code stringlengths 10 2.58M | original_code stringlengths 3 3.18M | original_language stringclasses 1
value | source stringclasses 7
values |
|---|---|---|---|
function receive_video self
begin
while true
begin
set tuple data addr = call recvfrom MAX_DATAGRAM_SIZE
if call should_video_flow and addr at 0 == call get_send_address at 0
begin
set udp_datagram = call udp_datagram_from_msg data
insert udp_buffer udp_datagram
end
end
end function | def receive_video(self):
while True:
data, addr = self.receive_socket.recvfrom(MAX_DATAGRAM_SIZE)
if self.call_control.should_video_flow() and addr[0] == self.call_control.get_send_address()[0]:
udp_datagram = udp_datagram_from_msg(data)
self.udp_buffer.in... | Python | nomic_cornstack_python_v1 |
comment you can write to stdout for debugging purposes, e.g.
comment print("this is a debug message")
function solution A
begin
comment write your code in Python 3.6
comment key point: sort the array
set sorted_array = sorted A
for index in range length A - 2
begin
if sorted_array at index + sorted_array at index + 1 >... | # you can write to stdout for debugging purposes, e.g.
# print("this is a debug message")
def solution(A):
# write your code in Python 3.6
# key point: sort the array
sorted_array = sorted(A)
for index in range( len(A)-2 ):
if sorted_array[index] + sorted_array[index+1] > sorted_arra... | Python | zaydzuhri_stack_edu_python |
import TCP
import threading
import read_files
import sys
import os
import math
import analysis
set _BUFFER_SIZE = 400
class serverThread extends Thread
begin
function __init__ self serverSocket
begin
call __init__ self
set serverSocket = serverSocket
end function
function run self
begin
set file_name = call receive
try... | import TCP
import threading
import read_files
import sys
import os
import math
import analysis
_BUFFER_SIZE = 400
class serverThread(threading.Thread):
def __init__(self, serverSocket):
threading.Thread.__init__(self)
self.serverSocket = serverSocket
def run(self):
file_name = self.se... | Python | zaydzuhri_stack_edu_python |
while t <= T
begin
set seen_digits = set
set N = integer call raw_input
if N == 0
begin
print string Case #%d: INSOMNIA % t
set t = t + 1
continue
end
set cur = N
while length seen_digits < 10
begin
for d in string cur
begin
add seen_digits d
end
set cur = cur + N
end
set cur = cur - N
print string Case #%d: %d % tuple... | while t <= T:
seen_digits = set()
N = int(raw_input())
if N == 0:
print("Case #%d: INSOMNIA" % t)
t += 1
continue
cur = N
while(len(seen_digits) < 10):
for d in str(cur):
seen_digits.add(d)
cur += N
cur -= N
print("Case #%d: %d" % (t, cur))
t += 1
| Python | zaydzuhri_stack_edu_python |
comment !/usr/bin/env python
import numpy as np
from nupic.algorithms.temporal_memory import TemporalMemory
from group_by import groupby2
from nupic.bindings.math import SparseMatrixConnections
class TM extends TemporalMemory
begin
function __init__ self **kwargs
begin
call __init__ keyword kwargs
end function
end clas... | #!/usr/bin/env python
import numpy as np
from nupic.algorithms.temporal_memory import TemporalMemory
from group_by import groupby2
from nupic.bindings.math import SparseMatrixConnections
class TM(TemporalMemory):
def __init__(self, **kwargs):
super(TM, self).__init__(**kwargs)
| Python | zaydzuhri_stack_edu_python |
function tearDown self
begin
call Empty
end function | def tearDown(self):
self._resolver_context.Empty() | Python | nomic_cornstack_python_v1 |
import tensorflow as tf
import numpy as np
import sqlite3
import random
import os
import glob
import sys
from multiprocessing import Pool
from functools import partial
from sklearn.metrics import mean_squared_error
from nnmodels import compare
set EMBEDDINGS = 100
set VECTORS = string allMeSH_2016_%i.vectors.txt % EMBE... | import tensorflow as tf
import numpy as np
import sqlite3
import random
import os
import glob
import sys
from multiprocessing import Pool
from functools import partial
from sklearn.metrics import mean_squared_error
from nnmodels import compare
EMBEDDINGS = 100
VECTORS = 'allMeSH_2016_%i.vectors.txt' % EMBEDDINGS
DB ... | Python | zaydzuhri_stack_edu_python |
function generate self metrics=none
begin
set metric_group = metrics at call find_exercise
if autogen
begin
set children = list
if sets and weight_expr
begin
set children = list set reps=reps weight=weight_expr * sets
end
else
if bottom and top and increment
begin
set w = decimal call WeightExpr bottom metric_group=me... | def generate(self, metrics=None):
self.metric_group = metrics[self.find_exercise()]
if self.autogen:
self.children = []
if self.sets and self.weight_expr:
self.children = [Set(reps=self.reps, weight=self.weight_expr)] * self.sets
elif self.bottom and s... | Python | nomic_cornstack_python_v1 |
string Recognize handwritten digits using OpenCV library
import cv2
import numpy as np
comment Load the model
set model = call SVM_load string svm_model.xml
comment Read the input image
set img = call imread string input.png
comment Convert to grayscale and apply Gaussian filtering
set img_gray = call cvtColor img COLO... | """
Recognize handwritten digits using OpenCV library
"""
import cv2
import numpy as np
# Load the model
model = cv2.ml.SVM_load('svm_model.xml')
# Read the input image
img = cv2.imread('input.png')
# Convert to grayscale and apply Gaussian filtering
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
img_gray = cv2.Ga... | Python | jtatman_500k |
import matplotlib.pyplot as plt
import scipy.cluster.vq as vq
import numpy as np
set _COLORS = load np join path directory name path __file__ string pca_toy_colors.npy
function plot_label_3d x y
begin
string Show a 3D scatter plot of data. Parameters ---------- x: (n, 3) array-like y: (n,) array-like The labels
set y =... | import matplotlib.pyplot as plt
import scipy.cluster.vq as vq
import numpy as np
_COLORS = np.load(path.join(path.dirname(__file__), 'pca_toy_colors.npy'))
def plot_label_3d(x, y):
"""
Show a 3D scatter plot of data.
Parameters
----------
x: (n, 3) array-like
y: (n,) array-like
The ... | Python | zaydzuhri_stack_edu_python |
function _build_trex_packet self packet_definition adjust_size=true required_size=64
begin
import trex_stl_lib.api as TApi
function _value_repr value
begin
string Check if value contains layers.
if is instance value tuple list tuple
begin
return call type value list map _value_repr value
end
else
if is instance value d... | def _build_trex_packet(self, packet_definition, adjust_size=True, required_size=64):
import trex_stl_lib.api as TApi
def _value_repr(value):
"""Check if value contains layers.
