_x = []
for x_single, y_single in tqdm(zip(x, y), leave=False, total=len(x)):
adv_x_single = spsa(
model_fn=model_fn,
x=x_single.unsqueeze(0),
eps=eps,
nb_iter=nb_iter,
norm=norm,
clip_min=clip_min,
clip_max=clip_max,
y=y_single.unsqueeze(0),
targeted=targeted,
early_stop_loss_threshold=early_stop_loss_threshold,
learning_rate=learning_rate,
delta=delta,
spsa_samples=spsa_samples,
spsa_iters=spsa_iters,
is_debug=is_debug,
sanity_checks=sanity_checks,
)
adv_x.append(adv_x_single)
return torch.cat(adv_x)
if eps < 0:
raise ValueError(
"eps must be greater than or equal to 0, got {} instead".format(eps)
)
if eps == 0:
return x
if clip_min is not None and clip_max is not None:
if clip_min > clip_max:
raise ValueError(
"clip_min must be less than or equal to clip_max, got clip_min={} and clip_max={}".format(
clip_min, clip_max
)
)
asserts = []
# If a data range was specified, check that the input was in that range
asserts.append(torch.all(x >= clip_min))
asserts.append(torch.all(x <= clip_max))
if is_debug:
print("Starting SPSA attack with eps = {}".format(eps))
perturbation = (torch.rand_like(x) * 2 - 1) * eps
_project_perturbation(perturbation, norm, eps, x, clip_min, clip_max)
optimizer = optim.Adam([perturbation], lr=learning_rate)
for i in range(nb_iter):
def loss_fn(pert):
"""
Margin logit loss, with correct sign for targeted vs untargeted loss.
"""
logits = model_fn(x + pert)[0]
loss_multiplier = 1 if targeted else -1
return loss_multiplier * _margin_logit_loss(logits,
y.expand(len(pert)))
spsa_grad = _compute_spsa_gradient(
loss_fn, x, delta=delta, samples=spsa_samples, iters=spsa_iters
)
perturbation.grad = spsa_grad
optimizer.step()
_project_perturbation(perturbation, norm, eps, x, clip_min, clip_max)
loss = loss_fn(perturbation).item()
if is_debug:
print("Iteration {}: loss = {}".format(i, loss))
if early_stop_loss_threshold is not None and loss < early_stop_loss_threshold:
break
adv_x = torch.clamp((x + perturbation).detach(), clip_min, clip_max)
if norm == np.inf:
asserts.append(torch.all(torch.abs(adv_x - x) <= eps + 1e-6))
else:
asserts.append(
torch.all(
torch.abs(
torch.renorm(adv_x - x, p=norm, dim=0, maxnorm=eps) - (
adv_x - x)
)
< 1e-6
)
)
asserts.append(torch.all(adv_x >= clip_min))
asserts.append(torch.all(adv_x <= clip_max))
if sanity_checks:
assert np.all(asserts)
return adv_x
def _project_perturbation(
perturbation, norm, epsilon, input_image, clip_min=-np.inf,
clip_max=np.inf
):
"""
Project `perturbation` onto L-infinity ball of radius `epsilon`. Also project into
hypercube such that the resulting adversarial example is between clip_min and clip_max,
if applicable. This is an in-place operation.
"""
clipped_perturbation = clip_eta(perturbation, norm, epsilon)
new_image = torch.clamp(input_image + clipped_perturbation, clip_min,
clip_max)
perturbation.add_((new_image - input_image) - perturbation)
def _compute_spsa_gradient(loss_fn, x, delta, samples, iters):
"""
Approximately compute the gradient of `loss_fn` at `x` using SPSA with the
given parameters. The gradient is approximated by evaluating `iters` batches
of `samples` size each.
"""
assert len(x) == 1
num_dims = len(x.size())
x_batch = x.expand(samples, *([-1] * (num_dims - 1)))
grad_list = []
for i in range(iters):
delta_x = delta * torch.sign(torch.rand_like(x_batch) - 0.5)
delta_x = torch.cat([delta_x, -delta_x])
with torch.no_grad():
loss_vals = loss_fn(x + delta_x)
while len(loss_vals.size()) < num_dims:
loss_vals = loss_vals.unsqueeze(-1)
avg_grad = (
torch.mean(loss_vals * torch.sign(delta_x), dim=0,
keepdim=True) / delta
)
grad_list.append(avg_grad)
return torch.mean(torch.cat(grad_list), dim=0, keepdim=True)
def _margin_logit_loss(logits, labels):
"""
Computes difference between logits for `labels` and next highest logits.
The loss is high when `label` is unlikely (targeted by default).
"""
correct_logits = logits.gather(1, labels[:, None]).squeeze(1)
logit_indices = torch.arange(
logits.size()[1],
dtype=labels.dtype,
device=labels.device,
)[None, :].expand(labels.size()[0], -1)
incorrect_logits = torch.where(
logit_indices == labels[:, None],
torch.full_like(logits, float("-inf")),
logits,
)
max_incorrect_logits, _ = torch.max(incorrect_logits, 1)
return max_incorrect_logits - correct_logits
|
[
"win778500@gmail.com"
] |
win778500@gmail.com
|
a638cb48c3c3ae642ae77d0ee9745db81883ee2a
|
fcd4443abbf2638e1c13362f58b10a347a959af8
|
/trials/3pc.py
|
f706d3cdd9b982e766283c9ec548e5a23dfe8b93
|
[] |
no_license
|
Shariar076/atomic-commit
|
952ec46f1b81b727015401b6b13455b151ca4fbc
|
55e2bb5361a28f346e6ecac21c47bc3647afd371
|
refs/heads/master
| 2023-08-19T23:03:03.087909
| 2021-10-06T11:28:34
| 2021-10-06T11:28:34
| 356,931,998
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 879
|
py
|
from server import Server
from client import Client
import sys, getopt
from threading import Thread
from time import sleep
def get_host_port(argv):
host = None
port = None
try:
opts, args = getopt.getopt(argv, "h:p:", ["host=", "port="])
except getopt.GetoptError:
print('test.py -h <host> -p <port>')
sys.exit(2)
for opt, arg in opts:
if opt in ("-h", "--host"):
host = str(arg)
elif opt in ("-p", "--port"):
port = int(arg)
print(f"host: {host}")
print(f"port: {port}")
return host, port
if __name__ == "__main__":
host, port = get_host_port(sys.argv[1:])
server = Server(host, port)
server_thread = Thread(target=server.start_server)
server_thread.start()
client = Client()
client.connect_server(host, port)
sleep(1)
print(server.clients)
|
[
"shariar.kabir@cellosco.pe"
] |
shariar.kabir@cellosco.pe
|
833e7120f03a37b0a7cc7b01c1f37f7b23e29be5
|
299d0b949676470f542cd2d0ad7383a5ede00c30
|
/Networks/qnetwork.py
|
f7e7d45bac1a006de4ba52294592d55dfefec15a
|
[] |
no_license
|
Morgan-Griffiths/Udacity_Navigation
|
0987787d7f44cd76609b16f085a5168a35082599
|
a871b48111b5416aa3d7246d7db696d39ce5fcf0
|
refs/heads/master
| 2023-08-24T03:55:19.114784
| 2022-01-24T20:47:28
| 2022-01-24T20:47:28
| 188,105,824
| 0
| 0
| null | 2023-07-22T06:27:25
| 2019-05-22T20:03:30
|
Jupyter Notebook
|
UTF-8
|
Python
| false
| false
| 612
|
py
|
import torch
import torch.nn as nn
import torch.nn.functional as F
"""
QNetwork for function aproximation.
"""
class QNetwork(nn.Module):
def __init__(self,action_space,state_space,seed):
super(QNetwork,self).__init__()
self.action_space = action_space
self.state_space = state_space
self.seed = torch.manual_seed(seed)
self.fc1 = nn.Linear(state_space,64)
self.fc2 = nn.Linear(64,32)
self.fc3 = nn.Linear(32,action_space)
def forward(self,state):
x = F.relu(self.fc1(state))
x = F.relu(self.fc2(x))
return self.fc3(x)
|
[
"C5ipo7i@gmail.com"
] |
C5ipo7i@gmail.com
|
b3bca2fa7b1096d2eb77d7ed7e62e9fa12f6c42b
|
426b91ccc883a56db3d87520956153392739674e
|
/CART.py
|
9d22f9c02927b8c4d64e1bdc702bfb1e5e450062
|
[] |
no_license
|
HuixiangWen/region-
|
1be5497cd3899ef6bedbd6dba43f4ff3c694a556
|
ba7d56744b8116a2896dc99d2aac4d6f51e01598
|
refs/heads/master
| 2020-04-10T21:47:20.879134
| 2018-12-11T09:26:18
| 2018-12-11T09:26:18
| 161,306,555
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,300
|
py
|
from sklearn.externals import joblib
from sklearn.tree import DecisionTreeClassifier
import pandas as pd
from sklearn.metrics import make_scorer, accuracy_score
from sklearn.model_selection import GridSearchCV, KFold, train_test_split
import os
path = "./newdata"
list1 = os.listdir(path)
print(list1)
list1 = ["0.csv"]
for i in list1:
print(i)
Project_data = pd.read_csv(path + "/" + i, encoding="gbk") # 读取预测数据
df1 = Project_data[['Rent_amount', 'floor', 'Total_floor', 'Area', 'towards', 'Number_bedroom', 'Number_hall', 'Number_wei', 'location',
'subway_route', 'subway_site', 'distance', 'region', 'price']]
from sklearn.model_selection import train_test_split
import seaborn as sns
sns.set()
m, n = df1.shape
X = df1.iloc[:, 0: n - 1]
Y = df1["price"]
x_train, x_test, y_train, y_test = train_test_split(X, Y, test_size=0.2, random_state=0)
test = pd.concat([x_test, y_test], axis=1)
# test.to_csv("./t.csv", sep=",", index=0)
# from sklearn.preprocessing import StandardScaler
#
# ss = StandardScaler()
# x_train = ss.fit_transform(x_train)
# x_test = ss.transform(x_test)
regressor = DecisionTreeClassifier(random_state=0)
parameters = {'max_depth': range(10, 50)}
scoring_fnc = make_scorer(accuracy_score)
kfold = KFold(n_splits=10)
grid = GridSearchCV(regressor, parameters, scoring_fnc, cv=kfold)
grid = grid.fit(x_train, y_train.ravel())
reg = grid.best_estimator_
print('train score: %f' % grid.best_score_)
print('best parameters:')
for key in parameters.keys():
print('%s: %d' % (key, reg.get_params()[key]))
print('test score: %f' % reg.score(x_test, y_test))
from sklearn.externals import joblib
joblib.dump(grid, "./" + i[:-4] + ".m")
# joblib.dump(grid, "asd1.m")
# clf = DecisionTreeClassifier(criterion='entropy', max_depth=20, min_samples_leaf=2)
# clf.fit(x_train, y_train)
#
# clf.fit(x_train, y_train.ravel())
#
# print(clf.score(x_train, y_train)) # 精度
# y_hat = clf.predict(x_train)
# show_accuracy(y_hat, y_train, '训练集')
# print(clf.score(x_test, y_test))
# y_hat = clf.predict(x_test)
# print(list(y_test))
# print(list(y_hat))
|
[
"jswenhuixiang@163.com"
] |
jswenhuixiang@163.com
|
872b16bed9932977abd190f8dc1a4240c3c9334b
|
bd58aa45e6feb0916f18997535c29150a85a081d
|
/experinmenting/3sectors_temp/agg_results.py
|
47dcfdec55091d276531bcd92f6b20e57040c90a
|
[] |
no_license
|
johnsonice/ABM_MacroEconomy
|
58f3edb2207a69b88beab741fdfad6c238c1f19b
|
8065dc4f2caa77f7a877cf684221386e198632bc
|
refs/heads/main
| 2023-08-21T21:04:18.934370
| 2021-11-03T05:31:44
| 2021-11-03T05:31:44
| 383,259,063
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 5,320
|
py
|
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Sep 20 14:52:41 2021
@author: chengyu
"""
import pandas as pd
import ast
from utils import get_current_res_folder
from config import simulation_parameters
import os
import matplotlib.pyplot as plt
#%%
def convert_dict_columns(df,colum_name):
if isinstance(df[colum_name][0],str):
df[colum_name] = df[colum_name].map(ast.literal_eval)
# reset the index if the index is not unique integers from 0 to n-1
# df.reset_index(inplace=True) # uncomment if needed
x = pd.json_normalize(df[colum_name])
df = df.join(x)
df.drop(columns=[colum_name], inplace=True)
return df
def post_process_firm_log(f,out_f=None):
df = pd.read_csv(f)
# df.index = df.index.astype(int)
# df.sort_index(inplace=True)
df = convert_dict_columns(df,'out_iter_memory_current')
df['n_labor_hired'] = df['labor_hired'].apply(len)
df['n_product_sold'] = df['actual_production']-df['balance_sheet.consumption_good']
if out_f:
df.to_csv(out_f)
return df
def post_process_hh_log(f,out_f=None):
df = pd.read_csv(f)
df['iter'] = df['round'].apply(get_round)
# df.index = df.index.astype(int)
# df.sort_index(inplace=True)
df = convert_dict_columns(df,'out_balance_sheet')
if out_f:
df.to_csv(out_f)
return df
def post_process_bank_log(f,out_f=None):
df = pd.read_csv(f)
df = convert_dict_columns(df,'out_financial_account')
if out_f:
df.to_csv(out_f)
return df
def get_round(r):
offset = len(str(simulation_parameters['sub_hiring_rounds']-1)) + len(str(simulation_parameters['sub_purchase_rounds']-1))
inp = str(r)
if len(inp)==offset:
return 0
else:
return int(inp[:-offset])
def calculate_firm_aggregate(df,out_f = None):
"""
aggregate firm df for global statistics
"""
df['iter'] = df['round'].apply(get_round)
## get total revenue and cost for global averaging
df['total_labor_cost'] = df['price_labor']*df['n_labor_hired']
df['total_revenue'] = df['price_consumption_good']*df['n_product_sold']
## set up variables for aggregating
sum_columns = ['planned_production','labor_needed',
'actual_production','new_credit_received',
'balance_sheet.money','balance_sheet.debt',
'total_labor_cost','total_revenue',
'n_labor_hired','n_product_sold']
agg_dict = {k:'sum' for k in sum_columns}
agg_df = df.groupby('iter').agg(agg_dict)
## fix and sort index
agg_df.index = agg_df.index.astype(int)
agg_df.sort_index(inplace=True)
## calculate average prices
agg_df['avg_consumption_price'] = agg_df['total_revenue'] / agg_df['n_product_sold']
agg_df['avg_labor_price'] = agg_df['total_labor_cost'] / agg_df['n_labor_hired']
if out_f:
agg_df.to_csv(out_f)
return agg_df
def calculate_hh_aggregate(df,out_f = None):
"""
aggregate hh df for global statistics
"""
#df['iter'] = df['round'].apply(get_round)
df['employed'] = df['employer'].notnull()
sum_columns = ['accumulated_utility','money','employed']
agg_dict = {k:'sum' for k in sum_columns}
agg_dict['index']='count'
agg_df = df.groupby('iter').agg(agg_dict)
agg_df.rename(columns={'index':"total_labor"},inplace=True)
## fix and sort index
agg_df.index = agg_df.index.astype(int)
agg_df.sort_index(inplace=True)
## calculate unemployment rate
agg_df['unemployment_rate'] = 1- agg_df['employed']/agg_df['total_labor']
return agg_df
#%%
if __name__ == "__main__":
## get result folder
res_folder = get_current_res_folder('./result')
## process firms
f = os.path.join(res_folder,'panel_firm.csv')
out_f = os.path.join(res_folder,'panel_firm_processed.csv')
firm_df = post_process_firm_log(f,out_f)
## product global statistics
agg_firm_df = calculate_firm_aggregate(firm_df)
agg_firm_df[['avg_consumption_price','avg_labor_price',
'balance_sheet.money','balance_sheet.debt',
'n_labor_hired','labor_needed']].plot(title='Frims agg statistics',subplots=True)
plt.savefig('result/firm_agg_1.png')
agg_firm_df[['planned_production','actual_production','n_product_sold']].plot(title='Frims agg statistics 2',subplots=False)
plt.savefig('result/firm_agg_2.png')
## process household
f = os.path.join(res_folder,'panel_household.csv')
out_f = os.path.join(res_folder,'panel_household_processed.csv')
hh_df = post_process_hh_log(f,out_f)
## product global statistics
agg_hh_df = calculate_hh_aggregate(hh_df)
agg_hh_df[['money','accumulated_utility','unemployment_rate']].plot(title='Hourseholds agg statistics',subplots=True)
plt.savefig('result/hh_agg_1.png')
## process bank
f = os.path.join(res_folder,'panel_bank.csv')
out_f = os.path.join(res_folder,'panel_bank_processed.csv')
bank_df = post_process_bank_log(f,out_f)
bank_df[['policy_rate','outstanding_loan','interest_payment','bad_loan']].plot(title='Bank agg statistics',subplots=True)
plt.savefig('result/bank_agg_1.png')
|
[
"huangchengyu16@gmail.com"
] |
huangchengyu16@gmail.com
|
b9de5a803a149b52dbecfe06e0ea5968797d4cb1
|
8d21ccde698901503f7f07f9b26f912c4c8d08d3
|
/ex01/wsgi.py
|
afea0f3f7341528697685f0a5b4ce8af0eaae6ba
|
[] |
no_license
|
wonginx/django_ex01
|
c41b3b40da07a7a54feb62a9989aa4668562a5d9
|
13258575d3285e9568992a6651c3d98e95d853fb
|
refs/heads/master
| 2023-08-20T23:06:30.800227
| 2021-10-06T08:45:58
| 2021-10-06T08:45:58
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 385
|
py
|
"""
WSGI config for ex01 project.
It exposes the WSGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/3.2/howto/deployment/wsgi/
"""
import os
from django.core.wsgi import get_wsgi_application
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'ex01.settings')
application = get_wsgi_application()
|
[
"nngg375@naver.com"
] |
nngg375@naver.com
|
1afda8ddb48c047d6ef756e490ec117335c07cc2
|
5e3ebc83bc3fe2f85c34563689b82b1fc8b93a04
|
/google/ads/googleads/v5/services/services/payments_account_service/client.py
|
846d30511be6ebd57110fc5b9a0bdc3ea6980507
|
[
"Apache-2.0"
] |
permissive
|
pdsing/google-ads-python
|
0ce70227cd6bb13a25cd13de0ca05c2636279ecd
|
ee2c059498d5679a0d1d9011f3795324439fad7c
|
refs/heads/master
| 2023-05-04T18:39:57.412453
| 2021-05-21T16:38:17
| 2021-05-21T16:38:17
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 18,552
|
py
|
# -*- coding: utf-8 -*-
# Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from collections import OrderedDict
from distutils import util
import os
import re
from typing import Dict, Optional, Sequence, Tuple, Type, Union
from google.api_core import client_options as client_options_lib # type: ignore
from google.api_core import exceptions # type: ignore
from google.api_core import gapic_v1 # type: ignore
from google.api_core import retry as retries # type: ignore
from google.auth import credentials # type: ignore
from google.auth.transport import mtls # type: ignore
from google.auth.transport.grpc import SslCredentials # type: ignore
from google.auth.exceptions import MutualTLSChannelError # type: ignore
from google.oauth2 import service_account # type: ignore
from google.ads.googleads.v5.services.types import payments_account_service
from .transports.base import (
PaymentsAccountServiceTransport,
DEFAULT_CLIENT_INFO,
)
from .transports.grpc import PaymentsAccountServiceGrpcTransport
class PaymentsAccountServiceClientMeta(type):
"""Metaclass for the PaymentsAccountService client.
This provides class-level methods for building and retrieving
support objects (e.g. transport) without polluting the client instance
objects.
"""
_transport_registry = (
OrderedDict()
) # type: Dict[str, Type[PaymentsAccountServiceTransport]]
_transport_registry["grpc"] = PaymentsAccountServiceGrpcTransport
def get_transport_class(
cls, label: str = None,
) -> Type[PaymentsAccountServiceTransport]:
"""Return an appropriate transport class.
Args:
label: The name of the desired transport. If none is
provided, then the first transport in the registry is used.
Returns:
The transport class to use.
"""
# If a specific transport is requested, return that one.
if label:
return cls._transport_registry[label]
# No transport is requested; return the default (that is, the first one
# in the dictionary).
return next(iter(cls._transport_registry.values()))
class PaymentsAccountServiceClient(metaclass=PaymentsAccountServiceClientMeta):
"""Service to provide payments accounts that can be used to set
up consolidated billing.
"""
@staticmethod
def _get_default_mtls_endpoint(api_endpoint):
"""Convert api endpoint to mTLS endpoint.
Convert "*.sandbox.googleapis.com" and "*.googleapis.com" to
"*.mtls.sandbox.googleapis.com" and "*.mtls.googleapis.com" respectively.
Args:
api_endpoint (Optional[str]): the api endpoint to convert.
Returns:
str: converted mTLS api endpoint.
"""
if not api_endpoint:
return api_endpoint
mtls_endpoint_re = re.compile(
r"(?P<name>[^.]+)(?P<mtls>\.mtls)?(?P<sandbox>\.sandbox)?(?P<googledomain>\.googleapis\.com)?"
)
m = mtls_endpoint_re.match(api_endpoint)
name, mtls, sandbox, googledomain = m.groups()
if mtls or not googledomain:
return api_endpoint
if sandbox:
return api_endpoint.replace(
"sandbox.googleapis.com", "mtls.sandbox.googleapis.com"
)
return api_endpoint.replace(".googleapis.com", ".mtls.googleapis.com")
DEFAULT_ENDPOINT = "googleads.googleapis.com"
DEFAULT_MTLS_ENDPOINT = _get_default_mtls_endpoint.__func__( # type: ignore
DEFAULT_ENDPOINT
)
@classmethod
def from_service_account_info(cls, info: dict, *args, **kwargs):
"""Creates an instance of this client using the provided credentials info.
Args:
info (dict): The service account private key info.
args: Additional arguments to pass to the constructor.
kwargs: Additional arguments to pass to the constructor.
Returns:
PaymentsAccountServiceClient: The constructed client.
"""
credentials = service_account.Credentials.from_service_account_info(
info
)
kwargs["credentials"] = credentials
return cls(*args, **kwargs)
@classmethod
def from_service_account_file(cls, filename: str, *args, **kwargs):
"""Creates an instance of this client using the provided credentials
file.
Args:
filename (str): The path to the service account private key json
file.
args: Additional arguments to pass to the constructor.
kwargs: Additional arguments to pass to the constructor.
Returns:
PaymentsAccountServiceClient: The constructed client.
"""
credentials = service_account.Credentials.from_service_account_file(
filename
)
kwargs["credentials"] = credentials
return cls(*args, **kwargs)
from_service_account_json = from_service_account_file
@property
def transport(self) -> PaymentsAccountServiceTransport:
"""Return the transport used by the client instance.
Returns:
PaymentsAccountServiceTransport: The transport used by the client instance.
"""
return self._transport
@staticmethod
def customer_path(customer: str,) -> str:
"""Return a fully-qualified customer string."""
return "customers/{customer}".format(customer=customer,)
@staticmethod
def parse_customer_path(path: str) -> Dict[str, str]:
"""Parse a customer path into its component segments."""
m = re.match(r"^customers/(?P<customer>.+?)$", path)
return m.groupdict() if m else {}
@staticmethod
def payments_account_path(customer: str, payments_account: str,) -> str:
"""Return a fully-qualified payments_account string."""
return "customers/{customer}/paymentsAccounts/{payments_account}".format(
customer=customer, payments_account=payments_account,
)
@staticmethod
def parse_payments_account_path(path: str) -> Dict[str, str]:
"""Parse a payments_account path into its component segments."""
m = re.match(
r"^customers/(?P<customer>.+?)/paymentsAccounts/(?P<payments_account>.+?)$",
path,
)
return m.groupdict() if m else {}
@staticmethod
def common_billing_account_path(billing_account: str,) -> str:
"""Return a fully-qualified billing_account string."""
return "billingAccounts/{billing_account}".format(
billing_account=billing_account,
)
@staticmethod
def parse_common_billing_account_path(path: str) -> Dict[str, str]:
"""Parse a billing_account path into its component segments."""
m = re.match(r"^billingAccounts/(?P<billing_account>.+?)$", path)
return m.groupdict() if m else {}
@staticmethod
def common_folder_path(folder: str,) -> str:
"""Return a fully-qualified folder string."""
return "folders/{folder}".format(folder=folder,)
@staticmethod
def parse_common_folder_path(path: str) -> Dict[str, str]:
"""Parse a folder path into its component segments."""
m = re.match(r"^folders/(?P<folder>.+?)$", path)
return m.groupdict() if m else {}
@staticmethod
def common_organization_path(organization: str,) -> str:
"""Return a fully-qualified organization string."""
return "organizations/{organization}".format(organization=organization,)
@staticmethod
def parse_common_organization_path(path: str) -> Dict[str, str]:
"""Parse a organization path into its component segments."""
m = re.match(r"^organizations/(?P<organization>.+?)$", path)
return m.groupdict() if m else {}
@staticmethod
def common_project_path(project: str,) -> str:
"""Return a fully-qualified project string."""
return "projects/{project}".format(project=project,)
@staticmethod
def parse_common_project_path(path: str) -> Dict[str, str]:
"""Parse a project path into its component segments."""
m = re.match(r"^projects/(?P<project>.+?)$", path)
return m.groupdict() if m else {}
@staticmethod
def common_location_path(project: str, location: str,) -> str:
"""Return a fully-qualified location string."""
return "projects/{project}/locations/{location}".format(
project=project, location=location,
)
@staticmethod
def parse_common_location_path(path: str) -> Dict[str, str]:
"""Parse a location path into its component segments."""
m = re.match(
r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)$", path
)
return m.groupdict() if m else {}
def __init__(
self,
*,
credentials: Optional[credentials.Credentials] = None,
transport: Union[str, PaymentsAccountServiceTransport, None] = None,
client_options: Optional[client_options_lib.ClientOptions] = None,
client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
) -> None:
"""Instantiate the payments account service client.
Args:
credentials (Optional[google.auth.credentials.Credentials]): The
authorization credentials to attach to requests. These
credentials identify the application to the service; if none
are specified, the client will attempt to ascertain the
credentials from the environment.
transport (Union[str, ~.PaymentsAccountServiceTransport]): The
transport to use. If set to None, a transport is chosen
automatically.
client_options (google.api_core.client_options.ClientOptions): Custom options for the
client. It won't take effect if a ``transport`` instance is provided.
(1) The ``api_endpoint`` property can be used to override the
default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT
environment variable can also be used to override the endpoint:
"always" (always use the default mTLS endpoint), "never" (always
use the default regular endpoint) and "auto" (auto switch to the
default mTLS endpoint if client certificate is present, this is
the default value). However, the ``api_endpoint`` property takes
precedence if provided.
(2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable
is "true", then the ``client_cert_source`` property can be used
to provide client certificate for mutual TLS transport. If
not provided, the default SSL client certificate will be used if
present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not
set, no client certificate will be used.
client_info (google.api_core.gapic_v1.client_info.ClientInfo):
The client info used to send a user-agent string along with
API requests. If ``None``, then default info will be used.
Generally, you only need to set this if you're developing
your own client library.
Raises:
google.auth.exceptions.MutualTLSChannelError: If mutual TLS transport
creation failed for any reason.
"""
if isinstance(client_options, dict):
client_options = client_options_lib.from_dict(client_options)
if client_options is None:
client_options = client_options_lib.ClientOptions()
# Create SSL credentials for mutual TLS if needed.
use_client_cert = bool(
util.strtobool(
os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false")
)
)
ssl_credentials = None
is_mtls = False
if use_client_cert:
if client_options.client_cert_source:
import grpc # type: ignore
cert, key = client_options.client_cert_source()
ssl_credentials = grpc.ssl_channel_credentials(
certificate_chain=cert, private_key=key
)
is_mtls = True
else:
creds = SslCredentials()
is_mtls = creds.is_mtls
ssl_credentials = creds.ssl_credentials if is_mtls else None
# Figure out which api endpoint to use.
if client_options.api_endpoint is not None:
api_endpoint = client_options.api_endpoint
else:
use_mtls_env = os.getenv("GOOGLE_API_USE_MTLS_ENDPOINT", "auto")
if use_mtls_env == "never":
api_endpoint = self.DEFAULT_ENDPOINT
elif use_mtls_env == "always":
api_endpoint = self.DEFAULT_MTLS_ENDPOINT
elif use_mtls_env == "auto":
api_endpoint = (
self.DEFAULT_MTLS_ENDPOINT
if is_mtls
else self.DEFAULT_ENDPOINT
)
else:
raise MutualTLSChannelError(
"Unsupported GOOGLE_API_USE_MTLS_ENDPOINT value. Accepted values: never, auto, always"
)
# Save or instantiate the transport.
# Ordinarily, we provide the transport, but allowing a custom transport
# instance provides an extensibility point for unusual situations.
if isinstance(transport, PaymentsAccountServiceTransport):
# transport is a PaymentsAccountServiceTransport instance.
if credentials:
raise ValueError(
"When providing a transport instance, "
"provide its credentials directly."
)
self._transport = transport
elif isinstance(transport, str):
Transport = type(self).get_transport_class(transport)
self._transport = Transport(
credentials=credentials, host=self.DEFAULT_ENDPOINT
)
else:
self._transport = PaymentsAccountServiceGrpcTransport(
credentials=credentials,
host=api_endpoint,
ssl_channel_credentials=ssl_credentials,
client_info=client_info,
)
def list_payments_accounts(
self,
request: payments_account_service.ListPaymentsAccountsRequest = None,
*,
customer_id: str = None,
retry: retries.Retry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> payments_account_service.ListPaymentsAccountsResponse:
r"""Returns all payments accounts associated with all
managers between the login customer ID and specified
serving customer in the hierarchy, inclusive.
Args:
request (:class:`google.ads.googleads.v5.services.types.ListPaymentsAccountsRequest`):
The request object. Request message for fetching all
accessible payments accounts.
customer_id (:class:`str`):
Required. The ID of the customer to
apply the PaymentsAccount list operation
to.
This corresponds to the ``customer_id`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry.Retry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.ads.googleads.v5.services.types.ListPaymentsAccountsResponse:
Response message for
[PaymentsAccountService.ListPaymentsAccounts][google.ads.googleads.v5.services.PaymentsAccountService.ListPaymentsAccounts].
"""
# Create or coerce a protobuf request object.
# Sanity check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
if request is not None and any([customer_id]):
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
# Minor optimization to avoid making a copy if the user passes
# in a payments_account_service.ListPaymentsAccountsRequest.
# There's no risk of modifying the input as we've already verified
# there are no flattened fields.
if not isinstance(
request, payments_account_service.ListPaymentsAccountsRequest
):
request = payments_account_service.ListPaymentsAccountsRequest(
request
)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if customer_id is not None:
request.customer_id = customer_id
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[
self._transport.list_payments_accounts
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata(
(("customer_id", request.customer_id),)
),
)
# Send the request.
response = rpc(
request, retry=retry, timeout=timeout, metadata=metadata,
)
# Done; return the response.
return response
__all__ = ("PaymentsAccountServiceClient",)
|
[
"noreply@github.com"
] |
pdsing.noreply@github.com
|
71bfd6033266f0ff9ba160f37173c98c2ac26562
|
6a990a3d549ca3d1c607b60b13b10f14c0e15787
|
/game/douniu/mode/douniu_room.py
|
b2df67f7bd92383dec3420b6d88d711e47d3f06f
|
[] |
no_license
|
qianyc1020/server
|
217a766f7df5a0acfb983d3fc48317a932fe092e
|
3c897e5d6ee453d0a2f3b371b5eda5af954b8d1a
|
refs/heads/master
| 2020-06-10T08:55:31.996449
| 2019-06-24T06:26:43
| 2019-06-24T06:26:43
| 193,626,075
| 1
| 0
| null | 2019-06-25T03:12:39
| 2019-06-25T03:12:37
| null |
UTF-8
|
Python
| false
| false
| 8,883
|
py
|
# coding=utf-8
import threading
import random
import core.globalvar as gl
from game.douniu.command.game import roomover_cmd, gamestart_cmd, gameover_cmd, dealcard_cmd
from game.douniu.mode.game_status import GameStatus
from game.douniu.timeout import operation_timeout
from mode.game.room import Room
from protocol.base.base_pb2 import EXECUTE_ACTION, UPDATE_GAME_INFO, UPDATE_GAME_PLAYER_INFO, \
REENTER_GAME_INFO, ASK_ACTION, EXIT_GAME, APPLY_CHANGE_MATCH
from protocol.base.game_base_pb2 import RecExecuteAction, RecUpdateGameInfo, RecUpdateGameUsers, RecReEnterGameInfo
from protocol.base.server_to_game_pb2 import UserExit
from protocol.game.bairen_pb2 import BaiRenRecAsk
from protocol.game.douniu_pb2 import DouniuBankerConfirm, DouniuCreateRoom, DouniuCardAction
class DouniuRoom(Room):
def __init__(self, roomNo=0, count=0, gameRules=0, matchLevel=0, score=0, inScore=0, leaveScore=0, gameType=0,
betType=1):
super(DouniuRoom, self).__init__(roomNo, count, gameRules, matchLevel)
self.score = score
self.inScore = inScore
self.leaveScore = leaveScore
self.gameStatus = GameStatus.WAITING
self.banker = 0
self.gameType = gameType
self.betType = betType
self.historyActions = []
def save(self, redis):
if self.gameStatus != GameStatus.DESTORY:
redis.setobj("room_" + str(self.roomNo), self)
def clear(self):
super(DouniuRoom, self).clear()
self.gameStatus = GameStatus.WAITING
self.historyActions = []
self.banker = 0
def bankerConfirm(self, messageHandle):
bankerConfirm = DouniuBankerConfirm()
bankerConfirm.bankerId = self.banker
self.executeAction(0, 4, bankerConfirm, messageHandle)
def executeAction(self, userId, actionType, data, messageHandle):
recExecuteAction = RecExecuteAction()
recExecuteAction.actionType = actionType
recExecuteAction.playerId = userId
if data is not None:
recExecuteAction.data = data.SerializeToString()
messageHandle.broadcast_seat_to_gateway(EXECUTE_ACTION, recExecuteAction, self)
self.historyActions.append(recExecuteAction.SerializeToString())
def recUpdateGameInfo(self, messageHandle):
recUpdateGameInfo = RecUpdateGameInfo()
recUpdateGameInfo.allocId = 2
douniuCreateRoom = DouniuCreateRoom()
douniuCreateRoom.baseScore = self.score
douniuCreateRoom.inScore = self.inScore
douniuCreateRoom.leaveScore = self.leaveScore
douniuCreateRoom.type = self.gameType
douniuCreateRoom.gameRules = self.gameRules
douniuCreateRoom.betType = self.betType
douniuCreateRoom.match = True
recUpdateGameInfo.content = douniuCreateRoom.SerializeToString()
messageHandle.send_to_gateway(UPDATE_GAME_INFO, recUpdateGameInfo)
def recUpdateScore(self, messageHandle, userId):
recUpdateGameUsers = RecUpdateGameUsers()
for s in self.seats:
userInfo = recUpdateGameUsers.users.add()
userInfo.account = s.account
userInfo.playerId = s.userId
userInfo.headUrl = s.head
userInfo.createTime = s.createDate
userInfo.ip = s.ip
userInfo.online = s.online
userInfo.nick = s.nickname
userInfo.ready = s.ready
userInfo.score = s.score
userInfo.sex = s.sex
userInfo.totalCount = s.total_count
userInfo.loc = s.seatNo
userInfo.consumeVip = s.level
if 0 == userId:
messageHandle.broadcast_seat_to_gateway(UPDATE_GAME_PLAYER_INFO, recUpdateGameUsers, self)
else:
messageHandle.send_to_gateway(UPDATE_GAME_PLAYER_INFO, recUpdateGameUsers)
def recReEnterGameInfo(self, messageHandle, userId):
recReEnterGameInfo = RecReEnterGameInfo()
recReEnterGameInfo.allocId = 2
seat = self.getSeatByUserId(userId)
for a in self.historyActions:
executeAction = recReEnterGameInfo.actionInfos.add()
executeAction.ParseFromString(a)
if 0 == executeAction.actionType:
dealCardAction = DouniuCardAction()
dealCardAction.ParseFromString(executeAction.data)
if 4 == len(dealCardAction.cards):
if 0 != len(seat.initialCards):
dealCardAction = DouniuCardAction()
dealCardAction.cards.extend(seat.initialCards)
else:
dealCardAction = DouniuCardAction()
dealCardAction.cards.extend([0, 0, 0, 0])
else:
if 0 != len(seat.initialCards):
dealCardAction = DouniuCardAction()
dealCardAction.cards.append(seat.initialCards[4])
else:
dealCardAction = DouniuCardAction()
dealCardAction.cards.append(0)
executeAction.data = dealCardAction.SerializeToString()
messageHandle.send_to_gateway(REENTER_GAME_INFO, recReEnterGameInfo, userId)
if self.gameStatus == GameStatus.GRABING:
self.executeAsk(messageHandle, userId, 1)
if self.gameStatus == GameStatus.PLAYING:
self.executeAsk(messageHandle, userId, 2)
if self.gameStatus == GameStatus.OPENING:
self.executeAsk(messageHandle, userId, 3)
def executeAsk(self, messageHandle, userId, type):
douniuRecAsk = BaiRenRecAsk()
douniuRecAsk.type = type
threading.Thread(target=operation_timeout.execute,
args=(self.roomNo, messageHandle, self.gameStatus, self.gameCount),
name='operation_timeout').start() # 线程对象.
if 0 == userId:
messageHandle.broadcast_seat_to_gateway(ASK_ACTION, douniuRecAsk, self)
else:
messageHandle.send_to_gateway(ASK_ACTION, douniuRecAsk, userId)
def exit(self, userId, messageHandle):
self.exitOrChangeMatch(userId, messageHandle, False)
def changeMatch(self, userId, messageHandle):
self.exitOrChangeMatch(userId, messageHandle, True)
def exitOrChangeMatch(self, userId, messageHandle, changeMatch):
seat = self.getSeatByUserId(userId)
if seat is not None and (seat.guanzhan or self.gameStatus == GameStatus.WAITING):
while seat is not None:
self.seatNos.append(seat.seatNo)
self.seats.remove(seat)
seat = self.getSeatByUserId(userId)
redis = gl.get_v("redis")
redis.delobj(str(userId) + "_room")
userExit = UserExit()
userExit.playerId = userId
userExit.roomNo = self.roomNo
userExit.level = self.matchLevel
from game.douniu.server.server import Server
Server.send_to_coordinate(APPLY_CHANGE_MATCH if changeMatch else EXIT_GAME, userExit)
self.recUpdateScore(messageHandle, 0)
if 0 == len(self.seats):
roomover_cmd.execute(self, messageHandle)
elif self.gameStatus == GameStatus.WAITING:
self.checkReady(messageHandle)
def checkReady(self, messageHandle):
allReady = True
for seat in self.seats:
if not seat.ready:
allReady = False
break
if allReady and len(self.seats) > 1:
gamestart_cmd.execute(self, messageHandle)
def checkGrab(self, messageHandle):
bankers = []
maxGrab = 0
for seat in self.seats:
if -1 == seat.grab and not seat.guanzhan:
return
if seat.grab > maxGrab:
bankers = []
bankers.append(seat.userId)
maxGrab = seat.grab
elif seat.grab == maxGrab:
bankers.append(seat.userId)
if len(bankers) > 0:
self.banker = bankers[random.randint(0, len(bankers) - 1)]
else:
self.banker = self.seats[random.randint(0, len(self.seats) - 1)].userId
self.bankerConfirm(messageHandle)
self.gameStatus = GameStatus.PLAYING
self.executeAsk(messageHandle, 0, 2)
def checkPlay(self, messageHandle):
if self.gameStatus != GameStatus.PLAYING:
return
for seat in self.seats:
if -1 == seat.playScore and not seat.guanzhan and seat.userId != self.banker:
return
dealcard_cmd.execute(self, messageHandle)
def checkOpen(self, messageHandle):
for seat in self.seats:
if not seat.openCard and not seat.guanzhan:
return
gameover_cmd.execute(self, messageHandle)
|
[
"pengyi9627@gmail.com"
] |
pengyi9627@gmail.com
|
f225dd25a52b2e3e872805bebfc869deb6403608
|
15f321878face2af9317363c5f6de1e5ddd9b749
|
/solutions_python/Problem_200/3307.py
|
0b45963022441cf19c13a42c6bfcac2c7069bca0
|
[] |
no_license
|
dr-dos-ok/Code_Jam_Webscraper
|
c06fd59870842664cd79c41eb460a09553e1c80a
|
26a35bf114a3aa30fc4c677ef069d95f41665cc0
|
refs/heads/master
| 2020-04-06T08:17:40.938460
| 2018-10-14T10:12:47
| 2018-10-14T10:12:47
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 327
|
py
|
T = int(input())
for case in range(T):
N = input()
R = "0"
for digit in range(len(N),0,-1):
for n in range(9,int(R[-1])-1,-1):
R = R[0:len(N)-digit] + digit*str(n)
if(int(R) <= int(N)):
break;
R = R.strip('0')
print("Case #{}: {}".format(case+1, R))
|
[
"miliar1732@gmail.com"
] |
miliar1732@gmail.com
|
205196db7584b5071414be641278ef9edd2597c2
|
2859496fcd4dd1e9c94f903ab31069c40eca469c
|
/guardians_of_children/migrations/0005_auto_20211003_0646.py
|
2394944fa0c0b524bad3c7116cc5904313144a73
|
[] |
no_license
|
Seoha-Yoon/ai_guardians_backend
|
8910384f8fa24d06827da78a5d038415491acecc
|
79d7fea57801a3bb58f21842918b2e498c53c6ad
|
refs/heads/main
| 2023-08-19T11:42:33.108165
| 2021-10-04T12:21:30
| 2021-10-04T12:21:30
| 412,526,300
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 376
|
py
|
# Generated by Django 2.2.5 on 2021-10-03 06:46
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('guardians_of_children', '0004_auto_20211003_0642'),
]
operations = [
migrations.RenameField(
model_name='videos',
old_name='videos',
new_name='video',
),
]
|
[
"seohayn127@gmail.com"
] |
seohayn127@gmail.com
|
f4db245ed76e913ad2797cc535061d803a260f34
|
a2f22c92a047cb2840e9273b06aeaf26fbe06129
|
/user.globalmilestone.org/interface/standard/migrations/0007_remove_student_grade_level.py
|
733d4c956ac2a0836cc7a3b0e5ceb63cd6f4e304
|
[] |
no_license
|
sashaberger31/BishopsHCS
|
4ab53bbe7dea781e1dd4efe0bf40ffa12ab0eadb
|
f5dee997b2a72f4513286fff0c45f6faf798f2f4
|
refs/heads/master
| 2023-01-07T22:22:15.560469
| 2020-09-03T06:08:40
| 2020-09-03T06:08:40
| 292,396,305
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 333
|
py
|
# Generated by Django 3.1 on 2020-08-12 17:26
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('standard', '0006_auto_20200812_1723'),
]
operations = [
migrations.RemoveField(
model_name='student',
name='grade_level',
),
]
|
[
"sasha@globalmilestone.org"
] |
sasha@globalmilestone.org
|
cfba3bc559cc82b538914a447694d7373ad555d6
|
8acffb8c4ddca5bfef910e58d3faa0e4de83fce8
|
/ml-flask/Lib/site-packages/sklearn/preprocessing/tests/test_function_transformer.py
|
86f0f1155f93774d77023cae05380cc15dba50b1
|
[
"MIT"
] |
permissive
|
YaminiHP/SimilitudeApp
|
8cbde52caec3c19d5fa73508fc005f38f79b8418
|
005c59894d8788c97be16ec420c0a43aaec99b80
|
refs/heads/master
| 2023-06-27T00:03:00.404080
| 2021-07-25T17:51:27
| 2021-07-25T17:51:27
| 389,390,951
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 129
|
py
|
version https://git-lfs.github.com/spec/v1
oid sha256:8dd493e6459816a7ce3af5334d0d4d42b0b6cfbbf9a6650d4e6b945651ce74da
size 5431
|
[
"yamprakash130@gmail.com"
] |
yamprakash130@gmail.com
|
627080aae5a63a549c017d35ab18c5c6c6ae77a0
|
28328e0efe3c801ecc4e785d85d471089b366839
|
/examples/pub_sub_receive.py
|
426af39d332c87152e54fbaa5ecadc6ae0048f4c
|
[
"MIT"
] |
permissive
|
leviethung2103/imagezmq_replicate
|
0010446d027ac08aa0399049f9f2f9022fe72780
|
7fc60788fc2b024ea86dedea63fd9962f5af4516
|
refs/heads/master
| 2022-11-22T06:09:19.498457
| 2020-07-25T23:20:56
| 2020-07-25T23:20:56
| 282,538,914
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,792
|
py
|
"""pub_sub_receive.py -- receive OpenCV stream using PUB SUB."""
import sys
import socket
import traceback
import cv2
from imutils.video import VideoStream
import imagezmq
import threading
import numpy as np
from time import sleep
# Helper class implementing an IO deamon thread
class VideoStreamSubscriber:
def __init__(self, hostname, port):
self.hostname = hostname
self.port = port
self._stop = False
self._data_ready = threading.Event()
self._thread = threading.Thread(target=self._run, args=())
self._thread.daemon = True
self._thread.start()
def receive(self, timeout=15.0):
flag = self._data_ready.wait(timeout=timeout)
if not flag:
raise TimeoutError(
"Timeout while reading from subscriber tcp://{}:{}".format(self.hostname, self.port))
self._data_ready.clear()
return self._data
def _run(self):
receiver = imagezmq.ImageHub("tcp://{}:{}".format(self.hostname, self.port), REQ_REP=False)
while not self._stop:
self._data = receiver.recv_jpg()
self._data_ready.set()
receiver.close()
def close(self):
self._stop = True
# Simulating heavy processing load
def limit_to_2_fps():
sleep(0.5)
if __name__ == "__main__":
# Receive from broadcast
# There are 2 hostname styles; comment out the one you don't need
# hostname = "127.0.0.1" # Use to receive from localhost
hostname = "hunglv1994.ddns.net" # Use to receive from localhost
# hostname = "192.168.86.38" # Use to receive from other computer
port = 5555
receiver = VideoStreamSubscriber(hostname, port)
old_image = None
try:
while True:
msg, frame = receiver.receive()
image = cv2.imdecode(np.frombuffer(frame, dtype='uint8'), -1)
if (old_image is not None) and (image.all() != old_image.all()):
print ("new image is obtained")
old_image = image.copy()
# Due to the IO thread constantly fetching images, we can do any amount
# of processing here and the next call to receive() will still give us
# the most recent frame (more or less realtime behaviour)
# Uncomment this statement to simulate processing load
# limit_to_2_fps() # Comment this statement out to run full speeed
cv2.imshow("Pub Sub Receive", image)
cv2.waitKey(1)
except (KeyboardInterrupt, SystemExit):
print('Exit due to keyboard interrupt')
except Exception as ex:
print('Python error with no Exception handler:')
print('Traceback error:', ex)
traceback.print_exc()
finally:
receiver.close()
sys.exit()
|
[
"hunglv@greenglobal.vn"
] |
hunglv@greenglobal.vn
|
936a02e2e528ae1b24dfc6b747fe4f5e89fed379
|
6c57b1694817d1710335429c12c2d9774ff446e3
|
/2017-08-06/AS-DA-DB_case07/generated_files/LEMS_c302_C2_AS_DA_DB_nrn.py
|
95fa1c511d60824f5db04a48a7fc9228e17b2f13
|
[] |
no_license
|
lungd/openworm-experiments
|
cd3875e8071c35eacb919c318344bac56d0fe379
|
065f481fbb445ef12b8ab2110f501686d26c213c
|
refs/heads/master
| 2021-01-01T04:41:38.397726
| 2017-09-12T13:55:40
| 2017-09-12T13:55:40
| 97,220,679
| 1
| 1
| null | 2017-09-01T17:10:28
| 2017-07-14T10:07:56
|
Python
|
UTF-8
|
Python
| false
| false
| 749,109
|
py
|
'''
Neuron simulator export for:
Components:
Leak (Type: ionChannelPassive: conductance=1.0E-11 (SI conductance))
k_fast (Type: ionChannelHH: conductance=1.0E-11 (SI conductance))
k_slow (Type: ionChannelHH: conductance=1.0E-11 (SI conductance))
ca_boyle (Type: ionChannelHH: conductance=1.0E-11 (SI conductance))
ca_simple (Type: ionChannelHH: conductance=1.0E-11 (SI conductance))
k_muscle (Type: ionChannelHH: conductance=1.0E-11 (SI conductance))
ca_muscle (Type: ionChannelHH: conductance=1.0E-11 (SI conductance))
null (Type: notes)
CaPool (Type: fixedFactorConcentrationModel: restingConc=0.0 (SI concentration) decayConstant=0.013811870945509265 (SI time) rho=2.38919E-4 (SI rho_factor))
neuron_to_neuron_elec_syn_2conns (Type: gapJunction: conductance=2.504E-11 (SI conductance))
neuron_to_neuron_elec_syn_7conns (Type: gapJunction: conductance=8.764000000000001E-11 (SI conductance))
neuron_to_neuron_elec_syn_6conns (Type: gapJunction: conductance=7.512000000000001E-11 (SI conductance))
neuron_to_neuron_elec_syn_4conns (Type: gapJunction: conductance=5.008E-11 (SI conductance))
neuron_to_neuron_elec_syn_10conns (Type: gapJunction: conductance=1.2520000000000002E-10 (SI conductance))
neuron_to_neuron_elec_syn_8conns (Type: gapJunction: conductance=1.0016E-10 (SI conductance))
neuron_to_neuron_elec_syn_1conns (Type: gapJunction: conductance=1.252E-11 (SI conductance))
neuron_to_neuron_elec_syn_3conns (Type: gapJunction: conductance=3.7560000000000004E-11 (SI conductance))
neuron_to_neuron_elec_syn_9conns (Type: gapJunction: conductance=1.1268E-10 (SI conductance))
neuron_to_neuron_elec_syn_5conns (Type: gapJunction: conductance=6.260000000000001E-11 (SI conductance))
neuron_to_neuron_elec_syn_13conns (Type: gapJunction: conductance=1.6276E-10 (SI conductance))
neuron_to_neuron_elec_syn_15conns (Type: gapJunction: conductance=1.8780000000000001E-10 (SI conductance))
muscle_to_muscle_elec_syn_15conns (Type: gapJunction: conductance=0.0 (SI conductance))
muscle_to_muscle_elec_syn_2conns (Type: gapJunction: conductance=0.0 (SI conductance))
silent (Type: silentSynapse)
neuron_to_neuron_exc_syn_2conns (Type: gradedSynapse: conductance=1.2E-9 (SI conductance) delta=0.005 (SI voltage) k=500.0 (SI per_time) Vth=0.0 (SI voltage) erev=-0.01 (SI voltage))
neuron_to_neuron_exc_syn_6conns (Type: gradedSynapse: conductance=3.6000000000000004E-9 (SI conductance) delta=0.005 (SI voltage) k=500.0 (SI per_time) Vth=0.0 (SI voltage) erev=-0.01 (SI voltage))
neuron_to_neuron_exc_syn_10conns (Type: gradedSynapse: conductance=6.000000000000001E-9 (SI conductance) delta=0.005 (SI voltage) k=500.0 (SI per_time) Vth=0.0 (SI voltage) erev=-0.01 (SI voltage))
neuron_to_neuron_exc_syn_12conns (Type: gradedSynapse: conductance=7.200000000000001E-9 (SI conductance) delta=0.005 (SI voltage) k=500.0 (SI per_time) Vth=0.0 (SI voltage) erev=-0.01 (SI voltage))
neuron_to_neuron_exc_syn_14conns (Type: gradedSynapse: conductance=8.4E-9 (SI conductance) delta=0.005 (SI voltage) k=500.0 (SI per_time) Vth=0.0 (SI voltage) erev=-0.01 (SI voltage))
neuron_to_neuron_exc_syn_4conns (Type: gradedSynapse: conductance=2.4E-9 (SI conductance) delta=0.005 (SI voltage) k=500.0 (SI per_time) Vth=0.0 (SI voltage) erev=-0.01 (SI voltage))
neuron_to_neuron_exc_syn_5conns (Type: gradedSynapse: conductance=3.0000000000000004E-9 (SI conductance) delta=0.005 (SI voltage) k=500.0 (SI per_time) Vth=0.0 (SI voltage) erev=-0.01 (SI voltage))
neuron_to_neuron_exc_syn_3conns (Type: gradedSynapse: conductance=1.8000000000000002E-9 (SI conductance) delta=0.005 (SI voltage) k=500.0 (SI per_time) Vth=0.0 (SI voltage) erev=-0.01 (SI voltage))
neuron_to_neuron_exc_syn_9conns (Type: gradedSynapse: conductance=5.4E-9 (SI conductance) delta=0.005 (SI voltage) k=500.0 (SI per_time) Vth=0.0 (SI voltage) erev=-0.01 (SI voltage))
neuron_to_neuron_exc_syn_8conns (Type: gradedSynapse: conductance=4.8E-9 (SI conductance) delta=0.005 (SI voltage) k=500.0 (SI per_time) Vth=0.0 (SI voltage) erev=-0.01 (SI voltage))
neuron_to_neuron_exc_syn_20conns (Type: gradedSynapse: conductance=1.2000000000000002E-8 (SI conductance) delta=0.005 (SI voltage) k=500.0 (SI per_time) Vth=0.0 (SI voltage) erev=-0.01 (SI voltage))
neuron_to_neuron_exc_syn_1conns (Type: gradedSynapse: conductance=6.0E-10 (SI conductance) delta=0.005 (SI voltage) k=500.0 (SI per_time) Vth=0.0 (SI voltage) erev=-0.01 (SI voltage))
neuron_to_neuron_inh_syn_28conns (Type: gradedSynapse: conductance=2.8000000000000003E-8 (SI conductance) delta=0.005 (SI voltage) k=15.0 (SI per_time) Vth=0.0 (SI voltage) erev=-0.07 (SI voltage))
neuron_to_neuron_inh_syn_4conns (Type: gradedSynapse: conductance=4.0E-9 (SI conductance) delta=0.005 (SI voltage) k=15.0 (SI per_time) Vth=0.0 (SI voltage) erev=-0.07 (SI voltage))
neuron_to_neuron_inh_syn_3conns (Type: gradedSynapse: conductance=3.0000000000000004E-9 (SI conductance) delta=0.005 (SI voltage) k=15.0 (SI per_time) Vth=0.0 (SI voltage) erev=-0.07 (SI voltage))
neuron_to_neuron_inh_syn_2conns (Type: gradedSynapse: conductance=2.0E-9 (SI conductance) delta=0.005 (SI voltage) k=15.0 (SI per_time) Vth=0.0 (SI voltage) erev=-0.07 (SI voltage))
neuron_to_neuron_inh_syn_1conns (Type: gradedSynapse: conductance=1.0E-9 (SI conductance) delta=0.005 (SI voltage) k=15.0 (SI per_time) Vth=0.0 (SI voltage) erev=-0.07 (SI voltage))
neuron_to_muscle_exc_syn_9conns (Type: gradedSynapse: conductance=9.000000000000001E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
neuron_to_muscle_exc_syn_8conns (Type: gradedSynapse: conductance=8.000000000000001E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
neuron_to_muscle_exc_syn_3conns (Type: gradedSynapse: conductance=3.0E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
neuron_to_muscle_exc_syn_1conns (Type: gradedSynapse: conductance=1.0000000000000002E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
neuron_to_muscle_exc_syn_5conns (Type: gradedSynapse: conductance=5.0E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
neuron_to_muscle_exc_syn_4conns (Type: gradedSynapse: conductance=4.0000000000000007E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
neuron_to_muscle_exc_syn_2conns (Type: gradedSynapse: conductance=2.0000000000000003E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
neuron_to_muscle_exc_syn_6conns (Type: gradedSynapse: conductance=6.0E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
neuron_to_muscle_exc_syn_7conns (Type: gradedSynapse: conductance=7.0E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
neuron_to_muscle_exc_syn_17conns (Type: gradedSynapse: conductance=1.7000000000000001E-9 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
neuron_to_muscle_exc_syn_12conns (Type: gradedSynapse: conductance=1.2E-9 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
neuron_to_muscle_exc_syn_14conns (Type: gradedSynapse: conductance=1.4E-9 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
neuron_to_muscle_exc_syn_10conns (Type: gradedSynapse: conductance=1.0E-9 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
DB1_to_MDL06_exc_syn_3conns (Type: gradedSynapse: conductance=3.0E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
DB1_to_MDL08_exc_syn_3conns (Type: gradedSynapse: conductance=3.0E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
DB1_to_MDL09_exc_syn_6conns (Type: gradedSynapse: conductance=6.0E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
DB1_to_MDR08_exc_syn_6conns (Type: gradedSynapse: conductance=6.0E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
DB1_to_MDR09_exc_syn_2conns (Type: gradedSynapse: conductance=2.0000000000000003E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
DB2_to_MDL09_exc_syn_2conns (Type: gradedSynapse: conductance=2.0000000000000003E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
DB2_to_MDL10_exc_syn_4conns (Type: gradedSynapse: conductance=4.0000000000000007E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
DB2_to_MDL11_exc_syn_5conns (Type: gradedSynapse: conductance=5.0E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
DB2_to_MDL12_exc_syn_1conns (Type: gradedSynapse: conductance=1.0000000000000002E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
DB2_to_MDR09_exc_syn_1conns (Type: gradedSynapse: conductance=1.0000000000000002E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
DB2_to_MDR10_exc_syn_6conns (Type: gradedSynapse: conductance=6.0E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
DB2_to_MDR11_exc_syn_8conns (Type: gradedSynapse: conductance=8.000000000000001E-10 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
neuron_to_muscle_exc_syn_13conns (Type: gradedSynapse: conductance=1.3E-9 (SI conductance) delta=0.019 (SI voltage) k=1205.0 (SI per_time) Vth=0.027 (SI voltage) erev=0.037 (SI voltage))
GenericMuscleCell (Type: cell)
GenericNeuronCell (Type: cell)
offset_current (Type: pulseGenerator: delay=0.0 (SI time) duration=2.0 (SI time) amplitude=0.0 (SI current))
stim_AVBL_1 (Type: pulseGenerator: delay=0.05 (SI time) duration=1.9000000000000001 (SI time) amplitude=1.5E-11 (SI current))
stim_AVBR_1 (Type: pulseGenerator: delay=0.05 (SI time) duration=1.9000000000000001 (SI time) amplitude=1.5E-11 (SI current))
stim_AS1_1 (Type: pulseGenerator: delay=0.05 (SI time) duration=1.9000000000000001 (SI time) amplitude=2.5E-12 (SI current))
stim_AS2_1 (Type: pulseGenerator: delay=0.05 (SI time) duration=1.9000000000000001 (SI time) amplitude=2.5E-12 (SI current))
stim_AS3_1 (Type: pulseGenerator: delay=0.05 (SI time) duration=1.9000000000000001 (SI time) amplitude=2.5E-12 (SI current))
stim_AS4_1 (Type: pulseGenerator: delay=0.05 (SI time) duration=1.9000000000000001 (SI time) amplitude=2.5E-12 (SI current))
stim_AS5_1 (Type: pulseGenerator: delay=0.05 (SI time) duration=1.9000000000000001 (SI time) amplitude=2.5E-12 (SI current))
stim_AS6_1 (Type: pulseGenerator: delay=0.05 (SI time) duration=1.9000000000000001 (SI time) amplitude=2.5E-12 (SI current))
stim_AS7_1 (Type: pulseGenerator: delay=0.05 (SI time) duration=1.9000000000000001 (SI time) amplitude=2.5E-12 (SI current))
stim_AS8_1 (Type: pulseGenerator: delay=0.05 (SI time) duration=1.9000000000000001 (SI time) amplitude=2.5E-12 (SI current))
stim_AS9_1 (Type: pulseGenerator: delay=0.05 (SI time) duration=1.9000000000000001 (SI time) amplitude=2.5E-12 (SI current))
stim_AS10_1 (Type: pulseGenerator: delay=0.05 (SI time) duration=1.9000000000000001 (SI time) amplitude=2.5E-12 (SI current))
stim_AS11_1 (Type: pulseGenerator: delay=0.05 (SI time) duration=1.9000000000000001 (SI time) amplitude=2.5E-12 (SI current))
c302_C2_AS_DA_DB (Type: network)
sim_c302_C2_AS_DA_DB (Type: Simulation: length=2.0 (SI time) step=5.0E-5 (SI time))
This NEURON file has been generated by org.neuroml.export (see https://github.com/NeuroML/org.neuroml.export)
org.neuroml.export v1.5.2
org.neuroml.model v1.5.2
jLEMS v0.9.8.9
'''
import neuron
import time
import hashlib
h = neuron.h
h.load_file("stdlib.hoc")
h.load_file("stdgui.hoc")
h("objref p")
h("p = new PythonObject()")
class NeuronSimulation():
def __init__(self, tstop, dt, seed=123456789):
print("\n Starting simulation in NEURON generated from NeuroML2 model...\n")
self.seed = seed
self.randoms = []
self.next_global_id = 0 # Used in Random123 classes for elements using random(), etc.
self.next_spiking_input_id = 0 # Used in Random123 classes for elements using random(), etc.
