text stringlengths 232 16.3k | domain stringclasses 1
value | difficulty stringclasses 3
values | meta dict |
|---|---|---|---|
<|fim_prefix|># repo: MosesSymeonidis/aggregation_builder path: /aggregation_builder/operators/boolean.py
def AND(*expressions):
"""
Evaluates one or more expressions and returns true if all of the expressions are true.
See https://docs.mongodb.com/manual/reference/operator/aggregation/and/
for more de... | code_fim | medium | {
"lang": "python",
"repo": "MosesSymeonidis/aggregation_builder",
"path": "/aggregation_builder/operators/boolean.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
Evaluates a boolean and returns the opposite boolean value.
See https://docs.mongodb.com/manual/reference/operator/aggregation/not/
for more details
:param expression: An array of expressions
:return: Aggregation operator
"""
return {'$not': [expression]}<|fim_prefix|>#... | code_fim | hard | {
"lang": "python",
"repo": "MosesSymeonidis/aggregation_builder",
"path": "/aggregation_builder/operators/boolean.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: KohlbacherLab/diaproteomics path: /bin/select_pseudo_irts_from_lib.py
#!/usr/bin/env python
from __future__ import print_function
import sys
import scipy
import numpy as np
from scipy import stats
import pandas as pd
import matplotlib.pyplot as plt
import glob
import argparse
"""
select_pseudo_... | code_fim | hard | {
"lang": "python",
"repo": "KohlbacherLab/diaproteomics",
"path": "/bin/select_pseudo_irts_from_lib.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> model.add_argument(
'-rn', '--max_rt',
type=int,
help='maximum rt of irts to select for alignment'
)
model.add_argument(
'-q', '--quantiles',
type=bool,
help='whether to use only the 1st and 4th RT quantile for irt selection'
)
model.ad... | code_fim | hard | {
"lang": "python",
"repo": "KohlbacherLab/diaproteomics",
"path": "/bin/select_pseudo_irts_from_lib.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nk2028/qieyun-sqlite path: /build.py
import os
import sqlite3
os.system('curl -LsSo 字頭表.csv https://raw.githubusercontent.com/nk2028/qieyun-data/9849852/%E5%AD%97%E9%A0%AD%E8%A1%A8.csv')
os.system('curl -LsSo 小韻表.csv https://raw.githubusercontent.com/nk2028/qieyun-data/9849852/%E5%B0%8F%E9%9F%BB... | code_fim | hard | {
"lang": "python",
"repo": "nk2028/qieyun-sqlite",
"path": "/build.py",
"mode": "psm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>cur.executemany('INSERT INTO 字頭 VALUES (?, ?, ?, ?)', 字頭資料())
# Extra
cur.execute(f'''
CREATE VIEW '小韻全' AS
SELECT 小韻號,
母 ||
ifnull(呼, '') ||
CASE 等數字 {等數字SQL} END ||
ifnull(重紐, '') ||
韻 ||
聲 AS 音韻描述,
母,
呼,
CASE 等數字 {等數字SQL} END AS 等,
重紐,
韻,
聲,
CASE {清濁SQL} END AS 清濁,
CASE {音SQL} END AS 音,
CASE {組SQL} E... | code_fim | hard | {
"lang": "python",
"repo": "nk2028/qieyun-sqlite",
"path": "/build.py",
"mode": "spm",
"license": "CC0-1.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
if __name__ == '__main__':
start_x = -1.9 # x range
end_x = 1.9
start_y = -1.1 # y range
end_y = 1.1
width = 1200 # image width
c = -0.835 - 0.2321 * 1j
bg_ratio = (4, 2.5, 1)
ratio = (0.9, 0.9, 0.9)
step = (end_x - start_x) / width
Y, X = np.mgrid[... | code_fim | hard | {
"lang": "python",
"repo": "MJPeppersdev/fracture",
"path": "/julia.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> step = (end_x - start_x) / width
Y, X = np.mgrid[start_y:end_y:step, start_x:end_x:step]
Z = X + 1j * Y
img = gen_julia(Z, c, bg_ratio, ratio)