"""
if isinstance(value, (list, tuple)):
return type(value)(list(map(_valu... | Python | nomic_cornstack_python_v1 |
function _get_submodule_has_out_user_under_public_parent self public_module node_out_user
begin
for module_struct in module_structs
begin
if onnx_name in onnx_names
begin
return module_struct
end
end
return none
end function | def _get_submodule_has_out_user_under_public_parent(self, public_module: ModuleStruct, node_out_user: NodeStruct):
for module_struct in public_module.module_structs:
if node_out_user.onnx_name in module_struct.onnx_names:
return module_struct
return None | Python | nomic_cornstack_python_v1 |
function test_migrate_all_carni_in_cell_new_location standard_map_peninsula
begin
set parameters at string mu = 1000
set mock_ek = dict tuple 1 18 2
call _migrate_all_carnivores_in_cell standard_map_peninsula tuple 1 19 mock_ek
set parameters at string mu = 0.24
assert carnivore_list == list
assert carnivore_list != l... | def test_migrate_all_carni_in_cell_new_location(
standard_map_peninsula):
animals.Carnivores.parameters["mu"] = 1000
mock_ek = {(1, 18): 2}
standard_map_peninsula.raster_model[(
1, 19)]._migrate_all_carnivores_in_cell(
standard_map_peninsula, (1, 19), mock_ek)
animals.Carnivores.... | Python | nomic_cornstack_python_v1 |
comment from flask_testing import TestCase
import unittest
from app import create_app , db
class BaseTestCase extends TestCase
begin
string Parent of all test units
function setUp self
begin
string Define test variables and init app
set app = call create_app config_name=string testing
set client = test_client
comment b... | # from flask_testing import TestCase
import unittest
from app import create_app, db
class BaseTestCase(unittest.TestCase):
""" Parent of all test units """
def setUp(self):
""" Define test variables and init app """
self.app = create_app(config_name="testing")
self.client = self.app.t... | Python | zaydzuhri_stack_edu_python |
import pandas as pd
import io
import string
import itertools as it
import pickle as pk
from talib.abstract import MA , EMA , WMA , RSI , CCI , ROC , MOM , WILLR
from pyCBT.providers.gdrive.account import get_client
from pyCBT.common.path import exist
class DriveTables extends object
begin
comment parent ID of data tabl... | import pandas as pd
import io
import string
import itertools as it
import pickle as pk
from talib.abstract import MA, EMA, WMA, RSI, CCI, ROC, MOM, WILLR
from pyCBT.providers.gdrive.account import get_client
from pyCBT.common.path import exist
class DriveTables(object):
# parent ID of data tables in Google Driv... | Python | zaydzuhri_stack_edu_python |
function count_bits x
begin
set c = 0
while x
begin
set x = x / 2
set c = c + 1
end
return c
end function
function get_bit x i
begin
set mask = 1 ? i
return integer not not x ? mask
end function
class Solution extends object
begin
function rangeBitwiseAnd self m n
begin
string :type m: int :type n: int :rtype: int
set ... | def count_bits(x):
c = 0
while x:
x /= 2
c += 1
return c
def get_bit(x, i):
mask = (1 << i)
return int(not(not(x & mask)))
class Solution(object):
def rangeBitwiseAnd(self, m, n):
"""
:type m: int
:type n: int
:rtype: int
"""
flag... | Python | zaydzuhri_stack_edu_python |
function run self
begin
for pipe in inputs
begin
for row in call rows
begin
put row
end
end
end function | def run(self):
for pipe in self.inputs:
for row in pipe.rows():
self.put(row) | Python | nomic_cornstack_python_v1 |
comment Import required libraries
import pandas as pd
import numpy as np
from datetime import datetime
from geneticalgorithm import geneticalgorithm as ga
from scipy.optimize import differential_evolution
import matplotlib.pyplot as plt
import math
import os
import tkinter as tk
from tkinter import messagebox
from tkin... | #Import required libraries
import pandas as pd
import numpy as np
from datetime import datetime
from geneticalgorithm import geneticalgorithm as ga
from scipy.optimize import differential_evolution
import matplotlib.pyplot as plt
import math
import os
import tkinter as tk
from tkinter import messagebox
fro... | Python | zaydzuhri_stack_edu_python |
import itertools as it
import more_itertools as mi
import numpy as np
import fileinput , sys
from collections import defaultdict
comment lol
call setrecursionlimit 10 ^ 6
function solve line
begin
set buf = list
for c in line
begin
if buf and buf at - 1 == call swapcase
begin
pop buf
end
else
begin
append buf c
end
en... | import itertools as it
import more_itertools as mi
import numpy as np
import fileinput, sys
from collections import defaultdict
sys.setrecursionlimit(10**6) #lol
def solve(line: str):
buf = []
for c in line:
if buf and buf[-1] == c.swapcase():
buf.pop()
else:
buf.append(c)
return len(buf)
de... | Python | zaydzuhri_stack_edu_python |
function filter_excluded self nodes
begin
debug string Excluded nodes:
debug excluded
set filtered_nodes = list
for node in nodes
begin
comment TODO: Add a filter here. None now as I do not know what filters are needed, if any.
append filtered_nodes node
end
return filtered_nodes
end function | def filter_excluded(self, nodes):
self.logger.debug('Excluded nodes:')
self.logger.debug(self.excluded)
filtered_nodes = []
for node in nodes:
# TODO: Add a filter here. None now as I do not know what filters are needed, if any.
filtered_nodes.append(node)
... | Python | nomic_cornstack_python_v1 |
comment -*- coding: utf-8 -*-
import time
from html.parser import HTMLParser
import numpy as np
import urllib
from urllib import request
from openpyxl import Workbook
set hds = list set literal string Mozilla/5.0 (Windows; U; Windows NT 6.1; en-US; rv:1.9.1.6) Gecko/20091201 Firefox/3.5.6 set literal string Mozilla/5.0... | # -*- coding: utf-8 -*-
import time
from html.parser import HTMLParser
import numpy as np
import urllib
from urllib import request
from openpyxl import Workbook
hds=[{'Mozilla/5.0 (Windows; U; Windows NT 6.1; en-US; rv:1.9.1.6) Gecko/20091201 Firefox/3.5.6'},{'Mozilla/5.0 (Windows NT 6.2) AppleWebKit/535.11 (KHTML, lik... | Python | zaydzuhri_stack_edu_python |
function swap_columns df column1 column2 inplace=true
begin
set columns_name = list df
comment Change the parameters to index if they are column name
if is instance column1 str
begin
set column1 = index columns_name column1
end
if is instance column2 str
begin
set column2 = index columns_name column2
end
comment Swap t... | def swap_columns(df, column1, column2, inplace=True):
columns_name = list(df)
# Change the parameters to index if they are column name
if isinstance(column1, str):
column1 = columns_name.index(column1)
if isinstance(column2, str):
column2 = columns_name.index(column2)
# Swap the co... | Python | nomic_cornstack_python_v1 |
function delete_user user_name
begin
set iam_user = call delete_user user_name
return
end function | def delete_user(user_name):
iam_user = iam_manager.delete_user(user_name)
return | Python | nomic_cornstack_python_v1 |
function read_chain_annotated_interactome inPath
begin
set interactome = call read_table inPath sep=string
set interactome at string Mapping_chains = apply interactome at string Mapping_chains str_to_tuples
return interactome
end function | def read_chain_annotated_interactome (inPath):
interactome = pd.read_table(inPath, sep='\t')
interactome["Mapping_chains"] = interactome["Mapping_chains"].apply( str_to_tuples )
return interactome | Python | nomic_cornstack_python_v1 |
comment Don't erase the template code, except "Your code here" comments.