'''
Adding simulation Component(id=sim_c302_C2_AS_DA_DB type=Simulation) of network/component: c302_C2_AS_DA_DB (Type: network)
'''
# ###################### Population: AS1
print("Population AS1 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_AS1 = []
h("{ n_AS1 = 1 }")
h("objectvar a_AS1[n_AS1]")
for i in range(int(h.n_AS1)):
h("a_AS1[%i] = new GenericNeuronCell()"%i)
h("access a_AS1[%i].soma"%i)
self.next_global_id+=1
h("{ a_AS1[0].position(-0.275, -229.038000000000011, 4.738) }")
h("proc initialiseV_AS1() { for i = 0, n_AS1-1 { a_AS1[i].set_initial_v() } }")
h("objref fih_AS1")
h('{fih_AS1 = new FInitializeHandler(0, "initialiseV_AS1()")}')
h("proc initialiseIons_AS1() { for i = 0, n_AS1-1 { a_AS1[i].set_initial_ion_properties() } }")
h("objref fih_ion_AS1")
h('{fih_ion_AS1 = new FInitializeHandler(1, "initialiseIons_AS1()")}')
# ###################### Population: AS10
print("Population AS10 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_AS10 = []
h("{ n_AS10 = 1 }")
h("objectvar a_AS10[n_AS10]")
for i in range(int(h.n_AS10)):
h("a_AS10[%i] = new GenericNeuronCell()"%i)
h("access a_AS10[%i].soma"%i)
self.next_global_id+=1
h("{ a_AS10[0].position(-1.9, 278.25, -24.) }")
h("proc initialiseV_AS10() { for i = 0, n_AS10-1 { a_AS10[i].set_initial_v() } }")
h("objref fih_AS10")
h('{fih_AS10 = new FInitializeHandler(0, "initialiseV_AS10()")}')
h("proc initialiseIons_AS10() { for i = 0, n_AS10-1 { a_AS10[i].set_initial_ion_properties() } }")
h("objref fih_ion_AS10")
h('{fih_ion_AS10 = new FInitializeHandler(1, "initialiseIons_AS10()")}')
# ###################### Population: AS11
print("Population AS11 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_AS11 = []
h("{ n_AS11 = 1 }")
h("objectvar a_AS11[n_AS11]")
for i in range(int(h.n_AS11)):
h("a_AS11[%i] = new GenericNeuronCell()"%i)
h("access a_AS11[%i].soma"%i)
self.next_global_id+=1
h("{ a_AS11[0].position(-1.8750001, 315.699999999999989, -26.124998000000001) }")
h("proc initialiseV_AS11() { for i = 0, n_AS11-1 { a_AS11[i].set_initial_v() } }")
h("objref fih_AS11")
h('{fih_AS11 = new FInitializeHandler(0, "initialiseV_AS11()")}')
h("proc initialiseIons_AS11() { for i = 0, n_AS11-1 { a_AS11[i].set_initial_ion_properties() } }")
h("objref fih_ion_AS11")
h('{fih_ion_AS11 = new FInitializeHandler(1, "initialiseIons_AS11()")}')
# ###################### Population: AS2
print("Population AS2 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_AS2 = []
h("{ n_AS2 = 1 }")
h("objectvar a_AS2[n_AS2]")
for i in range(int(h.n_AS2)):
h("a_AS2[%i] = new GenericNeuronCell()"%i)
h("access a_AS2[%i].soma"%i)
self.next_global_id+=1
h("{ a_AS2[0].position(-1.8750001, -203.875, -12.725) }")
h("proc initialiseV_AS2() { for i = 0, n_AS2-1 { a_AS2[i].set_initial_v() } }")
h("objref fih_AS2")
h('{fih_AS2 = new FInitializeHandler(0, "initialiseV_AS2()")}')
h("proc initialiseIons_AS2() { for i = 0, n_AS2-1 { a_AS2[i].set_initial_ion_properties() } }")
h("objref fih_ion_AS2")
h('{fih_ion_AS2 = new FInitializeHandler(1, "initialiseIons_AS2()")}')
# ###################### Population: AS3
print("Population AS3 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_AS3 = []
h("{ n_AS3 = 1 }")
h("objectvar a_AS3[n_AS3]")
for i in range(int(h.n_AS3)):
h("a_AS3[%i] = new GenericNeuronCell()"%i)
h("access a_AS3[%i].soma"%i)
self.next_global_id+=1
h("{ a_AS3[0].position(-1.9, -151.400010000000009, -45.649997999999997) }")
h("proc initialiseV_AS3() { for i = 0, n_AS3-1 { a_AS3[i].set_initial_v() } }")
h("objref fih_AS3")
h('{fih_AS3 = new FInitializeHandler(0, "initialiseV_AS3()")}')
h("proc initialiseIons_AS3() { for i = 0, n_AS3-1 { a_AS3[i].set_initial_ion_properties() } }")
h("objref fih_ion_AS3")
h('{fih_ion_AS3 = new FInitializeHandler(1, "initialiseIons_AS3()")}')
# ###################### Population: AS4
print("Population AS4 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_AS4 = []
h("{ n_AS4 = 1 }")
h("objectvar a_AS4[n_AS4]")
for i in range(int(h.n_AS4)):
h("a_AS4[%i] = new GenericNeuronCell()"%i)
h("access a_AS4[%i].soma"%i)
self.next_global_id+=1
h("{ a_AS4[0].position(-1.8750001, -90.200005000000004, -65.375) }")
h("proc initialiseV_AS4() { for i = 0, n_AS4-1 { a_AS4[i].set_initial_v() } }")
h("objref fih_AS4")
h('{fih_AS4 = new FInitializeHandler(0, "initialiseV_AS4()")}')
h("proc initialiseIons_AS4() { for i = 0, n_AS4-1 { a_AS4[i].set_initial_ion_properties() } }")
h("objref fih_ion_AS4")
h('{fih_ion_AS4 = new FInitializeHandler(1, "initialiseIons_AS4()")}')
# ###################### Population: AS5
print("Population AS5 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_AS5 = []
h("{ n_AS5 = 1 }")
h("objectvar a_AS5[n_AS5]")
for i in range(int(h.n_AS5)):
h("a_AS5[%i] = new GenericNeuronCell()"%i)
h("access a_AS5[%i].soma"%i)
self.next_global_id+=1
h("{ a_AS5[0].position(-1.8750001, -3.7500002, -52.524999999999999) }")
h("proc initialiseV_AS5() { for i = 0, n_AS5-1 { a_AS5[i].set_initial_v() } }")
h("objref fih_AS5")
h('{fih_AS5 = new FInitializeHandler(0, "initialiseV_AS5()")}')
h("proc initialiseIons_AS5() { for i = 0, n_AS5-1 { a_AS5[i].set_initial_ion_properties() } }")
h("objref fih_ion_AS5")
h('{fih_ion_AS5 = new FInitializeHandler(1, "initialiseIons_AS5()")}')
# ###################### Population: AS6
print("Population AS6 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_AS6 = []
h("{ n_AS6 = 1 }")
h("objectvar a_AS6[n_AS6]")
for i in range(int(h.n_AS6)):
h("a_AS6[%i] = new GenericNeuronCell()"%i)
h("access a_AS6[%i].soma"%i)
self.next_global_id+=1
h("{ a_AS6[0].position(-1.9, 28.25, -34.25) }")
h("proc initialiseV_AS6() { for i = 0, n_AS6-1 { a_AS6[i].set_initial_v() } }")
h("objref fih_AS6")
h('{fih_AS6 = new FInitializeHandler(0, "initialiseV_AS6()")}')
h("proc initialiseIons_AS6() { for i = 0, n_AS6-1 { a_AS6[i].set_initial_ion_properties() } }")
h("objref fih_ion_AS6")
h('{fih_ion_AS6 = new FInitializeHandler(1, "initialiseIons_AS6()")}')
# ###################### Population: AS7
print("Population AS7 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_AS7 = []
h("{ n_AS7 = 1 }")
h("objectvar a_AS7[n_AS7]")
for i in range(int(h.n_AS7)):
h("a_AS7[%i] = new GenericNeuronCell()"%i)
h("access a_AS7[%i].soma"%i)
self.next_global_id+=1
h("{ a_AS7[0].position(-1.9, 119.900000000000006, 3.9500003) }")
h("proc initialiseV_AS7() { for i = 0, n_AS7-1 { a_AS7[i].set_initial_v() } }")
h("objref fih_AS7")
h('{fih_AS7 = new FInitializeHandler(0, "initialiseV_AS7()")}')
h("proc initialiseIons_AS7() { for i = 0, n_AS7-1 { a_AS7[i].set_initial_ion_properties() } }")
h("objref fih_ion_AS7")
h('{fih_ion_AS7 = new FInitializeHandler(1, "initialiseIons_AS7()")}')
# ###################### Population: AS8
print("Population AS8 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_AS8 = []
h("{ n_AS8 = 1 }")
h("objectvar a_AS8[n_AS8]")
for i in range(int(h.n_AS8)):
h("a_AS8[%i] = new GenericNeuronCell()"%i)
h("access a_AS8[%i].soma"%i)
self.next_global_id+=1
h("{ a_AS8[0].position(-1.9, 181.849999999999994, -1.7750001) }")
h("proc initialiseV_AS8() { for i = 0, n_AS8-1 { a_AS8[i].set_initial_v() } }")
h("objref fih_AS8")
h('{fih_AS8 = new FInitializeHandler(0, "initialiseV_AS8()")}')
h("proc initialiseIons_AS8() { for i = 0, n_AS8-1 { a_AS8[i].set_initial_ion_properties() } }")
h("objref fih_ion_AS8")
h('{fih_ion_AS8 = new FInitializeHandler(1, "initialiseIons_AS8()")}')
# ###################### Population: AS9
print("Population AS9 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_AS9 = []
h("{ n_AS9 = 1 }")
h("objectvar a_AS9[n_AS9]")
for i in range(int(h.n_AS9)):
h("a_AS9[%i] = new GenericNeuronCell()"%i)
h("access a_AS9[%i].soma"%i)
self.next_global_id+=1
h("{ a_AS9[0].position(-1.8750001, 228.924990000000008, -14.5) }")
h("proc initialiseV_AS9() { for i = 0, n_AS9-1 { a_AS9[i].set_initial_v() } }")
h("objref fih_AS9")
h('{fih_AS9 = new FInitializeHandler(0, "initialiseV_AS9()")}')
h("proc initialiseIons_AS9() { for i = 0, n_AS9-1 { a_AS9[i].set_initial_ion_properties() } }")
h("objref fih_ion_AS9")
h('{fih_ion_AS9 = new FInitializeHandler(1, "initialiseIons_AS9()")}')
# ###################### Population: AVAL
print("Population AVAL contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_AVAL = []
h("{ n_AVAL = 1 }")
h("objectvar a_AVAL[n_AVAL]")
for i in range(int(h.n_AVAL)):
h("a_AVAL[%i] = new GenericNeuronCell()"%i)
h("access a_AVAL[%i].soma"%i)
self.next_global_id+=1
h("{ a_AVAL[0].position(-0.55, -271.5, 37.982999999999997) }")
h("proc initialiseV_AVAL() { for i = 0, n_AVAL-1 { a_AVAL[i].set_initial_v() } }")
h("objref fih_AVAL")
h('{fih_AVAL = new FInitializeHandler(0, "initialiseV_AVAL()")}')
h("proc initialiseIons_AVAL() { for i = 0, n_AVAL-1 { a_AVAL[i].set_initial_ion_properties() } }")
h("objref fih_ion_AVAL")
h('{fih_ion_AVAL = new FInitializeHandler(1, "initialiseIons_AVAL()")}')
# ###################### Population: AVAR
print("Population AVAR contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_AVAR = []
h("{ n_AVAR = 1 }")
h("objectvar a_AVAR[n_AVAR]")
for i in range(int(h.n_AVAR)):
h("a_AVAR[%i] = new GenericNeuronCell()"%i)
h("access a_AVAR[%i].soma"%i)
self.next_global_id+=1
h("{ a_AVAR[0].position(-3.5, -271.5, 37.982999999999997) }")
h("proc initialiseV_AVAR() { for i = 0, n_AVAR-1 { a_AVAR[i].set_initial_v() } }")
h("objref fih_AVAR")
h('{fih_AVAR = new FInitializeHandler(0, "initialiseV_AVAR()")}')
h("proc initialiseIons_AVAR() { for i = 0, n_AVAR-1 { a_AVAR[i].set_initial_ion_properties() } }")
h("objref fih_ion_AVAR")
h('{fih_ion_AVAR = new FInitializeHandler(1, "initialiseIons_AVAR()")}')
# ###################### Population: AVBL
print("Population AVBL contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_AVBL = []
h("{ n_AVBL = 1 }")
h("objectvar a_AVBL[n_AVBL]")
for i in range(int(h.n_AVBL)):
h("a_AVBL[%i] = new GenericNeuronCell()"%i)
h("access a_AVBL[%i].soma"%i)
self.next_global_id+=1
h("{ a_AVBL[0].position(0.225, -269.793999999999983, 37.863002999999999) }")
h("proc initialiseV_AVBL() { for i = 0, n_AVBL-1 { a_AVBL[i].set_initial_v() } }")
h("objref fih_AVBL")
h('{fih_AVBL = new FInitializeHandler(0, "initialiseV_AVBL()")}')
h("proc initialiseIons_AVBL() { for i = 0, n_AVBL-1 { a_AVBL[i].set_initial_ion_properties() } }")
h("objref fih_ion_AVBL")
h('{fih_ion_AVBL = new FInitializeHandler(1, "initialiseIons_AVBL()")}')
# ###################### Population: AVBR
print("Population AVBR contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_AVBR = []
h("{ n_AVBR = 1 }")
h("objectvar a_AVBR[n_AVBR]")
for i in range(int(h.n_AVBR)):
h("a_AVBR[%i] = new GenericNeuronCell()"%i)
h("access a_AVBR[%i].soma"%i)
self.next_global_id+=1
h("{ a_AVBR[0].position(-4.581, -269.793999999999983, 37.863002999999999) }")
h("proc initialiseV_AVBR() { for i = 0, n_AVBR-1 { a_AVBR[i].set_initial_v() } }")
h("objref fih_AVBR")
h('{fih_AVBR = new FInitializeHandler(0, "initialiseV_AVBR()")}')
h("proc initialiseIons_AVBR() { for i = 0, n_AVBR-1 { a_AVBR[i].set_initial_ion_properties() } }")
h("objref fih_ion_AVBR")
h('{fih_ion_AVBR = new FInitializeHandler(1, "initialiseIons_AVBR()")}')
# ###################### Population: DA1
print("Population DA1 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_DA1 = []
h("{ n_DA1 = 1 }")
h("objectvar a_DA1[n_DA1]")
for i in range(int(h.n_DA1)):
h("a_DA1[%i] = new GenericNeuronCell()"%i)
h("access a_DA1[%i].soma"%i)
self.next_global_id+=1
h("{ a_DA1[0].position(-0.75, -227.075009999999992, 3.425) }")
h("proc initialiseV_DA1() { for i = 0, n_DA1-1 { a_DA1[i].set_initial_v() } }")
h("objref fih_DA1")
h('{fih_DA1 = new FInitializeHandler(0, "initialiseV_DA1()")}')
h("proc initialiseIons_DA1() { for i = 0, n_DA1-1 { a_DA1[i].set_initial_ion_properties() } }")
h("objref fih_ion_DA1")
h('{fih_ion_DA1 = new FInitializeHandler(1, "initialiseIons_DA1()")}')
# ###################### Population: DA2
print("Population DA2 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_DA2 = []
h("{ n_DA2 = 1 }")
h("objectvar a_DA2[n_DA2]")
for i in range(int(h.n_DA2)):
h("a_DA2[%i] = new GenericNeuronCell()"%i)
h("access a_DA2[%i].soma"%i)
self.next_global_id+=1
h("{ a_DA2[0].position(-1.9, -190.75, -21.675000000000001) }")
h("proc initialiseV_DA2() { for i = 0, n_DA2-1 { a_DA2[i].set_initial_v() } }")
h("objref fih_DA2")
h('{fih_DA2 = new FInitializeHandler(0, "initialiseV_DA2()")}')
h("proc initialiseIons_DA2() { for i = 0, n_DA2-1 { a_DA2[i].set_initial_ion_properties() } }")
h("objref fih_ion_DA2")
h('{fih_ion_DA2 = new FInitializeHandler(1, "initialiseIons_DA2()")}')
# ###################### Population: DA3
print("Population DA3 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_DA3 = []
h("{ n_DA3 = 1 }")
h("objectvar a_DA3[n_DA3]")
for i in range(int(h.n_DA3)):
h("a_DA3[%i] = new GenericNeuronCell()"%i)
h("access a_DA3[%i].soma"%i)
self.next_global_id+=1
h("{ a_DA3[0].position(-1.65, -123.650000000000006, -58.350002000000003) }")
h("proc initialiseV_DA3() { for i = 0, n_DA3-1 { a_DA3[i].set_initial_v() } }")
h("objref fih_DA3")
h('{fih_DA3 = new FInitializeHandler(0, "initialiseV_DA3()")}')
h("proc initialiseIons_DA3() { for i = 0, n_DA3-1 { a_DA3[i].set_initial_ion_properties() } }")
h("objref fih_ion_DA3")
h('{fih_ion_DA3 = new FInitializeHandler(1, "initialiseIons_DA3()")}')
# ###################### Population: DA4
print("Population DA4 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_DA4 = []
h("{ n_DA4 = 1 }")
h("objectvar a_DA4[n_DA4]")
for i in range(int(h.n_DA4)):
h("a_DA4[%i] = new GenericNeuronCell()"%i)
h("access a_DA4[%i].soma"%i)
self.next_global_id+=1
h("{ a_DA4[0].position(-1.7, -32.399999999999999, -61.75) }")
h("proc initialiseV_DA4() { for i = 0, n_DA4-1 { a_DA4[i].set_initial_v() } }")
h("objref fih_DA4")
h('{fih_DA4 = new FInitializeHandler(0, "initialiseV_DA4()")}')
h("proc initialiseIons_DA4() { for i = 0, n_DA4-1 { a_DA4[i].set_initial_ion_properties() } }")
h("objref fih_ion_DA4")
h('{fih_ion_DA4 = new FInitializeHandler(1, "initialiseIons_DA4()")}')
# ###################### Population: DA5
print("Population DA5 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_DA5 = []
h("{ n_DA5 = 1 }")
h("objectvar a_DA5[n_DA5]")
for i in range(int(h.n_DA5)):
h("a_DA5[%i] = new GenericNeuronCell()"%i)
h("access a_DA5[%i].soma"%i)
self.next_global_id+=1
h("{ a_DA5[0].position(-1.65, 84.200000000000003, -3.15) }")
h("proc initialiseV_DA5() { for i = 0, n_DA5-1 { a_DA5[i].set_initial_v() } }")
h("objref fih_DA5")
h('{fih_DA5 = new FInitializeHandler(0, "initialiseV_DA5()")}')
h("proc initialiseIons_DA5() { for i = 0, n_DA5-1 { a_DA5[i].set_initial_ion_properties() } }")
h("objref fih_ion_DA5")
h('{fih_ion_DA5 = new FInitializeHandler(1, "initialiseIons_DA5()")}')
# ###################### Population: DA6
print("Population DA6 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_DA6 = []
h("{ n_DA6 = 1 }")
h("objectvar a_DA6[n_DA6]")
for i in range(int(h.n_DA6)):
h("a_DA6[%i] = new GenericNeuronCell()"%i)
h("access a_DA6[%i].soma"%i)
self.next_global_id+=1
h("{ a_DA6[0].position(-1.65, 198.675000000000011, -6.3500004) }")
h("proc initialiseV_DA6() { for i = 0, n_DA6-1 { a_DA6[i].set_initial_v() } }")
h("objref fih_DA6")
h('{fih_DA6 = new FInitializeHandler(0, "initialiseV_DA6()")}')
h("proc initialiseIons_DA6() { for i = 0, n_DA6-1 { a_DA6[i].set_initial_ion_properties() } }")
h("objref fih_ion_DA6")
h('{fih_ion_DA6 = new FInitializeHandler(1, "initialiseIons_DA6()")}')
# ###################### Population: DA7
print("Population DA7 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_DA7 = []
h("{ n_DA7 = 1 }")
h("objectvar a_DA7[n_DA7]")
for i in range(int(h.n_DA7)):
h("a_DA7[%i] = new GenericNeuronCell()"%i)
h("access a_DA7[%i].soma"%i)
self.next_global_id+=1
h("{ a_DA7[0].position(-1.65, 281.600000000000023, -24.949999999999999) }")
h("proc initialiseV_DA7() { for i = 0, n_DA7-1 { a_DA7[i].set_initial_v() } }")
h("objref fih_DA7")
h('{fih_DA7 = new FInitializeHandler(0, "initialiseV_DA7()")}')
h("proc initialiseIons_DA7() { for i = 0, n_DA7-1 { a_DA7[i].set_initial_ion_properties() } }")
h("objref fih_ion_DA7")
h('{fih_ion_DA7 = new FInitializeHandler(1, "initialiseIons_DA7()")}')
# ###################### Population: DA8
print("Population DA8 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_DA8 = []
h("{ n_DA8 = 1 }")
h("objectvar a_DA8[n_DA8]")
for i in range(int(h.n_DA8)):
h("a_DA8[%i] = new GenericNeuronCell()"%i)
h("access a_DA8[%i].soma"%i)
self.next_global_id+=1
h("{ a_DA8[0].position(1.275, 376.800000000000011, -10.925000000000001) }")
h("proc initialiseV_DA8() { for i = 0, n_DA8-1 { a_DA8[i].set_initial_v() } }")
h("objref fih_DA8")
h('{fih_DA8 = new FInitializeHandler(0, "initialiseV_DA8()")}')
h("proc initialiseIons_DA8() { for i = 0, n_DA8-1 { a_DA8[i].set_initial_ion_properties() } }")
h("objref fih_ion_DA8")
h('{fih_ion_DA8 = new FInitializeHandler(1, "initialiseIons_DA8()")}')
# ###################### Population: DA9
print("Population DA9 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_DA9 = []
h("{ n_DA9 = 1 }")
h("objectvar a_DA9[n_DA9]")
for i in range(int(h.n_DA9)):
h("a_DA9[%i] = new GenericNeuronCell()"%i)
h("access a_DA9[%i].soma"%i)
self.next_global_id+=1
h("{ a_DA9[0].position(-4.6, 376.800000000000011, -10.925000000000001) }")
h("proc initialiseV_DA9() { for i = 0, n_DA9-1 { a_DA9[i].set_initial_v() } }")
h("objref fih_DA9")
h('{fih_DA9 = new FInitializeHandler(0, "initialiseV_DA9()")}')
h("proc initialiseIons_DA9() { for i = 0, n_DA9-1 { a_DA9[i].set_initial_ion_properties() } }")
h("objref fih_ion_DA9")
h('{fih_ion_DA9 = new FInitializeHandler(1, "initialiseIons_DA9()")}')
# ###################### Population: DB1
print("Population DB1 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_DB1 = []
h("{ n_DB1 = 1 }")
h("objectvar a_DB1[n_DB1]")
for i in range(int(h.n_DB1)):
h("a_DB1[%i] = new GenericNeuronCell()"%i)
h("access a_DB1[%i].soma"%i)
self.next_global_id+=1
h("{ a_DB1[0].position(-1.9, -230.349989999999991, 6.85) }")
h("proc initialiseV_DB1() { for i = 0, n_DB1-1 { a_DB1[i].set_initial_v() } }")
h("objref fih_DB1")
h('{fih_DB1 = new FInitializeHandler(0, "initialiseV_DB1()")}')
h("proc initialiseIons_DB1() { for i = 0, n_DB1-1 { a_DB1[i].set_initial_ion_properties() } }")
h("objref fih_ion_DB1")
h('{fih_ion_DB1 = new FInitializeHandler(1, "initialiseIons_DB1()")}')
# ###################### Population: DB2
print("Population DB2 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_DB2 = []
h("{ n_DB2 = 1 }")
h("objectvar a_DB2[n_DB2]")
for i in range(int(h.n_DB2)):
h("a_DB2[%i] = new GenericNeuronCell()"%i)
h("access a_DB2[%i].soma"%i)
self.next_global_id+=1
h("{ a_DB2[0].position(-0.2, -244.5, 15.787000000000001) }")
h("proc initialiseV_DB2() { for i = 0, n_DB2-1 { a_DB2[i].set_initial_v() } }")
h("objref fih_DB2")
h('{fih_DB2 = new FInitializeHandler(0, "initialiseV_DB2()")}')
h("proc initialiseIons_DB2() { for i = 0, n_DB2-1 { a_DB2[i].set_initial_ion_properties() } }")
h("objref fih_ion_DB2")
h('{fih_ion_DB2 = new FInitializeHandler(1, "initialiseIons_DB2()")}')
# ###################### Population: DB3
print("Population DB3 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_DB3 = []
h("{ n_DB3 = 1 }")
h("objectvar a_DB3[n_DB3]")
for i in range(int(h.n_DB3)):
h("a_DB3[%i] = new GenericNeuronCell()"%i)
h("access a_DB3[%i].soma"%i)
self.next_global_id+=1
h("{ a_DB3[0].position(-1.85, -195.275000000000006, -18.524999999999999) }")
h("proc initialiseV_DB3() { for i = 0, n_DB3-1 { a_DB3[i].set_initial_v() } }")
h("objref fih_DB3")
h('{fih_DB3 = new FInitializeHandler(0, "initialiseV_DB3()")}')
h("proc initialiseIons_DB3() { for i = 0, n_DB3-1 { a_DB3[i].set_initial_ion_properties() } }")
h("objref fih_ion_DB3")
h('{fih_ion_DB3 = new FInitializeHandler(1, "initialiseIons_DB3()")}')
# ###################### Population: DB4
print("Population DB4 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_DB4 = []
h("{ n_DB4 = 1 }")
h("objectvar a_DB4[n_DB4]")
for i in range(int(h.n_DB4)):
h("a_DB4[%i] = new GenericNeuronCell()"%i)
h("access a_DB4[%i].soma"%i)
self.next_global_id+=1
h("{ a_DB4[0].position(-1.8750001, -96.275000000000006, -64.650000000000006) }")
h("proc initialiseV_DB4() { for i = 0, n_DB4-1 { a_DB4[i].set_initial_v() } }")
h("objref fih_DB4")
h('{fih_DB4 = new FInitializeHandler(0, "initialiseV_DB4()")}')
h("proc initialiseIons_DB4() { for i = 0, n_DB4-1 { a_DB4[i].set_initial_ion_properties() } }")
h("objref fih_ion_DB4")
h('{fih_ion_DB4 = new FInitializeHandler(1, "initialiseIons_DB4()")}')
# ###################### Population: DB5
print("Population DB5 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_DB5 = []
h("{ n_DB5 = 1 }")
h("objectvar a_DB5[n_DB5]")
for i in range(int(h.n_DB5)):
h("a_DB5[%i] = new GenericNeuronCell()"%i)
h("access a_DB5[%i].soma"%i)
self.next_global_id+=1
h("{ a_DB5[0].position(-4.05, 35.25, -30.449999999999999) }")
h("proc initialiseV_DB5() { for i = 0, n_DB5-1 { a_DB5[i].set_initial_v() } }")
h("objref fih_DB5")
h('{fih_DB5 = new FInitializeHandler(0, "initialiseV_DB5()")}')
h("proc initialiseIons_DB5() { for i = 0, n_DB5-1 { a_DB5[i].set_initial_ion_properties() } }")
h("objref fih_ion_DB5")
h('{fih_ion_DB5 = new FInitializeHandler(1, "initialiseIons_DB5()")}')
# ###################### Population: DB6
print("Population DB6 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_DB6 = []
h("{ n_DB6 = 1 }")
h("objectvar a_DB6[n_DB6]")
for i in range(int(h.n_DB6)):
h("a_DB6[%i] = new GenericNeuronCell()"%i)
h("access a_DB6[%i].soma"%i)
self.next_global_id+=1
h("{ a_DB6[0].position(-1.8249999, 178.099999999999994, -0.2) }")
h("proc initialiseV_DB6() { for i = 0, n_DB6-1 { a_DB6[i].set_initial_v() } }")
h("objref fih_DB6")
h('{fih_DB6 = new FInitializeHandler(0, "initialiseV_DB6()")}')
h("proc initialiseIons_DB6() { for i = 0, n_DB6-1 { a_DB6[i].set_initial_ion_properties() } }")
h("objref fih_ion_DB6")
h('{fih_ion_DB6 = new FInitializeHandler(1, "initialiseIons_DB6()")}')
# ###################### Population: DB7
print("Population DB7 contains 1 instance(s) of component: GenericNeuronCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericNeuronCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericNeuronCell.hoc")
a_DB7 = []
h("{ n_DB7 = 1 }")
h("objectvar a_DB7[n_DB7]")
for i in range(int(h.n_DB7)):
h("a_DB7[%i] = new GenericNeuronCell()"%i)
h("access a_DB7[%i].soma"%i)
self.next_global_id+=1
h("{ a_DB7[0].position(-1.85, 267.75, -22.625) }")
h("proc initialiseV_DB7() { for i = 0, n_DB7-1 { a_DB7[i].set_initial_v() } }")
h("objref fih_DB7")
h('{fih_DB7 = new FInitializeHandler(0, "initialiseV_DB7()")}')
h("proc initialiseIons_DB7() { for i = 0, n_DB7-1 { a_DB7[i].set_initial_ion_properties() } }")
h("objref fih_ion_DB7")
h('{fih_ion_DB7 = new FInitializeHandler(1, "initialiseIons_DB7()")}')
# ###################### Population: MDR01
print("Population MDR01 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR01 = []
h("{ n_MDR01 = 1 }")
h("objectvar a_MDR01[n_MDR01]")
for i in range(int(h.n_MDR01)):
h("a_MDR01[%i] = new GenericMuscleCell()"%i)
h("access a_MDR01[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR01[0].position(80., -270., 80.) }")
h("proc initialiseV_MDR01() { for i = 0, n_MDR01-1 { a_MDR01[i].set_initial_v() } }")
h("objref fih_MDR01")
h('{fih_MDR01 = new FInitializeHandler(0, "initialiseV_MDR01()")}')
h("proc initialiseIons_MDR01() { for i = 0, n_MDR01-1 { a_MDR01[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR01")
h('{fih_ion_MDR01 = new FInitializeHandler(1, "initialiseIons_MDR01()")}')
# ###################### Population: MDR02
print("Population MDR02 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR02 = []
h("{ n_MDR02 = 1 }")
h("objectvar a_MDR02[n_MDR02]")
for i in range(int(h.n_MDR02)):
h("a_MDR02[%i] = new GenericMuscleCell()"%i)
h("access a_MDR02[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR02[0].position(80., -240., 80.) }")
h("proc initialiseV_MDR02() { for i = 0, n_MDR02-1 { a_MDR02[i].set_initial_v() } }")
h("objref fih_MDR02")
h('{fih_MDR02 = new FInitializeHandler(0, "initialiseV_MDR02()")}')
h("proc initialiseIons_MDR02() { for i = 0, n_MDR02-1 { a_MDR02[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR02")
h('{fih_ion_MDR02 = new FInitializeHandler(1, "initialiseIons_MDR02()")}')
# ###################### Population: MDR03
print("Population MDR03 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR03 = []
h("{ n_MDR03 = 1 }")
h("objectvar a_MDR03[n_MDR03]")
for i in range(int(h.n_MDR03)):
h("a_MDR03[%i] = new GenericMuscleCell()"%i)
h("access a_MDR03[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR03[0].position(80., -210., 80.) }")
h("proc initialiseV_MDR03() { for i = 0, n_MDR03-1 { a_MDR03[i].set_initial_v() } }")
h("objref fih_MDR03")
h('{fih_MDR03 = new FInitializeHandler(0, "initialiseV_MDR03()")}')
h("proc initialiseIons_MDR03() { for i = 0, n_MDR03-1 { a_MDR03[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR03")
h('{fih_ion_MDR03 = new FInitializeHandler(1, "initialiseIons_MDR03()")}')
# ###################### Population: MDR04
print("Population MDR04 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR04 = []
h("{ n_MDR04 = 1 }")
h("objectvar a_MDR04[n_MDR04]")
for i in range(int(h.n_MDR04)):
h("a_MDR04[%i] = new GenericMuscleCell()"%i)
h("access a_MDR04[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR04[0].position(80., -180., 80.) }")
h("proc initialiseV_MDR04() { for i = 0, n_MDR04-1 { a_MDR04[i].set_initial_v() } }")
h("objref fih_MDR04")
h('{fih_MDR04 = new FInitializeHandler(0, "initialiseV_MDR04()")}')
h("proc initialiseIons_MDR04() { for i = 0, n_MDR04-1 { a_MDR04[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR04")
h('{fih_ion_MDR04 = new FInitializeHandler(1, "initialiseIons_MDR04()")}')
# ###################### Population: MDR05
print("Population MDR05 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR05 = []
h("{ n_MDR05 = 1 }")
h("objectvar a_MDR05[n_MDR05]")
for i in range(int(h.n_MDR05)):
h("a_MDR05[%i] = new GenericMuscleCell()"%i)
h("access a_MDR05[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR05[0].position(80., -150., 80.) }")
h("proc initialiseV_MDR05() { for i = 0, n_MDR05-1 { a_MDR05[i].set_initial_v() } }")
h("objref fih_MDR05")
h('{fih_MDR05 = new FInitializeHandler(0, "initialiseV_MDR05()")}')
h("proc initialiseIons_MDR05() { for i = 0, n_MDR05-1 { a_MDR05[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR05")
h('{fih_ion_MDR05 = new FInitializeHandler(1, "initialiseIons_MDR05()")}')
# ###################### Population: MDR06
print("Population MDR06 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR06 = []
h("{ n_MDR06 = 1 }")
h("objectvar a_MDR06[n_MDR06]")
for i in range(int(h.n_MDR06)):
h("a_MDR06[%i] = new GenericMuscleCell()"%i)
h("access a_MDR06[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR06[0].position(80., -120., 80.) }")
h("proc initialiseV_MDR06() { for i = 0, n_MDR06-1 { a_MDR06[i].set_initial_v() } }")
h("objref fih_MDR06")
h('{fih_MDR06 = new FInitializeHandler(0, "initialiseV_MDR06()")}')
h("proc initialiseIons_MDR06() { for i = 0, n_MDR06-1 { a_MDR06[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR06")
h('{fih_ion_MDR06 = new FInitializeHandler(1, "initialiseIons_MDR06()")}')
# ###################### Population: MDR07
print("Population MDR07 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR07 = []
h("{ n_MDR07 = 1 }")
h("objectvar a_MDR07[n_MDR07]")
for i in range(int(h.n_MDR07)):
h("a_MDR07[%i] = new GenericMuscleCell()"%i)
h("access a_MDR07[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR07[0].position(80., -90., 80.) }")
h("proc initialiseV_MDR07() { for i = 0, n_MDR07-1 { a_MDR07[i].set_initial_v() } }")
h("objref fih_MDR07")
h('{fih_MDR07 = new FInitializeHandler(0, "initialiseV_MDR07()")}')
h("proc initialiseIons_MDR07() { for i = 0, n_MDR07-1 { a_MDR07[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR07")
h('{fih_ion_MDR07 = new FInitializeHandler(1, "initialiseIons_MDR07()")}')
# ###################### Population: MDR08
print("Population MDR08 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR08 = []
h("{ n_MDR08 = 1 }")
h("objectvar a_MDR08[n_MDR08]")
for i in range(int(h.n_MDR08)):
h("a_MDR08[%i] = new GenericMuscleCell()"%i)
h("access a_MDR08[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR08[0].position(80., -60., 80.) }")
h("proc initialiseV_MDR08() { for i = 0, n_MDR08-1 { a_MDR08[i].set_initial_v() } }")
h("objref fih_MDR08")
h('{fih_MDR08 = new FInitializeHandler(0, "initialiseV_MDR08()")}')
h("proc initialiseIons_MDR08() { for i = 0, n_MDR08-1 { a_MDR08[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR08")
h('{fih_ion_MDR08 = new FInitializeHandler(1, "initialiseIons_MDR08()")}')
# ###################### Population: MDR09
print("Population MDR09 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR09 = []
h("{ n_MDR09 = 1 }")
h("objectvar a_MDR09[n_MDR09]")
for i in range(int(h.n_MDR09)):
h("a_MDR09[%i] = new GenericMuscleCell()"%i)
h("access a_MDR09[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR09[0].position(80., -30., 80.) }")
h("proc initialiseV_MDR09() { for i = 0, n_MDR09-1 { a_MDR09[i].set_initial_v() } }")
h("objref fih_MDR09")
h('{fih_MDR09 = new FInitializeHandler(0, "initialiseV_MDR09()")}')
h("proc initialiseIons_MDR09() { for i = 0, n_MDR09-1 { a_MDR09[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR09")
h('{fih_ion_MDR09 = new FInitializeHandler(1, "initialiseIons_MDR09()")}')
# ###################### Population: MDR10
print("Population MDR10 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR10 = []
h("{ n_MDR10 = 1 }")
h("objectvar a_MDR10[n_MDR10]")
for i in range(int(h.n_MDR10)):
h("a_MDR10[%i] = new GenericMuscleCell()"%i)
h("access a_MDR10[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR10[0].position(80., 0., 80.) }")
h("proc initialiseV_MDR10() { for i = 0, n_MDR10-1 { a_MDR10[i].set_initial_v() } }")
h("objref fih_MDR10")
h('{fih_MDR10 = new FInitializeHandler(0, "initialiseV_MDR10()")}')
h("proc initialiseIons_MDR10() { for i = 0, n_MDR10-1 { a_MDR10[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR10")
h('{fih_ion_MDR10 = new FInitializeHandler(1, "initialiseIons_MDR10()")}')
# ###################### Population: MDR11
print("Population MDR11 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR11 = []
h("{ n_MDR11 = 1 }")
h("objectvar a_MDR11[n_MDR11]")
for i in range(int(h.n_MDR11)):
h("a_MDR11[%i] = new GenericMuscleCell()"%i)
h("access a_MDR11[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR11[0].position(80., 30., 80.) }")
h("proc initialiseV_MDR11() { for i = 0, n_MDR11-1 { a_MDR11[i].set_initial_v() } }")
h("objref fih_MDR11")
h('{fih_MDR11 = new FInitializeHandler(0, "initialiseV_MDR11()")}')
h("proc initialiseIons_MDR11() { for i = 0, n_MDR11-1 { a_MDR11[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR11")
h('{fih_ion_MDR11 = new FInitializeHandler(1, "initialiseIons_MDR11()")}')
# ###################### Population: MDR12
print("Population MDR12 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR12 = []
h("{ n_MDR12 = 1 }")
h("objectvar a_MDR12[n_MDR12]")
for i in range(int(h.n_MDR12)):
h("a_MDR12[%i] = new GenericMuscleCell()"%i)
h("access a_MDR12[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR12[0].position(80., 60., 80.) }")
h("proc initialiseV_MDR12() { for i = 0, n_MDR12-1 { a_MDR12[i].set_initial_v() } }")
h("objref fih_MDR12")
h('{fih_MDR12 = new FInitializeHandler(0, "initialiseV_MDR12()")}')
h("proc initialiseIons_MDR12() { for i = 0, n_MDR12-1 { a_MDR12[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR12")
h('{fih_ion_MDR12 = new FInitializeHandler(1, "initialiseIons_MDR12()")}')
# ###################### Population: MDR13
print("Population MDR13 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR13 = []
h("{ n_MDR13 = 1 }")
h("objectvar a_MDR13[n_MDR13]")
for i in range(int(h.n_MDR13)):
h("a_MDR13[%i] = new GenericMuscleCell()"%i)
h("access a_MDR13[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR13[0].position(80., 90., 80.) }")
h("proc initialiseV_MDR13() { for i = 0, n_MDR13-1 { a_MDR13[i].set_initial_v() } }")
h("objref fih_MDR13")
h('{fih_MDR13 = new FInitializeHandler(0, "initialiseV_MDR13()")}')
h("proc initialiseIons_MDR13() { for i = 0, n_MDR13-1 { a_MDR13[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR13")
h('{fih_ion_MDR13 = new FInitializeHandler(1, "initialiseIons_MDR13()")}')
# ###################### Population: MDR14
print("Population MDR14 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR14 = []
h("{ n_MDR14 = 1 }")
h("objectvar a_MDR14[n_MDR14]")
for i in range(int(h.n_MDR14)):
h("a_MDR14[%i] = new GenericMuscleCell()"%i)
h("access a_MDR14[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR14[0].position(80., 120., 80.) }")
h("proc initialiseV_MDR14() { for i = 0, n_MDR14-1 { a_MDR14[i].set_initial_v() } }")
h("objref fih_MDR14")
h('{fih_MDR14 = new FInitializeHandler(0, "initialiseV_MDR14()")}')
h("proc initialiseIons_MDR14() { for i = 0, n_MDR14-1 { a_MDR14[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR14")
h('{fih_ion_MDR14 = new FInitializeHandler(1, "initialiseIons_MDR14()")}')
# ###################### Population: MDR15
print("Population MDR15 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR15 = []
h("{ n_MDR15 = 1 }")
h("objectvar a_MDR15[n_MDR15]")
for i in range(int(h.n_MDR15)):
h("a_MDR15[%i] = new GenericMuscleCell()"%i)
h("access a_MDR15[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR15[0].position(80., 150., 80.) }")
h("proc initialiseV_MDR15() { for i = 0, n_MDR15-1 { a_MDR15[i].set_initial_v() } }")
h("objref fih_MDR15")
h('{fih_MDR15 = new FInitializeHandler(0, "initialiseV_MDR15()")}')
h("proc initialiseIons_MDR15() { for i = 0, n_MDR15-1 { a_MDR15[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR15")
h('{fih_ion_MDR15 = new FInitializeHandler(1, "initialiseIons_MDR15()")}')
# ###################### Population: MDR16
print("Population MDR16 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR16 = []
h("{ n_MDR16 = 1 }")
h("objectvar a_MDR16[n_MDR16]")
for i in range(int(h.n_MDR16)):
h("a_MDR16[%i] = new GenericMuscleCell()"%i)
h("access a_MDR16[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR16[0].position(80., 180., 80.) }")
h("proc initialiseV_MDR16() { for i = 0, n_MDR16-1 { a_MDR16[i].set_initial_v() } }")
h("objref fih_MDR16")
h('{fih_MDR16 = new FInitializeHandler(0, "initialiseV_MDR16()")}')
h("proc initialiseIons_MDR16() { for i = 0, n_MDR16-1 { a_MDR16[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR16")
h('{fih_ion_MDR16 = new FInitializeHandler(1, "initialiseIons_MDR16()")}')
# ###################### Population: MDR17
print("Population MDR17 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR17 = []
h("{ n_MDR17 = 1 }")
h("objectvar a_MDR17[n_MDR17]")
for i in range(int(h.n_MDR17)):
h("a_MDR17[%i] = new GenericMuscleCell()"%i)
h("access a_MDR17[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR17[0].position(80., 210., 80.) }")
h("proc initialiseV_MDR17() { for i = 0, n_MDR17-1 { a_MDR17[i].set_initial_v() } }")
h("objref fih_MDR17")
h('{fih_MDR17 = new FInitializeHandler(0, "initialiseV_MDR17()")}')
h("proc initialiseIons_MDR17() { for i = 0, n_MDR17-1 { a_MDR17[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR17")
h('{fih_ion_MDR17 = new FInitializeHandler(1, "initialiseIons_MDR17()")}')
# ###################### Population: MDR18
print("Population MDR18 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR18 = []
h("{ n_MDR18 = 1 }")
h("objectvar a_MDR18[n_MDR18]")
for i in range(int(h.n_MDR18)):
h("a_MDR18[%i] = new GenericMuscleCell()"%i)
h("access a_MDR18[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR18[0].position(80., 240., 80.) }")
h("proc initialiseV_MDR18() { for i = 0, n_MDR18-1 { a_MDR18[i].set_initial_v() } }")
h("objref fih_MDR18")
h('{fih_MDR18 = new FInitializeHandler(0, "initialiseV_MDR18()")}')
h("proc initialiseIons_MDR18() { for i = 0, n_MDR18-1 { a_MDR18[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR18")
h('{fih_ion_MDR18 = new FInitializeHandler(1, "initialiseIons_MDR18()")}')
# ###################### Population: MDR19
print("Population MDR19 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR19 = []
h("{ n_MDR19 = 1 }")
h("objectvar a_MDR19[n_MDR19]")
for i in range(int(h.n_MDR19)):
h("a_MDR19[%i] = new GenericMuscleCell()"%i)
h("access a_MDR19[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR19[0].position(80., 270., 80.) }")
h("proc initialiseV_MDR19() { for i = 0, n_MDR19-1 { a_MDR19[i].set_initial_v() } }")
h("objref fih_MDR19")
h('{fih_MDR19 = new FInitializeHandler(0, "initialiseV_MDR19()")}')
h("proc initialiseIons_MDR19() { for i = 0, n_MDR19-1 { a_MDR19[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR19")
h('{fih_ion_MDR19 = new FInitializeHandler(1, "initialiseIons_MDR19()")}')
# ###################### Population: MDR20
print("Population MDR20 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR20 = []
h("{ n_MDR20 = 1 }")
h("objectvar a_MDR20[n_MDR20]")
for i in range(int(h.n_MDR20)):
h("a_MDR20[%i] = new GenericMuscleCell()"%i)
h("access a_MDR20[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR20[0].position(80., 300., 80.) }")
h("proc initialiseV_MDR20() { for i = 0, n_MDR20-1 { a_MDR20[i].set_initial_v() } }")
h("objref fih_MDR20")
h('{fih_MDR20 = new FInitializeHandler(0, "initialiseV_MDR20()")}')
h("proc initialiseIons_MDR20() { for i = 0, n_MDR20-1 { a_MDR20[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR20")
h('{fih_ion_MDR20 = new FInitializeHandler(1, "initialiseIons_MDR20()")}')
# ###################### Population: MDR21
print("Population MDR21 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR21 = []
h("{ n_MDR21 = 1 }")
h("objectvar a_MDR21[n_MDR21]")
for i in range(int(h.n_MDR21)):
h("a_MDR21[%i] = new GenericMuscleCell()"%i)
h("access a_MDR21[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR21[0].position(80., 330., 80.) }")
h("proc initialiseV_MDR21() { for i = 0, n_MDR21-1 { a_MDR21[i].set_initial_v() } }")
h("objref fih_MDR21")
h('{fih_MDR21 = new FInitializeHandler(0, "initialiseV_MDR21()")}')
h("proc initialiseIons_MDR21() { for i = 0, n_MDR21-1 { a_MDR21[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR21")
h('{fih_ion_MDR21 = new FInitializeHandler(1, "initialiseIons_MDR21()")}')
# ###################### Population: MDR22
print("Population MDR22 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR22 = []
h("{ n_MDR22 = 1 }")
h("objectvar a_MDR22[n_MDR22]")
for i in range(int(h.n_MDR22)):
h("a_MDR22[%i] = new GenericMuscleCell()"%i)
h("access a_MDR22[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR22[0].position(80., 360., 80.) }")
h("proc initialiseV_MDR22() { for i = 0, n_MDR22-1 { a_MDR22[i].set_initial_v() } }")
h("objref fih_MDR22")
h('{fih_MDR22 = new FInitializeHandler(0, "initialiseV_MDR22()")}')
h("proc initialiseIons_MDR22() { for i = 0, n_MDR22-1 { a_MDR22[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR22")
h('{fih_ion_MDR22 = new FInitializeHandler(1, "initialiseIons_MDR22()")}')
# ###################### Population: MDR23
print("Population MDR23 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR23 = []
h("{ n_MDR23 = 1 }")
h("objectvar a_MDR23[n_MDR23]")
for i in range(int(h.n_MDR23)):
h("a_MDR23[%i] = new GenericMuscleCell()"%i)
h("access a_MDR23[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR23[0].position(80., 390., 80.) }")
h("proc initialiseV_MDR23() { for i = 0, n_MDR23-1 { a_MDR23[i].set_initial_v() } }")
h("objref fih_MDR23")
h('{fih_MDR23 = new FInitializeHandler(0, "initialiseV_MDR23()")}')
h("proc initialiseIons_MDR23() { for i = 0, n_MDR23-1 { a_MDR23[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR23")
h('{fih_ion_MDR23 = new FInitializeHandler(1, "initialiseIons_MDR23()")}')
# ###################### Population: MDR24
print("Population MDR24 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDR24 = []
h("{ n_MDR24 = 1 }")
h("objectvar a_MDR24[n_MDR24]")
for i in range(int(h.n_MDR24)):
h("a_MDR24[%i] = new GenericMuscleCell()"%i)
h("access a_MDR24[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDR24[0].position(80., 420., 80.) }")
h("proc initialiseV_MDR24() { for i = 0, n_MDR24-1 { a_MDR24[i].set_initial_v() } }")
h("objref fih_MDR24")
h('{fih_MDR24 = new FInitializeHandler(0, "initialiseV_MDR24()")}')
h("proc initialiseIons_MDR24() { for i = 0, n_MDR24-1 { a_MDR24[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDR24")
h('{fih_ion_MDR24 = new FInitializeHandler(1, "initialiseIons_MDR24()")}')
# ###################### Population: MVR01
print("Population MVR01 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR01 = []
h("{ n_MVR01 = 1 }")
h("objectvar a_MVR01[n_MVR01]")
for i in range(int(h.n_MVR01)):
h("a_MVR01[%i] = new GenericMuscleCell()"%i)
h("access a_MVR01[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR01[0].position(-80., -270., 80.) }")
h("proc initialiseV_MVR01() { for i = 0, n_MVR01-1 { a_MVR01[i].set_initial_v() } }")
h("objref fih_MVR01")
h('{fih_MVR01 = new FInitializeHandler(0, "initialiseV_MVR01()")}')
h("proc initialiseIons_MVR01() { for i = 0, n_MVR01-1 { a_MVR01[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR01")
h('{fih_ion_MVR01 = new FInitializeHandler(1, "initialiseIons_MVR01()")}')
# ###################### Population: MVR02
print("Population MVR02 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR02 = []
h("{ n_MVR02 = 1 }")
h("objectvar a_MVR02[n_MVR02]")
for i in range(int(h.n_MVR02)):
h("a_MVR02[%i] = new GenericMuscleCell()"%i)
h("access a_MVR02[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR02[0].position(-80., -240., 80.) }")
h("proc initialiseV_MVR02() { for i = 0, n_MVR02-1 { a_MVR02[i].set_initial_v() } }")
h("objref fih_MVR02")
h('{fih_MVR02 = new FInitializeHandler(0, "initialiseV_MVR02()")}')
h("proc initialiseIons_MVR02() { for i = 0, n_MVR02-1 { a_MVR02[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR02")
h('{fih_ion_MVR02 = new FInitializeHandler(1, "initialiseIons_MVR02()")}')
# ###################### Population: MVR03
print("Population MVR03 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR03 = []
h("{ n_MVR03 = 1 }")
h("objectvar a_MVR03[n_MVR03]")
for i in range(int(h.n_MVR03)):
h("a_MVR03[%i] = new GenericMuscleCell()"%i)
h("access a_MVR03[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR03[0].position(-80., -210., 80.) }")
h("proc initialiseV_MVR03() { for i = 0, n_MVR03-1 { a_MVR03[i].set_initial_v() } }")
h("objref fih_MVR03")
h('{fih_MVR03 = new FInitializeHandler(0, "initialiseV_MVR03()")}')
h("proc initialiseIons_MVR03() { for i = 0, n_MVR03-1 { a_MVR03[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR03")
h('{fih_ion_MVR03 = new FInitializeHandler(1, "initialiseIons_MVR03()")}')
# ###################### Population: MVR04
print("Population MVR04 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR04 = []
h("{ n_MVR04 = 1 }")
h("objectvar a_MVR04[n_MVR04]")
for i in range(int(h.n_MVR04)):
h("a_MVR04[%i] = new GenericMuscleCell()"%i)
h("access a_MVR04[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR04[0].position(-80., -180., 80.) }")
h("proc initialiseV_MVR04() { for i = 0, n_MVR04-1 { a_MVR04[i].set_initial_v() } }")
h("objref fih_MVR04")
h('{fih_MVR04 = new FInitializeHandler(0, "initialiseV_MVR04()")}')
h("proc initialiseIons_MVR04() { for i = 0, n_MVR04-1 { a_MVR04[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR04")
h('{fih_ion_MVR04 = new FInitializeHandler(1, "initialiseIons_MVR04()")}')
# ###################### Population: MVR05
print("Population MVR05 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR05 = []
h("{ n_MVR05 = 1 }")
h("objectvar a_MVR05[n_MVR05]")
for i in range(int(h.n_MVR05)):
h("a_MVR05[%i] = new GenericMuscleCell()"%i)
h("access a_MVR05[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR05[0].position(-80., -150., 80.) }")
h("proc initialiseV_MVR05() { for i = 0, n_MVR05-1 { a_MVR05[i].set_initial_v() } }")
h("objref fih_MVR05")
h('{fih_MVR05 = new FInitializeHandler(0, "initialiseV_MVR05()")}')
h("proc initialiseIons_MVR05() { for i = 0, n_MVR05-1 { a_MVR05[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR05")
h('{fih_ion_MVR05 = new FInitializeHandler(1, "initialiseIons_MVR05()")}')
# ###################### Population: MVR06
print("Population MVR06 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR06 = []
h("{ n_MVR06 = 1 }")
h("objectvar a_MVR06[n_MVR06]")
for i in range(int(h.n_MVR06)):
h("a_MVR06[%i] = new GenericMuscleCell()"%i)
h("access a_MVR06[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR06[0].position(-80., -120., 80.) }")
h("proc initialiseV_MVR06() { for i = 0, n_MVR06-1 { a_MVR06[i].set_initial_v() } }")
h("objref fih_MVR06")
h('{fih_MVR06 = new FInitializeHandler(0, "initialiseV_MVR06()")}')
h("proc initialiseIons_MVR06() { for i = 0, n_MVR06-1 { a_MVR06[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR06")
h('{fih_ion_MVR06 = new FInitializeHandler(1, "initialiseIons_MVR06()")}')
# ###################### Population: MVR07
print("Population MVR07 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR07 = []
h("{ n_MVR07 = 1 }")
h("objectvar a_MVR07[n_MVR07]")
for i in range(int(h.n_MVR07)):
h("a_MVR07[%i] = new GenericMuscleCell()"%i)
h("access a_MVR07[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR07[0].position(-80., -90., 80.) }")
h("proc initialiseV_MVR07() { for i = 0, n_MVR07-1 { a_MVR07[i].set_initial_v() } }")
h("objref fih_MVR07")
h('{fih_MVR07 = new FInitializeHandler(0, "initialiseV_MVR07()")}')
h("proc initialiseIons_MVR07() { for i = 0, n_MVR07-1 { a_MVR07[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR07")
h('{fih_ion_MVR07 = new FInitializeHandler(1, "initialiseIons_MVR07()")}')
# ###################### Population: MVR08
print("Population MVR08 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR08 = []
h("{ n_MVR08 = 1 }")
h("objectvar a_MVR08[n_MVR08]")
for i in range(int(h.n_MVR08)):
h("a_MVR08[%i] = new GenericMuscleCell()"%i)
h("access a_MVR08[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR08[0].position(-80., -60., 80.) }")
h("proc initialiseV_MVR08() { for i = 0, n_MVR08-1 { a_MVR08[i].set_initial_v() } }")
h("objref fih_MVR08")
h('{fih_MVR08 = new FInitializeHandler(0, "initialiseV_MVR08()")}')
h("proc initialiseIons_MVR08() { for i = 0, n_MVR08-1 { a_MVR08[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR08")
h('{fih_ion_MVR08 = new FInitializeHandler(1, "initialiseIons_MVR08()")}')
# ###################### Population: MVR09
print("Population MVR09 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR09 = []
h("{ n_MVR09 = 1 }")
h("objectvar a_MVR09[n_MVR09]")
for i in range(int(h.n_MVR09)):
h("a_MVR09[%i] = new GenericMuscleCell()"%i)
h("access a_MVR09[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR09[0].position(-80., -30., 80.) }")
h("proc initialiseV_MVR09() { for i = 0, n_MVR09-1 { a_MVR09[i].set_initial_v() } }")
h("objref fih_MVR09")
h('{fih_MVR09 = new FInitializeHandler(0, "initialiseV_MVR09()")}')
h("proc initialiseIons_MVR09() { for i = 0, n_MVR09-1 { a_MVR09[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR09")
h('{fih_ion_MVR09 = new FInitializeHandler(1, "initialiseIons_MVR09()")}')
# ###################### Population: MVR10
print("Population MVR10 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR10 = []
h("{ n_MVR10 = 1 }")
h("objectvar a_MVR10[n_MVR10]")
for i in range(int(h.n_MVR10)):
h("a_MVR10[%i] = new GenericMuscleCell()"%i)
h("access a_MVR10[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR10[0].position(-80., 0., 80.) }")
h("proc initialiseV_MVR10() { for i = 0, n_MVR10-1 { a_MVR10[i].set_initial_v() } }")
h("objref fih_MVR10")
h('{fih_MVR10 = new FInitializeHandler(0, "initialiseV_MVR10()")}')
h("proc initialiseIons_MVR10() { for i = 0, n_MVR10-1 { a_MVR10[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR10")
h('{fih_ion_MVR10 = new FInitializeHandler(1, "initialiseIons_MVR10()")}')
# ###################### Population: MVR11
print("Population MVR11 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR11 = []
h("{ n_MVR11 = 1 }")
h("objectvar a_MVR11[n_MVR11]")
for i in range(int(h.n_MVR11)):
h("a_MVR11[%i] = new GenericMuscleCell()"%i)
h("access a_MVR11[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR11[0].position(-80., 30., 80.) }")
h("proc initialiseV_MVR11() { for i = 0, n_MVR11-1 { a_MVR11[i].set_initial_v() } }")
h("objref fih_MVR11")
h('{fih_MVR11 = new FInitializeHandler(0, "initialiseV_MVR11()")}')
h("proc initialiseIons_MVR11() { for i = 0, n_MVR11-1 { a_MVR11[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR11")
h('{fih_ion_MVR11 = new FInitializeHandler(1, "initialiseIons_MVR11()")}')
# ###################### Population: MVR12
print("Population MVR12 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR12 = []
h("{ n_MVR12 = 1 }")
h("objectvar a_MVR12[n_MVR12]")
for i in range(int(h.n_MVR12)):
h("a_MVR12[%i] = new GenericMuscleCell()"%i)
h("access a_MVR12[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR12[0].position(-80., 60., 80.) }")
h("proc initialiseV_MVR12() { for i = 0, n_MVR12-1 { a_MVR12[i].set_initial_v() } }")
h("objref fih_MVR12")
h('{fih_MVR12 = new FInitializeHandler(0, "initialiseV_MVR12()")}')
h("proc initialiseIons_MVR12() { for i = 0, n_MVR12-1 { a_MVR12[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR12")
h('{fih_ion_MVR12 = new FInitializeHandler(1, "initialiseIons_MVR12()")}')
# ###################### Population: MVR13
print("Population MVR13 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR13 = []
h("{ n_MVR13 = 1 }")
h("objectvar a_MVR13[n_MVR13]")
for i in range(int(h.n_MVR13)):
h("a_MVR13[%i] = new GenericMuscleCell()"%i)
h("access a_MVR13[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR13[0].position(-80., 90., 80.) }")
h("proc initialiseV_MVR13() { for i = 0, n_MVR13-1 { a_MVR13[i].set_initial_v() } }")
h("objref fih_MVR13")
h('{fih_MVR13 = new FInitializeHandler(0, "initialiseV_MVR13()")}')
h("proc initialiseIons_MVR13() { for i = 0, n_MVR13-1 { a_MVR13[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR13")
h('{fih_ion_MVR13 = new FInitializeHandler(1, "initialiseIons_MVR13()")}')
# ###################### Population: MVR14
print("Population MVR14 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR14 = []
h("{ n_MVR14 = 1 }")
h("objectvar a_MVR14[n_MVR14]")
for i in range(int(h.n_MVR14)):
h("a_MVR14[%i] = new GenericMuscleCell()"%i)
h("access a_MVR14[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR14[0].position(-80., 120., 80.) }")
h("proc initialiseV_MVR14() { for i = 0, n_MVR14-1 { a_MVR14[i].set_initial_v() } }")
h("objref fih_MVR14")
h('{fih_MVR14 = new FInitializeHandler(0, "initialiseV_MVR14()")}')
h("proc initialiseIons_MVR14() { for i = 0, n_MVR14-1 { a_MVR14[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR14")
h('{fih_ion_MVR14 = new FInitializeHandler(1, "initialiseIons_MVR14()")}')
# ###################### Population: MVR15
print("Population MVR15 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR15 = []
h("{ n_MVR15 = 1 }")
h("objectvar a_MVR15[n_MVR15]")
for i in range(int(h.n_MVR15)):
h("a_MVR15[%i] = new GenericMuscleCell()"%i)
h("access a_MVR15[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR15[0].position(-80., 150., 80.) }")
h("proc initialiseV_MVR15() { for i = 0, n_MVR15-1 { a_MVR15[i].set_initial_v() } }")
h("objref fih_MVR15")
h('{fih_MVR15 = new FInitializeHandler(0, "initialiseV_MVR15()")}')
h("proc initialiseIons_MVR15() { for i = 0, n_MVR15-1 { a_MVR15[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR15")
h('{fih_ion_MVR15 = new FInitializeHandler(1, "initialiseIons_MVR15()")}')
# ###################### Population: MVR16
print("Population MVR16 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR16 = []
h("{ n_MVR16 = 1 }")
h("objectvar a_MVR16[n_MVR16]")
for i in range(int(h.n_MVR16)):
h("a_MVR16[%i] = new GenericMuscleCell()"%i)
h("access a_MVR16[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR16[0].position(-80., 180., 80.) }")
h("proc initialiseV_MVR16() { for i = 0, n_MVR16-1 { a_MVR16[i].set_initial_v() } }")
h("objref fih_MVR16")
h('{fih_MVR16 = new FInitializeHandler(0, "initialiseV_MVR16()")}')
h("proc initialiseIons_MVR16() { for i = 0, n_MVR16-1 { a_MVR16[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR16")
h('{fih_ion_MVR16 = new FInitializeHandler(1, "initialiseIons_MVR16()")}')
# ###################### Population: MVR17
print("Population MVR17 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR17 = []
h("{ n_MVR17 = 1 }")
h("objectvar a_MVR17[n_MVR17]")
for i in range(int(h.n_MVR17)):
h("a_MVR17[%i] = new GenericMuscleCell()"%i)
h("access a_MVR17[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR17[0].position(-80., 210., 80.) }")
h("proc initialiseV_MVR17() { for i = 0, n_MVR17-1 { a_MVR17[i].set_initial_v() } }")
h("objref fih_MVR17")
h('{fih_MVR17 = new FInitializeHandler(0, "initialiseV_MVR17()")}')
h("proc initialiseIons_MVR17() { for i = 0, n_MVR17-1 { a_MVR17[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR17")
h('{fih_ion_MVR17 = new FInitializeHandler(1, "initialiseIons_MVR17()")}')
# ###################### Population: MVR18
print("Population MVR18 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR18 = []
h("{ n_MVR18 = 1 }")
h("objectvar a_MVR18[n_MVR18]")
for i in range(int(h.n_MVR18)):
h("a_MVR18[%i] = new GenericMuscleCell()"%i)
h("access a_MVR18[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR18[0].position(-80., 240., 80.) }")
h("proc initialiseV_MVR18() { for i = 0, n_MVR18-1 { a_MVR18[i].set_initial_v() } }")
h("objref fih_MVR18")
h('{fih_MVR18 = new FInitializeHandler(0, "initialiseV_MVR18()")}')
h("proc initialiseIons_MVR18() { for i = 0, n_MVR18-1 { a_MVR18[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR18")
h('{fih_ion_MVR18 = new FInitializeHandler(1, "initialiseIons_MVR18()")}')
# ###################### Population: MVR19
print("Population MVR19 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR19 = []
h("{ n_MVR19 = 1 }")
h("objectvar a_MVR19[n_MVR19]")
for i in range(int(h.n_MVR19)):
h("a_MVR19[%i] = new GenericMuscleCell()"%i)
h("access a_MVR19[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR19[0].position(-80., 270., 80.) }")
h("proc initialiseV_MVR19() { for i = 0, n_MVR19-1 { a_MVR19[i].set_initial_v() } }")
h("objref fih_MVR19")
h('{fih_MVR19 = new FInitializeHandler(0, "initialiseV_MVR19()")}')
h("proc initialiseIons_MVR19() { for i = 0, n_MVR19-1 { a_MVR19[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR19")
h('{fih_ion_MVR19 = new FInitializeHandler(1, "initialiseIons_MVR19()")}')
# ###################### Population: MVR20
print("Population MVR20 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR20 = []
h("{ n_MVR20 = 1 }")
h("objectvar a_MVR20[n_MVR20]")
for i in range(int(h.n_MVR20)):
h("a_MVR20[%i] = new GenericMuscleCell()"%i)
h("access a_MVR20[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR20[0].position(-80., 300., 80.) }")
h("proc initialiseV_MVR20() { for i = 0, n_MVR20-1 { a_MVR20[i].set_initial_v() } }")
h("objref fih_MVR20")
h('{fih_MVR20 = new FInitializeHandler(0, "initialiseV_MVR20()")}')
h("proc initialiseIons_MVR20() { for i = 0, n_MVR20-1 { a_MVR20[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR20")
h('{fih_ion_MVR20 = new FInitializeHandler(1, "initialiseIons_MVR20()")}')
# ###################### Population: MVR21
print("Population MVR21 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR21 = []
h("{ n_MVR21 = 1 }")
h("objectvar a_MVR21[n_MVR21]")
for i in range(int(h.n_MVR21)):
h("a_MVR21[%i] = new GenericMuscleCell()"%i)
h("access a_MVR21[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR21[0].position(-80., 330., 80.) }")
h("proc initialiseV_MVR21() { for i = 0, n_MVR21-1 { a_MVR21[i].set_initial_v() } }")
h("objref fih_MVR21")
h('{fih_MVR21 = new FInitializeHandler(0, "initialiseV_MVR21()")}')
h("proc initialiseIons_MVR21() { for i = 0, n_MVR21-1 { a_MVR21[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR21")
h('{fih_ion_MVR21 = new FInitializeHandler(1, "initialiseIons_MVR21()")}')
# ###################### Population: MVR22
print("Population MVR22 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR22 = []
h("{ n_MVR22 = 1 }")
h("objectvar a_MVR22[n_MVR22]")
for i in range(int(h.n_MVR22)):
h("a_MVR22[%i] = new GenericMuscleCell()"%i)
h("access a_MVR22[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR22[0].position(-80., 360., 80.) }")
h("proc initialiseV_MVR22() { for i = 0, n_MVR22-1 { a_MVR22[i].set_initial_v() } }")
h("objref fih_MVR22")
h('{fih_MVR22 = new FInitializeHandler(0, "initialiseV_MVR22()")}')
h("proc initialiseIons_MVR22() { for i = 0, n_MVR22-1 { a_MVR22[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR22")
h('{fih_ion_MVR22 = new FInitializeHandler(1, "initialiseIons_MVR22()")}')
# ###################### Population: MVR23
print("Population MVR23 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVR23 = []
h("{ n_MVR23 = 1 }")
h("objectvar a_MVR23[n_MVR23]")
for i in range(int(h.n_MVR23)):
h("a_MVR23[%i] = new GenericMuscleCell()"%i)
h("access a_MVR23[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVR23[0].position(-80., 390., 80.) }")
h("proc initialiseV_MVR23() { for i = 0, n_MVR23-1 { a_MVR23[i].set_initial_v() } }")
h("objref fih_MVR23")
h('{fih_MVR23 = new FInitializeHandler(0, "initialiseV_MVR23()")}')
h("proc initialiseIons_MVR23() { for i = 0, n_MVR23-1 { a_MVR23[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVR23")
h('{fih_ion_MVR23 = new FInitializeHandler(1, "initialiseIons_MVR23()")}')
# ###################### Population: MVL01
print("Population MVL01 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL01 = []
h("{ n_MVL01 = 1 }")
h("objectvar a_MVL01[n_MVL01]")
for i in range(int(h.n_MVL01)):
h("a_MVL01[%i] = new GenericMuscleCell()"%i)
h("access a_MVL01[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL01[0].position(-80., -270., -80.) }")
h("proc initialiseV_MVL01() { for i = 0, n_MVL01-1 { a_MVL01[i].set_initial_v() } }")
h("objref fih_MVL01")
h('{fih_MVL01 = new FInitializeHandler(0, "initialiseV_MVL01()")}')
h("proc initialiseIons_MVL01() { for i = 0, n_MVL01-1 { a_MVL01[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL01")
h('{fih_ion_MVL01 = new FInitializeHandler(1, "initialiseIons_MVL01()")}')
# ###################### Population: MVL02
print("Population MVL02 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL02 = []
h("{ n_MVL02 = 1 }")
h("objectvar a_MVL02[n_MVL02]")
for i in range(int(h.n_MVL02)):
h("a_MVL02[%i] = new GenericMuscleCell()"%i)
h("access a_MVL02[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL02[0].position(-80., -240., -80.) }")
h("proc initialiseV_MVL02() { for i = 0, n_MVL02-1 { a_MVL02[i].set_initial_v() } }")
h("objref fih_MVL02")
h('{fih_MVL02 = new FInitializeHandler(0, "initialiseV_MVL02()")}')
h("proc initialiseIons_MVL02() { for i = 0, n_MVL02-1 { a_MVL02[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL02")
h('{fih_ion_MVL02 = new FInitializeHandler(1, "initialiseIons_MVL02()")}')
# ###################### Population: MVL03
print("Population MVL03 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL03 = []
h("{ n_MVL03 = 1 }")
h("objectvar a_MVL03[n_MVL03]")
for i in range(int(h.n_MVL03)):
h("a_MVL03[%i] = new GenericMuscleCell()"%i)
h("access a_MVL03[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL03[0].position(-80., -210., -80.) }")
h("proc initialiseV_MVL03() { for i = 0, n_MVL03-1 { a_MVL03[i].set_initial_v() } }")
h("objref fih_MVL03")
h('{fih_MVL03 = new FInitializeHandler(0, "initialiseV_MVL03()")}')
h("proc initialiseIons_MVL03() { for i = 0, n_MVL03-1 { a_MVL03[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL03")
h('{fih_ion_MVL03 = new FInitializeHandler(1, "initialiseIons_MVL03()")}')
# ###################### Population: MVL04
print("Population MVL04 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL04 = []
h("{ n_MVL04 = 1 }")
h("objectvar a_MVL04[n_MVL04]")
for i in range(int(h.n_MVL04)):
h("a_MVL04[%i] = new GenericMuscleCell()"%i)
h("access a_MVL04[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL04[0].position(-80., -180., -80.) }")
h("proc initialiseV_MVL04() { for i = 0, n_MVL04-1 { a_MVL04[i].set_initial_v() } }")
h("objref fih_MVL04")
h('{fih_MVL04 = new FInitializeHandler(0, "initialiseV_MVL04()")}')
h("proc initialiseIons_MVL04() { for i = 0, n_MVL04-1 { a_MVL04[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL04")
h('{fih_ion_MVL04 = new FInitializeHandler(1, "initialiseIons_MVL04()")}')
# ###################### Population: MVL05
print("Population MVL05 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL05 = []
h("{ n_MVL05 = 1 }")
h("objectvar a_MVL05[n_MVL05]")
for i in range(int(h.n_MVL05)):
h("a_MVL05[%i] = new GenericMuscleCell()"%i)
h("access a_MVL05[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL05[0].position(-80., -150., -80.) }")
h("proc initialiseV_MVL05() { for i = 0, n_MVL05-1 { a_MVL05[i].set_initial_v() } }")
h("objref fih_MVL05")
h('{fih_MVL05 = new FInitializeHandler(0, "initialiseV_MVL05()")}')
h("proc initialiseIons_MVL05() { for i = 0, n_MVL05-1 { a_MVL05[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL05")
h('{fih_ion_MVL05 = new FInitializeHandler(1, "initialiseIons_MVL05()")}')
# ###################### Population: MVL06
print("Population MVL06 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL06 = []
h("{ n_MVL06 = 1 }")
h("objectvar a_MVL06[n_MVL06]")
for i in range(int(h.n_MVL06)):
h("a_MVL06[%i] = new GenericMuscleCell()"%i)
h("access a_MVL06[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL06[0].position(-80., -120., -80.) }")
h("proc initialiseV_MVL06() { for i = 0, n_MVL06-1 { a_MVL06[i].set_initial_v() } }")
h("objref fih_MVL06")
h('{fih_MVL06 = new FInitializeHandler(0, "initialiseV_MVL06()")}')
h("proc initialiseIons_MVL06() { for i = 0, n_MVL06-1 { a_MVL06[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL06")
h('{fih_ion_MVL06 = new FInitializeHandler(1, "initialiseIons_MVL06()")}')
# ###################### Population: MVL07
print("Population MVL07 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL07 = []
h("{ n_MVL07 = 1 }")
h("objectvar a_MVL07[n_MVL07]")
for i in range(int(h.n_MVL07)):
h("a_MVL07[%i] = new GenericMuscleCell()"%i)
h("access a_MVL07[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL07[0].position(-80., -90., -80.) }")
h("proc initialiseV_MVL07() { for i = 0, n_MVL07-1 { a_MVL07[i].set_initial_v() } }")
h("objref fih_MVL07")
h('{fih_MVL07 = new FInitializeHandler(0, "initialiseV_MVL07()")}')
h("proc initialiseIons_MVL07() { for i = 0, n_MVL07-1 { a_MVL07[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL07")
h('{fih_ion_MVL07 = new FInitializeHandler(1, "initialiseIons_MVL07()")}')
# ###################### Population: MVL08
print("Population MVL08 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL08 = []
h("{ n_MVL08 = 1 }")
h("objectvar a_MVL08[n_MVL08]")
for i in range(int(h.n_MVL08)):
h("a_MVL08[%i] = new GenericMuscleCell()"%i)
h("access a_MVL08[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL08[0].position(-80., -60., -80.) }")
h("proc initialiseV_MVL08() { for i = 0, n_MVL08-1 { a_MVL08[i].set_initial_v() } }")
h("objref fih_MVL08")
h('{fih_MVL08 = new FInitializeHandler(0, "initialiseV_MVL08()")}')
h("proc initialiseIons_MVL08() { for i = 0, n_MVL08-1 { a_MVL08[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL08")
h('{fih_ion_MVL08 = new FInitializeHandler(1, "initialiseIons_MVL08()")}')
# ###################### Population: MVL09
print("Population MVL09 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL09 = []
h("{ n_MVL09 = 1 }")
h("objectvar a_MVL09[n_MVL09]")
for i in range(int(h.n_MVL09)):
h("a_MVL09[%i] = new GenericMuscleCell()"%i)
h("access a_MVL09[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL09[0].position(-80., -30., -80.) }")
h("proc initialiseV_MVL09() { for i = 0, n_MVL09-1 { a_MVL09[i].set_initial_v() } }")
h("objref fih_MVL09")
h('{fih_MVL09 = new FInitializeHandler(0, "initialiseV_MVL09()")}')
h("proc initialiseIons_MVL09() { for i = 0, n_MVL09-1 { a_MVL09[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL09")
h('{fih_ion_MVL09 = new FInitializeHandler(1, "initialiseIons_MVL09()")}')
# ###################### Population: MVL10
print("Population MVL10 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL10 = []
h("{ n_MVL10 = 1 }")
h("objectvar a_MVL10[n_MVL10]")
for i in range(int(h.n_MVL10)):
h("a_MVL10[%i] = new GenericMuscleCell()"%i)
h("access a_MVL10[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL10[0].position(-80., 0., -80.) }")
h("proc initialiseV_MVL10() { for i = 0, n_MVL10-1 { a_MVL10[i].set_initial_v() } }")
h("objref fih_MVL10")
h('{fih_MVL10 = new FInitializeHandler(0, "initialiseV_MVL10()")}')
h("proc initialiseIons_MVL10() { for i = 0, n_MVL10-1 { a_MVL10[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL10")
h('{fih_ion_MVL10 = new FInitializeHandler(1, "initialiseIons_MVL10()")}')
# ###################### Population: MVL11
print("Population MVL11 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL11 = []
h("{ n_MVL11 = 1 }")
h("objectvar a_MVL11[n_MVL11]")
for i in range(int(h.n_MVL11)):
h("a_MVL11[%i] = new GenericMuscleCell()"%i)
h("access a_MVL11[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL11[0].position(-80., 30., -80.) }")
h("proc initialiseV_MVL11() { for i = 0, n_MVL11-1 { a_MVL11[i].set_initial_v() } }")
h("objref fih_MVL11")
h('{fih_MVL11 = new FInitializeHandler(0, "initialiseV_MVL11()")}')
h("proc initialiseIons_MVL11() { for i = 0, n_MVL11-1 { a_MVL11[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL11")
h('{fih_ion_MVL11 = new FInitializeHandler(1, "initialiseIons_MVL11()")}')
# ###################### Population: MVL12
print("Population MVL12 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL12 = []
h("{ n_MVL12 = 1 }")
h("objectvar a_MVL12[n_MVL12]")
for i in range(int(h.n_MVL12)):
h("a_MVL12[%i] = new GenericMuscleCell()"%i)
h("access a_MVL12[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL12[0].position(-80., 60., -80.) }")
h("proc initialiseV_MVL12() { for i = 0, n_MVL12-1 { a_MVL12[i].set_initial_v() } }")
h("objref fih_MVL12")
h('{fih_MVL12 = new FInitializeHandler(0, "initialiseV_MVL12()")}')
h("proc initialiseIons_MVL12() { for i = 0, n_MVL12-1 { a_MVL12[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL12")
h('{fih_ion_MVL12 = new FInitializeHandler(1, "initialiseIons_MVL12()")}')
# ###################### Population: MVL13
print("Population MVL13 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL13 = []
h("{ n_MVL13 = 1 }")
h("objectvar a_MVL13[n_MVL13]")
for i in range(int(h.n_MVL13)):
h("a_MVL13[%i] = new GenericMuscleCell()"%i)
h("access a_MVL13[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL13[0].position(-80., 90., -80.) }")
h("proc initialiseV_MVL13() { for i = 0, n_MVL13-1 { a_MVL13[i].set_initial_v() } }")
h("objref fih_MVL13")
h('{fih_MVL13 = new FInitializeHandler(0, "initialiseV_MVL13()")}')
h("proc initialiseIons_MVL13() { for i = 0, n_MVL13-1 { a_MVL13[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL13")
h('{fih_ion_MVL13 = new FInitializeHandler(1, "initialiseIons_MVL13()")}')
# ###################### Population: MVL14
print("Population MVL14 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL14 = []
h("{ n_MVL14 = 1 }")
h("objectvar a_MVL14[n_MVL14]")
for i in range(int(h.n_MVL14)):
h("a_MVL14[%i] = new GenericMuscleCell()"%i)
h("access a_MVL14[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL14[0].position(-80., 120., -80.) }")
h("proc initialiseV_MVL14() { for i = 0, n_MVL14-1 { a_MVL14[i].set_initial_v() } }")
h("objref fih_MVL14")
h('{fih_MVL14 = new FInitializeHandler(0, "initialiseV_MVL14()")}')
h("proc initialiseIons_MVL14() { for i = 0, n_MVL14-1 { a_MVL14[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL14")
h('{fih_ion_MVL14 = new FInitializeHandler(1, "initialiseIons_MVL14()")}')
# ###################### Population: MVL15
print("Population MVL15 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL15 = []
h("{ n_MVL15 = 1 }")
h("objectvar a_MVL15[n_MVL15]")
for i in range(int(h.n_MVL15)):
h("a_MVL15[%i] = new GenericMuscleCell()"%i)
h("access a_MVL15[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL15[0].position(-80., 150., -80.) }")
h("proc initialiseV_MVL15() { for i = 0, n_MVL15-1 { a_MVL15[i].set_initial_v() } }")
h("objref fih_MVL15")
h('{fih_MVL15 = new FInitializeHandler(0, "initialiseV_MVL15()")}')
h("proc initialiseIons_MVL15() { for i = 0, n_MVL15-1 { a_MVL15[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL15")
h('{fih_ion_MVL15 = new FInitializeHandler(1, "initialiseIons_MVL15()")}')
# ###################### Population: MVL16
print("Population MVL16 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL16 = []
h("{ n_MVL16 = 1 }")
h("objectvar a_MVL16[n_MVL16]")
for i in range(int(h.n_MVL16)):
h("a_MVL16[%i] = new GenericMuscleCell()"%i)
h("access a_MVL16[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL16[0].position(-80., 180., -80.) }")
h("proc initialiseV_MVL16() { for i = 0, n_MVL16-1 { a_MVL16[i].set_initial_v() } }")
h("objref fih_MVL16")
h('{fih_MVL16 = new FInitializeHandler(0, "initialiseV_MVL16()")}')
h("proc initialiseIons_MVL16() { for i = 0, n_MVL16-1 { a_MVL16[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL16")
h('{fih_ion_MVL16 = new FInitializeHandler(1, "initialiseIons_MVL16()")}')
# ###################### Population: MVL17
print("Population MVL17 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL17 = []
h("{ n_MVL17 = 1 }")
h("objectvar a_MVL17[n_MVL17]")
for i in range(int(h.n_MVL17)):
h("a_MVL17[%i] = new GenericMuscleCell()"%i)
h("access a_MVL17[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL17[0].position(-80., 210., -80.) }")
h("proc initialiseV_MVL17() { for i = 0, n_MVL17-1 { a_MVL17[i].set_initial_v() } }")
h("objref fih_MVL17")
h('{fih_MVL17 = new FInitializeHandler(0, "initialiseV_MVL17()")}')
h("proc initialiseIons_MVL17() { for i = 0, n_MVL17-1 { a_MVL17[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL17")
h('{fih_ion_MVL17 = new FInitializeHandler(1, "initialiseIons_MVL17()")}')
# ###################### Population: MVL18
print("Population MVL18 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL18 = []
h("{ n_MVL18 = 1 }")
h("objectvar a_MVL18[n_MVL18]")
for i in range(int(h.n_MVL18)):
h("a_MVL18[%i] = new GenericMuscleCell()"%i)
h("access a_MVL18[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL18[0].position(-80., 240., -80.) }")
h("proc initialiseV_MVL18() { for i = 0, n_MVL18-1 { a_MVL18[i].set_initial_v() } }")
h("objref fih_MVL18")
h('{fih_MVL18 = new FInitializeHandler(0, "initialiseV_MVL18()")}')
h("proc initialiseIons_MVL18() { for i = 0, n_MVL18-1 { a_MVL18[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL18")
h('{fih_ion_MVL18 = new FInitializeHandler(1, "initialiseIons_MVL18()")}')
# ###################### Population: MVL19
print("Population MVL19 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL19 = []
h("{ n_MVL19 = 1 }")
h("objectvar a_MVL19[n_MVL19]")
for i in range(int(h.n_MVL19)):
h("a_MVL19[%i] = new GenericMuscleCell()"%i)
h("access a_MVL19[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL19[0].position(-80., 270., -80.) }")
h("proc initialiseV_MVL19() { for i = 0, n_MVL19-1 { a_MVL19[i].set_initial_v() } }")
h("objref fih_MVL19")
h('{fih_MVL19 = new FInitializeHandler(0, "initialiseV_MVL19()")}')
h("proc initialiseIons_MVL19() { for i = 0, n_MVL19-1 { a_MVL19[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL19")
h('{fih_ion_MVL19 = new FInitializeHandler(1, "initialiseIons_MVL19()")}')
# ###################### Population: MVL20
print("Population MVL20 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL20 = []
h("{ n_MVL20 = 1 }")
h("objectvar a_MVL20[n_MVL20]")
for i in range(int(h.n_MVL20)):
h("a_MVL20[%i] = new GenericMuscleCell()"%i)
h("access a_MVL20[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL20[0].position(-80., 300., -80.) }")
h("proc initialiseV_MVL20() { for i = 0, n_MVL20-1 { a_MVL20[i].set_initial_v() } }")
h("objref fih_MVL20")
h('{fih_MVL20 = new FInitializeHandler(0, "initialiseV_MVL20()")}')
h("proc initialiseIons_MVL20() { for i = 0, n_MVL20-1 { a_MVL20[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL20")
h('{fih_ion_MVL20 = new FInitializeHandler(1, "initialiseIons_MVL20()")}')
# ###################### Population: MVL21
print("Population MVL21 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL21 = []
h("{ n_MVL21 = 1 }")
h("objectvar a_MVL21[n_MVL21]")
for i in range(int(h.n_MVL21)):
h("a_MVL21[%i] = new GenericMuscleCell()"%i)
h("access a_MVL21[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL21[0].position(-80., 330., -80.) }")
h("proc initialiseV_MVL21() { for i = 0, n_MVL21-1 { a_MVL21[i].set_initial_v() } }")
h("objref fih_MVL21")
h('{fih_MVL21 = new FInitializeHandler(0, "initialiseV_MVL21()")}')
h("proc initialiseIons_MVL21() { for i = 0, n_MVL21-1 { a_MVL21[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL21")
h('{fih_ion_MVL21 = new FInitializeHandler(1, "initialiseIons_MVL21()")}')
# ###################### Population: MVL22
print("Population MVL22 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL22 = []
h("{ n_MVL22 = 1 }")
h("objectvar a_MVL22[n_MVL22]")
for i in range(int(h.n_MVL22)):
h("a_MVL22[%i] = new GenericMuscleCell()"%i)
h("access a_MVL22[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL22[0].position(-80., 360., -80.) }")
h("proc initialiseV_MVL22() { for i = 0, n_MVL22-1 { a_MVL22[i].set_initial_v() } }")
h("objref fih_MVL22")
h('{fih_MVL22 = new FInitializeHandler(0, "initialiseV_MVL22()")}')
h("proc initialiseIons_MVL22() { for i = 0, n_MVL22-1 { a_MVL22[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL22")
h('{fih_ion_MVL22 = new FInitializeHandler(1, "initialiseIons_MVL22()")}')
# ###################### Population: MVL23
print("Population MVL23 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL23 = []
h("{ n_MVL23 = 1 }")
h("objectvar a_MVL23[n_MVL23]")
for i in range(int(h.n_MVL23)):
h("a_MVL23[%i] = new GenericMuscleCell()"%i)
h("access a_MVL23[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL23[0].position(-80., 390., -80.) }")
h("proc initialiseV_MVL23() { for i = 0, n_MVL23-1 { a_MVL23[i].set_initial_v() } }")
h("objref fih_MVL23")
h('{fih_MVL23 = new FInitializeHandler(0, "initialiseV_MVL23()")}')
h("proc initialiseIons_MVL23() { for i = 0, n_MVL23-1 { a_MVL23[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL23")
h('{fih_ion_MVL23 = new FInitializeHandler(1, "initialiseIons_MVL23()")}')
# ###################### Population: MVL24
print("Population MVL24 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MVL24 = []
h("{ n_MVL24 = 1 }")
h("objectvar a_MVL24[n_MVL24]")
for i in range(int(h.n_MVL24)):
h("a_MVL24[%i] = new GenericMuscleCell()"%i)
h("access a_MVL24[%i].soma"%i)
self.next_global_id+=1
h("{ a_MVL24[0].position(-80., 420., -80.) }")
h("proc initialiseV_MVL24() { for i = 0, n_MVL24-1 { a_MVL24[i].set_initial_v() } }")
h("objref fih_MVL24")
h('{fih_MVL24 = new FInitializeHandler(0, "initialiseV_MVL24()")}')
h("proc initialiseIons_MVL24() { for i = 0, n_MVL24-1 { a_MVL24[i].set_initial_ion_properties() } }")
h("objref fih_ion_MVL24")
h('{fih_ion_MVL24 = new FInitializeHandler(1, "initialiseIons_MVL24()")}')
# ###################### Population: MDL01
print("Population MDL01 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL01 = []
h("{ n_MDL01 = 1 }")
h("objectvar a_MDL01[n_MDL01]")
for i in range(int(h.n_MDL01)):
h("a_MDL01[%i] = new GenericMuscleCell()"%i)
h("access a_MDL01[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL01[0].position(80., -270., -80.) }")
h("proc initialiseV_MDL01() { for i = 0, n_MDL01-1 { a_MDL01[i].set_initial_v() } }")
h("objref fih_MDL01")
h('{fih_MDL01 = new FInitializeHandler(0, "initialiseV_MDL01()")}')
h("proc initialiseIons_MDL01() { for i = 0, n_MDL01-1 { a_MDL01[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL01")
h('{fih_ion_MDL01 = new FInitializeHandler(1, "initialiseIons_MDL01()")}')
# ###################### Population: MDL02
print("Population MDL02 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL02 = []
h("{ n_MDL02 = 1 }")
h("objectvar a_MDL02[n_MDL02]")
for i in range(int(h.n_MDL02)):
h("a_MDL02[%i] = new GenericMuscleCell()"%i)
h("access a_MDL02[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL02[0].position(80., -240., -80.) }")
h("proc initialiseV_MDL02() { for i = 0, n_MDL02-1 { a_MDL02[i].set_initial_v() } }")
h("objref fih_MDL02")
h('{fih_MDL02 = new FInitializeHandler(0, "initialiseV_MDL02()")}')
h("proc initialiseIons_MDL02() { for i = 0, n_MDL02-1 { a_MDL02[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL02")
h('{fih_ion_MDL02 = new FInitializeHandler(1, "initialiseIons_MDL02()")}')
# ###################### Population: MDL03
print("Population MDL03 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL03 = []
h("{ n_MDL03 = 1 }")
h("objectvar a_MDL03[n_MDL03]")
for i in range(int(h.n_MDL03)):
h("a_MDL03[%i] = new GenericMuscleCell()"%i)
h("access a_MDL03[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL03[0].position(80., -210., -80.) }")
h("proc initialiseV_MDL03() { for i = 0, n_MDL03-1 { a_MDL03[i].set_initial_v() } }")
h("objref fih_MDL03")
h('{fih_MDL03 = new FInitializeHandler(0, "initialiseV_MDL03()")}')
h("proc initialiseIons_MDL03() { for i = 0, n_MDL03-1 { a_MDL03[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL03")
h('{fih_ion_MDL03 = new FInitializeHandler(1, "initialiseIons_MDL03()")}')
# ###################### Population: MDL04
print("Population MDL04 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL04 = []
h("{ n_MDL04 = 1 }")
h("objectvar a_MDL04[n_MDL04]")
for i in range(int(h.n_MDL04)):
h("a_MDL04[%i] = new GenericMuscleCell()"%i)
h("access a_MDL04[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL04[0].position(80., -180., -80.) }")
h("proc initialiseV_MDL04() { for i = 0, n_MDL04-1 { a_MDL04[i].set_initial_v() } }")
h("objref fih_MDL04")
h('{fih_MDL04 = new FInitializeHandler(0, "initialiseV_MDL04()")}')
h("proc initialiseIons_MDL04() { for i = 0, n_MDL04-1 { a_MDL04[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL04")
h('{fih_ion_MDL04 = new FInitializeHandler(1, "initialiseIons_MDL04()")}')
# ###################### Population: MDL05
print("Population MDL05 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL05 = []
h("{ n_MDL05 = 1 }")
h("objectvar a_MDL05[n_MDL05]")
for i in range(int(h.n_MDL05)):
h("a_MDL05[%i] = new GenericMuscleCell()"%i)
h("access a_MDL05[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL05[0].position(80., -150., -80.) }")
h("proc initialiseV_MDL05() { for i = 0, n_MDL05-1 { a_MDL05[i].set_initial_v() } }")
h("objref fih_MDL05")
h('{fih_MDL05 = new FInitializeHandler(0, "initialiseV_MDL05()")}')
h("proc initialiseIons_MDL05() { for i = 0, n_MDL05-1 { a_MDL05[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL05")
h('{fih_ion_MDL05 = new FInitializeHandler(1, "initialiseIons_MDL05()")}')
# ###################### Population: MDL06
print("Population MDL06 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL06 = []
h("{ n_MDL06 = 1 }")
h("objectvar a_MDL06[n_MDL06]")
for i in range(int(h.n_MDL06)):
h("a_MDL06[%i] = new GenericMuscleCell()"%i)
h("access a_MDL06[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL06[0].position(80., -120., -80.) }")
h("proc initialiseV_MDL06() { for i = 0, n_MDL06-1 { a_MDL06[i].set_initial_v() } }")
h("objref fih_MDL06")
h('{fih_MDL06 = new FInitializeHandler(0, "initialiseV_MDL06()")}')
h("proc initialiseIons_MDL06() { for i = 0, n_MDL06-1 { a_MDL06[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL06")
h('{fih_ion_MDL06 = new FInitializeHandler(1, "initialiseIons_MDL06()")}')
# ###################### Population: MDL07
print("Population MDL07 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL07 = []
h("{ n_MDL07 = 1 }")
h("objectvar a_MDL07[n_MDL07]")
for i in range(int(h.n_MDL07)):
h("a_MDL07[%i] = new GenericMuscleCell()"%i)
h("access a_MDL07[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL07[0].position(80., -90., -80.) }")
h("proc initialiseV_MDL07() { for i = 0, n_MDL07-1 { a_MDL07[i].set_initial_v() } }")
h("objref fih_MDL07")
h('{fih_MDL07 = new FInitializeHandler(0, "initialiseV_MDL07()")}')
h("proc initialiseIons_MDL07() { for i = 0, n_MDL07-1 { a_MDL07[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL07")
h('{fih_ion_MDL07 = new FInitializeHandler(1, "initialiseIons_MDL07()")}')
# ###################### Population: MDL08
print("Population MDL08 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL08 = []
h("{ n_MDL08 = 1 }")
h("objectvar a_MDL08[n_MDL08]")
for i in range(int(h.n_MDL08)):
h("a_MDL08[%i] = new GenericMuscleCell()"%i)
h("access a_MDL08[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL08[0].position(80., -60., -80.) }")
h("proc initialiseV_MDL08() { for i = 0, n_MDL08-1 { a_MDL08[i].set_initial_v() } }")
h("objref fih_MDL08")
h('{fih_MDL08 = new FInitializeHandler(0, "initialiseV_MDL08()")}')
h("proc initialiseIons_MDL08() { for i = 0, n_MDL08-1 { a_MDL08[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL08")
h('{fih_ion_MDL08 = new FInitializeHandler(1, "initialiseIons_MDL08()")}')
# ###################### Population: MDL09
print("Population MDL09 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL09 = []
h("{ n_MDL09 = 1 }")
h("objectvar a_MDL09[n_MDL09]")
for i in range(int(h.n_MDL09)):
h("a_MDL09[%i] = new GenericMuscleCell()"%i)
h("access a_MDL09[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL09[0].position(80., -30., -80.) }")
h("proc initialiseV_MDL09() { for i = 0, n_MDL09-1 { a_MDL09[i].set_initial_v() } }")
h("objref fih_MDL09")
h('{fih_MDL09 = new FInitializeHandler(0, "initialiseV_MDL09()")}')
h("proc initialiseIons_MDL09() { for i = 0, n_MDL09-1 { a_MDL09[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL09")
h('{fih_ion_MDL09 = new FInitializeHandler(1, "initialiseIons_MDL09()")}')
# ###################### Population: MDL10
print("Population MDL10 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL10 = []
h("{ n_MDL10 = 1 }")
h("objectvar a_MDL10[n_MDL10]")
for i in range(int(h.n_MDL10)):
h("a_MDL10[%i] = new GenericMuscleCell()"%i)
h("access a_MDL10[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL10[0].position(80., 0., -80.) }")
h("proc initialiseV_MDL10() { for i = 0, n_MDL10-1 { a_MDL10[i].set_initial_v() } }")
h("objref fih_MDL10")
h('{fih_MDL10 = new FInitializeHandler(0, "initialiseV_MDL10()")}')
h("proc initialiseIons_MDL10() { for i = 0, n_MDL10-1 { a_MDL10[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL10")
h('{fih_ion_MDL10 = new FInitializeHandler(1, "initialiseIons_MDL10()")}')
# ###################### Population: MDL11
print("Population MDL11 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL11 = []
h("{ n_MDL11 = 1 }")
h("objectvar a_MDL11[n_MDL11]")
for i in range(int(h.n_MDL11)):
h("a_MDL11[%i] = new GenericMuscleCell()"%i)
h("access a_MDL11[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL11[0].position(80., 30., -80.) }")
h("proc initialiseV_MDL11() { for i = 0, n_MDL11-1 { a_MDL11[i].set_initial_v() } }")
h("objref fih_MDL11")
h('{fih_MDL11 = new FInitializeHandler(0, "initialiseV_MDL11()")}')
h("proc initialiseIons_MDL11() { for i = 0, n_MDL11-1 { a_MDL11[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL11")
h('{fih_ion_MDL11 = new FInitializeHandler(1, "initialiseIons_MDL11()")}')
# ###################### Population: MDL12
print("Population MDL12 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL12 = []
h("{ n_MDL12 = 1 }")
h("objectvar a_MDL12[n_MDL12]")
for i in range(int(h.n_MDL12)):
h("a_MDL12[%i] = new GenericMuscleCell()"%i)
h("access a_MDL12[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL12[0].position(80., 60., -80.) }")
h("proc initialiseV_MDL12() { for i = 0, n_MDL12-1 { a_MDL12[i].set_initial_v() } }")
h("objref fih_MDL12")
h('{fih_MDL12 = new FInitializeHandler(0, "initialiseV_MDL12()")}')
h("proc initialiseIons_MDL12() { for i = 0, n_MDL12-1 { a_MDL12[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL12")
h('{fih_ion_MDL12 = new FInitializeHandler(1, "initialiseIons_MDL12()")}')
# ###################### Population: MDL13
print("Population MDL13 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL13 = []
h("{ n_MDL13 = 1 }")
h("objectvar a_MDL13[n_MDL13]")
for i in range(int(h.n_MDL13)):
h("a_MDL13[%i] = new GenericMuscleCell()"%i)
h("access a_MDL13[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL13[0].position(80., 90., -80.) }")
h("proc initialiseV_MDL13() { for i = 0, n_MDL13-1 { a_MDL13[i].set_initial_v() } }")
h("objref fih_MDL13")
h('{fih_MDL13 = new FInitializeHandler(0, "initialiseV_MDL13()")}')
h("proc initialiseIons_MDL13() { for i = 0, n_MDL13-1 { a_MDL13[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL13")
h('{fih_ion_MDL13 = new FInitializeHandler(1, "initialiseIons_MDL13()")}')
# ###################### Population: MDL14
print("Population MDL14 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL14 = []
h("{ n_MDL14 = 1 }")
h("objectvar a_MDL14[n_MDL14]")
for i in range(int(h.n_MDL14)):
h("a_MDL14[%i] = new GenericMuscleCell()"%i)
h("access a_MDL14[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL14[0].position(80., 120., -80.) }")
h("proc initialiseV_MDL14() { for i = 0, n_MDL14-1 { a_MDL14[i].set_initial_v() } }")
h("objref fih_MDL14")
h('{fih_MDL14 = new FInitializeHandler(0, "initialiseV_MDL14()")}')
h("proc initialiseIons_MDL14() { for i = 0, n_MDL14-1 { a_MDL14[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL14")
h('{fih_ion_MDL14 = new FInitializeHandler(1, "initialiseIons_MDL14()")}')
# ###################### Population: MDL15
print("Population MDL15 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL15 = []
h("{ n_MDL15 = 1 }")
h("objectvar a_MDL15[n_MDL15]")
for i in range(int(h.n_MDL15)):
h("a_MDL15[%i] = new GenericMuscleCell()"%i)
h("access a_MDL15[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL15[0].position(80., 150., -80.) }")
h("proc initialiseV_MDL15() { for i = 0, n_MDL15-1 { a_MDL15[i].set_initial_v() } }")
h("objref fih_MDL15")
h('{fih_MDL15 = new FInitializeHandler(0, "initialiseV_MDL15()")}')
h("proc initialiseIons_MDL15() { for i = 0, n_MDL15-1 { a_MDL15[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL15")
h('{fih_ion_MDL15 = new FInitializeHandler(1, "initialiseIons_MDL15()")}')
# ###################### Population: MDL16
print("Population MDL16 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL16 = []
h("{ n_MDL16 = 1 }")
h("objectvar a_MDL16[n_MDL16]")
for i in range(int(h.n_MDL16)):
h("a_MDL16[%i] = new GenericMuscleCell()"%i)
h("access a_MDL16[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL16[0].position(80., 180., -80.) }")
h("proc initialiseV_MDL16() { for i = 0, n_MDL16-1 { a_MDL16[i].set_initial_v() } }")
h("objref fih_MDL16")
h('{fih_MDL16 = new FInitializeHandler(0, "initialiseV_MDL16()")}')
h("proc initialiseIons_MDL16() { for i = 0, n_MDL16-1 { a_MDL16[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL16")
h('{fih_ion_MDL16 = new FInitializeHandler(1, "initialiseIons_MDL16()")}')
# ###################### Population: MDL17
print("Population MDL17 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL17 = []
h("{ n_MDL17 = 1 }")
h("objectvar a_MDL17[n_MDL17]")
for i in range(int(h.n_MDL17)):
h("a_MDL17[%i] = new GenericMuscleCell()"%i)
h("access a_MDL17[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL17[0].position(80., 210., -80.) }")
h("proc initialiseV_MDL17() { for i = 0, n_MDL17-1 { a_MDL17[i].set_initial_v() } }")
h("objref fih_MDL17")
h('{fih_MDL17 = new FInitializeHandler(0, "initialiseV_MDL17()")}')
h("proc initialiseIons_MDL17() { for i = 0, n_MDL17-1 { a_MDL17[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL17")
h('{fih_ion_MDL17 = new FInitializeHandler(1, "initialiseIons_MDL17()")}')
# ###################### Population: MDL18
print("Population MDL18 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL18 = []
h("{ n_MDL18 = 1 }")
h("objectvar a_MDL18[n_MDL18]")
for i in range(int(h.n_MDL18)):
h("a_MDL18[%i] = new GenericMuscleCell()"%i)
h("access a_MDL18[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL18[0].position(80., 240., -80.) }")
h("proc initialiseV_MDL18() { for i = 0, n_MDL18-1 { a_MDL18[i].set_initial_v() } }")
h("objref fih_MDL18")
h('{fih_MDL18 = new FInitializeHandler(0, "initialiseV_MDL18()")}')
h("proc initialiseIons_MDL18() { for i = 0, n_MDL18-1 { a_MDL18[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL18")
h('{fih_ion_MDL18 = new FInitializeHandler(1, "initialiseIons_MDL18()")}')
# ###################### Population: MDL19
print("Population MDL19 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL19 = []
h("{ n_MDL19 = 1 }")
h("objectvar a_MDL19[n_MDL19]")
for i in range(int(h.n_MDL19)):
h("a_MDL19[%i] = new GenericMuscleCell()"%i)
h("access a_MDL19[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL19[0].position(80., 270., -80.) }")
h("proc initialiseV_MDL19() { for i = 0, n_MDL19-1 { a_MDL19[i].set_initial_v() } }")
h("objref fih_MDL19")
h('{fih_MDL19 = new FInitializeHandler(0, "initialiseV_MDL19()")}')
h("proc initialiseIons_MDL19() { for i = 0, n_MDL19-1 { a_MDL19[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL19")
h('{fih_ion_MDL19 = new FInitializeHandler(1, "initialiseIons_MDL19()")}')
# ###################### Population: MDL20
print("Population MDL20 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL20 = []
h("{ n_MDL20 = 1 }")
h("objectvar a_MDL20[n_MDL20]")
for i in range(int(h.n_MDL20)):
h("a_MDL20[%i] = new GenericMuscleCell()"%i)
h("access a_MDL20[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL20[0].position(80., 300., -80.) }")
h("proc initialiseV_MDL20() { for i = 0, n_MDL20-1 { a_MDL20[i].set_initial_v() } }")
h("objref fih_MDL20")
h('{fih_MDL20 = new FInitializeHandler(0, "initialiseV_MDL20()")}')
h("proc initialiseIons_MDL20() { for i = 0, n_MDL20-1 { a_MDL20[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL20")
h('{fih_ion_MDL20 = new FInitializeHandler(1, "initialiseIons_MDL20()")}')
# ###################### Population: MDL21
print("Population MDL21 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL21 = []
h("{ n_MDL21 = 1 }")
h("objectvar a_MDL21[n_MDL21]")
for i in range(int(h.n_MDL21)):
h("a_MDL21[%i] = new GenericMuscleCell()"%i)
h("access a_MDL21[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL21[0].position(80., 330., -80.) }")
h("proc initialiseV_MDL21() { for i = 0, n_MDL21-1 { a_MDL21[i].set_initial_v() } }")
h("objref fih_MDL21")
h('{fih_MDL21 = new FInitializeHandler(0, "initialiseV_MDL21()")}')
h("proc initialiseIons_MDL21() { for i = 0, n_MDL21-1 { a_MDL21[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL21")
h('{fih_ion_MDL21 = new FInitializeHandler(1, "initialiseIons_MDL21()")}')
# ###################### Population: MDL22
print("Population MDL22 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL22 = []
h("{ n_MDL22 = 1 }")
h("objectvar a_MDL22[n_MDL22]")
for i in range(int(h.n_MDL22)):
h("a_MDL22[%i] = new GenericMuscleCell()"%i)
h("access a_MDL22[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL22[0].position(80., 360., -80.) }")
h("proc initialiseV_MDL22() { for i = 0, n_MDL22-1 { a_MDL22[i].set_initial_v() } }")
h("objref fih_MDL22")
h('{fih_MDL22 = new FInitializeHandler(0, "initialiseV_MDL22()")}')
h("proc initialiseIons_MDL22() { for i = 0, n_MDL22-1 { a_MDL22[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL22")
h('{fih_ion_MDL22 = new FInitializeHandler(1, "initialiseIons_MDL22()")}')
# ###################### Population: MDL23
print("Population MDL23 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL23 = []
h("{ n_MDL23 = 1 }")
h("objectvar a_MDL23[n_MDL23]")
for i in range(int(h.n_MDL23)):
h("a_MDL23[%i] = new GenericMuscleCell()"%i)
h("access a_MDL23[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL23[0].position(80., 390., -80.) }")
h("proc initialiseV_MDL23() { for i = 0, n_MDL23-1 { a_MDL23[i].set_initial_v() } }")
h("objref fih_MDL23")
h('{fih_MDL23 = new FInitializeHandler(0, "initialiseV_MDL23()")}')
h("proc initialiseIons_MDL23() { for i = 0, n_MDL23-1 { a_MDL23[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL23")
h('{fih_ion_MDL23 = new FInitializeHandler(1, "initialiseIons_MDL23()")}')
# ###################### Population: MDL24
print("Population MDL24 contains 1 instance(s) of component: GenericMuscleCell of type: cell")
print("Setting the default initial concentrations for ca (used in GenericMuscleCell) to 0.0 mM (internal), 2.0 mM (external)")
h("cai0_ca_ion = 0.0")
h("cao0_ca_ion = 2.0")
h.load_file("GenericMuscleCell.hoc")
a_MDL24 = []
h("{ n_MDL24 = 1 }")
h("objectvar a_MDL24[n_MDL24]")
for i in range(int(h.n_MDL24)):
h("a_MDL24[%i] = new GenericMuscleCell()"%i)
h("access a_MDL24[%i].soma"%i)
self.next_global_id+=1
h("{ a_MDL24[0].position(80., 420., -80.) }")
h("proc initialiseV_MDL24() { for i = 0, n_MDL24-1 { a_MDL24[i].set_initial_v() } }")
h("objref fih_MDL24")
h('{fih_MDL24 = new FInitializeHandler(0, "initialiseV_MDL24()")}')
h("proc initialiseIons_MDL24() { for i = 0, n_MDL24-1 { a_MDL24[i].set_initial_ion_properties() } }")
h("objref fih_ion_MDL24")
h('{fih_ion_MDL24 = new FInitializeHandler(1, "initialiseIons_MDL24()")}')
# ###################### Electrical Projection: NC_AVAL_DA1_Generic_GJ
print("Adding electrical projection: NC_AVAL_DA1_Generic_GJ from AVAL to DA1, with 1 connection(s)")
h("objectvar syn_NC_AVAL_DA1_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[1]")
h("objectvar syn_NC_AVAL_DA1_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA1[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_DA1_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("a_DA1[0].soma { syn_NC_AVAL_DA1_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("setpointer syn_NC_AVAL_DA1_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0].vpeer, a_DA1[0].soma.v(0.5)")
h("setpointer syn_NC_AVAL_DA1_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0].vpeer, a_AVAL[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVAL_DA2_Generic_GJ
print("Adding electrical projection: NC_AVAL_DA2_Generic_GJ from AVAL to DA2, with 1 connection(s)")
h("objectvar syn_NC_AVAL_DA2_Generic_GJ_neuron_to_neuron_elec_syn_7conns_A[1]")
h("objectvar syn_NC_AVAL_DA2_Generic_GJ_neuron_to_neuron_elec_syn_7conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA2[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_DA2_Generic_GJ_neuron_to_neuron_elec_syn_7conns_A[0] = new neuron_to_neuron_elec_syn_7conns(0.5) }")