img.save('julia.png')<|fim_prefix|># repo: MJPeppersdev/fracture path: /julia.py
import tensorflow as tf
import numpy as np
from PIL i... | code_fim | hard | {
"lang": "python",
"repo": "MJPeppersdev/fracture",
"path": "/julia.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MJPeppersdev/fracture path: /julia.py
import tensorflow as tf
import numpy as np
from PIL import Image
R = 4
ITER_NUM = 200
def get_color(bg_ratio, ratio):
def color(z, i):
if abs(z) < R:
return 0, 0, 0
v = np.log2(i + R - np.log2(np.log2(abs(z)))) /... | code_fim | hard | {
"lang": "python",
"repo": "MJPeppersdev/fracture",
"path": "/julia.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def _preprocess_file(file_name):
"""
reads and preprocesses a file, return the raw content
and the content without comments
"""
raw_content = utils.run_on_main_thread(
partial(utils.get_file_content, file_name, force_lf_endings=True))
# replace all comments with spaces to ... | code_fim | hard | {
"lang": "python",
"repo": "MPvHarmelen/MarkdownCiteCompletions",
"path": "/latextools_utils/analysis.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: MPvHarmelen/MarkdownCiteCompletions path: /latextools_utils/analysis.py
import copy
import os
import re
import itertools
from functools import partial
import traceback
import sublime
_ST3 = True
from . import utils
from .cache import LocalCache
from ..external.frozendict import frozendict
from ... | code_fim | hard | {
"lang": "python",
"repo": "MPvHarmelen/MarkdownCiteCompletions",
"path": "/latextools_utils/analysis.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """Decorator: define a function that will never display its help if asked"""
func.no_help = True
return func
def regex(exp):
"Decorator: only process the line if it matched with regular expression"
def real_decorator(func):
@wraps(func)
def newfunc(bot, line):
... | code_fim | hard | {
"lang": "python",
"repo": "brunobord/cmdbot",
"path": "/cmdbot/decorators.py",
"mode": "spm",
"license": "WTFPL",
"source": "the-stack-v2"
} |
<|fim_suffix|> if string in line.message:
return func(bot, line)
return newfunc
return real_decorator
def no_verb(func):
"""Decorator: define a function that will be executed if no verb is found
in the line"""
func.no_verb = True
return func
def no_help(func):
... | code_fim | hard | {
"lang": "python",
"repo": "brunobord/cmdbot",
"path": "/cmdbot/decorators.py",
"mode": "spm",
"license": "WTFPL",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: brunobord/cmdbot path: /cmdbot/decorators.py
#-*- coding: utf8 -*-
import re
from functools import wraps
def direct(func):
"Decorator: only process the line if it's a direct message"
@wraps(func)
def newfunc(bot, line):
if line.direct:
return func(bot, line)
... | code_fim | hard | {
"lang": "python",
"repo": "brunobord/cmdbot",
"path": "/cmdbot/decorators.py",
"mode": "psm",
"license": "WTFPL",
"source": "the-stack-v2"
} |
<|fim_suffix|> return state.copy(
latest_block_header=BeaconBlockHeader(
slot=block.slot,
parent_root=block.parent_root,
body_root=block.body.hash_tree_root,
),
)
def process_randao(state: BeaconState,
block: BaseBeaconBlock,
... | code_fim | hard | {
"lang": "python",
"repo": "davesque/trinity",
"path": "/eth2/beacon/state_machines/forks/serenity/block_processing.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return state.copy(
randao_mixes=update_tuple_item(
state.randao_mixes,
randao_mix_index,
new_randao_mix,
),
)
def process_eth1_data(state: BeaconState,
block: BaseBeaconBlock,