import torch
comment Pi
import math
string Task 1
function get_rho
begin
comment (1) Your code here; theta = ...
set theta = linear space - pi pi 1000 dtype=float64
assert shape == tuple 1000
comment (2) Your code here; rho = ...
set rho = 1 + 0.9... | # Don't erase the template code, except "Your code here" comments.
import torch
import math # Pi
""" Task 1 """
def get_rho():
# (1) Your code here; theta = ...
theta = torch.linspace(-math.pi, math.pi, 1000, dtype=torch.float64)
assert theta.shape == (1000,)
# (2) Your code her... | Python | zaydzuhri_stack_edu_python |
comment !/usr/bin/python
comment coding=utf-8
comment 文件输入流 | #!/usr/bin/python
#coding=utf-8
#文件输入流 | Python | zaydzuhri_stack_edu_python |
import random
class Solution extends object
begin
function __init__ self nums
begin
string :type nums: List[int]
set nums = nums
set numsBak = nums at slice : :
end function
comment print 111, self.nums, self.numsBak
function reset self
begin
string :rtype: List[int]
comment print 222, self.nums, self.numsBak
return... | import random
class Solution(object):
def __init__(self, nums):
"""
:type nums: List[int]
"""
self.nums = nums
self.numsBak = nums[:]
##print 111, self.nums, self.numsBak
def reset(self):
"""
:rtype: List[int]
"""
##print ... | Python | zaydzuhri_stack_edu_python |
function formatPickupType string
begin
if string == string N/A
begin
return 0
end
else
if string == string D
begin
return 1
end
else
if string == string M
begin
return 2
end
else
if string == string C
begin
return 3
end
else
if string == string R
begin
return 4
end
else
begin
return 5
end
end function | def formatPickupType(string):
if string == 'N/A':
return 0
elif string == 'D':
return 1
elif string == 'M':
return 2
elif string == 'C':
return 3
elif string == 'R':
return 4
else:
return 5 | Python | nomic_cornstack_python_v1 |
function lda X y
begin
string Calculates the projection matrix U to perform LDA on X with labels y. LDA finds the projecting matrix W that allows us to linearly project X to another (sub) space in which the between-class and within-class variances are jointly optimized: the between-class variance is maximized while the... | def lda(X, y):
"""Calculates the projection matrix U to perform LDA on X with labels y.
LDA finds the projecting matrix W that allows us to linearly project X to
another (sub) space in which the between-class and within-class variances are
jointly optimized: the between-class variance is maximized while the
... | Python | zaydzuhri_stack_edu_python |
function visualize_images images figure_size=tuple 7 7 browser_style=string buttons custom_info_callback=none
begin
comment Make sure that images is a list even with one member
if not is instance images Sized
begin
set images = list images
end
comment Get the number of images
set n_images = length images
comment Define... | def visualize_images(
images, figure_size=(7, 7), browser_style="buttons", custom_info_callback=None
):
# Make sure that images is a list even with one member
if not isinstance(images, Sized):
images = [images]
# Get the number of images
n_images = len(images)
# Define the styling opti... | Python | nomic_cornstack_python_v1 |
function StringToDoubleAddress pString
begin
set parts = split pString string .
if length parts is not 4
begin
raise call LabJackException 0 string IP address not correctly formatted
end
try
begin
set value = integer parts at 0 ? 8 * 3 + integer parts at 1 ? 8 * 2 + integer parts at 2 ? 8 + integer parts at 3
end
excep... | def StringToDoubleAddress(pString):
parts = pString.split('.')
if len(parts) is not 4:
raise LabJackException(0, "IP address not correctly formatted")
try:
value = (int(parts[0]) << 8*3) + (int(parts[1]) << 8*2) + (int(parts[2]) << 8) + int(parts[3])
except ValueError... | Python | nomic_cornstack_python_v1 |
function print_objects objects
begin
set longest_name = max list comprehension length name for obj in objects
for obj in objects
begin
print string %s: handle=%s, size=%0.1f, rot_x_p=%d, rot_x_m_sym=%d, rot_y_p=%d, rot_y_m_sym=%d, rot_z_p=%d, rot_z_m_sym=%d, Handles: nondiag=%s, diag=%s % tuple call ljust longest_name ... | def print_objects(objects):
longest_name = max([len(obj.name) for obj in objects])
for obj in objects:
print("%s: handle=%s, size=%0.1f, "
"rot_x_p=%d, rot_x_m_sym=%d, "
"rot_y_p=%d, rot_y_m_sym=%d, "
"rot_z_p=%d, rot_z_m_sym=%d, "
"Handles: nondi... | Python | nomic_cornstack_python_v1 |
function show_schema_updates self
begin
for mode in list string source string target
begin
set deltas = database at string deltas at string new_columns_in_ + mode
set working_db = if expression mode == string source then source at string alias else target at string alias
set other_db = if expression mode == string sour... | def show_schema_updates(self):
for mode in ['source', 'target']:
deltas = self.database['deltas']['new_columns_in_' + mode]
working_db = self.source['alias'] if mode == 'source' else self.target['alias']
other_db = self.target['alias'] if mode == 'source' else self.source['al... | Python | nomic_cornstack_python_v1 |
function handle_order
begin
set order = lower input string >
if order != string quit
begin
if order in available_menu
begin
append order_list order
if order in order_list
begin
set count = 0
for i in order_list
begin
if i == order
begin
set count = count + 1
end
end
print string ** { count } order of { order } have bee... | def handle_order():
order=input("> ").lower()
if order != "quit":
if order in available_menu:
order_list.append(order)
if order in order_list:
count=0
for i in order_list:
if i==order:
count+=1
print(f"** {count} order of {order} have been added to your meal **")
handle_order()
... | Python | nomic_cornstack_python_v1 |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
set data = values
set tuple N d = shape
set X = reshape data at tuple slice : : slice 0 : d - 1 : - 1 d - 1
set y = reshape data at tuple slice : : 2 - 1 1
function sigmoid x
begin
return 1 / 1 + exp - x
end function
scatter plt X at tuple sl... | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
data = pd.read_csv('dataset.csv').values
N, d = data.shape
X = data[:, 0:d-1].reshape(-1, d-1)
y = data[:, 2].reshape(-1, 1)
def sigmoid(x):
return 1 / (1 + np.exp(-x))
plt.scatter(X[:10,0], X[:10,1], color = 'red', label = 'Cho vay')
plt.sca... | Python | zaydzuhri_stack_edu_python |
function team_stats self
begin
return call _aggregate_event_stats string team_id string stat_key
end function | def team_stats(self):
return self._aggregate_event_stats("team_id", "stat_key") | Python | nomic_cornstack_python_v1 |
comment https://www.codewars.com/kata/54edbc7200b811e956000556
function count_sheeps arrayOfSheeps
begin
return count arrayOfSheeps true
end function | # https://www.codewars.com/kata/54edbc7200b811e956000556
def count_sheeps(arrayOfSheeps):
return arrayOfSheeps.count(True) | Python | zaydzuhri_stack_edu_python |
function collect scan_folder copy_folder
begin
set files = call get_files call Path scan_folder
set copy_folder = call Path copy_folder
set copy_id = 0
if not call is_dir
begin
make directory copy_folder
end
print string { length files } have been found and will be copied.