h("a_DA2[0].soma { syn_NC_AVAL_DA2_Generic_GJ_neuron_to_neuron_elec_syn_7conns_B[0] = new neuron_to_neuron_elec_syn_7conns(0.5) }")
h("setpointer syn_NC_AVAL_DA2_Generic_GJ_neuron_to_neuron_elec_syn_7conns_A[0].vpeer, a_DA2[0].soma.v(0.5)")
h("setpointer syn_NC_AVAL_DA2_Generic_GJ_neuron_to_neuron_elec_syn_7conns_B[0].vpeer, a_AVAL[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVAL_DA3_Generic_GJ
print("Adding electrical projection: NC_AVAL_DA3_Generic_GJ from AVAL to DA3, with 1 connection(s)")
h("objectvar syn_NC_AVAL_DA3_Generic_GJ_neuron_to_neuron_elec_syn_6conns_A[1]")
h("objectvar syn_NC_AVAL_DA3_Generic_GJ_neuron_to_neuron_elec_syn_6conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA3[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_DA3_Generic_GJ_neuron_to_neuron_elec_syn_6conns_A[0] = new neuron_to_neuron_elec_syn_6conns(0.5) }")
h("a_DA3[0].soma { syn_NC_AVAL_DA3_Generic_GJ_neuron_to_neuron_elec_syn_6conns_B[0] = new neuron_to_neuron_elec_syn_6conns(0.5) }")
h("setpointer syn_NC_AVAL_DA3_Generic_GJ_neuron_to_neuron_elec_syn_6conns_A[0].vpeer, a_DA3[0].soma.v(0.5)")
h("setpointer syn_NC_AVAL_DA3_Generic_GJ_neuron_to_neuron_elec_syn_6conns_B[0].vpeer, a_AVAL[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVAL_DA4_Generic_GJ
print("Adding electrical projection: NC_AVAL_DA4_Generic_GJ from AVAL to DA4, with 1 connection(s)")
h("objectvar syn_NC_AVAL_DA4_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[1]")
h("objectvar syn_NC_AVAL_DA4_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA4[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_DA4_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("a_DA4[0].soma { syn_NC_AVAL_DA4_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("setpointer syn_NC_AVAL_DA4_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0].vpeer, a_DA4[0].soma.v(0.5)")
h("setpointer syn_NC_AVAL_DA4_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0].vpeer, a_AVAL[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVAL_DA5_Generic_GJ
print("Adding electrical projection: NC_AVAL_DA5_Generic_GJ from AVAL to DA5, with 1 connection(s)")
h("objectvar syn_NC_AVAL_DA5_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[1]")
h("objectvar syn_NC_AVAL_DA5_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA5[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_DA5_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("a_DA5[0].soma { syn_NC_AVAL_DA5_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("setpointer syn_NC_AVAL_DA5_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0].vpeer, a_DA5[0].soma.v(0.5)")
h("setpointer syn_NC_AVAL_DA5_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0].vpeer, a_AVAL[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVAL_DA6_Generic_GJ
print("Adding electrical projection: NC_AVAL_DA6_Generic_GJ from AVAL to DA6, with 1 connection(s)")
h("objectvar syn_NC_AVAL_DA6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[1]")
h("objectvar syn_NC_AVAL_DA6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_DA6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("a_DA6[0].soma { syn_NC_AVAL_DA6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("setpointer syn_NC_AVAL_DA6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0].vpeer, a_DA6[0].soma.v(0.5)")
h("setpointer syn_NC_AVAL_DA6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0].vpeer, a_AVAL[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVAL_DA7_Generic_GJ
print("Adding electrical projection: NC_AVAL_DA7_Generic_GJ from AVAL to DA7, with 1 connection(s)")
h("objectvar syn_NC_AVAL_DA7_Generic_GJ_neuron_to_neuron_elec_syn_10conns_A[1]")
h("objectvar syn_NC_AVAL_DA7_Generic_GJ_neuron_to_neuron_elec_syn_10conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA7[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_DA7_Generic_GJ_neuron_to_neuron_elec_syn_10conns_A[0] = new neuron_to_neuron_elec_syn_10conns(0.5) }")
h("a_DA7[0].soma { syn_NC_AVAL_DA7_Generic_GJ_neuron_to_neuron_elec_syn_10conns_B[0] = new neuron_to_neuron_elec_syn_10conns(0.5) }")
h("setpointer syn_NC_AVAL_DA7_Generic_GJ_neuron_to_neuron_elec_syn_10conns_A[0].vpeer, a_DA7[0].soma.v(0.5)")
h("setpointer syn_NC_AVAL_DA7_Generic_GJ_neuron_to_neuron_elec_syn_10conns_B[0].vpeer, a_AVAL[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVAL_DA8_Generic_GJ
print("Adding electrical projection: NC_AVAL_DA8_Generic_GJ from AVAL to DA8, with 1 connection(s)")
h("objectvar syn_NC_AVAL_DA8_Generic_GJ_neuron_to_neuron_elec_syn_8conns_A[1]")
h("objectvar syn_NC_AVAL_DA8_Generic_GJ_neuron_to_neuron_elec_syn_8conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_DA8_Generic_GJ_neuron_to_neuron_elec_syn_8conns_A[0] = new neuron_to_neuron_elec_syn_8conns(0.5) }")
h("a_DA8[0].soma { syn_NC_AVAL_DA8_Generic_GJ_neuron_to_neuron_elec_syn_8conns_B[0] = new neuron_to_neuron_elec_syn_8conns(0.5) }")
h("setpointer syn_NC_AVAL_DA8_Generic_GJ_neuron_to_neuron_elec_syn_8conns_A[0].vpeer, a_DA8[0].soma.v(0.5)")
h("setpointer syn_NC_AVAL_DA8_Generic_GJ_neuron_to_neuron_elec_syn_8conns_B[0].vpeer, a_AVAL[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVAL_DA9_Generic_GJ
print("Adding electrical projection: NC_AVAL_DA9_Generic_GJ from AVAL to DA9, with 1 connection(s)")
h("objectvar syn_NC_AVAL_DA9_Generic_GJ_neuron_to_neuron_elec_syn_1conns_A[1]")
h("objectvar syn_NC_AVAL_DA9_Generic_GJ_neuron_to_neuron_elec_syn_1conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_DA9_Generic_GJ_neuron_to_neuron_elec_syn_1conns_A[0] = new neuron_to_neuron_elec_syn_1conns(0.5) }")
h("a_DA9[0].soma { syn_NC_AVAL_DA9_Generic_GJ_neuron_to_neuron_elec_syn_1conns_B[0] = new neuron_to_neuron_elec_syn_1conns(0.5) }")
h("setpointer syn_NC_AVAL_DA9_Generic_GJ_neuron_to_neuron_elec_syn_1conns_A[0].vpeer, a_DA9[0].soma.v(0.5)")
h("setpointer syn_NC_AVAL_DA9_Generic_GJ_neuron_to_neuron_elec_syn_1conns_B[0].vpeer, a_AVAL[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVAR_AVBL_Generic_GJ
print("Adding electrical projection: NC_AVAR_AVBL_Generic_GJ from AVAR to AVBL, with 1 connection(s)")
h("objectvar syn_NC_AVAR_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[1]")
h("objectvar syn_NC_AVAR_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("a_AVBL[0].soma { syn_NC_AVAR_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("setpointer syn_NC_AVAR_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0].vpeer, a_AVBL[0].soma.v(0.5)")
h("setpointer syn_NC_AVAR_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0].vpeer, a_AVAR[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVAR_DA1_Generic_GJ
print("Adding electrical projection: NC_AVAR_DA1_Generic_GJ from AVAR to DA1, with 1 connection(s)")
h("objectvar syn_NC_AVAR_DA1_Generic_GJ_neuron_to_neuron_elec_syn_9conns_A[1]")
h("objectvar syn_NC_AVAR_DA1_Generic_GJ_neuron_to_neuron_elec_syn_9conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA1[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_DA1_Generic_GJ_neuron_to_neuron_elec_syn_9conns_A[0] = new neuron_to_neuron_elec_syn_9conns(0.5) }")
h("a_DA1[0].soma { syn_NC_AVAR_DA1_Generic_GJ_neuron_to_neuron_elec_syn_9conns_B[0] = new neuron_to_neuron_elec_syn_9conns(0.5) }")
h("setpointer syn_NC_AVAR_DA1_Generic_GJ_neuron_to_neuron_elec_syn_9conns_A[0].vpeer, a_DA1[0].soma.v(0.5)")
h("setpointer syn_NC_AVAR_DA1_Generic_GJ_neuron_to_neuron_elec_syn_9conns_B[0].vpeer, a_AVAR[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVAR_DA2_Generic_GJ
print("Adding electrical projection: NC_AVAR_DA2_Generic_GJ from AVAR to DA2, with 1 connection(s)")
h("objectvar syn_NC_AVAR_DA2_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[1]")
h("objectvar syn_NC_AVAR_DA2_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA2[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_DA2_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("a_DA2[0].soma { syn_NC_AVAR_DA2_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("setpointer syn_NC_AVAR_DA2_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0].vpeer, a_DA2[0].soma.v(0.5)")
h("setpointer syn_NC_AVAR_DA2_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0].vpeer, a_AVAR[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVAR_DA3_Generic_GJ
print("Adding electrical projection: NC_AVAR_DA3_Generic_GJ from AVAR to DA3, with 1 connection(s)")
h("objectvar syn_NC_AVAR_DA3_Generic_GJ_neuron_to_neuron_elec_syn_7conns_A[1]")
h("objectvar syn_NC_AVAR_DA3_Generic_GJ_neuron_to_neuron_elec_syn_7conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA3[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_DA3_Generic_GJ_neuron_to_neuron_elec_syn_7conns_A[0] = new neuron_to_neuron_elec_syn_7conns(0.5) }")
h("a_DA3[0].soma { syn_NC_AVAR_DA3_Generic_GJ_neuron_to_neuron_elec_syn_7conns_B[0] = new neuron_to_neuron_elec_syn_7conns(0.5) }")
h("setpointer syn_NC_AVAR_DA3_Generic_GJ_neuron_to_neuron_elec_syn_7conns_A[0].vpeer, a_DA3[0].soma.v(0.5)")
h("setpointer syn_NC_AVAR_DA3_Generic_GJ_neuron_to_neuron_elec_syn_7conns_B[0].vpeer, a_AVAR[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVAR_DA4_Generic_GJ
print("Adding electrical projection: NC_AVAR_DA4_Generic_GJ from AVAR to DA4, with 1 connection(s)")
h("objectvar syn_NC_AVAR_DA4_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[1]")
h("objectvar syn_NC_AVAR_DA4_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA4[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_DA4_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("a_DA4[0].soma { syn_NC_AVAR_DA4_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("setpointer syn_NC_AVAR_DA4_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0].vpeer, a_DA4[0].soma.v(0.5)")
h("setpointer syn_NC_AVAR_DA4_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0].vpeer, a_AVAR[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVAR_DA5_Generic_GJ
print("Adding electrical projection: NC_AVAR_DA5_Generic_GJ from AVAR to DA5, with 1 connection(s)")
h("objectvar syn_NC_AVAR_DA5_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[1]")
h("objectvar syn_NC_AVAR_DA5_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA5[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_DA5_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[0] = new neuron_to_neuron_elec_syn_5conns(0.5) }")
h("a_DA5[0].soma { syn_NC_AVAR_DA5_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[0] = new neuron_to_neuron_elec_syn_5conns(0.5) }")
h("setpointer syn_NC_AVAR_DA5_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[0].vpeer, a_DA5[0].soma.v(0.5)")
h("setpointer syn_NC_AVAR_DA5_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[0].vpeer, a_AVAR[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVAR_DA6_Generic_GJ
print("Adding electrical projection: NC_AVAR_DA6_Generic_GJ from AVAR to DA6, with 1 connection(s)")
h("objectvar syn_NC_AVAR_DA6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[1]")
h("objectvar syn_NC_AVAR_DA6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_DA6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("a_DA6[0].soma { syn_NC_AVAR_DA6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("setpointer syn_NC_AVAR_DA6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0].vpeer, a_DA6[0].soma.v(0.5)")
h("setpointer syn_NC_AVAR_DA6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0].vpeer, a_AVAR[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVAR_DA8_Generic_GJ
print("Adding electrical projection: NC_AVAR_DA8_Generic_GJ from AVAR to DA8, with 1 connection(s)")
h("objectvar syn_NC_AVAR_DA8_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[1]")
h("objectvar syn_NC_AVAR_DA8_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_DA8_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[0] = new neuron_to_neuron_elec_syn_5conns(0.5) }")
h("a_DA8[0].soma { syn_NC_AVAR_DA8_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[0] = new neuron_to_neuron_elec_syn_5conns(0.5) }")
h("setpointer syn_NC_AVAR_DA8_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[0].vpeer, a_DA8[0].soma.v(0.5)")
h("setpointer syn_NC_AVAR_DA8_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[0].vpeer, a_AVAR[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVAR_DA9_Generic_GJ
print("Adding electrical projection: NC_AVAR_DA9_Generic_GJ from AVAR to DA9, with 1 connection(s)")
h("objectvar syn_NC_AVAR_DA9_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[1]")
h("objectvar syn_NC_AVAR_DA9_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_DA9_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("a_DA9[0].soma { syn_NC_AVAR_DA9_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("setpointer syn_NC_AVAR_DA9_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0].vpeer, a_DA9[0].soma.v(0.5)")
h("setpointer syn_NC_AVAR_DA9_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0].vpeer, a_AVAR[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVBL_AVAR_Generic_GJ
print("Adding electrical projection: NC_AVBL_AVAR_Generic_GJ from AVBL to AVAR, with 1 connection(s)")
h("objectvar syn_NC_AVBL_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[1]")
h("objectvar syn_NC_AVBL_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma], weight: 1.0
h("a_AVBL[0].soma { syn_NC_AVBL_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("a_AVAR[0].soma { syn_NC_AVBL_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("setpointer syn_NC_AVBL_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0].vpeer, a_AVAR[0].soma.v(0.5)")
h("setpointer syn_NC_AVBL_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0].vpeer, a_AVBL[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVBL_DB2_Generic_GJ
print("Adding electrical projection: NC_AVBL_DB2_Generic_GJ from AVBL to DB2, with 1 connection(s)")
h("objectvar syn_NC_AVBL_DB2_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[1]")
h("objectvar syn_NC_AVBL_DB2_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB2[0].soma], weight: 1.0
h("a_AVBL[0].soma { syn_NC_AVBL_DB2_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("a_DB2[0].soma { syn_NC_AVBL_DB2_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("setpointer syn_NC_AVBL_DB2_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0].vpeer, a_DB2[0].soma.v(0.5)")
h("setpointer syn_NC_AVBL_DB2_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0].vpeer, a_AVBL[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVBL_DB3_Generic_GJ
print("Adding electrical projection: NC_AVBL_DB3_Generic_GJ from AVBL to DB3, with 1 connection(s)")
h("objectvar syn_NC_AVBL_DB3_Generic_GJ_neuron_to_neuron_elec_syn_9conns_A[1]")
h("objectvar syn_NC_AVBL_DB3_Generic_GJ_neuron_to_neuron_elec_syn_9conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB3[0].soma], weight: 1.0
h("a_AVBL[0].soma { syn_NC_AVBL_DB3_Generic_GJ_neuron_to_neuron_elec_syn_9conns_A[0] = new neuron_to_neuron_elec_syn_9conns(0.5) }")
h("a_DB3[0].soma { syn_NC_AVBL_DB3_Generic_GJ_neuron_to_neuron_elec_syn_9conns_B[0] = new neuron_to_neuron_elec_syn_9conns(0.5) }")
h("setpointer syn_NC_AVBL_DB3_Generic_GJ_neuron_to_neuron_elec_syn_9conns_A[0].vpeer, a_DB3[0].soma.v(0.5)")
h("setpointer syn_NC_AVBL_DB3_Generic_GJ_neuron_to_neuron_elec_syn_9conns_B[0].vpeer, a_AVBL[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVBL_DB4_Generic_GJ
print("Adding electrical projection: NC_AVBL_DB4_Generic_GJ from AVBL to DB4, with 1 connection(s)")
h("objectvar syn_NC_AVBL_DB4_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[1]")
h("objectvar syn_NC_AVBL_DB4_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB4[0].soma], weight: 1.0
h("a_AVBL[0].soma { syn_NC_AVBL_DB4_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("a_DB4[0].soma { syn_NC_AVBL_DB4_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("setpointer syn_NC_AVBL_DB4_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0].vpeer, a_DB4[0].soma.v(0.5)")
h("setpointer syn_NC_AVBL_DB4_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0].vpeer, a_AVBL[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVBL_DB5_Generic_GJ
print("Adding electrical projection: NC_AVBL_DB5_Generic_GJ from AVBL to DB5, with 1 connection(s)")
h("objectvar syn_NC_AVBL_DB5_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[1]")
h("objectvar syn_NC_AVBL_DB5_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma], weight: 1.0
h("a_AVBL[0].soma { syn_NC_AVBL_DB5_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("a_DB5[0].soma { syn_NC_AVBL_DB5_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("setpointer syn_NC_AVBL_DB5_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0].vpeer, a_DB5[0].soma.v(0.5)")
h("setpointer syn_NC_AVBL_DB5_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0].vpeer, a_AVBL[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVBL_DB6_Generic_GJ
print("Adding electrical projection: NC_AVBL_DB6_Generic_GJ from AVBL to DB6, with 1 connection(s)")
h("objectvar syn_NC_AVBL_DB6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[1]")
h("objectvar syn_NC_AVBL_DB6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma], weight: 1.0
h("a_AVBL[0].soma { syn_NC_AVBL_DB6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("a_DB6[0].soma { syn_NC_AVBL_DB6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("setpointer syn_NC_AVBL_DB6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0].vpeer, a_DB6[0].soma.v(0.5)")
h("setpointer syn_NC_AVBL_DB6_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0].vpeer, a_AVBL[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVBL_DB7_Generic_GJ
print("Adding electrical projection: NC_AVBL_DB7_Generic_GJ from AVBL to DB7, with 1 connection(s)")
h("objectvar syn_NC_AVBL_DB7_Generic_GJ_neuron_to_neuron_elec_syn_13conns_A[1]")
h("objectvar syn_NC_AVBL_DB7_Generic_GJ_neuron_to_neuron_elec_syn_13conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma], weight: 1.0
h("a_AVBL[0].soma { syn_NC_AVBL_DB7_Generic_GJ_neuron_to_neuron_elec_syn_13conns_A[0] = new neuron_to_neuron_elec_syn_13conns(0.5) }")
h("a_DB7[0].soma { syn_NC_AVBL_DB7_Generic_GJ_neuron_to_neuron_elec_syn_13conns_B[0] = new neuron_to_neuron_elec_syn_13conns(0.5) }")
h("setpointer syn_NC_AVBL_DB7_Generic_GJ_neuron_to_neuron_elec_syn_13conns_A[0].vpeer, a_DB7[0].soma.v(0.5)")
h("setpointer syn_NC_AVBL_DB7_Generic_GJ_neuron_to_neuron_elec_syn_13conns_B[0].vpeer, a_AVBL[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVBR_DB1_Generic_GJ
print("Adding electrical projection: NC_AVBR_DB1_Generic_GJ from AVBR to DB1, with 1 connection(s)")
h("objectvar syn_NC_AVBR_DB1_Generic_GJ_neuron_to_neuron_elec_syn_15conns_A[1]")
h("objectvar syn_NC_AVBR_DB1_Generic_GJ_neuron_to_neuron_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB1[0].soma], weight: 1.0
h("a_AVBR[0].soma { syn_NC_AVBR_DB1_Generic_GJ_neuron_to_neuron_elec_syn_15conns_A[0] = new neuron_to_neuron_elec_syn_15conns(0.5) }")
h("a_DB1[0].soma { syn_NC_AVBR_DB1_Generic_GJ_neuron_to_neuron_elec_syn_15conns_B[0] = new neuron_to_neuron_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_AVBR_DB1_Generic_GJ_neuron_to_neuron_elec_syn_15conns_A[0].vpeer, a_DB1[0].soma.v(0.5)")
h("setpointer syn_NC_AVBR_DB1_Generic_GJ_neuron_to_neuron_elec_syn_15conns_B[0].vpeer, a_AVBR[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVBR_DB2_Generic_GJ
print("Adding electrical projection: NC_AVBR_DB2_Generic_GJ from AVBR to DB2, with 1 connection(s)")
h("objectvar syn_NC_AVBR_DB2_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[1]")
h("objectvar syn_NC_AVBR_DB2_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB2[0].soma], weight: 1.0
h("a_AVBR[0].soma { syn_NC_AVBR_DB2_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("a_DB2[0].soma { syn_NC_AVBR_DB2_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("setpointer syn_NC_AVBR_DB2_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0].vpeer, a_DB2[0].soma.v(0.5)")
h("setpointer syn_NC_AVBR_DB2_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0].vpeer, a_AVBR[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVBR_DB3_Generic_GJ
print("Adding electrical projection: NC_AVBR_DB3_Generic_GJ from AVBR to DB3, with 1 connection(s)")
h("objectvar syn_NC_AVBR_DB3_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[1]")
h("objectvar syn_NC_AVBR_DB3_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB3[0].soma], weight: 1.0
h("a_AVBR[0].soma { syn_NC_AVBR_DB3_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("a_DB3[0].soma { syn_NC_AVBR_DB3_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("setpointer syn_NC_AVBR_DB3_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0].vpeer, a_DB3[0].soma.v(0.5)")
h("setpointer syn_NC_AVBR_DB3_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0].vpeer, a_AVBR[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVBR_DB4_Generic_GJ
print("Adding electrical projection: NC_AVBR_DB4_Generic_GJ from AVBR to DB4, with 1 connection(s)")
h("objectvar syn_NC_AVBR_DB4_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[1]")
h("objectvar syn_NC_AVBR_DB4_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB4[0].soma], weight: 1.0
h("a_AVBR[0].soma { syn_NC_AVBR_DB4_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[0] = new neuron_to_neuron_elec_syn_5conns(0.5) }")
h("a_DB4[0].soma { syn_NC_AVBR_DB4_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[0] = new neuron_to_neuron_elec_syn_5conns(0.5) }")
h("setpointer syn_NC_AVBR_DB4_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[0].vpeer, a_DB4[0].soma.v(0.5)")
h("setpointer syn_NC_AVBR_DB4_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[0].vpeer, a_AVBR[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVBR_DB5_Generic_GJ
print("Adding electrical projection: NC_AVBR_DB5_Generic_GJ from AVBR to DB5, with 1 connection(s)")
h("objectvar syn_NC_AVBR_DB5_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[1]")
h("objectvar syn_NC_AVBR_DB5_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma], weight: 1.0
h("a_AVBR[0].soma { syn_NC_AVBR_DB5_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("a_DB5[0].soma { syn_NC_AVBR_DB5_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("setpointer syn_NC_AVBR_DB5_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0].vpeer, a_DB5[0].soma.v(0.5)")
h("setpointer syn_NC_AVBR_DB5_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0].vpeer, a_AVBR[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVBR_DB6_Generic_GJ
print("Adding electrical projection: NC_AVBR_DB6_Generic_GJ from AVBR to DB6, with 1 connection(s)")
h("objectvar syn_NC_AVBR_DB6_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[1]")
h("objectvar syn_NC_AVBR_DB6_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma], weight: 1.0
h("a_AVBR[0].soma { syn_NC_AVBR_DB6_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("a_DB6[0].soma { syn_NC_AVBR_DB6_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("setpointer syn_NC_AVBR_DB6_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0].vpeer, a_DB6[0].soma.v(0.5)")
h("setpointer syn_NC_AVBR_DB6_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0].vpeer, a_AVBR[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_AVBR_DB7_Generic_GJ
print("Adding electrical projection: NC_AVBR_DB7_Generic_GJ from AVBR to DB7, with 1 connection(s)")
h("objectvar syn_NC_AVBR_DB7_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[1]")
h("objectvar syn_NC_AVBR_DB7_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma], weight: 1.0
h("a_AVBR[0].soma { syn_NC_AVBR_DB7_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("a_DB7[0].soma { syn_NC_AVBR_DB7_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("setpointer syn_NC_AVBR_DB7_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0].vpeer, a_DB7[0].soma.v(0.5)")
h("setpointer syn_NC_AVBR_DB7_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0].vpeer, a_AVBR[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DA1_AVAL_Generic_GJ
print("Adding electrical projection: NC_DA1_AVAL_Generic_GJ from DA1 to AVAL, with 1 connection(s)")
h("objectvar syn_NC_DA1_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[1]")
h("objectvar syn_NC_DA1_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA1[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma], weight: 1.0
h("a_DA1[0].soma { syn_NC_DA1_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("a_AVAL[0].soma { syn_NC_DA1_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("setpointer syn_NC_DA1_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0].vpeer, a_AVAL[0].soma.v(0.5)")
h("setpointer syn_NC_DA1_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0].vpeer, a_DA1[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DA1_AVAR_Generic_GJ
print("Adding electrical projection: NC_DA1_AVAR_Generic_GJ from DA1 to AVAR, with 1 connection(s)")
h("objectvar syn_NC_DA1_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_9conns_A[1]")
h("objectvar syn_NC_DA1_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_9conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA1[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma], weight: 1.0
h("a_DA1[0].soma { syn_NC_DA1_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_9conns_A[0] = new neuron_to_neuron_elec_syn_9conns(0.5) }")
h("a_AVAR[0].soma { syn_NC_DA1_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_9conns_B[0] = new neuron_to_neuron_elec_syn_9conns(0.5) }")
h("setpointer syn_NC_DA1_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_9conns_A[0].vpeer, a_AVAR[0].soma.v(0.5)")
h("setpointer syn_NC_DA1_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_9conns_B[0].vpeer, a_DA1[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DA2_AVAL_Generic_GJ
print("Adding electrical projection: NC_DA2_AVAL_Generic_GJ from DA2 to AVAL, with 1 connection(s)")
h("objectvar syn_NC_DA2_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_7conns_A[1]")
h("objectvar syn_NC_DA2_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_7conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma], weight: 1.0
h("a_DA2[0].soma { syn_NC_DA2_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_7conns_A[0] = new neuron_to_neuron_elec_syn_7conns(0.5) }")
h("a_AVAL[0].soma { syn_NC_DA2_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_7conns_B[0] = new neuron_to_neuron_elec_syn_7conns(0.5) }")
h("setpointer syn_NC_DA2_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_7conns_A[0].vpeer, a_AVAL[0].soma.v(0.5)")
h("setpointer syn_NC_DA2_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_7conns_B[0].vpeer, a_DA2[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DA2_AVAR_Generic_GJ
print("Adding electrical projection: NC_DA2_AVAR_Generic_GJ from DA2 to AVAR, with 1 connection(s)")
h("objectvar syn_NC_DA2_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[1]")
h("objectvar syn_NC_DA2_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma], weight: 1.0
h("a_DA2[0].soma { syn_NC_DA2_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("a_AVAR[0].soma { syn_NC_DA2_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("setpointer syn_NC_DA2_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0].vpeer, a_AVAR[0].soma.v(0.5)")
h("setpointer syn_NC_DA2_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0].vpeer, a_DA2[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DA3_AVAL_Generic_GJ
print("Adding electrical projection: NC_DA3_AVAL_Generic_GJ from DA3 to AVAL, with 1 connection(s)")
h("objectvar syn_NC_DA3_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_6conns_A[1]")
h("objectvar syn_NC_DA3_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_6conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma], weight: 1.0
h("a_DA3[0].soma { syn_NC_DA3_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_6conns_A[0] = new neuron_to_neuron_elec_syn_6conns(0.5) }")
h("a_AVAL[0].soma { syn_NC_DA3_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_6conns_B[0] = new neuron_to_neuron_elec_syn_6conns(0.5) }")
h("setpointer syn_NC_DA3_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_6conns_A[0].vpeer, a_AVAL[0].soma.v(0.5)")
h("setpointer syn_NC_DA3_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_6conns_B[0].vpeer, a_DA3[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DA3_AVAR_Generic_GJ
print("Adding electrical projection: NC_DA3_AVAR_Generic_GJ from DA3 to AVAR, with 1 connection(s)")
h("objectvar syn_NC_DA3_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_7conns_A[1]")
h("objectvar syn_NC_DA3_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_7conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma], weight: 1.0
h("a_DA3[0].soma { syn_NC_DA3_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_7conns_A[0] = new neuron_to_neuron_elec_syn_7conns(0.5) }")
h("a_AVAR[0].soma { syn_NC_DA3_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_7conns_B[0] = new neuron_to_neuron_elec_syn_7conns(0.5) }")
h("setpointer syn_NC_DA3_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_7conns_A[0].vpeer, a_AVAR[0].soma.v(0.5)")
h("setpointer syn_NC_DA3_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_7conns_B[0].vpeer, a_DA3[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DA4_AVAL_Generic_GJ
print("Adding electrical projection: NC_DA4_AVAL_Generic_GJ from DA4 to AVAL, with 1 connection(s)")
h("objectvar syn_NC_DA4_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[1]")
h("objectvar syn_NC_DA4_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma], weight: 1.0
h("a_DA4[0].soma { syn_NC_DA4_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("a_AVAL[0].soma { syn_NC_DA4_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("setpointer syn_NC_DA4_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0].vpeer, a_AVAL[0].soma.v(0.5)")
h("setpointer syn_NC_DA4_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0].vpeer, a_DA4[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DA4_AVAR_Generic_GJ
print("Adding electrical projection: NC_DA4_AVAR_Generic_GJ from DA4 to AVAR, with 1 connection(s)")
h("objectvar syn_NC_DA4_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[1]")
h("objectvar syn_NC_DA4_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma], weight: 1.0
h("a_DA4[0].soma { syn_NC_DA4_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("a_AVAR[0].soma { syn_NC_DA4_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("setpointer syn_NC_DA4_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0].vpeer, a_AVAR[0].soma.v(0.5)")
h("setpointer syn_NC_DA4_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0].vpeer, a_DA4[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DA5_AVAL_Generic_GJ
print("Adding electrical projection: NC_DA5_AVAL_Generic_GJ from DA5 to AVAL, with 1 connection(s)")
h("objectvar syn_NC_DA5_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[1]")
h("objectvar syn_NC_DA5_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma], weight: 1.0
h("a_DA5[0].soma { syn_NC_DA5_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("a_AVAL[0].soma { syn_NC_DA5_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("setpointer syn_NC_DA5_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0].vpeer, a_AVAL[0].soma.v(0.5)")
h("setpointer syn_NC_DA5_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0].vpeer, a_DA5[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DA5_AVAR_Generic_GJ
print("Adding electrical projection: NC_DA5_AVAR_Generic_GJ from DA5 to AVAR, with 1 connection(s)")
h("objectvar syn_NC_DA5_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[1]")
h("objectvar syn_NC_DA5_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma], weight: 1.0
h("a_DA5[0].soma { syn_NC_DA5_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[0] = new neuron_to_neuron_elec_syn_5conns(0.5) }")
h("a_AVAR[0].soma { syn_NC_DA5_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[0] = new neuron_to_neuron_elec_syn_5conns(0.5) }")
h("setpointer syn_NC_DA5_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[0].vpeer, a_AVAR[0].soma.v(0.5)")
h("setpointer syn_NC_DA5_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[0].vpeer, a_DA5[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DA6_AVAL_Generic_GJ
print("Adding electrical projection: NC_DA6_AVAL_Generic_GJ from DA6 to AVAL, with 1 connection(s)")
h("objectvar syn_NC_DA6_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[1]")
h("objectvar syn_NC_DA6_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma], weight: 1.0
h("a_DA6[0].soma { syn_NC_DA6_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("a_AVAL[0].soma { syn_NC_DA6_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("setpointer syn_NC_DA6_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0].vpeer, a_AVAL[0].soma.v(0.5)")
h("setpointer syn_NC_DA6_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0].vpeer, a_DA6[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DA6_AVAR_Generic_GJ
print("Adding electrical projection: NC_DA6_AVAR_Generic_GJ from DA6 to AVAR, with 1 connection(s)")
h("objectvar syn_NC_DA6_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[1]")
h("objectvar syn_NC_DA6_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma], weight: 1.0
h("a_DA6[0].soma { syn_NC_DA6_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("a_AVAR[0].soma { syn_NC_DA6_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("setpointer syn_NC_DA6_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0].vpeer, a_AVAR[0].soma.v(0.5)")
h("setpointer syn_NC_DA6_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0].vpeer, a_DA6[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DA7_AVAL_Generic_GJ
print("Adding electrical projection: NC_DA7_AVAL_Generic_GJ from DA7 to AVAL, with 1 connection(s)")
h("objectvar syn_NC_DA7_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_10conns_A[1]")
h("objectvar syn_NC_DA7_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_10conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma], weight: 1.0
h("a_DA7[0].soma { syn_NC_DA7_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_10conns_A[0] = new neuron_to_neuron_elec_syn_10conns(0.5) }")
h("a_AVAL[0].soma { syn_NC_DA7_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_10conns_B[0] = new neuron_to_neuron_elec_syn_10conns(0.5) }")
h("setpointer syn_NC_DA7_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_10conns_A[0].vpeer, a_AVAL[0].soma.v(0.5)")
h("setpointer syn_NC_DA7_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_10conns_B[0].vpeer, a_DA7[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DA8_AVAL_Generic_GJ
print("Adding electrical projection: NC_DA8_AVAL_Generic_GJ from DA8 to AVAL, with 1 connection(s)")
h("objectvar syn_NC_DA8_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_8conns_A[1]")
h("objectvar syn_NC_DA8_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_8conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma], weight: 1.0
h("a_DA8[0].soma { syn_NC_DA8_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_8conns_A[0] = new neuron_to_neuron_elec_syn_8conns(0.5) }")
h("a_AVAL[0].soma { syn_NC_DA8_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_8conns_B[0] = new neuron_to_neuron_elec_syn_8conns(0.5) }")
h("setpointer syn_NC_DA8_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_8conns_A[0].vpeer, a_AVAL[0].soma.v(0.5)")
h("setpointer syn_NC_DA8_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_8conns_B[0].vpeer, a_DA8[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DA8_AVAR_Generic_GJ
print("Adding electrical projection: NC_DA8_AVAR_Generic_GJ from DA8 to AVAR, with 1 connection(s)")
h("objectvar syn_NC_DA8_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[1]")
h("objectvar syn_NC_DA8_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma], weight: 1.0
h("a_DA8[0].soma { syn_NC_DA8_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[0] = new neuron_to_neuron_elec_syn_5conns(0.5) }")
h("a_AVAR[0].soma { syn_NC_DA8_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[0] = new neuron_to_neuron_elec_syn_5conns(0.5) }")
h("setpointer syn_NC_DA8_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[0].vpeer, a_AVAR[0].soma.v(0.5)")
h("setpointer syn_NC_DA8_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[0].vpeer, a_DA8[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DA9_AVAL_Generic_GJ
print("Adding electrical projection: NC_DA9_AVAL_Generic_GJ from DA9 to AVAL, with 1 connection(s)")
h("objectvar syn_NC_DA9_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_1conns_A[1]")
h("objectvar syn_NC_DA9_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_1conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma], weight: 1.0
h("a_DA9[0].soma { syn_NC_DA9_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_1conns_A[0] = new neuron_to_neuron_elec_syn_1conns(0.5) }")
h("a_AVAL[0].soma { syn_NC_DA9_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_1conns_B[0] = new neuron_to_neuron_elec_syn_1conns(0.5) }")
h("setpointer syn_NC_DA9_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_1conns_A[0].vpeer, a_AVAL[0].soma.v(0.5)")
h("setpointer syn_NC_DA9_AVAL_Generic_GJ_neuron_to_neuron_elec_syn_1conns_B[0].vpeer, a_DA9[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DA9_AVAR_Generic_GJ
print("Adding electrical projection: NC_DA9_AVAR_Generic_GJ from DA9 to AVAR, with 1 connection(s)")
h("objectvar syn_NC_DA9_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[1]")
h("objectvar syn_NC_DA9_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma], weight: 1.0
h("a_DA9[0].soma { syn_NC_DA9_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("a_AVAR[0].soma { syn_NC_DA9_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("setpointer syn_NC_DA9_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0].vpeer, a_AVAR[0].soma.v(0.5)")
h("setpointer syn_NC_DA9_AVAR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0].vpeer, a_DA9[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DB1_AVBR_Generic_GJ
print("Adding electrical projection: NC_DB1_AVBR_Generic_GJ from DB1 to AVBR, with 1 connection(s)")
h("objectvar syn_NC_DB1_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_15conns_A[1]")
h("objectvar syn_NC_DB1_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB1[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma], weight: 1.0
h("a_DB1[0].soma { syn_NC_DB1_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_15conns_A[0] = new neuron_to_neuron_elec_syn_15conns(0.5) }")
h("a_AVBR[0].soma { syn_NC_DB1_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_15conns_B[0] = new neuron_to_neuron_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_DB1_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_15conns_A[0].vpeer, a_AVBR[0].soma.v(0.5)")
h("setpointer syn_NC_DB1_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_15conns_B[0].vpeer, a_DB1[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DB2_AVBL_Generic_GJ
print("Adding electrical projection: NC_DB2_AVBL_Generic_GJ from DB2 to AVBL, with 1 connection(s)")
h("objectvar syn_NC_DB2_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[1]")
h("objectvar syn_NC_DB2_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma], weight: 1.0
h("a_DB2[0].soma { syn_NC_DB2_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("a_AVBL[0].soma { syn_NC_DB2_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("setpointer syn_NC_DB2_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0].vpeer, a_AVBL[0].soma.v(0.5)")
h("setpointer syn_NC_DB2_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0].vpeer, a_DB2[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DB2_AVBR_Generic_GJ
print("Adding electrical projection: NC_DB2_AVBR_Generic_GJ from DB2 to AVBR, with 1 connection(s)")
h("objectvar syn_NC_DB2_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[1]")
h("objectvar syn_NC_DB2_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma], weight: 1.0
h("a_DB2[0].soma { syn_NC_DB2_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("a_AVBR[0].soma { syn_NC_DB2_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("setpointer syn_NC_DB2_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0].vpeer, a_AVBR[0].soma.v(0.5)")
h("setpointer syn_NC_DB2_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0].vpeer, a_DB2[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DB3_AVBL_Generic_GJ
print("Adding electrical projection: NC_DB3_AVBL_Generic_GJ from DB3 to AVBL, with 1 connection(s)")
h("objectvar syn_NC_DB3_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_9conns_A[1]")
h("objectvar syn_NC_DB3_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_9conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma], weight: 1.0
h("a_DB3[0].soma { syn_NC_DB3_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_9conns_A[0] = new neuron_to_neuron_elec_syn_9conns(0.5) }")
h("a_AVBL[0].soma { syn_NC_DB3_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_9conns_B[0] = new neuron_to_neuron_elec_syn_9conns(0.5) }")
h("setpointer syn_NC_DB3_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_9conns_A[0].vpeer, a_AVBL[0].soma.v(0.5)")
h("setpointer syn_NC_DB3_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_9conns_B[0].vpeer, a_DB3[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DB3_AVBR_Generic_GJ
print("Adding electrical projection: NC_DB3_AVBR_Generic_GJ from DB3 to AVBR, with 1 connection(s)")
h("objectvar syn_NC_DB3_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[1]")
h("objectvar syn_NC_DB3_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma], weight: 1.0
h("a_DB3[0].soma { syn_NC_DB3_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("a_AVBR[0].soma { syn_NC_DB3_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0] = new neuron_to_neuron_elec_syn_2conns(0.5) }")
h("setpointer syn_NC_DB3_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_2conns_A[0].vpeer, a_AVBR[0].soma.v(0.5)")
h("setpointer syn_NC_DB3_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_2conns_B[0].vpeer, a_DB3[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DB4_AVBL_Generic_GJ
print("Adding electrical projection: NC_DB4_AVBL_Generic_GJ from DB4 to AVBL, with 1 connection(s)")
h("objectvar syn_NC_DB4_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[1]")
h("objectvar syn_NC_DB4_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma], weight: 1.0
h("a_DB4[0].soma { syn_NC_DB4_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("a_AVBL[0].soma { syn_NC_DB4_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("setpointer syn_NC_DB4_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0].vpeer, a_AVBL[0].soma.v(0.5)")
h("setpointer syn_NC_DB4_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0].vpeer, a_DB4[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DB4_AVBR_Generic_GJ
print("Adding electrical projection: NC_DB4_AVBR_Generic_GJ from DB4 to AVBR, with 1 connection(s)")
h("objectvar syn_NC_DB4_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[1]")
h("objectvar syn_NC_DB4_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma], weight: 1.0
h("a_DB4[0].soma { syn_NC_DB4_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[0] = new neuron_to_neuron_elec_syn_5conns(0.5) }")
h("a_AVBR[0].soma { syn_NC_DB4_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[0] = new neuron_to_neuron_elec_syn_5conns(0.5) }")
h("setpointer syn_NC_DB4_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_A[0].vpeer, a_AVBR[0].soma.v(0.5)")
h("setpointer syn_NC_DB4_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_5conns_B[0].vpeer, a_DB4[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DB5_AVBL_Generic_GJ
print("Adding electrical projection: NC_DB5_AVBL_Generic_GJ from DB5 to AVBL, with 1 connection(s)")
h("objectvar syn_NC_DB5_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[1]")
h("objectvar syn_NC_DB5_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma], weight: 1.0
h("a_DB5[0].soma { syn_NC_DB5_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("a_AVBL[0].soma { syn_NC_DB5_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("setpointer syn_NC_DB5_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0].vpeer, a_AVBL[0].soma.v(0.5)")
h("setpointer syn_NC_DB5_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0].vpeer, a_DB5[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DB5_AVBR_Generic_GJ
print("Adding electrical projection: NC_DB5_AVBR_Generic_GJ from DB5 to AVBR, with 1 connection(s)")
h("objectvar syn_NC_DB5_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[1]")
h("objectvar syn_NC_DB5_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma], weight: 1.0
h("a_DB5[0].soma { syn_NC_DB5_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("a_AVBR[0].soma { syn_NC_DB5_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("setpointer syn_NC_DB5_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0].vpeer, a_AVBR[0].soma.v(0.5)")
h("setpointer syn_NC_DB5_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0].vpeer, a_DB5[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DB6_AVBL_Generic_GJ
print("Adding electrical projection: NC_DB6_AVBL_Generic_GJ from DB6 to AVBL, with 1 connection(s)")
h("objectvar syn_NC_DB6_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[1]")
h("objectvar syn_NC_DB6_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma], weight: 1.0
h("a_DB6[0].soma { syn_NC_DB6_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("a_AVBL[0].soma { syn_NC_DB6_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("setpointer syn_NC_DB6_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0].vpeer, a_AVBL[0].soma.v(0.5)")
h("setpointer syn_NC_DB6_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0].vpeer, a_DB6[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DB6_AVBR_Generic_GJ
print("Adding electrical projection: NC_DB6_AVBR_Generic_GJ from DB6 to AVBR, with 1 connection(s)")
h("objectvar syn_NC_DB6_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[1]")
h("objectvar syn_NC_DB6_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma], weight: 1.0
h("a_DB6[0].soma { syn_NC_DB6_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("a_AVBR[0].soma { syn_NC_DB6_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0] = new neuron_to_neuron_elec_syn_4conns(0.5) }")
h("setpointer syn_NC_DB6_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_A[0].vpeer, a_AVBR[0].soma.v(0.5)")
h("setpointer syn_NC_DB6_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_4conns_B[0].vpeer, a_DB6[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DB7_AVBL_Generic_GJ
print("Adding electrical projection: NC_DB7_AVBL_Generic_GJ from DB7 to AVBL, with 1 connection(s)")
h("objectvar syn_NC_DB7_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_13conns_A[1]")
h("objectvar syn_NC_DB7_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_13conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma], weight: 1.0
h("a_DB7[0].soma { syn_NC_DB7_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_13conns_A[0] = new neuron_to_neuron_elec_syn_13conns(0.5) }")
h("a_AVBL[0].soma { syn_NC_DB7_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_13conns_B[0] = new neuron_to_neuron_elec_syn_13conns(0.5) }")
h("setpointer syn_NC_DB7_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_13conns_A[0].vpeer, a_AVBL[0].soma.v(0.5)")
h("setpointer syn_NC_DB7_AVBL_Generic_GJ_neuron_to_neuron_elec_syn_13conns_B[0].vpeer, a_DB7[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_DB7_AVBR_Generic_GJ
print("Adding electrical projection: NC_DB7_AVBR_Generic_GJ from DB7 to AVBR, with 1 connection(s)")
h("objectvar syn_NC_DB7_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[1]")
h("objectvar syn_NC_DB7_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma], weight: 1.0
h("a_DB7[0].soma { syn_NC_DB7_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("a_AVBR[0].soma { syn_NC_DB7_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0] = new neuron_to_neuron_elec_syn_3conns(0.5) }")
h("setpointer syn_NC_DB7_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_A[0].vpeer, a_AVBR[0].soma.v(0.5)")
h("setpointer syn_NC_DB7_AVBR_Generic_GJ_neuron_to_neuron_elec_syn_3conns_B[0].vpeer, a_DB7[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL01_MDL02_Generic_GJ
print("Adding electrical projection: NC_MDL01_MDL02_Generic_GJ from MDL01 to MDL02, with 1 connection(s)")
h("objectvar syn_NC_MDL01_MDL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL01_MDL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL01[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL02[0].soma], weight: 1.0
h("a_MDL01[0].soma { syn_NC_MDL01_MDL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL02[0].soma { syn_NC_MDL01_MDL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL01_MDL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL02[0].soma.v(0.5)")
h("setpointer syn_NC_MDL01_MDL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL01[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL01_MDL03_Generic_GJ
print("Adding electrical projection: NC_MDL01_MDL03_Generic_GJ from MDL01 to MDL03, with 1 connection(s)")
h("objectvar syn_NC_MDL01_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL01_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL01[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL03[0].soma], weight: 1.0
h("a_MDL01[0].soma { syn_NC_MDL01_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL03[0].soma { syn_NC_MDL01_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL01_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL03[0].soma.v(0.5)")
h("setpointer syn_NC_MDL01_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL01[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL02_MDL01_Generic_GJ
print("Adding electrical projection: NC_MDL02_MDL01_Generic_GJ from MDL02 to MDL01, with 1 connection(s)")
h("objectvar syn_NC_MDL02_MDL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL02_MDL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL02[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL01[0].soma], weight: 1.0
h("a_MDL02[0].soma { syn_NC_MDL02_MDL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL01[0].soma { syn_NC_MDL02_MDL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL02_MDL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL01[0].soma.v(0.5)")
h("setpointer syn_NC_MDL02_MDL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL02[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL02_MDL03_Generic_GJ
print("Adding electrical projection: NC_MDL02_MDL03_Generic_GJ from MDL02 to MDL03, with 1 connection(s)")
h("objectvar syn_NC_MDL02_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL02_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL02[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL03[0].soma], weight: 1.0
h("a_MDL02[0].soma { syn_NC_MDL02_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL03[0].soma { syn_NC_MDL02_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL02_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL03[0].soma.v(0.5)")
h("setpointer syn_NC_MDL02_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL02[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL03_MDL01_Generic_GJ
print("Adding electrical projection: NC_MDL03_MDL01_Generic_GJ from MDL03 to MDL01, with 1 connection(s)")
h("objectvar syn_NC_MDL03_MDL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL03_MDL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL03[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL01[0].soma], weight: 1.0
h("a_MDL03[0].soma { syn_NC_MDL03_MDL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL01[0].soma { syn_NC_MDL03_MDL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL03_MDL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL01[0].soma.v(0.5)")
h("setpointer syn_NC_MDL03_MDL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL03[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL03_MDL02_Generic_GJ
print("Adding electrical projection: NC_MDL03_MDL02_Generic_GJ from MDL03 to MDL02, with 1 connection(s)")
h("objectvar syn_NC_MDL03_MDL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL03_MDL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL03[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL02[0].soma], weight: 1.0
h("a_MDL03[0].soma { syn_NC_MDL03_MDL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL02[0].soma { syn_NC_MDL03_MDL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL03_MDL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL02[0].soma.v(0.5)")
h("setpointer syn_NC_MDL03_MDL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL03[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL03_MDL04_Generic_GJ
print("Adding electrical projection: NC_MDL03_MDL04_Generic_GJ from MDL03 to MDL04, with 1 connection(s)")
h("objectvar syn_NC_MDL03_MDL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL03_MDL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL03[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL04[0].soma], weight: 1.0
h("a_MDL03[0].soma { syn_NC_MDL03_MDL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL04[0].soma { syn_NC_MDL03_MDL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL03_MDL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL04[0].soma.v(0.5)")
h("setpointer syn_NC_MDL03_MDL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL03[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL04_MDL03_Generic_GJ
print("Adding electrical projection: NC_MDL04_MDL03_Generic_GJ from MDL04 to MDL03, with 1 connection(s)")
h("objectvar syn_NC_MDL04_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL04_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL04[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL03[0].soma], weight: 1.0
h("a_MDL04[0].soma { syn_NC_MDL04_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL03[0].soma { syn_NC_MDL04_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL04_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL03[0].soma.v(0.5)")
h("setpointer syn_NC_MDL04_MDL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL04[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL04_MDL05_Generic_GJ
print("Adding electrical projection: NC_MDL04_MDL05_Generic_GJ from MDL04 to MDL05, with 1 connection(s)")
h("objectvar syn_NC_MDL04_MDL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL04_MDL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL04[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL05[0].soma], weight: 1.0
h("a_MDL04[0].soma { syn_NC_MDL04_MDL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL05[0].soma { syn_NC_MDL04_MDL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL04_MDL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL05[0].soma.v(0.5)")
h("setpointer syn_NC_MDL04_MDL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL04[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL05_MDL04_Generic_GJ
print("Adding electrical projection: NC_MDL05_MDL04_Generic_GJ from MDL05 to MDL04, with 1 connection(s)")
h("objectvar syn_NC_MDL05_MDL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL05_MDL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL05[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL04[0].soma], weight: 1.0
h("a_MDL05[0].soma { syn_NC_MDL05_MDL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL04[0].soma { syn_NC_MDL05_MDL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL05_MDL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL04[0].soma.v(0.5)")
h("setpointer syn_NC_MDL05_MDL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL05[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL05_MDL06_Generic_GJ
print("Adding electrical projection: NC_MDL05_MDL06_Generic_GJ from MDL05 to MDL06, with 1 connection(s)")
h("objectvar syn_NC_MDL05_MDL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL05_MDL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL05[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL06[0].soma], weight: 1.0
h("a_MDL05[0].soma { syn_NC_MDL05_MDL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL06[0].soma { syn_NC_MDL05_MDL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL05_MDL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL06[0].soma.v(0.5)")
h("setpointer syn_NC_MDL05_MDL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL05[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL06_MDL05_Generic_GJ
print("Adding electrical projection: NC_MDL06_MDL05_Generic_GJ from MDL06 to MDL05, with 1 connection(s)")
h("objectvar syn_NC_MDL06_MDL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL06_MDL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL06[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL05[0].soma], weight: 1.0
h("a_MDL06[0].soma { syn_NC_MDL06_MDL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL05[0].soma { syn_NC_MDL06_MDL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL06_MDL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL05[0].soma.v(0.5)")
h("setpointer syn_NC_MDL06_MDL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL06[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL06_MDL07_Generic_GJ
print("Adding electrical projection: NC_MDL06_MDL07_Generic_GJ from MDL06 to MDL07, with 1 connection(s)")
h("objectvar syn_NC_MDL06_MDL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL06_MDL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL06[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL07[0].soma], weight: 1.0
h("a_MDL06[0].soma { syn_NC_MDL06_MDL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL07[0].soma { syn_NC_MDL06_MDL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL06_MDL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL07[0].soma.v(0.5)")
h("setpointer syn_NC_MDL06_MDL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL06[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL07_MDL06_Generic_GJ
print("Adding electrical projection: NC_MDL07_MDL06_Generic_GJ from MDL07 to MDL06, with 1 connection(s)")
h("objectvar syn_NC_MDL07_MDL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL07_MDL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL07[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL06[0].soma], weight: 1.0
h("a_MDL07[0].soma { syn_NC_MDL07_MDL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL06[0].soma { syn_NC_MDL07_MDL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL07_MDL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL06[0].soma.v(0.5)")
h("setpointer syn_NC_MDL07_MDL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL07[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL07_MDL08_Generic_GJ
print("Adding electrical projection: NC_MDL07_MDL08_Generic_GJ from MDL07 to MDL08, with 1 connection(s)")
h("objectvar syn_NC_MDL07_MDL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL07_MDL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL07[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL08[0].soma], weight: 1.0
h("a_MDL07[0].soma { syn_NC_MDL07_MDL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL08[0].soma { syn_NC_MDL07_MDL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL07_MDL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL08[0].soma.v(0.5)")
h("setpointer syn_NC_MDL07_MDL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL07[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL08_MDL07_Generic_GJ
print("Adding electrical projection: NC_MDL08_MDL07_Generic_GJ from MDL08 to MDL07, with 1 connection(s)")
h("objectvar syn_NC_MDL08_MDL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL08_MDL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL08[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL07[0].soma], weight: 1.0
h("a_MDL08[0].soma { syn_NC_MDL08_MDL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL07[0].soma { syn_NC_MDL08_MDL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL08_MDL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL07[0].soma.v(0.5)")
h("setpointer syn_NC_MDL08_MDL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL08[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL08_MDL09_Generic_GJ
print("Adding electrical projection: NC_MDL08_MDL09_Generic_GJ from MDL08 to MDL09, with 1 connection(s)")
h("objectvar syn_NC_MDL08_MDL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL08_MDL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL08[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL09[0].soma], weight: 1.0
h("a_MDL08[0].soma { syn_NC_MDL08_MDL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL09[0].soma { syn_NC_MDL08_MDL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL08_MDL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL09[0].soma.v(0.5)")
h("setpointer syn_NC_MDL08_MDL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL08[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL09_MDL08_Generic_GJ
print("Adding electrical projection: NC_MDL09_MDL08_Generic_GJ from MDL09 to MDL08, with 1 connection(s)")
h("objectvar syn_NC_MDL09_MDL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL09_MDL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL09[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL08[0].soma], weight: 1.0
h("a_MDL09[0].soma { syn_NC_MDL09_MDL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL08[0].soma { syn_NC_MDL09_MDL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL09_MDL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL08[0].soma.v(0.5)")
h("setpointer syn_NC_MDL09_MDL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL09[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL09_MDL10_Generic_GJ
print("Adding electrical projection: NC_MDL09_MDL10_Generic_GJ from MDL09 to MDL10, with 1 connection(s)")
h("objectvar syn_NC_MDL09_MDL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL09_MDL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL09[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL10[0].soma], weight: 1.0
h("a_MDL09[0].soma { syn_NC_MDL09_MDL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL10[0].soma { syn_NC_MDL09_MDL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL09_MDL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL10[0].soma.v(0.5)")
h("setpointer syn_NC_MDL09_MDL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL09[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL10_MDL09_Generic_GJ
print("Adding electrical projection: NC_MDL10_MDL09_Generic_GJ from MDL10 to MDL09, with 1 connection(s)")
h("objectvar syn_NC_MDL10_MDL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL10_MDL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL10[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL09[0].soma], weight: 1.0
h("a_MDL10[0].soma { syn_NC_MDL10_MDL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL09[0].soma { syn_NC_MDL10_MDL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL10_MDL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL09[0].soma.v(0.5)")
h("setpointer syn_NC_MDL10_MDL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL10[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL10_MDL11_Generic_GJ
print("Adding electrical projection: NC_MDL10_MDL11_Generic_GJ from MDL10 to MDL11, with 1 connection(s)")
h("objectvar syn_NC_MDL10_MDL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL10_MDL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL10[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL11[0].soma], weight: 1.0
h("a_MDL10[0].soma { syn_NC_MDL10_MDL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL11[0].soma { syn_NC_MDL10_MDL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL10_MDL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL11[0].soma.v(0.5)")
h("setpointer syn_NC_MDL10_MDL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL10[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL11_MDL10_Generic_GJ
print("Adding electrical projection: NC_MDL11_MDL10_Generic_GJ from MDL11 to MDL10, with 1 connection(s)")
h("objectvar syn_NC_MDL11_MDL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL11_MDL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL11[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL10[0].soma], weight: 1.0
h("a_MDL11[0].soma { syn_NC_MDL11_MDL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL10[0].soma { syn_NC_MDL11_MDL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL11_MDL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL10[0].soma.v(0.5)")
h("setpointer syn_NC_MDL11_MDL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL11[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL11_MDL12_Generic_GJ
print("Adding electrical projection: NC_MDL11_MDL12_Generic_GJ from MDL11 to MDL12, with 1 connection(s)")
h("objectvar syn_NC_MDL11_MDL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL11_MDL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL11[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL12[0].soma], weight: 1.0
h("a_MDL11[0].soma { syn_NC_MDL11_MDL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL12[0].soma { syn_NC_MDL11_MDL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL11_MDL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL12[0].soma.v(0.5)")
h("setpointer syn_NC_MDL11_MDL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL11[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL12_MDL11_Generic_GJ
print("Adding electrical projection: NC_MDL12_MDL11_Generic_GJ from MDL12 to MDL11, with 1 connection(s)")
h("objectvar syn_NC_MDL12_MDL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL12_MDL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL12[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL11[0].soma], weight: 1.0
h("a_MDL12[0].soma { syn_NC_MDL12_MDL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL11[0].soma { syn_NC_MDL12_MDL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL12_MDL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL11[0].soma.v(0.5)")
h("setpointer syn_NC_MDL12_MDL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL12[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL12_MDL13_Generic_GJ
print("Adding electrical projection: NC_MDL12_MDL13_Generic_GJ from MDL12 to MDL13, with 1 connection(s)")
h("objectvar syn_NC_MDL12_MDL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL12_MDL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL12[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL13[0].soma], weight: 1.0
h("a_MDL12[0].soma { syn_NC_MDL12_MDL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL13[0].soma { syn_NC_MDL12_MDL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL12_MDL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL13[0].soma.v(0.5)")
h("setpointer syn_NC_MDL12_MDL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL12[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL13_MDL12_Generic_GJ
print("Adding electrical projection: NC_MDL13_MDL12_Generic_GJ from MDL13 to MDL12, with 1 connection(s)")
h("objectvar syn_NC_MDL13_MDL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL13_MDL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL13[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL12[0].soma], weight: 1.0
h("a_MDL13[0].soma { syn_NC_MDL13_MDL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL12[0].soma { syn_NC_MDL13_MDL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL13_MDL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL12[0].soma.v(0.5)")
h("setpointer syn_NC_MDL13_MDL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL13[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL13_MDL14_Generic_GJ
print("Adding electrical projection: NC_MDL13_MDL14_Generic_GJ from MDL13 to MDL14, with 1 connection(s)")
h("objectvar syn_NC_MDL13_MDL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL13_MDL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL13[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL14[0].soma], weight: 1.0
h("a_MDL13[0].soma { syn_NC_MDL13_MDL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL14[0].soma { syn_NC_MDL13_MDL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL13_MDL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL14[0].soma.v(0.5)")
h("setpointer syn_NC_MDL13_MDL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL13[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL14_MDL13_Generic_GJ
print("Adding electrical projection: NC_MDL14_MDL13_Generic_GJ from MDL14 to MDL13, with 1 connection(s)")
h("objectvar syn_NC_MDL14_MDL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL14_MDL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL14[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL13[0].soma], weight: 1.0
h("a_MDL14[0].soma { syn_NC_MDL14_MDL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL13[0].soma { syn_NC_MDL14_MDL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL14_MDL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL13[0].soma.v(0.5)")
h("setpointer syn_NC_MDL14_MDL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL14[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL14_MDL15_Generic_GJ
print("Adding electrical projection: NC_MDL14_MDL15_Generic_GJ from MDL14 to MDL15, with 1 connection(s)")
h("objectvar syn_NC_MDL14_MDL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL14_MDL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL14[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL15[0].soma], weight: 1.0
h("a_MDL14[0].soma { syn_NC_MDL14_MDL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL15[0].soma { syn_NC_MDL14_MDL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL14_MDL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL15[0].soma.v(0.5)")
h("setpointer syn_NC_MDL14_MDL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL14[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL15_MDL14_Generic_GJ
print("Adding electrical projection: NC_MDL15_MDL14_Generic_GJ from MDL15 to MDL14, with 1 connection(s)")
h("objectvar syn_NC_MDL15_MDL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL15_MDL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL15[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL14[0].soma], weight: 1.0
h("a_MDL15[0].soma { syn_NC_MDL15_MDL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL14[0].soma { syn_NC_MDL15_MDL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL15_MDL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL14[0].soma.v(0.5)")
h("setpointer syn_NC_MDL15_MDL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL15[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL15_MDL16_Generic_GJ
print("Adding electrical projection: NC_MDL15_MDL16_Generic_GJ from MDL15 to MDL16, with 1 connection(s)")
h("objectvar syn_NC_MDL15_MDL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL15_MDL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL15[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL16[0].soma], weight: 1.0
h("a_MDL15[0].soma { syn_NC_MDL15_MDL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL16[0].soma { syn_NC_MDL15_MDL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL15_MDL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL16[0].soma.v(0.5)")
h("setpointer syn_NC_MDL15_MDL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL15[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL16_MDL15_Generic_GJ
print("Adding electrical projection: NC_MDL16_MDL15_Generic_GJ from MDL16 to MDL15, with 1 connection(s)")
h("objectvar syn_NC_MDL16_MDL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL16_MDL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL16[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL15[0].soma], weight: 1.0
h("a_MDL16[0].soma { syn_NC_MDL16_MDL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL15[0].soma { syn_NC_MDL16_MDL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL16_MDL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL15[0].soma.v(0.5)")
h("setpointer syn_NC_MDL16_MDL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL16[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL16_MDL17_Generic_GJ
print("Adding electrical projection: NC_MDL16_MDL17_Generic_GJ from MDL16 to MDL17, with 1 connection(s)")
h("objectvar syn_NC_MDL16_MDL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL16_MDL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL16[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL17[0].soma], weight: 1.0
h("a_MDL16[0].soma { syn_NC_MDL16_MDL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL17[0].soma { syn_NC_MDL16_MDL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL16_MDL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL17[0].soma.v(0.5)")
h("setpointer syn_NC_MDL16_MDL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL16[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL17_MDL16_Generic_GJ
print("Adding electrical projection: NC_MDL17_MDL16_Generic_GJ from MDL17 to MDL16, with 1 connection(s)")
h("objectvar syn_NC_MDL17_MDL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL17_MDL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL17[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL16[0].soma], weight: 1.0
h("a_MDL17[0].soma { syn_NC_MDL17_MDL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL16[0].soma { syn_NC_MDL17_MDL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL17_MDL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL16[0].soma.v(0.5)")
h("setpointer syn_NC_MDL17_MDL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL17[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL17_MDL18_Generic_GJ
print("Adding electrical projection: NC_MDL17_MDL18_Generic_GJ from MDL17 to MDL18, with 1 connection(s)")
h("objectvar syn_NC_MDL17_MDL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL17_MDL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL17[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL18[0].soma], weight: 1.0
h("a_MDL17[0].soma { syn_NC_MDL17_MDL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL18[0].soma { syn_NC_MDL17_MDL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL17_MDL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL18[0].soma.v(0.5)")
h("setpointer syn_NC_MDL17_MDL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL17[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL18_MDL17_Generic_GJ
print("Adding electrical projection: NC_MDL18_MDL17_Generic_GJ from MDL18 to MDL17, with 1 connection(s)")
h("objectvar syn_NC_MDL18_MDL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL18_MDL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL18[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL17[0].soma], weight: 1.0
h("a_MDL18[0].soma { syn_NC_MDL18_MDL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL17[0].soma { syn_NC_MDL18_MDL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL18_MDL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL17[0].soma.v(0.5)")
h("setpointer syn_NC_MDL18_MDL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL18[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL18_MDL19_Generic_GJ
print("Adding electrical projection: NC_MDL18_MDL19_Generic_GJ from MDL18 to MDL19, with 1 connection(s)")
h("objectvar syn_NC_MDL18_MDL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL18_MDL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL18[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL19[0].soma], weight: 1.0
h("a_MDL18[0].soma { syn_NC_MDL18_MDL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL19[0].soma { syn_NC_MDL18_MDL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL18_MDL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL19[0].soma.v(0.5)")
h("setpointer syn_NC_MDL18_MDL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL18[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL19_MDL18_Generic_GJ
print("Adding electrical projection: NC_MDL19_MDL18_Generic_GJ from MDL19 to MDL18, with 1 connection(s)")
h("objectvar syn_NC_MDL19_MDL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL19_MDL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL19[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL18[0].soma], weight: 1.0
h("a_MDL19[0].soma { syn_NC_MDL19_MDL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL18[0].soma { syn_NC_MDL19_MDL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL19_MDL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL18[0].soma.v(0.5)")
h("setpointer syn_NC_MDL19_MDL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL19[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL19_MDL20_Generic_GJ
print("Adding electrical projection: NC_MDL19_MDL20_Generic_GJ from MDL19 to MDL20, with 1 connection(s)")
h("objectvar syn_NC_MDL19_MDL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL19_MDL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL19[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL20[0].soma], weight: 1.0
h("a_MDL19[0].soma { syn_NC_MDL19_MDL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL20[0].soma { syn_NC_MDL19_MDL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL19_MDL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL20[0].soma.v(0.5)")
h("setpointer syn_NC_MDL19_MDL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL19[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL20_MDL19_Generic_GJ
print("Adding electrical projection: NC_MDL20_MDL19_Generic_GJ from MDL20 to MDL19, with 1 connection(s)")
h("objectvar syn_NC_MDL20_MDL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL20_MDL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL20[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL19[0].soma], weight: 1.0
h("a_MDL20[0].soma { syn_NC_MDL20_MDL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL19[0].soma { syn_NC_MDL20_MDL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL20_MDL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL19[0].soma.v(0.5)")
h("setpointer syn_NC_MDL20_MDL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL20[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL20_MDL21_Generic_GJ
print("Adding electrical projection: NC_MDL20_MDL21_Generic_GJ from MDL20 to MDL21, with 1 connection(s)")
h("objectvar syn_NC_MDL20_MDL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL20_MDL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL20[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL21[0].soma], weight: 1.0
h("a_MDL20[0].soma { syn_NC_MDL20_MDL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL21[0].soma { syn_NC_MDL20_MDL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL20_MDL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL21[0].soma.v(0.5)")
h("setpointer syn_NC_MDL20_MDL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL20[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL21_MDL20_Generic_GJ
print("Adding electrical projection: NC_MDL21_MDL20_Generic_GJ from MDL21 to MDL20, with 1 connection(s)")
h("objectvar syn_NC_MDL21_MDL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL21_MDL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL21[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL20[0].soma], weight: 1.0
h("a_MDL21[0].soma { syn_NC_MDL21_MDL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL20[0].soma { syn_NC_MDL21_MDL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL21_MDL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL20[0].soma.v(0.5)")
h("setpointer syn_NC_MDL21_MDL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL21[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL21_MDL22_Generic_GJ
print("Adding electrical projection: NC_MDL21_MDL22_Generic_GJ from MDL21 to MDL22, with 1 connection(s)")
h("objectvar syn_NC_MDL21_MDL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL21_MDL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL21[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL22[0].soma], weight: 1.0
h("a_MDL21[0].soma { syn_NC_MDL21_MDL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL22[0].soma { syn_NC_MDL21_MDL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL21_MDL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL22[0].soma.v(0.5)")
h("setpointer syn_NC_MDL21_MDL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL21[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL22_MDL21_Generic_GJ
print("Adding electrical projection: NC_MDL22_MDL21_Generic_GJ from MDL22 to MDL21, with 1 connection(s)")
h("objectvar syn_NC_MDL22_MDL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL22_MDL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL22[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL21[0].soma], weight: 1.0
h("a_MDL22[0].soma { syn_NC_MDL22_MDL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL21[0].soma { syn_NC_MDL22_MDL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL22_MDL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL21[0].soma.v(0.5)")
h("setpointer syn_NC_MDL22_MDL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL22[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL22_MDL23_Generic_GJ
print("Adding electrical projection: NC_MDL22_MDL23_Generic_GJ from MDL22 to MDL23, with 1 connection(s)")
h("objectvar syn_NC_MDL22_MDL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL22_MDL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL22[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL23[0].soma], weight: 1.0
h("a_MDL22[0].soma { syn_NC_MDL22_MDL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL23[0].soma { syn_NC_MDL22_MDL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL22_MDL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL23[0].soma.v(0.5)")
h("setpointer syn_NC_MDL22_MDL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL22[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL23_MDL22_Generic_GJ
print("Adding electrical projection: NC_MDL23_MDL22_Generic_GJ from MDL23 to MDL22, with 1 connection(s)")
h("objectvar syn_NC_MDL23_MDL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL23_MDL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL23[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL22[0].soma], weight: 1.0
h("a_MDL23[0].soma { syn_NC_MDL23_MDL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL22[0].soma { syn_NC_MDL23_MDL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL23_MDL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL22[0].soma.v(0.5)")
h("setpointer syn_NC_MDL23_MDL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL23[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL23_MDL24_Generic_GJ
print("Adding electrical projection: NC_MDL23_MDL24_Generic_GJ from MDL23 to MDL24, with 1 connection(s)")
h("objectvar syn_NC_MDL23_MDL24_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL23_MDL24_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL23[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL24[0].soma], weight: 1.0
h("a_MDL23[0].soma { syn_NC_MDL23_MDL24_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL24[0].soma { syn_NC_MDL23_MDL24_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL23_MDL24_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL24[0].soma.v(0.5)")
h("setpointer syn_NC_MDL23_MDL24_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL23[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDL24_MDL23_Generic_GJ
print("Adding electrical projection: NC_MDL24_MDL23_Generic_GJ from MDL24 to MDL23, with 1 connection(s)")
h("objectvar syn_NC_MDL24_MDL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDL24_MDL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDL24[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL23[0].soma], weight: 1.0
h("a_MDL24[0].soma { syn_NC_MDL24_MDL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDL23[0].soma { syn_NC_MDL24_MDL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDL24_MDL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDL23[0].soma.v(0.5)")
h("setpointer syn_NC_MDL24_MDL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDL24[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR01_MDR02_Generic_GJ
print("Adding electrical projection: NC_MDR01_MDR02_Generic_GJ from MDR01 to MDR02, with 1 connection(s)")
h("objectvar syn_NC_MDR01_MDR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR01_MDR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR01[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR02[0].soma], weight: 1.0
h("a_MDR01[0].soma { syn_NC_MDR01_MDR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR02[0].soma { syn_NC_MDR01_MDR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR01_MDR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR02[0].soma.v(0.5)")
h("setpointer syn_NC_MDR01_MDR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR01[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR01_MDR03_Generic_GJ
print("Adding electrical projection: NC_MDR01_MDR03_Generic_GJ from MDR01 to MDR03, with 1 connection(s)")
h("objectvar syn_NC_MDR01_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR01_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR01[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR03[0].soma], weight: 1.0
h("a_MDR01[0].soma { syn_NC_MDR01_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR03[0].soma { syn_NC_MDR01_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR01_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR03[0].soma.v(0.5)")
h("setpointer syn_NC_MDR01_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR01[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR02_MDR01_Generic_GJ
print("Adding electrical projection: NC_MDR02_MDR01_Generic_GJ from MDR02 to MDR01, with 1 connection(s)")
h("objectvar syn_NC_MDR02_MDR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR02_MDR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR02[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR01[0].soma], weight: 1.0
h("a_MDR02[0].soma { syn_NC_MDR02_MDR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR01[0].soma { syn_NC_MDR02_MDR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR02_MDR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR01[0].soma.v(0.5)")
h("setpointer syn_NC_MDR02_MDR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR02[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR02_MDR03_Generic_GJ
print("Adding electrical projection: NC_MDR02_MDR03_Generic_GJ from MDR02 to MDR03, with 1 connection(s)")
h("objectvar syn_NC_MDR02_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR02_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR02[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR03[0].soma], weight: 1.0
h("a_MDR02[0].soma { syn_NC_MDR02_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR03[0].soma { syn_NC_MDR02_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR02_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR03[0].soma.v(0.5)")
h("setpointer syn_NC_MDR02_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR02[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR03_MDR01_Generic_GJ
print("Adding electrical projection: NC_MDR03_MDR01_Generic_GJ from MDR03 to MDR01, with 1 connection(s)")
h("objectvar syn_NC_MDR03_MDR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR03_MDR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR03[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR01[0].soma], weight: 1.0
h("a_MDR03[0].soma { syn_NC_MDR03_MDR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR01[0].soma { syn_NC_MDR03_MDR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR03_MDR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR01[0].soma.v(0.5)")
h("setpointer syn_NC_MDR03_MDR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR03[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR03_MDR02_Generic_GJ
print("Adding electrical projection: NC_MDR03_MDR02_Generic_GJ from MDR03 to MDR02, with 1 connection(s)")
h("objectvar syn_NC_MDR03_MDR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR03_MDR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR03[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR02[0].soma], weight: 1.0
h("a_MDR03[0].soma { syn_NC_MDR03_MDR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR02[0].soma { syn_NC_MDR03_MDR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR03_MDR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR02[0].soma.v(0.5)")
h("setpointer syn_NC_MDR03_MDR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR03[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR03_MDR04_Generic_GJ
print("Adding electrical projection: NC_MDR03_MDR04_Generic_GJ from MDR03 to MDR04, with 1 connection(s)")
h("objectvar syn_NC_MDR03_MDR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR03_MDR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR03[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR04[0].soma], weight: 1.0
h("a_MDR03[0].soma { syn_NC_MDR03_MDR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR04[0].soma { syn_NC_MDR03_MDR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR03_MDR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR04[0].soma.v(0.5)")
h("setpointer syn_NC_MDR03_MDR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR03[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR04_MDR03_Generic_GJ
print("Adding electrical projection: NC_MDR04_MDR03_Generic_GJ from MDR04 to MDR03, with 1 connection(s)")
h("objectvar syn_NC_MDR04_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR04_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR04[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR03[0].soma], weight: 1.0
h("a_MDR04[0].soma { syn_NC_MDR04_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR03[0].soma { syn_NC_MDR04_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR04_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR03[0].soma.v(0.5)")
h("setpointer syn_NC_MDR04_MDR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR04[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR04_MDR05_Generic_GJ
print("Adding electrical projection: NC_MDR04_MDR05_Generic_GJ from MDR04 to MDR05, with 1 connection(s)")
h("objectvar syn_NC_MDR04_MDR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR04_MDR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR04[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR05[0].soma], weight: 1.0
h("a_MDR04[0].soma { syn_NC_MDR04_MDR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR05[0].soma { syn_NC_MDR04_MDR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR04_MDR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR05[0].soma.v(0.5)")
h("setpointer syn_NC_MDR04_MDR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR04[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR05_MDR04_Generic_GJ
print("Adding electrical projection: NC_MDR05_MDR04_Generic_GJ from MDR05 to MDR04, with 1 connection(s)")
h("objectvar syn_NC_MDR05_MDR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR05_MDR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR05[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR04[0].soma], weight: 1.0
h("a_MDR05[0].soma { syn_NC_MDR05_MDR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR04[0].soma { syn_NC_MDR05_MDR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR05_MDR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR04[0].soma.v(0.5)")
h("setpointer syn_NC_MDR05_MDR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR05[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR05_MDR06_Generic_GJ
print("Adding electrical projection: NC_MDR05_MDR06_Generic_GJ from MDR05 to MDR06, with 1 connection(s)")
h("objectvar syn_NC_MDR05_MDR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR05_MDR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR05[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR06[0].soma], weight: 1.0
h("a_MDR05[0].soma { syn_NC_MDR05_MDR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR06[0].soma { syn_NC_MDR05_MDR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR05_MDR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR06[0].soma.v(0.5)")
h("setpointer syn_NC_MDR05_MDR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR05[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR06_MDR05_Generic_GJ
print("Adding electrical projection: NC_MDR06_MDR05_Generic_GJ from MDR06 to MDR05, with 1 connection(s)")
h("objectvar syn_NC_MDR06_MDR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR06_MDR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR06[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR05[0].soma], weight: 1.0
h("a_MDR06[0].soma { syn_NC_MDR06_MDR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR05[0].soma { syn_NC_MDR06_MDR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR06_MDR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR05[0].soma.v(0.5)")
h("setpointer syn_NC_MDR06_MDR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR06[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR06_MDR07_Generic_GJ
print("Adding electrical projection: NC_MDR06_MDR07_Generic_GJ from MDR06 to MDR07, with 1 connection(s)")
h("objectvar syn_NC_MDR06_MDR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR06_MDR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR06[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR07[0].soma], weight: 1.0
h("a_MDR06[0].soma { syn_NC_MDR06_MDR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR07[0].soma { syn_NC_MDR06_MDR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR06_MDR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR07[0].soma.v(0.5)")
h("setpointer syn_NC_MDR06_MDR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR06[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR07_MDR06_Generic_GJ
print("Adding electrical projection: NC_MDR07_MDR06_Generic_GJ from MDR07 to MDR06, with 1 connection(s)")
h("objectvar syn_NC_MDR07_MDR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR07_MDR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR07[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR06[0].soma], weight: 1.0
h("a_MDR07[0].soma { syn_NC_MDR07_MDR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR06[0].soma { syn_NC_MDR07_MDR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR07_MDR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR06[0].soma.v(0.5)")
h("setpointer syn_NC_MDR07_MDR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR07[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR07_MDR08_Generic_GJ
print("Adding electrical projection: NC_MDR07_MDR08_Generic_GJ from MDR07 to MDR08, with 1 connection(s)")