config: Eth2Config) -> B... | code_fim | hard | {
"lang": "python",
"repo": "davesque/trinity",
"path": "/eth2/beacon/state_machines/forks/serenity/block_processing.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: davesque/trinity path: /eth2/beacon/state_machines/forks/serenity/block_processing.py
from eth2._utils.hash import hash_eth2
from eth2._utils.tuple import update_tuple_item
from eth2._utils.numeric import (
bitwise_xor,
)
from eth2.configs import (
Eth2Config,
CommitteeConfig,
)
from... | code_fim | hard | {
"lang": "python",
"repo": "davesque/trinity",
"path": "/eth2/beacon/state_machines/forks/serenity/block_processing.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>The official definition of this extension is available here:
http://www.opengl.org/registry/specs/EXT/swap_control.txt
'''
from OpenGL import platform, constant, arrays
from OpenGL import extensions, wrapper
import ctypes
from OpenGL.raw.WGL import _types, _glgets
from OpenGL.raw.WGL.EXT.swap_control impo... | code_fim | hard | {
"lang": "python",
"repo": "juso40/bl2sdk_Mods",
"path": "/blimgui/dist/OpenGL/WGL/EXT/swap_control.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: juso40/bl2sdk_Mods path: /blimgui/dist/OpenGL/WGL/EXT/swap_control.py
'''OpenGL extension EXT.swap_control
This module customises the behaviour of the
OpenGL.raw.WGL.EXT.swap_control to provide a more
Python-friendly API
<|fim_suffix|>def glInitSwapControlEXT():
'''Return boolean indicati... | code_fim | hard | {
"lang": "python",
"repo": "juso40/bl2sdk_Mods",
"path": "/blimgui/dist/OpenGL/WGL/EXT/swap_control.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> if 'prune' not in tcrrep.hcluster_df.columns:
if verbose: print("NO PRUNE COLUMNS USED ALL SET TO 0")
tcrrep.hcluster_df['prune'] = 0
print("ITERATE THROUGH CLUSTERS")
svgs = list()
svgs_raw = list()
reference_unique = list()
reference_unique_olga= list()
r... | code_fim | hard | {
"lang": "python",
"repo": "kmayerb/tcrdist3",
"path": "/tcrdist/tree.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kmayerb/tcrdist3 path: /tcrdist/tree.py
r_diff)
clone_df : pd.DataFrame [nclones x metadata]
Contains metadata for each clone.
pwmat : np.ndarray [nclones x nclones]
Square distance matrix for defining neighborhoods
x_cols : lis... | code_fim | hard | {
"lang": "python",
"repo": "kmayerb/tcrdist3",
"path": "/tcrdist/tree.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: kmayerb/tcrdist3 path: /tcrdist/tree.py
n in clone_df that specifies counts.
Default none assumes count of 1 cell for each row.
subset_ind : None or np.ndarray with partial index of df, optional
Provides option to tally counts only within a ... | code_fim | hard | {
"lang": "python",
"repo": "kmayerb/tcrdist3",
"path": "/tcrdist/tree.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: DavidWhittingham/agsadmin path: /agsadmin/rest_admin/system/Directory.py
from __future__ import (absolute_import, division, print_function, unicode_literals)
from builtins import (ascii, bytes, chr, dict, filter, hex, input, int, map, next, oct, open, pow, range, round, str,
... | code_fim | hard | {
"lang": "python",
"repo": "DavidWhittingham/agsadmin",
"path": "/agsadmin/rest_admin/system/Directory.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> @local_directory_path.setter
def local_directory_path(self, value):
if self.use_local_directory == False:
raise Exception("Cannot edit local directory path when 'use_local_directory' is false.")