for wavfile in files
begin
set copy_id = copy_... | def collect(scan_folder, copy_folder):
files = get_files(Path(scan_folder))
copy_folder = Path(copy_folder)
copy_id = 0
if not copy_folder.is_dir():
copy_folder.mkdir()
print(f'{len(files)} have been found and will be copied.')
for wavfile in files:
copy_id += 1
... | Python | nomic_cornstack_python_v1 |
comment Claculates correlation between two graphs. Collects graphs by using collect_graphs()
comment from graphs.py
comment CHANGELOG ########################
comment v0.1 (alpha): ##
comment + Begun alpha development ##
comment + Imported 'collect_graphs' from graphs.py to do ##
comment just that ##
comment + Added a ... | # Claculates correlation between two graphs. Collects graphs by using collect_graphs()
# from graphs.py
######################## CHANGELOG ########################
###########################################################
## v0.1 (alpha): ##
## + Begun alpha development ... | Python | zaydzuhri_stack_edu_python |
function cluster_indices x
begin
set x = absolute x > 1e-20
set indices = list where diff np x at 0 + 1
if x at 0
begin
set indices = list 0 + indices
end
if x at - 1
begin
set indices = indices + list length x
end
set indices = array indices
set bounds = call empty tuple shape at 0 // 2 2 dtype=int32
for tuple i tuple... | def cluster_indices(x):
x = np.abs(x) > 1e-20
indices = list(np.where(np.diff(x))[0] + 1)
if x[0]:
indices = [0] + indices
if x[-1]:
indices = indices + [len(x)]
indices = np.array(indices)
bounds = np.empty((indices.shape[0] // 2, 2), dtype=np.int32)
for (i, (a, b)) in enu... | Python | nomic_cornstack_python_v1 |
comment See figure 3.2 in [Algorithmic Beauty of Plants](http://algorithmicbotany.org/papers/abop/abop.pdf)
comment on page [69](http://algorithmicbotany.org/papers/abop/abop.pdf#page=81).
import lsystem.exec
set ex = exec
call set_axiom string a(1)
call add_rule string a(t) string F(1)[&(30)L(0)]/(137.5)a(add(t,1)) st... | # See figure 3.2 in [Algorithmic Beauty of Plants](http://algorithmicbotany.org/papers/abop/abop.pdf)
# on page [69](http://algorithmicbotany.org/papers/abop/abop.pdf#page=81).
import lsystem.exec
ex = lsystem.exec.Exec()
ex.set_axiom("a(1)")
ex.add_rule("a(t)", "F(1)[&(30)L(0)]/(137.5)a(add(t,1))", "lt(t,7)")
ex.add... | Python | zaydzuhri_stack_edu_python |
function restore_config self
begin
call _clear_previous_windows_assigment
call _restart_i3_config
end function | def restore_config(self):
self._clear_previous_windows_assigment()
self._restart_i3_config() | Python | nomic_cornstack_python_v1 |
function shortestpath graph current end visited=list distances=dict predecessors=dict
begin
comment we've found our end node, now find the path to it, and return
if current == end
begin
set pathShortest = list
while end != none
begin
append pathShortest end
set end = get predecessors end none
end
pass
return tuple d... | def shortestpath(graph, current, end, visited=[], distances={}, predecessors={}):
# we've found our end node, now find the path to it, and return
if current == end:
pathShortest = []
while end != None:
pathShortest.append(end)
end = predecessors.get(end, None)
pass
return distances[current], pathShortes... | Python | nomic_cornstack_python_v1 |
function annotate_function_of_rare_variants inputs outputs
begin
comment use only the filtered input file, leave dropped
set filtered = inputs at 0
call get_stats_on_prefiltered_variants input=filtered outputs=outputs at slice 2 : 4 : cleanup=false
end function | def annotate_function_of_rare_variants(inputs, outputs):
filtered = inputs[0] # use only the filtered input file, leave dropped
get_stats_on_prefiltered_variants(input=filtered, outputs=outputs[2:4], cleanup=False) | Python | nomic_cornstack_python_v1 |
function get_non_blocking_io self path mode=string r buffering=- 1 encoding=none errors=none newline=none closefd=true opener=none
begin
if path not in _path_to_data
begin
set queue = queue
set t = thread target=_poll_jobs args=tuple queue
start t
set _path_to_data at path = call PathData queue t
end
set binary = strin... | def get_non_blocking_io(
self,
path: str,
mode: str = "r",
buffering: int = -1,
encoding: Optional[str] = None,
errors: Optional[str] = None,
newline: Optional[str] = None,
closefd: bool = True,
opener: Optional[Callable] = None,
) -> Union[IO[... | Python | nomic_cornstack_python_v1 |
comment -*- coding: utf-8 -*-
string Created on Wed Jul 11 14:06:37 2018 @author: Administrator
import numpy as np
import matplotlib.pyplot as plt
axis list 0 100 0 1
call ion
for i in range 100
begin
set y = random
scatter plt i y
call pause 0.1
end
show | # -*- coding: utf-8 -*-
"""
Created on Wed Jul 11 14:06:37 2018
@author: Administrator
"""
import numpy as np
import matplotlib.pyplot as plt
plt.axis([0, 100, 0, 1])
plt.ion()
for i in range(100):
y = np.random.random()
plt.scatter(i, y)
plt.pause(0.1)
plt.show() | Python | zaydzuhri_stack_edu_python |
comment Importing the libraries
import numpy as np
import pandas as pd
comment Import the dataset
set dataset = read csv string spam.csv
comment Cleaning the texts
import re
import nltk
call download string stopwords
from nltk.corpus import stopwords
from nltk.stem.porter import PorterStemmer
set corpus = list
for i i... | # Importing the libraries
import numpy as np
import pandas as pd
# Import the dataset
dataset = pd.read_csv ('spam.csv')
# Cleaning the texts
import re
import nltk
nltk.download('stopwords')
from nltk.corpus import stopwords
from nltk.stem.porter import PorterStemmer
corpus = []
for i in range(0, dataset.shape[0]):
... | Python | jtatman_500k |
import webbrowser
comment You can insert your desired link here
set link = string https://github.com/michaelcronk
function run_website
begin
try
begin
open link new=2 autoraise=true
print link
end
except ValueError
begin
print string That's not a valid link. Please try again.
end
end function
call run_website | import webbrowser
link = 'https://github.com/michaelcronk' # You can insert your desired link here
def run_website():
try:
webbrowser.open(link, new=2, autoraise=True)
print(link)
except ValueError:
print("That's not a valid link. Please try again.")
run_website()
| Python | zaydzuhri_stack_edu_python |
with open string ../data/9.txt as f
begin
set data = read line f
end
function is_valid string idx
begin
set exclamations = 0
while idx > 0
begin
set idx = idx - 1
if string at idx == string !