h("objectvar syn_NC_MDR07_MDR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR07_MDR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR07[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR08[0].soma], weight: 1.0
h("a_MDR07[0].soma { syn_NC_MDR07_MDR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR08[0].soma { syn_NC_MDR07_MDR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR07_MDR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR08[0].soma.v(0.5)")
h("setpointer syn_NC_MDR07_MDR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR07[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR08_MDR07_Generic_GJ
print("Adding electrical projection: NC_MDR08_MDR07_Generic_GJ from MDR08 to MDR07, with 1 connection(s)")
h("objectvar syn_NC_MDR08_MDR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR08_MDR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR08[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR07[0].soma], weight: 1.0
h("a_MDR08[0].soma { syn_NC_MDR08_MDR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR07[0].soma { syn_NC_MDR08_MDR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR08_MDR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR07[0].soma.v(0.5)")
h("setpointer syn_NC_MDR08_MDR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR08[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR08_MDR09_Generic_GJ
print("Adding electrical projection: NC_MDR08_MDR09_Generic_GJ from MDR08 to MDR09, with 1 connection(s)")
h("objectvar syn_NC_MDR08_MDR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR08_MDR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR08[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR09[0].soma], weight: 1.0
h("a_MDR08[0].soma { syn_NC_MDR08_MDR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR09[0].soma { syn_NC_MDR08_MDR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR08_MDR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR09[0].soma.v(0.5)")
h("setpointer syn_NC_MDR08_MDR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR08[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR09_MDR08_Generic_GJ
print("Adding electrical projection: NC_MDR09_MDR08_Generic_GJ from MDR09 to MDR08, with 1 connection(s)")
h("objectvar syn_NC_MDR09_MDR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR09_MDR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR09[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR08[0].soma], weight: 1.0
h("a_MDR09[0].soma { syn_NC_MDR09_MDR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR08[0].soma { syn_NC_MDR09_MDR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR09_MDR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR08[0].soma.v(0.5)")
h("setpointer syn_NC_MDR09_MDR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR09[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR09_MDR10_Generic_GJ
print("Adding electrical projection: NC_MDR09_MDR10_Generic_GJ from MDR09 to MDR10, with 1 connection(s)")
h("objectvar syn_NC_MDR09_MDR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR09_MDR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR09[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR10[0].soma], weight: 1.0
h("a_MDR09[0].soma { syn_NC_MDR09_MDR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR10[0].soma { syn_NC_MDR09_MDR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR09_MDR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR10[0].soma.v(0.5)")
h("setpointer syn_NC_MDR09_MDR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR09[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR10_MDR09_Generic_GJ
print("Adding electrical projection: NC_MDR10_MDR09_Generic_GJ from MDR10 to MDR09, with 1 connection(s)")
h("objectvar syn_NC_MDR10_MDR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR10_MDR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR10[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR09[0].soma], weight: 1.0
h("a_MDR10[0].soma { syn_NC_MDR10_MDR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR09[0].soma { syn_NC_MDR10_MDR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR10_MDR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR09[0].soma.v(0.5)")
h("setpointer syn_NC_MDR10_MDR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR10[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR10_MDR11_Generic_GJ
print("Adding electrical projection: NC_MDR10_MDR11_Generic_GJ from MDR10 to MDR11, with 1 connection(s)")
h("objectvar syn_NC_MDR10_MDR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR10_MDR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR10[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR11[0].soma], weight: 1.0
h("a_MDR10[0].soma { syn_NC_MDR10_MDR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR11[0].soma { syn_NC_MDR10_MDR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR10_MDR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR11[0].soma.v(0.5)")
h("setpointer syn_NC_MDR10_MDR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR10[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR11_MDR10_Generic_GJ
print("Adding electrical projection: NC_MDR11_MDR10_Generic_GJ from MDR11 to MDR10, with 1 connection(s)")
h("objectvar syn_NC_MDR11_MDR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR11_MDR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR11[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR10[0].soma], weight: 1.0
h("a_MDR11[0].soma { syn_NC_MDR11_MDR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR10[0].soma { syn_NC_MDR11_MDR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR11_MDR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR10[0].soma.v(0.5)")
h("setpointer syn_NC_MDR11_MDR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR11[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR11_MDR12_Generic_GJ
print("Adding electrical projection: NC_MDR11_MDR12_Generic_GJ from MDR11 to MDR12, with 1 connection(s)")
h("objectvar syn_NC_MDR11_MDR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR11_MDR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR11[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR12[0].soma], weight: 1.0
h("a_MDR11[0].soma { syn_NC_MDR11_MDR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR12[0].soma { syn_NC_MDR11_MDR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR11_MDR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR12[0].soma.v(0.5)")
h("setpointer syn_NC_MDR11_MDR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR11[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR12_MDR11_Generic_GJ
print("Adding electrical projection: NC_MDR12_MDR11_Generic_GJ from MDR12 to MDR11, with 1 connection(s)")
h("objectvar syn_NC_MDR12_MDR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR12_MDR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR12[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR11[0].soma], weight: 1.0
h("a_MDR12[0].soma { syn_NC_MDR12_MDR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR11[0].soma { syn_NC_MDR12_MDR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR12_MDR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR11[0].soma.v(0.5)")
h("setpointer syn_NC_MDR12_MDR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR12[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR12_MDR13_Generic_GJ
print("Adding electrical projection: NC_MDR12_MDR13_Generic_GJ from MDR12 to MDR13, with 1 connection(s)")
h("objectvar syn_NC_MDR12_MDR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR12_MDR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR12[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR13[0].soma], weight: 1.0
h("a_MDR12[0].soma { syn_NC_MDR12_MDR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR13[0].soma { syn_NC_MDR12_MDR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR12_MDR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR13[0].soma.v(0.5)")
h("setpointer syn_NC_MDR12_MDR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR12[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR13_MDR12_Generic_GJ
print("Adding electrical projection: NC_MDR13_MDR12_Generic_GJ from MDR13 to MDR12, with 1 connection(s)")
h("objectvar syn_NC_MDR13_MDR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR13_MDR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR13[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR12[0].soma], weight: 1.0
h("a_MDR13[0].soma { syn_NC_MDR13_MDR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR12[0].soma { syn_NC_MDR13_MDR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR13_MDR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR12[0].soma.v(0.5)")
h("setpointer syn_NC_MDR13_MDR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR13[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR13_MDR14_Generic_GJ
print("Adding electrical projection: NC_MDR13_MDR14_Generic_GJ from MDR13 to MDR14, with 1 connection(s)")
h("objectvar syn_NC_MDR13_MDR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR13_MDR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR13[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR14[0].soma], weight: 1.0
h("a_MDR13[0].soma { syn_NC_MDR13_MDR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR14[0].soma { syn_NC_MDR13_MDR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR13_MDR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR14[0].soma.v(0.5)")
h("setpointer syn_NC_MDR13_MDR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR13[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR14_MDR13_Generic_GJ
print("Adding electrical projection: NC_MDR14_MDR13_Generic_GJ from MDR14 to MDR13, with 1 connection(s)")
h("objectvar syn_NC_MDR14_MDR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR14_MDR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR14[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR13[0].soma], weight: 1.0
h("a_MDR14[0].soma { syn_NC_MDR14_MDR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR13[0].soma { syn_NC_MDR14_MDR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR14_MDR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR13[0].soma.v(0.5)")
h("setpointer syn_NC_MDR14_MDR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR14[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR14_MDR15_Generic_GJ
print("Adding electrical projection: NC_MDR14_MDR15_Generic_GJ from MDR14 to MDR15, with 1 connection(s)")
h("objectvar syn_NC_MDR14_MDR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR14_MDR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR14[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR15[0].soma], weight: 1.0
h("a_MDR14[0].soma { syn_NC_MDR14_MDR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR15[0].soma { syn_NC_MDR14_MDR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR14_MDR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR15[0].soma.v(0.5)")
h("setpointer syn_NC_MDR14_MDR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR14[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR15_MDR14_Generic_GJ
print("Adding electrical projection: NC_MDR15_MDR14_Generic_GJ from MDR15 to MDR14, with 1 connection(s)")
h("objectvar syn_NC_MDR15_MDR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR15_MDR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR15[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR14[0].soma], weight: 1.0
h("a_MDR15[0].soma { syn_NC_MDR15_MDR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR14[0].soma { syn_NC_MDR15_MDR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR15_MDR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR14[0].soma.v(0.5)")
h("setpointer syn_NC_MDR15_MDR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR15[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR15_MDR16_Generic_GJ
print("Adding electrical projection: NC_MDR15_MDR16_Generic_GJ from MDR15 to MDR16, with 1 connection(s)")
h("objectvar syn_NC_MDR15_MDR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR15_MDR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR15[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR16[0].soma], weight: 1.0
h("a_MDR15[0].soma { syn_NC_MDR15_MDR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR16[0].soma { syn_NC_MDR15_MDR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR15_MDR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR16[0].soma.v(0.5)")
h("setpointer syn_NC_MDR15_MDR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR15[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR16_MDR15_Generic_GJ
print("Adding electrical projection: NC_MDR16_MDR15_Generic_GJ from MDR16 to MDR15, with 1 connection(s)")
h("objectvar syn_NC_MDR16_MDR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR16_MDR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR16[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR15[0].soma], weight: 1.0
h("a_MDR16[0].soma { syn_NC_MDR16_MDR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR15[0].soma { syn_NC_MDR16_MDR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR16_MDR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR15[0].soma.v(0.5)")
h("setpointer syn_NC_MDR16_MDR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR16[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR16_MDR17_Generic_GJ
print("Adding electrical projection: NC_MDR16_MDR17_Generic_GJ from MDR16 to MDR17, with 1 connection(s)")
h("objectvar syn_NC_MDR16_MDR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR16_MDR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR16[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR17[0].soma], weight: 1.0
h("a_MDR16[0].soma { syn_NC_MDR16_MDR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR17[0].soma { syn_NC_MDR16_MDR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR16_MDR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR17[0].soma.v(0.5)")
h("setpointer syn_NC_MDR16_MDR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR16[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR17_MDR16_Generic_GJ
print("Adding electrical projection: NC_MDR17_MDR16_Generic_GJ from MDR17 to MDR16, with 1 connection(s)")
h("objectvar syn_NC_MDR17_MDR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR17_MDR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR17[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR16[0].soma], weight: 1.0
h("a_MDR17[0].soma { syn_NC_MDR17_MDR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR16[0].soma { syn_NC_MDR17_MDR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR17_MDR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR16[0].soma.v(0.5)")
h("setpointer syn_NC_MDR17_MDR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR17[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR17_MDR18_Generic_GJ
print("Adding electrical projection: NC_MDR17_MDR18_Generic_GJ from MDR17 to MDR18, with 1 connection(s)")
h("objectvar syn_NC_MDR17_MDR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR17_MDR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR17[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR18[0].soma], weight: 1.0
h("a_MDR17[0].soma { syn_NC_MDR17_MDR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR18[0].soma { syn_NC_MDR17_MDR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR17_MDR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR18[0].soma.v(0.5)")
h("setpointer syn_NC_MDR17_MDR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR17[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR18_MDR17_Generic_GJ
print("Adding electrical projection: NC_MDR18_MDR17_Generic_GJ from MDR18 to MDR17, with 1 connection(s)")
h("objectvar syn_NC_MDR18_MDR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR18_MDR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR18[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR17[0].soma], weight: 1.0
h("a_MDR18[0].soma { syn_NC_MDR18_MDR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR17[0].soma { syn_NC_MDR18_MDR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR18_MDR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR17[0].soma.v(0.5)")
h("setpointer syn_NC_MDR18_MDR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR18[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR18_MDR19_Generic_GJ
print("Adding electrical projection: NC_MDR18_MDR19_Generic_GJ from MDR18 to MDR19, with 1 connection(s)")
h("objectvar syn_NC_MDR18_MDR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR18_MDR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR18[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR19[0].soma], weight: 1.0
h("a_MDR18[0].soma { syn_NC_MDR18_MDR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR19[0].soma { syn_NC_MDR18_MDR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR18_MDR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR19[0].soma.v(0.5)")
h("setpointer syn_NC_MDR18_MDR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR18[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR19_MDR18_Generic_GJ
print("Adding electrical projection: NC_MDR19_MDR18_Generic_GJ from MDR19 to MDR18, with 1 connection(s)")
h("objectvar syn_NC_MDR19_MDR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR19_MDR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR19[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR18[0].soma], weight: 1.0
h("a_MDR19[0].soma { syn_NC_MDR19_MDR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR18[0].soma { syn_NC_MDR19_MDR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR19_MDR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR18[0].soma.v(0.5)")
h("setpointer syn_NC_MDR19_MDR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR19[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR19_MDR20_Generic_GJ
print("Adding electrical projection: NC_MDR19_MDR20_Generic_GJ from MDR19 to MDR20, with 1 connection(s)")
h("objectvar syn_NC_MDR19_MDR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR19_MDR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR19[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR20[0].soma], weight: 1.0
h("a_MDR19[0].soma { syn_NC_MDR19_MDR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR20[0].soma { syn_NC_MDR19_MDR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR19_MDR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR20[0].soma.v(0.5)")
h("setpointer syn_NC_MDR19_MDR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR19[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR20_MDR19_Generic_GJ
print("Adding electrical projection: NC_MDR20_MDR19_Generic_GJ from MDR20 to MDR19, with 1 connection(s)")
h("objectvar syn_NC_MDR20_MDR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR20_MDR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR20[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR19[0].soma], weight: 1.0
h("a_MDR20[0].soma { syn_NC_MDR20_MDR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR19[0].soma { syn_NC_MDR20_MDR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR20_MDR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR19[0].soma.v(0.5)")
h("setpointer syn_NC_MDR20_MDR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR20[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR20_MDR21_Generic_GJ
print("Adding electrical projection: NC_MDR20_MDR21_Generic_GJ from MDR20 to MDR21, with 1 connection(s)")
h("objectvar syn_NC_MDR20_MDR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR20_MDR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR20[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR21[0].soma], weight: 1.0
h("a_MDR20[0].soma { syn_NC_MDR20_MDR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR21[0].soma { syn_NC_MDR20_MDR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR20_MDR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR21[0].soma.v(0.5)")
h("setpointer syn_NC_MDR20_MDR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR20[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR21_MDR20_Generic_GJ
print("Adding electrical projection: NC_MDR21_MDR20_Generic_GJ from MDR21 to MDR20, with 1 connection(s)")
h("objectvar syn_NC_MDR21_MDR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR21_MDR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR21[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR20[0].soma], weight: 1.0
h("a_MDR21[0].soma { syn_NC_MDR21_MDR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR20[0].soma { syn_NC_MDR21_MDR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR21_MDR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR20[0].soma.v(0.5)")
h("setpointer syn_NC_MDR21_MDR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR21[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR21_MDR22_Generic_GJ
print("Adding electrical projection: NC_MDR21_MDR22_Generic_GJ from MDR21 to MDR22, with 1 connection(s)")
h("objectvar syn_NC_MDR21_MDR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR21_MDR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR21[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR22[0].soma], weight: 1.0
h("a_MDR21[0].soma { syn_NC_MDR21_MDR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR22[0].soma { syn_NC_MDR21_MDR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR21_MDR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR22[0].soma.v(0.5)")
h("setpointer syn_NC_MDR21_MDR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR21[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR22_MDR21_Generic_GJ
print("Adding electrical projection: NC_MDR22_MDR21_Generic_GJ from MDR22 to MDR21, with 1 connection(s)")
h("objectvar syn_NC_MDR22_MDR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR22_MDR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR22[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR21[0].soma], weight: 1.0
h("a_MDR22[0].soma { syn_NC_MDR22_MDR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR21[0].soma { syn_NC_MDR22_MDR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR22_MDR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR21[0].soma.v(0.5)")
h("setpointer syn_NC_MDR22_MDR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR22[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR22_MDR23_Generic_GJ
print("Adding electrical projection: NC_MDR22_MDR23_Generic_GJ from MDR22 to MDR23, with 1 connection(s)")
h("objectvar syn_NC_MDR22_MDR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR22_MDR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR22[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR23[0].soma], weight: 1.0
h("a_MDR22[0].soma { syn_NC_MDR22_MDR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR23[0].soma { syn_NC_MDR22_MDR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR22_MDR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR23[0].soma.v(0.5)")
h("setpointer syn_NC_MDR22_MDR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR22[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR23_MDR22_Generic_GJ
print("Adding electrical projection: NC_MDR23_MDR22_Generic_GJ from MDR23 to MDR22, with 1 connection(s)")
h("objectvar syn_NC_MDR23_MDR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR23_MDR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR23[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR22[0].soma], weight: 1.0
h("a_MDR23[0].soma { syn_NC_MDR23_MDR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR22[0].soma { syn_NC_MDR23_MDR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR23_MDR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR22[0].soma.v(0.5)")
h("setpointer syn_NC_MDR23_MDR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR23[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR23_MDR24_Generic_GJ
print("Adding electrical projection: NC_MDR23_MDR24_Generic_GJ from MDR23 to MDR24, with 1 connection(s)")
h("objectvar syn_NC_MDR23_MDR24_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR23_MDR24_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR23[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR24[0].soma], weight: 1.0
h("a_MDR23[0].soma { syn_NC_MDR23_MDR24_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR24[0].soma { syn_NC_MDR23_MDR24_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR23_MDR24_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR24[0].soma.v(0.5)")
h("setpointer syn_NC_MDR23_MDR24_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR23[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MDR24_MDR23_Generic_GJ
print("Adding electrical projection: NC_MDR24_MDR23_Generic_GJ from MDR24 to MDR23, with 1 connection(s)")
h("objectvar syn_NC_MDR24_MDR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MDR24_MDR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MDR24[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR23[0].soma], weight: 1.0
h("a_MDR24[0].soma { syn_NC_MDR24_MDR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MDR23[0].soma { syn_NC_MDR24_MDR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MDR24_MDR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MDR23[0].soma.v(0.5)")
h("setpointer syn_NC_MDR24_MDR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MDR24[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL01_MVL02_Generic_GJ
print("Adding electrical projection: NC_MVL01_MVL02_Generic_GJ from MVL01 to MVL02, with 1 connection(s)")
h("objectvar syn_NC_MVL01_MVL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL01_MVL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL01[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL02[0].soma], weight: 1.0
h("a_MVL01[0].soma { syn_NC_MVL01_MVL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL02[0].soma { syn_NC_MVL01_MVL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL01_MVL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL02[0].soma.v(0.5)")
h("setpointer syn_NC_MVL01_MVL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL01[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL01_MVL03_Generic_GJ
print("Adding electrical projection: NC_MVL01_MVL03_Generic_GJ from MVL01 to MVL03, with 1 connection(s)")
h("objectvar syn_NC_MVL01_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL01_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL01[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL03[0].soma], weight: 1.0
h("a_MVL01[0].soma { syn_NC_MVL01_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL03[0].soma { syn_NC_MVL01_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL01_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL03[0].soma.v(0.5)")
h("setpointer syn_NC_MVL01_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL01[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL02_MVL01_Generic_GJ
print("Adding electrical projection: NC_MVL02_MVL01_Generic_GJ from MVL02 to MVL01, with 1 connection(s)")
h("objectvar syn_NC_MVL02_MVL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL02_MVL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL02[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL01[0].soma], weight: 1.0
h("a_MVL02[0].soma { syn_NC_MVL02_MVL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL01[0].soma { syn_NC_MVL02_MVL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL02_MVL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL01[0].soma.v(0.5)")
h("setpointer syn_NC_MVL02_MVL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL02[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL02_MVL03_Generic_GJ
print("Adding electrical projection: NC_MVL02_MVL03_Generic_GJ from MVL02 to MVL03, with 1 connection(s)")
h("objectvar syn_NC_MVL02_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL02_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL02[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL03[0].soma], weight: 1.0
h("a_MVL02[0].soma { syn_NC_MVL02_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL03[0].soma { syn_NC_MVL02_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL02_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL03[0].soma.v(0.5)")
h("setpointer syn_NC_MVL02_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL02[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL03_MVL01_Generic_GJ
print("Adding electrical projection: NC_MVL03_MVL01_Generic_GJ from MVL03 to MVL01, with 1 connection(s)")
h("objectvar syn_NC_MVL03_MVL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL03_MVL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL03[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL01[0].soma], weight: 1.0
h("a_MVL03[0].soma { syn_NC_MVL03_MVL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL01[0].soma { syn_NC_MVL03_MVL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL03_MVL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL01[0].soma.v(0.5)")
h("setpointer syn_NC_MVL03_MVL01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL03[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL03_MVL02_Generic_GJ
print("Adding electrical projection: NC_MVL03_MVL02_Generic_GJ from MVL03 to MVL02, with 1 connection(s)")
h("objectvar syn_NC_MVL03_MVL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL03_MVL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL03[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL02[0].soma], weight: 1.0
h("a_MVL03[0].soma { syn_NC_MVL03_MVL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL02[0].soma { syn_NC_MVL03_MVL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL03_MVL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL02[0].soma.v(0.5)")
h("setpointer syn_NC_MVL03_MVL02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL03[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL03_MVL04_Generic_GJ
print("Adding electrical projection: NC_MVL03_MVL04_Generic_GJ from MVL03 to MVL04, with 1 connection(s)")
h("objectvar syn_NC_MVL03_MVL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL03_MVL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL03[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL04[0].soma], weight: 1.0
h("a_MVL03[0].soma { syn_NC_MVL03_MVL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL04[0].soma { syn_NC_MVL03_MVL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL03_MVL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL04[0].soma.v(0.5)")
h("setpointer syn_NC_MVL03_MVL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL03[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL04_MVL03_Generic_GJ
print("Adding electrical projection: NC_MVL04_MVL03_Generic_GJ from MVL04 to MVL03, with 1 connection(s)")
h("objectvar syn_NC_MVL04_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL04_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL04[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL03[0].soma], weight: 1.0
h("a_MVL04[0].soma { syn_NC_MVL04_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL03[0].soma { syn_NC_MVL04_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL04_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL03[0].soma.v(0.5)")
h("setpointer syn_NC_MVL04_MVL03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL04[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL04_MVL05_Generic_GJ
print("Adding electrical projection: NC_MVL04_MVL05_Generic_GJ from MVL04 to MVL05, with 1 connection(s)")
h("objectvar syn_NC_MVL04_MVL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL04_MVL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL04[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL05[0].soma], weight: 1.0
h("a_MVL04[0].soma { syn_NC_MVL04_MVL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL05[0].soma { syn_NC_MVL04_MVL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL04_MVL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL05[0].soma.v(0.5)")
h("setpointer syn_NC_MVL04_MVL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL04[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL05_MVL04_Generic_GJ
print("Adding electrical projection: NC_MVL05_MVL04_Generic_GJ from MVL05 to MVL04, with 1 connection(s)")
h("objectvar syn_NC_MVL05_MVL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL05_MVL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL05[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL04[0].soma], weight: 1.0
h("a_MVL05[0].soma { syn_NC_MVL05_MVL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL04[0].soma { syn_NC_MVL05_MVL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL05_MVL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL04[0].soma.v(0.5)")
h("setpointer syn_NC_MVL05_MVL04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL05[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL05_MVL06_Generic_GJ
print("Adding electrical projection: NC_MVL05_MVL06_Generic_GJ from MVL05 to MVL06, with 1 connection(s)")
h("objectvar syn_NC_MVL05_MVL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL05_MVL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL05[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL06[0].soma], weight: 1.0
h("a_MVL05[0].soma { syn_NC_MVL05_MVL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL06[0].soma { syn_NC_MVL05_MVL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL05_MVL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL06[0].soma.v(0.5)")
h("setpointer syn_NC_MVL05_MVL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL05[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL06_MVL05_Generic_GJ
print("Adding electrical projection: NC_MVL06_MVL05_Generic_GJ from MVL06 to MVL05, with 1 connection(s)")
h("objectvar syn_NC_MVL06_MVL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL06_MVL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL06[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL05[0].soma], weight: 1.0
h("a_MVL06[0].soma { syn_NC_MVL06_MVL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL05[0].soma { syn_NC_MVL06_MVL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL06_MVL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL05[0].soma.v(0.5)")
h("setpointer syn_NC_MVL06_MVL05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL06[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL06_MVL07_Generic_GJ
print("Adding electrical projection: NC_MVL06_MVL07_Generic_GJ from MVL06 to MVL07, with 1 connection(s)")
h("objectvar syn_NC_MVL06_MVL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL06_MVL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL06[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL07[0].soma], weight: 1.0
h("a_MVL06[0].soma { syn_NC_MVL06_MVL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL07[0].soma { syn_NC_MVL06_MVL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL06_MVL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL07[0].soma.v(0.5)")
h("setpointer syn_NC_MVL06_MVL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL06[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL07_MVL06_Generic_GJ
print("Adding electrical projection: NC_MVL07_MVL06_Generic_GJ from MVL07 to MVL06, with 1 connection(s)")
h("objectvar syn_NC_MVL07_MVL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL07_MVL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL07[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL06[0].soma], weight: 1.0
h("a_MVL07[0].soma { syn_NC_MVL07_MVL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL06[0].soma { syn_NC_MVL07_MVL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL07_MVL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL06[0].soma.v(0.5)")
h("setpointer syn_NC_MVL07_MVL06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL07[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL07_MVL08_Generic_GJ
print("Adding electrical projection: NC_MVL07_MVL08_Generic_GJ from MVL07 to MVL08, with 1 connection(s)")
h("objectvar syn_NC_MVL07_MVL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL07_MVL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL07[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL08[0].soma], weight: 1.0
h("a_MVL07[0].soma { syn_NC_MVL07_MVL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL08[0].soma { syn_NC_MVL07_MVL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL07_MVL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL08[0].soma.v(0.5)")
h("setpointer syn_NC_MVL07_MVL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL07[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL08_MVL07_Generic_GJ
print("Adding electrical projection: NC_MVL08_MVL07_Generic_GJ from MVL08 to MVL07, with 1 connection(s)")
h("objectvar syn_NC_MVL08_MVL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL08_MVL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL08[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL07[0].soma], weight: 1.0
h("a_MVL08[0].soma { syn_NC_MVL08_MVL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL07[0].soma { syn_NC_MVL08_MVL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL08_MVL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL07[0].soma.v(0.5)")
h("setpointer syn_NC_MVL08_MVL07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL08[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL08_MVL09_Generic_GJ
print("Adding electrical projection: NC_MVL08_MVL09_Generic_GJ from MVL08 to MVL09, with 1 connection(s)")
h("objectvar syn_NC_MVL08_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL08_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL08[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL09[0].soma], weight: 1.0
h("a_MVL08[0].soma { syn_NC_MVL08_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL09[0].soma { syn_NC_MVL08_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL08_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL09[0].soma.v(0.5)")
h("setpointer syn_NC_MVL08_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL08[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL09_MVL08_Generic_GJ
print("Adding electrical projection: NC_MVL09_MVL08_Generic_GJ from MVL09 to MVL08, with 1 connection(s)")
h("objectvar syn_NC_MVL09_MVL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL09_MVL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL09[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL08[0].soma], weight: 1.0
h("a_MVL09[0].soma { syn_NC_MVL09_MVL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL08[0].soma { syn_NC_MVL09_MVL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL09_MVL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL08[0].soma.v(0.5)")
h("setpointer syn_NC_MVL09_MVL08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL09[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL09_MVL10_Generic_GJ
print("Adding electrical projection: NC_MVL09_MVL10_Generic_GJ from MVL09 to MVL10, with 1 connection(s)")
h("objectvar syn_NC_MVL09_MVL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL09_MVL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL09[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL10[0].soma], weight: 1.0
h("a_MVL09[0].soma { syn_NC_MVL09_MVL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL10[0].soma { syn_NC_MVL09_MVL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL09_MVL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL10[0].soma.v(0.5)")
h("setpointer syn_NC_MVL09_MVL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL09[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL09_MVR08_Generic_GJ
print("Adding electrical projection: NC_MVL09_MVR08_Generic_GJ from MVL09 to MVR08, with 1 connection(s)")
h("objectvar syn_NC_MVL09_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_2conns_A[1]")
h("objectvar syn_NC_MVL09_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_2conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL09[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR08[0].soma], weight: 1.0
h("a_MVL09[0].soma { syn_NC_MVL09_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_2conns_A[0] = new muscle_to_muscle_elec_syn_2conns(0.5) }")
h("a_MVR08[0].soma { syn_NC_MVL09_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_2conns_B[0] = new muscle_to_muscle_elec_syn_2conns(0.5) }")
h("setpointer syn_NC_MVL09_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_2conns_A[0].vpeer, a_MVR08[0].soma.v(0.5)")
h("setpointer syn_NC_MVL09_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_2conns_B[0].vpeer, a_MVL09[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL10_MVL09_Generic_GJ
print("Adding electrical projection: NC_MVL10_MVL09_Generic_GJ from MVL10 to MVL09, with 1 connection(s)")
h("objectvar syn_NC_MVL10_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL10_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL10[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL09[0].soma], weight: 1.0
h("a_MVL10[0].soma { syn_NC_MVL10_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL09[0].soma { syn_NC_MVL10_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL10_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL09[0].soma.v(0.5)")
h("setpointer syn_NC_MVL10_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL10[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL10_MVL11_Generic_GJ
print("Adding electrical projection: NC_MVL10_MVL11_Generic_GJ from MVL10 to MVL11, with 1 connection(s)")
h("objectvar syn_NC_MVL10_MVL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL10_MVL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL10[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL11[0].soma], weight: 1.0
h("a_MVL10[0].soma { syn_NC_MVL10_MVL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL11[0].soma { syn_NC_MVL10_MVL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL10_MVL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL11[0].soma.v(0.5)")
h("setpointer syn_NC_MVL10_MVL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL10[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL11_MVL10_Generic_GJ
print("Adding electrical projection: NC_MVL11_MVL10_Generic_GJ from MVL11 to MVL10, with 1 connection(s)")
h("objectvar syn_NC_MVL11_MVL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL11_MVL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL11[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL10[0].soma], weight: 1.0
h("a_MVL11[0].soma { syn_NC_MVL11_MVL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL10[0].soma { syn_NC_MVL11_MVL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL11_MVL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL10[0].soma.v(0.5)")
h("setpointer syn_NC_MVL11_MVL10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL11[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL11_MVL12_Generic_GJ
print("Adding electrical projection: NC_MVL11_MVL12_Generic_GJ from MVL11 to MVL12, with 1 connection(s)")
h("objectvar syn_NC_MVL11_MVL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL11_MVL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL11[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL12[0].soma], weight: 1.0
h("a_MVL11[0].soma { syn_NC_MVL11_MVL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL12[0].soma { syn_NC_MVL11_MVL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL11_MVL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL12[0].soma.v(0.5)")
h("setpointer syn_NC_MVL11_MVL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL11[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL12_MVL11_Generic_GJ
print("Adding electrical projection: NC_MVL12_MVL11_Generic_GJ from MVL12 to MVL11, with 1 connection(s)")
h("objectvar syn_NC_MVL12_MVL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL12_MVL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL12[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL11[0].soma], weight: 1.0
h("a_MVL12[0].soma { syn_NC_MVL12_MVL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL11[0].soma { syn_NC_MVL12_MVL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL12_MVL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL11[0].soma.v(0.5)")
h("setpointer syn_NC_MVL12_MVL11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL12[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL12_MVL13_Generic_GJ
print("Adding electrical projection: NC_MVL12_MVL13_Generic_GJ from MVL12 to MVL13, with 1 connection(s)")
h("objectvar syn_NC_MVL12_MVL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL12_MVL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL12[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL13[0].soma], weight: 1.0
h("a_MVL12[0].soma { syn_NC_MVL12_MVL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL13[0].soma { syn_NC_MVL12_MVL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL12_MVL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL13[0].soma.v(0.5)")
h("setpointer syn_NC_MVL12_MVL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL12[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL13_MVL12_Generic_GJ
print("Adding electrical projection: NC_MVL13_MVL12_Generic_GJ from MVL13 to MVL12, with 1 connection(s)")
h("objectvar syn_NC_MVL13_MVL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL13_MVL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL13[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL12[0].soma], weight: 1.0
h("a_MVL13[0].soma { syn_NC_MVL13_MVL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL12[0].soma { syn_NC_MVL13_MVL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL13_MVL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL12[0].soma.v(0.5)")
h("setpointer syn_NC_MVL13_MVL12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL13[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL13_MVL14_Generic_GJ
print("Adding electrical projection: NC_MVL13_MVL14_Generic_GJ from MVL13 to MVL14, with 1 connection(s)")
h("objectvar syn_NC_MVL13_MVL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL13_MVL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL13[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL14[0].soma], weight: 1.0
h("a_MVL13[0].soma { syn_NC_MVL13_MVL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL14[0].soma { syn_NC_MVL13_MVL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL13_MVL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL14[0].soma.v(0.5)")
h("setpointer syn_NC_MVL13_MVL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL13[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL14_MVL13_Generic_GJ
print("Adding electrical projection: NC_MVL14_MVL13_Generic_GJ from MVL14 to MVL13, with 1 connection(s)")
h("objectvar syn_NC_MVL14_MVL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL14_MVL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL14[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL13[0].soma], weight: 1.0
h("a_MVL14[0].soma { syn_NC_MVL14_MVL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL13[0].soma { syn_NC_MVL14_MVL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL14_MVL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL13[0].soma.v(0.5)")
h("setpointer syn_NC_MVL14_MVL13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL14[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL14_MVL15_Generic_GJ
print("Adding electrical projection: NC_MVL14_MVL15_Generic_GJ from MVL14 to MVL15, with 1 connection(s)")
h("objectvar syn_NC_MVL14_MVL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL14_MVL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL14[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL15[0].soma], weight: 1.0
h("a_MVL14[0].soma { syn_NC_MVL14_MVL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL15[0].soma { syn_NC_MVL14_MVL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL14_MVL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL15[0].soma.v(0.5)")
h("setpointer syn_NC_MVL14_MVL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL14[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL15_MVL14_Generic_GJ
print("Adding electrical projection: NC_MVL15_MVL14_Generic_GJ from MVL15 to MVL14, with 1 connection(s)")
h("objectvar syn_NC_MVL15_MVL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL15_MVL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL15[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL14[0].soma], weight: 1.0
h("a_MVL15[0].soma { syn_NC_MVL15_MVL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL14[0].soma { syn_NC_MVL15_MVL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL15_MVL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL14[0].soma.v(0.5)")
h("setpointer syn_NC_MVL15_MVL14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL15[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL15_MVL16_Generic_GJ
print("Adding electrical projection: NC_MVL15_MVL16_Generic_GJ from MVL15 to MVL16, with 1 connection(s)")
h("objectvar syn_NC_MVL15_MVL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL15_MVL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL15[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL16[0].soma], weight: 1.0
h("a_MVL15[0].soma { syn_NC_MVL15_MVL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL16[0].soma { syn_NC_MVL15_MVL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL15_MVL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL16[0].soma.v(0.5)")
h("setpointer syn_NC_MVL15_MVL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL15[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL16_MVL15_Generic_GJ
print("Adding electrical projection: NC_MVL16_MVL15_Generic_GJ from MVL16 to MVL15, with 1 connection(s)")
h("objectvar syn_NC_MVL16_MVL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL16_MVL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL16[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL15[0].soma], weight: 1.0
h("a_MVL16[0].soma { syn_NC_MVL16_MVL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL15[0].soma { syn_NC_MVL16_MVL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL16_MVL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL15[0].soma.v(0.5)")
h("setpointer syn_NC_MVL16_MVL15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL16[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL16_MVL17_Generic_GJ
print("Adding electrical projection: NC_MVL16_MVL17_Generic_GJ from MVL16 to MVL17, with 1 connection(s)")
h("objectvar syn_NC_MVL16_MVL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL16_MVL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL16[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL17[0].soma], weight: 1.0
h("a_MVL16[0].soma { syn_NC_MVL16_MVL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL17[0].soma { syn_NC_MVL16_MVL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL16_MVL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL17[0].soma.v(0.5)")
h("setpointer syn_NC_MVL16_MVL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL16[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL17_MVL16_Generic_GJ
print("Adding electrical projection: NC_MVL17_MVL16_Generic_GJ from MVL17 to MVL16, with 1 connection(s)")
h("objectvar syn_NC_MVL17_MVL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL17_MVL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL17[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL16[0].soma], weight: 1.0
h("a_MVL17[0].soma { syn_NC_MVL17_MVL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL16[0].soma { syn_NC_MVL17_MVL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL17_MVL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL16[0].soma.v(0.5)")
h("setpointer syn_NC_MVL17_MVL16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL17[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL17_MVL18_Generic_GJ
print("Adding electrical projection: NC_MVL17_MVL18_Generic_GJ from MVL17 to MVL18, with 1 connection(s)")
h("objectvar syn_NC_MVL17_MVL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL17_MVL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL17[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL18[0].soma], weight: 1.0
h("a_MVL17[0].soma { syn_NC_MVL17_MVL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL18[0].soma { syn_NC_MVL17_MVL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL17_MVL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL18[0].soma.v(0.5)")
h("setpointer syn_NC_MVL17_MVL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL17[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL18_MVL17_Generic_GJ
print("Adding electrical projection: NC_MVL18_MVL17_Generic_GJ from MVL18 to MVL17, with 1 connection(s)")
h("objectvar syn_NC_MVL18_MVL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL18_MVL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL18[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL17[0].soma], weight: 1.0
h("a_MVL18[0].soma { syn_NC_MVL18_MVL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL17[0].soma { syn_NC_MVL18_MVL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL18_MVL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL17[0].soma.v(0.5)")
h("setpointer syn_NC_MVL18_MVL17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL18[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL18_MVL19_Generic_GJ
print("Adding electrical projection: NC_MVL18_MVL19_Generic_GJ from MVL18 to MVL19, with 1 connection(s)")
h("objectvar syn_NC_MVL18_MVL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL18_MVL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL18[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL19[0].soma], weight: 1.0
h("a_MVL18[0].soma { syn_NC_MVL18_MVL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL19[0].soma { syn_NC_MVL18_MVL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL18_MVL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL19[0].soma.v(0.5)")
h("setpointer syn_NC_MVL18_MVL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL18[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL19_MVL18_Generic_GJ
print("Adding electrical projection: NC_MVL19_MVL18_Generic_GJ from MVL19 to MVL18, with 1 connection(s)")
h("objectvar syn_NC_MVL19_MVL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL19_MVL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL19[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL18[0].soma], weight: 1.0
h("a_MVL19[0].soma { syn_NC_MVL19_MVL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL18[0].soma { syn_NC_MVL19_MVL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL19_MVL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL18[0].soma.v(0.5)")
h("setpointer syn_NC_MVL19_MVL18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL19[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL19_MVL20_Generic_GJ
print("Adding electrical projection: NC_MVL19_MVL20_Generic_GJ from MVL19 to MVL20, with 1 connection(s)")
h("objectvar syn_NC_MVL19_MVL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL19_MVL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL19[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL20[0].soma], weight: 1.0
h("a_MVL19[0].soma { syn_NC_MVL19_MVL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL20[0].soma { syn_NC_MVL19_MVL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL19_MVL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL20[0].soma.v(0.5)")
h("setpointer syn_NC_MVL19_MVL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL19[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL20_MVL19_Generic_GJ
print("Adding electrical projection: NC_MVL20_MVL19_Generic_GJ from MVL20 to MVL19, with 1 connection(s)")
h("objectvar syn_NC_MVL20_MVL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL20_MVL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL20[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL19[0].soma], weight: 1.0
h("a_MVL20[0].soma { syn_NC_MVL20_MVL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL19[0].soma { syn_NC_MVL20_MVL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL20_MVL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL19[0].soma.v(0.5)")
h("setpointer syn_NC_MVL20_MVL19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL20[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL20_MVL21_Generic_GJ
print("Adding electrical projection: NC_MVL20_MVL21_Generic_GJ from MVL20 to MVL21, with 1 connection(s)")
h("objectvar syn_NC_MVL20_MVL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL20_MVL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL20[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL21[0].soma], weight: 1.0
h("a_MVL20[0].soma { syn_NC_MVL20_MVL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL21[0].soma { syn_NC_MVL20_MVL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL20_MVL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL21[0].soma.v(0.5)")
h("setpointer syn_NC_MVL20_MVL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL20[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL21_MVL20_Generic_GJ
print("Adding electrical projection: NC_MVL21_MVL20_Generic_GJ from MVL21 to MVL20, with 1 connection(s)")
h("objectvar syn_NC_MVL21_MVL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL21_MVL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL21[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL20[0].soma], weight: 1.0
h("a_MVL21[0].soma { syn_NC_MVL21_MVL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL20[0].soma { syn_NC_MVL21_MVL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL21_MVL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL20[0].soma.v(0.5)")
h("setpointer syn_NC_MVL21_MVL20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL21[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL21_MVL22_Generic_GJ
print("Adding electrical projection: NC_MVL21_MVL22_Generic_GJ from MVL21 to MVL22, with 1 connection(s)")
h("objectvar syn_NC_MVL21_MVL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL21_MVL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL21[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL22[0].soma], weight: 1.0
h("a_MVL21[0].soma { syn_NC_MVL21_MVL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL22[0].soma { syn_NC_MVL21_MVL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL21_MVL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL22[0].soma.v(0.5)")
h("setpointer syn_NC_MVL21_MVL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL21[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL22_MVL21_Generic_GJ
print("Adding electrical projection: NC_MVL22_MVL21_Generic_GJ from MVL22 to MVL21, with 1 connection(s)")
h("objectvar syn_NC_MVL22_MVL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL22_MVL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL22[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL21[0].soma], weight: 1.0
h("a_MVL22[0].soma { syn_NC_MVL22_MVL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL21[0].soma { syn_NC_MVL22_MVL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL22_MVL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL21[0].soma.v(0.5)")
h("setpointer syn_NC_MVL22_MVL21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL22[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL22_MVL23_Generic_GJ
print("Adding electrical projection: NC_MVL22_MVL23_Generic_GJ from MVL22 to MVL23, with 1 connection(s)")
h("objectvar syn_NC_MVL22_MVL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL22_MVL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL22[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL23[0].soma], weight: 1.0
h("a_MVL22[0].soma { syn_NC_MVL22_MVL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL23[0].soma { syn_NC_MVL22_MVL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL22_MVL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL23[0].soma.v(0.5)")
h("setpointer syn_NC_MVL22_MVL23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL22[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVL23_MVL22_Generic_GJ
print("Adding electrical projection: NC_MVL23_MVL22_Generic_GJ from MVL23 to MVL22, with 1 connection(s)")
h("objectvar syn_NC_MVL23_MVL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVL23_MVL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVL23[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL22[0].soma], weight: 1.0
h("a_MVL23[0].soma { syn_NC_MVL23_MVL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVL22[0].soma { syn_NC_MVL23_MVL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVL23_MVL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVL22[0].soma.v(0.5)")
h("setpointer syn_NC_MVL23_MVL22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVL23[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR01_MVR02_Generic_GJ
print("Adding electrical projection: NC_MVR01_MVR02_Generic_GJ from MVR01 to MVR02, with 1 connection(s)")
h("objectvar syn_NC_MVR01_MVR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR01_MVR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR01[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR02[0].soma], weight: 1.0
h("a_MVR01[0].soma { syn_NC_MVR01_MVR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR02[0].soma { syn_NC_MVR01_MVR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR01_MVR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR02[0].soma.v(0.5)")
h("setpointer syn_NC_MVR01_MVR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR01[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR01_MVR03_Generic_GJ
print("Adding electrical projection: NC_MVR01_MVR03_Generic_GJ from MVR01 to MVR03, with 1 connection(s)")
h("objectvar syn_NC_MVR01_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR01_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR01[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR03[0].soma], weight: 1.0
h("a_MVR01[0].soma { syn_NC_MVR01_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR03[0].soma { syn_NC_MVR01_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR01_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR03[0].soma.v(0.5)")
h("setpointer syn_NC_MVR01_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR01[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR02_MVR01_Generic_GJ
print("Adding electrical projection: NC_MVR02_MVR01_Generic_GJ from MVR02 to MVR01, with 1 connection(s)")
h("objectvar syn_NC_MVR02_MVR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR02_MVR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR02[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR01[0].soma], weight: 1.0
h("a_MVR02[0].soma { syn_NC_MVR02_MVR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR01[0].soma { syn_NC_MVR02_MVR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR02_MVR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR01[0].soma.v(0.5)")
h("setpointer syn_NC_MVR02_MVR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR02[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR02_MVR03_Generic_GJ
print("Adding electrical projection: NC_MVR02_MVR03_Generic_GJ from MVR02 to MVR03, with 1 connection(s)")
h("objectvar syn_NC_MVR02_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR02_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR02[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR03[0].soma], weight: 1.0
h("a_MVR02[0].soma { syn_NC_MVR02_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR03[0].soma { syn_NC_MVR02_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR02_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR03[0].soma.v(0.5)")
h("setpointer syn_NC_MVR02_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR02[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR03_MVR01_Generic_GJ
print("Adding electrical projection: NC_MVR03_MVR01_Generic_GJ from MVR03 to MVR01, with 1 connection(s)")
h("objectvar syn_NC_MVR03_MVR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR03_MVR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR03[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR01[0].soma], weight: 1.0
h("a_MVR03[0].soma { syn_NC_MVR03_MVR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR01[0].soma { syn_NC_MVR03_MVR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR03_MVR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR01[0].soma.v(0.5)")
h("setpointer syn_NC_MVR03_MVR01_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR03[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR03_MVR02_Generic_GJ
print("Adding electrical projection: NC_MVR03_MVR02_Generic_GJ from MVR03 to MVR02, with 1 connection(s)")
h("objectvar syn_NC_MVR03_MVR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR03_MVR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR03[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR02[0].soma], weight: 1.0
h("a_MVR03[0].soma { syn_NC_MVR03_MVR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR02[0].soma { syn_NC_MVR03_MVR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR03_MVR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR02[0].soma.v(0.5)")
h("setpointer syn_NC_MVR03_MVR02_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR03[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR03_MVR04_Generic_GJ
print("Adding electrical projection: NC_MVR03_MVR04_Generic_GJ from MVR03 to MVR04, with 1 connection(s)")
h("objectvar syn_NC_MVR03_MVR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR03_MVR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR03[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR04[0].soma], weight: 1.0
h("a_MVR03[0].soma { syn_NC_MVR03_MVR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR04[0].soma { syn_NC_MVR03_MVR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR03_MVR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR04[0].soma.v(0.5)")
h("setpointer syn_NC_MVR03_MVR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR03[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR04_MVR03_Generic_GJ
print("Adding electrical projection: NC_MVR04_MVR03_Generic_GJ from MVR04 to MVR03, with 1 connection(s)")
h("objectvar syn_NC_MVR04_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR04_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR04[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR03[0].soma], weight: 1.0
h("a_MVR04[0].soma { syn_NC_MVR04_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR03[0].soma { syn_NC_MVR04_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR04_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR03[0].soma.v(0.5)")
h("setpointer syn_NC_MVR04_MVR03_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR04[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR04_MVR05_Generic_GJ
print("Adding electrical projection: NC_MVR04_MVR05_Generic_GJ from MVR04 to MVR05, with 1 connection(s)")
h("objectvar syn_NC_MVR04_MVR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR04_MVR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR04[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR05[0].soma], weight: 1.0
h("a_MVR04[0].soma { syn_NC_MVR04_MVR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR05[0].soma { syn_NC_MVR04_MVR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR04_MVR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR05[0].soma.v(0.5)")
h("setpointer syn_NC_MVR04_MVR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR04[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR05_MVR04_Generic_GJ
print("Adding electrical projection: NC_MVR05_MVR04_Generic_GJ from MVR05 to MVR04, with 1 connection(s)")
h("objectvar syn_NC_MVR05_MVR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR05_MVR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR05[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR04[0].soma], weight: 1.0
h("a_MVR05[0].soma { syn_NC_MVR05_MVR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR04[0].soma { syn_NC_MVR05_MVR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR05_MVR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR04[0].soma.v(0.5)")
h("setpointer syn_NC_MVR05_MVR04_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR05[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR05_MVR06_Generic_GJ
print("Adding electrical projection: NC_MVR05_MVR06_Generic_GJ from MVR05 to MVR06, with 1 connection(s)")
h("objectvar syn_NC_MVR05_MVR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR05_MVR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR05[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR06[0].soma], weight: 1.0
h("a_MVR05[0].soma { syn_NC_MVR05_MVR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR06[0].soma { syn_NC_MVR05_MVR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR05_MVR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR06[0].soma.v(0.5)")
h("setpointer syn_NC_MVR05_MVR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR05[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR06_MVR05_Generic_GJ
print("Adding electrical projection: NC_MVR06_MVR05_Generic_GJ from MVR06 to MVR05, with 1 connection(s)")
h("objectvar syn_NC_MVR06_MVR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR06_MVR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR06[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR05[0].soma], weight: 1.0
h("a_MVR06[0].soma { syn_NC_MVR06_MVR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR05[0].soma { syn_NC_MVR06_MVR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR06_MVR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR05[0].soma.v(0.5)")
h("setpointer syn_NC_MVR06_MVR05_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR06[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR06_MVR07_Generic_GJ
print("Adding electrical projection: NC_MVR06_MVR07_Generic_GJ from MVR06 to MVR07, with 1 connection(s)")
h("objectvar syn_NC_MVR06_MVR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR06_MVR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR06[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR07[0].soma], weight: 1.0
h("a_MVR06[0].soma { syn_NC_MVR06_MVR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR07[0].soma { syn_NC_MVR06_MVR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR06_MVR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR07[0].soma.v(0.5)")
h("setpointer syn_NC_MVR06_MVR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR06[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR07_MVR06_Generic_GJ
print("Adding electrical projection: NC_MVR07_MVR06_Generic_GJ from MVR07 to MVR06, with 1 connection(s)")
h("objectvar syn_NC_MVR07_MVR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR07_MVR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR07[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR06[0].soma], weight: 1.0
h("a_MVR07[0].soma { syn_NC_MVR07_MVR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR06[0].soma { syn_NC_MVR07_MVR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR07_MVR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR06[0].soma.v(0.5)")
h("setpointer syn_NC_MVR07_MVR06_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR07[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR07_MVR08_Generic_GJ
print("Adding electrical projection: NC_MVR07_MVR08_Generic_GJ from MVR07 to MVR08, with 1 connection(s)")
h("objectvar syn_NC_MVR07_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR07_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR07[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR08[0].soma], weight: 1.0
h("a_MVR07[0].soma { syn_NC_MVR07_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR08[0].soma { syn_NC_MVR07_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR07_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR08[0].soma.v(0.5)")
h("setpointer syn_NC_MVR07_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR07[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR08_MVL09_Generic_GJ
print("Adding electrical projection: NC_MVR08_MVL09_Generic_GJ from MVR08 to MVL09, with 1 connection(s)")
h("objectvar syn_NC_MVR08_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_2conns_A[1]")
h("objectvar syn_NC_MVR08_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_2conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR08[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVL09[0].soma], weight: 1.0
h("a_MVR08[0].soma { syn_NC_MVR08_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_2conns_A[0] = new muscle_to_muscle_elec_syn_2conns(0.5) }")
h("a_MVL09[0].soma { syn_NC_MVR08_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_2conns_B[0] = new muscle_to_muscle_elec_syn_2conns(0.5) }")
h("setpointer syn_NC_MVR08_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_2conns_A[0].vpeer, a_MVL09[0].soma.v(0.5)")
h("setpointer syn_NC_MVR08_MVL09_Generic_GJ_muscle_to_muscle_elec_syn_2conns_B[0].vpeer, a_MVR08[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR08_MVR07_Generic_GJ
print("Adding electrical projection: NC_MVR08_MVR07_Generic_GJ from MVR08 to MVR07, with 1 connection(s)")
h("objectvar syn_NC_MVR08_MVR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR08_MVR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR08[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR07[0].soma], weight: 1.0
h("a_MVR08[0].soma { syn_NC_MVR08_MVR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR07[0].soma { syn_NC_MVR08_MVR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR08_MVR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR07[0].soma.v(0.5)")
h("setpointer syn_NC_MVR08_MVR07_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR08[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR08_MVR09_Generic_GJ
print("Adding electrical projection: NC_MVR08_MVR09_Generic_GJ from MVR08 to MVR09, with 1 connection(s)")
h("objectvar syn_NC_MVR08_MVR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR08_MVR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR08[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR09[0].soma], weight: 1.0
h("a_MVR08[0].soma { syn_NC_MVR08_MVR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR09[0].soma { syn_NC_MVR08_MVR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR08_MVR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR09[0].soma.v(0.5)")
h("setpointer syn_NC_MVR08_MVR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR08[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR09_MVR08_Generic_GJ
print("Adding electrical projection: NC_MVR09_MVR08_Generic_GJ from MVR09 to MVR08, with 1 connection(s)")
h("objectvar syn_NC_MVR09_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR09_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR09[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR08[0].soma], weight: 1.0
h("a_MVR09[0].soma { syn_NC_MVR09_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR08[0].soma { syn_NC_MVR09_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR09_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR08[0].soma.v(0.5)")
h("setpointer syn_NC_MVR09_MVR08_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR09[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR09_MVR10_Generic_GJ
print("Adding electrical projection: NC_MVR09_MVR10_Generic_GJ from MVR09 to MVR10, with 1 connection(s)")
h("objectvar syn_NC_MVR09_MVR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR09_MVR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR09[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR10[0].soma], weight: 1.0
h("a_MVR09[0].soma { syn_NC_MVR09_MVR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR10[0].soma { syn_NC_MVR09_MVR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR09_MVR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR10[0].soma.v(0.5)")
h("setpointer syn_NC_MVR09_MVR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR09[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR10_MVR09_Generic_GJ
print("Adding electrical projection: NC_MVR10_MVR09_Generic_GJ from MVR10 to MVR09, with 1 connection(s)")
h("objectvar syn_NC_MVR10_MVR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR10_MVR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR10[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR09[0].soma], weight: 1.0
h("a_MVR10[0].soma { syn_NC_MVR10_MVR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR09[0].soma { syn_NC_MVR10_MVR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR10_MVR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR09[0].soma.v(0.5)")
h("setpointer syn_NC_MVR10_MVR09_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR10[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR10_MVR11_Generic_GJ
print("Adding electrical projection: NC_MVR10_MVR11_Generic_GJ from MVR10 to MVR11, with 1 connection(s)")
h("objectvar syn_NC_MVR10_MVR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR10_MVR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR10[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR11[0].soma], weight: 1.0
h("a_MVR10[0].soma { syn_NC_MVR10_MVR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR11[0].soma { syn_NC_MVR10_MVR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR10_MVR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR11[0].soma.v(0.5)")
h("setpointer syn_NC_MVR10_MVR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR10[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR11_MVR10_Generic_GJ
print("Adding electrical projection: NC_MVR11_MVR10_Generic_GJ from MVR11 to MVR10, with 1 connection(s)")
h("objectvar syn_NC_MVR11_MVR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR11_MVR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR11[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR10[0].soma], weight: 1.0
h("a_MVR11[0].soma { syn_NC_MVR11_MVR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR10[0].soma { syn_NC_MVR11_MVR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR11_MVR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR10[0].soma.v(0.5)")
h("setpointer syn_NC_MVR11_MVR10_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR11[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR11_MVR12_Generic_GJ
print("Adding electrical projection: NC_MVR11_MVR12_Generic_GJ from MVR11 to MVR12, with 1 connection(s)")
h("objectvar syn_NC_MVR11_MVR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR11_MVR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR11[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR12[0].soma], weight: 1.0
h("a_MVR11[0].soma { syn_NC_MVR11_MVR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR12[0].soma { syn_NC_MVR11_MVR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR11_MVR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR12[0].soma.v(0.5)")
h("setpointer syn_NC_MVR11_MVR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR11[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR12_MVR11_Generic_GJ
print("Adding electrical projection: NC_MVR12_MVR11_Generic_GJ from MVR12 to MVR11, with 1 connection(s)")
h("objectvar syn_NC_MVR12_MVR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR12_MVR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR12[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR11[0].soma], weight: 1.0
h("a_MVR12[0].soma { syn_NC_MVR12_MVR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR11[0].soma { syn_NC_MVR12_MVR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR12_MVR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR11[0].soma.v(0.5)")
h("setpointer syn_NC_MVR12_MVR11_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR12[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR12_MVR13_Generic_GJ
print("Adding electrical projection: NC_MVR12_MVR13_Generic_GJ from MVR12 to MVR13, with 1 connection(s)")
h("objectvar syn_NC_MVR12_MVR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR12_MVR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR12[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR13[0].soma], weight: 1.0
h("a_MVR12[0].soma { syn_NC_MVR12_MVR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR13[0].soma { syn_NC_MVR12_MVR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR12_MVR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR13[0].soma.v(0.5)")
h("setpointer syn_NC_MVR12_MVR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR12[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR13_MVR12_Generic_GJ
print("Adding electrical projection: NC_MVR13_MVR12_Generic_GJ from MVR13 to MVR12, with 1 connection(s)")
h("objectvar syn_NC_MVR13_MVR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR13_MVR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR13[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR12[0].soma], weight: 1.0
h("a_MVR13[0].soma { syn_NC_MVR13_MVR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR12[0].soma { syn_NC_MVR13_MVR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR13_MVR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR12[0].soma.v(0.5)")
h("setpointer syn_NC_MVR13_MVR12_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR13[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR13_MVR14_Generic_GJ
print("Adding electrical projection: NC_MVR13_MVR14_Generic_GJ from MVR13 to MVR14, with 1 connection(s)")
h("objectvar syn_NC_MVR13_MVR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR13_MVR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR13[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR14[0].soma], weight: 1.0
h("a_MVR13[0].soma { syn_NC_MVR13_MVR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR14[0].soma { syn_NC_MVR13_MVR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR13_MVR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR14[0].soma.v(0.5)")
h("setpointer syn_NC_MVR13_MVR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR13[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR14_MVR13_Generic_GJ
print("Adding electrical projection: NC_MVR14_MVR13_Generic_GJ from MVR14 to MVR13, with 1 connection(s)")
h("objectvar syn_NC_MVR14_MVR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR14_MVR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR14[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR13[0].soma], weight: 1.0
h("a_MVR14[0].soma { syn_NC_MVR14_MVR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR13[0].soma { syn_NC_MVR14_MVR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR14_MVR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR13[0].soma.v(0.5)")
h("setpointer syn_NC_MVR14_MVR13_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR14[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR14_MVR15_Generic_GJ
print("Adding electrical projection: NC_MVR14_MVR15_Generic_GJ from MVR14 to MVR15, with 1 connection(s)")
h("objectvar syn_NC_MVR14_MVR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR14_MVR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR14[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR15[0].soma], weight: 1.0
h("a_MVR14[0].soma { syn_NC_MVR14_MVR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR15[0].soma { syn_NC_MVR14_MVR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR14_MVR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR15[0].soma.v(0.5)")
h("setpointer syn_NC_MVR14_MVR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR14[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR15_MVR14_Generic_GJ
print("Adding electrical projection: NC_MVR15_MVR14_Generic_GJ from MVR15 to MVR14, with 1 connection(s)")
h("objectvar syn_NC_MVR15_MVR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR15_MVR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR15[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR14[0].soma], weight: 1.0
h("a_MVR15[0].soma { syn_NC_MVR15_MVR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR14[0].soma { syn_NC_MVR15_MVR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR15_MVR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR14[0].soma.v(0.5)")
h("setpointer syn_NC_MVR15_MVR14_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR15[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR15_MVR16_Generic_GJ
print("Adding electrical projection: NC_MVR15_MVR16_Generic_GJ from MVR15 to MVR16, with 1 connection(s)")
h("objectvar syn_NC_MVR15_MVR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR15_MVR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR15[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR16[0].soma], weight: 1.0
h("a_MVR15[0].soma { syn_NC_MVR15_MVR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR16[0].soma { syn_NC_MVR15_MVR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR15_MVR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR16[0].soma.v(0.5)")
h("setpointer syn_NC_MVR15_MVR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR15[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR16_MVR15_Generic_GJ
print("Adding electrical projection: NC_MVR16_MVR15_Generic_GJ from MVR16 to MVR15, with 1 connection(s)")
h("objectvar syn_NC_MVR16_MVR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR16_MVR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR16[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR15[0].soma], weight: 1.0
h("a_MVR16[0].soma { syn_NC_MVR16_MVR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR15[0].soma { syn_NC_MVR16_MVR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR16_MVR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR15[0].soma.v(0.5)")
h("setpointer syn_NC_MVR16_MVR15_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR16[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR16_MVR17_Generic_GJ
print("Adding electrical projection: NC_MVR16_MVR17_Generic_GJ from MVR16 to MVR17, with 1 connection(s)")
h("objectvar syn_NC_MVR16_MVR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR16_MVR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR16[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR17[0].soma], weight: 1.0
h("a_MVR16[0].soma { syn_NC_MVR16_MVR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR17[0].soma { syn_NC_MVR16_MVR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR16_MVR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR17[0].soma.v(0.5)")
h("setpointer syn_NC_MVR16_MVR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR16[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR17_MVR16_Generic_GJ
print("Adding electrical projection: NC_MVR17_MVR16_Generic_GJ from MVR17 to MVR16, with 1 connection(s)")
h("objectvar syn_NC_MVR17_MVR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR17_MVR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR17[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR16[0].soma], weight: 1.0
h("a_MVR17[0].soma { syn_NC_MVR17_MVR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR16[0].soma { syn_NC_MVR17_MVR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR17_MVR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR16[0].soma.v(0.5)")
h("setpointer syn_NC_MVR17_MVR16_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR17[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR17_MVR18_Generic_GJ
print("Adding electrical projection: NC_MVR17_MVR18_Generic_GJ from MVR17 to MVR18, with 1 connection(s)")
h("objectvar syn_NC_MVR17_MVR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR17_MVR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR17[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR18[0].soma], weight: 1.0
h("a_MVR17[0].soma { syn_NC_MVR17_MVR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR18[0].soma { syn_NC_MVR17_MVR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR17_MVR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR18[0].soma.v(0.5)")
h("setpointer syn_NC_MVR17_MVR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR17[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR18_MVR17_Generic_GJ
print("Adding electrical projection: NC_MVR18_MVR17_Generic_GJ from MVR18 to MVR17, with 1 connection(s)")
h("objectvar syn_NC_MVR18_MVR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR18_MVR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR18[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR17[0].soma], weight: 1.0
h("a_MVR18[0].soma { syn_NC_MVR18_MVR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR17[0].soma { syn_NC_MVR18_MVR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR18_MVR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR17[0].soma.v(0.5)")
h("setpointer syn_NC_MVR18_MVR17_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR18[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR18_MVR19_Generic_GJ
print("Adding electrical projection: NC_MVR18_MVR19_Generic_GJ from MVR18 to MVR19, with 1 connection(s)")
h("objectvar syn_NC_MVR18_MVR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR18_MVR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR18[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR19[0].soma], weight: 1.0
h("a_MVR18[0].soma { syn_NC_MVR18_MVR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR19[0].soma { syn_NC_MVR18_MVR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR18_MVR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR19[0].soma.v(0.5)")
h("setpointer syn_NC_MVR18_MVR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR18[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR19_MVR18_Generic_GJ
print("Adding electrical projection: NC_MVR19_MVR18_Generic_GJ from MVR19 to MVR18, with 1 connection(s)")
h("objectvar syn_NC_MVR19_MVR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR19_MVR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR19[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR18[0].soma], weight: 1.0
h("a_MVR19[0].soma { syn_NC_MVR19_MVR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR18[0].soma { syn_NC_MVR19_MVR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR19_MVR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR18[0].soma.v(0.5)")
h("setpointer syn_NC_MVR19_MVR18_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR19[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR19_MVR20_Generic_GJ
print("Adding electrical projection: NC_MVR19_MVR20_Generic_GJ from MVR19 to MVR20, with 1 connection(s)")
h("objectvar syn_NC_MVR19_MVR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR19_MVR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR19[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR20[0].soma], weight: 1.0
h("a_MVR19[0].soma { syn_NC_MVR19_MVR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR20[0].soma { syn_NC_MVR19_MVR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR19_MVR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR20[0].soma.v(0.5)")
h("setpointer syn_NC_MVR19_MVR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR19[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR20_MVR19_Generic_GJ
print("Adding electrical projection: NC_MVR20_MVR19_Generic_GJ from MVR20 to MVR19, with 1 connection(s)")
h("objectvar syn_NC_MVR20_MVR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR20_MVR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR20[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR19[0].soma], weight: 1.0
h("a_MVR20[0].soma { syn_NC_MVR20_MVR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR19[0].soma { syn_NC_MVR20_MVR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR20_MVR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR19[0].soma.v(0.5)")
h("setpointer syn_NC_MVR20_MVR19_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR20[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR20_MVR21_Generic_GJ
print("Adding electrical projection: NC_MVR20_MVR21_Generic_GJ from MVR20 to MVR21, with 1 connection(s)")
h("objectvar syn_NC_MVR20_MVR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR20_MVR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR20[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR21[0].soma], weight: 1.0
h("a_MVR20[0].soma { syn_NC_MVR20_MVR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR21[0].soma { syn_NC_MVR20_MVR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR20_MVR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR21[0].soma.v(0.5)")
h("setpointer syn_NC_MVR20_MVR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR20[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR21_MVR20_Generic_GJ
print("Adding electrical projection: NC_MVR21_MVR20_Generic_GJ from MVR21 to MVR20, with 1 connection(s)")
h("objectvar syn_NC_MVR21_MVR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR21_MVR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR21[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR20[0].soma], weight: 1.0
h("a_MVR21[0].soma { syn_NC_MVR21_MVR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR20[0].soma { syn_NC_MVR21_MVR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR21_MVR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR20[0].soma.v(0.5)")
h("setpointer syn_NC_MVR21_MVR20_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR21[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR21_MVR22_Generic_GJ
print("Adding electrical projection: NC_MVR21_MVR22_Generic_GJ from MVR21 to MVR22, with 1 connection(s)")
h("objectvar syn_NC_MVR21_MVR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR21_MVR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR21[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR22[0].soma], weight: 1.0
h("a_MVR21[0].soma { syn_NC_MVR21_MVR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR22[0].soma { syn_NC_MVR21_MVR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR21_MVR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR22[0].soma.v(0.5)")
h("setpointer syn_NC_MVR21_MVR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR21[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR22_MVR21_Generic_GJ
print("Adding electrical projection: NC_MVR22_MVR21_Generic_GJ from MVR22 to MVR21, with 1 connection(s)")
h("objectvar syn_NC_MVR22_MVR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR22_MVR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR22[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR21[0].soma], weight: 1.0
h("a_MVR22[0].soma { syn_NC_MVR22_MVR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR21[0].soma { syn_NC_MVR22_MVR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR22_MVR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR21[0].soma.v(0.5)")
h("setpointer syn_NC_MVR22_MVR21_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR22[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR22_MVR23_Generic_GJ
print("Adding electrical projection: NC_MVR22_MVR23_Generic_GJ from MVR22 to MVR23, with 1 connection(s)")
h("objectvar syn_NC_MVR22_MVR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR22_MVR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR22[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR23[0].soma], weight: 1.0