self._pdata["local_directory_path"] = value
@property
def max_file... | code_fim | hard | {
"lang": "python",
"repo": "DavidWhittingham/agsadmin",
"path": "/agsadmin/rest_admin/system/Directory.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> return "{0}/system/directories/{1}".format(self._url_base, self.name)
def clean(self):
send_session_request(
self._session,
self._create_operation_request(
self,
operation = "clean",
method = "POST")
)
... | code_fim | hard | {
"lang": "python",
"repo": "DavidWhittingham/agsadmin",
"path": "/agsadmin/rest_admin/system/Directory.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.leftSub = rospy.Subscriber(
"/stepper_cmd", Int16MultiArray, self.stepper_callback)
#self.pi = pigpio_istance
self.pins_config = pins_config
self.init_pins()
self.l_speed = init_speed
self.r_speed = init_speed
self.left_dir = bool(0)... | code_fim | medium | {
"lang": "python",
"repo": "ahmedokasha000/aio_robot",
"path": "/src/stepper_driver_ros_jetson.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: ahmedokasha000/aio_robot path: /src/stepper_driver_ros_jetson.py
#!/usr/bin/env python3
import RPi.GPIO as GPIO
import rospy
from std_msgs.msg import String
from std_msgs.msg import Int16MultiArray
import time
from math import pi
from math import copysign
PINS_CONFIG = {"STEP_L": 18, "DIR_L": 4,... | code_fim | hard | {
"lang": "python",
"repo": "ahmedokasha000/aio_robot",
"path": "/src/stepper_driver_ros_jetson.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: NinoDoko/nino_pianino path: /ninopianino/decision_maker.py
import random
import song_generator
#attributes_table is a table with keys that look like this:
# 'key':
# {
# 'related_key' :
# [
# {
# 'func' : get_key_values,
# 'args' : ['s... | code_fim | medium | {
"lang": "python",
"repo": "NinoDoko/nino_pianino",
"path": "/ninopianino/decision_maker.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def get_table_result(self, attribute_table):
r, s = random.random(), 0
for d in table:
if type(d['value']) == list:
d_value = self.get_table_result(d)
else:
d_value = d['value']
s += d['prob']
if s >= r: ... | code_fim | hard | {
"lang": "python",
"repo": "NinoDoko/nino_pianino",
"path": "/ninopianino/decision_maker.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> r, s = random.random(), 0
for d in table:
if type(d['value']) == list:
d_value = self.get_table_result(d)
else:
d_value = d['value']
s += d['prob']
if s >= r:
return d_value<|fim_prefix|># rep... | code_fim | hard | {
"lang": "python",
"repo": "NinoDoko/nino_pianino",
"path": "/ninopianino/decision_maker.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Returns:
tensor with same shape as input injected with some information
about the relative or absolute position of the tokens in the
sequence.
"""
x = x + self.pe[: x.size(0)]
return self.dropout(x)
def gen_square_subsequent_mas... | code_fim | hard | {
"lang": "python",
"repo": "gpauloski/kfac-pytorch",
"path": "/examples/language/transformer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gpauloski/kfac-pytorch path: /examples/language/transformer.py
"""Simple Transformer Model.
Based on Attention is All You Need and
https://pytorch.org/tutorials/beginner/transformer_tutorial.html.