begin
set exclamations = exclamations + 1
end
else
begin
break
end
end
comment If even number of exclamations they cancel out, e... | with open("../data/9.txt") as f:
data = f.readline()
def is_valid(string: str, idx: int):
exclamations = 0
while idx > 0:
idx -= 1
if string[idx] == "!":
exclamations += 1
else:
break
# If even number of exclamations they cancel out, else invalid.
re... | Python | zaydzuhri_stack_edu_python |
function select_area ev x y _1 _2
begin
global x_init y_init drawing top_left bottom_right orig_img img
if ev == EVENT_LBUTTONDOWN
begin
set drawing = true
set x_init = x
set y_init = y
end
else
if ev == EVENT_MOUSEMOVE and drawing
begin
call draw_rect img x_init y_init x y
end
else
if ev == EVENT_LBUTTONUP
begin
set d... | def select_area(ev, x, y, _1, _2):
global x_init, y_init, drawing, top_left, bottom_right, orig_img, img
if ev == cv.EVENT_LBUTTONDOWN:
drawing = True
x_init = x
y_init = y
elif ev == cv.EVENT_MOUSEMOVE and drawing:
draw_rect(img, x_init, y_init, x, y)
elif ev == cv.EVEN... | Python | nomic_cornstack_python_v1 |
function New *args **kargs
begin
set obj = call __New_orig__
import itkTemplate
call New obj *args keyword kargs
return obj
end function | def New(*args, **kargs):
obj = itkMorphologicalWatershedFromMarkersImageFilterIUL3IUL3.__New_orig__()
import itkTemplate
itkTemplate.New(obj, *args, **kargs)
return obj | Python | nomic_cornstack_python_v1 |
string author:dengwei date:2020-05-06 descript:遍历文件夹，读取Excel文件，将信息汇总到一个Excel文件中
import os
import openpyxl
from exceloperator import *
from loggerhelper import *
function get_all_excel_data directory
begin
string 文件夹目录
set workbook = call Workbook
set worksheet = active
set title = string total
set rows = list
comment ... | '''
author:dengwei
date:2020-05-06
descript:遍历文件夹，读取Excel文件，将信息汇总到一个Excel文件中
'''
import os
import openpyxl
from exceloperator import *
from loggerhelper import *
def get_all_excel_data(directory):
'''
文件夹目录
'''
workbook = openpyxl.Workbook()
worksheet = workbook.active
worksheet.title = "tota... | Python | zaydzuhri_stack_edu_python |
comment import numpy as np
class Solution
begin
function subtractProductAndSum self n
begin
comment intを文字列にしてからをリストに変換⇒各桁をリストに追加
set n_list = list map int list string n
set prod = 1
set sum = 0
for i in n_list
begin
set prod = prod * i
set sum = sum + i
end
return prod - sum
end function
end class
comment return np.pr... | # import numpy as np
class Solution:
def subtractProductAndSum(self, n: int) -> int:
# intを文字列にしてからをリストに変換⇒各桁をリストに追加
n_list = list(map(int,list(str(n))))
prod = 1
sum = 0
for i in n_list:
prod *= i
sum += i
return prod-sum
# return np.... | Python | zaydzuhri_stack_edu_python |
import torch.nn as nn
import torch.optim as optim
class Optimizer extends object
begin
function __init__ self params lr lr_decay=1.0 weight_decay=0.0 max_grad_norm=none
begin
set parameters = params
set lr = lr
set lr_decay = lr_decay
set weight_decay = weight_decay
set max_grad_norm = max_grad_norm
set optimizer = non... | import torch.nn as nn
import torch.optim as optim
class Optimizer(object):
def __init__(self,
params,
lr,
lr_decay=1.0,
weight_decay=0.0,
max_grad_norm=None):
self.parameters = params
self.lr = lr
self.lr_... | Python | zaydzuhri_stack_edu_python |
function PP_SPF_AVG Dataframe HNAME_List Raceday
begin
set Feature_DF = loc at tuple slice : : list string HNAME string RARID
set Extraction = call Extraction_Database format string Select HNAME, RARID, BEYER_SPEED PP_SPF_AVG from Race_PosteriorDb where RADAT < {Raceday} and HNAME in {HNAME_List} Raceday=Raceday HNA... | def PP_SPF_AVG(Dataframe, HNAME_List, Raceday):
Feature_DF = Dataframe.loc[:,['HNAME','RARID']]
Extraction = Extraction_Database("""
Select HNAME, RARID, BEYER_SPEED PP_SPF_AVG from Race_PosteriorDb
where RADAT < {Raceday} and HNAME in ... | Python | nomic_cornstack_python_v1 |
import tensorflow as tf
import numpy as np
from torchvision import transforms
import random
import torch
import cv2
from PIL import ImageEnhance
from PIL import Image
class RandomCropTarget extends object
begin
string Crop the image and target randomly in a sample. Args: output_size (tuple or int): Desired output size.... | import tensorflow as tf
import numpy as np
from torchvision import transforms
import random
import torch
import cv2
from PIL import ImageEnhance
from PIL import Image
class RandomCropTarget(object):
"""
Crop the image and target randomly in a sample.
Args:
output_size (tuple or int): Desired output s... | Python | zaydzuhri_stack_edu_python |
function debug self **kwargs
begin
set logger = logger
if string level in kwargs
begin
set level = kwargs at string level
call setLevel level
end
else
begin
call setLevel INFO
end
end function | def debug(self, **kwargs):
logger = self.logger
if 'level' in kwargs:
level = kwargs['level']
logger.setLevel(level)
else:
logger.setLevel(logging.INFO) | Python | nomic_cornstack_python_v1 |
function _init_words_embedding self glove_vectors=string glove.6B.300d
begin
set vocab = call Vocab counter words_dict vectors=glove_vectors specials=SPECIAL_TOKENS
return tuple stoi itos vectors
end function | def _init_words_embedding(
self, glove_vectors: Optional[str] = "glove.6B.300d"
) -> Tuple[defaultdict, List[str], torch.Tensor]:
vocab = Vocab(Counter(self.words_dict), vectors=glove_vectors, specials=SPECIAL_TOKENS)
return vocab.stoi, vocab.itos, vocab.vectors | Python | nomic_cornstack_python_v1 |
function _finishMany self results request
begin
set templateURLs = list
for tuple succeeded result in results
begin
if succeeded
begin
set low = lower result
if starts with low string http:// or starts with low string https://
begin
set result = string <a href="%s">%s</a> % tuple result result
end
append templateURLs ... | def _finishMany(self, results, request):
templateURLs = []
for (succeeded, result) in results:
if succeeded:
low = result.lower()
if low.startswith('http://') or low.startswith('https://'):
result = '<a href="%s">%s</a>' % (result, result)
... | Python | nomic_cornstack_python_v1 |
if km <= 1.5
begin
print string 所需車資為: total
end
else
begin
set a = km - 1.5 * 1000
if a <= 250
begin
set total = total + 5
print string 所需車資為: total
end
else
if a % 250 == 0
begin
set total = total + 5 * a // 250
print string 所需車資為: total
end
else
begin
set total = total + 5 * a // 250 + 5
print string 所需車資為: total
en... | if (km<=1.5):
print("所需車資為:",total)
else:
a=(km-1.5)*1000
if (a<=250):
total=total+5
print("所需車資為:",total)
else:
if ((a%250)==0):
total=total+5*(a//250)
print("所需車資為:",total)
else:
total=total+5*(a//250)+5
print("所需車資為:",t... | Python | zaydzuhri_stack_edu_python |
function write_network_info self layers layer_names
begin
for tuple layer name in zip layers layer_names
begin
call add_histogram name + string Bias bias epoch
call add_histogram name + string Weights weight epoch
end
flush writer
end function | def write_network_info(self, layers: list, layer_names: list):
for layer, name in zip(layers, layer_names):
self.writer.add_histogram(name + " Bias", layer.bias, self.epoch)
self.writer.add_histogram(name + " Weights", layer.weight, self.epoch)
self.writer.flush() | Python | nomic_cornstack_python_v1 |
comment Definition for a binary tree node.