h("a_MVR22[0].soma { syn_NC_MVR22_MVR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR23[0].soma { syn_NC_MVR22_MVR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR22_MVR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR23[0].soma.v(0.5)")
h("setpointer syn_NC_MVR22_MVR23_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR22[0].soma.v(0.5)")
# ###################### Electrical Projection: NC_MVR23_MVR22_Generic_GJ
print("Adding electrical projection: NC_MVR23_MVR22_Generic_GJ from MVR23 to MVR22, with 1 connection(s)")
h("objectvar syn_NC_MVR23_MVR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[1]")
h("objectvar syn_NC_MVR23_MVR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[1]")
# Elect Connection 0: cell 0, seg 0 (0.5) [0.5 on a_MVR23[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MVR22[0].soma], weight: 1.0
h("a_MVR23[0].soma { syn_NC_MVR23_MVR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("a_MVR22[0].soma { syn_NC_MVR23_MVR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0] = new muscle_to_muscle_elec_syn_15conns(0.5) }")
h("setpointer syn_NC_MVR23_MVR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_A[0].vpeer, a_MVR22[0].soma.v(0.5)")
h("setpointer syn_NC_MVR23_MVR22_Generic_GJ_muscle_to_muscle_elec_syn_15conns_B[0].vpeer, a_MVR23[0].soma.v(0.5)")
# ###################### Continuous Projection: NC_AVAL_AVBL_Acetylcholine
print("Adding continuous projection: NC_AVAL_AVBL_Acetylcholine from AVAL to AVBL, with 1 connection(s)")
h("objectvar syn_NC_AVAL_AVBL_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAL_AVBL_Acetylcholine_neuron_to_neuron_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_AVBL_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AVBL[0].soma { syn_NC_AVAL_AVBL_Acetylcholine_neuron_to_neuron_exc_syn_2conns_post[0] = new neuron_to_neuron_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_AVAL_AVBL_Acetylcholine_silent_pre[0].vpeer, a_AVBL[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAL_AVBL_Acetylcholine_neuron_to_neuron_exc_syn_2conns_post[0].vpeer, a_AVAL[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAL_DA1_Acetylcholine
print("Adding continuous projection: NC_AVAL_DA1_Acetylcholine from AVAL to DA1, with 1 connection(s)")
h("objectvar syn_NC_AVAL_DA1_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAL_DA1_Acetylcholine_neuron_to_neuron_exc_syn_6conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA1[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_DA1_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA1[0].soma { syn_NC_AVAL_DA1_Acetylcholine_neuron_to_neuron_exc_syn_6conns_post[0] = new neuron_to_neuron_exc_syn_6conns(0.500000) }")
h("setpointer syn_NC_AVAL_DA1_Acetylcholine_silent_pre[0].vpeer, a_DA1[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAL_DA1_Acetylcholine_neuron_to_neuron_exc_syn_6conns_post[0].vpeer, a_AVAL[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAL_DA2_Acetylcholine
print("Adding continuous projection: NC_AVAL_DA2_Acetylcholine from AVAL to DA2, with 1 connection(s)")
h("objectvar syn_NC_AVAL_DA2_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAL_DA2_Acetylcholine_neuron_to_neuron_exc_syn_10conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA2[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_DA2_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA2[0].soma { syn_NC_AVAL_DA2_Acetylcholine_neuron_to_neuron_exc_syn_10conns_post[0] = new neuron_to_neuron_exc_syn_10conns(0.500000) }")
h("setpointer syn_NC_AVAL_DA2_Acetylcholine_silent_pre[0].vpeer, a_DA2[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAL_DA2_Acetylcholine_neuron_to_neuron_exc_syn_10conns_post[0].vpeer, a_AVAL[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAL_DA3_Acetylcholine
print("Adding continuous projection: NC_AVAL_DA3_Acetylcholine from AVAL to DA3, with 1 connection(s)")
h("objectvar syn_NC_AVAL_DA3_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAL_DA3_Acetylcholine_neuron_to_neuron_exc_syn_12conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA3[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_DA3_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA3[0].soma { syn_NC_AVAL_DA3_Acetylcholine_neuron_to_neuron_exc_syn_12conns_post[0] = new neuron_to_neuron_exc_syn_12conns(0.500000) }")
h("setpointer syn_NC_AVAL_DA3_Acetylcholine_silent_pre[0].vpeer, a_DA3[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAL_DA3_Acetylcholine_neuron_to_neuron_exc_syn_12conns_post[0].vpeer, a_AVAL[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAL_DA4_Acetylcholine
print("Adding continuous projection: NC_AVAL_DA4_Acetylcholine from AVAL to DA4, with 1 connection(s)")
h("objectvar syn_NC_AVAL_DA4_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAL_DA4_Acetylcholine_neuron_to_neuron_exc_syn_12conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA4[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_DA4_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA4[0].soma { syn_NC_AVAL_DA4_Acetylcholine_neuron_to_neuron_exc_syn_12conns_post[0] = new neuron_to_neuron_exc_syn_12conns(0.500000) }")
h("setpointer syn_NC_AVAL_DA4_Acetylcholine_silent_pre[0].vpeer, a_DA4[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAL_DA4_Acetylcholine_neuron_to_neuron_exc_syn_12conns_post[0].vpeer, a_AVAL[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAL_DA5_Acetylcholine
print("Adding continuous projection: NC_AVAL_DA5_Acetylcholine from AVAL to DA5, with 1 connection(s)")
h("objectvar syn_NC_AVAL_DA5_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAL_DA5_Acetylcholine_neuron_to_neuron_exc_syn_14conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA5[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_DA5_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA5[0].soma { syn_NC_AVAL_DA5_Acetylcholine_neuron_to_neuron_exc_syn_14conns_post[0] = new neuron_to_neuron_exc_syn_14conns(0.500000) }")
h("setpointer syn_NC_AVAL_DA5_Acetylcholine_silent_pre[0].vpeer, a_DA5[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAL_DA5_Acetylcholine_neuron_to_neuron_exc_syn_14conns_post[0].vpeer, a_AVAL[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAL_DA7_Acetylcholine
print("Adding continuous projection: NC_AVAL_DA7_Acetylcholine from AVAL to DA7, with 1 connection(s)")
h("objectvar syn_NC_AVAL_DA7_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAL_DA7_Acetylcholine_neuron_to_neuron_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA7[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_DA7_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA7[0].soma { syn_NC_AVAL_DA7_Acetylcholine_neuron_to_neuron_exc_syn_4conns_post[0] = new neuron_to_neuron_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_AVAL_DA7_Acetylcholine_silent_pre[0].vpeer, a_DA7[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAL_DA7_Acetylcholine_neuron_to_neuron_exc_syn_4conns_post[0].vpeer, a_AVAL[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAL_DA8_Acetylcholine
print("Adding continuous projection: NC_AVAL_DA8_Acetylcholine from AVAL to DA8, with 1 connection(s)")
h("objectvar syn_NC_AVAL_DA8_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAL_DA8_Acetylcholine_neuron_to_neuron_exc_syn_5conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_DA8_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA8[0].soma { syn_NC_AVAL_DA8_Acetylcholine_neuron_to_neuron_exc_syn_5conns_post[0] = new neuron_to_neuron_exc_syn_5conns(0.500000) }")
h("setpointer syn_NC_AVAL_DA8_Acetylcholine_silent_pre[0].vpeer, a_DA8[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAL_DA8_Acetylcholine_neuron_to_neuron_exc_syn_5conns_post[0].vpeer, a_AVAL[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAL_DA9_Acetylcholine
print("Adding continuous projection: NC_AVAL_DA9_Acetylcholine from AVAL to DA9, with 1 connection(s)")
h("objectvar syn_NC_AVAL_DA9_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAL_DA9_Acetylcholine_neuron_to_neuron_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma], weight: 1.0
h("a_AVAL[0].soma { syn_NC_AVAL_DA9_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA9[0].soma { syn_NC_AVAL_DA9_Acetylcholine_neuron_to_neuron_exc_syn_3conns_post[0] = new neuron_to_neuron_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_AVAL_DA9_Acetylcholine_silent_pre[0].vpeer, a_DA9[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAL_DA9_Acetylcholine_neuron_to_neuron_exc_syn_3conns_post[0].vpeer, a_AVAL[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAR_AVBL_Acetylcholine
print("Adding continuous projection: NC_AVAR_AVBL_Acetylcholine from AVAR to AVBL, with 1 connection(s)")
h("objectvar syn_NC_AVAR_AVBL_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAR_AVBL_Acetylcholine_neuron_to_neuron_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_AVBL_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AVBL[0].soma { syn_NC_AVAR_AVBL_Acetylcholine_neuron_to_neuron_exc_syn_3conns_post[0] = new neuron_to_neuron_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_AVAR_AVBL_Acetylcholine_silent_pre[0].vpeer, a_AVBL[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAR_AVBL_Acetylcholine_neuron_to_neuron_exc_syn_3conns_post[0].vpeer, a_AVAR[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAR_AVBR_Acetylcholine
print("Adding continuous projection: NC_AVAR_AVBR_Acetylcholine from AVAR to AVBR, with 1 connection(s)")
h("objectvar syn_NC_AVAR_AVBR_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAR_AVBR_Acetylcholine_neuron_to_neuron_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_AVBR_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AVBR[0].soma { syn_NC_AVAR_AVBR_Acetylcholine_neuron_to_neuron_exc_syn_4conns_post[0] = new neuron_to_neuron_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_AVAR_AVBR_Acetylcholine_silent_pre[0].vpeer, a_AVBR[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAR_AVBR_Acetylcholine_neuron_to_neuron_exc_syn_4conns_post[0].vpeer, a_AVAR[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAR_DA1_Acetylcholine
print("Adding continuous projection: NC_AVAR_DA1_Acetylcholine from AVAR to DA1, with 1 connection(s)")
h("objectvar syn_NC_AVAR_DA1_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAR_DA1_Acetylcholine_neuron_to_neuron_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA1[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_DA1_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA1[0].soma { syn_NC_AVAR_DA1_Acetylcholine_neuron_to_neuron_exc_syn_2conns_post[0] = new neuron_to_neuron_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_AVAR_DA1_Acetylcholine_silent_pre[0].vpeer, a_DA1[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAR_DA1_Acetylcholine_neuron_to_neuron_exc_syn_2conns_post[0].vpeer, a_AVAR[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAR_DA2_Acetylcholine
print("Adding continuous projection: NC_AVAR_DA2_Acetylcholine from AVAR to DA2, with 1 connection(s)")
h("objectvar syn_NC_AVAR_DA2_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAR_DA2_Acetylcholine_neuron_to_neuron_exc_syn_9conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA2[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_DA2_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA2[0].soma { syn_NC_AVAR_DA2_Acetylcholine_neuron_to_neuron_exc_syn_9conns_post[0] = new neuron_to_neuron_exc_syn_9conns(0.500000) }")
h("setpointer syn_NC_AVAR_DA2_Acetylcholine_silent_pre[0].vpeer, a_DA2[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAR_DA2_Acetylcholine_neuron_to_neuron_exc_syn_9conns_post[0].vpeer, a_AVAR[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAR_DA3_Acetylcholine
print("Adding continuous projection: NC_AVAR_DA3_Acetylcholine from AVAR to DA3, with 1 connection(s)")
h("objectvar syn_NC_AVAR_DA3_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAR_DA3_Acetylcholine_neuron_to_neuron_exc_syn_8conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA3[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_DA3_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA3[0].soma { syn_NC_AVAR_DA3_Acetylcholine_neuron_to_neuron_exc_syn_8conns_post[0] = new neuron_to_neuron_exc_syn_8conns(0.500000) }")
h("setpointer syn_NC_AVAR_DA3_Acetylcholine_silent_pre[0].vpeer, a_DA3[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAR_DA3_Acetylcholine_neuron_to_neuron_exc_syn_8conns_post[0].vpeer, a_AVAR[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAR_DA4_Acetylcholine
print("Adding continuous projection: NC_AVAR_DA4_Acetylcholine from AVAR to DA4, with 1 connection(s)")
h("objectvar syn_NC_AVAR_DA4_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAR_DA4_Acetylcholine_neuron_to_neuron_exc_syn_9conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA4[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_DA4_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA4[0].soma { syn_NC_AVAR_DA4_Acetylcholine_neuron_to_neuron_exc_syn_9conns_post[0] = new neuron_to_neuron_exc_syn_9conns(0.500000) }")
h("setpointer syn_NC_AVAR_DA4_Acetylcholine_silent_pre[0].vpeer, a_DA4[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAR_DA4_Acetylcholine_neuron_to_neuron_exc_syn_9conns_post[0].vpeer, a_AVAR[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAR_DA5_Acetylcholine
print("Adding continuous projection: NC_AVAR_DA5_Acetylcholine from AVAR to DA5, with 1 connection(s)")
h("objectvar syn_NC_AVAR_DA5_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAR_DA5_Acetylcholine_neuron_to_neuron_exc_syn_9conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA5[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_DA5_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA5[0].soma { syn_NC_AVAR_DA5_Acetylcholine_neuron_to_neuron_exc_syn_9conns_post[0] = new neuron_to_neuron_exc_syn_9conns(0.500000) }")
h("setpointer syn_NC_AVAR_DA5_Acetylcholine_silent_pre[0].vpeer, a_DA5[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAR_DA5_Acetylcholine_neuron_to_neuron_exc_syn_9conns_post[0].vpeer, a_AVAR[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAR_DA6_Acetylcholine
print("Adding continuous projection: NC_AVAR_DA6_Acetylcholine from AVAR to DA6, with 1 connection(s)")
h("objectvar syn_NC_AVAR_DA6_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAR_DA6_Acetylcholine_neuron_to_neuron_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_DA6_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA6[0].soma { syn_NC_AVAR_DA6_Acetylcholine_neuron_to_neuron_exc_syn_4conns_post[0] = new neuron_to_neuron_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_AVAR_DA6_Acetylcholine_silent_pre[0].vpeer, a_DA6[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAR_DA6_Acetylcholine_neuron_to_neuron_exc_syn_4conns_post[0].vpeer, a_AVAR[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAR_DA7_Acetylcholine
print("Adding continuous projection: NC_AVAR_DA7_Acetylcholine from AVAR to DA7, with 1 connection(s)")
h("objectvar syn_NC_AVAR_DA7_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAR_DA7_Acetylcholine_neuron_to_neuron_exc_syn_6conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA7[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_DA7_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA7[0].soma { syn_NC_AVAR_DA7_Acetylcholine_neuron_to_neuron_exc_syn_6conns_post[0] = new neuron_to_neuron_exc_syn_6conns(0.500000) }")
h("setpointer syn_NC_AVAR_DA7_Acetylcholine_silent_pre[0].vpeer, a_DA7[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAR_DA7_Acetylcholine_neuron_to_neuron_exc_syn_6conns_post[0].vpeer, a_AVAR[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAR_DA8_Acetylcholine
print("Adding continuous projection: NC_AVAR_DA8_Acetylcholine from AVAR to DA8, with 1 connection(s)")
h("objectvar syn_NC_AVAR_DA8_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAR_DA8_Acetylcholine_neuron_to_neuron_exc_syn_20conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_DA8_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA8[0].soma { syn_NC_AVAR_DA8_Acetylcholine_neuron_to_neuron_exc_syn_20conns_post[0] = new neuron_to_neuron_exc_syn_20conns(0.500000) }")
h("setpointer syn_NC_AVAR_DA8_Acetylcholine_silent_pre[0].vpeer, a_DA8[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAR_DA8_Acetylcholine_neuron_to_neuron_exc_syn_20conns_post[0].vpeer, a_AVAR[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVAR_DA9_Acetylcholine
print("Adding continuous projection: NC_AVAR_DA9_Acetylcholine from AVAR to DA9, with 1 connection(s)")
h("objectvar syn_NC_AVAR_DA9_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVAR_DA9_Acetylcholine_neuron_to_neuron_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma], weight: 1.0
h("a_AVAR[0].soma { syn_NC_AVAR_DA9_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA9[0].soma { syn_NC_AVAR_DA9_Acetylcholine_neuron_to_neuron_exc_syn_3conns_post[0] = new neuron_to_neuron_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_AVAR_DA9_Acetylcholine_silent_pre[0].vpeer, a_DA9[0].soma.v(0.500000)")
h("setpointer syn_NC_AVAR_DA9_Acetylcholine_neuron_to_neuron_exc_syn_3conns_post[0].vpeer, a_AVAR[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVBL_AVAL_Acetylcholine
print("Adding continuous projection: NC_AVBL_AVAL_Acetylcholine from AVBL to AVAL, with 1 connection(s)")
h("objectvar syn_NC_AVBL_AVAL_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVBL_AVAL_Acetylcholine_neuron_to_neuron_exc_syn_9conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma], weight: 1.0
h("a_AVBL[0].soma { syn_NC_AVBL_AVAL_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AVAL[0].soma { syn_NC_AVBL_AVAL_Acetylcholine_neuron_to_neuron_exc_syn_9conns_post[0] = new neuron_to_neuron_exc_syn_9conns(0.500000) }")
h("setpointer syn_NC_AVBL_AVAL_Acetylcholine_silent_pre[0].vpeer, a_AVAL[0].soma.v(0.500000)")
h("setpointer syn_NC_AVBL_AVAL_Acetylcholine_neuron_to_neuron_exc_syn_9conns_post[0].vpeer, a_AVBL[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVBL_AVAR_Acetylcholine
print("Adding continuous projection: NC_AVBL_AVAR_Acetylcholine from AVBL to AVAR, with 1 connection(s)")
h("objectvar syn_NC_AVBL_AVAR_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVBL_AVAR_Acetylcholine_neuron_to_neuron_exc_syn_14conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBL[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma], weight: 1.0
h("a_AVBL[0].soma { syn_NC_AVBL_AVAR_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AVAR[0].soma { syn_NC_AVBL_AVAR_Acetylcholine_neuron_to_neuron_exc_syn_14conns_post[0] = new neuron_to_neuron_exc_syn_14conns(0.500000) }")
h("setpointer syn_NC_AVBL_AVAR_Acetylcholine_silent_pre[0].vpeer, a_AVAR[0].soma.v(0.500000)")
h("setpointer syn_NC_AVBL_AVAR_Acetylcholine_neuron_to_neuron_exc_syn_14conns_post[0].vpeer, a_AVBL[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVBR_AVAL_Acetylcholine
print("Adding continuous projection: NC_AVBR_AVAL_Acetylcholine from AVBR to AVAL, with 1 connection(s)")
h("objectvar syn_NC_AVBR_AVAL_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVBR_AVAL_Acetylcholine_neuron_to_neuron_exc_syn_10conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAL[0].soma], weight: 1.0
h("a_AVBR[0].soma { syn_NC_AVBR_AVAL_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AVAL[0].soma { syn_NC_AVBR_AVAL_Acetylcholine_neuron_to_neuron_exc_syn_10conns_post[0] = new neuron_to_neuron_exc_syn_10conns(0.500000) }")
h("setpointer syn_NC_AVBR_AVAL_Acetylcholine_silent_pre[0].vpeer, a_AVAL[0].soma.v(0.500000)")
h("setpointer syn_NC_AVBR_AVAL_Acetylcholine_neuron_to_neuron_exc_syn_10conns_post[0].vpeer, a_AVBR[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVBR_AVAR_Acetylcholine
print("Adding continuous projection: NC_AVBR_AVAR_Acetylcholine from AVBR to AVAR, with 1 connection(s)")
h("objectvar syn_NC_AVBR_AVAR_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVBR_AVAR_Acetylcholine_neuron_to_neuron_exc_syn_14conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AVAR[0].soma], weight: 1.0
h("a_AVBR[0].soma { syn_NC_AVBR_AVAR_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AVAR[0].soma { syn_NC_AVBR_AVAR_Acetylcholine_neuron_to_neuron_exc_syn_14conns_post[0] = new neuron_to_neuron_exc_syn_14conns(0.500000) }")
h("setpointer syn_NC_AVBR_AVAR_Acetylcholine_silent_pre[0].vpeer, a_AVAR[0].soma.v(0.500000)")
h("setpointer syn_NC_AVBR_AVAR_Acetylcholine_neuron_to_neuron_exc_syn_14conns_post[0].vpeer, a_AVBR[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AVBR_DB4_Acetylcholine
print("Adding continuous projection: NC_AVBR_DB4_Acetylcholine from AVBR to DB4, with 1 connection(s)")
h("objectvar syn_NC_AVBR_DB4_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AVBR_DB4_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AVBR[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB4[0].soma], weight: 1.0
h("a_AVBR[0].soma { syn_NC_AVBR_DB4_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DB4[0].soma { syn_NC_AVBR_DB4_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0] = new neuron_to_neuron_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_AVBR_DB4_Acetylcholine_silent_pre[0].vpeer, a_DB4[0].soma.v(0.500000)")
h("setpointer syn_NC_AVBR_DB4_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0].vpeer, a_AVBR[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA1_DB1_Acetylcholine
print("Adding continuous projection: NC_DA1_DB1_Acetylcholine from DA1 to DB1, with 1 connection(s)")
h("objectvar syn_NC_DA1_DB1_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA1_DB1_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA1[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB1[0].soma], weight: 1.0
h("a_DA1[0].soma { syn_NC_DA1_DB1_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DB1[0].soma { syn_NC_DA1_DB1_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0] = new neuron_to_neuron_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DA1_DB1_Acetylcholine_silent_pre[0].vpeer, a_DB1[0].soma.v(0.500000)")
h("setpointer syn_NC_DA1_DB1_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0].vpeer, a_DA1[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA2_DB1_Acetylcholine
print("Adding continuous projection: NC_DA2_DB1_Acetylcholine from DA2 to DB1, with 1 connection(s)")
h("objectvar syn_NC_DA2_DB1_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA2_DB1_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB1[0].soma], weight: 1.0
h("a_DA2[0].soma { syn_NC_DA2_DB1_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DB1[0].soma { syn_NC_DA2_DB1_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0] = new neuron_to_neuron_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DA2_DB1_Acetylcholine_silent_pre[0].vpeer, a_DB1[0].soma.v(0.500000)")
h("setpointer syn_NC_DA2_DB1_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0].vpeer, a_DA2[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA3_DB3_Acetylcholine
print("Adding continuous projection: NC_DA3_DB3_Acetylcholine from DA3 to DB3, with 1 connection(s)")
h("objectvar syn_NC_DA3_DB3_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA3_DB3_Acetylcholine_neuron_to_neuron_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB3[0].soma], weight: 1.0
h("a_DA3[0].soma { syn_NC_DA3_DB3_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DB3[0].soma { syn_NC_DA3_DB3_Acetylcholine_neuron_to_neuron_exc_syn_2conns_post[0] = new neuron_to_neuron_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DA3_DB3_Acetylcholine_silent_pre[0].vpeer, a_DB3[0].soma.v(0.500000)")
h("setpointer syn_NC_DA3_DB3_Acetylcholine_neuron_to_neuron_exc_syn_2conns_post[0].vpeer, a_DA3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA4_DB2_Acetylcholine
print("Adding continuous projection: NC_DA4_DB2_Acetylcholine from DA4 to DB2, with 1 connection(s)")
h("objectvar syn_NC_DA4_DB2_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA4_DB2_Acetylcholine_neuron_to_neuron_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB2[0].soma], weight: 1.0
h("a_DA4[0].soma { syn_NC_DA4_DB2_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DB2[0].soma { syn_NC_DA4_DB2_Acetylcholine_neuron_to_neuron_exc_syn_2conns_post[0] = new neuron_to_neuron_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DA4_DB2_Acetylcholine_silent_pre[0].vpeer, a_DB2[0].soma.v(0.500000)")
h("setpointer syn_NC_DA4_DB2_Acetylcholine_neuron_to_neuron_exc_syn_2conns_post[0].vpeer, a_DA4[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA5_DB4_Acetylcholine
print("Adding continuous projection: NC_DA5_DB4_Acetylcholine from DA5 to DB4, with 1 connection(s)")
h("objectvar syn_NC_DA5_DB4_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA5_DB4_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB4[0].soma], weight: 1.0
h("a_DA5[0].soma { syn_NC_DA5_DB4_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DB4[0].soma { syn_NC_DA5_DB4_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0] = new neuron_to_neuron_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DA5_DB4_Acetylcholine_silent_pre[0].vpeer, a_DB4[0].soma.v(0.500000)")
h("setpointer syn_NC_DA5_DB4_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0].vpeer, a_DA5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA6_DB5_Acetylcholine
print("Adding continuous projection: NC_DA6_DB5_Acetylcholine from DA6 to DB5, with 1 connection(s)")
h("objectvar syn_NC_DA6_DB5_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA6_DB5_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma], weight: 1.0
h("a_DA6[0].soma { syn_NC_DA6_DB5_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DB5[0].soma { syn_NC_DA6_DB5_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0] = new neuron_to_neuron_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DA6_DB5_Acetylcholine_silent_pre[0].vpeer, a_DB5[0].soma.v(0.500000)")
h("setpointer syn_NC_DA6_DB5_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0].vpeer, a_DA6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA7_DB6_Acetylcholine
print("Adding continuous projection: NC_DA7_DB6_Acetylcholine from DA7 to DB6, with 1 connection(s)")
h("objectvar syn_NC_DA7_DB6_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA7_DB6_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma], weight: 1.0
h("a_DA7[0].soma { syn_NC_DA7_DB6_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DB6[0].soma { syn_NC_DA7_DB6_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0] = new neuron_to_neuron_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DA7_DB6_Acetylcholine_silent_pre[0].vpeer, a_DB6[0].soma.v(0.500000)")
h("setpointer syn_NC_DA7_DB6_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0].vpeer, a_DA7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA8_DB7_Acetylcholine
print("Adding continuous projection: NC_DA8_DB7_Acetylcholine from DA8 to DB7, with 1 connection(s)")
h("objectvar syn_NC_DA8_DB7_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA8_DB7_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma], weight: 1.0
h("a_DA8[0].soma { syn_NC_DA8_DB7_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DB7[0].soma { syn_NC_DA8_DB7_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0] = new neuron_to_neuron_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DA8_DB7_Acetylcholine_silent_pre[0].vpeer, a_DB7[0].soma.v(0.500000)")
h("setpointer syn_NC_DA8_DB7_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0].vpeer, a_DA8[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA9_DB7_Acetylcholine
print("Adding continuous projection: NC_DA9_DB7_Acetylcholine from DA9 to DB7, with 1 connection(s)")
h("objectvar syn_NC_DA9_DB7_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA9_DB7_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma], weight: 1.0
h("a_DA9[0].soma { syn_NC_DA9_DB7_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DB7[0].soma { syn_NC_DA9_DB7_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0] = new neuron_to_neuron_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DA9_DB7_Acetylcholine_silent_pre[0].vpeer, a_DB7[0].soma.v(0.500000)")
h("setpointer syn_NC_DA9_DB7_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0].vpeer, a_DA9[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB1_AS1_Acetylcholine
print("Adding continuous projection: NC_DB1_AS1_Acetylcholine from DB1 to AS1, with 1 connection(s)")
h("objectvar syn_NC_DB1_AS1_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB1_AS1_Acetylcholine_neuron_to_neuron_inh_syn_28conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB1[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AS1[0].soma], weight: 1.0
h("a_DB1[0].soma { syn_NC_DB1_AS1_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AS1[0].soma { syn_NC_DB1_AS1_Acetylcholine_neuron_to_neuron_inh_syn_28conns_post[0] = new neuron_to_neuron_inh_syn_28conns(0.500000) }")
h("setpointer syn_NC_DB1_AS1_Acetylcholine_silent_pre[0].vpeer, a_AS1[0].soma.v(0.500000)")
h("setpointer syn_NC_DB1_AS1_Acetylcholine_neuron_to_neuron_inh_syn_28conns_post[0].vpeer, a_DB1[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB1_AS2_Acetylcholine
print("Adding continuous projection: NC_DB1_AS2_Acetylcholine from DB1 to AS2, with 1 connection(s)")
h("objectvar syn_NC_DB1_AS2_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB1_AS2_Acetylcholine_neuron_to_neuron_inh_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB1[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AS2[0].soma], weight: 1.0
h("a_DB1[0].soma { syn_NC_DB1_AS2_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AS2[0].soma { syn_NC_DB1_AS2_Acetylcholine_neuron_to_neuron_inh_syn_4conns_post[0] = new neuron_to_neuron_inh_syn_4conns(0.500000) }")
h("setpointer syn_NC_DB1_AS2_Acetylcholine_silent_pre[0].vpeer, a_AS2[0].soma.v(0.500000)")
h("setpointer syn_NC_DB1_AS2_Acetylcholine_neuron_to_neuron_inh_syn_4conns_post[0].vpeer, a_DB1[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB2_AS3_Acetylcholine
print("Adding continuous projection: NC_DB2_AS3_Acetylcholine from DB2 to AS3, with 1 connection(s)")
h("objectvar syn_NC_DB2_AS3_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB2_AS3_Acetylcholine_neuron_to_neuron_inh_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AS3[0].soma], weight: 1.0
h("a_DB2[0].soma { syn_NC_DB2_AS3_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AS3[0].soma { syn_NC_DB2_AS3_Acetylcholine_neuron_to_neuron_inh_syn_3conns_post[0] = new neuron_to_neuron_inh_syn_3conns(0.500000) }")
h("setpointer syn_NC_DB2_AS3_Acetylcholine_silent_pre[0].vpeer, a_AS3[0].soma.v(0.500000)")
h("setpointer syn_NC_DB2_AS3_Acetylcholine_neuron_to_neuron_inh_syn_3conns_post[0].vpeer, a_DB2[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB2_AS4_Acetylcholine
print("Adding continuous projection: NC_DB2_AS4_Acetylcholine from DB2 to AS4, with 1 connection(s)")
h("objectvar syn_NC_DB2_AS4_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB2_AS4_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AS4[0].soma], weight: 1.0
h("a_DB2[0].soma { syn_NC_DB2_AS4_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AS4[0].soma { syn_NC_DB2_AS4_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[0] = new neuron_to_neuron_inh_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB2_AS4_Acetylcholine_silent_pre[0].vpeer, a_AS4[0].soma.v(0.500000)")
h("setpointer syn_NC_DB2_AS4_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[0].vpeer, a_DB2[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB3_AS4_Acetylcholine
print("Adding continuous projection: NC_DB3_AS4_Acetylcholine from DB3 to AS4, with 1 connection(s)")
h("objectvar syn_NC_DB3_AS4_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB3_AS4_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AS4[0].soma], weight: 1.0
h("a_DB3[0].soma { syn_NC_DB3_AS4_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AS4[0].soma { syn_NC_DB3_AS4_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[0] = new neuron_to_neuron_inh_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB3_AS4_Acetylcholine_silent_pre[0].vpeer, a_AS4[0].soma.v(0.500000)")
h("setpointer syn_NC_DB3_AS4_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[0].vpeer, a_DB3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB3_AS5_Acetylcholine
print("Adding continuous projection: NC_DB3_AS5_Acetylcholine from DB3 to AS5, with 1 connection(s)")
h("objectvar syn_NC_DB3_AS5_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB3_AS5_Acetylcholine_neuron_to_neuron_inh_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AS5[0].soma], weight: 1.0
h("a_DB3[0].soma { syn_NC_DB3_AS5_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AS5[0].soma { syn_NC_DB3_AS5_Acetylcholine_neuron_to_neuron_inh_syn_1conns_post[0] = new neuron_to_neuron_inh_syn_1conns(0.500000) }")
h("setpointer syn_NC_DB3_AS5_Acetylcholine_silent_pre[0].vpeer, a_AS5[0].soma.v(0.500000)")
h("setpointer syn_NC_DB3_AS5_Acetylcholine_neuron_to_neuron_inh_syn_1conns_post[0].vpeer, a_DB3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB4_AS6_Acetylcholine
print("Adding continuous projection: NC_DB4_AS6_Acetylcholine from DB4 to AS6, with 1 connection(s)")
h("objectvar syn_NC_DB4_AS6_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB4_AS6_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AS6[0].soma], weight: 1.0
h("a_DB4[0].soma { syn_NC_DB4_AS6_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AS6[0].soma { syn_NC_DB4_AS6_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[0] = new neuron_to_neuron_inh_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB4_AS6_Acetylcholine_silent_pre[0].vpeer, a_AS6[0].soma.v(0.500000)")
h("setpointer syn_NC_DB4_AS6_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[0].vpeer, a_DB4[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB5_AS7_Acetylcholine
print("Adding continuous projection: NC_DB5_AS7_Acetylcholine from DB5 to AS7, with 1 connection(s)")
h("objectvar syn_NC_DB5_AS7_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB5_AS7_Acetylcholine_neuron_to_neuron_inh_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AS7[0].soma], weight: 1.0
h("a_DB5[0].soma { syn_NC_DB5_AS7_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AS7[0].soma { syn_NC_DB5_AS7_Acetylcholine_neuron_to_neuron_inh_syn_3conns_post[0] = new neuron_to_neuron_inh_syn_3conns(0.500000) }")
h("setpointer syn_NC_DB5_AS7_Acetylcholine_silent_pre[0].vpeer, a_AS7[0].soma.v(0.500000)")
h("setpointer syn_NC_DB5_AS7_Acetylcholine_neuron_to_neuron_inh_syn_3conns_post[0].vpeer, a_DB5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB5_AS8_Acetylcholine
print("Adding continuous projection: NC_DB5_AS8_Acetylcholine from DB5 to AS8, with 1 connection(s)")
h("objectvar syn_NC_DB5_AS8_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB5_AS8_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AS8[0].soma], weight: 1.0
h("a_DB5[0].soma { syn_NC_DB5_AS8_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AS8[0].soma { syn_NC_DB5_AS8_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[0] = new neuron_to_neuron_inh_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB5_AS8_Acetylcholine_silent_pre[0].vpeer, a_AS8[0].soma.v(0.500000)")
h("setpointer syn_NC_DB5_AS8_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[0].vpeer, a_DB5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB6_AS8_Acetylcholine
print("Adding continuous projection: NC_DB6_AS8_Acetylcholine from DB6 to AS8, with 1 connection(s)")
h("objectvar syn_NC_DB6_AS8_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB6_AS8_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AS8[0].soma], weight: 1.0
h("a_DB6[0].soma { syn_NC_DB6_AS8_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AS8[0].soma { syn_NC_DB6_AS8_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[0] = new neuron_to_neuron_inh_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB6_AS8_Acetylcholine_silent_pre[0].vpeer, a_AS8[0].soma.v(0.500000)")
h("setpointer syn_NC_DB6_AS8_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[0].vpeer, a_DB6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB6_AS9_Acetylcholine
print("Adding continuous projection: NC_DB6_AS9_Acetylcholine from DB6 to AS9, with 1 connection(s)")
h("objectvar syn_NC_DB6_AS9_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB6_AS9_Acetylcholine_neuron_to_neuron_inh_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AS9[0].soma], weight: 1.0
h("a_DB6[0].soma { syn_NC_DB6_AS9_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AS9[0].soma { syn_NC_DB6_AS9_Acetylcholine_neuron_to_neuron_inh_syn_1conns_post[0] = new neuron_to_neuron_inh_syn_1conns(0.500000) }")
h("setpointer syn_NC_DB6_AS9_Acetylcholine_silent_pre[0].vpeer, a_AS9[0].soma.v(0.500000)")
h("setpointer syn_NC_DB6_AS9_Acetylcholine_neuron_to_neuron_inh_syn_1conns_post[0].vpeer, a_DB6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB7_AS10_Acetylcholine
print("Adding continuous projection: NC_DB7_AS10_Acetylcholine from DB7 to AS10, with 1 connection(s)")
h("objectvar syn_NC_DB7_AS10_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB7_AS10_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AS10[0].soma], weight: 1.0
h("a_DB7[0].soma { syn_NC_DB7_AS10_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AS10[0].soma { syn_NC_DB7_AS10_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[0] = new neuron_to_neuron_inh_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB7_AS10_Acetylcholine_silent_pre[0].vpeer, a_AS10[0].soma.v(0.500000)")
h("setpointer syn_NC_DB7_AS10_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[0].vpeer, a_DB7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB7_AS11_Acetylcholine
print("Adding continuous projection: NC_DB7_AS11_Acetylcholine from DB7 to AS11, with 1 connection(s)")
h("objectvar syn_NC_DB7_AS11_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB7_AS11_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_AS11[0].soma], weight: 1.0
h("a_DB7[0].soma { syn_NC_DB7_AS11_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_AS11[0].soma { syn_NC_DB7_AS11_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[0] = new neuron_to_neuron_inh_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB7_AS11_Acetylcholine_silent_pre[0].vpeer, a_AS11[0].soma.v(0.500000)")
h("setpointer syn_NC_DB7_AS11_Acetylcholine_neuron_to_neuron_inh_syn_2conns_post[0].vpeer, a_DB7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AS1_DA1_Acetylcholine
print("Adding continuous projection: NC_AS1_DA1_Acetylcholine from AS1 to DA1, with 1 connection(s)")
h("objectvar syn_NC_AS1_DA1_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AS1_DA1_Acetylcholine_neuron_to_neuron_exc_syn_8conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AS1[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA1[0].soma], weight: 1.0
h("a_AS1[0].soma { syn_NC_AS1_DA1_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA1[0].soma { syn_NC_AS1_DA1_Acetylcholine_neuron_to_neuron_exc_syn_8conns_post[0] = new neuron_to_neuron_exc_syn_8conns(0.500000) }")
h("setpointer syn_NC_AS1_DA1_Acetylcholine_silent_pre[0].vpeer, a_DA1[0].soma.v(0.500000)")
h("setpointer syn_NC_AS1_DA1_Acetylcholine_neuron_to_neuron_exc_syn_8conns_post[0].vpeer, a_AS1[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AS3_DA3_Acetylcholine
print("Adding continuous projection: NC_AS3_DA3_Acetylcholine from AS3 to DA3, with 1 connection(s)")
h("objectvar syn_NC_AS3_DA3_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AS3_DA3_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AS3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA3[0].soma], weight: 1.0
h("a_AS3[0].soma { syn_NC_AS3_DA3_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA3[0].soma { syn_NC_AS3_DA3_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0] = new neuron_to_neuron_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_AS3_DA3_Acetylcholine_silent_pre[0].vpeer, a_DA3[0].soma.v(0.500000)")
h("setpointer syn_NC_AS3_DA3_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0].vpeer, a_AS3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AS4_DA3_Acetylcholine
print("Adding continuous projection: NC_AS4_DA3_Acetylcholine from AS4 to DA3, with 1 connection(s)")
h("objectvar syn_NC_AS4_DA3_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AS4_DA3_Acetylcholine_neuron_to_neuron_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AS4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA3[0].soma], weight: 1.0
h("a_AS4[0].soma { syn_NC_AS4_DA3_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA3[0].soma { syn_NC_AS4_DA3_Acetylcholine_neuron_to_neuron_exc_syn_2conns_post[0] = new neuron_to_neuron_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_AS4_DA3_Acetylcholine_silent_pre[0].vpeer, a_DA3[0].soma.v(0.500000)")
h("setpointer syn_NC_AS4_DA3_Acetylcholine_neuron_to_neuron_exc_syn_2conns_post[0].vpeer, a_AS4[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_AS6_DA5_Acetylcholine
print("Adding continuous projection: NC_AS6_DA5_Acetylcholine from AS6 to DA5, with 1 connection(s)")
h("objectvar syn_NC_AS6_DA5_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_AS6_DA5_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_AS6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_DA5[0].soma], weight: 1.0
h("a_AS6[0].soma { syn_NC_AS6_DA5_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_DA5[0].soma { syn_NC_AS6_DA5_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0] = new neuron_to_neuron_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_AS6_DA5_Acetylcholine_silent_pre[0].vpeer, a_DA5[0].soma.v(0.500000)")
h("setpointer syn_NC_AS6_DA5_Acetylcholine_neuron_to_neuron_exc_syn_1conns_post[0].vpeer, a_AS6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA1_MDL06_Acetylcholine
print("Adding continuous projection: NC_DA1_MDL06_Acetylcholine from DA1 to MDL06, with 1 connection(s)")
h("objectvar syn_NC_DA1_MDL06_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA1_MDL06_Acetylcholine_neuron_to_muscle_exc_syn_9conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA1[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL06[0].soma], weight: 1.0
h("a_DA1[0].soma { syn_NC_DA1_MDL06_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL06[0].soma { syn_NC_DA1_MDL06_Acetylcholine_neuron_to_muscle_exc_syn_9conns_post[0] = new neuron_to_muscle_exc_syn_9conns(0.500000) }")
h("setpointer syn_NC_DA1_MDL06_Acetylcholine_silent_pre[0].vpeer, a_MDL06[0].soma.v(0.500000)")
h("setpointer syn_NC_DA1_MDL06_Acetylcholine_neuron_to_muscle_exc_syn_9conns_post[0].vpeer, a_DA1[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA1_MDL07_Acetylcholine
print("Adding continuous projection: NC_DA1_MDL07_Acetylcholine from DA1 to MDL07, with 1 connection(s)")
h("objectvar syn_NC_DA1_MDL07_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA1_MDL07_Acetylcholine_neuron_to_muscle_exc_syn_8conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA1[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL07[0].soma], weight: 1.0
h("a_DA1[0].soma { syn_NC_DA1_MDL07_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL07[0].soma { syn_NC_DA1_MDL07_Acetylcholine_neuron_to_muscle_exc_syn_8conns_post[0] = new neuron_to_muscle_exc_syn_8conns(0.500000) }")
h("setpointer syn_NC_DA1_MDL07_Acetylcholine_silent_pre[0].vpeer, a_MDL07[0].soma.v(0.500000)")
h("setpointer syn_NC_DA1_MDL07_Acetylcholine_neuron_to_muscle_exc_syn_8conns_post[0].vpeer, a_DA1[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA1_MDL08_Acetylcholine
print("Adding continuous projection: NC_DA1_MDL08_Acetylcholine from DA1 to MDL08, with 1 connection(s)")
h("objectvar syn_NC_DA1_MDL08_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA1_MDL08_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA1[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL08[0].soma], weight: 1.0
h("a_DA1[0].soma { syn_NC_DA1_MDL08_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL08[0].soma { syn_NC_DA1_MDL08_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA1_MDL08_Acetylcholine_silent_pre[0].vpeer, a_MDL08[0].soma.v(0.500000)")
h("setpointer syn_NC_DA1_MDL08_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA1[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA1_MDR06_Acetylcholine
print("Adding continuous projection: NC_DA1_MDR06_Acetylcholine from DA1 to MDR06, with 1 connection(s)")
h("objectvar syn_NC_DA1_MDR06_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA1_MDR06_Acetylcholine_neuron_to_muscle_exc_syn_8conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA1[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR06[0].soma], weight: 1.0
h("a_DA1[0].soma { syn_NC_DA1_MDR06_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR06[0].soma { syn_NC_DA1_MDR06_Acetylcholine_neuron_to_muscle_exc_syn_8conns_post[0] = new neuron_to_muscle_exc_syn_8conns(0.500000) }")
h("setpointer syn_NC_DA1_MDR06_Acetylcholine_silent_pre[0].vpeer, a_MDR06[0].soma.v(0.500000)")
h("setpointer syn_NC_DA1_MDR06_Acetylcholine_neuron_to_muscle_exc_syn_8conns_post[0].vpeer, a_DA1[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA1_MDR07_Acetylcholine
print("Adding continuous projection: NC_DA1_MDR07_Acetylcholine from DA1 to MDR07, with 1 connection(s)")
h("objectvar syn_NC_DA1_MDR07_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA1_MDR07_Acetylcholine_neuron_to_muscle_exc_syn_9conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA1[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR07[0].soma], weight: 1.0
h("a_DA1[0].soma { syn_NC_DA1_MDR07_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR07[0].soma { syn_NC_DA1_MDR07_Acetylcholine_neuron_to_muscle_exc_syn_9conns_post[0] = new neuron_to_muscle_exc_syn_9conns(0.500000) }")
h("setpointer syn_NC_DA1_MDR07_Acetylcholine_silent_pre[0].vpeer, a_MDR07[0].soma.v(0.500000)")
h("setpointer syn_NC_DA1_MDR07_Acetylcholine_neuron_to_muscle_exc_syn_9conns_post[0].vpeer, a_DA1[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA2_MDL07_Acetylcholine
print("Adding continuous projection: NC_DA2_MDL07_Acetylcholine from DA2 to MDL07, with 1 connection(s)")
h("objectvar syn_NC_DA2_MDL07_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA2_MDL07_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL07[0].soma], weight: 1.0
h("a_DA2[0].soma { syn_NC_DA2_MDL07_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL07[0].soma { syn_NC_DA2_MDL07_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0] = new neuron_to_muscle_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DA2_MDL07_Acetylcholine_silent_pre[0].vpeer, a_MDL07[0].soma.v(0.500000)")
h("setpointer syn_NC_DA2_MDL07_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0].vpeer, a_DA2[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA2_MDL08_Acetylcholine
print("Adding continuous projection: NC_DA2_MDL08_Acetylcholine from DA2 to MDL08, with 1 connection(s)")
h("objectvar syn_NC_DA2_MDL08_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA2_MDL08_Acetylcholine_neuron_to_muscle_exc_syn_5conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL08[0].soma], weight: 1.0
h("a_DA2[0].soma { syn_NC_DA2_MDL08_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL08[0].soma { syn_NC_DA2_MDL08_Acetylcholine_neuron_to_muscle_exc_syn_5conns_post[0] = new neuron_to_muscle_exc_syn_5conns(0.500000) }")
h("setpointer syn_NC_DA2_MDL08_Acetylcholine_silent_pre[0].vpeer, a_MDL08[0].soma.v(0.500000)")
h("setpointer syn_NC_DA2_MDL08_Acetylcholine_neuron_to_muscle_exc_syn_5conns_post[0].vpeer, a_DA2[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA2_MDL09_Acetylcholine
print("Adding continuous projection: NC_DA2_MDL09_Acetylcholine from DA2 to MDL09, with 1 connection(s)")
h("objectvar syn_NC_DA2_MDL09_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA2_MDL09_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL09[0].soma], weight: 1.0
h("a_DA2[0].soma { syn_NC_DA2_MDL09_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL09[0].soma { syn_NC_DA2_MDL09_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0] = new neuron_to_muscle_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_DA2_MDL09_Acetylcholine_silent_pre[0].vpeer, a_MDL09[0].soma.v(0.500000)")
h("setpointer syn_NC_DA2_MDL09_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0].vpeer, a_DA2[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA2_MDL10_Acetylcholine
print("Adding continuous projection: NC_DA2_MDL10_Acetylcholine from DA2 to MDL10, with 1 connection(s)")
h("objectvar syn_NC_DA2_MDL10_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA2_MDL10_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL10[0].soma], weight: 1.0
h("a_DA2[0].soma { syn_NC_DA2_MDL10_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL10[0].soma { syn_NC_DA2_MDL10_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DA2_MDL10_Acetylcholine_silent_pre[0].vpeer, a_MDL10[0].soma.v(0.500000)")
h("setpointer syn_NC_DA2_MDL10_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DA2[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA2_MDR07_Acetylcholine
print("Adding continuous projection: NC_DA2_MDR07_Acetylcholine from DA2 to MDR07, with 1 connection(s)")
h("objectvar syn_NC_DA2_MDR07_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA2_MDR07_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR07[0].soma], weight: 1.0
h("a_DA2[0].soma { syn_NC_DA2_MDR07_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR07[0].soma { syn_NC_DA2_MDR07_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA2_MDR07_Acetylcholine_silent_pre[0].vpeer, a_MDR07[0].soma.v(0.500000)")
h("setpointer syn_NC_DA2_MDR07_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA2[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA2_MDR08_Acetylcholine
print("Adding continuous projection: NC_DA2_MDR08_Acetylcholine from DA2 to MDR08, with 1 connection(s)")
h("objectvar syn_NC_DA2_MDR08_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA2_MDR08_Acetylcholine_neuron_to_muscle_exc_syn_6conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR08[0].soma], weight: 1.0
h("a_DA2[0].soma { syn_NC_DA2_MDR08_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR08[0].soma { syn_NC_DA2_MDR08_Acetylcholine_neuron_to_muscle_exc_syn_6conns_post[0] = new neuron_to_muscle_exc_syn_6conns(0.500000) }")
h("setpointer syn_NC_DA2_MDR08_Acetylcholine_silent_pre[0].vpeer, a_MDR08[0].soma.v(0.500000)")
h("setpointer syn_NC_DA2_MDR08_Acetylcholine_neuron_to_muscle_exc_syn_6conns_post[0].vpeer, a_DA2[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA2_MDR09_Acetylcholine
print("Adding continuous projection: NC_DA2_MDR09_Acetylcholine from DA2 to MDR09, with 1 connection(s)")
h("objectvar syn_NC_DA2_MDR09_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA2_MDR09_Acetylcholine_neuron_to_muscle_exc_syn_7conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR09[0].soma], weight: 1.0
h("a_DA2[0].soma { syn_NC_DA2_MDR09_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR09[0].soma { syn_NC_DA2_MDR09_Acetylcholine_neuron_to_muscle_exc_syn_7conns_post[0] = new neuron_to_muscle_exc_syn_7conns(0.500000) }")
h("setpointer syn_NC_DA2_MDR09_Acetylcholine_silent_pre[0].vpeer, a_MDR09[0].soma.v(0.500000)")
h("setpointer syn_NC_DA2_MDR09_Acetylcholine_neuron_to_muscle_exc_syn_7conns_post[0].vpeer, a_DA2[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA3_MDL09_Acetylcholine
print("Adding continuous projection: NC_DA3_MDL09_Acetylcholine from DA3 to MDL09, with 1 connection(s)")
h("objectvar syn_NC_DA3_MDL09_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA3_MDL09_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL09[0].soma], weight: 1.0
h("a_DA3[0].soma { syn_NC_DA3_MDL09_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL09[0].soma { syn_NC_DA3_MDL09_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA3_MDL09_Acetylcholine_silent_pre[0].vpeer, a_MDL09[0].soma.v(0.500000)")
h("setpointer syn_NC_DA3_MDL09_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA3_MDL10_Acetylcholine
print("Adding continuous projection: NC_DA3_MDL10_Acetylcholine from DA3 to MDL10, with 1 connection(s)")
h("objectvar syn_NC_DA3_MDL10_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA3_MDL10_Acetylcholine_neuron_to_muscle_exc_syn_17conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL10[0].soma], weight: 1.0
h("a_DA3[0].soma { syn_NC_DA3_MDL10_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL10[0].soma { syn_NC_DA3_MDL10_Acetylcholine_neuron_to_muscle_exc_syn_17conns_post[0] = new neuron_to_muscle_exc_syn_17conns(0.500000) }")
h("setpointer syn_NC_DA3_MDL10_Acetylcholine_silent_pre[0].vpeer, a_MDL10[0].soma.v(0.500000)")
h("setpointer syn_NC_DA3_MDL10_Acetylcholine_neuron_to_muscle_exc_syn_17conns_post[0].vpeer, a_DA3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA3_MDL11_Acetylcholine
print("Adding continuous projection: NC_DA3_MDL11_Acetylcholine from DA3 to MDL11, with 1 connection(s)")
h("objectvar syn_NC_DA3_MDL11_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA3_MDL11_Acetylcholine_neuron_to_muscle_exc_syn_12conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL11[0].soma], weight: 1.0
h("a_DA3[0].soma { syn_NC_DA3_MDL11_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL11[0].soma { syn_NC_DA3_MDL11_Acetylcholine_neuron_to_muscle_exc_syn_12conns_post[0] = new neuron_to_muscle_exc_syn_12conns(0.500000) }")
h("setpointer syn_NC_DA3_MDL11_Acetylcholine_silent_pre[0].vpeer, a_MDL11[0].soma.v(0.500000)")
h("setpointer syn_NC_DA3_MDL11_Acetylcholine_neuron_to_muscle_exc_syn_12conns_post[0].vpeer, a_DA3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA3_MDR09_Acetylcholine
print("Adding continuous projection: NC_DA3_MDR09_Acetylcholine from DA3 to MDR09, with 1 connection(s)")
h("objectvar syn_NC_DA3_MDR09_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA3_MDR09_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR09[0].soma], weight: 1.0
h("a_DA3[0].soma { syn_NC_DA3_MDR09_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR09[0].soma { syn_NC_DA3_MDR09_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA3_MDR09_Acetylcholine_silent_pre[0].vpeer, a_MDR09[0].soma.v(0.500000)")
h("setpointer syn_NC_DA3_MDR09_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA3_MDR10_Acetylcholine
print("Adding continuous projection: NC_DA3_MDR10_Acetylcholine from DA3 to MDR10, with 1 connection(s)")
h("objectvar syn_NC_DA3_MDR10_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA3_MDR10_Acetylcholine_neuron_to_muscle_exc_syn_14conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR10[0].soma], weight: 1.0
h("a_DA3[0].soma { syn_NC_DA3_MDR10_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR10[0].soma { syn_NC_DA3_MDR10_Acetylcholine_neuron_to_muscle_exc_syn_14conns_post[0] = new neuron_to_muscle_exc_syn_14conns(0.500000) }")
h("setpointer syn_NC_DA3_MDR10_Acetylcholine_silent_pre[0].vpeer, a_MDR10[0].soma.v(0.500000)")
h("setpointer syn_NC_DA3_MDR10_Acetylcholine_neuron_to_muscle_exc_syn_14conns_post[0].vpeer, a_DA3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA3_MDR11_Acetylcholine
print("Adding continuous projection: NC_DA3_MDR11_Acetylcholine from DA3 to MDR11, with 1 connection(s)")
h("objectvar syn_NC_DA3_MDR11_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA3_MDR11_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR11[0].soma], weight: 1.0
h("a_DA3[0].soma { syn_NC_DA3_MDR11_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR11[0].soma { syn_NC_DA3_MDR11_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0] = new neuron_to_muscle_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_DA3_MDR11_Acetylcholine_silent_pre[0].vpeer, a_MDR11[0].soma.v(0.500000)")
h("setpointer syn_NC_DA3_MDR11_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0].vpeer, a_DA3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA3_MDR12_Acetylcholine
print("Adding continuous projection: NC_DA3_MDR12_Acetylcholine from DA3 to MDR12, with 1 connection(s)")
h("objectvar syn_NC_DA3_MDR12_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA3_MDR12_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR12[0].soma], weight: 1.0
h("a_DA3[0].soma { syn_NC_DA3_MDR12_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR12[0].soma { syn_NC_DA3_MDR12_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DA3_MDR12_Acetylcholine_silent_pre[0].vpeer, a_MDR12[0].soma.v(0.500000)")
h("setpointer syn_NC_DA3_MDR12_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DA3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA4_MDL11_Acetylcholine
print("Adding continuous projection: NC_DA4_MDL11_Acetylcholine from DA4 to MDL11, with 1 connection(s)")
h("objectvar syn_NC_DA4_MDL11_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA4_MDL11_Acetylcholine_neuron_to_muscle_exc_syn_6conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL11[0].soma], weight: 1.0
h("a_DA4[0].soma { syn_NC_DA4_MDL11_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL11[0].soma { syn_NC_DA4_MDL11_Acetylcholine_neuron_to_muscle_exc_syn_6conns_post[0] = new neuron_to_muscle_exc_syn_6conns(0.500000) }")
h("setpointer syn_NC_DA4_MDL11_Acetylcholine_silent_pre[0].vpeer, a_MDL11[0].soma.v(0.500000)")
h("setpointer syn_NC_DA4_MDL11_Acetylcholine_neuron_to_muscle_exc_syn_6conns_post[0].vpeer, a_DA4[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA4_MDL12_Acetylcholine
print("Adding continuous projection: NC_DA4_MDL12_Acetylcholine from DA4 to MDL12, with 1 connection(s)")
h("objectvar syn_NC_DA4_MDL12_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA4_MDL12_Acetylcholine_neuron_to_muscle_exc_syn_10conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL12[0].soma], weight: 1.0
h("a_DA4[0].soma { syn_NC_DA4_MDL12_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL12[0].soma { syn_NC_DA4_MDL12_Acetylcholine_neuron_to_muscle_exc_syn_10conns_post[0] = new neuron_to_muscle_exc_syn_10conns(0.500000) }")
h("setpointer syn_NC_DA4_MDL12_Acetylcholine_silent_pre[0].vpeer, a_MDL12[0].soma.v(0.500000)")
h("setpointer syn_NC_DA4_MDL12_Acetylcholine_neuron_to_muscle_exc_syn_10conns_post[0].vpeer, a_DA4[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA4_MDL13_Acetylcholine
print("Adding continuous projection: NC_DA4_MDL13_Acetylcholine from DA4 to MDL13, with 1 connection(s)")
h("objectvar syn_NC_DA4_MDL13_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA4_MDL13_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL13[0].soma], weight: 1.0
h("a_DA4[0].soma { syn_NC_DA4_MDL13_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL13[0].soma { syn_NC_DA4_MDL13_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0] = new neuron_to_muscle_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DA4_MDL13_Acetylcholine_silent_pre[0].vpeer, a_MDL13[0].soma.v(0.500000)")
h("setpointer syn_NC_DA4_MDL13_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0].vpeer, a_DA4[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA4_MDR11_Acetylcholine
print("Adding continuous projection: NC_DA4_MDR11_Acetylcholine from DA4 to MDR11, with 1 connection(s)")
h("objectvar syn_NC_DA4_MDR11_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA4_MDR11_Acetylcholine_neuron_to_muscle_exc_syn_5conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR11[0].soma], weight: 1.0
h("a_DA4[0].soma { syn_NC_DA4_MDR11_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR11[0].soma { syn_NC_DA4_MDR11_Acetylcholine_neuron_to_muscle_exc_syn_5conns_post[0] = new neuron_to_muscle_exc_syn_5conns(0.500000) }")
h("setpointer syn_NC_DA4_MDR11_Acetylcholine_silent_pre[0].vpeer, a_MDR11[0].soma.v(0.500000)")
h("setpointer syn_NC_DA4_MDR11_Acetylcholine_neuron_to_muscle_exc_syn_5conns_post[0].vpeer, a_DA4[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA4_MDR12_Acetylcholine
print("Adding continuous projection: NC_DA4_MDR12_Acetylcholine from DA4 to MDR12, with 1 connection(s)")
h("objectvar syn_NC_DA4_MDR12_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA4_MDR12_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR12[0].soma], weight: 1.0
h("a_DA4[0].soma { syn_NC_DA4_MDR12_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR12[0].soma { syn_NC_DA4_MDR12_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0] = new neuron_to_muscle_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_DA4_MDR12_Acetylcholine_silent_pre[0].vpeer, a_MDR12[0].soma.v(0.500000)")
h("setpointer syn_NC_DA4_MDR12_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0].vpeer, a_DA4[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA4_MDR13_Acetylcholine
print("Adding continuous projection: NC_DA4_MDR13_Acetylcholine from DA4 to MDR13, with 1 connection(s)")
h("objectvar syn_NC_DA4_MDR13_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA4_MDR13_Acetylcholine_neuron_to_muscle_exc_syn_9conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR13[0].soma], weight: 1.0
h("a_DA4[0].soma { syn_NC_DA4_MDR13_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR13[0].soma { syn_NC_DA4_MDR13_Acetylcholine_neuron_to_muscle_exc_syn_9conns_post[0] = new neuron_to_muscle_exc_syn_9conns(0.500000) }")
h("setpointer syn_NC_DA4_MDR13_Acetylcholine_silent_pre[0].vpeer, a_MDR13[0].soma.v(0.500000)")
h("setpointer syn_NC_DA4_MDR13_Acetylcholine_neuron_to_muscle_exc_syn_9conns_post[0].vpeer, a_DA4[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA5_MDL12_Acetylcholine
print("Adding continuous projection: NC_DA5_MDL12_Acetylcholine from DA5 to MDL12, with 1 connection(s)")
h("objectvar syn_NC_DA5_MDL12_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA5_MDL12_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL12[0].soma], weight: 1.0
h("a_DA5[0].soma { syn_NC_DA5_MDL12_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL12[0].soma { syn_NC_DA5_MDL12_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0] = new neuron_to_muscle_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DA5_MDL12_Acetylcholine_silent_pre[0].vpeer, a_MDL12[0].soma.v(0.500000)")
h("setpointer syn_NC_DA5_MDL12_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0].vpeer, a_DA5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA5_MDL13_Acetylcholine
print("Adding continuous projection: NC_DA5_MDL13_Acetylcholine from DA5 to MDL13, with 1 connection(s)")
h("objectvar syn_NC_DA5_MDL13_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA5_MDL13_Acetylcholine_neuron_to_muscle_exc_syn_10conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL13[0].soma], weight: 1.0
h("a_DA5[0].soma { syn_NC_DA5_MDL13_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL13[0].soma { syn_NC_DA5_MDL13_Acetylcholine_neuron_to_muscle_exc_syn_10conns_post[0] = new neuron_to_muscle_exc_syn_10conns(0.500000) }")
h("setpointer syn_NC_DA5_MDL13_Acetylcholine_silent_pre[0].vpeer, a_MDL13[0].soma.v(0.500000)")
h("setpointer syn_NC_DA5_MDL13_Acetylcholine_neuron_to_muscle_exc_syn_10conns_post[0].vpeer, a_DA5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA5_MDL14_Acetylcholine
print("Adding continuous projection: NC_DA5_MDL14_Acetylcholine from DA5 to MDL14, with 1 connection(s)")
h("objectvar syn_NC_DA5_MDL14_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA5_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_7conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL14[0].soma], weight: 1.0
h("a_DA5[0].soma { syn_NC_DA5_MDL14_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL14[0].soma { syn_NC_DA5_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_7conns_post[0] = new neuron_to_muscle_exc_syn_7conns(0.500000) }")
h("setpointer syn_NC_DA5_MDL14_Acetylcholine_silent_pre[0].vpeer, a_MDL14[0].soma.v(0.500000)")
h("setpointer syn_NC_DA5_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_7conns_post[0].vpeer, a_DA5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA5_MDR12_Acetylcholine
print("Adding continuous projection: NC_DA5_MDR12_Acetylcholine from DA5 to MDR12, with 1 connection(s)")
h("objectvar syn_NC_DA5_MDR12_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA5_MDR12_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR12[0].soma], weight: 1.0
h("a_DA5[0].soma { syn_NC_DA5_MDR12_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR12[0].soma { syn_NC_DA5_MDR12_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DA5_MDR12_Acetylcholine_silent_pre[0].vpeer, a_MDR12[0].soma.v(0.500000)")
h("setpointer syn_NC_DA5_MDR12_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DA5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA5_MDR13_Acetylcholine
print("Adding continuous projection: NC_DA5_MDR13_Acetylcholine from DA5 to MDR13, with 1 connection(s)")
h("objectvar syn_NC_DA5_MDR13_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA5_MDR13_Acetylcholine_neuron_to_muscle_exc_syn_7conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR13[0].soma], weight: 1.0
h("a_DA5[0].soma { syn_NC_DA5_MDR13_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR13[0].soma { syn_NC_DA5_MDR13_Acetylcholine_neuron_to_muscle_exc_syn_7conns_post[0] = new neuron_to_muscle_exc_syn_7conns(0.500000) }")
h("setpointer syn_NC_DA5_MDR13_Acetylcholine_silent_pre[0].vpeer, a_MDR13[0].soma.v(0.500000)")
h("setpointer syn_NC_DA5_MDR13_Acetylcholine_neuron_to_muscle_exc_syn_7conns_post[0].vpeer, a_DA5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA5_MDR14_Acetylcholine
print("Adding continuous projection: NC_DA5_MDR14_Acetylcholine from DA5 to MDR14, with 1 connection(s)")
h("objectvar syn_NC_DA5_MDR14_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA5_MDR14_Acetylcholine_neuron_to_muscle_exc_syn_8conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR14[0].soma], weight: 1.0
h("a_DA5[0].soma { syn_NC_DA5_MDR14_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR14[0].soma { syn_NC_DA5_MDR14_Acetylcholine_neuron_to_muscle_exc_syn_8conns_post[0] = new neuron_to_muscle_exc_syn_8conns(0.500000) }")
h("setpointer syn_NC_DA5_MDR14_Acetylcholine_silent_pre[0].vpeer, a_MDR14[0].soma.v(0.500000)")
h("setpointer syn_NC_DA5_MDR14_Acetylcholine_neuron_to_muscle_exc_syn_8conns_post[0].vpeer, a_DA5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA6_MDL11_Acetylcholine
print("Adding continuous projection: NC_DA6_MDL11_Acetylcholine from DA6 to MDL11, with 1 connection(s)")
h("objectvar syn_NC_DA6_MDL11_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA6_MDL11_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL11[0].soma], weight: 1.0
h("a_DA6[0].soma { syn_NC_DA6_MDL11_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL11[0].soma { syn_NC_DA6_MDL11_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0] = new neuron_to_muscle_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DA6_MDL11_Acetylcholine_silent_pre[0].vpeer, a_MDL11[0].soma.v(0.500000)")
h("setpointer syn_NC_DA6_MDL11_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0].vpeer, a_DA6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA6_MDL12_Acetylcholine
print("Adding continuous projection: NC_DA6_MDL12_Acetylcholine from DA6 to MDL12, with 1 connection(s)")
h("objectvar syn_NC_DA6_MDL12_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA6_MDL12_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL12[0].soma], weight: 1.0
h("a_DA6[0].soma { syn_NC_DA6_MDL12_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL12[0].soma { syn_NC_DA6_MDL12_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0] = new neuron_to_muscle_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DA6_MDL12_Acetylcholine_silent_pre[0].vpeer, a_MDL12[0].soma.v(0.500000)")
h("setpointer syn_NC_DA6_MDL12_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0].vpeer, a_DA6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA6_MDL13_Acetylcholine
print("Adding continuous projection: NC_DA6_MDL13_Acetylcholine from DA6 to MDL13, with 1 connection(s)")
h("objectvar syn_NC_DA6_MDL13_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA6_MDL13_Acetylcholine_neuron_to_muscle_exc_syn_5conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL13[0].soma], weight: 1.0
h("a_DA6[0].soma { syn_NC_DA6_MDL13_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL13[0].soma { syn_NC_DA6_MDL13_Acetylcholine_neuron_to_muscle_exc_syn_5conns_post[0] = new neuron_to_muscle_exc_syn_5conns(0.500000) }")
h("setpointer syn_NC_DA6_MDL13_Acetylcholine_silent_pre[0].vpeer, a_MDL13[0].soma.v(0.500000)")
h("setpointer syn_NC_DA6_MDL13_Acetylcholine_neuron_to_muscle_exc_syn_5conns_post[0].vpeer, a_DA6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA6_MDL14_Acetylcholine
print("Adding continuous projection: NC_DA6_MDL14_Acetylcholine from DA6 to MDL14, with 1 connection(s)")
h("objectvar syn_NC_DA6_MDL14_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA6_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL14[0].soma], weight: 1.0
h("a_DA6[0].soma { syn_NC_DA6_MDL14_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL14[0].soma { syn_NC_DA6_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0] = new neuron_to_muscle_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_DA6_MDL14_Acetylcholine_silent_pre[0].vpeer, a_MDL14[0].soma.v(0.500000)")
h("setpointer syn_NC_DA6_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0].vpeer, a_DA6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA6_MDL15_Acetylcholine
print("Adding continuous projection: NC_DA6_MDL15_Acetylcholine from DA6 to MDL15, with 1 connection(s)")
h("objectvar syn_NC_DA6_MDL15_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA6_MDL15_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL15[0].soma], weight: 1.0
h("a_DA6[0].soma { syn_NC_DA6_MDL15_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL15[0].soma { syn_NC_DA6_MDL15_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0] = new neuron_to_muscle_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_DA6_MDL15_Acetylcholine_silent_pre[0].vpeer, a_MDL15[0].soma.v(0.500000)")
h("setpointer syn_NC_DA6_MDL15_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0].vpeer, a_DA6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA6_MDL16_Acetylcholine
print("Adding continuous projection: NC_DA6_MDL16_Acetylcholine from DA6 to MDL16, with 1 connection(s)")
h("objectvar syn_NC_DA6_MDL16_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA6_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL16[0].soma], weight: 1.0
h("a_DA6[0].soma { syn_NC_DA6_MDL16_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL16[0].soma { syn_NC_DA6_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0] = new neuron_to_muscle_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_DA6_MDL16_Acetylcholine_silent_pre[0].vpeer, a_MDL16[0].soma.v(0.500000)")
h("setpointer syn_NC_DA6_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0].vpeer, a_DA6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA6_MDR10_Acetylcholine
print("Adding continuous projection: NC_DA6_MDR10_Acetylcholine from DA6 to MDR10, with 1 connection(s)")
h("objectvar syn_NC_DA6_MDR10_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA6_MDR10_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR10[0].soma], weight: 1.0
h("a_DA6[0].soma { syn_NC_DA6_MDR10_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR10[0].soma { syn_NC_DA6_MDR10_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0] = new neuron_to_muscle_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DA6_MDR10_Acetylcholine_silent_pre[0].vpeer, a_MDR10[0].soma.v(0.500000)")
h("setpointer syn_NC_DA6_MDR10_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0].vpeer, a_DA6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA6_MDR11_Acetylcholine
print("Adding continuous projection: NC_DA6_MDR11_Acetylcholine from DA6 to MDR11, with 1 connection(s)")
h("objectvar syn_NC_DA6_MDR11_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA6_MDR11_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR11[0].soma], weight: 1.0
h("a_DA6[0].soma { syn_NC_DA6_MDR11_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR11[0].soma { syn_NC_DA6_MDR11_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0] = new neuron_to_muscle_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DA6_MDR11_Acetylcholine_silent_pre[0].vpeer, a_MDR11[0].soma.v(0.500000)")
h("setpointer syn_NC_DA6_MDR11_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0].vpeer, a_DA6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA6_MDR12_Acetylcholine
print("Adding continuous projection: NC_DA6_MDR12_Acetylcholine from DA6 to MDR12, with 1 connection(s)")
h("objectvar syn_NC_DA6_MDR12_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA6_MDR12_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR12[0].soma], weight: 1.0
h("a_DA6[0].soma { syn_NC_DA6_MDR12_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR12[0].soma { syn_NC_DA6_MDR12_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0] = new neuron_to_muscle_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DA6_MDR12_Acetylcholine_silent_pre[0].vpeer, a_MDR12[0].soma.v(0.500000)")
h("setpointer syn_NC_DA6_MDR12_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0].vpeer, a_DA6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA6_MDR13_Acetylcholine
print("Adding continuous projection: NC_DA6_MDR13_Acetylcholine from DA6 to MDR13, with 1 connection(s)")
h("objectvar syn_NC_DA6_MDR13_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA6_MDR13_Acetylcholine_neuron_to_muscle_exc_syn_5conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR13[0].soma], weight: 1.0
h("a_DA6[0].soma { syn_NC_DA6_MDR13_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR13[0].soma { syn_NC_DA6_MDR13_Acetylcholine_neuron_to_muscle_exc_syn_5conns_post[0] = new neuron_to_muscle_exc_syn_5conns(0.500000) }")
h("setpointer syn_NC_DA6_MDR13_Acetylcholine_silent_pre[0].vpeer, a_MDR13[0].soma.v(0.500000)")
h("setpointer syn_NC_DA6_MDR13_Acetylcholine_neuron_to_muscle_exc_syn_5conns_post[0].vpeer, a_DA6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA6_MDR14_Acetylcholine
print("Adding continuous projection: NC_DA6_MDR14_Acetylcholine from DA6 to MDR14, with 1 connection(s)")
h("objectvar syn_NC_DA6_MDR14_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA6_MDR14_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR14[0].soma], weight: 1.0
h("a_DA6[0].soma { syn_NC_DA6_MDR14_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR14[0].soma { syn_NC_DA6_MDR14_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0] = new neuron_to_muscle_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_DA6_MDR14_Acetylcholine_silent_pre[0].vpeer, a_MDR14[0].soma.v(0.500000)")
h("setpointer syn_NC_DA6_MDR14_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0].vpeer, a_DA6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA6_MDR15_Acetylcholine
print("Adding continuous projection: NC_DA6_MDR15_Acetylcholine from DA6 to MDR15, with 1 connection(s)")
h("objectvar syn_NC_DA6_MDR15_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA6_MDR15_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR15[0].soma], weight: 1.0
h("a_DA6[0].soma { syn_NC_DA6_MDR15_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR15[0].soma { syn_NC_DA6_MDR15_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0] = new neuron_to_muscle_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_DA6_MDR15_Acetylcholine_silent_pre[0].vpeer, a_MDR15[0].soma.v(0.500000)")
h("setpointer syn_NC_DA6_MDR15_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0].vpeer, a_DA6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA6_MDR16_Acetylcholine
print("Adding continuous projection: NC_DA6_MDR16_Acetylcholine from DA6 to MDR16, with 1 connection(s)")
h("objectvar syn_NC_DA6_MDR16_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA6_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR16[0].soma], weight: 1.0
h("a_DA6[0].soma { syn_NC_DA6_MDR16_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR16[0].soma { syn_NC_DA6_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0] = new neuron_to_muscle_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_DA6_MDR16_Acetylcholine_silent_pre[0].vpeer, a_MDR16[0].soma.v(0.500000)")
h("setpointer syn_NC_DA6_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0].vpeer, a_DA6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA7_MDL14_Acetylcholine
print("Adding continuous projection: NC_DA7_MDL14_Acetylcholine from DA7 to MDL14, with 1 connection(s)")
h("objectvar syn_NC_DA7_MDL14_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA7_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL14[0].soma], weight: 1.0
h("a_DA7[0].soma { syn_NC_DA7_MDL14_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL14[0].soma { syn_NC_DA7_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA7_MDL14_Acetylcholine_silent_pre[0].vpeer, a_MDL14[0].soma.v(0.500000)")
h("setpointer syn_NC_DA7_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA7_MDL15_Acetylcholine
print("Adding continuous projection: NC_DA7_MDL15_Acetylcholine from DA7 to MDL15, with 1 connection(s)")
h("objectvar syn_NC_DA7_MDL15_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA7_MDL15_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL15[0].soma], weight: 1.0
h("a_DA7[0].soma { syn_NC_DA7_MDL15_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL15[0].soma { syn_NC_DA7_MDL15_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA7_MDL15_Acetylcholine_silent_pre[0].vpeer, a_MDL15[0].soma.v(0.500000)")
h("setpointer syn_NC_DA7_MDL15_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA7_MDL16_Acetylcholine
print("Adding continuous projection: NC_DA7_MDL16_Acetylcholine from DA7 to MDL16, with 1 connection(s)")
h("objectvar syn_NC_DA7_MDL16_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA7_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL16[0].soma], weight: 1.0
h("a_DA7[0].soma { syn_NC_DA7_MDL16_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL16[0].soma { syn_NC_DA7_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA7_MDL16_Acetylcholine_silent_pre[0].vpeer, a_MDL16[0].soma.v(0.500000)")
h("setpointer syn_NC_DA7_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA7_MDL17_Acetylcholine
print("Adding continuous projection: NC_DA7_MDL17_Acetylcholine from DA7 to MDL17, with 1 connection(s)")
h("objectvar syn_NC_DA7_MDL17_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA7_MDL17_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL17[0].soma], weight: 1.0
h("a_DA7[0].soma { syn_NC_DA7_MDL17_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL17[0].soma { syn_NC_DA7_MDL17_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA7_MDL17_Acetylcholine_silent_pre[0].vpeer, a_MDL17[0].soma.v(0.500000)")
h("setpointer syn_NC_DA7_MDL17_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA7_MDL18_Acetylcholine
print("Adding continuous projection: NC_DA7_MDL18_Acetylcholine from DA7 to MDL18, with 1 connection(s)")
h("objectvar syn_NC_DA7_MDL18_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA7_MDL18_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL18[0].soma], weight: 1.0
h("a_DA7[0].soma { syn_NC_DA7_MDL18_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL18[0].soma { syn_NC_DA7_MDL18_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0] = new neuron_to_muscle_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_DA7_MDL18_Acetylcholine_silent_pre[0].vpeer, a_MDL18[0].soma.v(0.500000)")
h("setpointer syn_NC_DA7_MDL18_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0].vpeer, a_DA7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA7_MDL19_Acetylcholine
print("Adding continuous projection: NC_DA7_MDL19_Acetylcholine from DA7 to MDL19, with 1 connection(s)")
h("objectvar syn_NC_DA7_MDL19_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA7_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL19[0].soma], weight: 1.0
h("a_DA7[0].soma { syn_NC_DA7_MDL19_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL19[0].soma { syn_NC_DA7_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA7_MDL19_Acetylcholine_silent_pre[0].vpeer, a_MDL19[0].soma.v(0.500000)")
h("setpointer syn_NC_DA7_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA7_MDR14_Acetylcholine
print("Adding continuous projection: NC_DA7_MDR14_Acetylcholine from DA7 to MDR14, with 1 connection(s)")
h("objectvar syn_NC_DA7_MDR14_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA7_MDR14_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR14[0].soma], weight: 1.0
h("a_DA7[0].soma { syn_NC_DA7_MDR14_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR14[0].soma { syn_NC_DA7_MDR14_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA7_MDR14_Acetylcholine_silent_pre[0].vpeer, a_MDR14[0].soma.v(0.500000)")
h("setpointer syn_NC_DA7_MDR14_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA7_MDR15_Acetylcholine
print("Adding continuous projection: NC_DA7_MDR15_Acetylcholine from DA7 to MDR15, with 1 connection(s)")
h("objectvar syn_NC_DA7_MDR15_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA7_MDR15_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR15[0].soma], weight: 1.0
h("a_DA7[0].soma { syn_NC_DA7_MDR15_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR15[0].soma { syn_NC_DA7_MDR15_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA7_MDR15_Acetylcholine_silent_pre[0].vpeer, a_MDR15[0].soma.v(0.500000)")
h("setpointer syn_NC_DA7_MDR15_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA7_MDR16_Acetylcholine
print("Adding continuous projection: NC_DA7_MDR16_Acetylcholine from DA7 to MDR16, with 1 connection(s)")
h("objectvar syn_NC_DA7_MDR16_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA7_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR16[0].soma], weight: 1.0
h("a_DA7[0].soma { syn_NC_DA7_MDR16_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR16[0].soma { syn_NC_DA7_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA7_MDR16_Acetylcholine_silent_pre[0].vpeer, a_MDR16[0].soma.v(0.500000)")
h("setpointer syn_NC_DA7_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA7_MDR17_Acetylcholine
print("Adding continuous projection: NC_DA7_MDR17_Acetylcholine from DA7 to MDR17, with 1 connection(s)")
h("objectvar syn_NC_DA7_MDR17_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA7_MDR17_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR17[0].soma], weight: 1.0
h("a_DA7[0].soma { syn_NC_DA7_MDR17_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR17[0].soma { syn_NC_DA7_MDR17_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA7_MDR17_Acetylcholine_silent_pre[0].vpeer, a_MDR17[0].soma.v(0.500000)")
h("setpointer syn_NC_DA7_MDR17_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA7_MDR18_Acetylcholine
print("Adding continuous projection: NC_DA7_MDR18_Acetylcholine from DA7 to MDR18, with 1 connection(s)")
h("objectvar syn_NC_DA7_MDR18_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA7_MDR18_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR18[0].soma], weight: 1.0
h("a_DA7[0].soma { syn_NC_DA7_MDR18_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR18[0].soma { syn_NC_DA7_MDR18_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0] = new neuron_to_muscle_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_DA7_MDR18_Acetylcholine_silent_pre[0].vpeer, a_MDR18[0].soma.v(0.500000)")
h("setpointer syn_NC_DA7_MDR18_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0].vpeer, a_DA7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA7_MDR19_Acetylcholine
print("Adding continuous projection: NC_DA7_MDR19_Acetylcholine from DA7 to MDR19, with 1 connection(s)")
h("objectvar syn_NC_DA7_MDR19_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA7_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR19[0].soma], weight: 1.0
h("a_DA7[0].soma { syn_NC_DA7_MDR19_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR19[0].soma { syn_NC_DA7_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA7_MDR19_Acetylcholine_silent_pre[0].vpeer, a_MDR19[0].soma.v(0.500000)")
h("setpointer syn_NC_DA7_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA8_MDL16_Acetylcholine
print("Adding continuous projection: NC_DA8_MDL16_Acetylcholine from DA8 to MDL16, with 1 connection(s)")
h("objectvar syn_NC_DA8_MDL16_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA8_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL16[0].soma], weight: 1.0
h("a_DA8[0].soma { syn_NC_DA8_MDL16_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL16[0].soma { syn_NC_DA8_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA8_MDL16_Acetylcholine_silent_pre[0].vpeer, a_MDL16[0].soma.v(0.500000)")
h("setpointer syn_NC_DA8_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA8[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA8_MDL17_Acetylcholine
print("Adding continuous projection: NC_DA8_MDL17_Acetylcholine from DA8 to MDL17, with 1 connection(s)")
h("objectvar syn_NC_DA8_MDL17_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA8_MDL17_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL17[0].soma], weight: 1.0
h("a_DA8[0].soma { syn_NC_DA8_MDL17_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL17[0].soma { syn_NC_DA8_MDL17_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA8_MDL17_Acetylcholine_silent_pre[0].vpeer, a_MDL17[0].soma.v(0.500000)")
h("setpointer syn_NC_DA8_MDL17_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA8[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA8_MDL18_Acetylcholine
print("Adding continuous projection: NC_DA8_MDL18_Acetylcholine from DA8 to MDL18, with 1 connection(s)")
h("objectvar syn_NC_DA8_MDL18_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA8_MDL18_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL18[0].soma], weight: 1.0
h("a_DA8[0].soma { syn_NC_DA8_MDL18_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL18[0].soma { syn_NC_DA8_MDL18_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA8_MDL18_Acetylcholine_silent_pre[0].vpeer, a_MDL18[0].soma.v(0.500000)")
h("setpointer syn_NC_DA8_MDL18_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA8[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA8_MDL19_Acetylcholine
print("Adding continuous projection: NC_DA8_MDL19_Acetylcholine from DA8 to MDL19, with 1 connection(s)")
h("objectvar syn_NC_DA8_MDL19_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA8_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL19[0].soma], weight: 1.0
h("a_DA8[0].soma { syn_NC_DA8_MDL19_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL19[0].soma { syn_NC_DA8_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA8_MDL19_Acetylcholine_silent_pre[0].vpeer, a_MDL19[0].soma.v(0.500000)")
h("setpointer syn_NC_DA8_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA8[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA8_MDL20_Acetylcholine
print("Adding continuous projection: NC_DA8_MDL20_Acetylcholine from DA8 to MDL20, with 1 connection(s)")
h("objectvar syn_NC_DA8_MDL20_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA8_MDL20_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL20[0].soma], weight: 1.0
h("a_DA8[0].soma { syn_NC_DA8_MDL20_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL20[0].soma { syn_NC_DA8_MDL20_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0] = new neuron_to_muscle_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_DA8_MDL20_Acetylcholine_silent_pre[0].vpeer, a_MDL20[0].soma.v(0.500000)")
h("setpointer syn_NC_DA8_MDL20_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0].vpeer, a_DA8[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA8_MDL21_Acetylcholine
print("Adding continuous projection: NC_DA8_MDL21_Acetylcholine from DA8 to MDL21, with 1 connection(s)")
h("objectvar syn_NC_DA8_MDL21_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA8_MDL21_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL21[0].soma], weight: 1.0
h("a_DA8[0].soma { syn_NC_DA8_MDL21_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL21[0].soma { syn_NC_DA8_MDL21_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA8_MDL21_Acetylcholine_silent_pre[0].vpeer, a_MDL21[0].soma.v(0.500000)")
h("setpointer syn_NC_DA8_MDL21_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA8[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA8_MDR16_Acetylcholine
print("Adding continuous projection: NC_DA8_MDR16_Acetylcholine from DA8 to MDR16, with 1 connection(s)")
h("objectvar syn_NC_DA8_MDR16_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA8_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR16[0].soma], weight: 1.0
h("a_DA8[0].soma { syn_NC_DA8_MDR16_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR16[0].soma { syn_NC_DA8_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA8_MDR16_Acetylcholine_silent_pre[0].vpeer, a_MDR16[0].soma.v(0.500000)")
h("setpointer syn_NC_DA8_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA8[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA8_MDR17_Acetylcholine
print("Adding continuous projection: NC_DA8_MDR17_Acetylcholine from DA8 to MDR17, with 1 connection(s)")
h("objectvar syn_NC_DA8_MDR17_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA8_MDR17_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR17[0].soma], weight: 1.0
h("a_DA8[0].soma { syn_NC_DA8_MDR17_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR17[0].soma { syn_NC_DA8_MDR17_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA8_MDR17_Acetylcholine_silent_pre[0].vpeer, a_MDR17[0].soma.v(0.500000)")
h("setpointer syn_NC_DA8_MDR17_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA8[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA8_MDR18_Acetylcholine
print("Adding continuous projection: NC_DA8_MDR18_Acetylcholine from DA8 to MDR18, with 1 connection(s)")
h("objectvar syn_NC_DA8_MDR18_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA8_MDR18_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR18[0].soma], weight: 1.0
h("a_DA8[0].soma { syn_NC_DA8_MDR18_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR18[0].soma { syn_NC_DA8_MDR18_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA8_MDR18_Acetylcholine_silent_pre[0].vpeer, a_MDR18[0].soma.v(0.500000)")
h("setpointer syn_NC_DA8_MDR18_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA8[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA8_MDR19_Acetylcholine
print("Adding continuous projection: NC_DA8_MDR19_Acetylcholine from DA8 to MDR19, with 1 connection(s)")
h("objectvar syn_NC_DA8_MDR19_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA8_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR19[0].soma], weight: 1.0
h("a_DA8[0].soma { syn_NC_DA8_MDR19_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR19[0].soma { syn_NC_DA8_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA8_MDR19_Acetylcholine_silent_pre[0].vpeer, a_MDR19[0].soma.v(0.500000)")
h("setpointer syn_NC_DA8_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA8[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA8_MDR20_Acetylcholine
print("Adding continuous projection: NC_DA8_MDR20_Acetylcholine from DA8 to MDR20, with 1 connection(s)")
h("objectvar syn_NC_DA8_MDR20_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA8_MDR20_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR20[0].soma], weight: 1.0
h("a_DA8[0].soma { syn_NC_DA8_MDR20_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR20[0].soma { syn_NC_DA8_MDR20_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0] = new neuron_to_muscle_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_DA8_MDR20_Acetylcholine_silent_pre[0].vpeer, a_MDR20[0].soma.v(0.500000)")
h("setpointer syn_NC_DA8_MDR20_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0].vpeer, a_DA8[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA8_MDR21_Acetylcholine
print("Adding continuous projection: NC_DA8_MDR21_Acetylcholine from DA8 to MDR21, with 1 connection(s)")
h("objectvar syn_NC_DA8_MDR21_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA8_MDR21_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA8[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR21[0].soma], weight: 1.0
h("a_DA8[0].soma { syn_NC_DA8_MDR21_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR21[0].soma { syn_NC_DA8_MDR21_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA8_MDR21_Acetylcholine_silent_pre[0].vpeer, a_MDR21[0].soma.v(0.500000)")
h("setpointer syn_NC_DA8_MDR21_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA8[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA9_MDL19_Acetylcholine
print("Adding continuous projection: NC_DA9_MDL19_Acetylcholine from DA9 to MDL19, with 1 connection(s)")
h("objectvar syn_NC_DA9_MDL19_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA9_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL19[0].soma], weight: 1.0
h("a_DA9[0].soma { syn_NC_DA9_MDL19_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL19[0].soma { syn_NC_DA9_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA9_MDL19_Acetylcholine_silent_pre[0].vpeer, a_MDL19[0].soma.v(0.500000)")
h("setpointer syn_NC_DA9_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA9[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA9_MDL20_Acetylcholine
print("Adding continuous projection: NC_DA9_MDL20_Acetylcholine from DA9 to MDL20, with 1 connection(s)")
h("objectvar syn_NC_DA9_MDL20_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA9_MDL20_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL20[0].soma], weight: 1.0
h("a_DA9[0].soma { syn_NC_DA9_MDL20_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL20[0].soma { syn_NC_DA9_MDL20_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA9_MDL20_Acetylcholine_silent_pre[0].vpeer, a_MDL20[0].soma.v(0.500000)")
h("setpointer syn_NC_DA9_MDL20_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA9[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA9_MDL21_Acetylcholine
print("Adding continuous projection: NC_DA9_MDL21_Acetylcholine from DA9 to MDL21, with 1 connection(s)")
h("objectvar syn_NC_DA9_MDL21_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA9_MDL21_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL21[0].soma], weight: 1.0
h("a_DA9[0].soma { syn_NC_DA9_MDL21_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL21[0].soma { syn_NC_DA9_MDL21_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA9_MDL21_Acetylcholine_silent_pre[0].vpeer, a_MDL21[0].soma.v(0.500000)")
h("setpointer syn_NC_DA9_MDL21_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA9[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA9_MDL22_Acetylcholine