comment class TreeNode(object):
comment def __init__(self, x):
comment self.val = x
comment self.left = None
comment self.right = None
comment Non trivial Iterative solution
class Solution extends object
begin
function preorderTraversal self root
begin
string :type root: TreeN... | # Definition for a binary tree node.
# class TreeNode(object):
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
# Non trivial Iterative solution
class Solution(object):
def preorderTraversal(self, root):
"""
:type root: TreeNode
:rty... | Python | zaydzuhri_stack_edu_python |
function word_value word
begin
return if expression word == string then 0 else call word_value word at slice : - 1 : + call letter_index_upper word at - 1
end function | def word_value(word: str) -> int:
return (0 if word == '' else
word_value(word[:-1]) + alpha.letter_index_upper(word[-1])) | Python | nomic_cornstack_python_v1 |
function remove_colors string
begin
set color_list = list string [0;30m string [0;31m string [0;32m string [0;33m string [0;34m string [0;35m string [0;36m string [0;37m string [0;39m string [0;40m string [0;41m string [0;42m string [0;43m string [0;44m string [0;45m string [0;46m string [0;47m string ... | def remove_colors(string):
color_list = ['\x1b[0;30m', '\x1b[0;31m', '\x1b[0;32m', '\x1b[0;33m', '\x1b[0;34m', '\x1b[0;35m', '\x1b[0;36m', '\x1b[0;37m', '\x1b[0;39m', '\x1b[0;40m', '\x1b[0;41m', '\x1b[0;42m', '\x1b[0;43m', '\x1b[0;44m', '\x1b[0;45m', '\x1b[0;46m', '\x1b[0;47m', '\x1b[0;49m', '\x1b[0;90m', '\x1b[0;9... | Python | nomic_cornstack_python_v1 |
function lookup_class_name name context depth=3
begin
string given a table name in the form `schema_name`.`table_name`, find its class in the context. :param name: `schema_name`.`table_name` :param context: dictionary representing the namespace :param depth: search depth into imported modules, helps avoid infinite recu... | def lookup_class_name(name, context, depth=3):
"""
given a table name in the form `schema_name`.`table_name`, find its class in the context.
:param name: `schema_name`.`table_name`
:param context: dictionary representing the namespace
:param depth: search depth into imported modules, helps avoid inf... | Python | jtatman_500k |
from metaflow import FlowSpec , step , retry
import json
class ReinforcementLearningSimulatorFlow extends FlowSpec
begin
string Train RL Agents With Different Input States and Reward Functions. Simulate the Same Trained Agent in Simulations of 1. Left Environment with all left data. 2. Right Environment with all Right ... | from metaflow import FlowSpec, step, retry
import json
class ReinforcementLearningSimulatorFlow(FlowSpec):
'''
Train RL Agents With Different Input States and Reward Functions.
Simulate the Same Trained Agent in Simulations of
1. Left Environment with all left data.
2. Right Environment... | Python | zaydzuhri_stack_edu_python |
import sys
comment 직사각형 개수
set n = integer read line stdin
comment 너비는 1로 고정
set h = list
for i in range n
begin
comment 직사각형 높이
append h integer read line stdin
end
sort h | import sys
n = int(sys.stdin.readline()) # 직사각형 개수
# 너비는 1로 고정
h = []
for i in range(n):
h.append(int(sys.stdin.readline())) # 직사각형 높이
h.sort()
| Python | zaydzuhri_stack_edu_python |
import re
comment pattern for check response as reference_number
set reference_number = compile string ^([A-Z0-9]){64}
function AssertNotEmptyOrError status result
begin
string Ожидание что result, возвращаемый вызовом метода, не пустой и не содержит слово Error
assert status msg string Status or request: + string stat... | import re
reference_number = re.compile("^([A-Z0-9]){64}") # pattern for check response as reference_number
def AssertNotEmptyOrError(status, result):
"""Ожидание что result, возвращаемый вызовом метода, не пустой и не содержит слово Error"""
assert status, "Status or request: " + str(status) + "... | Python | zaydzuhri_stack_edu_python |
function line_geo_plot two_line_gdf
begin
set tuple _ ax = call subplots
plot ax=ax
return call VectorTester ax
end function | def line_geo_plot(two_line_gdf):
_, ax = plt.subplots()
two_line_gdf.plot(ax=ax)
return VectorTester(ax) | Python | nomic_cornstack_python_v1 |
function __expandArgs args forStages=none substitutions=none
begin
return call from_iterable generator expression call forCommandLine forStages substitutions for arg in args
end function | def __expandArgs(args, forStages=None, substitutions=None):
return chain.from_iterable(arg.forCommandLine(forStages, substitutions) for arg in args) | Python | nomic_cornstack_python_v1 |
string The sum of the squares of the first ten natural numbers is, 1^2 + 2^2 + ... + 10^2 = 385 The square of the sum of the first ten natural numbers is, (1 + 2 + ... + 10)^2 = 552 = 3025 Hence the difference between the sum of the squares of the first ten natural numbers and the square of the sum is 3025 - 385 = 2640... | '''
The sum of the squares of the first ten natural numbers is,
1^2 + 2^2 + ... + 10^2 = 385
The square of the sum of the first ten natural numbers is,
(1 + 2 + ... + 10)^2 = 552 = 3025
Hence the difference between the sum of the squares of the first ten natural numbers and the square of the sum is 3025 - 385 = ... | Python | zaydzuhri_stack_edu_python |
function remove_duplicate_peaks self
begin
set peaks = list comprehension dictionary t for t in set generator expression call frozenset items d for d in peaks
end function | def remove_duplicate_peaks(self):
self.peaks = [dict(t) for t in set(frozenset(d.items())
for d in self.peaks)] | Python | nomic_cornstack_python_v1 |
function myFunc
begin
set num_1 = integer input string Please enter your first number:
set num_2 = integer input string Please enter your second number:
print num_1 + num_2
end function
set is_Running = true
while is_Running == true
begin
try
begin
call myFunc
end
except ValueError
begin
print string I said enter a num... | def myFunc():
num_1 = int(input("Please enter your first number: "))
num_2 = int(input("Please enter your second number: "))
print(num_1+num_2)
is_Running = True
while is_Running == True:
try:
myFunc()
except ValueError:
print('I said enter a number...')