print("Adding continuous projection: NC_DA9_MDL22_Acetylcholine from DA9 to MDL22, with 1 connection(s)")
h("objectvar syn_NC_DA9_MDL22_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA9_MDL22_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL22[0].soma], weight: 1.0
h("a_DA9[0].soma { syn_NC_DA9_MDL22_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL22[0].soma { syn_NC_DA9_MDL22_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA9_MDL22_Acetylcholine_silent_pre[0].vpeer, a_MDL22[0].soma.v(0.500000)")
h("setpointer syn_NC_DA9_MDL22_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA9[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA9_MDL23_Acetylcholine
print("Adding continuous projection: NC_DA9_MDL23_Acetylcholine from DA9 to MDL23, with 1 connection(s)")
h("objectvar syn_NC_DA9_MDL23_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA9_MDL23_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL23[0].soma], weight: 1.0
h("a_DA9[0].soma { syn_NC_DA9_MDL23_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL23[0].soma { syn_NC_DA9_MDL23_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA9_MDL23_Acetylcholine_silent_pre[0].vpeer, a_MDL23[0].soma.v(0.500000)")
h("setpointer syn_NC_DA9_MDL23_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA9[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA9_MDL24_Acetylcholine
print("Adding continuous projection: NC_DA9_MDL24_Acetylcholine from DA9 to MDL24, with 1 connection(s)")
h("objectvar syn_NC_DA9_MDL24_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA9_MDL24_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL24[0].soma], weight: 1.0
h("a_DA9[0].soma { syn_NC_DA9_MDL24_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL24[0].soma { syn_NC_DA9_MDL24_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0] = new neuron_to_muscle_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_DA9_MDL24_Acetylcholine_silent_pre[0].vpeer, a_MDL24[0].soma.v(0.500000)")
h("setpointer syn_NC_DA9_MDL24_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0].vpeer, a_DA9[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA9_MDR19_Acetylcholine
print("Adding continuous projection: NC_DA9_MDR19_Acetylcholine from DA9 to MDR19, with 1 connection(s)")
h("objectvar syn_NC_DA9_MDR19_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA9_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR19[0].soma], weight: 1.0
h("a_DA9[0].soma { syn_NC_DA9_MDR19_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR19[0].soma { syn_NC_DA9_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA9_MDR19_Acetylcholine_silent_pre[0].vpeer, a_MDR19[0].soma.v(0.500000)")
h("setpointer syn_NC_DA9_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA9[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA9_MDR20_Acetylcholine
print("Adding continuous projection: NC_DA9_MDR20_Acetylcholine from DA9 to MDR20, with 1 connection(s)")
h("objectvar syn_NC_DA9_MDR20_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA9_MDR20_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR20[0].soma], weight: 1.0
h("a_DA9[0].soma { syn_NC_DA9_MDR20_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR20[0].soma { syn_NC_DA9_MDR20_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA9_MDR20_Acetylcholine_silent_pre[0].vpeer, a_MDR20[0].soma.v(0.500000)")
h("setpointer syn_NC_DA9_MDR20_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA9[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA9_MDR21_Acetylcholine
print("Adding continuous projection: NC_DA9_MDR21_Acetylcholine from DA9 to MDR21, with 1 connection(s)")
h("objectvar syn_NC_DA9_MDR21_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA9_MDR21_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR21[0].soma], weight: 1.0
h("a_DA9[0].soma { syn_NC_DA9_MDR21_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR21[0].soma { syn_NC_DA9_MDR21_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA9_MDR21_Acetylcholine_silent_pre[0].vpeer, a_MDR21[0].soma.v(0.500000)")
h("setpointer syn_NC_DA9_MDR21_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA9[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA9_MDR22_Acetylcholine
print("Adding continuous projection: NC_DA9_MDR22_Acetylcholine from DA9 to MDR22, with 1 connection(s)")
h("objectvar syn_NC_DA9_MDR22_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA9_MDR22_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR22[0].soma], weight: 1.0
h("a_DA9[0].soma { syn_NC_DA9_MDR22_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR22[0].soma { syn_NC_DA9_MDR22_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA9_MDR22_Acetylcholine_silent_pre[0].vpeer, a_MDR22[0].soma.v(0.500000)")
h("setpointer syn_NC_DA9_MDR22_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA9[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA9_MDR23_Acetylcholine
print("Adding continuous projection: NC_DA9_MDR23_Acetylcholine from DA9 to MDR23, with 1 connection(s)")
h("objectvar syn_NC_DA9_MDR23_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA9_MDR23_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR23[0].soma], weight: 1.0
h("a_DA9[0].soma { syn_NC_DA9_MDR23_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR23[0].soma { syn_NC_DA9_MDR23_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DA9_MDR23_Acetylcholine_silent_pre[0].vpeer, a_MDR23[0].soma.v(0.500000)")
h("setpointer syn_NC_DA9_MDR23_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DA9[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DA9_MDR24_Acetylcholine
print("Adding continuous projection: NC_DA9_MDR24_Acetylcholine from DA9 to MDR24, with 1 connection(s)")
h("objectvar syn_NC_DA9_MDR24_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DA9_MDR24_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DA9[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR24[0].soma], weight: 1.0
h("a_DA9[0].soma { syn_NC_DA9_MDR24_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR24[0].soma { syn_NC_DA9_MDR24_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0] = new neuron_to_muscle_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_DA9_MDR24_Acetylcholine_silent_pre[0].vpeer, a_MDR24[0].soma.v(0.500000)")
h("setpointer syn_NC_DA9_MDR24_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0].vpeer, a_DA9[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB1_MDL06_Acetylcholine
print("Adding continuous projection: NC_DB1_MDL06_Acetylcholine from DB1 to MDL06, with 1 connection(s)")
h("objectvar syn_NC_DB1_MDL06_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB1_MDL06_Acetylcholine_DB1_to_MDL06_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB1[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL06[0].soma], weight: 1.0
h("a_DB1[0].soma { syn_NC_DB1_MDL06_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL06[0].soma { syn_NC_DB1_MDL06_Acetylcholine_DB1_to_MDL06_exc_syn_3conns_post[0] = new DB1_to_MDL06_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DB1_MDL06_Acetylcholine_silent_pre[0].vpeer, a_MDL06[0].soma.v(0.500000)")
h("setpointer syn_NC_DB1_MDL06_Acetylcholine_DB1_to_MDL06_exc_syn_3conns_post[0].vpeer, a_DB1[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB1_MDL08_Acetylcholine
print("Adding continuous projection: NC_DB1_MDL08_Acetylcholine from DB1 to MDL08, with 1 connection(s)")
h("objectvar syn_NC_DB1_MDL08_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB1_MDL08_Acetylcholine_DB1_to_MDL08_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB1[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL08[0].soma], weight: 1.0
h("a_DB1[0].soma { syn_NC_DB1_MDL08_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL08[0].soma { syn_NC_DB1_MDL08_Acetylcholine_DB1_to_MDL08_exc_syn_3conns_post[0] = new DB1_to_MDL08_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DB1_MDL08_Acetylcholine_silent_pre[0].vpeer, a_MDL08[0].soma.v(0.500000)")
h("setpointer syn_NC_DB1_MDL08_Acetylcholine_DB1_to_MDL08_exc_syn_3conns_post[0].vpeer, a_DB1[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB1_MDL09_Acetylcholine
print("Adding continuous projection: NC_DB1_MDL09_Acetylcholine from DB1 to MDL09, with 1 connection(s)")
h("objectvar syn_NC_DB1_MDL09_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB1_MDL09_Acetylcholine_DB1_to_MDL09_exc_syn_6conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB1[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL09[0].soma], weight: 1.0
h("a_DB1[0].soma { syn_NC_DB1_MDL09_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL09[0].soma { syn_NC_DB1_MDL09_Acetylcholine_DB1_to_MDL09_exc_syn_6conns_post[0] = new DB1_to_MDL09_exc_syn_6conns(0.500000) }")
h("setpointer syn_NC_DB1_MDL09_Acetylcholine_silent_pre[0].vpeer, a_MDL09[0].soma.v(0.500000)")
h("setpointer syn_NC_DB1_MDL09_Acetylcholine_DB1_to_MDL09_exc_syn_6conns_post[0].vpeer, a_DB1[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB1_MDR08_Acetylcholine
print("Adding continuous projection: NC_DB1_MDR08_Acetylcholine from DB1 to MDR08, with 1 connection(s)")
h("objectvar syn_NC_DB1_MDR08_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB1_MDR08_Acetylcholine_DB1_to_MDR08_exc_syn_6conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB1[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR08[0].soma], weight: 1.0
h("a_DB1[0].soma { syn_NC_DB1_MDR08_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR08[0].soma { syn_NC_DB1_MDR08_Acetylcholine_DB1_to_MDR08_exc_syn_6conns_post[0] = new DB1_to_MDR08_exc_syn_6conns(0.500000) }")
h("setpointer syn_NC_DB1_MDR08_Acetylcholine_silent_pre[0].vpeer, a_MDR08[0].soma.v(0.500000)")
h("setpointer syn_NC_DB1_MDR08_Acetylcholine_DB1_to_MDR08_exc_syn_6conns_post[0].vpeer, a_DB1[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB1_MDR09_Acetylcholine
print("Adding continuous projection: NC_DB1_MDR09_Acetylcholine from DB1 to MDR09, with 1 connection(s)")
h("objectvar syn_NC_DB1_MDR09_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB1_MDR09_Acetylcholine_DB1_to_MDR09_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB1[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR09[0].soma], weight: 1.0
h("a_DB1[0].soma { syn_NC_DB1_MDR09_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR09[0].soma { syn_NC_DB1_MDR09_Acetylcholine_DB1_to_MDR09_exc_syn_2conns_post[0] = new DB1_to_MDR09_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB1_MDR09_Acetylcholine_silent_pre[0].vpeer, a_MDR09[0].soma.v(0.500000)")
h("setpointer syn_NC_DB1_MDR09_Acetylcholine_DB1_to_MDR09_exc_syn_2conns_post[0].vpeer, a_DB1[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB2_MDL09_Acetylcholine
print("Adding continuous projection: NC_DB2_MDL09_Acetylcholine from DB2 to MDL09, with 1 connection(s)")
h("objectvar syn_NC_DB2_MDL09_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB2_MDL09_Acetylcholine_DB2_to_MDL09_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL09[0].soma], weight: 1.0
h("a_DB2[0].soma { syn_NC_DB2_MDL09_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL09[0].soma { syn_NC_DB2_MDL09_Acetylcholine_DB2_to_MDL09_exc_syn_2conns_post[0] = new DB2_to_MDL09_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB2_MDL09_Acetylcholine_silent_pre[0].vpeer, a_MDL09[0].soma.v(0.500000)")
h("setpointer syn_NC_DB2_MDL09_Acetylcholine_DB2_to_MDL09_exc_syn_2conns_post[0].vpeer, a_DB2[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB2_MDL10_Acetylcholine
print("Adding continuous projection: NC_DB2_MDL10_Acetylcholine from DB2 to MDL10, with 1 connection(s)")
h("objectvar syn_NC_DB2_MDL10_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB2_MDL10_Acetylcholine_DB2_to_MDL10_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL10[0].soma], weight: 1.0
h("a_DB2[0].soma { syn_NC_DB2_MDL10_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL10[0].soma { syn_NC_DB2_MDL10_Acetylcholine_DB2_to_MDL10_exc_syn_4conns_post[0] = new DB2_to_MDL10_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_DB2_MDL10_Acetylcholine_silent_pre[0].vpeer, a_MDL10[0].soma.v(0.500000)")
h("setpointer syn_NC_DB2_MDL10_Acetylcholine_DB2_to_MDL10_exc_syn_4conns_post[0].vpeer, a_DB2[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB2_MDL11_Acetylcholine
print("Adding continuous projection: NC_DB2_MDL11_Acetylcholine from DB2 to MDL11, with 1 connection(s)")
h("objectvar syn_NC_DB2_MDL11_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB2_MDL11_Acetylcholine_DB2_to_MDL11_exc_syn_5conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL11[0].soma], weight: 1.0
h("a_DB2[0].soma { syn_NC_DB2_MDL11_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL11[0].soma { syn_NC_DB2_MDL11_Acetylcholine_DB2_to_MDL11_exc_syn_5conns_post[0] = new DB2_to_MDL11_exc_syn_5conns(0.500000) }")
h("setpointer syn_NC_DB2_MDL11_Acetylcholine_silent_pre[0].vpeer, a_MDL11[0].soma.v(0.500000)")
h("setpointer syn_NC_DB2_MDL11_Acetylcholine_DB2_to_MDL11_exc_syn_5conns_post[0].vpeer, a_DB2[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB2_MDL12_Acetylcholine
print("Adding continuous projection: NC_DB2_MDL12_Acetylcholine from DB2 to MDL12, with 1 connection(s)")
h("objectvar syn_NC_DB2_MDL12_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB2_MDL12_Acetylcholine_DB2_to_MDL12_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL12[0].soma], weight: 1.0
h("a_DB2[0].soma { syn_NC_DB2_MDL12_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL12[0].soma { syn_NC_DB2_MDL12_Acetylcholine_DB2_to_MDL12_exc_syn_1conns_post[0] = new DB2_to_MDL12_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DB2_MDL12_Acetylcholine_silent_pre[0].vpeer, a_MDL12[0].soma.v(0.500000)")
h("setpointer syn_NC_DB2_MDL12_Acetylcholine_DB2_to_MDL12_exc_syn_1conns_post[0].vpeer, a_DB2[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB2_MDR09_Acetylcholine
print("Adding continuous projection: NC_DB2_MDR09_Acetylcholine from DB2 to MDR09, with 1 connection(s)")
h("objectvar syn_NC_DB2_MDR09_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB2_MDR09_Acetylcholine_DB2_to_MDR09_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR09[0].soma], weight: 1.0
h("a_DB2[0].soma { syn_NC_DB2_MDR09_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR09[0].soma { syn_NC_DB2_MDR09_Acetylcholine_DB2_to_MDR09_exc_syn_1conns_post[0] = new DB2_to_MDR09_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DB2_MDR09_Acetylcholine_silent_pre[0].vpeer, a_MDR09[0].soma.v(0.500000)")
h("setpointer syn_NC_DB2_MDR09_Acetylcholine_DB2_to_MDR09_exc_syn_1conns_post[0].vpeer, a_DB2[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB2_MDR10_Acetylcholine
print("Adding continuous projection: NC_DB2_MDR10_Acetylcholine from DB2 to MDR10, with 1 connection(s)")
h("objectvar syn_NC_DB2_MDR10_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB2_MDR10_Acetylcholine_DB2_to_MDR10_exc_syn_6conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR10[0].soma], weight: 1.0
h("a_DB2[0].soma { syn_NC_DB2_MDR10_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR10[0].soma { syn_NC_DB2_MDR10_Acetylcholine_DB2_to_MDR10_exc_syn_6conns_post[0] = new DB2_to_MDR10_exc_syn_6conns(0.500000) }")
h("setpointer syn_NC_DB2_MDR10_Acetylcholine_silent_pre[0].vpeer, a_MDR10[0].soma.v(0.500000)")
h("setpointer syn_NC_DB2_MDR10_Acetylcholine_DB2_to_MDR10_exc_syn_6conns_post[0].vpeer, a_DB2[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB2_MDR11_Acetylcholine
print("Adding continuous projection: NC_DB2_MDR11_Acetylcholine from DB2 to MDR11, with 1 connection(s)")
h("objectvar syn_NC_DB2_MDR11_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB2_MDR11_Acetylcholine_DB2_to_MDR11_exc_syn_8conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB2[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR11[0].soma], weight: 1.0
h("a_DB2[0].soma { syn_NC_DB2_MDR11_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR11[0].soma { syn_NC_DB2_MDR11_Acetylcholine_DB2_to_MDR11_exc_syn_8conns_post[0] = new DB2_to_MDR11_exc_syn_8conns(0.500000) }")
h("setpointer syn_NC_DB2_MDR11_Acetylcholine_silent_pre[0].vpeer, a_MDR11[0].soma.v(0.500000)")
h("setpointer syn_NC_DB2_MDR11_Acetylcholine_DB2_to_MDR11_exc_syn_8conns_post[0].vpeer, a_DB2[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB3_MDL11_Acetylcholine
print("Adding continuous projection: NC_DB3_MDL11_Acetylcholine from DB3 to MDL11, with 1 connection(s)")
h("objectvar syn_NC_DB3_MDL11_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB3_MDL11_Acetylcholine_neuron_to_muscle_exc_syn_6conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL11[0].soma], weight: 1.0
h("a_DB3[0].soma { syn_NC_DB3_MDL11_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL11[0].soma { syn_NC_DB3_MDL11_Acetylcholine_neuron_to_muscle_exc_syn_6conns_post[0] = new neuron_to_muscle_exc_syn_6conns(0.500000) }")
h("setpointer syn_NC_DB3_MDL11_Acetylcholine_silent_pre[0].vpeer, a_MDL11[0].soma.v(0.500000)")
h("setpointer syn_NC_DB3_MDL11_Acetylcholine_neuron_to_muscle_exc_syn_6conns_post[0].vpeer, a_DB3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB3_MDL12_Acetylcholine
print("Adding continuous projection: NC_DB3_MDL12_Acetylcholine from DB3 to MDL12, with 1 connection(s)")
h("objectvar syn_NC_DB3_MDL12_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB3_MDL12_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL12[0].soma], weight: 1.0
h("a_DB3[0].soma { syn_NC_DB3_MDL12_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL12[0].soma { syn_NC_DB3_MDL12_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0] = new neuron_to_muscle_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DB3_MDL12_Acetylcholine_silent_pre[0].vpeer, a_MDL12[0].soma.v(0.500000)")
h("setpointer syn_NC_DB3_MDL12_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0].vpeer, a_DB3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB3_MDL13_Acetylcholine
print("Adding continuous projection: NC_DB3_MDL13_Acetylcholine from DB3 to MDL13, with 1 connection(s)")
h("objectvar syn_NC_DB3_MDL13_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB3_MDL13_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL13[0].soma], weight: 1.0
h("a_DB3[0].soma { syn_NC_DB3_MDL13_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL13[0].soma { syn_NC_DB3_MDL13_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DB3_MDL13_Acetylcholine_silent_pre[0].vpeer, a_MDL13[0].soma.v(0.500000)")
h("setpointer syn_NC_DB3_MDL13_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DB3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB3_MDL14_Acetylcholine
print("Adding continuous projection: NC_DB3_MDL14_Acetylcholine from DB3 to MDL14, with 1 connection(s)")
h("objectvar syn_NC_DB3_MDL14_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB3_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL14[0].soma], weight: 1.0
h("a_DB3[0].soma { syn_NC_DB3_MDL14_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL14[0].soma { syn_NC_DB3_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0] = new neuron_to_muscle_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DB3_MDL14_Acetylcholine_silent_pre[0].vpeer, a_MDL14[0].soma.v(0.500000)")
h("setpointer syn_NC_DB3_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0].vpeer, a_DB3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB3_MDR11_Acetylcholine
print("Adding continuous projection: NC_DB3_MDR11_Acetylcholine from DB3 to MDR11, with 1 connection(s)")
h("objectvar syn_NC_DB3_MDR11_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB3_MDR11_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR11[0].soma], weight: 1.0
h("a_DB3[0].soma { syn_NC_DB3_MDR11_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR11[0].soma { syn_NC_DB3_MDR11_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB3_MDR11_Acetylcholine_silent_pre[0].vpeer, a_MDR11[0].soma.v(0.500000)")
h("setpointer syn_NC_DB3_MDR11_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB3_MDR12_Acetylcholine
print("Adding continuous projection: NC_DB3_MDR12_Acetylcholine from DB3 to MDR12, with 1 connection(s)")
h("objectvar syn_NC_DB3_MDR12_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB3_MDR12_Acetylcholine_neuron_to_muscle_exc_syn_13conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR12[0].soma], weight: 1.0
h("a_DB3[0].soma { syn_NC_DB3_MDR12_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR12[0].soma { syn_NC_DB3_MDR12_Acetylcholine_neuron_to_muscle_exc_syn_13conns_post[0] = new neuron_to_muscle_exc_syn_13conns(0.500000) }")
h("setpointer syn_NC_DB3_MDR12_Acetylcholine_silent_pre[0].vpeer, a_MDR12[0].soma.v(0.500000)")
h("setpointer syn_NC_DB3_MDR12_Acetylcholine_neuron_to_muscle_exc_syn_13conns_post[0].vpeer, a_DB3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB3_MDR13_Acetylcholine
print("Adding continuous projection: NC_DB3_MDR13_Acetylcholine from DB3 to MDR13, with 1 connection(s)")
h("objectvar syn_NC_DB3_MDR13_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB3_MDR13_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB3[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR13[0].soma], weight: 1.0
h("a_DB3[0].soma { syn_NC_DB3_MDR13_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR13[0].soma { syn_NC_DB3_MDR13_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0] = new neuron_to_muscle_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DB3_MDR13_Acetylcholine_silent_pre[0].vpeer, a_MDR13[0].soma.v(0.500000)")
h("setpointer syn_NC_DB3_MDR13_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0].vpeer, a_DB3[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB4_MDL13_Acetylcholine
print("Adding continuous projection: NC_DB4_MDL13_Acetylcholine from DB4 to MDL13, with 1 connection(s)")
h("objectvar syn_NC_DB4_MDL13_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB4_MDL13_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL13[0].soma], weight: 1.0
h("a_DB4[0].soma { syn_NC_DB4_MDL13_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL13[0].soma { syn_NC_DB4_MDL13_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0] = new neuron_to_muscle_exc_syn_4conns(0.500000) }")
h("setpointer syn_NC_DB4_MDL13_Acetylcholine_silent_pre[0].vpeer, a_MDL13[0].soma.v(0.500000)")
h("setpointer syn_NC_DB4_MDL13_Acetylcholine_neuron_to_muscle_exc_syn_4conns_post[0].vpeer, a_DB4[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB4_MDL14_Acetylcholine
print("Adding continuous projection: NC_DB4_MDL14_Acetylcholine from DB4 to MDL14, with 1 connection(s)")
h("objectvar syn_NC_DB4_MDL14_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB4_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL14[0].soma], weight: 1.0
h("a_DB4[0].soma { syn_NC_DB4_MDL14_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL14[0].soma { syn_NC_DB4_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0] = new neuron_to_muscle_exc_syn_1conns(0.500000) }")
h("setpointer syn_NC_DB4_MDL14_Acetylcholine_silent_pre[0].vpeer, a_MDL14[0].soma.v(0.500000)")
h("setpointer syn_NC_DB4_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_1conns_post[0].vpeer, a_DB4[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB4_MDL15_Acetylcholine
print("Adding continuous projection: NC_DB4_MDL15_Acetylcholine from DB4 to MDL15, with 1 connection(s)")
h("objectvar syn_NC_DB4_MDL15_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB4_MDL15_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL15[0].soma], weight: 1.0
h("a_DB4[0].soma { syn_NC_DB4_MDL15_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL15[0].soma { syn_NC_DB4_MDL15_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DB4_MDL15_Acetylcholine_silent_pre[0].vpeer, a_MDL15[0].soma.v(0.500000)")
h("setpointer syn_NC_DB4_MDL15_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DB4[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB4_MDL16_Acetylcholine
print("Adding continuous projection: NC_DB4_MDL16_Acetylcholine from DB4 to MDL16, with 1 connection(s)")
h("objectvar syn_NC_DB4_MDL16_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB4_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL16[0].soma], weight: 1.0
h("a_DB4[0].soma { syn_NC_DB4_MDL16_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL16[0].soma { syn_NC_DB4_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DB4_MDL16_Acetylcholine_silent_pre[0].vpeer, a_MDL16[0].soma.v(0.500000)")
h("setpointer syn_NC_DB4_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DB4[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB4_MDR13_Acetylcholine
print("Adding continuous projection: NC_DB4_MDR13_Acetylcholine from DB4 to MDR13, with 1 connection(s)")
h("objectvar syn_NC_DB4_MDR13_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB4_MDR13_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR13[0].soma], weight: 1.0
h("a_DB4[0].soma { syn_NC_DB4_MDR13_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR13[0].soma { syn_NC_DB4_MDR13_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DB4_MDR13_Acetylcholine_silent_pre[0].vpeer, a_MDR13[0].soma.v(0.500000)")
h("setpointer syn_NC_DB4_MDR13_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DB4[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB4_MDR14_Acetylcholine
print("Adding continuous projection: NC_DB4_MDR14_Acetylcholine from DB4 to MDR14, with 1 connection(s)")
h("objectvar syn_NC_DB4_MDR14_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB4_MDR14_Acetylcholine_neuron_to_muscle_exc_syn_5conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR14[0].soma], weight: 1.0
h("a_DB4[0].soma { syn_NC_DB4_MDR14_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR14[0].soma { syn_NC_DB4_MDR14_Acetylcholine_neuron_to_muscle_exc_syn_5conns_post[0] = new neuron_to_muscle_exc_syn_5conns(0.500000) }")
h("setpointer syn_NC_DB4_MDR14_Acetylcholine_silent_pre[0].vpeer, a_MDR14[0].soma.v(0.500000)")
h("setpointer syn_NC_DB4_MDR14_Acetylcholine_neuron_to_muscle_exc_syn_5conns_post[0].vpeer, a_DB4[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB4_MDR15_Acetylcholine
print("Adding continuous projection: NC_DB4_MDR15_Acetylcholine from DB4 to MDR15, with 1 connection(s)")
h("objectvar syn_NC_DB4_MDR15_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB4_MDR15_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR15[0].soma], weight: 1.0
h("a_DB4[0].soma { syn_NC_DB4_MDR15_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR15[0].soma { syn_NC_DB4_MDR15_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DB4_MDR15_Acetylcholine_silent_pre[0].vpeer, a_MDR15[0].soma.v(0.500000)")
h("setpointer syn_NC_DB4_MDR15_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DB4[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB4_MDR16_Acetylcholine
print("Adding continuous projection: NC_DB4_MDR16_Acetylcholine from DB4 to MDR16, with 1 connection(s)")
h("objectvar syn_NC_DB4_MDR16_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB4_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB4[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR16[0].soma], weight: 1.0
h("a_DB4[0].soma { syn_NC_DB4_MDR16_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR16[0].soma { syn_NC_DB4_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0] = new neuron_to_muscle_exc_syn_3conns(0.500000) }")
h("setpointer syn_NC_DB4_MDR16_Acetylcholine_silent_pre[0].vpeer, a_MDR16[0].soma.v(0.500000)")
h("setpointer syn_NC_DB4_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_3conns_post[0].vpeer, a_DB4[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB5_MDL14_Acetylcholine
print("Adding continuous projection: NC_DB5_MDL14_Acetylcholine from DB5 to MDL14, with 1 connection(s)")
h("objectvar syn_NC_DB5_MDL14_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB5_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL14[0].soma], weight: 1.0
h("a_DB5[0].soma { syn_NC_DB5_MDL14_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL14[0].soma { syn_NC_DB5_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB5_MDL14_Acetylcholine_silent_pre[0].vpeer, a_MDL14[0].soma.v(0.500000)")
h("setpointer syn_NC_DB5_MDL14_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB5_MDL15_Acetylcholine
print("Adding continuous projection: NC_DB5_MDL15_Acetylcholine from DB5 to MDL15, with 1 connection(s)")
h("objectvar syn_NC_DB5_MDL15_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB5_MDL15_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL15[0].soma], weight: 1.0
h("a_DB5[0].soma { syn_NC_DB5_MDL15_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL15[0].soma { syn_NC_DB5_MDL15_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB5_MDL15_Acetylcholine_silent_pre[0].vpeer, a_MDL15[0].soma.v(0.500000)")
h("setpointer syn_NC_DB5_MDL15_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB5_MDL16_Acetylcholine
print("Adding continuous projection: NC_DB5_MDL16_Acetylcholine from DB5 to MDL16, with 1 connection(s)")
h("objectvar syn_NC_DB5_MDL16_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB5_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL16[0].soma], weight: 1.0
h("a_DB5[0].soma { syn_NC_DB5_MDL16_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL16[0].soma { syn_NC_DB5_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB5_MDL16_Acetylcholine_silent_pre[0].vpeer, a_MDL16[0].soma.v(0.500000)")
h("setpointer syn_NC_DB5_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB5_MDL17_Acetylcholine
print("Adding continuous projection: NC_DB5_MDL17_Acetylcholine from DB5 to MDL17, with 1 connection(s)")
h("objectvar syn_NC_DB5_MDL17_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB5_MDL17_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL17[0].soma], weight: 1.0
h("a_DB5[0].soma { syn_NC_DB5_MDL17_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL17[0].soma { syn_NC_DB5_MDL17_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB5_MDL17_Acetylcholine_silent_pre[0].vpeer, a_MDL17[0].soma.v(0.500000)")
h("setpointer syn_NC_DB5_MDL17_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB5_MDL18_Acetylcholine
print("Adding continuous projection: NC_DB5_MDL18_Acetylcholine from DB5 to MDL18, with 1 connection(s)")
h("objectvar syn_NC_DB5_MDL18_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB5_MDL18_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL18[0].soma], weight: 1.0
h("a_DB5[0].soma { syn_NC_DB5_MDL18_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL18[0].soma { syn_NC_DB5_MDL18_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB5_MDL18_Acetylcholine_silent_pre[0].vpeer, a_MDL18[0].soma.v(0.500000)")
h("setpointer syn_NC_DB5_MDL18_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB5_MDL19_Acetylcholine
print("Adding continuous projection: NC_DB5_MDL19_Acetylcholine from DB5 to MDL19, with 1 connection(s)")
h("objectvar syn_NC_DB5_MDL19_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB5_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL19[0].soma], weight: 1.0
h("a_DB5[0].soma { syn_NC_DB5_MDL19_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL19[0].soma { syn_NC_DB5_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB5_MDL19_Acetylcholine_silent_pre[0].vpeer, a_MDL19[0].soma.v(0.500000)")
h("setpointer syn_NC_DB5_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB5_MDR14_Acetylcholine
print("Adding continuous projection: NC_DB5_MDR14_Acetylcholine from DB5 to MDR14, with 1 connection(s)")
h("objectvar syn_NC_DB5_MDR14_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB5_MDR14_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR14[0].soma], weight: 1.0
h("a_DB5[0].soma { syn_NC_DB5_MDR14_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR14[0].soma { syn_NC_DB5_MDR14_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB5_MDR14_Acetylcholine_silent_pre[0].vpeer, a_MDR14[0].soma.v(0.500000)")
h("setpointer syn_NC_DB5_MDR14_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB5_MDR15_Acetylcholine
print("Adding continuous projection: NC_DB5_MDR15_Acetylcholine from DB5 to MDR15, with 1 connection(s)")
h("objectvar syn_NC_DB5_MDR15_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB5_MDR15_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR15[0].soma], weight: 1.0
h("a_DB5[0].soma { syn_NC_DB5_MDR15_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR15[0].soma { syn_NC_DB5_MDR15_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB5_MDR15_Acetylcholine_silent_pre[0].vpeer, a_MDR15[0].soma.v(0.500000)")
h("setpointer syn_NC_DB5_MDR15_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB5_MDR16_Acetylcholine
print("Adding continuous projection: NC_DB5_MDR16_Acetylcholine from DB5 to MDR16, with 1 connection(s)")
h("objectvar syn_NC_DB5_MDR16_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB5_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR16[0].soma], weight: 1.0
h("a_DB5[0].soma { syn_NC_DB5_MDR16_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR16[0].soma { syn_NC_DB5_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB5_MDR16_Acetylcholine_silent_pre[0].vpeer, a_MDR16[0].soma.v(0.500000)")
h("setpointer syn_NC_DB5_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB5_MDR17_Acetylcholine
print("Adding continuous projection: NC_DB5_MDR17_Acetylcholine from DB5 to MDR17, with 1 connection(s)")
h("objectvar syn_NC_DB5_MDR17_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB5_MDR17_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR17[0].soma], weight: 1.0
h("a_DB5[0].soma { syn_NC_DB5_MDR17_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR17[0].soma { syn_NC_DB5_MDR17_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB5_MDR17_Acetylcholine_silent_pre[0].vpeer, a_MDR17[0].soma.v(0.500000)")
h("setpointer syn_NC_DB5_MDR17_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB5_MDR18_Acetylcholine
print("Adding continuous projection: NC_DB5_MDR18_Acetylcholine from DB5 to MDR18, with 1 connection(s)")
h("objectvar syn_NC_DB5_MDR18_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB5_MDR18_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR18[0].soma], weight: 1.0
h("a_DB5[0].soma { syn_NC_DB5_MDR18_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR18[0].soma { syn_NC_DB5_MDR18_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB5_MDR18_Acetylcholine_silent_pre[0].vpeer, a_MDR18[0].soma.v(0.500000)")
h("setpointer syn_NC_DB5_MDR18_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB5_MDR19_Acetylcholine
print("Adding continuous projection: NC_DB5_MDR19_Acetylcholine from DB5 to MDR19, with 1 connection(s)")
h("objectvar syn_NC_DB5_MDR19_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB5_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB5[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR19[0].soma], weight: 1.0
h("a_DB5[0].soma { syn_NC_DB5_MDR19_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR19[0].soma { syn_NC_DB5_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB5_MDR19_Acetylcholine_silent_pre[0].vpeer, a_MDR19[0].soma.v(0.500000)")
h("setpointer syn_NC_DB5_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB5[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB6_MDL16_Acetylcholine
print("Adding continuous projection: NC_DB6_MDL16_Acetylcholine from DB6 to MDL16, with 1 connection(s)")
h("objectvar syn_NC_DB6_MDL16_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB6_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL16[0].soma], weight: 1.0
h("a_DB6[0].soma { syn_NC_DB6_MDL16_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL16[0].soma { syn_NC_DB6_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB6_MDL16_Acetylcholine_silent_pre[0].vpeer, a_MDL16[0].soma.v(0.500000)")
h("setpointer syn_NC_DB6_MDL16_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB6_MDL17_Acetylcholine
print("Adding continuous projection: NC_DB6_MDL17_Acetylcholine from DB6 to MDL17, with 1 connection(s)")
h("objectvar syn_NC_DB6_MDL17_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB6_MDL17_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL17[0].soma], weight: 1.0
h("a_DB6[0].soma { syn_NC_DB6_MDL17_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL17[0].soma { syn_NC_DB6_MDL17_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB6_MDL17_Acetylcholine_silent_pre[0].vpeer, a_MDL17[0].soma.v(0.500000)")
h("setpointer syn_NC_DB6_MDL17_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB6_MDL18_Acetylcholine
print("Adding continuous projection: NC_DB6_MDL18_Acetylcholine from DB6 to MDL18, with 1 connection(s)")
h("objectvar syn_NC_DB6_MDL18_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB6_MDL18_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL18[0].soma], weight: 1.0
h("a_DB6[0].soma { syn_NC_DB6_MDL18_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL18[0].soma { syn_NC_DB6_MDL18_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB6_MDL18_Acetylcholine_silent_pre[0].vpeer, a_MDL18[0].soma.v(0.500000)")
h("setpointer syn_NC_DB6_MDL18_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB6_MDL19_Acetylcholine
print("Adding continuous projection: NC_DB6_MDL19_Acetylcholine from DB6 to MDL19, with 1 connection(s)")
h("objectvar syn_NC_DB6_MDL19_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB6_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL19[0].soma], weight: 1.0
h("a_DB6[0].soma { syn_NC_DB6_MDL19_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL19[0].soma { syn_NC_DB6_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB6_MDL19_Acetylcholine_silent_pre[0].vpeer, a_MDL19[0].soma.v(0.500000)")
h("setpointer syn_NC_DB6_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB6_MDL20_Acetylcholine
print("Adding continuous projection: NC_DB6_MDL20_Acetylcholine from DB6 to MDL20, with 1 connection(s)")
h("objectvar syn_NC_DB6_MDL20_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB6_MDL20_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL20[0].soma], weight: 1.0
h("a_DB6[0].soma { syn_NC_DB6_MDL20_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL20[0].soma { syn_NC_DB6_MDL20_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB6_MDL20_Acetylcholine_silent_pre[0].vpeer, a_MDL20[0].soma.v(0.500000)")
h("setpointer syn_NC_DB6_MDL20_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB6_MDL21_Acetylcholine
print("Adding continuous projection: NC_DB6_MDL21_Acetylcholine from DB6 to MDL21, with 1 connection(s)")
h("objectvar syn_NC_DB6_MDL21_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB6_MDL21_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL21[0].soma], weight: 1.0
h("a_DB6[0].soma { syn_NC_DB6_MDL21_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL21[0].soma { syn_NC_DB6_MDL21_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB6_MDL21_Acetylcholine_silent_pre[0].vpeer, a_MDL21[0].soma.v(0.500000)")
h("setpointer syn_NC_DB6_MDL21_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB6_MDR16_Acetylcholine
print("Adding continuous projection: NC_DB6_MDR16_Acetylcholine from DB6 to MDR16, with 1 connection(s)")
h("objectvar syn_NC_DB6_MDR16_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB6_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR16[0].soma], weight: 1.0
h("a_DB6[0].soma { syn_NC_DB6_MDR16_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR16[0].soma { syn_NC_DB6_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB6_MDR16_Acetylcholine_silent_pre[0].vpeer, a_MDR16[0].soma.v(0.500000)")
h("setpointer syn_NC_DB6_MDR16_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB6_MDR17_Acetylcholine
print("Adding continuous projection: NC_DB6_MDR17_Acetylcholine from DB6 to MDR17, with 1 connection(s)")
h("objectvar syn_NC_DB6_MDR17_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB6_MDR17_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR17[0].soma], weight: 1.0
h("a_DB6[0].soma { syn_NC_DB6_MDR17_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR17[0].soma { syn_NC_DB6_MDR17_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB6_MDR17_Acetylcholine_silent_pre[0].vpeer, a_MDR17[0].soma.v(0.500000)")
h("setpointer syn_NC_DB6_MDR17_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB6_MDR18_Acetylcholine
print("Adding continuous projection: NC_DB6_MDR18_Acetylcholine from DB6 to MDR18, with 1 connection(s)")
h("objectvar syn_NC_DB6_MDR18_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB6_MDR18_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR18[0].soma], weight: 1.0
h("a_DB6[0].soma { syn_NC_DB6_MDR18_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR18[0].soma { syn_NC_DB6_MDR18_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB6_MDR18_Acetylcholine_silent_pre[0].vpeer, a_MDR18[0].soma.v(0.500000)")
h("setpointer syn_NC_DB6_MDR18_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB6_MDR19_Acetylcholine
print("Adding continuous projection: NC_DB6_MDR19_Acetylcholine from DB6 to MDR19, with 1 connection(s)")
h("objectvar syn_NC_DB6_MDR19_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB6_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR19[0].soma], weight: 1.0
h("a_DB6[0].soma { syn_NC_DB6_MDR19_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR19[0].soma { syn_NC_DB6_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB6_MDR19_Acetylcholine_silent_pre[0].vpeer, a_MDR19[0].soma.v(0.500000)")
h("setpointer syn_NC_DB6_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB6_MDR20_Acetylcholine
print("Adding continuous projection: NC_DB6_MDR20_Acetylcholine from DB6 to MDR20, with 1 connection(s)")
h("objectvar syn_NC_DB6_MDR20_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB6_MDR20_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR20[0].soma], weight: 1.0
h("a_DB6[0].soma { syn_NC_DB6_MDR20_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR20[0].soma { syn_NC_DB6_MDR20_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB6_MDR20_Acetylcholine_silent_pre[0].vpeer, a_MDR20[0].soma.v(0.500000)")
h("setpointer syn_NC_DB6_MDR20_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB6_MDR21_Acetylcholine
print("Adding continuous projection: NC_DB6_MDR21_Acetylcholine from DB6 to MDR21, with 1 connection(s)")
h("objectvar syn_NC_DB6_MDR21_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB6_MDR21_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB6[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR21[0].soma], weight: 1.0
h("a_DB6[0].soma { syn_NC_DB6_MDR21_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR21[0].soma { syn_NC_DB6_MDR21_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB6_MDR21_Acetylcholine_silent_pre[0].vpeer, a_MDR21[0].soma.v(0.500000)")
h("setpointer syn_NC_DB6_MDR21_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB6[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB7_MDL19_Acetylcholine
print("Adding continuous projection: NC_DB7_MDL19_Acetylcholine from DB7 to MDL19, with 1 connection(s)")
h("objectvar syn_NC_DB7_MDL19_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB7_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL19[0].soma], weight: 1.0
h("a_DB7[0].soma { syn_NC_DB7_MDL19_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL19[0].soma { syn_NC_DB7_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB7_MDL19_Acetylcholine_silent_pre[0].vpeer, a_MDL19[0].soma.v(0.500000)")
h("setpointer syn_NC_DB7_MDL19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB7_MDL20_Acetylcholine
print("Adding continuous projection: NC_DB7_MDL20_Acetylcholine from DB7 to MDL20, with 1 connection(s)")
h("objectvar syn_NC_DB7_MDL20_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB7_MDL20_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL20[0].soma], weight: 1.0
h("a_DB7[0].soma { syn_NC_DB7_MDL20_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL20[0].soma { syn_NC_DB7_MDL20_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB7_MDL20_Acetylcholine_silent_pre[0].vpeer, a_MDL20[0].soma.v(0.500000)")
h("setpointer syn_NC_DB7_MDL20_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB7_MDL21_Acetylcholine
print("Adding continuous projection: NC_DB7_MDL21_Acetylcholine from DB7 to MDL21, with 1 connection(s)")
h("objectvar syn_NC_DB7_MDL21_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB7_MDL21_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL21[0].soma], weight: 1.0
h("a_DB7[0].soma { syn_NC_DB7_MDL21_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL21[0].soma { syn_NC_DB7_MDL21_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB7_MDL21_Acetylcholine_silent_pre[0].vpeer, a_MDL21[0].soma.v(0.500000)")
h("setpointer syn_NC_DB7_MDL21_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB7_MDL22_Acetylcholine
print("Adding continuous projection: NC_DB7_MDL22_Acetylcholine from DB7 to MDL22, with 1 connection(s)")
h("objectvar syn_NC_DB7_MDL22_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB7_MDL22_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL22[0].soma], weight: 1.0
h("a_DB7[0].soma { syn_NC_DB7_MDL22_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL22[0].soma { syn_NC_DB7_MDL22_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB7_MDL22_Acetylcholine_silent_pre[0].vpeer, a_MDL22[0].soma.v(0.500000)")
h("setpointer syn_NC_DB7_MDL22_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB7_MDL23_Acetylcholine
print("Adding continuous projection: NC_DB7_MDL23_Acetylcholine from DB7 to MDL23, with 1 connection(s)")
h("objectvar syn_NC_DB7_MDL23_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB7_MDL23_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL23[0].soma], weight: 1.0
h("a_DB7[0].soma { syn_NC_DB7_MDL23_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL23[0].soma { syn_NC_DB7_MDL23_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB7_MDL23_Acetylcholine_silent_pre[0].vpeer, a_MDL23[0].soma.v(0.500000)")
h("setpointer syn_NC_DB7_MDL23_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB7_MDL24_Acetylcholine
print("Adding continuous projection: NC_DB7_MDL24_Acetylcholine from DB7 to MDL24, with 1 connection(s)")
h("objectvar syn_NC_DB7_MDL24_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB7_MDL24_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDL24[0].soma], weight: 1.0
h("a_DB7[0].soma { syn_NC_DB7_MDL24_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDL24[0].soma { syn_NC_DB7_MDL24_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB7_MDL24_Acetylcholine_silent_pre[0].vpeer, a_MDL24[0].soma.v(0.500000)")
h("setpointer syn_NC_DB7_MDL24_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB7_MDR19_Acetylcholine
print("Adding continuous projection: NC_DB7_MDR19_Acetylcholine from DB7 to MDR19, with 1 connection(s)")
h("objectvar syn_NC_DB7_MDR19_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB7_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR19[0].soma], weight: 1.0
h("a_DB7[0].soma { syn_NC_DB7_MDR19_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR19[0].soma { syn_NC_DB7_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB7_MDR19_Acetylcholine_silent_pre[0].vpeer, a_MDR19[0].soma.v(0.500000)")
h("setpointer syn_NC_DB7_MDR19_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB7_MDR20_Acetylcholine
print("Adding continuous projection: NC_DB7_MDR20_Acetylcholine from DB7 to MDR20, with 1 connection(s)")
h("objectvar syn_NC_DB7_MDR20_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB7_MDR20_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR20[0].soma], weight: 1.0
h("a_DB7[0].soma { syn_NC_DB7_MDR20_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR20[0].soma { syn_NC_DB7_MDR20_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB7_MDR20_Acetylcholine_silent_pre[0].vpeer, a_MDR20[0].soma.v(0.500000)")
h("setpointer syn_NC_DB7_MDR20_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB7_MDR21_Acetylcholine
print("Adding continuous projection: NC_DB7_MDR21_Acetylcholine from DB7 to MDR21, with 1 connection(s)")
h("objectvar syn_NC_DB7_MDR21_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB7_MDR21_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR21[0].soma], weight: 1.0
h("a_DB7[0].soma { syn_NC_DB7_MDR21_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR21[0].soma { syn_NC_DB7_MDR21_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB7_MDR21_Acetylcholine_silent_pre[0].vpeer, a_MDR21[0].soma.v(0.500000)")
h("setpointer syn_NC_DB7_MDR21_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB7_MDR22_Acetylcholine
print("Adding continuous projection: NC_DB7_MDR22_Acetylcholine from DB7 to MDR22, with 1 connection(s)")
h("objectvar syn_NC_DB7_MDR22_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB7_MDR22_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR22[0].soma], weight: 1.0
h("a_DB7[0].soma { syn_NC_DB7_MDR22_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR22[0].soma { syn_NC_DB7_MDR22_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB7_MDR22_Acetylcholine_silent_pre[0].vpeer, a_MDR22[0].soma.v(0.500000)")
h("setpointer syn_NC_DB7_MDR22_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB7_MDR23_Acetylcholine
print("Adding continuous projection: NC_DB7_MDR23_Acetylcholine from DB7 to MDR23, with 1 connection(s)")
h("objectvar syn_NC_DB7_MDR23_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB7_MDR23_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR23[0].soma], weight: 1.0
h("a_DB7[0].soma { syn_NC_DB7_MDR23_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR23[0].soma { syn_NC_DB7_MDR23_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB7_MDR23_Acetylcholine_silent_pre[0].vpeer, a_MDR23[0].soma.v(0.500000)")
h("setpointer syn_NC_DB7_MDR23_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB7[0].soma.v(0.500000)")
# ###################### Continuous Projection: NC_DB7_MDR24_Acetylcholine
print("Adding continuous projection: NC_DB7_MDR24_Acetylcholine from DB7 to MDR24, with 1 connection(s)")
h("objectvar syn_NC_DB7_MDR24_Acetylcholine_silent_pre[1]")
h("objectvar syn_NC_DB7_MDR24_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[1]")
# Continuous Connection 0: cell 0, seg 0 (0.5) [0.5 on a_DB7[0].soma] -> cell 0, seg 0 (0.5) [0.5 on a_MDR24[0].soma], weight: 1.0
h("a_DB7[0].soma { syn_NC_DB7_MDR24_Acetylcholine_silent_pre[0] = new silent(0.500000) }")
h("a_MDR24[0].soma { syn_NC_DB7_MDR24_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0] = new neuron_to_muscle_exc_syn_2conns(0.500000) }")
h("setpointer syn_NC_DB7_MDR24_Acetylcholine_silent_pre[0].vpeer, a_MDR24[0].soma.v(0.500000)")
h("setpointer syn_NC_DB7_MDR24_Acetylcholine_neuron_to_muscle_exc_syn_2conns_post[0].vpeer, a_DB7[0].soma.v(0.500000)")
# ###################### Input List: Input_AVBL_stim_AVBL_1
print("Adding input list: Input_AVBL_stim_AVBL_1 to AVBL, with 1 inputs of type stim_AVBL_1")
# Adding single input: Component(id=0 type=input)
h("objref Input_AVBL_stim_AVBL_1_0")
h("a_AVBL[0].soma { Input_AVBL_stim_AVBL_1_0 = new stim_AVBL_1(0.5) } ")
# ###################### Input List: Input_AVBR_stim_AVBR_1
print("Adding input list: Input_AVBR_stim_AVBR_1 to AVBR, with 1 inputs of type stim_AVBR_1")
# Adding single input: Component(id=0 type=input)
h("objref Input_AVBR_stim_AVBR_1_0")
h("a_AVBR[0].soma { Input_AVBR_stim_AVBR_1_0 = new stim_AVBR_1(0.5) } ")
# ###################### Input List: Input_AS1_stim_AS1_1
print("Adding input list: Input_AS1_stim_AS1_1 to AS1, with 1 inputs of type stim_AS1_1")
# Adding single input: Component(id=0 type=input)
h("objref Input_AS1_stim_AS1_1_0")
h("a_AS1[0].soma { Input_AS1_stim_AS1_1_0 = new stim_AS1_1(0.5) } ")
# ###################### Input List: Input_AS2_stim_AS2_1
print("Adding input list: Input_AS2_stim_AS2_1 to AS2, with 1 inputs of type stim_AS2_1")
# Adding single input: Component(id=0 type=input)
h("objref Input_AS2_stim_AS2_1_0")
h("a_AS2[0].soma { Input_AS2_stim_AS2_1_0 = new stim_AS2_1(0.5) } ")
# ###################### Input List: Input_AS3_stim_AS3_1
print("Adding input list: Input_AS3_stim_AS3_1 to AS3, with 1 inputs of type stim_AS3_1")
# Adding single input: Component(id=0 type=input)
h("objref Input_AS3_stim_AS3_1_0")
h("a_AS3[0].soma { Input_AS3_stim_AS3_1_0 = new stim_AS3_1(0.5) } ")
# ###################### Input List: Input_AS4_stim_AS4_1
print("Adding input list: Input_AS4_stim_AS4_1 to AS4, with 1 inputs of type stim_AS4_1")
# Adding single input: Component(id=0 type=input)
h("objref Input_AS4_stim_AS4_1_0")
h("a_AS4[0].soma { Input_AS4_stim_AS4_1_0 = new stim_AS4_1(0.5) } ")
# ###################### Input List: Input_AS5_stim_AS5_1
print("Adding input list: Input_AS5_stim_AS5_1 to AS5, with 1 inputs of type stim_AS5_1")
# Adding single input: Component(id=0 type=input)
h("objref Input_AS5_stim_AS5_1_0")
h("a_AS5[0].soma { Input_AS5_stim_AS5_1_0 = new stim_AS5_1(0.5) } ")
# ###################### Input List: Input_AS6_stim_AS6_1
print("Adding input list: Input_AS6_stim_AS6_1 to AS6, with 1 inputs of type stim_AS6_1")
# Adding single input: Component(id=0 type=input)
h("objref Input_AS6_stim_AS6_1_0")
h("a_AS6[0].soma { Input_AS6_stim_AS6_1_0 = new stim_AS6_1(0.5) } ")
# ###################### Input List: Input_AS7_stim_AS7_1
print("Adding input list: Input_AS7_stim_AS7_1 to AS7, with 1 inputs of type stim_AS7_1")
# Adding single input: Component(id=0 type=input)
h("objref Input_AS7_stim_AS7_1_0")
h("a_AS7[0].soma { Input_AS7_stim_AS7_1_0 = new stim_AS7_1(0.5) } ")
# ###################### Input List: Input_AS8_stim_AS8_1
print("Adding input list: Input_AS8_stim_AS8_1 to AS8, with 1 inputs of type stim_AS8_1")
# Adding single input: Component(id=0 type=input)
h("objref Input_AS8_stim_AS8_1_0")
h("a_AS8[0].soma { Input_AS8_stim_AS8_1_0 = new stim_AS8_1(0.5) } ")
# ###################### Input List: Input_AS9_stim_AS9_1
print("Adding input list: Input_AS9_stim_AS9_1 to AS9, with 1 inputs of type stim_AS9_1")
# Adding single input: Component(id=0 type=input)
h("objref Input_AS9_stim_AS9_1_0")
h("a_AS9[0].soma { Input_AS9_stim_AS9_1_0 = new stim_AS9_1(0.5) } ")
# ###################### Input List: Input_AS10_stim_AS10_1
print("Adding input list: Input_AS10_stim_AS10_1 to AS10, with 1 inputs of type stim_AS10_1")
# Adding single input: Component(id=0 type=input)
h("objref Input_AS10_stim_AS10_1_0")
h("a_AS10[0].soma { Input_AS10_stim_AS10_1_0 = new stim_AS10_1(0.5) } ")
# ###################### Input List: Input_AS11_stim_AS11_1
print("Adding input list: Input_AS11_stim_AS11_1 to AS11, with 1 inputs of type stim_AS11_1")
# Adding single input: Component(id=0 type=input)
h("objref Input_AS11_stim_AS11_1_0")
h("a_AS11[0].soma { Input_AS11_stim_AS11_1_0 = new stim_AS11_1(0.5) } ")
trec = h.Vector()
trec.record(h._ref_t)
h.tstop = tstop
h.dt = dt
h.steps_per_ms = 1/h.dt
# ###################### File to save: c302_C2_AS_DA_DB.activity.dat (neurons_activity)
# Column: AS1/0/GenericNeuronCell/caConc
h(' objectvar v_AS1_v_neurons_activity ')
h(' { v_AS1_v_neurons_activity = new Vector() } ')
h(' { v_AS1_v_neurons_activity.record(&a_AS1[0].soma.cai(0.5)) } ')
h.v_AS1_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS10/0/GenericNeuronCell/caConc
h(' objectvar v_AS10_v_neurons_activity ')
h(' { v_AS10_v_neurons_activity = new Vector() } ')
h(' { v_AS10_v_neurons_activity.record(&a_AS10[0].soma.cai(0.5)) } ')
h.v_AS10_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS11/0/GenericNeuronCell/caConc
h(' objectvar v_AS11_v_neurons_activity ')
h(' { v_AS11_v_neurons_activity = new Vector() } ')
h(' { v_AS11_v_neurons_activity.record(&a_AS11[0].soma.cai(0.5)) } ')
h.v_AS11_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS2/0/GenericNeuronCell/caConc
h(' objectvar v_AS2_v_neurons_activity ')
h(' { v_AS2_v_neurons_activity = new Vector() } ')
h(' { v_AS2_v_neurons_activity.record(&a_AS2[0].soma.cai(0.5)) } ')
h.v_AS2_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS3/0/GenericNeuronCell/caConc
h(' objectvar v_AS3_v_neurons_activity ')
h(' { v_AS3_v_neurons_activity = new Vector() } ')
h(' { v_AS3_v_neurons_activity.record(&a_AS3[0].soma.cai(0.5)) } ')
h.v_AS3_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS4/0/GenericNeuronCell/caConc
h(' objectvar v_AS4_v_neurons_activity ')
h(' { v_AS4_v_neurons_activity = new Vector() } ')
h(' { v_AS4_v_neurons_activity.record(&a_AS4[0].soma.cai(0.5)) } ')
h.v_AS4_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS5/0/GenericNeuronCell/caConc
h(' objectvar v_AS5_v_neurons_activity ')
h(' { v_AS5_v_neurons_activity = new Vector() } ')
h(' { v_AS5_v_neurons_activity.record(&a_AS5[0].soma.cai(0.5)) } ')
h.v_AS5_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS6/0/GenericNeuronCell/caConc
h(' objectvar v_AS6_v_neurons_activity ')
h(' { v_AS6_v_neurons_activity = new Vector() } ')
h(' { v_AS6_v_neurons_activity.record(&a_AS6[0].soma.cai(0.5)) } ')
h.v_AS6_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS7/0/GenericNeuronCell/caConc
h(' objectvar v_AS7_v_neurons_activity ')
h(' { v_AS7_v_neurons_activity = new Vector() } ')
h(' { v_AS7_v_neurons_activity.record(&a_AS7[0].soma.cai(0.5)) } ')
h.v_AS7_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS8/0/GenericNeuronCell/caConc
h(' objectvar v_AS8_v_neurons_activity ')
h(' { v_AS8_v_neurons_activity = new Vector() } ')
h(' { v_AS8_v_neurons_activity.record(&a_AS8[0].soma.cai(0.5)) } ')
h.v_AS8_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS9/0/GenericNeuronCell/caConc
h(' objectvar v_AS9_v_neurons_activity ')
h(' { v_AS9_v_neurons_activity = new Vector() } ')
h(' { v_AS9_v_neurons_activity.record(&a_AS9[0].soma.cai(0.5)) } ')
h.v_AS9_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AVAL/0/GenericNeuronCell/caConc
h(' objectvar v_AVAL_v_neurons_activity ')
h(' { v_AVAL_v_neurons_activity = new Vector() } ')
h(' { v_AVAL_v_neurons_activity.record(&a_AVAL[0].soma.cai(0.5)) } ')
h.v_AVAL_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AVAR/0/GenericNeuronCell/caConc
h(' objectvar v_AVAR_v_neurons_activity ')
h(' { v_AVAR_v_neurons_activity = new Vector() } ')
h(' { v_AVAR_v_neurons_activity.record(&a_AVAR[0].soma.cai(0.5)) } ')
h.v_AVAR_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AVBL/0/GenericNeuronCell/caConc
h(' objectvar v_AVBL_v_neurons_activity ')
h(' { v_AVBL_v_neurons_activity = new Vector() } ')
h(' { v_AVBL_v_neurons_activity.record(&a_AVBL[0].soma.cai(0.5)) } ')
h.v_AVBL_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AVBR/0/GenericNeuronCell/caConc
h(' objectvar v_AVBR_v_neurons_activity ')
h(' { v_AVBR_v_neurons_activity = new Vector() } ')
h(' { v_AVBR_v_neurons_activity.record(&a_AVBR[0].soma.cai(0.5)) } ')
h.v_AVBR_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA1/0/GenericNeuronCell/caConc
h(' objectvar v_DA1_v_neurons_activity ')
h(' { v_DA1_v_neurons_activity = new Vector() } ')
h(' { v_DA1_v_neurons_activity.record(&a_DA1[0].soma.cai(0.5)) } ')
h.v_DA1_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA2/0/GenericNeuronCell/caConc
h(' objectvar v_DA2_v_neurons_activity ')
h(' { v_DA2_v_neurons_activity = new Vector() } ')
h(' { v_DA2_v_neurons_activity.record(&a_DA2[0].soma.cai(0.5)) } ')
h.v_DA2_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA3/0/GenericNeuronCell/caConc
h(' objectvar v_DA3_v_neurons_activity ')
h(' { v_DA3_v_neurons_activity = new Vector() } ')
h(' { v_DA3_v_neurons_activity.record(&a_DA3[0].soma.cai(0.5)) } ')
h.v_DA3_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA4/0/GenericNeuronCell/caConc
h(' objectvar v_DA4_v_neurons_activity ')
h(' { v_DA4_v_neurons_activity = new Vector() } ')
h(' { v_DA4_v_neurons_activity.record(&a_DA4[0].soma.cai(0.5)) } ')
h.v_DA4_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA5/0/GenericNeuronCell/caConc
h(' objectvar v_DA5_v_neurons_activity ')
h(' { v_DA5_v_neurons_activity = new Vector() } ')
h(' { v_DA5_v_neurons_activity.record(&a_DA5[0].soma.cai(0.5)) } ')
h.v_DA5_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA6/0/GenericNeuronCell/caConc
h(' objectvar v_DA6_v_neurons_activity ')
h(' { v_DA6_v_neurons_activity = new Vector() } ')
h(' { v_DA6_v_neurons_activity.record(&a_DA6[0].soma.cai(0.5)) } ')
h.v_DA6_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA7/0/GenericNeuronCell/caConc
h(' objectvar v_DA7_v_neurons_activity ')
h(' { v_DA7_v_neurons_activity = new Vector() } ')
h(' { v_DA7_v_neurons_activity.record(&a_DA7[0].soma.cai(0.5)) } ')
h.v_DA7_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA8/0/GenericNeuronCell/caConc
h(' objectvar v_DA8_v_neurons_activity ')
h(' { v_DA8_v_neurons_activity = new Vector() } ')
h(' { v_DA8_v_neurons_activity.record(&a_DA8[0].soma.cai(0.5)) } ')
h.v_DA8_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA9/0/GenericNeuronCell/caConc
h(' objectvar v_DA9_v_neurons_activity ')
h(' { v_DA9_v_neurons_activity = new Vector() } ')
h(' { v_DA9_v_neurons_activity.record(&a_DA9[0].soma.cai(0.5)) } ')
h.v_DA9_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DB1/0/GenericNeuronCell/caConc
h(' objectvar v_DB1_v_neurons_activity ')
h(' { v_DB1_v_neurons_activity = new Vector() } ')
h(' { v_DB1_v_neurons_activity.record(&a_DB1[0].soma.cai(0.5)) } ')
h.v_DB1_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DB2/0/GenericNeuronCell/caConc
h(' objectvar v_DB2_v_neurons_activity ')
h(' { v_DB2_v_neurons_activity = new Vector() } ')
h(' { v_DB2_v_neurons_activity.record(&a_DB2[0].soma.cai(0.5)) } ')
h.v_DB2_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DB3/0/GenericNeuronCell/caConc
h(' objectvar v_DB3_v_neurons_activity ')
h(' { v_DB3_v_neurons_activity = new Vector() } ')
h(' { v_DB3_v_neurons_activity.record(&a_DB3[0].soma.cai(0.5)) } ')
h.v_DB3_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DB4/0/GenericNeuronCell/caConc
h(' objectvar v_DB4_v_neurons_activity ')
h(' { v_DB4_v_neurons_activity = new Vector() } ')
h(' { v_DB4_v_neurons_activity.record(&a_DB4[0].soma.cai(0.5)) } ')
h.v_DB4_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DB5/0/GenericNeuronCell/caConc
h(' objectvar v_DB5_v_neurons_activity ')
h(' { v_DB5_v_neurons_activity = new Vector() } ')
h(' { v_DB5_v_neurons_activity.record(&a_DB5[0].soma.cai(0.5)) } ')
h.v_DB5_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DB6/0/GenericNeuronCell/caConc
h(' objectvar v_DB6_v_neurons_activity ')
h(' { v_DB6_v_neurons_activity = new Vector() } ')
h(' { v_DB6_v_neurons_activity.record(&a_DB6[0].soma.cai(0.5)) } ')
h.v_DB6_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DB7/0/GenericNeuronCell/caConc
h(' objectvar v_DB7_v_neurons_activity ')
h(' { v_DB7_v_neurons_activity = new Vector() } ')
h(' { v_DB7_v_neurons_activity.record(&a_DB7[0].soma.cai(0.5)) } ')
h.v_DB7_v_neurons_activity.resize((h.tstop * h.steps_per_ms) + 1)
# ###################### File to save: c302_C2_AS_DA_DB.muscles.dat (muscles_v)
# Column: MDR01/0/GenericMuscleCell/v
h(' objectvar v_MDR01_v_muscles_v ')
h(' { v_MDR01_v_muscles_v = new Vector() } ')
h(' { v_MDR01_v_muscles_v.record(&a_MDR01[0].soma.v(0.5)) } ')
h.v_MDR01_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR02/0/GenericMuscleCell/v
h(' objectvar v_MDR02_v_muscles_v ')
h(' { v_MDR02_v_muscles_v = new Vector() } ')
h(' { v_MDR02_v_muscles_v.record(&a_MDR02[0].soma.v(0.5)) } ')
h.v_MDR02_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR03/0/GenericMuscleCell/v
h(' objectvar v_MDR03_v_muscles_v ')
h(' { v_MDR03_v_muscles_v = new Vector() } ')
h(' { v_MDR03_v_muscles_v.record(&a_MDR03[0].soma.v(0.5)) } ')
h.v_MDR03_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR04/0/GenericMuscleCell/v
h(' objectvar v_MDR04_v_muscles_v ')
h(' { v_MDR04_v_muscles_v = new Vector() } ')
h(' { v_MDR04_v_muscles_v.record(&a_MDR04[0].soma.v(0.5)) } ')
h.v_MDR04_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR05/0/GenericMuscleCell/v
h(' objectvar v_MDR05_v_muscles_v ')
h(' { v_MDR05_v_muscles_v = new Vector() } ')
h(' { v_MDR05_v_muscles_v.record(&a_MDR05[0].soma.v(0.5)) } ')
h.v_MDR05_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR06/0/GenericMuscleCell/v
h(' objectvar v_MDR06_v_muscles_v ')
h(' { v_MDR06_v_muscles_v = new Vector() } ')
h(' { v_MDR06_v_muscles_v.record(&a_MDR06[0].soma.v(0.5)) } ')
h.v_MDR06_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR07/0/GenericMuscleCell/v
h(' objectvar v_MDR07_v_muscles_v ')
h(' { v_MDR07_v_muscles_v = new Vector() } ')
h(' { v_MDR07_v_muscles_v.record(&a_MDR07[0].soma.v(0.5)) } ')
h.v_MDR07_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR08/0/GenericMuscleCell/v
h(' objectvar v_MDR08_v_muscles_v ')
h(' { v_MDR08_v_muscles_v = new Vector() } ')
h(' { v_MDR08_v_muscles_v.record(&a_MDR08[0].soma.v(0.5)) } ')
h.v_MDR08_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR09/0/GenericMuscleCell/v
h(' objectvar v_MDR09_v_muscles_v ')
h(' { v_MDR09_v_muscles_v = new Vector() } ')
h(' { v_MDR09_v_muscles_v.record(&a_MDR09[0].soma.v(0.5)) } ')
h.v_MDR09_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR10/0/GenericMuscleCell/v
h(' objectvar v_MDR10_v_muscles_v ')
h(' { v_MDR10_v_muscles_v = new Vector() } ')
h(' { v_MDR10_v_muscles_v.record(&a_MDR10[0].soma.v(0.5)) } ')
h.v_MDR10_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR11/0/GenericMuscleCell/v
h(' objectvar v_MDR11_v_muscles_v ')
h(' { v_MDR11_v_muscles_v = new Vector() } ')
h(' { v_MDR11_v_muscles_v.record(&a_MDR11[0].soma.v(0.5)) } ')
h.v_MDR11_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR12/0/GenericMuscleCell/v
h(' objectvar v_MDR12_v_muscles_v ')
h(' { v_MDR12_v_muscles_v = new Vector() } ')
h(' { v_MDR12_v_muscles_v.record(&a_MDR12[0].soma.v(0.5)) } ')
h.v_MDR12_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR13/0/GenericMuscleCell/v
h(' objectvar v_MDR13_v_muscles_v ')
h(' { v_MDR13_v_muscles_v = new Vector() } ')
h(' { v_MDR13_v_muscles_v.record(&a_MDR13[0].soma.v(0.5)) } ')
h.v_MDR13_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR14/0/GenericMuscleCell/v
h(' objectvar v_MDR14_v_muscles_v ')
h(' { v_MDR14_v_muscles_v = new Vector() } ')
h(' { v_MDR14_v_muscles_v.record(&a_MDR14[0].soma.v(0.5)) } ')
h.v_MDR14_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR15/0/GenericMuscleCell/v
h(' objectvar v_MDR15_v_muscles_v ')
h(' { v_MDR15_v_muscles_v = new Vector() } ')
h(' { v_MDR15_v_muscles_v.record(&a_MDR15[0].soma.v(0.5)) } ')
h.v_MDR15_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR16/0/GenericMuscleCell/v
h(' objectvar v_MDR16_v_muscles_v ')
h(' { v_MDR16_v_muscles_v = new Vector() } ')
h(' { v_MDR16_v_muscles_v.record(&a_MDR16[0].soma.v(0.5)) } ')
h.v_MDR16_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR17/0/GenericMuscleCell/v
h(' objectvar v_MDR17_v_muscles_v ')
h(' { v_MDR17_v_muscles_v = new Vector() } ')
h(' { v_MDR17_v_muscles_v.record(&a_MDR17[0].soma.v(0.5)) } ')
h.v_MDR17_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR18/0/GenericMuscleCell/v
h(' objectvar v_MDR18_v_muscles_v ')
h(' { v_MDR18_v_muscles_v = new Vector() } ')
h(' { v_MDR18_v_muscles_v.record(&a_MDR18[0].soma.v(0.5)) } ')
h.v_MDR18_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR19/0/GenericMuscleCell/v
h(' objectvar v_MDR19_v_muscles_v ')
h(' { v_MDR19_v_muscles_v = new Vector() } ')
h(' { v_MDR19_v_muscles_v.record(&a_MDR19[0].soma.v(0.5)) } ')
h.v_MDR19_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR20/0/GenericMuscleCell/v
h(' objectvar v_MDR20_v_muscles_v ')
h(' { v_MDR20_v_muscles_v = new Vector() } ')
h(' { v_MDR20_v_muscles_v.record(&a_MDR20[0].soma.v(0.5)) } ')
h.v_MDR20_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR21/0/GenericMuscleCell/v
h(' objectvar v_MDR21_v_muscles_v ')
h(' { v_MDR21_v_muscles_v = new Vector() } ')
h(' { v_MDR21_v_muscles_v.record(&a_MDR21[0].soma.v(0.5)) } ')
h.v_MDR21_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR22/0/GenericMuscleCell/v
h(' objectvar v_MDR22_v_muscles_v ')
h(' { v_MDR22_v_muscles_v = new Vector() } ')
h(' { v_MDR22_v_muscles_v.record(&a_MDR22[0].soma.v(0.5)) } ')
h.v_MDR22_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR23/0/GenericMuscleCell/v
h(' objectvar v_MDR23_v_muscles_v ')
h(' { v_MDR23_v_muscles_v = new Vector() } ')
h(' { v_MDR23_v_muscles_v.record(&a_MDR23[0].soma.v(0.5)) } ')
h.v_MDR23_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR24/0/GenericMuscleCell/v
h(' objectvar v_MDR24_v_muscles_v ')
h(' { v_MDR24_v_muscles_v = new Vector() } ')
h(' { v_MDR24_v_muscles_v.record(&a_MDR24[0].soma.v(0.5)) } ')
h.v_MDR24_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR01/0/GenericMuscleCell/v
h(' objectvar v_MVR01_v_muscles_v ')
h(' { v_MVR01_v_muscles_v = new Vector() } ')
h(' { v_MVR01_v_muscles_v.record(&a_MVR01[0].soma.v(0.5)) } ')
h.v_MVR01_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR02/0/GenericMuscleCell/v
h(' objectvar v_MVR02_v_muscles_v ')
h(' { v_MVR02_v_muscles_v = new Vector() } ')
h(' { v_MVR02_v_muscles_v.record(&a_MVR02[0].soma.v(0.5)) } ')
h.v_MVR02_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR03/0/GenericMuscleCell/v
h(' objectvar v_MVR03_v_muscles_v ')
h(' { v_MVR03_v_muscles_v = new Vector() } ')
h(' { v_MVR03_v_muscles_v.record(&a_MVR03[0].soma.v(0.5)) } ')
h.v_MVR03_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR04/0/GenericMuscleCell/v
h(' objectvar v_MVR04_v_muscles_v ')
h(' { v_MVR04_v_muscles_v = new Vector() } ')
h(' { v_MVR04_v_muscles_v.record(&a_MVR04[0].soma.v(0.5)) } ')
h.v_MVR04_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR05/0/GenericMuscleCell/v
h(' objectvar v_MVR05_v_muscles_v ')
h(' { v_MVR05_v_muscles_v = new Vector() } ')
h(' { v_MVR05_v_muscles_v.record(&a_MVR05[0].soma.v(0.5)) } ')
h.v_MVR05_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR06/0/GenericMuscleCell/v
h(' objectvar v_MVR06_v_muscles_v ')
h(' { v_MVR06_v_muscles_v = new Vector() } ')
h(' { v_MVR06_v_muscles_v.record(&a_MVR06[0].soma.v(0.5)) } ')
h.v_MVR06_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR07/0/GenericMuscleCell/v
h(' objectvar v_MVR07_v_muscles_v ')
h(' { v_MVR07_v_muscles_v = new Vector() } ')
h(' { v_MVR07_v_muscles_v.record(&a_MVR07[0].soma.v(0.5)) } ')
h.v_MVR07_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR08/0/GenericMuscleCell/v
h(' objectvar v_MVR08_v_muscles_v ')
h(' { v_MVR08_v_muscles_v = new Vector() } ')
h(' { v_MVR08_v_muscles_v.record(&a_MVR08[0].soma.v(0.5)) } ')
h.v_MVR08_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR09/0/GenericMuscleCell/v
h(' objectvar v_MVR09_v_muscles_v ')
h(' { v_MVR09_v_muscles_v = new Vector() } ')
h(' { v_MVR09_v_muscles_v.record(&a_MVR09[0].soma.v(0.5)) } ')
h.v_MVR09_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR10/0/GenericMuscleCell/v
h(' objectvar v_MVR10_v_muscles_v ')
h(' { v_MVR10_v_muscles_v = new Vector() } ')
h(' { v_MVR10_v_muscles_v.record(&a_MVR10[0].soma.v(0.5)) } ')
h.v_MVR10_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR11/0/GenericMuscleCell/v
h(' objectvar v_MVR11_v_muscles_v ')
h(' { v_MVR11_v_muscles_v = new Vector() } ')
h(' { v_MVR11_v_muscles_v.record(&a_MVR11[0].soma.v(0.5)) } ')
h.v_MVR11_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR12/0/GenericMuscleCell/v
h(' objectvar v_MVR12_v_muscles_v ')
h(' { v_MVR12_v_muscles_v = new Vector() } ')
h(' { v_MVR12_v_muscles_v.record(&a_MVR12[0].soma.v(0.5)) } ')
h.v_MVR12_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR13/0/GenericMuscleCell/v
h(' objectvar v_MVR13_v_muscles_v ')
h(' { v_MVR13_v_muscles_v = new Vector() } ')
h(' { v_MVR13_v_muscles_v.record(&a_MVR13[0].soma.v(0.5)) } ')
h.v_MVR13_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR14/0/GenericMuscleCell/v
h(' objectvar v_MVR14_v_muscles_v ')
h(' { v_MVR14_v_muscles_v = new Vector() } ')
h(' { v_MVR14_v_muscles_v.record(&a_MVR14[0].soma.v(0.5)) } ')
h.v_MVR14_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR15/0/GenericMuscleCell/v
h(' objectvar v_MVR15_v_muscles_v ')
h(' { v_MVR15_v_muscles_v = new Vector() } ')
h(' { v_MVR15_v_muscles_v.record(&a_MVR15[0].soma.v(0.5)) } ')
h.v_MVR15_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR16/0/GenericMuscleCell/v
h(' objectvar v_MVR16_v_muscles_v ')
h(' { v_MVR16_v_muscles_v = new Vector() } ')
h(' { v_MVR16_v_muscles_v.record(&a_MVR16[0].soma.v(0.5)) } ')
h.v_MVR16_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR17/0/GenericMuscleCell/v
h(' objectvar v_MVR17_v_muscles_v ')
h(' { v_MVR17_v_muscles_v = new Vector() } ')
h(' { v_MVR17_v_muscles_v.record(&a_MVR17[0].soma.v(0.5)) } ')
h.v_MVR17_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR18/0/GenericMuscleCell/v
h(' objectvar v_MVR18_v_muscles_v ')
h(' { v_MVR18_v_muscles_v = new Vector() } ')
h(' { v_MVR18_v_muscles_v.record(&a_MVR18[0].soma.v(0.5)) } ')
h.v_MVR18_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR19/0/GenericMuscleCell/v
h(' objectvar v_MVR19_v_muscles_v ')
h(' { v_MVR19_v_muscles_v = new Vector() } ')
h(' { v_MVR19_v_muscles_v.record(&a_MVR19[0].soma.v(0.5)) } ')
h.v_MVR19_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR20/0/GenericMuscleCell/v
h(' objectvar v_MVR20_v_muscles_v ')
h(' { v_MVR20_v_muscles_v = new Vector() } ')
h(' { v_MVR20_v_muscles_v.record(&a_MVR20[0].soma.v(0.5)) } ')
h.v_MVR20_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR21/0/GenericMuscleCell/v
h(' objectvar v_MVR21_v_muscles_v ')
h(' { v_MVR21_v_muscles_v = new Vector() } ')
h(' { v_MVR21_v_muscles_v.record(&a_MVR21[0].soma.v(0.5)) } ')
h.v_MVR21_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR22/0/GenericMuscleCell/v
h(' objectvar v_MVR22_v_muscles_v ')
h(' { v_MVR22_v_muscles_v = new Vector() } ')
h(' { v_MVR22_v_muscles_v.record(&a_MVR22[0].soma.v(0.5)) } ')
h.v_MVR22_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR23/0/GenericMuscleCell/v
h(' objectvar v_MVR23_v_muscles_v ')
h(' { v_MVR23_v_muscles_v = new Vector() } ')
h(' { v_MVR23_v_muscles_v.record(&a_MVR23[0].soma.v(0.5)) } ')
h.v_MVR23_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL01/0/GenericMuscleCell/v
h(' objectvar v_MVL01_v_muscles_v ')
h(' { v_MVL01_v_muscles_v = new Vector() } ')
h(' { v_MVL01_v_muscles_v.record(&a_MVL01[0].soma.v(0.5)) } ')
h.v_MVL01_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL02/0/GenericMuscleCell/v
h(' objectvar v_MVL02_v_muscles_v ')
h(' { v_MVL02_v_muscles_v = new Vector() } ')
h(' { v_MVL02_v_muscles_v.record(&a_MVL02[0].soma.v(0.5)) } ')
h.v_MVL02_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL03/0/GenericMuscleCell/v
h(' objectvar v_MVL03_v_muscles_v ')
h(' { v_MVL03_v_muscles_v = new Vector() } ')
h(' { v_MVL03_v_muscles_v.record(&a_MVL03[0].soma.v(0.5)) } ')
h.v_MVL03_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL04/0/GenericMuscleCell/v
h(' objectvar v_MVL04_v_muscles_v ')
h(' { v_MVL04_v_muscles_v = new Vector() } ')
h(' { v_MVL04_v_muscles_v.record(&a_MVL04[0].soma.v(0.5)) } ')
h.v_MVL04_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL05/0/GenericMuscleCell/v
h(' objectvar v_MVL05_v_muscles_v ')
h(' { v_MVL05_v_muscles_v = new Vector() } ')
h(' { v_MVL05_v_muscles_v.record(&a_MVL05[0].soma.v(0.5)) } ')
h.v_MVL05_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL06/0/GenericMuscleCell/v
h(' objectvar v_MVL06_v_muscles_v ')
h(' { v_MVL06_v_muscles_v = new Vector() } ')
h(' { v_MVL06_v_muscles_v.record(&a_MVL06[0].soma.v(0.5)) } ')
h.v_MVL06_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL07/0/GenericMuscleCell/v
h(' objectvar v_MVL07_v_muscles_v ')
h(' { v_MVL07_v_muscles_v = new Vector() } ')
h(' { v_MVL07_v_muscles_v.record(&a_MVL07[0].soma.v(0.5)) } ')
h.v_MVL07_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL08/0/GenericMuscleCell/v
h(' objectvar v_MVL08_v_muscles_v ')
h(' { v_MVL08_v_muscles_v = new Vector() } ')
h(' { v_MVL08_v_muscles_v.record(&a_MVL08[0].soma.v(0.5)) } ')
h.v_MVL08_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL09/0/GenericMuscleCell/v
h(' objectvar v_MVL09_v_muscles_v ')
h(' { v_MVL09_v_muscles_v = new Vector() } ')
h(' { v_MVL09_v_muscles_v.record(&a_MVL09[0].soma.v(0.5)) } ')
h.v_MVL09_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL10/0/GenericMuscleCell/v
h(' objectvar v_MVL10_v_muscles_v ')
h(' { v_MVL10_v_muscles_v = new Vector() } ')
h(' { v_MVL10_v_muscles_v.record(&a_MVL10[0].soma.v(0.5)) } ')
h.v_MVL10_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL11/0/GenericMuscleCell/v
h(' objectvar v_MVL11_v_muscles_v ')
h(' { v_MVL11_v_muscles_v = new Vector() } ')
h(' { v_MVL11_v_muscles_v.record(&a_MVL11[0].soma.v(0.5)) } ')
h.v_MVL11_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL12/0/GenericMuscleCell/v
h(' objectvar v_MVL12_v_muscles_v ')
h(' { v_MVL12_v_muscles_v = new Vector() } ')
h(' { v_MVL12_v_muscles_v.record(&a_MVL12[0].soma.v(0.5)) } ')
h.v_MVL12_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL13/0/GenericMuscleCell/v
h(' objectvar v_MVL13_v_muscles_v ')
h(' { v_MVL13_v_muscles_v = new Vector() } ')
h(' { v_MVL13_v_muscles_v.record(&a_MVL13[0].soma.v(0.5)) } ')
h.v_MVL13_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL14/0/GenericMuscleCell/v
h(' objectvar v_MVL14_v_muscles_v ')
h(' { v_MVL14_v_muscles_v = new Vector() } ')
h(' { v_MVL14_v_muscles_v.record(&a_MVL14[0].soma.v(0.5)) } ')
h.v_MVL14_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL15/0/GenericMuscleCell/v
h(' objectvar v_MVL15_v_muscles_v ')
h(' { v_MVL15_v_muscles_v = new Vector() } ')
h(' { v_MVL15_v_muscles_v.record(&a_MVL15[0].soma.v(0.5)) } ')
h.v_MVL15_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL16/0/GenericMuscleCell/v
h(' objectvar v_MVL16_v_muscles_v ')
h(' { v_MVL16_v_muscles_v = new Vector() } ')
h(' { v_MVL16_v_muscles_v.record(&a_MVL16[0].soma.v(0.5)) } ')
h.v_MVL16_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL17/0/GenericMuscleCell/v
h(' objectvar v_MVL17_v_muscles_v ')
h(' { v_MVL17_v_muscles_v = new Vector() } ')
h(' { v_MVL17_v_muscles_v.record(&a_MVL17[0].soma.v(0.5)) } ')
h.v_MVL17_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL18/0/GenericMuscleCell/v
h(' objectvar v_MVL18_v_muscles_v ')
h(' { v_MVL18_v_muscles_v = new Vector() } ')
h(' { v_MVL18_v_muscles_v.record(&a_MVL18[0].soma.v(0.5)) } ')
h.v_MVL18_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL19/0/GenericMuscleCell/v
h(' objectvar v_MVL19_v_muscles_v ')
h(' { v_MVL19_v_muscles_v = new Vector() } ')
h(' { v_MVL19_v_muscles_v.record(&a_MVL19[0].soma.v(0.5)) } ')
h.v_MVL19_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL20/0/GenericMuscleCell/v
h(' objectvar v_MVL20_v_muscles_v ')
h(' { v_MVL20_v_muscles_v = new Vector() } ')
h(' { v_MVL20_v_muscles_v.record(&a_MVL20[0].soma.v(0.5)) } ')
h.v_MVL20_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL21/0/GenericMuscleCell/v
h(' objectvar v_MVL21_v_muscles_v ')
h(' { v_MVL21_v_muscles_v = new Vector() } ')
h(' { v_MVL21_v_muscles_v.record(&a_MVL21[0].soma.v(0.5)) } ')
h.v_MVL21_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL22/0/GenericMuscleCell/v
h(' objectvar v_MVL22_v_muscles_v ')
h(' { v_MVL22_v_muscles_v = new Vector() } ')
h(' { v_MVL22_v_muscles_v.record(&a_MVL22[0].soma.v(0.5)) } ')
h.v_MVL22_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL23/0/GenericMuscleCell/v
h(' objectvar v_MVL23_v_muscles_v ')
h(' { v_MVL23_v_muscles_v = new Vector() } ')
h(' { v_MVL23_v_muscles_v.record(&a_MVL23[0].soma.v(0.5)) } ')
h.v_MVL23_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL24/0/GenericMuscleCell/v
h(' objectvar v_MVL24_v_muscles_v ')
h(' { v_MVL24_v_muscles_v = new Vector() } ')
h(' { v_MVL24_v_muscles_v.record(&a_MVL24[0].soma.v(0.5)) } ')
h.v_MVL24_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL01/0/GenericMuscleCell/v
h(' objectvar v_MDL01_v_muscles_v ')
h(' { v_MDL01_v_muscles_v = new Vector() } ')
h(' { v_MDL01_v_muscles_v.record(&a_MDL01[0].soma.v(0.5)) } ')
h.v_MDL01_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL02/0/GenericMuscleCell/v
h(' objectvar v_MDL02_v_muscles_v ')
h(' { v_MDL02_v_muscles_v = new Vector() } ')
h(' { v_MDL02_v_muscles_v.record(&a_MDL02[0].soma.v(0.5)) } ')
h.v_MDL02_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL03/0/GenericMuscleCell/v
h(' objectvar v_MDL03_v_muscles_v ')
h(' { v_MDL03_v_muscles_v = new Vector() } ')
h(' { v_MDL03_v_muscles_v.record(&a_MDL03[0].soma.v(0.5)) } ')
h.v_MDL03_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL04/0/GenericMuscleCell/v
h(' objectvar v_MDL04_v_muscles_v ')
h(' { v_MDL04_v_muscles_v = new Vector() } ')
h(' { v_MDL04_v_muscles_v.record(&a_MDL04[0].soma.v(0.5)) } ')
h.v_MDL04_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL05/0/GenericMuscleCell/v
h(' objectvar v_MDL05_v_muscles_v ')
h(' { v_MDL05_v_muscles_v = new Vector() } ')
h(' { v_MDL05_v_muscles_v.record(&a_MDL05[0].soma.v(0.5)) } ')
h.v_MDL05_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL06/0/GenericMuscleCell/v
h(' objectvar v_MDL06_v_muscles_v ')
h(' { v_MDL06_v_muscles_v = new Vector() } ')
h(' { v_MDL06_v_muscles_v.record(&a_MDL06[0].soma.v(0.5)) } ')
h.v_MDL06_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL07/0/GenericMuscleCell/v
h(' objectvar v_MDL07_v_muscles_v ')
h(' { v_MDL07_v_muscles_v = new Vector() } ')
h(' { v_MDL07_v_muscles_v.record(&a_MDL07[0].soma.v(0.5)) } ')
h.v_MDL07_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL08/0/GenericMuscleCell/v
h(' objectvar v_MDL08_v_muscles_v ')
h(' { v_MDL08_v_muscles_v = new Vector() } ')
h(' { v_MDL08_v_muscles_v.record(&a_MDL08[0].soma.v(0.5)) } ')
h.v_MDL08_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL09/0/GenericMuscleCell/v
h(' objectvar v_MDL09_v_muscles_v ')
h(' { v_MDL09_v_muscles_v = new Vector() } ')
h(' { v_MDL09_v_muscles_v.record(&a_MDL09[0].soma.v(0.5)) } ')
h.v_MDL09_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL10/0/GenericMuscleCell/v
h(' objectvar v_MDL10_v_muscles_v ')
h(' { v_MDL10_v_muscles_v = new Vector() } ')
h(' { v_MDL10_v_muscles_v.record(&a_MDL10[0].soma.v(0.5)) } ')
h.v_MDL10_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL11/0/GenericMuscleCell/v
h(' objectvar v_MDL11_v_muscles_v ')
h(' { v_MDL11_v_muscles_v = new Vector() } ')
h(' { v_MDL11_v_muscles_v.record(&a_MDL11[0].soma.v(0.5)) } ')
h.v_MDL11_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL12/0/GenericMuscleCell/v
h(' objectvar v_MDL12_v_muscles_v ')
h(' { v_MDL12_v_muscles_v = new Vector() } ')
h(' { v_MDL12_v_muscles_v.record(&a_MDL12[0].soma.v(0.5)) } ')
h.v_MDL12_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL13/0/GenericMuscleCell/v
h(' objectvar v_MDL13_v_muscles_v ')
h(' { v_MDL13_v_muscles_v = new Vector() } ')
h(' { v_MDL13_v_muscles_v.record(&a_MDL13[0].soma.v(0.5)) } ')
h.v_MDL13_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL14/0/GenericMuscleCell/v
h(' objectvar v_MDL14_v_muscles_v ')
h(' { v_MDL14_v_muscles_v = new Vector() } ')
h(' { v_MDL14_v_muscles_v.record(&a_MDL14[0].soma.v(0.5)) } ')
h.v_MDL14_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL15/0/GenericMuscleCell/v
h(' objectvar v_MDL15_v_muscles_v ')
h(' { v_MDL15_v_muscles_v = new Vector() } ')
h(' { v_MDL15_v_muscles_v.record(&a_MDL15[0].soma.v(0.5)) } ')
h.v_MDL15_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL16/0/GenericMuscleCell/v
h(' objectvar v_MDL16_v_muscles_v ')
h(' { v_MDL16_v_muscles_v = new Vector() } ')
h(' { v_MDL16_v_muscles_v.record(&a_MDL16[0].soma.v(0.5)) } ')
h.v_MDL16_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL17/0/GenericMuscleCell/v
h(' objectvar v_MDL17_v_muscles_v ')
h(' { v_MDL17_v_muscles_v = new Vector() } ')
h(' { v_MDL17_v_muscles_v.record(&a_MDL17[0].soma.v(0.5)) } ')
h.v_MDL17_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL18/0/GenericMuscleCell/v
h(' objectvar v_MDL18_v_muscles_v ')
h(' { v_MDL18_v_muscles_v = new Vector() } ')
h(' { v_MDL18_v_muscles_v.record(&a_MDL18[0].soma.v(0.5)) } ')
h.v_MDL18_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL19/0/GenericMuscleCell/v
h(' objectvar v_MDL19_v_muscles_v ')
h(' { v_MDL19_v_muscles_v = new Vector() } ')
h(' { v_MDL19_v_muscles_v.record(&a_MDL19[0].soma.v(0.5)) } ')
h.v_MDL19_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL20/0/GenericMuscleCell/v
h(' objectvar v_MDL20_v_muscles_v ')
h(' { v_MDL20_v_muscles_v = new Vector() } ')
h(' { v_MDL20_v_muscles_v.record(&a_MDL20[0].soma.v(0.5)) } ')
h.v_MDL20_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL21/0/GenericMuscleCell/v
h(' objectvar v_MDL21_v_muscles_v ')
h(' { v_MDL21_v_muscles_v = new Vector() } ')
h(' { v_MDL21_v_muscles_v.record(&a_MDL21[0].soma.v(0.5)) } ')
h.v_MDL21_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL22/0/GenericMuscleCell/v
h(' objectvar v_MDL22_v_muscles_v ')
h(' { v_MDL22_v_muscles_v = new Vector() } ')
h(' { v_MDL22_v_muscles_v.record(&a_MDL22[0].soma.v(0.5)) } ')
h.v_MDL22_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL23/0/GenericMuscleCell/v
h(' objectvar v_MDL23_v_muscles_v ')
h(' { v_MDL23_v_muscles_v = new Vector() } ')
h(' { v_MDL23_v_muscles_v.record(&a_MDL23[0].soma.v(0.5)) } ')
h.v_MDL23_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL24/0/GenericMuscleCell/v
h(' objectvar v_MDL24_v_muscles_v ')
h(' { v_MDL24_v_muscles_v = new Vector() } ')
h(' { v_MDL24_v_muscles_v.record(&a_MDL24[0].soma.v(0.5)) } ')
h.v_MDL24_v_muscles_v.resize((h.tstop * h.steps_per_ms) + 1)
# ###################### File to save: c302_C2_AS_DA_DB.muscles.activity.dat (muscles_activity)
# Column: MDR01/0/GenericMuscleCell/caConc
h(' objectvar v_MDR01_v_muscles_activity ')
h(' { v_MDR01_v_muscles_activity = new Vector() } ')
h(' { v_MDR01_v_muscles_activity.record(&a_MDR01[0].soma.cai(0.5)) } ')
h.v_MDR01_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR02/0/GenericMuscleCell/caConc
h(' objectvar v_MDR02_v_muscles_activity ')
h(' { v_MDR02_v_muscles_activity = new Vector() } ')
h(' { v_MDR02_v_muscles_activity.record(&a_MDR02[0].soma.cai(0.5)) } ')
h.v_MDR02_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR03/0/GenericMuscleCell/caConc
h(' objectvar v_MDR03_v_muscles_activity ')
h(' { v_MDR03_v_muscles_activity = new Vector() } ')
h(' { v_MDR03_v_muscles_activity.record(&a_MDR03[0].soma.cai(0.5)) } ')
h.v_MDR03_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR04/0/GenericMuscleCell/caConc
h(' objectvar v_MDR04_v_muscles_activity ')
h(' { v_MDR04_v_muscles_activity = new Vector() } ')
h(' { v_MDR04_v_muscles_activity.record(&a_MDR04[0].soma.cai(0.5)) } ')
h.v_MDR04_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR05/0/GenericMuscleCell/caConc
h(' objectvar v_MDR05_v_muscles_activity ')
h(' { v_MDR05_v_muscles_activity = new Vector() } ')
h(' { v_MDR05_v_muscles_activity.record(&a_MDR05[0].soma.cai(0.5)) } ')
h.v_MDR05_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR06/0/GenericMuscleCell/caConc
h(' objectvar v_MDR06_v_muscles_activity ')
h(' { v_MDR06_v_muscles_activity = new Vector() } ')
h(' { v_MDR06_v_muscles_activity.record(&a_MDR06[0].soma.cai(0.5)) } ')
h.v_MDR06_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR07/0/GenericMuscleCell/caConc
h(' objectvar v_MDR07_v_muscles_activity ')
h(' { v_MDR07_v_muscles_activity = new Vector() } ')
h(' { v_MDR07_v_muscles_activity.record(&a_MDR07[0].soma.cai(0.5)) } ')
h.v_MDR07_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR08/0/GenericMuscleCell/caConc
h(' objectvar v_MDR08_v_muscles_activity ')
h(' { v_MDR08_v_muscles_activity = new Vector() } ')
h(' { v_MDR08_v_muscles_activity.record(&a_MDR08[0].soma.cai(0.5)) } ')
h.v_MDR08_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR09/0/GenericMuscleCell/caConc
h(' objectvar v_MDR09_v_muscles_activity ')
h(' { v_MDR09_v_muscles_activity = new Vector() } ')
h(' { v_MDR09_v_muscles_activity.record(&a_MDR09[0].soma.cai(0.5)) } ')
h.v_MDR09_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR10/0/GenericMuscleCell/caConc
h(' objectvar v_MDR10_v_muscles_activity ')
h(' { v_MDR10_v_muscles_activity = new Vector() } ')
h(' { v_MDR10_v_muscles_activity.record(&a_MDR10[0].soma.cai(0.5)) } ')
h.v_MDR10_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR11/0/GenericMuscleCell/caConc
h(' objectvar v_MDR11_v_muscles_activity ')
h(' { v_MDR11_v_muscles_activity = new Vector() } ')
h(' { v_MDR11_v_muscles_activity.record(&a_MDR11[0].soma.cai(0.5)) } ')
h.v_MDR11_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR12/0/GenericMuscleCell/caConc
h(' objectvar v_MDR12_v_muscles_activity ')
h(' { v_MDR12_v_muscles_activity = new Vector() } ')
h(' { v_MDR12_v_muscles_activity.record(&a_MDR12[0].soma.cai(0.5)) } ')
h.v_MDR12_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR13/0/GenericMuscleCell/caConc
h(' objectvar v_MDR13_v_muscles_activity ')
h(' { v_MDR13_v_muscles_activity = new Vector() } ')
h(' { v_MDR13_v_muscles_activity.record(&a_MDR13[0].soma.cai(0.5)) } ')
h.v_MDR13_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR14/0/GenericMuscleCell/caConc
h(' objectvar v_MDR14_v_muscles_activity ')
h(' { v_MDR14_v_muscles_activity = new Vector() } ')
h(' { v_MDR14_v_muscles_activity.record(&a_MDR14[0].soma.cai(0.5)) } ')
h.v_MDR14_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR15/0/GenericMuscleCell/caConc
h(' objectvar v_MDR15_v_muscles_activity ')
h(' { v_MDR15_v_muscles_activity = new Vector() } ')
h(' { v_MDR15_v_muscles_activity.record(&a_MDR15[0].soma.cai(0.5)) } ')
h.v_MDR15_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR16/0/GenericMuscleCell/caConc
h(' objectvar v_MDR16_v_muscles_activity ')
h(' { v_MDR16_v_muscles_activity = new Vector() } ')
h(' { v_MDR16_v_muscles_activity.record(&a_MDR16[0].soma.cai(0.5)) } ')
h.v_MDR16_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR17/0/GenericMuscleCell/caConc
h(' objectvar v_MDR17_v_muscles_activity ')
h(' { v_MDR17_v_muscles_activity = new Vector() } ')
h(' { v_MDR17_v_muscles_activity.record(&a_MDR17[0].soma.cai(0.5)) } ')
h.v_MDR17_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR18/0/GenericMuscleCell/caConc
h(' objectvar v_MDR18_v_muscles_activity ')
h(' { v_MDR18_v_muscles_activity = new Vector() } ')
h(' { v_MDR18_v_muscles_activity.record(&a_MDR18[0].soma.cai(0.5)) } ')
h.v_MDR18_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR19/0/GenericMuscleCell/caConc
h(' objectvar v_MDR19_v_muscles_activity ')
h(' { v_MDR19_v_muscles_activity = new Vector() } ')
h(' { v_MDR19_v_muscles_activity.record(&a_MDR19[0].soma.cai(0.5)) } ')
h.v_MDR19_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR20/0/GenericMuscleCell/caConc
h(' objectvar v_MDR20_v_muscles_activity ')
h(' { v_MDR20_v_muscles_activity = new Vector() } ')
h(' { v_MDR20_v_muscles_activity.record(&a_MDR20[0].soma.cai(0.5)) } ')
h.v_MDR20_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR21/0/GenericMuscleCell/caConc
h(' objectvar v_MDR21_v_muscles_activity ')
h(' { v_MDR21_v_muscles_activity = new Vector() } ')
h(' { v_MDR21_v_muscles_activity.record(&a_MDR21[0].soma.cai(0.5)) } ')
h.v_MDR21_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR22/0/GenericMuscleCell/caConc
h(' objectvar v_MDR22_v_muscles_activity ')
h(' { v_MDR22_v_muscles_activity = new Vector() } ')
h(' { v_MDR22_v_muscles_activity.record(&a_MDR22[0].soma.cai(0.5)) } ')
h.v_MDR22_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR23/0/GenericMuscleCell/caConc
h(' objectvar v_MDR23_v_muscles_activity ')
h(' { v_MDR23_v_muscles_activity = new Vector() } ')
h(' { v_MDR23_v_muscles_activity.record(&a_MDR23[0].soma.cai(0.5)) } ')
h.v_MDR23_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDR24/0/GenericMuscleCell/caConc
h(' objectvar v_MDR24_v_muscles_activity ')
h(' { v_MDR24_v_muscles_activity = new Vector() } ')
h(' { v_MDR24_v_muscles_activity.record(&a_MDR24[0].soma.cai(0.5)) } ')
h.v_MDR24_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR01/0/GenericMuscleCell/caConc
h(' objectvar v_MVR01_v_muscles_activity ')
h(' { v_MVR01_v_muscles_activity = new Vector() } ')
h(' { v_MVR01_v_muscles_activity.record(&a_MVR01[0].soma.cai(0.5)) } ')
h.v_MVR01_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR02/0/GenericMuscleCell/caConc
h(' objectvar v_MVR02_v_muscles_activity ')
h(' { v_MVR02_v_muscles_activity = new Vector() } ')
h(' { v_MVR02_v_muscles_activity.record(&a_MVR02[0].soma.cai(0.5)) } ')
h.v_MVR02_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR03/0/GenericMuscleCell/caConc
h(' objectvar v_MVR03_v_muscles_activity ')
h(' { v_MVR03_v_muscles_activity = new Vector() } ')
h(' { v_MVR03_v_muscles_activity.record(&a_MVR03[0].soma.cai(0.5)) } ')
h.v_MVR03_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR04/0/GenericMuscleCell/caConc
h(' objectvar v_MVR04_v_muscles_activity ')
h(' { v_MVR04_v_muscles_activity = new Vector() } ')
h(' { v_MVR04_v_muscles_activity.record(&a_MVR04[0].soma.cai(0.5)) } ')
h.v_MVR04_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR05/0/GenericMuscleCell/caConc
h(' objectvar v_MVR05_v_muscles_activity ')
h(' { v_MVR05_v_muscles_activity = new Vector() } ')
h(' { v_MVR05_v_muscles_activity.record(&a_MVR05[0].soma.cai(0.5)) } ')
h.v_MVR05_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR06/0/GenericMuscleCell/caConc
h(' objectvar v_MVR06_v_muscles_activity ')
h(' { v_MVR06_v_muscles_activity = new Vector() } ')
h(' { v_MVR06_v_muscles_activity.record(&a_MVR06[0].soma.cai(0.5)) } ')
h.v_MVR06_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR07/0/GenericMuscleCell/caConc
h(' objectvar v_MVR07_v_muscles_activity ')
h(' { v_MVR07_v_muscles_activity = new Vector() } ')
h(' { v_MVR07_v_muscles_activity.record(&a_MVR07[0].soma.cai(0.5)) } ')
h.v_MVR07_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR08/0/GenericMuscleCell/caConc
h(' objectvar v_MVR08_v_muscles_activity ')
h(' { v_MVR08_v_muscles_activity = new Vector() } ')
h(' { v_MVR08_v_muscles_activity.record(&a_MVR08[0].soma.cai(0.5)) } ')
h.v_MVR08_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR09/0/GenericMuscleCell/caConc
h(' objectvar v_MVR09_v_muscles_activity ')
h(' { v_MVR09_v_muscles_activity = new Vector() } ')
h(' { v_MVR09_v_muscles_activity.record(&a_MVR09[0].soma.cai(0.5)) } ')
h.v_MVR09_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR10/0/GenericMuscleCell/caConc
h(' objectvar v_MVR10_v_muscles_activity ')
h(' { v_MVR10_v_muscles_activity = new Vector() } ')
h(' { v_MVR10_v_muscles_activity.record(&a_MVR10[0].soma.cai(0.5)) } ')
h.v_MVR10_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR11/0/GenericMuscleCell/caConc
h(' objectvar v_MVR11_v_muscles_activity ')
h(' { v_MVR11_v_muscles_activity = new Vector() } ')
h(' { v_MVR11_v_muscles_activity.record(&a_MVR11[0].soma.cai(0.5)) } ')
h.v_MVR11_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR12/0/GenericMuscleCell/caConc
h(' objectvar v_MVR12_v_muscles_activity ')
h(' { v_MVR12_v_muscles_activity = new Vector() } ')
h(' { v_MVR12_v_muscles_activity.record(&a_MVR12[0].soma.cai(0.5)) } ')
h.v_MVR12_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR13/0/GenericMuscleCell/caConc
h(' objectvar v_MVR13_v_muscles_activity ')