choice = input... | Python | zaydzuhri_stack_edu_python |
function is_event_service_task jeditaskid
begin
set eventservice = false
set query = dict string jeditaskid jeditaskid
set task = list values filter keyword query string eventservice
if length task > 0 and string eventservice in task at 0 and task at 0 at string eventservice is not none and task at 0 at string eventser... | def is_event_service_task(jeditaskid):
eventservice = False
query = {'jeditaskid': jeditaskid}
task = list(JediTasks.objects.filter(**query).values('eventservice'))
if len(task) > 0 and 'eventservice' in task[0] and task[0]['eventservice'] is not None and task[0]['eventservice'] == 1:
eventserv... | Python | nomic_cornstack_python_v1 |
from random import randint
from time import sleep
import sys
import pyttsx
set FMT_STR = string {} {} --------------
function speak engine what
begin
call say what
call runAndWait
end function
set colors = list string red string yellow string blue string green
set directions = list string right string left
set body_par... | from random import randint
from time import sleep
import sys
import pyttsx
FMT_STR = "{}\n\n{}\n\n--------------\n"
def speak(engine, what):
engine.say(what)
engine.runAndWait()
colors = ["red", "yellow", "blue", "green"]
directions = ["right", "left"]
body_part = ["hand", "foot"]
part_colors = [[None, None], [No... | Python | zaydzuhri_stack_edu_python |
comment e.g. 8-2
from tkinter import *
set widget = call Button text=string Spam padx=10 pady=10
call pack padx=20 pady=20
call config bg=string black fg=string white
call config font=tuple string times 25 string italic underline
call config bd=8 relief=string raised
call config cursor=string target
call mainloop | # e.g. 8-2
from tkinter import *
widget = Button(text='Spam', padx=10, pady=10)
widget.pack(padx=20, pady=20)
widget.config(bg='black', fg='white')
widget.config(font=('times', 25, 'italic underline'))
widget.config(bd=8, relief='raised')
widget.config(cursor='target')
mainloop()
| Python | zaydzuhri_stack_edu_python |
import pygame , sys , time
call init
comment good luck !!
comment window settings
set width = 900
set height = 600
set win_size = tuple width height
comment game_box settings
set box_width = 600
set box_height = 600
comment colors code
set gris = tuple 179 182 183
set light_salmon = tuple 255 160 122
set gris_feta7 = t... | import pygame, sys, time
pygame.init()
#good luck !!
#window settings
width = 900
height= 600
win_size = width,height
#game_box settings
box_width = 600
box_height=600
#colors code
gris = ( 179, 182, 183 )
light_salmon = ( 255, 160, 122)
gris_feta7 = (93, 109, 126)
blue = (0,0,255)
#
#colors of surfaces
menu_color ... | Python | zaydzuhri_stack_edu_python |
function equal_split weights nbin
begin
set inds = call argsort weights at slice : : - 1
set bins = list comprehension list for b in call xrange nbin
set bw = zeros list nbin
for i in inds
begin
set j = argument minimum bw
append bins at j i
set bw at j = bw at j + weights at i
end
return bins
end function | def equal_split(weights, nbin):
inds = np.argsort(weights)[::-1]
bins = [[] for b in xrange(nbin)]
bw = np.zeros([nbin])
for i in inds:
j = np.argmin(bw)
bins[j].append(i)
bw[j] += weights[i]
return bins | Python | nomic_cornstack_python_v1 |
function GetStatus self
begin
return response at string status
end function | def GetStatus(self):
return self.response['status'] | Python | nomic_cornstack_python_v1 |
function instance_id self
begin
return get pulumi self string instance_id
end function | def instance_id(self) -> Optional[pulumi.Input[str]]:
return pulumi.get(self, "instance_id") | Python | nomic_cornstack_python_v1 |
function read_config self key registers_str=string
begin
comment treat as int or list
if registers_str
begin
set registers = call literal_eval registers_str
end
else
begin
set registers = none
end
if is instance io FakeIO
begin
set chip = call get_chip key
set packets = call get_configuration_packets CONFIG_WRITE_PACKE... | def read_config(self, key, registers_str=''):
if registers_str: # treat as int or list
registers = ast.literal_eval(registers_str)
else:
registers = None
if isinstance(self.board.io, FakeIO):
chip = self.board.get_chip(key)
packets = chip.get_conf... | Python | nomic_cornstack_python_v1 |
function close self
begin
if _con is not none
begin
call _commit
close _con
set _con = none
end
end function | def close(self):
if self._con is not None:
self._commit()
self._con.close()
self._con = None | Python | nomic_cornstack_python_v1 |
import sys
set stdin = open string input.txt string r
from collections import deque
comment 1개만 남을때까지 항상 K 번째 수(K의 배수)가 제거됨.
set tuple N K = map int split input
set dq = list range 1 N + 1
set dq = deque dq
while dq
begin
comment 아무 변수 없이 반복
for _ in range K - 1
begin
comment 맨 앞에거가 pop
set cur = call popleft
comment 맨... | import sys
sys.stdin=open("input.txt", "r")
from collections import deque
# 1개만 남을때까지 항상 K 번째 수(K의 배수)가 제거됨.
N, K = map(int, input().split())
dq = list(range(1, N+1))
dq = deque(dq)
while dq:
for _ in range(K-1): #아무 변수 없이 반복
cur = dq.popleft() # 맨 앞에거가 pop
dq.append(cur) # 맨 뒤로 붙이기
#이렇게 해서 K번... | Python | zaydzuhri_stack_edu_python |
function directiveString self
begin
return string %s %s %s %s %d %f %f %d ; %s % tuple atomtype1 atomtype2 atomtype3 atomtype4 func _value _value multiplicity comment
end function | def directiveString(self):
return '%s %s %s %s %d %f %f %d ; %s\n'%(self.atomtype1, self.atomtype2, self.atomtype3, self.atomtype4, self.func, self.phi._value, self.kphi._value, self.multiplicity, self.comment) | Python | nomic_cornstack_python_v1 |
from crypto_support import *
comment find certs with CERT_FIND_SUBJECT_STR_W by dn
function find_certs_subject_str CertStore dn
begin
set founded_certs_list = list
set pCertPrev = none
comment search for first cert
set pCert = call fCertFindCertificateInStore CertStore X509_ASN_ENCODING ? PKCS_7_ASN_ENCODING 0 CERT_FI... | from crypto_support import *
# find certs with CERT_FIND_SUBJECT_STR_W by dn
def find_certs_subject_str(CertStore, dn):
founded_certs_list = []
pCertPrev = None
# search for first cert
pCert = fCertFindCertificateInStore(CertStore,
X509_ASN_ENCODING | PKCS_7_ASN... | Python | zaydzuhri_stack_edu_python |
function write self data
begin
write _out data
end function | def write(self, data):
self._out.write(data) | Python | nomic_cornstack_python_v1 |
string Surrogate model based on Kriging.