h(' { v_MVR13_v_muscles_activity = new Vector() } ')
h(' { v_MVR13_v_muscles_activity.record(&a_MVR13[0].soma.cai(0.5)) } ')
h.v_MVR13_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR14/0/GenericMuscleCell/caConc
h(' objectvar v_MVR14_v_muscles_activity ')
h(' { v_MVR14_v_muscles_activity = new Vector() } ')
h(' { v_MVR14_v_muscles_activity.record(&a_MVR14[0].soma.cai(0.5)) } ')
h.v_MVR14_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR15/0/GenericMuscleCell/caConc
h(' objectvar v_MVR15_v_muscles_activity ')
h(' { v_MVR15_v_muscles_activity = new Vector() } ')
h(' { v_MVR15_v_muscles_activity.record(&a_MVR15[0].soma.cai(0.5)) } ')
h.v_MVR15_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR16/0/GenericMuscleCell/caConc
h(' objectvar v_MVR16_v_muscles_activity ')
h(' { v_MVR16_v_muscles_activity = new Vector() } ')
h(' { v_MVR16_v_muscles_activity.record(&a_MVR16[0].soma.cai(0.5)) } ')
h.v_MVR16_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR17/0/GenericMuscleCell/caConc
h(' objectvar v_MVR17_v_muscles_activity ')
h(' { v_MVR17_v_muscles_activity = new Vector() } ')
h(' { v_MVR17_v_muscles_activity.record(&a_MVR17[0].soma.cai(0.5)) } ')
h.v_MVR17_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR18/0/GenericMuscleCell/caConc
h(' objectvar v_MVR18_v_muscles_activity ')
h(' { v_MVR18_v_muscles_activity = new Vector() } ')
h(' { v_MVR18_v_muscles_activity.record(&a_MVR18[0].soma.cai(0.5)) } ')
h.v_MVR18_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR19/0/GenericMuscleCell/caConc
h(' objectvar v_MVR19_v_muscles_activity ')
h(' { v_MVR19_v_muscles_activity = new Vector() } ')
h(' { v_MVR19_v_muscles_activity.record(&a_MVR19[0].soma.cai(0.5)) } ')
h.v_MVR19_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR20/0/GenericMuscleCell/caConc
h(' objectvar v_MVR20_v_muscles_activity ')
h(' { v_MVR20_v_muscles_activity = new Vector() } ')
h(' { v_MVR20_v_muscles_activity.record(&a_MVR20[0].soma.cai(0.5)) } ')
h.v_MVR20_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR21/0/GenericMuscleCell/caConc
h(' objectvar v_MVR21_v_muscles_activity ')
h(' { v_MVR21_v_muscles_activity = new Vector() } ')
h(' { v_MVR21_v_muscles_activity.record(&a_MVR21[0].soma.cai(0.5)) } ')
h.v_MVR21_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR22/0/GenericMuscleCell/caConc
h(' objectvar v_MVR22_v_muscles_activity ')
h(' { v_MVR22_v_muscles_activity = new Vector() } ')
h(' { v_MVR22_v_muscles_activity.record(&a_MVR22[0].soma.cai(0.5)) } ')
h.v_MVR22_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVR23/0/GenericMuscleCell/caConc
h(' objectvar v_MVR23_v_muscles_activity ')
h(' { v_MVR23_v_muscles_activity = new Vector() } ')
h(' { v_MVR23_v_muscles_activity.record(&a_MVR23[0].soma.cai(0.5)) } ')
h.v_MVR23_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL01/0/GenericMuscleCell/caConc
h(' objectvar v_MVL01_v_muscles_activity ')
h(' { v_MVL01_v_muscles_activity = new Vector() } ')
h(' { v_MVL01_v_muscles_activity.record(&a_MVL01[0].soma.cai(0.5)) } ')
h.v_MVL01_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL02/0/GenericMuscleCell/caConc
h(' objectvar v_MVL02_v_muscles_activity ')
h(' { v_MVL02_v_muscles_activity = new Vector() } ')
h(' { v_MVL02_v_muscles_activity.record(&a_MVL02[0].soma.cai(0.5)) } ')
h.v_MVL02_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL03/0/GenericMuscleCell/caConc
h(' objectvar v_MVL03_v_muscles_activity ')
h(' { v_MVL03_v_muscles_activity = new Vector() } ')
h(' { v_MVL03_v_muscles_activity.record(&a_MVL03[0].soma.cai(0.5)) } ')
h.v_MVL03_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL04/0/GenericMuscleCell/caConc
h(' objectvar v_MVL04_v_muscles_activity ')
h(' { v_MVL04_v_muscles_activity = new Vector() } ')
h(' { v_MVL04_v_muscles_activity.record(&a_MVL04[0].soma.cai(0.5)) } ')
h.v_MVL04_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL05/0/GenericMuscleCell/caConc
h(' objectvar v_MVL05_v_muscles_activity ')
h(' { v_MVL05_v_muscles_activity = new Vector() } ')
h(' { v_MVL05_v_muscles_activity.record(&a_MVL05[0].soma.cai(0.5)) } ')
h.v_MVL05_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL06/0/GenericMuscleCell/caConc
h(' objectvar v_MVL06_v_muscles_activity ')
h(' { v_MVL06_v_muscles_activity = new Vector() } ')
h(' { v_MVL06_v_muscles_activity.record(&a_MVL06[0].soma.cai(0.5)) } ')
h.v_MVL06_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL07/0/GenericMuscleCell/caConc
h(' objectvar v_MVL07_v_muscles_activity ')
h(' { v_MVL07_v_muscles_activity = new Vector() } ')
h(' { v_MVL07_v_muscles_activity.record(&a_MVL07[0].soma.cai(0.5)) } ')
h.v_MVL07_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL08/0/GenericMuscleCell/caConc
h(' objectvar v_MVL08_v_muscles_activity ')
h(' { v_MVL08_v_muscles_activity = new Vector() } ')
h(' { v_MVL08_v_muscles_activity.record(&a_MVL08[0].soma.cai(0.5)) } ')
h.v_MVL08_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL09/0/GenericMuscleCell/caConc
h(' objectvar v_MVL09_v_muscles_activity ')
h(' { v_MVL09_v_muscles_activity = new Vector() } ')
h(' { v_MVL09_v_muscles_activity.record(&a_MVL09[0].soma.cai(0.5)) } ')
h.v_MVL09_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL10/0/GenericMuscleCell/caConc
h(' objectvar v_MVL10_v_muscles_activity ')
h(' { v_MVL10_v_muscles_activity = new Vector() } ')
h(' { v_MVL10_v_muscles_activity.record(&a_MVL10[0].soma.cai(0.5)) } ')
h.v_MVL10_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL11/0/GenericMuscleCell/caConc
h(' objectvar v_MVL11_v_muscles_activity ')
h(' { v_MVL11_v_muscles_activity = new Vector() } ')
h(' { v_MVL11_v_muscles_activity.record(&a_MVL11[0].soma.cai(0.5)) } ')
h.v_MVL11_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL12/0/GenericMuscleCell/caConc
h(' objectvar v_MVL12_v_muscles_activity ')
h(' { v_MVL12_v_muscles_activity = new Vector() } ')
h(' { v_MVL12_v_muscles_activity.record(&a_MVL12[0].soma.cai(0.5)) } ')
h.v_MVL12_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL13/0/GenericMuscleCell/caConc
h(' objectvar v_MVL13_v_muscles_activity ')
h(' { v_MVL13_v_muscles_activity = new Vector() } ')
h(' { v_MVL13_v_muscles_activity.record(&a_MVL13[0].soma.cai(0.5)) } ')
h.v_MVL13_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL14/0/GenericMuscleCell/caConc
h(' objectvar v_MVL14_v_muscles_activity ')
h(' { v_MVL14_v_muscles_activity = new Vector() } ')
h(' { v_MVL14_v_muscles_activity.record(&a_MVL14[0].soma.cai(0.5)) } ')
h.v_MVL14_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL15/0/GenericMuscleCell/caConc
h(' objectvar v_MVL15_v_muscles_activity ')
h(' { v_MVL15_v_muscles_activity = new Vector() } ')
h(' { v_MVL15_v_muscles_activity.record(&a_MVL15[0].soma.cai(0.5)) } ')
h.v_MVL15_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL16/0/GenericMuscleCell/caConc
h(' objectvar v_MVL16_v_muscles_activity ')
h(' { v_MVL16_v_muscles_activity = new Vector() } ')
h(' { v_MVL16_v_muscles_activity.record(&a_MVL16[0].soma.cai(0.5)) } ')
h.v_MVL16_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL17/0/GenericMuscleCell/caConc
h(' objectvar v_MVL17_v_muscles_activity ')
h(' { v_MVL17_v_muscles_activity = new Vector() } ')
h(' { v_MVL17_v_muscles_activity.record(&a_MVL17[0].soma.cai(0.5)) } ')
h.v_MVL17_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL18/0/GenericMuscleCell/caConc
h(' objectvar v_MVL18_v_muscles_activity ')
h(' { v_MVL18_v_muscles_activity = new Vector() } ')
h(' { v_MVL18_v_muscles_activity.record(&a_MVL18[0].soma.cai(0.5)) } ')
h.v_MVL18_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL19/0/GenericMuscleCell/caConc
h(' objectvar v_MVL19_v_muscles_activity ')
h(' { v_MVL19_v_muscles_activity = new Vector() } ')
h(' { v_MVL19_v_muscles_activity.record(&a_MVL19[0].soma.cai(0.5)) } ')
h.v_MVL19_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL20/0/GenericMuscleCell/caConc
h(' objectvar v_MVL20_v_muscles_activity ')
h(' { v_MVL20_v_muscles_activity = new Vector() } ')
h(' { v_MVL20_v_muscles_activity.record(&a_MVL20[0].soma.cai(0.5)) } ')
h.v_MVL20_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL21/0/GenericMuscleCell/caConc
h(' objectvar v_MVL21_v_muscles_activity ')
h(' { v_MVL21_v_muscles_activity = new Vector() } ')
h(' { v_MVL21_v_muscles_activity.record(&a_MVL21[0].soma.cai(0.5)) } ')
h.v_MVL21_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL22/0/GenericMuscleCell/caConc
h(' objectvar v_MVL22_v_muscles_activity ')
h(' { v_MVL22_v_muscles_activity = new Vector() } ')
h(' { v_MVL22_v_muscles_activity.record(&a_MVL22[0].soma.cai(0.5)) } ')
h.v_MVL22_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL23/0/GenericMuscleCell/caConc
h(' objectvar v_MVL23_v_muscles_activity ')
h(' { v_MVL23_v_muscles_activity = new Vector() } ')
h(' { v_MVL23_v_muscles_activity.record(&a_MVL23[0].soma.cai(0.5)) } ')
h.v_MVL23_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MVL24/0/GenericMuscleCell/caConc
h(' objectvar v_MVL24_v_muscles_activity ')
h(' { v_MVL24_v_muscles_activity = new Vector() } ')
h(' { v_MVL24_v_muscles_activity.record(&a_MVL24[0].soma.cai(0.5)) } ')
h.v_MVL24_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL01/0/GenericMuscleCell/caConc
h(' objectvar v_MDL01_v_muscles_activity ')
h(' { v_MDL01_v_muscles_activity = new Vector() } ')
h(' { v_MDL01_v_muscles_activity.record(&a_MDL01[0].soma.cai(0.5)) } ')
h.v_MDL01_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL02/0/GenericMuscleCell/caConc
h(' objectvar v_MDL02_v_muscles_activity ')
h(' { v_MDL02_v_muscles_activity = new Vector() } ')
h(' { v_MDL02_v_muscles_activity.record(&a_MDL02[0].soma.cai(0.5)) } ')
h.v_MDL02_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL03/0/GenericMuscleCell/caConc
h(' objectvar v_MDL03_v_muscles_activity ')
h(' { v_MDL03_v_muscles_activity = new Vector() } ')
h(' { v_MDL03_v_muscles_activity.record(&a_MDL03[0].soma.cai(0.5)) } ')
h.v_MDL03_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL04/0/GenericMuscleCell/caConc
h(' objectvar v_MDL04_v_muscles_activity ')
h(' { v_MDL04_v_muscles_activity = new Vector() } ')
h(' { v_MDL04_v_muscles_activity.record(&a_MDL04[0].soma.cai(0.5)) } ')
h.v_MDL04_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL05/0/GenericMuscleCell/caConc
h(' objectvar v_MDL05_v_muscles_activity ')
h(' { v_MDL05_v_muscles_activity = new Vector() } ')
h(' { v_MDL05_v_muscles_activity.record(&a_MDL05[0].soma.cai(0.5)) } ')
h.v_MDL05_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL06/0/GenericMuscleCell/caConc
h(' objectvar v_MDL06_v_muscles_activity ')
h(' { v_MDL06_v_muscles_activity = new Vector() } ')
h(' { v_MDL06_v_muscles_activity.record(&a_MDL06[0].soma.cai(0.5)) } ')
h.v_MDL06_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL07/0/GenericMuscleCell/caConc
h(' objectvar v_MDL07_v_muscles_activity ')
h(' { v_MDL07_v_muscles_activity = new Vector() } ')
h(' { v_MDL07_v_muscles_activity.record(&a_MDL07[0].soma.cai(0.5)) } ')
h.v_MDL07_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL08/0/GenericMuscleCell/caConc
h(' objectvar v_MDL08_v_muscles_activity ')
h(' { v_MDL08_v_muscles_activity = new Vector() } ')
h(' { v_MDL08_v_muscles_activity.record(&a_MDL08[0].soma.cai(0.5)) } ')
h.v_MDL08_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL09/0/GenericMuscleCell/caConc
h(' objectvar v_MDL09_v_muscles_activity ')
h(' { v_MDL09_v_muscles_activity = new Vector() } ')
h(' { v_MDL09_v_muscles_activity.record(&a_MDL09[0].soma.cai(0.5)) } ')
h.v_MDL09_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL10/0/GenericMuscleCell/caConc
h(' objectvar v_MDL10_v_muscles_activity ')
h(' { v_MDL10_v_muscles_activity = new Vector() } ')
h(' { v_MDL10_v_muscles_activity.record(&a_MDL10[0].soma.cai(0.5)) } ')
h.v_MDL10_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL11/0/GenericMuscleCell/caConc
h(' objectvar v_MDL11_v_muscles_activity ')
h(' { v_MDL11_v_muscles_activity = new Vector() } ')
h(' { v_MDL11_v_muscles_activity.record(&a_MDL11[0].soma.cai(0.5)) } ')
h.v_MDL11_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL12/0/GenericMuscleCell/caConc
h(' objectvar v_MDL12_v_muscles_activity ')
h(' { v_MDL12_v_muscles_activity = new Vector() } ')
h(' { v_MDL12_v_muscles_activity.record(&a_MDL12[0].soma.cai(0.5)) } ')
h.v_MDL12_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL13/0/GenericMuscleCell/caConc
h(' objectvar v_MDL13_v_muscles_activity ')
h(' { v_MDL13_v_muscles_activity = new Vector() } ')
h(' { v_MDL13_v_muscles_activity.record(&a_MDL13[0].soma.cai(0.5)) } ')
h.v_MDL13_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL14/0/GenericMuscleCell/caConc
h(' objectvar v_MDL14_v_muscles_activity ')
h(' { v_MDL14_v_muscles_activity = new Vector() } ')
h(' { v_MDL14_v_muscles_activity.record(&a_MDL14[0].soma.cai(0.5)) } ')
h.v_MDL14_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL15/0/GenericMuscleCell/caConc
h(' objectvar v_MDL15_v_muscles_activity ')
h(' { v_MDL15_v_muscles_activity = new Vector() } ')
h(' { v_MDL15_v_muscles_activity.record(&a_MDL15[0].soma.cai(0.5)) } ')
h.v_MDL15_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL16/0/GenericMuscleCell/caConc
h(' objectvar v_MDL16_v_muscles_activity ')
h(' { v_MDL16_v_muscles_activity = new Vector() } ')
h(' { v_MDL16_v_muscles_activity.record(&a_MDL16[0].soma.cai(0.5)) } ')
h.v_MDL16_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL17/0/GenericMuscleCell/caConc
h(' objectvar v_MDL17_v_muscles_activity ')
h(' { v_MDL17_v_muscles_activity = new Vector() } ')
h(' { v_MDL17_v_muscles_activity.record(&a_MDL17[0].soma.cai(0.5)) } ')
h.v_MDL17_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL18/0/GenericMuscleCell/caConc
h(' objectvar v_MDL18_v_muscles_activity ')
h(' { v_MDL18_v_muscles_activity = new Vector() } ')
h(' { v_MDL18_v_muscles_activity.record(&a_MDL18[0].soma.cai(0.5)) } ')
h.v_MDL18_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL19/0/GenericMuscleCell/caConc
h(' objectvar v_MDL19_v_muscles_activity ')
h(' { v_MDL19_v_muscles_activity = new Vector() } ')
h(' { v_MDL19_v_muscles_activity.record(&a_MDL19[0].soma.cai(0.5)) } ')
h.v_MDL19_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL20/0/GenericMuscleCell/caConc
h(' objectvar v_MDL20_v_muscles_activity ')
h(' { v_MDL20_v_muscles_activity = new Vector() } ')
h(' { v_MDL20_v_muscles_activity.record(&a_MDL20[0].soma.cai(0.5)) } ')
h.v_MDL20_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL21/0/GenericMuscleCell/caConc
h(' objectvar v_MDL21_v_muscles_activity ')
h(' { v_MDL21_v_muscles_activity = new Vector() } ')
h(' { v_MDL21_v_muscles_activity.record(&a_MDL21[0].soma.cai(0.5)) } ')
h.v_MDL21_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL22/0/GenericMuscleCell/caConc
h(' objectvar v_MDL22_v_muscles_activity ')
h(' { v_MDL22_v_muscles_activity = new Vector() } ')
h(' { v_MDL22_v_muscles_activity.record(&a_MDL22[0].soma.cai(0.5)) } ')
h.v_MDL22_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL23/0/GenericMuscleCell/caConc
h(' objectvar v_MDL23_v_muscles_activity ')
h(' { v_MDL23_v_muscles_activity = new Vector() } ')
h(' { v_MDL23_v_muscles_activity.record(&a_MDL23[0].soma.cai(0.5)) } ')
h.v_MDL23_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# Column: MDL24/0/GenericMuscleCell/caConc
h(' objectvar v_MDL24_v_muscles_activity ')
h(' { v_MDL24_v_muscles_activity = new Vector() } ')
h(' { v_MDL24_v_muscles_activity.record(&a_MDL24[0].soma.cai(0.5)) } ')
h.v_MDL24_v_muscles_activity.resize((h.tstop * h.steps_per_ms) + 1)
# ###################### File to save: c302_C2_AS_DA_DB.dat (neurons_v)
# Column: AS1/0/GenericNeuronCell/v
h(' objectvar v_AS1_v_neurons_v ')
h(' { v_AS1_v_neurons_v = new Vector() } ')
h(' { v_AS1_v_neurons_v.record(&a_AS1[0].soma.v(0.5)) } ')
h.v_AS1_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS10/0/GenericNeuronCell/v
h(' objectvar v_AS10_v_neurons_v ')
h(' { v_AS10_v_neurons_v = new Vector() } ')
h(' { v_AS10_v_neurons_v.record(&a_AS10[0].soma.v(0.5)) } ')
h.v_AS10_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS11/0/GenericNeuronCell/v
h(' objectvar v_AS11_v_neurons_v ')
h(' { v_AS11_v_neurons_v = new Vector() } ')
h(' { v_AS11_v_neurons_v.record(&a_AS11[0].soma.v(0.5)) } ')
h.v_AS11_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS2/0/GenericNeuronCell/v
h(' objectvar v_AS2_v_neurons_v ')
h(' { v_AS2_v_neurons_v = new Vector() } ')
h(' { v_AS2_v_neurons_v.record(&a_AS2[0].soma.v(0.5)) } ')
h.v_AS2_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS3/0/GenericNeuronCell/v
h(' objectvar v_AS3_v_neurons_v ')
h(' { v_AS3_v_neurons_v = new Vector() } ')
h(' { v_AS3_v_neurons_v.record(&a_AS3[0].soma.v(0.5)) } ')
h.v_AS3_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS4/0/GenericNeuronCell/v
h(' objectvar v_AS4_v_neurons_v ')
h(' { v_AS4_v_neurons_v = new Vector() } ')
h(' { v_AS4_v_neurons_v.record(&a_AS4[0].soma.v(0.5)) } ')
h.v_AS4_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS5/0/GenericNeuronCell/v
h(' objectvar v_AS5_v_neurons_v ')
h(' { v_AS5_v_neurons_v = new Vector() } ')
h(' { v_AS5_v_neurons_v.record(&a_AS5[0].soma.v(0.5)) } ')
h.v_AS5_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS6/0/GenericNeuronCell/v
h(' objectvar v_AS6_v_neurons_v ')
h(' { v_AS6_v_neurons_v = new Vector() } ')
h(' { v_AS6_v_neurons_v.record(&a_AS6[0].soma.v(0.5)) } ')
h.v_AS6_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS7/0/GenericNeuronCell/v
h(' objectvar v_AS7_v_neurons_v ')
h(' { v_AS7_v_neurons_v = new Vector() } ')
h(' { v_AS7_v_neurons_v.record(&a_AS7[0].soma.v(0.5)) } ')
h.v_AS7_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS8/0/GenericNeuronCell/v
h(' objectvar v_AS8_v_neurons_v ')
h(' { v_AS8_v_neurons_v = new Vector() } ')
h(' { v_AS8_v_neurons_v.record(&a_AS8[0].soma.v(0.5)) } ')
h.v_AS8_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AS9/0/GenericNeuronCell/v
h(' objectvar v_AS9_v_neurons_v ')
h(' { v_AS9_v_neurons_v = new Vector() } ')
h(' { v_AS9_v_neurons_v.record(&a_AS9[0].soma.v(0.5)) } ')
h.v_AS9_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AVAL/0/GenericNeuronCell/v
h(' objectvar v_AVAL_v_neurons_v ')
h(' { v_AVAL_v_neurons_v = new Vector() } ')
h(' { v_AVAL_v_neurons_v.record(&a_AVAL[0].soma.v(0.5)) } ')
h.v_AVAL_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AVAR/0/GenericNeuronCell/v
h(' objectvar v_AVAR_v_neurons_v ')
h(' { v_AVAR_v_neurons_v = new Vector() } ')
h(' { v_AVAR_v_neurons_v.record(&a_AVAR[0].soma.v(0.5)) } ')
h.v_AVAR_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AVBL/0/GenericNeuronCell/v
h(' objectvar v_AVBL_v_neurons_v ')
h(' { v_AVBL_v_neurons_v = new Vector() } ')
h(' { v_AVBL_v_neurons_v.record(&a_AVBL[0].soma.v(0.5)) } ')
h.v_AVBL_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: AVBR/0/GenericNeuronCell/v
h(' objectvar v_AVBR_v_neurons_v ')
h(' { v_AVBR_v_neurons_v = new Vector() } ')
h(' { v_AVBR_v_neurons_v.record(&a_AVBR[0].soma.v(0.5)) } ')
h.v_AVBR_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA1/0/GenericNeuronCell/v
h(' objectvar v_DA1_v_neurons_v ')
h(' { v_DA1_v_neurons_v = new Vector() } ')
h(' { v_DA1_v_neurons_v.record(&a_DA1[0].soma.v(0.5)) } ')
h.v_DA1_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA2/0/GenericNeuronCell/v
h(' objectvar v_DA2_v_neurons_v ')
h(' { v_DA2_v_neurons_v = new Vector() } ')
h(' { v_DA2_v_neurons_v.record(&a_DA2[0].soma.v(0.5)) } ')
h.v_DA2_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA3/0/GenericNeuronCell/v
h(' objectvar v_DA3_v_neurons_v ')
h(' { v_DA3_v_neurons_v = new Vector() } ')
h(' { v_DA3_v_neurons_v.record(&a_DA3[0].soma.v(0.5)) } ')
h.v_DA3_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA4/0/GenericNeuronCell/v
h(' objectvar v_DA4_v_neurons_v ')
h(' { v_DA4_v_neurons_v = new Vector() } ')
h(' { v_DA4_v_neurons_v.record(&a_DA4[0].soma.v(0.5)) } ')
h.v_DA4_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA5/0/GenericNeuronCell/v
h(' objectvar v_DA5_v_neurons_v ')
h(' { v_DA5_v_neurons_v = new Vector() } ')
h(' { v_DA5_v_neurons_v.record(&a_DA5[0].soma.v(0.5)) } ')
h.v_DA5_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA6/0/GenericNeuronCell/v
h(' objectvar v_DA6_v_neurons_v ')
h(' { v_DA6_v_neurons_v = new Vector() } ')
h(' { v_DA6_v_neurons_v.record(&a_DA6[0].soma.v(0.5)) } ')
h.v_DA6_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA7/0/GenericNeuronCell/v
h(' objectvar v_DA7_v_neurons_v ')
h(' { v_DA7_v_neurons_v = new Vector() } ')
h(' { v_DA7_v_neurons_v.record(&a_DA7[0].soma.v(0.5)) } ')
h.v_DA7_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA8/0/GenericNeuronCell/v
h(' objectvar v_DA8_v_neurons_v ')
h(' { v_DA8_v_neurons_v = new Vector() } ')
h(' { v_DA8_v_neurons_v.record(&a_DA8[0].soma.v(0.5)) } ')
h.v_DA8_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DA9/0/GenericNeuronCell/v
h(' objectvar v_DA9_v_neurons_v ')
h(' { v_DA9_v_neurons_v = new Vector() } ')
h(' { v_DA9_v_neurons_v.record(&a_DA9[0].soma.v(0.5)) } ')
h.v_DA9_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DB1/0/GenericNeuronCell/v
h(' objectvar v_DB1_v_neurons_v ')
h(' { v_DB1_v_neurons_v = new Vector() } ')
h(' { v_DB1_v_neurons_v.record(&a_DB1[0].soma.v(0.5)) } ')
h.v_DB1_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DB2/0/GenericNeuronCell/v
h(' objectvar v_DB2_v_neurons_v ')
h(' { v_DB2_v_neurons_v = new Vector() } ')
h(' { v_DB2_v_neurons_v.record(&a_DB2[0].soma.v(0.5)) } ')
h.v_DB2_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DB3/0/GenericNeuronCell/v
h(' objectvar v_DB3_v_neurons_v ')
h(' { v_DB3_v_neurons_v = new Vector() } ')
h(' { v_DB3_v_neurons_v.record(&a_DB3[0].soma.v(0.5)) } ')
h.v_DB3_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DB4/0/GenericNeuronCell/v
h(' objectvar v_DB4_v_neurons_v ')
h(' { v_DB4_v_neurons_v = new Vector() } ')
h(' { v_DB4_v_neurons_v.record(&a_DB4[0].soma.v(0.5)) } ')
h.v_DB4_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DB5/0/GenericNeuronCell/v
h(' objectvar v_DB5_v_neurons_v ')
h(' { v_DB5_v_neurons_v = new Vector() } ')
h(' { v_DB5_v_neurons_v.record(&a_DB5[0].soma.v(0.5)) } ')
h.v_DB5_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DB6/0/GenericNeuronCell/v
h(' objectvar v_DB6_v_neurons_v ')
h(' { v_DB6_v_neurons_v = new Vector() } ')
h(' { v_DB6_v_neurons_v.record(&a_DB6[0].soma.v(0.5)) } ')
h.v_DB6_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# Column: DB7/0/GenericNeuronCell/v
h(' objectvar v_DB7_v_neurons_v ')
h(' { v_DB7_v_neurons_v = new Vector() } ')
h(' { v_DB7_v_neurons_v.record(&a_DB7[0].soma.v(0.5)) } ')
h.v_DB7_v_neurons_v.resize((h.tstop * h.steps_per_ms) + 1)
# ###################### File to save: time.dat (time)
# Column: time
h(' objectvar v_time ')
h(' { v_time = new Vector() } ')
h(' { v_time.record(&t) } ')
h.v_time.resize((h.tstop * h.steps_per_ms) + 1)
self.initialized = False
self.sim_end = -1 # will be overwritten
def run(self):
self.initialized = True
sim_start = time.time()
print("Running a simulation of %sms (dt = %sms; seed=%s)" % (h.tstop, h.dt, self.seed))
h.run()
self.sim_end = time.time()
sim_time = self.sim_end - sim_start
print("Finished NEURON simulation in %f seconds (%f mins)..."%(sim_time, sim_time/60.0))
self.save_results()
def advance(self):
if not self.initialized:
h.finitialize()
self.initialized = True
h.fadvance()
###############################################################################
# Hash function to use in generation of random value
# This is copied from NetPyNE: https://github.com/Neurosim-lab/netpyne/blob/master/netpyne/simFuncs.py
###############################################################################
def _id32 (self,obj):
return int(hashlib.md5(obj).hexdigest()[0:8],16) # convert 8 first chars of md5 hash in base 16 to int
###############################################################################
# Initialize the stim randomizer
# This is copied from NetPyNE: https://github.com/Neurosim-lab/netpyne/blob/master/netpyne/simFuncs.py
###############################################################################
def _init_stim_randomizer(self,rand, stimType, gid, seed):
rand.Random123(self._id32(stimType), gid, seed)
def save_results(self):
print("Saving results at t=%s..."%h.t)
if self.sim_end < 0: self.sim_end = time.time()
# ###################### File to save: time.dat (time)
py_v_time = [ t/1000 for t in h.v_time.to_python() ] # Convert to Python list for speed...
f_time_f2 = open('time.dat', 'w')
num_points = len(py_v_time) # Simulation may have been stopped before tstop...
for i in range(num_points):
f_time_f2.write('%f'% py_v_time[i]) # Save in SI units...
f_time_f2.close()
print("Saved data to: time.dat")
# ###################### File to save: c302_C2_AS_DA_DB.activity.dat (neurons_activity)
py_v_AS1_v_neurons_activity = [ float(x ) for x in h.v_AS1_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_AS10_v_neurons_activity = [ float(x ) for x in h.v_AS10_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_AS11_v_neurons_activity = [ float(x ) for x in h.v_AS11_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_AS2_v_neurons_activity = [ float(x ) for x in h.v_AS2_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_AS3_v_neurons_activity = [ float(x ) for x in h.v_AS3_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_AS4_v_neurons_activity = [ float(x ) for x in h.v_AS4_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_AS5_v_neurons_activity = [ float(x ) for x in h.v_AS5_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_AS6_v_neurons_activity = [ float(x ) for x in h.v_AS6_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_AS7_v_neurons_activity = [ float(x ) for x in h.v_AS7_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_AS8_v_neurons_activity = [ float(x ) for x in h.v_AS8_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_AS9_v_neurons_activity = [ float(x ) for x in h.v_AS9_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_AVAL_v_neurons_activity = [ float(x ) for x in h.v_AVAL_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_AVAR_v_neurons_activity = [ float(x ) for x in h.v_AVAR_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_AVBL_v_neurons_activity = [ float(x ) for x in h.v_AVBL_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_AVBR_v_neurons_activity = [ float(x ) for x in h.v_AVBR_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_DA1_v_neurons_activity = [ float(x ) for x in h.v_DA1_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_DA2_v_neurons_activity = [ float(x ) for x in h.v_DA2_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_DA3_v_neurons_activity = [ float(x ) for x in h.v_DA3_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_DA4_v_neurons_activity = [ float(x ) for x in h.v_DA4_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_DA5_v_neurons_activity = [ float(x ) for x in h.v_DA5_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_DA6_v_neurons_activity = [ float(x ) for x in h.v_DA6_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_DA7_v_neurons_activity = [ float(x ) for x in h.v_DA7_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_DA8_v_neurons_activity = [ float(x ) for x in h.v_DA8_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_DA9_v_neurons_activity = [ float(x ) for x in h.v_DA9_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_DB1_v_neurons_activity = [ float(x ) for x in h.v_DB1_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_DB2_v_neurons_activity = [ float(x ) for x in h.v_DB2_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_DB3_v_neurons_activity = [ float(x ) for x in h.v_DB3_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_DB4_v_neurons_activity = [ float(x ) for x in h.v_DB4_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_DB5_v_neurons_activity = [ float(x ) for x in h.v_DB5_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_DB6_v_neurons_activity = [ float(x ) for x in h.v_DB6_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_DB7_v_neurons_activity = [ float(x ) for x in h.v_DB7_v_neurons_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
f_neurons_activity_f2 = open('c302_C2_AS_DA_DB.activity.dat', 'w')
num_points = len(py_v_time) # Simulation may have been stopped before tstop...
for i in range(num_points):
f_neurons_activity_f2.write('%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t\n' % (py_v_time[i], py_v_AS1_v_neurons_activity[i], py_v_AS10_v_neurons_activity[i], py_v_AS11_v_neurons_activity[i], py_v_AS2_v_neurons_activity[i], py_v_AS3_v_neurons_activity[i], py_v_AS4_v_neurons_activity[i], py_v_AS5_v_neurons_activity[i], py_v_AS6_v_neurons_activity[i], py_v_AS7_v_neurons_activity[i], py_v_AS8_v_neurons_activity[i], py_v_AS9_v_neurons_activity[i], py_v_AVAL_v_neurons_activity[i], py_v_AVAR_v_neurons_activity[i], py_v_AVBL_v_neurons_activity[i], py_v_AVBR_v_neurons_activity[i], py_v_DA1_v_neurons_activity[i], py_v_DA2_v_neurons_activity[i], py_v_DA3_v_neurons_activity[i], py_v_DA4_v_neurons_activity[i], py_v_DA5_v_neurons_activity[i], py_v_DA6_v_neurons_activity[i], py_v_DA7_v_neurons_activity[i], py_v_DA8_v_neurons_activity[i], py_v_DA9_v_neurons_activity[i], py_v_DB1_v_neurons_activity[i], py_v_DB2_v_neurons_activity[i], py_v_DB3_v_neurons_activity[i], py_v_DB4_v_neurons_activity[i], py_v_DB5_v_neurons_activity[i], py_v_DB6_v_neurons_activity[i], py_v_DB7_v_neurons_activity[i], ))
f_neurons_activity_f2.close()
print("Saved data to: c302_C2_AS_DA_DB.activity.dat")
# ###################### File to save: c302_C2_AS_DA_DB.muscles.dat (muscles_v)
py_v_MDR01_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR01_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR02_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR02_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR03_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR03_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR04_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR04_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR05_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR05_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR06_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR06_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR07_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR07_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR08_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR08_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR09_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR09_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR10_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR10_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR11_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR11_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR12_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR12_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR13_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR13_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR14_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR14_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR15_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR15_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR16_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR16_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR17_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR17_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR18_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR18_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR19_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR19_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR20_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR20_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR21_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR21_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR22_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR22_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR23_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR23_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDR24_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDR24_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR01_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR01_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR02_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR02_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR03_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR03_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR04_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR04_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR05_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR05_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR06_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR06_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR07_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR07_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR08_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR08_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR09_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR09_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR10_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR10_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR11_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR11_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR12_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR12_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR13_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR13_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR14_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR14_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR15_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR15_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR16_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR16_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR17_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR17_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR18_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR18_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR19_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR19_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR20_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR20_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR21_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR21_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR22_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR22_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVR23_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVR23_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL01_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL01_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL02_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL02_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL03_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL03_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL04_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL04_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL05_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL05_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL06_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL06_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL07_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL07_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL08_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL08_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL09_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL09_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL10_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL10_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL11_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL11_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL12_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL12_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL13_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL13_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL14_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL14_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL15_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL15_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL16_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL16_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL17_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL17_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL18_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL18_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL19_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL19_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL20_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL20_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL21_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL21_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL22_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL22_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL23_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL23_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MVL24_v_muscles_v = [ float(x / 1000.0) for x in h.v_MVL24_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL01_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL01_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL02_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL02_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL03_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL03_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL04_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL04_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL05_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL05_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL06_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL06_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL07_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL07_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL08_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL08_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL09_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL09_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL10_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL10_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL11_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL11_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL12_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL12_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL13_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL13_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL14_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL14_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL15_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL15_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL16_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL16_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL17_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL17_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL18_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL18_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL19_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL19_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL20_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL20_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL21_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL21_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL22_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL22_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL23_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL23_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_MDL24_v_muscles_v = [ float(x / 1000.0) for x in h.v_MDL24_v_muscles_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
f_muscles_v_f2 = open('c302_C2_AS_DA_DB.muscles.dat', 'w')
num_points = len(py_v_time) # Simulation may have been stopped before tstop...
for i in range(num_points):
f_muscles_v_f2.write('%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t\n' % (py_v_time[i], py_v_MDR01_v_muscles_v[i], py_v_MDR02_v_muscles_v[i], py_v_MDR03_v_muscles_v[i], py_v_MDR04_v_muscles_v[i], py_v_MDR05_v_muscles_v[i], py_v_MDR06_v_muscles_v[i], py_v_MDR07_v_muscles_v[i], py_v_MDR08_v_muscles_v[i], py_v_MDR09_v_muscles_v[i], py_v_MDR10_v_muscles_v[i], py_v_MDR11_v_muscles_v[i], py_v_MDR12_v_muscles_v[i], py_v_MDR13_v_muscles_v[i], py_v_MDR14_v_muscles_v[i], py_v_MDR15_v_muscles_v[i], py_v_MDR16_v_muscles_v[i], py_v_MDR17_v_muscles_v[i], py_v_MDR18_v_muscles_v[i], py_v_MDR19_v_muscles_v[i], py_v_MDR20_v_muscles_v[i], py_v_MDR21_v_muscles_v[i], py_v_MDR22_v_muscles_v[i], py_v_MDR23_v_muscles_v[i], py_v_MDR24_v_muscles_v[i], py_v_MVR01_v_muscles_v[i], py_v_MVR02_v_muscles_v[i], py_v_MVR03_v_muscles_v[i], py_v_MVR04_v_muscles_v[i], py_v_MVR05_v_muscles_v[i], py_v_MVR06_v_muscles_v[i], py_v_MVR07_v_muscles_v[i], py_v_MVR08_v_muscles_v[i], py_v_MVR09_v_muscles_v[i], py_v_MVR10_v_muscles_v[i], py_v_MVR11_v_muscles_v[i], py_v_MVR12_v_muscles_v[i], py_v_MVR13_v_muscles_v[i], py_v_MVR14_v_muscles_v[i], py_v_MVR15_v_muscles_v[i], py_v_MVR16_v_muscles_v[i], py_v_MVR17_v_muscles_v[i], py_v_MVR18_v_muscles_v[i], py_v_MVR19_v_muscles_v[i], py_v_MVR20_v_muscles_v[i], py_v_MVR21_v_muscles_v[i], py_v_MVR22_v_muscles_v[i], py_v_MVR23_v_muscles_v[i], py_v_MVL01_v_muscles_v[i], py_v_MVL02_v_muscles_v[i], py_v_MVL03_v_muscles_v[i], py_v_MVL04_v_muscles_v[i], py_v_MVL05_v_muscles_v[i], py_v_MVL06_v_muscles_v[i], py_v_MVL07_v_muscles_v[i], py_v_MVL08_v_muscles_v[i], py_v_MVL09_v_muscles_v[i], py_v_MVL10_v_muscles_v[i], py_v_MVL11_v_muscles_v[i], py_v_MVL12_v_muscles_v[i], py_v_MVL13_v_muscles_v[i], py_v_MVL14_v_muscles_v[i], py_v_MVL15_v_muscles_v[i], py_v_MVL16_v_muscles_v[i], py_v_MVL17_v_muscles_v[i], py_v_MVL18_v_muscles_v[i], py_v_MVL19_v_muscles_v[i], py_v_MVL20_v_muscles_v[i], py_v_MVL21_v_muscles_v[i], py_v_MVL22_v_muscles_v[i], py_v_MVL23_v_muscles_v[i], py_v_MVL24_v_muscles_v[i], py_v_MDL01_v_muscles_v[i], py_v_MDL02_v_muscles_v[i], py_v_MDL03_v_muscles_v[i], py_v_MDL04_v_muscles_v[i], py_v_MDL05_v_muscles_v[i], py_v_MDL06_v_muscles_v[i], py_v_MDL07_v_muscles_v[i], py_v_MDL08_v_muscles_v[i], py_v_MDL09_v_muscles_v[i], py_v_MDL10_v_muscles_v[i], py_v_MDL11_v_muscles_v[i], py_v_MDL12_v_muscles_v[i], py_v_MDL13_v_muscles_v[i], py_v_MDL14_v_muscles_v[i], py_v_MDL15_v_muscles_v[i], py_v_MDL16_v_muscles_v[i], py_v_MDL17_v_muscles_v[i], py_v_MDL18_v_muscles_v[i], py_v_MDL19_v_muscles_v[i], py_v_MDL20_v_muscles_v[i], py_v_MDL21_v_muscles_v[i], py_v_MDL22_v_muscles_v[i], py_v_MDL23_v_muscles_v[i], py_v_MDL24_v_muscles_v[i], ))
f_muscles_v_f2.close()
print("Saved data to: c302_C2_AS_DA_DB.muscles.dat")
# ###################### File to save: c302_C2_AS_DA_DB.muscles.activity.dat (muscles_activity)
py_v_MDR01_v_muscles_activity = [ float(x ) for x in h.v_MDR01_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR02_v_muscles_activity = [ float(x ) for x in h.v_MDR02_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR03_v_muscles_activity = [ float(x ) for x in h.v_MDR03_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR04_v_muscles_activity = [ float(x ) for x in h.v_MDR04_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR05_v_muscles_activity = [ float(x ) for x in h.v_MDR05_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR06_v_muscles_activity = [ float(x ) for x in h.v_MDR06_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR07_v_muscles_activity = [ float(x ) for x in h.v_MDR07_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR08_v_muscles_activity = [ float(x ) for x in h.v_MDR08_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR09_v_muscles_activity = [ float(x ) for x in h.v_MDR09_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR10_v_muscles_activity = [ float(x ) for x in h.v_MDR10_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR11_v_muscles_activity = [ float(x ) for x in h.v_MDR11_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR12_v_muscles_activity = [ float(x ) for x in h.v_MDR12_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR13_v_muscles_activity = [ float(x ) for x in h.v_MDR13_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR14_v_muscles_activity = [ float(x ) for x in h.v_MDR14_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR15_v_muscles_activity = [ float(x ) for x in h.v_MDR15_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR16_v_muscles_activity = [ float(x ) for x in h.v_MDR16_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR17_v_muscles_activity = [ float(x ) for x in h.v_MDR17_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR18_v_muscles_activity = [ float(x ) for x in h.v_MDR18_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR19_v_muscles_activity = [ float(x ) for x in h.v_MDR19_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR20_v_muscles_activity = [ float(x ) for x in h.v_MDR20_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR21_v_muscles_activity = [ float(x ) for x in h.v_MDR21_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR22_v_muscles_activity = [ float(x ) for x in h.v_MDR22_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR23_v_muscles_activity = [ float(x ) for x in h.v_MDR23_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDR24_v_muscles_activity = [ float(x ) for x in h.v_MDR24_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR01_v_muscles_activity = [ float(x ) for x in h.v_MVR01_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR02_v_muscles_activity = [ float(x ) for x in h.v_MVR02_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR03_v_muscles_activity = [ float(x ) for x in h.v_MVR03_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR04_v_muscles_activity = [ float(x ) for x in h.v_MVR04_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR05_v_muscles_activity = [ float(x ) for x in h.v_MVR05_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR06_v_muscles_activity = [ float(x ) for x in h.v_MVR06_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR07_v_muscles_activity = [ float(x ) for x in h.v_MVR07_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR08_v_muscles_activity = [ float(x ) for x in h.v_MVR08_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR09_v_muscles_activity = [ float(x ) for x in h.v_MVR09_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR10_v_muscles_activity = [ float(x ) for x in h.v_MVR10_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR11_v_muscles_activity = [ float(x ) for x in h.v_MVR11_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR12_v_muscles_activity = [ float(x ) for x in h.v_MVR12_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR13_v_muscles_activity = [ float(x ) for x in h.v_MVR13_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR14_v_muscles_activity = [ float(x ) for x in h.v_MVR14_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR15_v_muscles_activity = [ float(x ) for x in h.v_MVR15_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR16_v_muscles_activity = [ float(x ) for x in h.v_MVR16_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR17_v_muscles_activity = [ float(x ) for x in h.v_MVR17_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR18_v_muscles_activity = [ float(x ) for x in h.v_MVR18_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR19_v_muscles_activity = [ float(x ) for x in h.v_MVR19_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR20_v_muscles_activity = [ float(x ) for x in h.v_MVR20_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR21_v_muscles_activity = [ float(x ) for x in h.v_MVR21_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR22_v_muscles_activity = [ float(x ) for x in h.v_MVR22_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVR23_v_muscles_activity = [ float(x ) for x in h.v_MVR23_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL01_v_muscles_activity = [ float(x ) for x in h.v_MVL01_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL02_v_muscles_activity = [ float(x ) for x in h.v_MVL02_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL03_v_muscles_activity = [ float(x ) for x in h.v_MVL03_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL04_v_muscles_activity = [ float(x ) for x in h.v_MVL04_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL05_v_muscles_activity = [ float(x ) for x in h.v_MVL05_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL06_v_muscles_activity = [ float(x ) for x in h.v_MVL06_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL07_v_muscles_activity = [ float(x ) for x in h.v_MVL07_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL08_v_muscles_activity = [ float(x ) for x in h.v_MVL08_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL09_v_muscles_activity = [ float(x ) for x in h.v_MVL09_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL10_v_muscles_activity = [ float(x ) for x in h.v_MVL10_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL11_v_muscles_activity = [ float(x ) for x in h.v_MVL11_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL12_v_muscles_activity = [ float(x ) for x in h.v_MVL12_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL13_v_muscles_activity = [ float(x ) for x in h.v_MVL13_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL14_v_muscles_activity = [ float(x ) for x in h.v_MVL14_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL15_v_muscles_activity = [ float(x ) for x in h.v_MVL15_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL16_v_muscles_activity = [ float(x ) for x in h.v_MVL16_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL17_v_muscles_activity = [ float(x ) for x in h.v_MVL17_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL18_v_muscles_activity = [ float(x ) for x in h.v_MVL18_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL19_v_muscles_activity = [ float(x ) for x in h.v_MVL19_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL20_v_muscles_activity = [ float(x ) for x in h.v_MVL20_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL21_v_muscles_activity = [ float(x ) for x in h.v_MVL21_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL22_v_muscles_activity = [ float(x ) for x in h.v_MVL22_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL23_v_muscles_activity = [ float(x ) for x in h.v_MVL23_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MVL24_v_muscles_activity = [ float(x ) for x in h.v_MVL24_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL01_v_muscles_activity = [ float(x ) for x in h.v_MDL01_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL02_v_muscles_activity = [ float(x ) for x in h.v_MDL02_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL03_v_muscles_activity = [ float(x ) for x in h.v_MDL03_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL04_v_muscles_activity = [ float(x ) for x in h.v_MDL04_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL05_v_muscles_activity = [ float(x ) for x in h.v_MDL05_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL06_v_muscles_activity = [ float(x ) for x in h.v_MDL06_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL07_v_muscles_activity = [ float(x ) for x in h.v_MDL07_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL08_v_muscles_activity = [ float(x ) for x in h.v_MDL08_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL09_v_muscles_activity = [ float(x ) for x in h.v_MDL09_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL10_v_muscles_activity = [ float(x ) for x in h.v_MDL10_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL11_v_muscles_activity = [ float(x ) for x in h.v_MDL11_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL12_v_muscles_activity = [ float(x ) for x in h.v_MDL12_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL13_v_muscles_activity = [ float(x ) for x in h.v_MDL13_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL14_v_muscles_activity = [ float(x ) for x in h.v_MDL14_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL15_v_muscles_activity = [ float(x ) for x in h.v_MDL15_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL16_v_muscles_activity = [ float(x ) for x in h.v_MDL16_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL17_v_muscles_activity = [ float(x ) for x in h.v_MDL17_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL18_v_muscles_activity = [ float(x ) for x in h.v_MDL18_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL19_v_muscles_activity = [ float(x ) for x in h.v_MDL19_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL20_v_muscles_activity = [ float(x ) for x in h.v_MDL20_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL21_v_muscles_activity = [ float(x ) for x in h.v_MDL21_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL22_v_muscles_activity = [ float(x ) for x in h.v_MDL22_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL23_v_muscles_activity = [ float(x ) for x in h.v_MDL23_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
py_v_MDL24_v_muscles_activity = [ float(x ) for x in h.v_MDL24_v_muscles_activity.to_python() ] # Convert to Python list for speed, variable has dim: concentration
f_muscles_activity_f2 = open('c302_C2_AS_DA_DB.muscles.activity.dat', 'w')
num_points = len(py_v_time) # Simulation may have been stopped before tstop...
for i in range(num_points):
f_muscles_activity_f2.write('%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t\n' % (py_v_time[i], py_v_MDR01_v_muscles_activity[i], py_v_MDR02_v_muscles_activity[i], py_v_MDR03_v_muscles_activity[i], py_v_MDR04_v_muscles_activity[i], py_v_MDR05_v_muscles_activity[i], py_v_MDR06_v_muscles_activity[i], py_v_MDR07_v_muscles_activity[i], py_v_MDR08_v_muscles_activity[i], py_v_MDR09_v_muscles_activity[i], py_v_MDR10_v_muscles_activity[i], py_v_MDR11_v_muscles_activity[i], py_v_MDR12_v_muscles_activity[i], py_v_MDR13_v_muscles_activity[i], py_v_MDR14_v_muscles_activity[i], py_v_MDR15_v_muscles_activity[i], py_v_MDR16_v_muscles_activity[i], py_v_MDR17_v_muscles_activity[i], py_v_MDR18_v_muscles_activity[i], py_v_MDR19_v_muscles_activity[i], py_v_MDR20_v_muscles_activity[i], py_v_MDR21_v_muscles_activity[i], py_v_MDR22_v_muscles_activity[i], py_v_MDR23_v_muscles_activity[i], py_v_MDR24_v_muscles_activity[i], py_v_MVR01_v_muscles_activity[i], py_v_MVR02_v_muscles_activity[i], py_v_MVR03_v_muscles_activity[i], py_v_MVR04_v_muscles_activity[i], py_v_MVR05_v_muscles_activity[i], py_v_MVR06_v_muscles_activity[i], py_v_MVR07_v_muscles_activity[i], py_v_MVR08_v_muscles_activity[i], py_v_MVR09_v_muscles_activity[i], py_v_MVR10_v_muscles_activity[i], py_v_MVR11_v_muscles_activity[i], py_v_MVR12_v_muscles_activity[i], py_v_MVR13_v_muscles_activity[i], py_v_MVR14_v_muscles_activity[i], py_v_MVR15_v_muscles_activity[i], py_v_MVR16_v_muscles_activity[i], py_v_MVR17_v_muscles_activity[i], py_v_MVR18_v_muscles_activity[i], py_v_MVR19_v_muscles_activity[i], py_v_MVR20_v_muscles_activity[i], py_v_MVR21_v_muscles_activity[i], py_v_MVR22_v_muscles_activity[i], py_v_MVR23_v_muscles_activity[i], py_v_MVL01_v_muscles_activity[i], py_v_MVL02_v_muscles_activity[i], py_v_MVL03_v_muscles_activity[i], py_v_MVL04_v_muscles_activity[i], py_v_MVL05_v_muscles_activity[i], py_v_MVL06_v_muscles_activity[i], py_v_MVL07_v_muscles_activity[i], py_v_MVL08_v_muscles_activity[i], py_v_MVL09_v_muscles_activity[i], py_v_MVL10_v_muscles_activity[i], py_v_MVL11_v_muscles_activity[i], py_v_MVL12_v_muscles_activity[i], py_v_MVL13_v_muscles_activity[i], py_v_MVL14_v_muscles_activity[i], py_v_MVL15_v_muscles_activity[i], py_v_MVL16_v_muscles_activity[i], py_v_MVL17_v_muscles_activity[i], py_v_MVL18_v_muscles_activity[i], py_v_MVL19_v_muscles_activity[i], py_v_MVL20_v_muscles_activity[i], py_v_MVL21_v_muscles_activity[i], py_v_MVL22_v_muscles_activity[i], py_v_MVL23_v_muscles_activity[i], py_v_MVL24_v_muscles_activity[i], py_v_MDL01_v_muscles_activity[i], py_v_MDL02_v_muscles_activity[i], py_v_MDL03_v_muscles_activity[i], py_v_MDL04_v_muscles_activity[i], py_v_MDL05_v_muscles_activity[i], py_v_MDL06_v_muscles_activity[i], py_v_MDL07_v_muscles_activity[i], py_v_MDL08_v_muscles_activity[i], py_v_MDL09_v_muscles_activity[i], py_v_MDL10_v_muscles_activity[i], py_v_MDL11_v_muscles_activity[i], py_v_MDL12_v_muscles_activity[i], py_v_MDL13_v_muscles_activity[i], py_v_MDL14_v_muscles_activity[i], py_v_MDL15_v_muscles_activity[i], py_v_MDL16_v_muscles_activity[i], py_v_MDL17_v_muscles_activity[i], py_v_MDL18_v_muscles_activity[i], py_v_MDL19_v_muscles_activity[i], py_v_MDL20_v_muscles_activity[i], py_v_MDL21_v_muscles_activity[i], py_v_MDL22_v_muscles_activity[i], py_v_MDL23_v_muscles_activity[i], py_v_MDL24_v_muscles_activity[i], ))
f_muscles_activity_f2.close()
print("Saved data to: c302_C2_AS_DA_DB.muscles.activity.dat")
# ###################### File to save: c302_C2_AS_DA_DB.dat (neurons_v)
py_v_AS1_v_neurons_v = [ float(x / 1000.0) for x in h.v_AS1_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_AS10_v_neurons_v = [ float(x / 1000.0) for x in h.v_AS10_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_AS11_v_neurons_v = [ float(x / 1000.0) for x in h.v_AS11_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_AS2_v_neurons_v = [ float(x / 1000.0) for x in h.v_AS2_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_AS3_v_neurons_v = [ float(x / 1000.0) for x in h.v_AS3_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_AS4_v_neurons_v = [ float(x / 1000.0) for x in h.v_AS4_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_AS5_v_neurons_v = [ float(x / 1000.0) for x in h.v_AS5_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_AS6_v_neurons_v = [ float(x / 1000.0) for x in h.v_AS6_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_AS7_v_neurons_v = [ float(x / 1000.0) for x in h.v_AS7_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_AS8_v_neurons_v = [ float(x / 1000.0) for x in h.v_AS8_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_AS9_v_neurons_v = [ float(x / 1000.0) for x in h.v_AS9_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_AVAL_v_neurons_v = [ float(x / 1000.0) for x in h.v_AVAL_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_AVAR_v_neurons_v = [ float(x / 1000.0) for x in h.v_AVAR_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_AVBL_v_neurons_v = [ float(x / 1000.0) for x in h.v_AVBL_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_AVBR_v_neurons_v = [ float(x / 1000.0) for x in h.v_AVBR_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_DA1_v_neurons_v = [ float(x / 1000.0) for x in h.v_DA1_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_DA2_v_neurons_v = [ float(x / 1000.0) for x in h.v_DA2_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_DA3_v_neurons_v = [ float(x / 1000.0) for x in h.v_DA3_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_DA4_v_neurons_v = [ float(x / 1000.0) for x in h.v_DA4_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_DA5_v_neurons_v = [ float(x / 1000.0) for x in h.v_DA5_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_DA6_v_neurons_v = [ float(x / 1000.0) for x in h.v_DA6_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_DA7_v_neurons_v = [ float(x / 1000.0) for x in h.v_DA7_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_DA8_v_neurons_v = [ float(x / 1000.0) for x in h.v_DA8_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_DA9_v_neurons_v = [ float(x / 1000.0) for x in h.v_DA9_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_DB1_v_neurons_v = [ float(x / 1000.0) for x in h.v_DB1_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_DB2_v_neurons_v = [ float(x / 1000.0) for x in h.v_DB2_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_DB3_v_neurons_v = [ float(x / 1000.0) for x in h.v_DB3_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_DB4_v_neurons_v = [ float(x / 1000.0) for x in h.v_DB4_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_DB5_v_neurons_v = [ float(x / 1000.0) for x in h.v_DB5_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_DB6_v_neurons_v = [ float(x / 1000.0) for x in h.v_DB6_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
py_v_DB7_v_neurons_v = [ float(x / 1000.0) for x in h.v_DB7_v_neurons_v.to_python() ] # Convert to Python list for speed, variable has dim: voltage
f_neurons_v_f2 = open('c302_C2_AS_DA_DB.dat', 'w')
num_points = len(py_v_time) # Simulation may have been stopped before tstop...
for i in range(num_points):
f_neurons_v_f2.write('%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t%e\t\n' % (py_v_time[i], py_v_AS1_v_neurons_v[i], py_v_AS10_v_neurons_v[i], py_v_AS11_v_neurons_v[i], py_v_AS2_v_neurons_v[i], py_v_AS3_v_neurons_v[i], py_v_AS4_v_neurons_v[i], py_v_AS5_v_neurons_v[i], py_v_AS6_v_neurons_v[i], py_v_AS7_v_neurons_v[i], py_v_AS8_v_neurons_v[i], py_v_AS9_v_neurons_v[i], py_v_AVAL_v_neurons_v[i], py_v_AVAR_v_neurons_v[i], py_v_AVBL_v_neurons_v[i], py_v_AVBR_v_neurons_v[i], py_v_DA1_v_neurons_v[i], py_v_DA2_v_neurons_v[i], py_v_DA3_v_neurons_v[i], py_v_DA4_v_neurons_v[i], py_v_DA5_v_neurons_v[i], py_v_DA6_v_neurons_v[i], py_v_DA7_v_neurons_v[i], py_v_DA8_v_neurons_v[i], py_v_DA9_v_neurons_v[i], py_v_DB1_v_neurons_v[i], py_v_DB2_v_neurons_v[i], py_v_DB3_v_neurons_v[i], py_v_DB4_v_neurons_v[i], py_v_DB5_v_neurons_v[i], py_v_DB6_v_neurons_v[i], py_v_DB7_v_neurons_v[i], ))
f_neurons_v_f2.close()
print("Saved data to: c302_C2_AS_DA_DB.dat")
save_end = time.time()
save_time = save_end - self.sim_end
print("Finished saving results in %f seconds"%(save_time))
print("Done")
quit()
if __name__ == '__main__':
ns = NeuronSimulation(tstop=2000, dt=0.05, seed=123456789)
ns.run()
|
[
"lungdm@gmail.com"
] |
lungdm@gmail.com
|
84ba2de82f514a80b6a661f51dd0f753082f6e2d
|
29bcaf4d6d5e96fd4a85da3b0b3e813f92a84b77
|
/examples/pytorch/pagerank.py
|
1b66242c9121e643699df8ae610951ddd7e67483
|
[
"Apache-2.0"
] |
permissive
|
hetong007/dgl
|
844e48421fe899b1f36d40095cf54809b1724a26
|
11e910b6f88ec10c7549493dab9e2b218e988e97
|
refs/heads/master
| 2022-04-30T23:16:19.354461
| 2022-03-31T11:22:21
| 2022-03-31T11:22:21
| 228,311,655
| 1
| 0
|
Apache-2.0
| 2020-08-05T09:40:28
| 2019-12-16T05:45:10
|
Python
|
UTF-8
|
Python
| false
| false
| 598
|
py
|
import networkx as nx
import torch
import dgl
import dgl.function as fn
N = 100
g = nx.erdos_renyi_graph(N, 0.05)
g = dgl.DGLGraph(g)
DAMP = 0.85
K = 10
def compute_pagerank(g):
g.ndata['pv'] = torch.ones(N) / N
degrees = g.out_degrees(g.nodes()).type(torch.float32)
for k in range(K):
g.ndata['pv'] = g.ndata['pv'] / degrees
g.update_all(message_func=fn.copy_src(src='pv', out='m'),
reduce_func=fn.sum(msg='m', out='pv'))
g.ndata['pv'] = (1 - DAMP) / N + DAMP * g.ndata['pv']
return g.ndata['pv']
pv = compute_pagerank(g)
print(pv)
|
[
"noreply@github.com"
] |
hetong007.noreply@github.com
|
e3db28496321a7da1e62e32c2629cb74391a33b1
|
8a1519c2604e81eb3a4e2dc5829863f246218ea7
|
/SmartHouseController/Smart House controller.py
|
7860f563c574b51cb39c99dfcf20290ee7360006
|
[] |
no_license
|
ryanongra/SNCA_Projects
|
d032f3d6a90468a44e27a9ea4d347e4f0bde1971
|
a36460f3684151dca61e70cd275f311e73f63898
|
refs/heads/main
| 2023-07-11T19:38:56.949275
| 2021-08-12T11:28:35
| 2021-08-12T11:28:35
| 395,290,106
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 695
|
py
|
from microbit import *
import radio
radio.on()
while True:
if accelerometer.current_gesture() == "up":
radio.send("Come in")
sleep(1)
elif accelerometer.current_gesture() == "shake":
radio.send("Access denied")
sleep(1)
elif accelerometer.current_gesture() == "face down":
radio.send("Light on")
sleep(1)
elif accelerometer.current_gesture() == "face up":
radio.send("Light off")
sleep(1)
else:
radio.send("nothing")
sleep(1)
message = radio.receive()
if message == "Someone's at the door":
display.scroll(message)
message = ""
sleep(1)
|
[
"noreply@github.com"
] |
ryanongra.noreply@github.com
|
53a4c73643999112ef04e0602c63db6523b5ae48
|
d1593aefbf9560af6cca9a82f59302a84c5052fa
|
/migrations/versions/898c591f6665_creates_the_foreign_key_to_the_user_.py
|
cef423bed8c392cbf14408650c7392e06eb0cb24
|
[] |
no_license
|
jod35/car-parking
|
71ec9d91163658489d3277023c71c91237343c07
|
9448ae3660de1b4104ec34f19c4a2f25b022f7d6
|
refs/heads/master
| 2020-11-25T16:38:31.666940
| 2019-12-18T05:44:41
| 2019-12-18T05:44:41
| 228,759,269
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 816
|
py
|
"""creates the foreign key to the user table
Revision ID: 898c591f6665
Revises: ce5ec4406cd4
Create Date: 2019-12-17 00:23:15.563670
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = '898c591f6665'
down_revision = 'ce5ec4406cd4'
branch_labels = None
depends_on = None
def upgrade():
# ### commands auto generated by Alembic - please adjust! ###
op.add_column('service', sa.Column('user_id', sa.Integer(), nullable=True))
op.create_foreign_key(None, 'service', 'user', ['user_id'], ['id'])
# ### end Alembic commands ###
def downgrade():
# ### commands auto generated by Alembic - please adjust! ###
op.drop_constraint(None, 'service', type_='foreignkey')
op.drop_column('service', 'user_id')
# ### end Alembic commands ###
|
[
"jodestrevin@gmail.com"
] |
jodestrevin@gmail.com
|
a0ed4c078248390ebb22ef20c22100702dd2e33d
|
cd8e37979ad3d38b7a3726d2f7084cb30538a5dd
|
/setup.py
|
0bee80254fe71f8a601845b316ce06387873c25a
|
[
"MIT"
] |
permissive
|
lejar/Bard-s-Tale-IV-Code-Wheel
|
e6ab14b0b682da0aa5f100382a2bcc5f72382eda
|
67c4e27736f5d48bf1059cf4dd3ee488bfdd5130
|
refs/heads/master
| 2020-03-29T11:45:29.026217
| 2018-09-22T11:48:19
| 2018-09-22T11:48:19
| 149,869,105
| 8
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,348
|
py
|
import os
import subprocess
import shutil
from pathlib import Path
from setuptools import setup, find_packages, command
from setuptools.command.build_py import build_py
from distutils.command.build import build as _build
from distutils.command.clean import clean as _clean
from distutils.command.install import install as _install
# Get all of the ui files in the project.
UI_FILES = []
RC_FILES = []
for root, directories, files in os.walk('.'):
for file in files:
if os.path.splitext(file)[-1] == '.ui':
UI_FILES.append(os.path.join(root, file))
elif os.path.splitext(file)[-1] == '.qrc':
RC_FILES.append(os.path.join(root, file))
class UIBuild(_build):
def run(self):
# Convert all ui files into python files.
for file in UI_FILES:
basename = os.path.splitext(file)[0]
subprocess.run(f'pyuic5 --from-imports -o {basename}.py {file}', shell=True)
for file in RC_FILES:
basename = os.path.splitext(file)[0]
subprocess.run(f'pyrcc5 -o {basename}_rc.py {file}', shell=True)
super(UIBuild, self).run()
class UIClean(_clean):
def run(self):
# Clean up all converted UI files.
for file in UI_FILES + RC_FILES:
basename = os.path.splitext(file)[0]
if os.path.exists(f'{basename}.py'):
os.remove(f'{basename}.py')
# Remove some autogenerated things that setuptools never cleans up.
if os.path.exists('build'):
shutil.rmtree('build')
if os.path.exists('dist'):
shutil.rmtree('dist')
if os.path.exists('.DS_Store'):
os.remove('.DS_Store')
super(UIClean, self).run()
class pyinstaller(_install):
def run(self):
code_wheel = Path('.') / 'code_wheel' / '__main__.py'
resources = Path('.') / 'code_wheel' / 'resources'
icon = resources / 'icon.ico'
subprocess.run(f'pyinstaller -F -w -i {icon} {code_wheel}')
shutil.move(Path('dist') / '__main__.exe', Path('dist') / 'Bard\'s Tale IV Code Wheel.exe')
setup(
author='Christopher Pezley',
name="Bard's Tale 4 Code Wheel",
version="1.0",
packages=find_packages(),
cmdclass={
'build': UIBuild,
'clean': UIClean,
'install': pyinstaller,
},
)
|
[
"github@pezley.net"
] |
github@pezley.net
|
6579713cbee5298c4a87a717e50c2083d458a81b
|
1a5b990b87f86d23a636ce439d26a14d9664829b
|
/test_spider.py
|
930536f2d095edc88367616569534b59c283836f
|
[] |
no_license
|
btlishang/test
|
8be5875839ace07dfd0b3c4d949ab4acf5b06879
|
b56cc2a9d2946df63cd54a55b8edc5773cf47087
|
refs/heads/master
| 2022-12-22T10:37:01.219807
| 2019-01-23T07:41:23
| 2019-01-23T07:41:23
| 159,899,607
| 0
| 0
| null | 2022-12-08T01:19:32
| 2018-12-01T02:06:20
|
Python
|
UTF-8
|
Python
| false
| false
| 5,605
|
py
|
#-*- coding:utf-8 _*-
#
# File Name: test_spider
# Author : lishang
# date： 2018/11/25
import requests,time,mysql,re
from pyquery import PyQuery as pq
from requests.exceptions import ConnectionError,ReadTimeout
headers = {
"Host": "www.csh.edu.cn",
# "user-agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_13_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/66.0.3359.181 Safari/537.36",
"user-agent": "User-Agent:Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6_8; en-us) AppleWebKit/534.50 (KHTML, like Gecko) Version/5.1 Safari/534.50",
"referer": "http://www.csh.edu.cn/moetc/mdepartmentExtAction!toMdepartmentExtListWdOuter.action",
"upgrade - insecure - requests": "1",
"cookie":"test=vlan1821_web10; COLLPIC=r8yg; test=vlan1821_web10; JSESSIONID=OMpDkI0PwX0JhxDc9mm2zqH8Hx8_BnJvRjTUE9WhC2uuZFyknpII!1989823960"
}
basic_url = "http://www.csh.edu.cn"
start_url = "http://www.csh.edu.cn/moetc/mdepartmentExtAction!toMdepartmentExtListWdOuter.action"
# 获取代理IP
def get_proxy():
proxy_pool_url = "http://47.93.231.162:5010/get/"
try:
response = requests.get(proxy_pool_url)
if response.status_code == 200:
return response.text
else:
get_proxy()
except ConnectionError:
return None
def get_province(start_url):
try:
html = requests.get(start_url,headers=headers,proxies={"http": "http://{}".format(get_proxy())},timeout=10)
print(html.status_code)
if html.status_code == 200:
doc = pq(html.text)
items = doc('#serId > div > div:nth-child(3) > div.h_select_line_right > a').items()
if items:
for item in items:
province_name = item.text()
province_url = basic_url + item.attr('href')
province_id = item.attr('href')[70:72]
mysql.insert_content(province_id,province_name,province_url)
print("******当前省份为：-",province_name,"-******")
time.sleep(1)
get_city(province_url,province_name)
else:
get_province(start_url)
elif html.status_code == 400:
print("===========抓取省份超时",html.status_code,"，请等待===========")
get_province(start_url)
elif html.status_code == 503:
print("===========抓取省份超时",html.status_code,"，请等待===========")
get_province(start_url)
except (ConnectionError,ReadTimeout) as c:
print('===========省份抓取超时，重新连接中===========')
get_province(start_url)
def get_city(url,province_name):
try:
html = requests.get(url, timeout=10)
print(html.status_code)
if html.status_code == 200:
doc = pq(html.text)
items = doc('#serId > div > div:nth-child(4) > div.h_select_line_right > a').items()
for item in items:
city_name = item.text()
city_url = basic_url + item.attr('href')
city_id = item.attr('href')[72:74]
province_id = item.attr('href')[70: 72]
mysql.insert_city(province_id,city_id,city_name,city_url,province_name)
print("******当前城市为：-",city_name,"-******")
time.sleep(1)
get_country(city_url,city_name,province_name)
elif html.status_code == 400:
print("===========城市抓取超时，请等待===========")
return get_city(url,province_name)
except (ConnectionError, ReadTimeout) as c:
print('===========抓取城市连接超时，重新连接中===========')
return get_city(url,province_name)
def get_country(url,city_name,province_name):
try:
html = requests.get(url,timeout=5)
print(html.status_code)
if html.status_code == 200:
doc = pq(html.text)
items = doc('#serId > div > div:nth-child(5) > div.h_select_line_right > a').items()
for item in items:
country_name = item.text()
country_url = basic_url + item.attr('href')
country_id = item.attr('href')[-8:-6]
province_id = item.attr('href')[-12:-10]
city_id = item.attr('href')[-10:-8]
mysql.insert_country(province_id,city_id,country_id,country_name,country_url,city_name,province_name)
print("******当前县/区：-",country_name,"-******")
time.sleep(1)
elif html.status_code == 400:
print("==============县/区抓取超时，请等待==============")
return get_country(url,city_name,province_name)
except (ConnectionError, ReadTimeout) as c:
print('===========抓取县/区连接超时，重新连接中===========')
return get_country(url,city_name,province_name)
if __name__ == '__main__':
# 从头开始
# get_province(start_url)
# # 补充单个省
info = mysql.select_province("山东省")
city_url = info[3]
province_name = info[2]
print(city_url,province_name)
get_city(city_url,province_name)
# get_city()
# # 补充单个市
# info = mysql.select_city("抚州市")
# city_url = info[3]
# city_name = info[2]
# province_name = info[5]
# print(city_url, city_name, province_name)
# get_country(city_url,city_name,province_name)
mysql.db.close()
|
[
"542880395@qq.com"
] |
542880395@qq.com
|
7f6eb17b83d7f12b037cca2162485483f884b4d1
|
cbad8ab4208ed31a904028ba0f190ddb89b2b667
|
/chapter02/NumPy_and_SciPy.py
|
fffa49c7bd7e235f6f81d1171aa19fc1c245556b
|
[] |
no_license
|
ZhaoHuiXin/Fluent-Python
|
a4a2de649505437f77b2024ac61c48d56cc1cc0b
|
691b3a90e73061ad4f07ce0dd775b08a8779c7ec
|
refs/heads/master
| 2020-03-17T08:40:06.614237
| 2018-06-12T01:13:41
| 2018-06-12T01:13:41
| 133,446,109
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 373
|
py
|
# -*- coding=utf-8 -*-
#
# Copyright @ 2018 HuiXin Zhao
"""导入精度和性能都比较高的计时器(Python 3.3 及更新的版本中都有这个库)"""
from time import perf_counter as pc
import numpy
t0 = pc()
a = numpy.arange(12)
print(a, type(a))
print(a.shape)
a.shape = 3, 4
print(a)
print(a[2])
print(a[2][1])
print(a[:, 1])
print(a.transpose())
print(pc()-t0)
|
[
"zhaohuixin@autoforce.net"
] |
zhaohuixin@autoforce.net
|
fd69576b11ab5fcb0aa9abb70ebe2732844c00f8
|
51b907f1b20065b51b0a621bfb26b0d2f00e708f
|
/lib/python3.7/__future__.py
|
eac425093bd5116b3bcc5c3f7aafb8be151e4676
|
[] |
no_license
|
Atuahene3/house-deal
|
f4c807023029e3a3fe1527e287cf4d75db9fb0ca
|
177a5931018131504ea337b27597b18c39407441
|
refs/heads/master
| 2022-10-12T05:27:45.696243
| 2019-09-04T15:17:00
| 2019-09-04T15:17:00
| 206,359,713
| 0
| 0
| null | 2022-09-30T18:42:22
| 2019-09-04T16:05:23
|
Python
|
UTF-8
|
Python
| false
| false
| 54
|
py
|
/Users/theoatadu/anaconda3/lib/python3.7/__future__.py
|
[
"theoatadu@Theophiluss-MacBook-Pro.local"
] |
theoatadu@Theophiluss-MacBook-Pro.local
|
09190a89d9de114658ef9dc548c9bdce2cbb9738
|
8f62c24d6e3cd085af54ba0c63c4ce8e6d5752d3
|
/pythonpath/mytools_Mri/ui/dialogs.py
|
138039ee0154b7325fed171787d80fd0cc425c84
|
[
"Apache-2.0"
] |
permissive
|
Nienzu/MRI
|
fc7f7b3879691ec97dac3d62c5afc3420af015cc
|
0298496aaa25f792de9b9f040597f4dd4d6800e6
|
refs/heads/master
| 2020-07-23T04:13:54.806967
| 2018-12-25T15:25:06
| 2018-12-25T15:25:06
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 26,480
|
py
|
# Copyright 2011 Tsutomu Uchino
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import unohelper
import traceback
from com.sun.star.awt import XActionListener, XMouseListener, \
XItemListener, Rectangle
from com.sun.star.view import XSelectionChangeListener
class InputButtonListener(unohelper.Base, XActionListener):
def __init__(self,cast,idltarget='',word=''):
self.cast = cast
self.idltarget = idltarget
self.word = word
def set_target(self, idltarget, word):
self.idltarget = idltarget
self.word = word
def disposing(self,ev):
pass
def actionPerformed(self,actionEvent):
cmd = str(actionEvent.ActionCommand)
if cmd == 'idlref':
self.cast.open_idl_reference(self.idltarget, self.word)
class SelectListListener(unohelper.Base, XMouseListener):
def __init__(self,cast):
self.cast = cast
def disposing(self,ev):
pass
def mouseReleased(self,ev):
pass
def mouseEntered(self,ev):
pass
def mouseExited(self,ev):
pass
def mousePressed(self,ev):
if ev.ClickCount == 2:
self.cast.endDialog(1)
class DialogBase(object):
DISPOSE = True
POSSIZE = 0,0,0,0
HELP_URL = ""
def __init__(self, ctx, cast, *args):
self.ctx = ctx
self.cast = cast
self._dialog = self._create_dialog(*self.POSSIZE, help_url=self.HELP_URL)
self._create()
def execute(self):
toolkit = self.ctx.getServiceManager().createInstanceWithContext(
"com.sun.star.awt.Toolkit", self.ctx)
self._dialog.createPeer(toolkit, None)
#self._dialog.setVisible(True)
self._prepare()
n = self._dialog.execute()
ret = self._done(n)
if self.DISPOSE:
self._destruct()
self._dialog.dispose()
return ret
def _create(self): pass
def _destruct(self): pass
def _prepare(self): pass
def _done(self, n):
return n
def _create_service(self, name):
return self.ctx.getServiceManager().createInstanceWithContext(name, self.ctx)
# create control functions
def _create_dialog(self, x, y, width, height, help_url):
smgr = self.ctx.getServiceManager()
dialog = smgr.createInstanceWithContext(
'com.sun.star.awt.UnoControlDialog', self.ctx)
dialog_model = smgr.createInstanceWithContext(
'com.sun.star.awt.UnoControlDialogModel', self.ctx)
dialog_model.setPropertyValues(
('Height','HelpURL','PositionX','PositionY','Width',),
(height, help_url, x, y, width,) )
dialog.setModel(dialog_model)
#dialog.setVisible(False)
#dialog.createPeer(toolkit, None)
dialog.setVisible(False)
self._dialog = dialog
return dialog
def set_title(self, title):
self._dialog.setTitle(title)
def add_control(self, _type, name, x, y, width, height, names=None, props=None):
model = self._dialog.getModel().createInstance(_type)
model.setPropertyValues(
("Height", "PositionX", "PositionY", "Width"),
(height, x, y, width))
if names and props:
model.setPropertyValues(names, props)
self._dialog.getModel().insertByName(name, model)
return model
def add_edit(self, name, x, y, width, height, names=None, props=None):
return self.add_control("com.sun.star.awt.UnoControlEditModel",
name, x, y, width, height, names, props)
def add_label(self, name, x, y, width, height, names=None, props=None):
return self.add_control("com.sun.star.awt.UnoControlFixedTextModel",
name, x, y, width, height, names, props)
def add_button(self, name, x, y, width, height, names=None, props=None, command=None):
model = self.add_control("com.sun.star.awt.UnoControlButtonModel",
name, x, y, width, height, names, props)
if command:
self.get_control(name).setActionCommand(command)
return model
def add_check(self, name, x, y, width, height, names=None, props=None):
return self.add_control("com.sun.star.awt.UnoControlCheckBoxModel",
name, x, y, width, height, names, props)
def add_list(self, name, x, y, width, height, names=None, props=None):
return self.add_control("com.sun.star.awt.UnoControlListBoxModel",
name, x, y, width, height, names, props)
def add_line(self, name, x, y, width, height, names=None, props=None):
return self.add_control("com.sun.star.awt.UnoControlFixedLineModel",
name, x, y, width, height, names, props)
def add_ok(self, name, x, y, width, height):
return self.add_button(name, x, y, width, height,
("DefaultButton", "Label", "PushButtonType"), (True, "~OK", 1))
def add_cancel(self, name, x, y, width, height):
return self.add_button(name, x, y, width, height,
("Label", "PushButtonType"), ("~Cancel", 2))
def add_tree(self, name, x, y, width, height, names=None, props=None):
return self.add_control("com.sun.star.awt.tree.TreeControlModel",
name, x, y, width, height, names, props)
def get_control(self, name):
return self._dialog.getControl(name)
def get_control_model(self, name):
return self._dialog.getModel().getByName(name)
def set_dialog_height(self, height):
self._dialog.getModel().Height = height
# set/get value to/from a control
def set_y(self, name, y):
self.get_control_model(name).PositionY = y
def set_label(self, name, label):
self.get_control_model(name).Label = label
def set_text(self, name, text):
self.get_control_model(name).Text = text
def get_text(self, name):
return self.get_control_model(name).Text
def set_text_selection(self, name, r):
self.get_control(name).setSelection(r)
def is_checked(self, name):
return self.get_control_model(name).State == 1
## list
def add_items(self, name, index, items):
_items = tuple(items) if isinstance(items, list) else items
self.get_control(name).addItems(_items, index)
def get_item_count(self, name):
return self.get_control(name).getItemCount()
def select_item_pos(self, name, index, state=True):
self.get_control(name).selectItemPos(index, state)
def get_selected_item(self, name):
return self.get_control(name).getSelectedItem()
def get_selected_item_pos(self, name):
return self.get_control(name).getSelectedItemPos()
# misc
def set_visible(self, name, state=True):
self.get_control(name).setVisible(state)
def set_enable(self, name, state=True):
self.get_control(name).setEnable(state)
def set_focus(self, name):
return self.get_control(name).setFocus()
def create_tree_data_model(self):
return self._create_service("com.sun.star.awt.tree.MutableTreeDataModel")
class InfoDialog(DialogBase):
DISPOSE = False
POSSIZE = 30, 50, 176, 136
HELP_URL = "mytools.Mri:d_info"
def _create(self):
self.add_edit("edit", 2, 1, 172, 110,
('HelpURL','HideInactiveSelection','HScroll','MultiLine', 'VScroll',),
('mytools.Mri:d_info_edit',False,True,True, True,))
self.add_button("btn", 130, 117, 43, 16,
('DefaultButton', 'HelpURL','Label', 'PushButtonType'),
(True, 'mytools.Mri:d_info_btn','~close', 2))
self.add_label("label", 5, 115, 123, 23,
("FontHeight",),
(9,))
def _prepare(self):
self.set_focus("btn")
def execute(self, value, label=""):
self.set_text("edit", value)
self.set_label("label", label)
return DialogBase.execute(self)
class SelectDialog(DialogBase):
POSSIZE = 30, 50, 150, 150
HELP_URL = 'mytools.Mri:d_select'
def _create(self):
self.add_list("list", 2, 2, 146, 130)
self.add_cancel("cbtn", 82, 134, 36, 14)
self.add_ok("obtn", 42, 134, 36, 14)
self.get_control("list").addMouseListener(SelectListListener(self._dialog))
def _prepare(self):
if self.get_item_count("list"):
self.select_item_pos("list", 0, True)
def execute(self, itemtuple, title="", index=False):
if isinstance(itemtuple, tuple) or isinstance(itemtuple, list):
self.add_items("list", 0, itemtuple)
if self.get_item_count("list") <= 0:
self.set_enable("obtn", False)
self._index = index
return DialogBase.execute(self)
def _done(self, n):
if n:
if self._index:
return self.get_selected_item_pos("list")
else:
return self.get_selected_item("list")
else:
return None
class InputDialog(DialogBase):
POSSIZE = 30, 50, 177, 65
HELP_URL = "mytools.Mri:d_input"
def _create(self):
self.add_line("line", 4, 1, 170, 12)
self.add_cancel("cbtn", 142, 48, 29, 14)
self.add_ok("obtn", 142, 32, 29, 14)
self.add_edit("edit", 2, 15, 171, 13, ("MultiLine",), (False,))
self.add_label("label", 2, 30, 130, 8, ("FontHeight", "MultiLine"), (8, True))
self._selection = None
def _prepare(self):
self.set_focus("edit")
if self._selection:
from com.sun.star.awt import Selection
self.set_text_selection("edit", Selection(0, self._selection))
def execute(self, label="", txt="", init="", select=True):
self.set_label("line", label)
self.set_label("label", txt)
self.set_text("edit", init)
if init and select:
self._selection = len(init)
return DialogBase.execute(self)
def _done(self, n):
return (self.get_text("edit") if n else ""), n
class InputDialog2(InputDialog):
POSSIZE = 30, 50, 177, 81
def _create(self):
self.add_line("line", 4, 1, 170, 12)
self.add_cancel("cbtn", 142, 48, 29, 14)
self.add_ok("obtn", 142, 32, 29, 14)
self.add_edit("edit", 2, 15, 171, 13, ("MultiLine",), (False,))
self.add_label("label", 2, 30, 135, 8, ("FontHeight", "MultiLine"), (8, True))
self.add_button("ibtn", 142, 64, 29, 14, ("Label", "PushButtonType"), ("~Ref.", 0), command="idlref")
self._button_listener = InputButtonListener(self.cast)
self.get_control("ibtn").addActionListener(self._button_listener)
self._selection = None
def execute(self, label="", txt="", init="", dclass="", word="", select=True):
self.set_label("line", label)
self.set_label("label", txt)
self.set_text("edit", init)
self._button_listener.set_target(dclass, word)
if init and select:
self._selection = len(init)
return DialogBase.execute(self)
class ElementalInputDialog(InputDialog):
POSSIZE = 30, 50, 177, 67
FROM_HISTORY = {"INTERFACE", "STRUCT", "EXCEPTION", "SEQUENCE"}
class Result:
def __init__(self, type_name, value=None, value_type=None):
self.type_name = type_name
self.value = value
self.value_type = value_type
class ListenerBase(unohelper.Base):
def __init__(self, act):
self.act = act
def disposing(self, ev):
self.act = None
class ButtonListener(ListenerBase, XActionListener):
def actionPerformed(self, ev):
try:
self.act.button_pushed(ev)
except Exception as e:
print(e)
traceback.print_exc()
class TreeSelectionListener(ListenerBase, XSelectionChangeListener):
def selectionChanged(self, ev):
ev.Source.getContext().getControl("btnOk").setEnable(
self.act.tree_selection_changed())
class ItemListener(ListenerBase, XItemListener):
def itemStateChanged(self, ev):
self.act.void_check_changed(ev.Selected == 1)
def _create(self):
self.add_line("line", 4, 1, 170, 12)
self.add_ok("obtn", 142, 0, 29, 14)
self.add_cancel("cbtn", 142, 0, 29, 14)
self.add_button("ibtn", 142, 0, 29, 14, ("Label",), ("~Ref.",), "idlref")
self.add_edit("label", 2, 0, 135, 48, ("FontHeight", "MultiLine"), (8, True))
self._button_listener = InputButtonListener(self.cast)
self.get_control("ibtn").addActionListener(self._button_listener)
def _prepare(self):
self.set_focus("edit_0")
def execute(self, elements, label="", txt="", doc=("", "")):
self._results = []
self.set_dialog_height(67 + len(elements) * 27)
self.set_label("line", label)
self.set_text("label", txt)
self._button_listener.set_target(*doc)
# add and rearrange controls
from com.sun.star.style.VerticalAlignment import BOTTOM as VA_BOTTOM
listener = self.__class__.ButtonListener(self)
y = 14
complex_types = self.FROM_HISTORY | {"ANY"}
for i, element in enumerate(elements):
is_complex = element[1] in complex_types
self.add_label("label_%s" % i, 4, y, 170, 12,
("Label", "NoLabel", "VerticalAlign"), (element[0], True, VA_BOTTOM))
self.add_edit("edit_%s" % i, 2, y + 13, (130 if is_complex else 171), 13,
("MultiLine",), (False,))
if is_complex:
if element[1] != "ANY":
self.set_enable("edit_%s" % i, False)
self.add_button("btn_%s" % i, 133, y + 13, 40, 13, ("Label",), ("...",), str(i))
self.get_control("btn_%s" % i).addActionListener(listener)
self._results.append(self.Result(element[1]))
y += 27
y += 3
self.set_y("obtn", y)
self.set_y("cbtn", y + 15)
self.set_y("ibtn", y + 30)
self.set_y("label", y)
self._history_selector = None
return DialogBase.execute(self)
def void_check_changed(self, state):
self._history_selector.enable_ok_button(
state or self._history_selector.is_tree_selection_valid())
def tree_selection_changed(self):
return self._history_selector.is_tree_selection_valid()
def button_pushed(self, ev):
control = ev.Source
n = int(ev.ActionCommand)
type_name = self._results[n].type_name
with_type = False
if type_name == "ANY":
with_type = True
from mytools_Mri.ui.tools import create_popupmenu
entries = ((1, 0, 0, "void", "VOID", None),
(2, 1, 0, "boolean", "BOOLEAN", None),
(3, 2, 0, "byte", "BYTE", None),
(4, 3, 0, "short", "SHORT", None),
(5, 4, 0, "unsigned short", "UNSIGNED_SHORT", None),
(6, 5, 0, "long", "LONG", None),
(7, 6, 0, "unsigned long", "UNSIGNED_LONG", None),
(8, 7, 0, "hyper", "HYPER", None),
(9, 8, 0, "unsigned hyper", "UNSIGNED_HYPER", None),
(10, 9, 0, "float", "FLOAT", None),
(11, 10, 0, "double", "DOUBLE", None),
(12, 11, 0, "string", "STRING", None),
(13, 12, 0, "type", "TYPE", None),
(14, 13, 0, "enum", "ENUM", None),
(None, 14, 0, "", "", None),
(15, 15, 0, "struct", "STRUCT", None),
(16, 16, 0, "exception", "EXCEPTION", None),
(17, 17, 0, "sequence", "SEQUENCE", None),
(18, 18, 0, "interface", "INTERFACE", None))
popup = create_popupmenu(self.ctx, entries)
r = popup.execute(ev.Source.getPeer(), Rectangle(0, ev.Source.getPosSize().Height, 0, 0), 0)
if r == 0: return
value_type_name = popup.getCommand(r)
control.setLabel(popup.getItemText(r))
if value_type_name in self.FROM_HISTORY:
self.set_enable("edit_%s" % n, False)
else:
self.set_enable("edit_%s" % n, True)
self._results[n].value_type = value_type_name
return
obj = None
try:
self._history_selector = HistorySelectorDialog(self.ctx, self.cast)
obj = self._history_selector.execute(
"History", self.TreeSelectionListener(self),
allow_void=True, void_listener=self.ItemListener(self))
self._history_selector = None
except Exception as e:
print(e)
traceback.print_exc()
finally:
if obj is None:
return
name = "edit_%s" % n
if obj == "void":
self.set_text(name, "void")
self._results[n].value = None
self._results[n].value_type = "VOID"
elif obj:
self.set_text(name, str(obj))
self._results[n].value = obj
self._results[n].value_type = value_type_name if with_type else type_name
def _done(self, n):
if n:
for i, result in enumerate(self._results):
if result.type_name in self.FROM_HISTORY or result.value_type == "ANY":
pass
else:
result.value = self.get_text("edit_%s" % i)
return n, self._results
class HistorySelectorDialog(DialogBase):
POSSIZE = 30, 50, 180, 140
def _create(self):
class Wrapper(unohelper.Base):
def __init__(self, obj):
self.obj = obj
self.add_label("labelHistory", 5, 3, 96, 12, ("Label",), ("History",))
self.add_ok("btnOk", 134, 4, 43, 14)
self.add_cancel("btnCancel", 134, 24, 43, 14)
self.add_check("checkVoid", 134, 50, 43, 14, ("Label",), ("~void",))
data_model = self.create_tree_data_model()
self.add_tree("treeHistory", 3, 18, 127, 117,
("DataModel", "SelectionType", "RootDisplayed"),
(data_model, 1, True))
child = self.cast.main.history.get_children()[0]
def create_node(parent, entry):
for i in entry.children:
node = data_model.createNode(i.name, False)
parent.appendChild(node)
node.DataValue = Wrapper(i)
if i.get_child_count() > 0:
create_node(node, i)
root = data_model.createNode(child.name, False)
root.DataValue = Wrapper(child)
create_node(root, child)
data_model.setRoot(root)
def _prepare(self):
root = self.get_control_model("treeHistory").DataModel.getRoot()
if root.getChildCount() > 0:
self.get_control("treeHistory").makeNodeVisible(root.getChildAt(0))
def execute(self, title="", listener=None, allow_void=False, void_listener=None):
if listener:
self.get_control("treeHistory").addSelectionChangeListener(listener)
self.set_enable("btnOk", False)
self.set_title(title)
self.set_visible("checkVoid", allow_void)
if void_listener:
self.get_control("checkVoid").addItemListener(void_listener)
return DialogBase.execute(self)
def _done(self, n):
if n:
if self.is_checked("checkVoid"):
return "void"
else:
selected = self.get_control("treeHistory").getSelection()
if selected:
return selected.DataValue.obj
else:
return None
def enable_ok_button(self, state):
self.set_enable("btnOk", state)
def is_tree_selection_valid(self):
tree = self.get_control("treeHistory")
state = False
selected = tree.getSelection()
if selected:
state = selected != tree.getModel().DataModel.getRoot()
return state
class Dialogs(object):
""" Provides dialogs. """
def __init__(self,ctx,smgr,cast):
self.ctx = ctx
self.smgr = smgr
self.cast = cast
self.dlg_info = None
def dialog_info(self, value, label=''):
""" Shows value as a message with label. """
if not self.dlg_info:
self.dlg_info = InfoDialog(self.ctx, self.cast)
return self.dlg_info.execute(value, label)
def dialog_select(self, itemtuple, title='', index=False):
""" Let user select an entry from items. """
return SelectDialog(self.ctx, self.cast).execute(itemtuple, title, index)
def dialog_input(self, label='', txt='', init=''):
""" Input dialog. """
return InputDialog(self.ctx, self.cast).execute(label, txt, init)
def dialog_input2(self,label='',txt='',init='',dclass='',word=''):
""" Input dialog 2. """
return InputDialog2(self.ctx, self.cast).execute(label, txt, init, dclass, word)
def dialog_elemental_input(self, elements, label='', txt='', doc=('', '')):
return ElementalInputDialog(self.ctx, self.cast).execute(elements, label, txt, doc)
def message(self, message, title="", type="messbox", buttons=1):
""" Message box, see css.awt.XMessageBoxFactory. """
import mytools_Mri.tools
desktop = self.smgr.createInstanceWithContext(
"com.sun.star.frame.Desktop", self.ctx)
frame = desktop.getActiveFrame()
window = frame.getContainerWindow()
if mytools_Mri.tools.check_method_parameter(
self.ctx, "com.sun.star.awt.XMessageBoxFactory",
"createMessageBox", 1, "com.sun.star.awt.Rectangle"):
msgbox = window.getToolkit().createMessageBox(
window, Rectangle(), type, buttons, title, message)
else:
import uno
_type = uno.Enum("com.sun.star.awt.MessageBoxType",
{"messbox": "MESSAGEBOX", "infobox": "INFOBOX",
"warningbox": "WARNINGBOX", "errorbox": "ERRORBOX",
"querybox": "QUERYBOX"}[type])
msgbox = window.getToolkit().createMessageBox(
window, _type, buttons, title, message)
n = msgbox.execute()
msgbox.dispose()
return n
def history_selector(self, title="", listener=None):
""" Select an entry from history. """
return HistorySelectorDialog(self.ctx, self.cast).execute(title, listener)
def _create_file_dialog(self, title, default_name, display_dir, filters, default_filter, template):
fp = self.smgr.createInstanceWithContext("com.sun.star.ui.dialogs.FilePicker", self.ctx)
fp.initialize((template,))
fp.setTitle(title)
fp.setDefaultName(default_name)
if display_dir:
fp.setDisplayDirectory(display_dir)
for name, f in filters:
fp.appendFilter(name, f)
if default_filter:
fp.setCurrentFilter(filters[default_filter])
return fp
def dialog_open(self, title="", default_name="", display_dir="", filters=(('All Files (*.*)', '*.*'),), default_filter=0, multiple=False, template=0):
fp = self._create_file_dialog(title, default_name, display_dir, filters, default_filter, template)
fp.setMultiSelectionMode(multiple)
ret = None
if fp.execute() == 1:
files = fp.getFiles()
if multiple:
dir_url = files[0]
if not dir_url.endswith("/"):
dir_url += "/"
ret = [dir_url + name for name in files[1:]]
else:
ret = files[0]
fp.dispose()
return ret
def dialog_save(self, title="", default_name="", display_dir="", filters=(('All Files (*.*)', '*.*'),), default_filter=0, template=1):
fp = self._create_file_dialog(title, default_name, display_dir, filters, default_filter, template)
ret = None
if fp.execute() == 1:
ret = fp.getFiles()[0]
fp.dispose()
return ret
def directory_choose(self, title="", description="", directory=""):
fp = self.smgr.createInstanceWithContext("com.sun.star.ui.dialogs.FolderPicker", self.ctx)
fp.setTitle(title)
fp.setDescription(description)
if directory:
fp.setDisplayDirectory(directory)
ret = None
if fp.execute() == 1:
ret = fp.getDirectory()
fp.dispose()
return ret
|
[
"hanya.runo@gmail.com"