import numpy as np
import scipy.linalg as linalg
import os.path
from hashlib import md5
from scipy.optimize import minimize
from openmdao.surrogate_models.surrogate_model import SurrogateModel
from openmdao.warnings import issue_warning , CacheWarning
set MACHINE_EPSILON = eps
c... | """Surrogate model based on Kriging."""
import numpy as np
import scipy.linalg as linalg
import os.path
from hashlib import md5
from scipy.optimize import minimize
from openmdao.surrogate_models.surrogate_model import SurrogateModel
from openmdao.warnings import issue_warning, CacheWarning
MACHINE_EPSILON = np.finfo(... | Python | zaydzuhri_stack_edu_python |
function set_palette_colors self palette
begin
set palette = split palette string :
for i in range 16
begin
set color = call color_parse palette at i
call set_color color
end
end function | def set_palette_colors(self, palette):
palette = palette.split(':')
for i in range(16):
color = gtk.gdk.color_parse(palette[i])
self.get_widget('palette_%d' % i).set_color(color) | Python | nomic_cornstack_python_v1 |
comment Exercise 5
from pathlib import Path
import numpy as np
import pandas as pd
import xarray as xr
import matplotlib.pyplot as plt
set input_dir = call Path string data
set output_dir = call Path string solution
comment 1. Go to http://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles
comment and d... | # Exercise 5
from pathlib import Path
import numpy as np
import pandas as pd
import xarray as xr
import matplotlib.pyplot as plt
input_dir = Path("data")
output_dir = Path("solution")
# 1. Go to http://surfobs.climate.copernicus.eu/dataaccess/access_eobs.php#datafiles
# and download the 0.25 deg. file for daily m... | Python | zaydzuhri_stack_edu_python |
import json
with open string Beta/data/magias.json as f
begin
set magias = load json f
end
with open string Beta/data/classes.json as g
begin
set classes = load json g
end
set me = dict
set clase = list
while true
begin
while true
begin
set m = input string Qual nome da magia que você deseja editar?
set continuar = 0... | import json
with open('Beta/data/magias.json') as f:
magias=json.load(f)
with open('Beta/data/classes.json') as g:
classes=json.load(g)
me={}
clase=[]
while True:
while True:
m=input('Qual nome da magia que você deseja editar?\n')
continuar=0
if m in magias: break
elif m==... | Python | zaydzuhri_stack_edu_python |
function _get_float data position dummy0 dummy1 dummy2
begin
string Decode a BSON double to python float.
set end = position + 8
return tuple call _UNPACK_FLOAT data at slice position : end : at 0 end
end function | def _get_float(data, position, dummy0, dummy1, dummy2):
"""Decode a BSON double to python float."""
end = position + 8
return _UNPACK_FLOAT(data[position:end])[0], end | Python | jtatman_500k |
function c L n m
begin
return sum generator expression call b L i m for i in range n + 1
end function | def c(L,n,m):
return sum(b(L,i,m) for i in range(n+1)) | Python | nomic_cornstack_python_v1 |
function ls args
begin
string List S3 buckets. See also "aws s3 ls". Use "aws s3 ls NAME" to list bucket contents.
set table = list
for bucket in call filter_collection buckets args
begin
set LocationConstraint = call get_bucket_location Bucket=name at string LocationConstraint
set cloudwatch = cloudwatch
set bucket_r... | def ls(args):
"""
List S3 buckets. See also "aws s3 ls". Use "aws s3 ls NAME" to list bucket contents.
"""
table = []
for bucket in filter_collection(resources.s3.buckets, args):
bucket.LocationConstraint = clients.s3.get_bucket_location(Bucket=bucket.name)["LocationConstraint"]
clou... | Python | jtatman_500k |
function build_conv_net self
begin
set conv1 = conv 2d inputs=inputs filters=32 kernel_size=list 8 8 strides=tuple 4 4 padding=string valid kernel_initializer=call xavier_initializer_conv2d name=string conv1
set conv1_out = relu conv1 name=string conv1_out
set conv2 = conv 2d inputs=conv1_out filters=64 kernel_size=tup... | def build_conv_net(self):
conv1 = tf.layers.conv2d(
inputs=self.inputs,
filters=32,
kernel_size=[8, 8],
strides=(4, 4),
padding='valid',
kernel_initializer=tf.contrib.layers.xavier_initializer_conv2d(),
name='conv1'
)
... | Python | nomic_cornstack_python_v1 |
function run self
begin
comment loop until the recipe limit is reached or there are no more crawlers left
while num_recipes < recipe_limit or length crawlers < 1
begin
set crawler = next crawler_iter
try
begin
set num_recipes = num_recipes + call crawl
end
except AnchorListsEmptyError as e
begin
info string E is: { e }... | def run(self) -> None:
# loop until the recipe limit is reached or there are no more crawlers left
while self.num_recipes < self.recipe_limit or len(self.crawlers) < 1:
crawler = next(self.crawler_iter)
try:
self.num_recipes += crawler.crawl()
except A... | Python | nomic_cornstack_python_v1 |
from typing import List , Callable
import numpy as np
seed 42
set fns = list lambda x -> - call power x 3 lambda x -> log absolute x lambda x -> sin 3 * x lambda x -> exp x lambda x -> x + 4 lambda x -> - x + square root absolute x lambda x -> x
function generate functions target_index=0 n_samples=1000 x_normal_loc=0.0... | from typing import List, Callable
import numpy as np
np.random.seed(42)
fns = [
lambda x: -np.power(x, 3),
lambda x: np.log(np.abs(x)),
lambda x: np.sin(3 * x),
lambda x: np.exp(x),
lambda x: x + 4,
lambda x: -x + np.sqrt(np.abs(x)),
lambda x: x
]
def generate(
functions: List[C... | Python | zaydzuhri_stack_edu_python |
function connect self event_name callback
begin
call connect event_name callback
end function | def connect(self, event_name, callback):
self.canvas.connect(event_name, callback) | Python | nomic_cornstack_python_v1 |
function confidence95 self
begin
set degfreedom = reps at 0 - 1
return call student_t_quantile95 degfreedom * call Si2 n / reps at 0 ^ 0.5
end function | def confidence95(self):
degfreedom = self.reps[0] - 1
return student_t_quantile95(degfreedom) * \
(self.Si2(self.n) / self.reps[0]) ** 0.5 | Python | nomic_cornstack_python_v1 |
function all_with_acl cls user=none
begin
comment If no user, assume the user that made the request.
if not user
begin
set user = current_user
end
comment pylint: disable=singleton-comparison
return filter call or_ user == user call and_ user == none group == none call in_ list comprehension id for group in groups perm... | def all_with_acl(cls, user=None):
# If no user, assume the user that made the request.
if not user:
user = current_user
# pylint: disable=singleton-comparison
return cls.query.filter(
or_(
cls.AccessControlEntry.user == user,
and_(... | Python | nomic_cornstack_python_v1 |
function create_superuser self email username password
begin
set user = call create_user email password=password username=username
set is_admin = true
save using=_db
return user
end function | def create_superuser(self, email, username, password):
user = self.create_user(email, password=password,
username=username )
user.is_admin = True
user.save(using=self._db)
return user | Python | nomic_cornstack_python_v1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.