] |
hanya.runo@gmail.com
|
b67006d27c7752ea7c5a81f9de01ca5b928ca312
|
53134f27ca66d042da306781f5dbc7db1d5ec6fe
|
/apps/users/admin.py
|
97a3c2fe893cbf3fd5b6afac55565fd460de3b12
|
[] |
no_license
|
OrlandoGareca/django_rest_blog
|
9acf116d6bca942222b1e6ad1b6d5026210d59c9
|
27fa784023172bfbca6fbc5d80c3c4f4e710f73f
|
refs/heads/main
| 2023-02-28T11:12:35.013283
| 2021-02-03T13:17:38
| 2021-02-03T13:17:38
| 335,623,322
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 179
|
py
|
from django.contrib import admin
# Register your models here.
# from django_rest_blog.apps.users.models import User
from apps.users.models import User
admin.site.register(User)
|
[
"orlando.dilmar.gareca.pena@gmail.com"
] |
orlando.dilmar.gareca.pena@gmail.com
|
1b9422493fed54a03dc6c88cbbc755440cca619d
|
9aaee5f65c8dd9d18b1cc549740f4e6be295f091
|
/basic_analysis/read_gnom_pr.py
|
b53ae2787ced078b0fda87e2d0b345b5df14ec70
|
[] |
no_license
|
ssongna/sastbx_module_sastbx
|
285074d6f07c9d440bd750889322746d14448328
|
aa5cc2f59a4179db761125fb01fe7aaeda7d5dd0
|
refs/heads/master
| 2021-08-17T09:01:18.796977
| 2017-11-21T01:25:50
| 2017-11-21T01:25:50
| 111,428,819
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 754
|
py
|
from scitbx.array_family import flex
import sys
def read_pr_from_gnom(filename):
r= flex.double()
pr= flex.double()
error= flex.double()
file=open(filename, 'r')
pr_start = False
for line in file:
keys = line.split('\n')[0].split()
if(len(keys) == 3):
if(not pr_start):
if(keys[0] == 'R' and (keys[1] == 'P(R)') and (keys[2] == 'ERROR') ):
pr_start=True
else:
r.append( float(keys[0]) )
pr.append( float(keys[1]) )
error.append( float(keys[2]) )
file.close()
return r, pr, error
def print_pr(r,pr):
for ri,pri in zip(r,pr):
print ri, pri
def test(filename):
r,pr,err = read_pr_from_gnom(filename)
print_pr(r,pr)
if __name__ == "__main__":
test(sys.argv[1])
|
[
"15298375979@126.com"
] |
15298375979@126.com
|
b50d050dac270613e73ee112cfc10ed92724aa6e
|
d7be5ab6abbb79daef279974c0b3bf5e3de5515f
|
/venv/Scripts/pip-script.py
|
a21825c3c907375802dfa79ea818aada622bf889
|
[] |
no_license
|
Swingyboy/PlatformTests
|
f4ee77515c323dbc32307585db01649e9396481b
|
4128bef83e64841d8e98d0ffcddca2195405b843
|
refs/heads/master
| 2022-03-05T18:26:15.407792
| 2019-11-14T13:26:49
| 2019-11-14T13:26:49
| 183,031,822
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 402
|
py
|
#!E:\work\auto_tests\PlatformTests\venv\Scripts\python.exe
# EASY-INSTALL-ENTRY-SCRIPT: 'pip==9.0.1','console_scripts','pip'
__requires__ = 'pip==9.0.1'
import re
import sys
from pkg_resources import load_entry_point
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(
load_entry_point('pip==9.0.1', 'console_scripts', 'pip')()
)
|
[
"kedonosec@gmail.com"
] |
kedonosec@gmail.com
|
2052bc6a6757a5b1615d290435939055ffefea57
|
c956c89a021a7507cfd52b60f6ac5b5c3b8c886e
|
/tersa/productos/models.py
|
ddfdaf907ed0f8a38fc7c11d564bf32bd5b58018
|
[] |
no_license
|
cgallego08/tersa2019
|
6478fcbd47807ddd1c7058ff6de53fd8634abb2a
|
c6c1c8e6626bb248bae3443a3a3429a3e813cc1c
|
refs/heads/master
| 2020-08-07T16:00:38.776145
| 2019-10-08T00:58:39
| 2019-10-08T00:58:39
| 213,516,898
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 586
|
py
|
from django.db import models
from categorias.models import Categoria, Bodega
# Create your models here.
class Producto(models.Model):
nombre_producto = models.CharField(max_length=250)
categoria = models.ForeignKey(Categoria, on_delete=models.CASCADE)
Bodega = models.ForeignKey(Bodega, on_delete=models.CASCADE)
codigo_producto = models.CharField(max_length=255, unique=True,)
precio = models.FloatField()
cantidad_stock = models.IntegerField(default=0)
descripcion_producto = models.TextField()
def __str__(self):
return self.nombre_producto
|
[
"55272028+cgallego08@users.noreply.github.com"
] |
55272028+cgallego08@users.noreply.github.com
|
8dcbac18b80912d2eb5772c8182408c63abd2c73
|
434cfbd78ba08861bb40aa8290442556243bdbcc
|
/youtube_dl_gui/SignalHandler.py
|
f5211639e087497b3f395aaa04dfc3a9aae00361
|
[
"Unlicense"
] |
permissive
|
hotice/youtube-dl-gui
|
a18e80788eb769adb5cb2d8007e65d04f78eca5b
|
46a7983f0a729cf7ea2138c39f3163abe71c0509
|
refs/heads/master
| 2021-01-15T14:32:11.948468
| 2014-03-24T21:15:18
| 2014-03-24T21:15:18
| 18,078,947
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 2,898
|
py
|
#! /usr/bin/env python
class DownloadHandler():
def __init__(self, ListCtrl):
self.ListCtrl = ListCtrl
self.finished = False
self.close = False
self.handlers = []
def _has_closed(self):
return self.close
def _has_finished(self):
return self.finished
def handle(self, msg):
''' Handles msg base to Signals.txt '''
data = msg.data
index = self.get_index(data)
if index == -1:
if data[0] == 'finish':
self.finished = True
elif data[0] == 'close':
self.close = True
else:
''' Manage handlers for its index '''
if index == len(self.handlers):
''' Create new IndexDownloadHandler and add it to handlers '''
self.handlers.append(IndexDownloadHandler(self.ListCtrl, index))
''' Let IndexDownloadHandler handle message data for current index '''
self.handlers[index].handle(data)
def get_index(self, data):
return data.pop()
class IndexDownloadHandler():
def __init__(self, ListCtrl, index):
self.ListCtrl = ListCtrl
self.index = index
self.info = ''
def handle(self, data):
''' Handle its data message for current index '''
if data[0] == 'finish':
self.finish()
elif data[0] == 'close':
self.close()
elif data[0] == 'error':
self.error()
elif data[0] == 'playlist':
self.playlist(data)
elif data[0] == '[youtube]':
self.pre_proc()
elif data[0] == '[download]':
self.download(data)
elif data[0] == '[ffmpeg]':
self.post_proc()
def finish(self):
self.ListCtrl._write_data(self.index, 4, '')
self.ListCtrl._write_data(self.index, 5, 'Finished')
def close(self):
self.ListCtrl._write_data(self.index, 3, '')
self.ListCtrl._write_data(self.index, 4, '')
self.ListCtrl._write_data(self.index, 5, 'Stopped')
def error(self):
self.ListCtrl._write_data(self.index, 3, '')
self.ListCtrl._write_data(self.index, 4, '')
self.ListCtrl._write_data(self.index, 5, 'Error')
def pre_proc(self):
self.ListCtrl._write_data(self.index, 5, 'Pre-Processing %s' % self.info)
def post_proc(self):
self.ListCtrl._write_data(self.index, 4, '')
self.ListCtrl._write_data(self.index, 5, 'Converting to Audio %s' % self.info)
def download(self, data):
self.ListCtrl._write_data(self.index, 1, data[3])
self.ListCtrl._write_data(self.index, 2, data[1])
self.ListCtrl._write_data(self.index, 3, data[7])
self.ListCtrl._write_data(self.index, 4, data[5])
self.ListCtrl._write_data(self.index, 5, 'Downloading %s' % self.info)
def playlist(self, data):
self.ListCtrl._write_data(self.index, 1, '')
self.ListCtrl._write_data(self.index, 2, '')
self.ListCtrl._write_data(self.index, 3, '')
self.ListCtrl._write_data(self.index, 4, '')
self.info = '%s/%s' % (data[1], data[2])
|
[
"ytubedlg@gmail.com"
] |
ytubedlg@gmail.com
|
573e3dd3b178f91dba7132715f6a34622c436e4e
|
972a694174dfbd25dbf27d8aa98d272625c2400f
|
/external/AnniesLasso/sandbox-scripts/plot_label_recovery.py
|
1313fcf1b91da476022e3379017fc0afce6ac37b
|
[
"MIT",
"BSD-3-Clause"
] |
permissive
|
sdss/apogee
|
d3344021ac66f91e4259dd1fcf160ee7657740ec
|
e134409dc14b20f69e68a0d4d34b2c1b5056a901
|
refs/heads/master
| 2021-08-06T18:44:13.668542
| 2021-06-11T13:00:51
| 2021-06-11T13:00:51
| 127,458,050
| 5
| 5
|
BSD-3-Clause
| 2018-09-20T22:18:47
| 2018-03-30T18:02:58
|
IDL
|
UTF-8
|
Python
| false
| false
| 4,970
|
py
|
"""
Plot the label recovery for the validation set as a function of S/N.
"""
import numpy as np
from matplotlib.ticker import MaxNLocator
from six.moves import cPickle as pickle
from collections import Counter, OrderedDict
models = {
"model1": "gridsearch-2.0-3.0-s2-heuristically-set.model.individual_visits"
}
label_names = OrderedDict([
('TEFF', r'$T_{\rm eff}$ $(\rm{K})$'),
('LOGG', r'$\log{g}$ $(\rm{dex})$'),
('AL_H', r'$[\rm{Al}/\rm{H}]$ $(\rm{dex})$'),
('CA_H', r'$[\rm{Ca}/\rm{H}]$ $(\rm{dex})$'),
('C_H', r'$[\rm{C}/\rm{H}]$ $(\rm{dex})$'),
('FE_H', r'$[\rm{Fe}/\rm{H}]$ $(\rm{dex})$'),
('K_H', r'$[\rm{K}/\rm{H}]$ $(\rm{dex})$'),
('MG_H', r'$[\rm{Mg}/\rm{H}]$ $(\rm{dex})$'),
('MN_H', r'$[\rm{Mn}/\rm{H}]$ $(\rm{dex})$'),
('NA_H', r'$[\rm{Na}/\rm{H}]$ $(\rm{dex})$'),
('NI_H', r'$[\rm{Ni}/\rm{H}]$ $(\rm{dex})$'),
('N_H', r'$[\rm{N}/\rm{H}]$ $(\rm{dex})$'),
('O_H', r'$[\rm{O}/\rm{H}]$ $(\rm{dex})$'),
('SI_H', r'$[\rm{Si}/\rm{H}]$ $(\rm{dex})$'),
('S_H', r'$[\rm{S}/\rm{H}]$ $(\rm{dex})$'),
('TI_H', r'$[\rm{Ti}/\rm{H}]$ $(\rm{dex})$'),
('V_H', r'$[\rm{V}/\rm{H}]$ $(\rm{dex})$'),
])
# Load the APOGEE IDs from individual visits from a separate file because I am
# an idiot.
with open("apogee_ids_from_individual_visits.pkl", "rb") as fp:
apogee_ids = pickle.load(fp)
fig, axes = plt.subplots(6, 3, figsize=(8.5, 12.5))
axes = np.array(axes).flatten()
N_repeats_min = 2
N_bins = 25
colors = "kr"
wrt_cannon = True
common_ylim = 0.5
minimum_apogee_snr = 50.0 # Mark the minimum S/N in any combined APOGEE spectra
counts = Counter(apogee_ids)
is_repeated_enough = np.array(
[(counts[_] >= N_repeats_min) for _ in apogee_ids])
# Define the metric to show at each bin.
# MAD
metric = lambda differences: np.median(np.abs(differences))
# RMS
#metric = lambda differences: np.sqrt(np.sum((differences**2))/differences.size)
for i, (model_name, model_filename) in enumerate(models.items()):
color = colors[i]
fill_color = "#CCCCCC"
# Load the data:
# (snrs, high_snr_expected, high_snr_inferred, differences_expected,
# differences_inferred, single_visit_inferred)
with open(model_filename, "rb") as fp:
contents = pickle.load(fp)
# Let's unpack that.
iv_snr, combined_aspcap, combined_cannon, \
differences_aspcap, differences_cannon, \
iv_cannon = contents
# Which label residuals should we show?
differences = differences_cannon if wrt_cannon else differences_aspcap
_, bin_edges, __ = axes[0].hist(iv_snr[is_repeated_enough],
histtype="step", lw=2, color=color, bins=N_bins)
axes[0].hist(iv_snr[is_repeated_enough], bins=N_bins,
facecolor=fill_color, edgecolor=fill_color, zorder=-1)
axes[0].set_ylabel(r"$\rm{Count}$")
#axes[0].text(0.95, 0.95, r"${0:.0f}$".format(is_repeated_enough.sum()),
# color=color, transform=axes[0].transAxes,
# horizontalalignment="right", verticalalignment="bottom")
for j, label_name in enumerate(label_names.keys()):
# Take the mean per bin.
x = np.diff(bin_edges)[0]/2. + bin_edges[:-1]
y = []
for k in range(len(bin_edges) - 1):
mask = (bin_edges[k + 1] > iv_snr) * (iv_snr >= bin_edges[k]) \
* is_repeated_enough
if not any(mask):
y.append(np.nan)
else:
y.append(metric(differences_cannon[mask, j]))
y = np.array(y)
ax = axes[j + 1]
ax.plot(x, y, drawstyle="steps-mid", c=color, lw=2)
# fuck
x2 = np.repeat(x, 2)[1:]
xstep = np.repeat((x[1:] - x[:-1]), 2)
xstep = np.concatenate(([xstep[0]], xstep, [xstep[-1]]))
x2 = np.append(x2, x2.max() + xstep[-1])
x2 -= xstep /2.
y2 = np.repeat(y, 2)
ax.fill_between(x2, np.zeros_like(y2), y2, where=np.ones_like(y2),
color=fill_color,
zorder=-1)
ax.set_ylabel(label_names[label_name])
# Set common y-axes for abundance labels?
ylim = common_ylim if common_ylim is not None \
else np.max([ax.get_ylim()[1] for ax in axes[3:]])
# Some custom limits:
# MAGIC
axes[1].set_ylim(0, 100)
axes[2].set_ylim(0, 0.2)
axes[0].yaxis.set_major_locator(MaxNLocator(4))
axes[1].yaxis.set_major_locator(MaxNLocator(4))
axes[2].set_yticks([0, 0.1, 0.2])
for ax in axes[3:]:
ax.set_ylim(0, ylim)
ax.set_yticks([0, 0.2, 0.4])
for ax in axes:
if minimum_apogee_snr is not None:
ax.axvline(minimum_apogee_snr, c="#666666", linestyle="--", zorder=-1)
ax.set_xlim(bin_edges[0], bin_edges[-1])
if not ax.is_last_row():
ax.set_xticklabels([])
else:
ax.set_xlabel(r"$S/N$")
ax.set(adjustable="box-forced", aspect=np.ptp(ax.get_xlim())/np.ptp(ax.get_ylim()))
fig.tight_layout()
fig.savefig("papers/validation-label-recovery.pdf", dpi=300)
raise a
|
[
"holtz@nmsu.edu"
] |
holtz@nmsu.edu
|
1e328158a74ff438282aeaa61b0fc8b109732a80
|
b61e64d8715eebaafcc2c5187568eca2ffe9eeb9
|
/bson/objectid.py
|
75b5a3f266db93f7059fc65e4fe17ea3c3d72817
|
[] |
no_license
|
pawel344/nosql
|
ea2954dcbd56e4222dbfff2a2c60badfe0ac826b
|
8e0a155fca8395617a499a5307c94eb633ff383e
|
refs/heads/master
| 2021-01-22T09:04:02.981146
| 2012-05-16T23:02:34
| 2012-05-16T23:02:34
| null | 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 8,836
|
py
|
# Copyright 2009-2012 10gen, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Tools for working with MongoDB `ObjectIds
<http://dochub.mongodb.org/core/objectids>`_.
"""
import binascii
import calendar
import datetime
try:
import hashlib
_md5func = hashlib.md5
except ImportError: # for Python < 2.5
import md5
_md5func = md5.new
import os
import socket
import struct
import threading
import time
from bson.errors import InvalidId
from bson.py3compat import (b, binary_type, text_type,
bytes_from_hex, string_types)
from bson.tz_util import utc
EMPTY = b("")
ZERO = b("\x00")
def _machine_bytes():
"""Get the machine portion of an ObjectId.
"""
machine_hash = _md5func()
machine_hash.update(socket.gethostname().encode())
return machine_hash.digest()[0:3]
class ObjectId(object):
"""A MongoDB ObjectId.
"""
_inc = 0
_inc_lock = threading.Lock()
_machine_bytes = _machine_bytes()
__slots__ = ('__id')
def __init__(self, oid=None):
"""Initialize a new ObjectId.
If `oid` is ``None``, create a new (unique) ObjectId. If `oid`
is an instance of (:class:`basestring` (:class:`str` or :class:`bytes`
in python 3), :class:`ObjectId`) validate it and use that. Otherwise,
a :class:`TypeError` is raised. If `oid` is invalid,
:class:`~bson.errors.InvalidId` is raised.
:Parameters:
- `oid` (optional): a valid ObjectId (12 byte binary or 24 character
hex string)
.. versionadded:: 1.2.1
The `oid` parameter can be a ``unicode`` instance (that contains
only hexadecimal digits).
.. mongodoc:: objectids
"""
if oid is None:
self.__generate()
else:
self.__validate(oid)
@classmethod
def from_datetime(cls, generation_time):
"""Create a dummy ObjectId instance with a specific generation time.
This method is useful for doing range queries on a field
containing :class:`ObjectId` instances.
.. warning::
It is not safe to insert a document containing an ObjectId
generated using this method. This method deliberately
eliminates the uniqueness guarantee that ObjectIds
generally provide. ObjectIds generated with this method
should be used exclusively in queries.
`generation_time` will be converted to UTC. Naive datetime
instances will be treated as though they already contain UTC.
An example using this helper to get documents where ``"_id"``
was generated before January 1, 2010 would be:
>>> gen_time = datetime.datetime(2010, 1, 1)
>>> dummy_id = ObjectId.from_datetime(gen_time)
>>> result = collection.find({"_id": {"$lt": dummy_id}})
:Parameters:
- `generation_time`: :class:`~datetime.datetime` to be used
as the generation time for the resulting ObjectId.
.. versionchanged:: 1.8
Properly handle timezone aware values for
`generation_time`.
.. versionadded:: 1.6
"""
if generation_time.utcoffset() is not None:
generation_time = generation_time - generation_time.utcoffset()
ts = calendar.timegm(generation_time.timetuple())
oid = struct.pack(">i", int(ts)) + ZERO * 8
return cls(oid)
def __generate(self):
"""Generate a new value for this ObjectId.
"""
oid = EMPTY
# 4 bytes current time
oid += struct.pack(">i", int(time.time()))
# 3 bytes machine
oid += ObjectId._machine_bytes
# 2 bytes pid
oid += struct.pack(">H", os.getpid() % 0xFFFF)
# 3 bytes inc
ObjectId._inc_lock.acquire()
oid += struct.pack(">i", ObjectId._inc)[1:4]
ObjectId._inc = (ObjectId._inc + 1) % 0xFFFFFF
ObjectId._inc_lock.release()
self.__id = oid
def __validate(self, oid):
"""Validate and use the given id for this ObjectId.
Raises TypeError if id is not an instance of
(:class:`basestring` (:class:`str` or :class:`bytes`
in python 3), ObjectId) and InvalidId if it is not a
valid ObjectId.
:Parameters:
- `oid`: a valid ObjectId
"""
if isinstance(oid, ObjectId):
self.__id = oid.__id
elif isinstance(oid, string_types):
if len(oid) == 12:
if isinstance(oid, binary_type):
self.__id = oid
else:
raise InvalidId("%s is not a valid ObjectId" % oid)
elif len(oid) == 24:
try:
self.__id = bytes_from_hex(oid)
except (TypeError, ValueError):
raise InvalidId("%s is not a valid ObjectId" % oid)
else:
raise InvalidId("%s is not a valid ObjectId" % oid)
else:
raise TypeError("id must be an instance of (%s, %s, ObjectId), "
"not %s" % (binary_type.__name__,
text_type.__name__, type(oid)))
@property
def binary(self):
"""12-byte binary representation of this ObjectId.
"""
return self.__id
@property
def generation_time(self):
"""A :class:`datetime.datetime` instance representing the time of
generation for this :class:`ObjectId`.
The :class:`datetime.datetime` is timezone aware, and
represents the generation time in UTC. It is precise to the
second.
.. versionchanged:: 1.8
Now return an aware datetime instead of a naive one.
.. versionadded:: 1.2
"""
t = struct.unpack(">i", self.__id[0:4])[0]
return datetime.datetime.fromtimestamp(t, utc)
def __getstate__(self):
"""return value of object for pickling.
needed explicitly because __slots__() defined.
"""
return self.__id
def __setstate__(self, value):
"""explicit state set from pickling
"""
# Provide backwards compatability with OIDs
# pickled with pymongo-1.9.
if isinstance(value, dict):
try:
# ObjectIds pickled in python 2.x used `str` for __id.
# In python 3.x this has to be converted to `bytes`
# by encoding latin-1.
self.__id = value['_ObjectId__id'].encode('latin-1')
except UnicodeDecodeError:
self.__id = value['_ObjectId__id']
else:
try:
# See the previous comment about python 2/3 pickle issues.
self.__id = value.encode('latin-1')
except (UnicodeDecodeError, AttributeError):
self.__id = value
def __str__(self):
return binascii.hexlify(self.__id).decode()
def __repr__(self):
return "ObjectId('%s')" % (str(self),)
def __eq__(self, other):
if isinstance(other, ObjectId):
return self.__id == other.__id
return NotImplemented
def __ne__(self,other):
if isinstance(other, ObjectId):
return self.__id != other.__id
return NotImplemented
def __lt__(self, other):
if isinstance(other, ObjectId):
return self.__id < other.__id
return NotImplemented
def __le__(self, other):
if isinstance(other, ObjectId):
return self.__id <= other.__id
return NotImplemented
def __gt__(self, other):
if isinstance(other, ObjectId):
return self.__id > other.__id
return NotImplemented
def __ge__(self, other):
if isinstance(other, ObjectId):
return self.__id >= other.__id
return NotImplemented
def __hash__(self):
"""Get a hash value for this :class:`ObjectId`.
.. versionadded:: 1.1
"""
return hash(self.__id)
|
[
"notroot@ubuntu.(none)"
] |
notroot@ubuntu.(none)
|
e451a171b6bdbc9987bf3c451b834584db2663b4
|
6d3f739586564d4b3ecd8afe8270ce3c213362af
|
/unet_train.py
|
d8568fe3393472579395bc3e495dc598ecd3c076
|
[] |
no_license
|
shantanu778/Image_Segmantation_Tensorflow_Unet_landcover_AI
|
672b35a137b0ffce1deb7e14725f52346dcf5be9
|
b5f744af21a2130a8d45a967a19dfbcc56bd7cc5
|
refs/heads/main
| 2023-04-20T17:56:16.635249
| 2021-05-20T09:16:32
| 2021-05-20T09:16:32
| 369,143,081
| 2
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 5,308
|
py
|
import tensorflow as tf
import os
import numpy as np
import glob
from tqdm import tqdm
import cv2
from matplotlib import pyplot as plt
from preprocess import data_loading
## Plot Mask Histogram
## Number of Class 3
'''
img = cv2.imread('masks/M-33-20-D-d-3-3.tif',cv2.IMREAD_COLOR)
img_arr = np.array(img)
np.unique(img_arr)
# alternative way to find histogram of an image
plt.hist(img.ravel(),256,[0,256])
plt.show()
cv2.imshow('masks', img)
cv2.waitKey(0)
#closing all open windows
cv2.destroyAllWindows()
'''
##Configuration
IMG_WIDTH = 256
IMG_HEIGHT = 256
CHANNELS = 3
BATCH_SIZE = 32
NUM_CLASSES=4
TRAIN_PATH = os.path.dirname(os.path.abspath('F:/Personal Projects/Compressed/landcover.ai/images'))
with open('train.txt') as f:
train_ids = f.readlines()
with open('val.txt') as f:
val_ids = f.readlines()
with open('test.txt') as f:
test_ids = f.readlines()
dataset = data_loading(train_ids, val_ids)
dataset = dataset
STEPS_PER_EPOCH = len(train_ids)//BATCH_SIZE
VALIDATION_STEPS = len(val_ids)//BATCH_SIZE
#Defining U-NET
inputs = tf.keras.layers.Input((IMG_WIDTH, IMG_HEIGHT, CHANNELS))
s = inputs
conv1 = tf.keras.layers.Conv2D(16, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(s)
conv1 = tf.keras.layers.Dropout(0.1)(conv1)
conv1 = tf.keras.layers.Conv2D(16, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(conv1)
pool1 = tf.keras.layers.MaxPooling2D(2,2)(conv1)
conv2 = tf.keras.layers.Conv2D(32, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(pool1)
conv2 = tf.keras.layers.Dropout(0.1)(conv2)
conv2 = tf.keras.layers.Conv2D(32, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(conv2)
pool2 = tf.keras.layers.MaxPooling2D(2,2)(conv2)
conv3 = tf.keras.layers.Conv2D(64, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(pool2)
conv3 = tf.keras.layers.Dropout(0.1)(conv3)
conv3 = tf.keras.layers.Conv2D(64, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(conv3)
pool3 = tf.keras.layers.MaxPooling2D(2,2)(conv3)
conv4 = tf.keras.layers.Conv2D(128, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(pool3)
conv4 = tf.keras.layers.Dropout(0.1)(conv4)
conv4 = tf.keras.layers.Conv2D(128, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(conv4)
pool4 = tf.keras.layers.MaxPooling2D(2,2)(conv4)
conv5 = tf.keras.layers.Conv2D(256, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(pool4)
conv5 = tf.keras.layers.Dropout(0.1)(conv5)
conv5 = tf.keras.layers.Conv2D(256, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(conv5)
#EXPANSIVE U-NET
u6 = tf.keras.layers.Conv2DTranspose(128,(2,2), strides=(2,2), padding='same')(conv5)
u6 = tf.keras.layers.concatenate([u6, conv4])
conv6 = tf.keras.layers.Conv2D(128, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(u6)
conv6 = tf.keras.layers.Dropout(0.1)(conv6)
conv6 = tf.keras.layers.Conv2D(128, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(conv6)
u7 = tf.keras.layers.Conv2DTranspose(64,(2,2), strides=(2,2), padding='same')(conv6)
u7 = tf.keras.layers.concatenate([u7, conv3])
conv7 = tf.keras.layers.Conv2D(64, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(u7)
conv7 = tf.keras.layers.Dropout(0.1)(conv7)
conv7 = tf.keras.layers.Conv2D(64, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(conv7)
u8 = tf.keras.layers.Conv2DTranspose(32,(2,2), strides=(2,2), padding='same')(conv7)
u8 = tf.keras.layers.concatenate([u8, conv2])
conv8 = tf.keras.layers.Conv2D(32, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(u8)
conv8 = tf.keras.layers.Dropout(0.1)(conv8)
conv8 = tf.keras.layers.Conv2D(32, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(conv8)
u9 = tf.keras.layers.Conv2DTranspose(16,(2,2), strides=(2,2), padding='same')(conv8)
u9 = tf.keras.layers.concatenate([u9, conv1])
conv9 = tf.keras.layers.Conv2D(16, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(u9)
conv9 = tf.keras.layers.Dropout(0.1)(conv9)
conv9 = tf.keras.layers.Conv2D(16, (3,3), activation='relu', kernel_initializer='he_normal', padding='same')(conv9)
outputs = tf.keras.layers.Conv2D(NUM_CLASSES,(1,1), activation='softmax')(conv9)
model = tf.keras.Model(inputs = [inputs], outputs = [outputs])
model.compile(optimizer='adam', loss=tf.keras.losses.SparseCategoricalCrossentropy(),
metrics=['accuracy'])
es = tf.keras.callbacks.EarlyStopping(monitor='val_loss',
patience=10)
checkpoint = tf.keras.callbacks.ModelCheckpoint('unet_model_for_lancover_2.h5',
verbose=1,
save_best_only=True)
tensorboard = tf.keras.callbacks.TensorBoard(log_dir='logs')
results = model.fit(dataset['train'],
steps_per_epoch=STEPS_PER_EPOCH,
epochs = 50, validation_data = dataset['val'],
validation_steps = VALIDATION_STEPS,
callbacks = [es,checkpoint,tensorboard])
|
[
"shantunath778@gmail.com"
] |
shantunath778@gmail.com
|
d8ee10cbc40b90df55996475316537ec7e192c61
|
24fe1f54fee3a3df952ca26cce839cc18124357a
|
/servicegraph/lib/python2.7/site-packages/acimodel-4.0_3d-py2.7.egg/cobra/modelimpl/infra/rtpathtospaccgrp.py
|
eef4e3bb87ae031c1d22f63484adf1bc4d67f73b
|
[] |
no_license
|
aperiyed/servicegraph-cloudcenter
|
4b8dc9e776f6814cf07fe966fbd4a3481d0f45ff
|
9eb7975f2f6835e1c0528563a771526896306392
|
refs/heads/master
| 2023-05-10T17:27:18.022381
| 2020-01-20T09:18:28
| 2020-01-20T09:18:28
| 235,065,676
| 0
| 0
| null | 2023-05-01T21:19:14
| 2020-01-20T09:36:37
|
Python
|
UTF-8
|
Python
| false
| false
| 4,746
|
py
|
# coding=UTF-8
# **********************************************************************
# Copyright (c) 2013-2019 Cisco Systems, Inc. All rights reserved
# written by zen warriors, do not modify!
# **********************************************************************
from cobra.mit.meta import ClassMeta
from cobra.mit.meta import StatsClassMeta
from cobra.mit.meta import CounterMeta
from cobra.mit.meta import PropMeta
from cobra.mit.meta import Category
from cobra.mit.meta import SourceRelationMeta
from cobra.mit.meta import NamedSourceRelationMeta
from cobra.mit.meta import TargetRelationMeta
from cobra.mit.meta import DeploymentPathMeta, DeploymentCategory
from cobra.model.category import MoCategory, PropCategory, CounterCategory
from cobra.mit.mo import Mo
# ##################################################
class RtPathToSpAccGrp(Mo):
"""
Mo doc not defined in techpub!!!
"""
meta = TargetRelationMeta("cobra.model.infra.RtPathToSpAccGrp", "cobra.model.infra.SHPathS")
meta.moClassName = "infraRtPathToSpAccGrp"
meta.rnFormat = "rtpathToSpAccGrp-[%(tDn)s]"
meta.category = MoCategory.RELATIONSHIP_FROM_LOCAL
meta.label = "Host Path Selector"
meta.writeAccessMask = 0x100000000001
meta.readAccessMask = 0x80100000000001
meta.isDomainable = False
meta.isReadOnly = True
meta.isConfigurable = False
meta.isDeletable = False
meta.isContextRoot = False
meta.parentClasses.add("cobra.model.infra.SpAccPortGrp")
meta.superClasses.add("cobra.model.reln.From")
meta.superClasses.add("cobra.model.reln.Inst")
meta.rnPrefixes = [
('rtpathToSpAccGrp-', True),
]
prop = PropMeta("str", "childAction", "childAction", 4, PropCategory.CHILD_ACTION)
prop.label = "None"
prop.isImplicit = True
prop.isAdmin = True
prop._addConstant("deleteAll", "deleteall", 16384)
prop._addConstant("deleteNonPresent", "deletenonpresent", 8192)
prop._addConstant("ignore", "ignore", 4096)
meta.props.add("childAction", prop)
prop = PropMeta("str", "dn", "dn", 1, PropCategory.DN)
prop.label = "None"
prop.isDn = True
prop.isImplicit = True
prop.isAdmin = True
prop.isCreateOnly = True
meta.props.add("dn", prop)
prop = PropMeta("str", "lcOwn", "lcOwn", 9, PropCategory.REGULAR)
prop.label = "None"
prop.isImplicit = True
prop.isAdmin = True
prop.defaultValue = 0
prop.defaultValueStr = "local"
prop._addConstant("implicit", "implicit", 4)
prop._addConstant("local", "local", 0)
prop._addConstant("policy", "policy", 1)
prop._addConstant("replica", "replica", 2)
prop._addConstant("resolveOnBehalf", "resolvedonbehalf", 3)
meta.props.add("lcOwn", prop)
prop = PropMeta("str", "modTs", "modTs", 7, PropCategory.REGULAR)
prop.label = "None"
prop.isImplicit = True
prop.isAdmin = True
prop.defaultValue = 0
prop.defaultValueStr = "never"
prop._addConstant("never", "never", 0)
meta.props.add("modTs", prop)
prop = PropMeta("str", "rn", "rn", 2, PropCategory.RN)
prop.label = "None"
prop.isRn = True
prop.isImplicit = True
prop.isAdmin = True
prop.isCreateOnly = True
meta.props.add("rn", prop)
prop = PropMeta("str", "status", "status", 3, PropCategory.STATUS)
prop.label = "None"
prop.isImplicit = True
prop.isAdmin = True
prop._addConstant("created", "created", 2)
prop._addConstant("deleted", "deleted", 8)
prop._addConstant("modified", "modified", 4)
meta.props.add("status", prop)
prop = PropMeta("str", "tCl", "tCl", 24369, PropCategory.REGULAR)
prop.label = "Target-class"
prop.isImplicit = True
prop.isAdmin = True
prop.defaultValue = 8244
prop.defaultValueStr = "infraSHPathS"
prop._addConstant("infraSHPathS", None, 8244)
prop._addConstant("unspecified", "unspecified", 0)
meta.props.add("tCl", prop)
prop = PropMeta("str", "tDn", "tDn", 24368, PropCategory.REGULAR)
prop.label = "Target-dn"
prop.isConfig = True
prop.isAdmin = True
prop.isCreateOnly = True
prop.isNaming = True
meta.props.add("tDn", prop)
meta.namingProps.append(getattr(meta.props, "tDn"))
getattr(meta.props, "tDn").needDelimiter = True
# Deployment Meta
meta.deploymentQuery = True
meta.deploymentType = "Ancestor"
meta.deploymentQueryPaths.append(DeploymentPathMeta("AccBaseGrpToEthIf", "Interface", "cobra.model.l1.EthIf"))
def __init__(self, parentMoOrDn, tDn, markDirty=True, **creationProps):
namingVals = [tDn]
Mo.__init__(self, parentMoOrDn, markDirty, *namingVals, **creationProps)
# End of package file
# ##################################################
|
[
"rrishike@cisco.com"
] |
rrishike@cisco.com
|
caad58faa73eecb141cdfe7e2295c03ac8db6083
|
427eefd3d18d4323ac2e3920aabc50d7346b7c11
|
/reading.py
|
f7b67bdddb023032fa6d9f934129b0e3478374df
|
[] |
no_license
|
jvparidon/tamil-test-suite
|
b9f0f53002793103a4e6e2686dff8547df0ba94d
|
74bd6b45555ad35aa9c3969e65185de5a1407ebb
|
refs/heads/master
| 2021-07-02T17:44:00.313961
| 2020-09-01T16:52:31
| 2020-09-01T16:52:31
| 155,201,570
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,619
|
py
|
import audio
from psychopy import prefs
prefs.general['audioLib'] = ['pygame']
from psychopy import core, visual
from test_tools import get_pp_info, pause
# experiment routines for presenting word reading stimuli and recording spoken responses
class Experiment(object):
def __init__(self, mode, pp_info, fps=60.0):
self.mode = mode
self.pp_info = pp_info
self.fps = fps
# set up file paths, etc.
self.log_fname = 'logs/reading/' + mode + '_' + pp_info['literate'] + '_' + pp_info['number'] + '.wav'
def run(self):
# set up presentation window color, and size
bgcolor = 'black'
txtcolor = 'white'
self.win = visual.Window(fullscr=True, color=bgcolor)
#self.win = visual.Window((1200, 900), color=bgcolor) # temporary presentation window setup, exchange for line above when running actual experiment
self.text = visual.TextStim(self.win, color=txtcolor)
for i in range(5, 0, -1):
self.text.text = '+' * (2 * i - 1)
self.text.draw()
self.win.flip()
core.wait(1)
self.text.text = '-'
self.text.draw()
self.win.flip()
# record
samples = audio.record(60, wait=True)
self.text.text = '+'
self.text.draw()
self.win.flip()
audio.write(self.log_fname, samples)
core.wait(3)
self.win.close()
if __name__ == '__main__':
pp_info = get_pp_info()
for mode in ['tamil', 'tamil_nonword', 'english', 'english_nonword']:
pause()
Experiment(mode, pp_info).run()
|
[
"jvparidon@gmail.com"
] |
jvparidon@gmail.com
|
b7c1d90ded90c00f06a5b584532562d4652f4c1e
|
d98d2f725cb425eb38de6a34a7ba601b84fcad44
|
/MediaPrep1.py
|
35d8199d4543d6fcc55c4e4fdc5d817082fd8c6a
|
[] |
no_license
|
Naturalenemy07/Opentrons
|
438f624001b759dcdc43793342e3e996e1625a9b
|
3470dc46e3c970a696d4397ce3613527618ba972
|
refs/heads/master
| 2020-04-07T01:12:27.519214
| 2020-01-20T03:55:08
| 2020-01-20T03:55:08
| 157,934,798
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 4,442
|
py
|
"""This protocol is for prepping different media conditions in a plate (Duetz or otherwise). It relies on
a list from the Opentrons Protocol Settings protocol to determine the type of media and what wells to
add it to."""
from opentrons import robot, containers, instruments
class MediaPrepSettings:
def __init__(self):
self.mediadict = dict() # names of media and their locations
def add_media(self, name, concentration, location):
mytuple = (concentration, location, list())
self.mediadict[name] = mytuple
# This function is written pretty general, it can be used for multiple read ins.
def importmediasettings(self):
f = open('C:/Users/User/Desktop/mediasettings.txt')
Medias = list()
while True:
line = f.readline()
if line.find("Media Stocks:") != -1:
num_media = int(line[-2])
for i in range(num_media):
media = f.readline()[-1]
media = media.split('\t')
Medias.append(media)
if line.find("Strains") != -1:
num_strains = int(line[-2])
if ismedia != -1:
medianame = line[ismedia+11:-1]
else:
self.mediadict[medianame][2].append(line[:-1])
f.close()
#if no number assume a concentration of 1x
class Plate:
def __init__(self):
self.totalvolume = 500
self.wellmatrix = dict()
self.fill_wellmatrix()
def fill_wellmatrix(self):
f = open('C:/Users/Trinh Lab/Desktop/OpentronsProtocols/96welllist.txt')
for line in f:
self.wellmatrix[line[:-1]] = 0
f.close()
def change_well_volume(self, mywell, amount_added):
self.wellmatrix[mywell] += amount_added
def get_well_volume(self, mywell):
return self.wellmatrix[mywell]
# Initializing the containers and media
p1000rack = containers.load('tiprack-1000ul', 'D2')
trash = containers.load('point', 'D1')
DuetzPlate = containers.load('96-deep-well', 'A1')
smalltubes = containers.load('tube-rack-2ml', 'B2')
bigtubes = containers.load('tube-rack-15_50ml', 'C2')
# These are the hardcoded media that will be added via the protocol gui later.
MyMedia = MediaPrepSettings()
Plate1 = Plate()
# Medias
MyMedia.add_media('SC-Leu-Ura',2, bigtubes.wells('A4'))
MyMedia.add_media('Leu', 40, bigtubes.wells('B4'))
MyMedia.add_media('Ura', 50, bigtubes.wells('B2'))
MyMedia.add_media('YPD', 1.11, bigtubes.wells('A2'))
# Carbon Sources
MyMedia.add_media('Galactose', 10, bigtubes.wells('B1'))
MyMedia.add_media('Glucose', 10, bigtubes.wells('A1'))
# Antibiotics
MyMedia.add_media('G418', 10, bigtubes.wells('C1'))
MyMedia.add_media('Amp', 10, bigtubes.wells('C2'))
MyMedia.importmediasettings()
# Initialize the Pipette
p1000_single = instruments.Pipette(
axis="b",
name='p1000',
max_volume=900,
min_volume=50,
channels=1,
trash_container=trash,
tip_racks=[p1000rack]
)
# ---PROTOCOL--- #
# Distribute every needed media from the list
for media, info in MyMedia.mediadict.items():
vol = Plate1.totalvolume / info[0]
p1000_single.distribute(vol, info[1], DuetzPlate.wells(info[2]), disposal_vol=10)
for well in info[2]: # Iterates through every well that requires the media and adds media to it
Plate1.change_well_volume(well, vol) # reset the volume on the plate tracker
# Determine the appropriate volume of water for each well to get to its final total volume
wells_lists = list()
# Temporary Storage
cum_volume = 0
well_subset = list()
for well in Plate1.wellmatrix:
vol_water = int(Plate1.totalvolume) - int(Plate1.wellmatrix[well])
if cum_volume + vol_water >= 800:
# Consolidate current information:
wells_lists.append([well_subset, cum_volume])
#Reset the temporary storage:
well_subset = []
cum_volume = 0
# Add inf into temporary storage vectors
cum_volume += vol_water
well_subset.append([well, vol_water])
wells_lists.append([well_subset, cum_volume])
#Add the appropriate volume of water to each of the wells
p1000_single.pick_up_tip(p1000rack)
for wells in wells_lists:
p1000_single.aspirate(wells[1]+10, bigtubes.wells('A3'))
for awell in wells[0]:
p1000_single.dispense(awell[1], DuetzPlate.wells(awell[0])) # index 1 gives volume, index 0 is the well name
p1000_single.blow_out(trash)
p1000_single.drop_tip(trash)
|
[
"noreply@github.com"
] |
Naturalenemy07.noreply@github.com
|
595e5bca39ed448a4b056fa662028de4209da8f1
|
aa6667f476b2c6f9c79d49acffc3f6c0f9b69597
|
/setup.py
|
3089700fb7316e15568bf9f812cf712bff36472d
|
[
"WTFPL"
] |
permissive
|
jziemer1996/BanDiTS
|
212f84c4ddc616b4cbd44f2429745e6ac4dfe040
|
f6a2b2fda4363f83de18059366381c4fbe7f1e5b
|
refs/heads/master
| 2021-06-13T23:20:12.412149
| 2020-05-11T14:27:07
| 2020-05-11T14:27:07
| 254,461,079
| 0
| 0
|
WTFPL
| 2020-04-09T19:31:06
| 2020-04-09T19:31:06
| null |
UTF-8
|
Python
| false
| false
| 1,308
|
py
|
from setuptools import setup, find_packages
import os
import sys
directory = os.path.abspath(os.path.dirname(__file__))
if sys.version_info >= (3, 0):
with open(os.path.join(directory, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
else:
with open(os.path.join(directory, 'README.md')) as f:
long_description = f.read()
setup(name='BanDiTS',
packages=find_packages(),
include_package_data=True,
setup_requires=['setuptools_scm'],
use_scm_version=True,
description='A Python module for time series analysis',
classifiers=[
'License :: FSF Approved :: WTFPL License',
'Operating System :: Microsoft :: Windows',
'Programming Language :: Python',
],
install_requires=["fiona",
'scipy',
'rasterio',
'pathos>=0.2',
'numpy'],
python_requires='>=3.6.0',
url='https://github.com/marlinmm/GEO419_South_Africa.git',
author='Marlin Mueller', #'Jonas Ziemer' # how to add second author?
author_email='marlin.markus.mueller@uni-jena.de',
license='WTFPL',
zip_safe=False,
long_description=long_description,
long_description_content_type='text/markdown')
|
[
"marlinmueller.mm@gmail.com"
] |
marlinmueller.mm@gmail.com
|
f73f3efc3938ee3cf1a170decf4ffb381517ee34
|
97d1fe99690ea7e02d2ba0e1750b27c5123ecbcc
|
/tuxradar/mousegame/ball1.py
|
501c737b038d3065d11dda7e65a8ae4e72627561
|
[] |
no_license
|
AdmiralAsshat/learn_python
|
3c7f9ac7518b9da1e6d6bdc5dcf6bc4bdb813d67
|
89fd515855b5dd487e45d0970f1790cde1e88657
|
refs/heads/master
| 2021-01-19T10:02:22.650283
| 2016-10-29T18:46:03
| 2016-10-29T18:46:03
| 13,074,466
| 7
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 906
|
py
|
from pygame import * # Why this instead of just import pygame?
ballpic = image.load('ball.png')
done = False
ballx = 0 # ball_x would be easier to read
bally = 0
ballxmove = 1 # velocity
ballymove = 1
init()
screen = display.set_mode((640,480)) # Is there an autodetect native resolution function?
display.set_caption('Balls in my mouth')
while done == False:
screen.fill(0) # Fill screen with black (color 0)
screen.blit(ballpic, (ballx, bally)) # Does blit insert pic at center or at bottom-left corner?
display.update()
time.delay(1) # Slow it down!
ballx += ballxmove # Update ball position
bally += ballymove
if ballx > 600: # Ball reached screen edges?
ballxmove = -1
if ballx < 0:
ballxmove = 1
if bally > 440:
ballymove = -1
if bally < 0:
ballymove = 1
for e in event.get(): # Check for ESC pressed
if e.type == KEYUP:
if e.key == K_ESCAPE:
done = True
|
[
"asshatadmiral@gmail.com"
] |
asshatadmiral@gmail.com
|
a26b89cd6a7378808cf4517d87628ab0508d4c0b
|
7db3d7f745693479238f6d3af98cb970408bfcca
|
/src/python/pants/engine/internals/options_parsing_test.py
|
047964d04683963d0024b7e1c2edf0c7aee882ca
|
[
"Apache-2.0"
] |
permissive
|
silverguo/pants
|
3b75bc0e736f2de5b41c2ddb8ba21f0d7cc314da
|
141510d03fbf2b7e1a0b54f66b54088697f6fa51
|
refs/heads/master
| 2022-05-24T13:57:02.596103
| 2020-04-23T02:39:59
| 2020-04-23T02:39:59
| 257,949,101
| 0
| 0
|
Apache-2.0
| 2020-04-22T15:54:24
| 2020-04-22T15:54:24
| null |
UTF-8
|
Python
| false
| false
| 2,716
|
py
|
# Copyright 2018 Pants project contributors (see CONTRIBUTORS.md).
# Licensed under the Apache License, Version 2.0 (see LICENSE).
from pants.engine.selectors import Params
from pants.init.options_initializer import BuildConfigInitializer
from pants.option.options_bootstrapper import OptionsBootstrapper
from pants.option.scope import GLOBAL_SCOPE, Scope, ScopedOptions
from pants.testutil.test_base import TestBase
from pants.util.logging import LogLevel
class TestEngineOptionsParsing(TestBase):
def _ob(self, args=tuple(), env=tuple()):
self.create_file("pants.toml")
options_bootstrap = OptionsBootstrapper.create(args=tuple(args), env=dict(env),)
# NB: BuildConfigInitializer has sideeffects on first-run: in actual usage, these
# sideeffects will happen during setup. We force them here.
BuildConfigInitializer.get(options_bootstrap)
return options_bootstrap
def test_options_parse_scoped(self):
options_bootstrapper = self._ob(
args=["./pants", "-ldebug", "binary", "src/python::"],
env=dict(PANTS_ENABLE_PANTSD="True", PANTS_BINARIES_BASEURLS='["https://bins.com"]'),
)
global_options_params = Params(Scope(str(GLOBAL_SCOPE)), options_bootstrapper)
python_setup_options_params = Params(Scope(str("python-setup")), options_bootstrapper)
global_options, python_setup_options = self.scheduler.product_request(
ScopedOptions, [global_options_params, python_setup_options_params],
)
self.assertEqual(global_options.options.level, LogLevel.DEBUG)
self.assertEqual(global_options.options.enable_pantsd, True)
self.assertEqual(global_options.options.binaries_baseurls, ["https://bins.com"])
self.assertEqual(python_setup_options.options.platforms, ["current"])
def test_options_parse_memoization(self):
# Confirm that re-executing with a new-but-identical Options object results in memoization.
def ob():
return self._ob(args=["./pants", "-ldebug", "binary", "src/python::"])
def parse(ob):
params = Params(Scope(str(GLOBAL_SCOPE)), ob)
return self.request_single_product(ScopedOptions, params)
# If two OptionsBootstrapper instances are not equal, memoization will definitely not kick in.
one_opts = ob()
two_opts = ob()
self.assertEquals(one_opts, two_opts)
self.assertEquals(hash(one_opts), hash(two_opts))
# If they are equal, executing parsing on them should result in a memoized object.
one = parse(one_opts)
two = parse(two_opts)
self.assertEqual(one, two)
self.assertIs(one, two)
|
[
"noreply@github.com"
] |
silverguo.noreply@github.com
|
50ddaaeab08af012481289d7553d0e3129d36c18
|
0f9a97d48a9f0179bcf1e3d80c08340096eb561e
|
/ДЗ-5. Функции и рекурсия/K. Возведение в степень.py
|
b21cb2ad4fda6a241147eb326ed1dbb62d7ade51
|
[] |
no_license
|
dmitryokh/python
|
96d8ec8c3f2d3428b90d510a1003aecf102b13d0
|
8efe761412779bed9a7516832d3152843088fa43
|
refs/heads/master
| 2020-04-24T03:08:42.865813
| 2019-02-20T11:41:52
| 2019-02-20T11:41:52
| 171,661,235
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 189
|
py
|
def power(a, n):
if n == 0:
return("1")
elif n == 1:
return(a)
else:
return(power(a, n - 1) * a)
a = float(input())
n = int(input())
print(power(a, n))
|
[
"noreply@github.com"
] |
dmitryokh.noreply@github.com
|
d17c784e4f5fe6bed513799634a673e566433300
|
7c3ba04f7a7894d95da7ef0affc57e609ca03459
|
/differentModels/train4.py
|
57f5451f13bb596efbbaab4aa44fd2e488751e37
|
[] |
no_license
|
muellerelias/nnpostprocessing
|
cc49adbbc17cdb15e5923e485823687c6f3e3a77
|
f4686cd205c95da232f9711dea69d250efe20ac9
|
refs/heads/master
| 2023-01-28T09:56:53.692428
| 2020-12-15T08:31:23
| 2020-12-15T08:31:23
| 272,470,116
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 6,193
|
py
|
# go to parent directory
import sys
sys.path.append('..')
import argparse
import json
import os
from datetime import datetime
import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
from tensorflow.keras import utils
from tensorflow.keras.layers import (Activation, Concatenate, Dense, Embedding,
Flatten, Input, InputLayer)
from tensorflow.keras.models import Model, Sequential
from tensorflow.keras.optimizers import SGD, Adam
import dataset.converter as converter
import dataset.helper.crps as crps
import dataset.shape as shape
import helper as helpers
import model.build_model as modelprovider
import model.loss_functions as loss
"""
- temperature + remaining NWP inputs
"""
expname = 'model-4'
forecast = '15days'
numpy_path = '/home/elias/Nextcloud/1.Masterarbeit/Daten/'+forecast+'/vorverarbeitetRegime/'
logdir = '/home/elias/Nextcloud/1.Masterarbeit/Tests/'+forecast+'/'
batchsize = 16
epochs = 30
initial_epochs = 0
learning_rate = 5e-05
train_model = False
def main():
start = datetime.now()
# get the data
train_data = helpers.load_data(numpy_path, 'train_set.npy')
valid_data = helpers.load_data(numpy_path, 'valid_set.npy')
test_data = helpers.load_data(numpy_path, 'test_set.npy')
# filter the data
test_data_labels = np.array([item[0] for item in test_data[:, 2]])
test_data_countries = np.array([item[0] for item in test_data[:, 0]])
test_data_month = test_data[:, 5]
# convert the data
train_dataset, train_shape = convert_dataset(
train_data, batchsize=batchsize, shuffle=1000, shape=True)
valid_dataset = convert_dataset(
valid_data, batchsize=1000, shuffle=100)
test_dataset = convert_dataset(
test_data, batchsize=1000)
# build the model
model = build_model(
train_shape[1], train_shape[2])
# Print Model
# modelprovider.printModel(model, dir=os.path.join(
# logdir, expname), name=expname+".png")
# compiling the model
lossfn = loss.crps_cost_function
opt = Adam(lr=learning_rate, amsgrad=True)
model.compile(loss=lossfn, optimizer=opt)
# Load model if exits
checkpoint_dir = os.path.join(logdir, expname, 'checkpoints/')
# begin with training 10 times
print('[INFO] Starting training')
predictions = []
for i in range(1, 11):
print('Round number: '+str(i))
model = build_model(
train_shape[1], train_shape[2])
# compile new model with new inital weights
model.compile(loss=lossfn, optimizer=opt)
# checkpoint callbacks
# all checkpoints
cp_callback_versuch = tf.keras.callbacks.ModelCheckpoint(
os.path.join(checkpoint_dir, 'round-'+str(i)+'/')+"checkpoint_{epoch}", monitor='val_loss', save_weights_only=True, mode='min', verbose=0)
# best checkpoint
cp_callback = tf.keras.callbacks.ModelCheckpoint(
os.path.join(checkpoint_dir, 'round-'+str(i)+'/checkpoint'), monitor='val_loss', save_weights_only=True, mode='min', save_best_only=True, verbose=0)
# train the model
if train_model:
model.fit(
train_dataset,
epochs=epochs,
initial_epoch=initial_epochs,
batch_size=batchsize,
verbose=1,
validation_data=valid_dataset,
validation_batch_size=1000,
callbacks=[cp_callback, cp_callback_versuch],
)
# load the best checkpoint of round i
model.load_weights(os.path.join(checkpoint_dir, 'round-'+str(i)+'/checkpoint')).expect_partial()
predictions.append(model.predict(
test_dataset, batch_size=1000, verbose=0))
# convert to numpy array
predictions = np.array(predictions)
# Make sure std is positive
predictions[:, :, 1] = np.abs(predictions[:, :, 1])
mean_predictions = np.mean(predictions, 0)
# calculate the score for each record in test set
test_crps = crps.norm_data(test_data_labels, mean_predictions)
# print the results with filters
helpers.printIntCountries(test_data_labels, test_data_countries , mean_predictions)
helpers.printHist(helpers.datasetPIT(mean_predictions, test_data_labels))
np.save(os.path.join(logdir, expname, 'prediction'), predictions)
print(datetime.now()-start)
def build_model(shape_vec, shape_mat):
# first branch for the
inp1 = Input(shape=(1,), name='Country_ID')
model1 = Embedding(23, 2, name='Country_Embedding')(inp1)
model1 = Flatten()(model1)
# second branch for the vector input
inp2 = Input(shape=(1,), name="Date_and_Regimes")
# third branch for the matrix input
inp3 = Input(shape=shape_mat, name="Ensemble")
model3 = Flatten()(inp3)
# concatenate the two inputs
x = Concatenate(axis=1)([model1,inp2, model3])
# add the hiddden layers
x = Dense(100, activation='linear' , name="Combined_Hidden_Layer_1")(x)
x = Dense(100, activation='relu' , name="Combined_Hidden_Layer_2")(x)
x = Dense(100, activation='relu' , name="Combined_Hidden_Layer_3")(x)
x = Dense( 2, activation='linear' , name="Output_Layer")(x)
# returns the Model
return Model([inp1,inp2, inp3], outputs=x)
def convert_dataset(data, batchsize=None, shuffle=None, shape=False):
input1 = []
input2 = []
input3 = []
label = []
for item in data:
input1.append( item[0][0] )
input2.append(item[0][1])
input3.append(item[1])
label.append(item[2][0])
dataset_input = tf.data.Dataset.from_tensor_slices((input1, input2, input3))
dataset_label = tf.data.Dataset.from_tensor_slices(label)
dataset = tf.data.Dataset.zip((dataset_input, dataset_label))
if (shuffle != None):
dataset = dataset.shuffle(shuffle)
if (batchsize != None):
dataset = dataset.batch(batchsize)
if (shape):
return dataset, (input1[0].shape , input2[0].shape, input3[0].shape)
else:
return dataset
if __name__ == "__main__":
helpers.mkdir_not_exists(os.path.join(logdir, expname))
main()
|
[
"elias@mumail.de"
] |
elias@mumail.de
|
295b40469d0181e648db1e4009021cac508e9f74
|
bf2553af41f11067751000f4e504399cce5c4e49
|
/Prediction of Wastewater Treatment Plant Performances by Artificial Intelligence/Asya/ultrafiltrasyon/forxgboost.py
|
4d0ae375c5449b2facac0236eb71af17ac28fd9e
|
[] |
no_license
|
emrecemaksu/Python
|
ae6d27bd934b050c962527310a6be13bdec462ff
|
07091f100293999f9669120ba5bf28ea2f8dff2d
|
refs/heads/master
| 2020-06-19T14:57:11.121356
| 2019-07-13T18:20:31
| 2019-07-13T18:20:31
| 196,753,154
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 3,044
|
py
|
# -*- coding: utf-8 -*-
"""
Created on Thu Feb 20 21:13:46 2019
@author: emrecemaksu
"""
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.preprocessing import Imputer
from sklearn.model_selection import train_test_split
from sklearn import ensemble
from xgboost.sklearn import XGBRegressor
from sklearn.metrics import r2_score
from sklearn.svm import SVR
from sklearn.preprocessing import StandardScaler
veriler = pd.read_csv("veriler_uf.csv")
Nhdort = veriler[["NH4N"]]
ALF = veriler[["Averageleachateflow"]]
SS = veriler[["SS"]]
Sicaklik = veriler[["Temperature"]]
Cod = veriler[["COD"]]
MLSSAero = veriler[["MLSSaerobic"]]
Nuf = veriler[["NH4NUF"]]
Coduf = veriler[["CODUF"]]
imputer= Imputer
imputer= Imputer(missing_values='NaN', strategy = 'mean', axis=0 )
SS = imputer.fit_transform(SS)
MLSSAero = imputer.fit_transform(MLSSAero)
SS = pd.DataFrame(data = SS, index = range(358), columns=['SS'])
MLSSAero = pd.DataFrame(data = MLSSAero, index = range(358), columns =['MLSSAero'])
degerler = pd.concat([Cod, Nhdort, SS, ALF, Sicaklik, MLSSAero], axis=1)
x_train, x_test, y_train, y_test = train_test_split(degerler, Coduf, test_size=0.25, random_state=57)
params = {'n_estimators': 9, 'max_depth': 14, 'min_samples_split': 12,'learning_rate': 0.3, 'loss': 'ls'}
model = ensemble.GradientBoostingRegressor(**params)
model.fit(x_train, y_train)
y_pred = model.predict(x_test)
print('\nXGBOOST CODUF R2 Skoru => ')
print(r2_score(y_test, y_pred))
"""
x_train_NUF, x_test_NUF, y_train_NUF, y_test_NUF = train_test_split(degerler, Nuf, test_size=0.10, random_state=5)
params2 = {'n_estimators': 16, 'max_depth': 5, 'min_samples_split': 4,'learning_rate': 0.66, 'loss': 'ls'}
model_NUF = ensemble.GradientBoostingRegressor(**params2)
model_NUF.fit(x_train_NUF, y_train_NUF)
y_pred_NUF = model_NUF.predict(x_test_NUF)
print('\nXGBOOST NH4UF R2 Skoru => ')
print(r2_score(y_test_NUF, y_pred_NUF))
eskiskor = 0
eskiestimator = 0
eskidepth = 0
eskisplit = 0
eskirandom = 0
eskirate = 0
for rate in np.arange(0.3, 1, 0.10):
for estimator in range(1,30):
for depth in range(1,30):
for randomsta in range(0,75):
for split in range(2,75):
x_train, x_test, y_train, y_test = train_test_split(degerler, Coduf, test_size=0.25, random_state=randomsta)
params2 = {'n_estimators': estimator, 'max_depth': depth, 'min_samples_split': split,'learning_rate': rate, 'loss': 'ls'}
model = ensemble.GradientBoostingRegressor(**params2)
model.fit(x_train, y_train)
y_pred = model.predict(x_test)
skor = r2_score(y_test, y_pred)
if(skor > eskiskor):
eskiskor = skor
eskirandom = randomsta
eskisplit = split
eskidepth = depth
eskiestimator = estimator
eskirate = rate
"""
|
[
"emrecemaksu@hotmail.com"
] |
emrecemaksu@hotmail.com
|
1a83cc3491267b032c141421d5d9bb8d0fc1472a
|
c702d957c9bb1655ffab7da46c54fc3d0c1c21a8
|
/flask/citation_venn.py
|
2bba0088e32f1622be58f24ad0ba7b251a79a9c6
|
[] |
no_license
|
julianpistorius/Webdev-for-bioNLP-lit-tool
|
87af23f5657b58a4e914057f1e5bbfe3b8ab2159
|
3a1646314c21a0b749437fa08fd63ff50f330e0c
|
refs/heads/master
| 2021-01-25T09:44:54.349659
| 2017-06-06T19:01:22
| 2017-06-06T19:01:22
| 93,875,232
| 1
| 0
| null | 2017-06-09T16:00:34
| 2017-06-09T16:00:34
| null |
UTF-8
|
Python
| false
| false
| 3,357
|
py
|
from database_management import db_citation_titles, db_citation_pmc_ids
from itertools import combinations
from collections import defaultdict
#pmid_list = ['18269575']
#pmid_list = ['18269575', '18952863']
def make_venn(pmid_list):
i = 0
i_count = []
all_pmcids = [] #[pmc1, pmc2, ... pmc-n]
pmc_id_list = [] #list of lists [[pmid_ids paper1], [pmid_ids paper2]]
citationsDict = defaultdict(list)
possible_vals = []
venn_data = []
for pmid in pmid_list:
#add pmc_ids to master list for making citationsDict
pmc_ids = db_citation_pmc_ids(pmid)
pmc_id_list.append(pmc_ids)
for id in pmc_ids:
all_pmcids.append(id)
#do first entries for venn
x = [int(i)]
pmid_label = 'PMID:'+str(pmid)+' ('+str(len(pmc_ids))+')'
#href_base = 'https://www.ncbi.nlm.nih.gov/pubmed/'+str(pmid)
#href_label = str('<a href="'+href_base+'">'+str(pmid_label)+'</a>')
pmid_Dict = {'sets': x, 'label': pmid_label, 'size': (len(pmc_ids))}
#print(pmid_Dict)
venn_data.append(pmid_Dict)
i_count.append(str(i))
i+=1
#if there is more than one pmid,
if (len(pmid_list)) > 1:
#print("more than 1")
#make dictionary of {citating: ['papers', 'that', 'are', 'cited'] }
for citation in all_pmcids:
j = 0
papers = []
for pmclist in pmc_id_list:
if citation in pmclist:
#print(str(citation) + " is in P"+str(j))
if j not in papers:
papers.append(j)
j +=1
#print(papers)
citationsDict[citation] = papers
### enumerate all possible dictionary values ####
s = ''
combos = s.join(i_count) #format combos for 'combinations' method
#print(combos)
for n in range(2, len(pmid_list)+1):
compare_all = (combinations(combos, int(n)))
for c in compare_all:
option_list = [] #dict keys are in list format [1, 2]
#print("c")
#print(c)
for number in c:
#print("number")
#print(number)
option_list.append(int(number))
possible_vals.append(option_list)
#print("inside possible_vals")
#print(possible_vals)
#print(citationsDict)
#print("OUTSIDE possible vales")
#print(possible_vals)
#if there were multiple pmids, must look at overlap
if citationsDict:
for p_vals in possible_vals:
#print(p_vals)
sum = 0
for key, value in citationsDict.items():
if value == p_vals:
#print(str(key)+' has '+str(value)+' == '+str(p_vals))
sum += 1
#print(sum)
if sum > 0:
count_label = str(sum)
overlap_Dict = {'sets': p_vals, 'label': count_label, 'size': sum }
#print(overlap_Dict)
venn_data.append(overlap_Dict)
#if there was only 1 input pmid, no other work needed
if not citationsDict:
#print("there's no citationDict")
pass
return venn_data
#venn_data = make_venn(pmid_list)
#print(venn_data)
|
[
"hclent1@gmail.com"
] |
hclent1@gmail.com
|
91d36c7e5037514ae3939fb1980f2e0cd06f21b7
|
90656f5ce4efdf07ea0a61ad425673887e517371
|
/ch8/message.py
|
fec37600c7f48a2cda8521e610a80c72b491bfe9
|
[] |
no_license
|
fjluartes/pcc
|
bec2e15e8b70aaee11f562cdf78c39e3a9844269
|
cda4510937f5772d3a0a0b51609ab9554206aa06
|
refs/heads/master
| 2021-06-04T14:37:03.953253
| 2020-05-03T13:09:10
| 2020-05-03T13:09:10
| 144,001,097
| 1
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 184
|
py
|
#!/usr/bin/env python
# message.py: Exercise 8-1
# 22 Aug 2018 | fjgl
def display_message():
"""Display a message"""
print("I'm learning about functions.")
display_message()
|
[
"fjluartes@gmail.com"
] |
fjluartes@gmail.com
|
22dd5027964a66ca1a9bb0aa89892e6a475aa7d9
|
f67fe1dfb0c02cab1e61db17bbec9948ac907a6c
|
/torch_utils.py
|
7cf684213d67772c20a361b184633efaac7e8d5f
|
[
"Apache-2.0"
] |
permissive
|
terrifyzhao/torch_utils
|
c404435896ae9aed23c50d55d13339343114f909
|
5a62cc1e97435db02c0441f9f95d69d6f5db9e15
|
refs/heads/master
| 2022-11-27T10:15:36.738686
| 2020-08-06T01:43:39
| 2020-08-06T01:43:39
| 285,166,603
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 7,759
|
py
|
import torch
import time
import numpy as np
import six
class TrainHandler:
def __init__(self,
train_loader,
valid_loader,
model,
criterion,
optimizer,
model_path,
batch_size=32,
epochs=5,
scheduler=None,
gpu_num=0):
self.train_loader = train_loader
self.valid_loader = valid_loader
self.criterion = criterion
self.optimizer = optimizer
self.model_path = model_path
self.batch_size = batch_size
self.epochs = epochs
self.scheduler = scheduler
if torch.cuda.is_available():
self.device = torch.device(f'cuda:{gpu_num}')
print('Training device is gpu:{gpu_num}')
else:
self.device = torch.device('cpu')
print('Training device is cpu')
self.model = model.to(self.device)
def _train_func(self):
train_loss = 0
train_correct = 0
for i, (x, y) in enumerate(self.train_loader):
self.optimizer.zero_grad()
x, y = x.to(self.device), y.to(self.device)
output = self.model(x)
loss = self.criterion(output, y)
train_loss += loss.item()
loss.backward()
self.optimizer.step()
train_correct += (output.argmax(1) == y).sum().item()
if self.scheduler is not None:
self.scheduler.step()
return train_loss / len(self.train_loader), train_correct / len(self.train_loader.dataset)
def _test_func(self):
valid_loss = 0
valid_correct = 0
for x, y in self.valid_loader:
x, y = x.to(self.device), y.to(self.device)
with torch.no_grad():
output = self.model(x)
loss = self.criterion(output, y)
valid_loss += loss.item()
valid_correct += (output.argmax(1) == y).sum().item()
return valid_loss / len(self.valid_loader), valid_correct / len(self.valid_loader.dateset)
def train(self):
min_valid_loss = float('inf')
for epoch in range(self.epochs):
start_time = time.time()
train_loss, train_acc = self._train_func()
valid_loss, valid_acc = self._test_func()
if min_valid_loss > valid_loss:
min_valid_loss = valid_loss
torch.save(self.model.state_dict(), self.model_path)
print(f'\tSave model done valid loss: {valid_loss:.4f}')
secs = int(time.time() - start_time)
mins = secs / 60
secs = secs % 60
print('Epoch: %d' % (epoch + 1), " | time in %d minutes, %d seconds" % (mins, secs))
print(f'\tLoss: {train_loss:.4f}(train)\t|\tAcc: {train_acc * 100:.1f}%(train)')
print(f'\tLoss: {valid_loss:.4f}(valid)\t|\tAcc: {valid_acc * 100:.1f}%(valid)')
def torch_text_process():
from torchtext import data
def tokenizer(text):
import jieba
return list(jieba.cut(text))
TEXT = data.Field(sequential=True, tokenize=tokenizer, lower=True, fix_length=20)
LABEL = data.Field(sequential=False, use_vocab=False)
all_dataset = data.TabularDataset.splits(path='',
train='LCQMC.csv',
format='csv',
fields=[('sentence1', TEXT), ('sentence2', TEXT), ('label', LABEL)])[0]
TEXT.build_vocab(all_dataset)
train, valid = all_dataset.split(0.1)
(train_iter, valid_iter) = data.BucketIterator.splits(datasets=(train, valid),
batch_sizes=(64, 128),
sort_key=lambda x: len(x.sentence1))
return train_iter, valid_iter
def pad_sequences(sequences, maxlen=None, dtype='int32',
padding='post', truncating='pre', value=0.):
"""Pads sequences to the same length.
This function transforms a list of
`num_samples` sequences (lists of integers)
into a 2D Numpy array of shape `(num_samples, num_timesteps)`.
`num_timesteps` is either the `maxlen` argument if provided,
or the length of the longest sequence otherwise.
Sequences that are shorter than `num_timesteps`
are padded with `value` at the end.
Sequences longer than `num_timesteps` are truncated
so that they fit the desired length.
The position where padding or truncation happens is determined by
the arguments `padding` and `truncating`, respectively.
Pre-padding is the default.
# Arguments
sequences: List of lists, where each element is a sequence.
maxlen: Int, maximum length of all sequences.
dtype: Type of the output sequences.
To pad sequences with variable length strings, you can use `object`.
padding: String, 'pre' or 'post':
pad either before or after each sequence.
truncating: String, 'pre' or 'post':
remove values from sequences larger than
`maxlen`, either at the beginning or at the end of the sequences.
value: Float or String, padding value.
# Returns
x: Numpy array with shape `(len(sequences), maxlen)`
# Raises
ValueError: In case of invalid values for `truncating` or `padding`,
or in case of invalid shape for a `sequences` entry.
"""
if not hasattr(sequences, '__len__'):
raise ValueError('`sequences` must be iterable.')
num_samples = len(sequences)
lengths = []
for x in sequences:
try:
lengths.append(len(x))
except TypeError:
raise ValueError('`sequences` must be a list of iterables. '
'Found non-iterable: ' + str(x))
if maxlen is None:
maxlen = np.max(lengths)
# take the sample shape from the first non empty sequence
# checking for consistency in the main loop below.
sample_shape = tuple()
for s in sequences:
if len(s) > 0:
sample_shape = np.asarray(s).shape[1:]
break
is_dtype_str = np.issubdtype(dtype, np.str_) or np.issubdtype(dtype, np.unicode_)
if isinstance(value, six.string_types) and dtype != object and not is_dtype_str:
raise ValueError("`dtype` {} is not compatible with `value`'s type: {}\n"
"You should set `dtype=object` for variable length strings."
.format(dtype, type(value)))
x = np.full((num_samples, maxlen) + sample_shape, value, dtype=dtype)
for idx, s in enumerate(sequences):
if not len(s):
continue # empty list/array was found
if truncating == 'pre':
trunc = s[-maxlen:]
elif truncating == 'post':
trunc = s[:maxlen]
else:
raise ValueError('Truncating type "%s" '
'not understood' % truncating)
# check `trunc` has expected shape
trunc = np.asarray(trunc, dtype=dtype)
if trunc.shape[1:] != sample_shape:
raise ValueError('Shape of sample %s of sequence at position %s '
'is different from expected shape %s' %
(trunc.shape[1:], idx, sample_shape))
if padding == 'post':
x[idx, :len(trunc)] = trunc
elif padding == 'pre':
x[idx, -len(trunc):] = trunc
else:
raise ValueError('Padding type "%s" not understood' % padding)
return x
if __name__ == '__main__':
torch_text_process()
|
[
"zjiuzhou@gmail.com"
] |
zjiuzhou@gmail.com
|
67c1f43f556c5731c6222cc2ab1ca7d5cf18afd8
|
685e4b07ee6458a9eb5be4cc213c940050c7af0b
|
/Kg Convert.py
|
8d50a92cf1ff4e88af1bb874b6836aa8543bfe84
|
[] |
no_license
|
FatematuzZohura/Python
|
574343ef46651ac6478e50966d7c04eb0811935f
|
36e1abe6cb701ac38a3504d02cf8564ba0916426
|
refs/heads/main
| 2023-08-17T05:41:00.459969
| 2021-10-05T04:35:58
| 2021-10-05T04:35:58
| 410,034,302
| 0
| 0
| null | null | null | null |
UTF-8
|
Python
| false
| false
| 1,493
|
py
|
from tkinter import *
# Create a GUI window
window = Tk()
window.title("Converter app")
# Function to convert weight
# given in kg to grams, pounds
# and ounces
def from_kg():
# convert kg to gram
gram = float(e2_value.get()) * 1000
# convert kg to pound
pound = float(e2_value.get()) * 2.20462
# convert kg to ounce
ounce = float(e2_value.get()) * 35.274
# Enters the converted weight to
# the text widget
t1.delete("1.0", END)
t1.insert(END, gram)
t2.delete("1.0", END)
t2.insert(END, pound)
t3.delete("1.0", END)
t3.insert(END, ounce)
# Create the Label widgets
e1 = Label(window, text="Enter the weight in Kg")
e2_value = StringVar()
e2 = Entry(window, textvariable=e2_value)
e3 = Label(window, text='Gram')
e4 = Label(window, text='Pounds')
e5 = Label(window, text='Ounce')
# Create the Text Widgets
t1 = Text(window, height=1, width=20)
t2 = Text(window, height=1, width=20)
t3 = Text(window, height=1, width=20)
# Create the Button Widget
b1 = Button(window, text="Convert", command=from_kg)
# grid method is used for placing
# the widgets at respective positions
# in table like structure
e1.grid(row=0, column=0)
e2.grid(row=0, column=1)
e3.grid(row=1, column=0)
e4.grid(row=1, column=1)
e5.grid(row=1, column=2)
t1.grid(row=2, column=0)
t2.grid(row=2, column=1)
t3.grid(row=2, column=2)
b1.grid(row=0, column=2)
# Start the GUI
window.mainloop()
|
[
"noreply@github.com"
] |
FatematuzZohura.noreply@github.com
|
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