"""
from __future__ import annotations
import math
import torch
from torch import nn
class Tran... | code_fim | hard | {
"lang": "python",
"repo": "gpauloski/kfac-pytorch",
"path": "/examples/language/transformer.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> position = torch.arange(max_len).unsqueeze(1)
div_term = torch.exp(
torch.arange(0, d_model, 2) * (-math.log(10000.0) / d_model),
)
self.pe: torch.Tensor
pe = torch.zeros(max_len, 1, d_model)
pe[:, 0, 0::2] = torch.sin(position * div_term)
... | code_fim | hard | {
"lang": "python",
"repo": "gpauloski/kfac-pytorch",
"path": "/examples/language/transformer.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Naavy/CodeBrainers_projekt path: /__init__.py
from flask import Flask
from playhouse.flask_utils import FlaskDB
from flask_admin import Admin
from flask_security import (
Security,
PeeweeUserDatastore,
UserMixin,
RoleMixin,
login_required
)
from .config import Config
<|fim_su... | code_fim | medium | {
"lang": "python",
"repo": "Naavy/CodeBrainers_projekt",
"path": "/__init__.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>user_datastore = PeeweeUserDatastore(db_wrapper.database, models.User,
models.Role, models.UserRoles)
security = Security(app, user_datastore)<|fim_prefix|># repo: Naavy/CodeBrainers_projekt path: /__init__.py
from flask import Flask
from playhouse.flask_utils import... | code_fim | medium | {
"lang": "python",
"repo": "Naavy/CodeBrainers_projekt",
"path": "/__init__.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def stop(self):
self._stop.set()
self.thread.join()
self._stop.clear()
def hasFailed(self):
return self._failed.is_set()
class _TooMuchWorkException(Exception):
'''
Raised when looper's work takes too long to exectute, and looper can't keep up
'''<|fim... | code_fim | medium | {
"lang": "python",
"repo": "WildOrangutan/RPi-fan-controller",
"path": "/src/looper.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> self._stop.set()
self.thread.join()
self._stop.clear()
def hasFailed(self):
return self._failed.is_set()
class _TooMuchWorkException(Exception):
'''
Raised when looper's work takes too long to exectute, and looper can't keep up
'''<|fim_prefix|># repo: Wil... | code_fim | hard | {
"lang": "python",
"repo": "WildOrangutan/RPi-fan-controller",
"path": "/src/looper.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: WildOrangutan/RPi-fan-controller path: /src/looper.py
from typing import Callable
from time import time, sleep
from queue import Queue
from threading import Thread, Event
import src.check as check
class Looper:
def __init__(self, period:float, work:Callable):
'''
period - ti... | code_fim | medium | {
"lang": "python",
"repo": "WildOrangutan/RPi-fan-controller",
"path": "/src/looper.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>
test2 = {key: value for key, value in test1.items()}
test2['img_prefix'] = test_img_prefix2
test2['ann_file'] = test_ann_file2
# test3 = {key: value for key, value in test1.items()}
# test3['img_prefix'] = test_img_prefix3
# test3['ann_file'] = test_ann_file3
# test_list = [test1, test2, test3]
test_li... | code_fim | hard | {
"lang": "python",
"repo": "Deep-Spark/DeepSparkHub",
"path": "/cv/ocr/satrn/pytorch/base/configs/datasets_/Sample_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Deep-Spark/DeepSparkHub path: /cv/ocr/satrn/pytorch/base/configs/datasets_/Sample_test.py
test_root = 'data/mixture'
# test_img_prefix1 = f'{test_root}/IIIT5K/'
test_img_prefix1 = f'{test_root}/icdar_2013/'
test_img_prefix2 = f'{test_root}/icdar_2015/'
<|fim_suffix|>test1 = dict(
type='OCRD... | code_fim | medium | {
"lang": "python",
"repo": "Deep-Spark/DeepSparkHub",
"path": "/cv/ocr/satrn/pytorch/base/configs/datasets_/Sample_test.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|># test3 = {key: value for key, value in test1.items()}
# test3['img_prefix'] = test_img_prefix3
# test3['ann_file'] = test_ann_file3
# test_list = [test1, test2, test3]
test_list = [test1, test2]<|fim_prefix|># repo: Deep-Spark/DeepSparkHub path: /cv/ocr/satrn/pytorch/base/configs/datasets_/Sample_test.... | code_fim | medium | {
"lang": "python",
"repo": "Deep-Spark/DeepSparkHub",
"path": "/cv/ocr/satrn/pytorch/base/configs/datasets_/Sample_test.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nicksan2c/diskover path: /diskover/diskover.py
= plugin.add_meta(path, d_stat)
if extrameta_dict is not None:
data.update(extrameta_dict)
except (RuntimeWarning, RuntimeError) as e:
err_messag... | code_fim | hard | {
"lang": "python",
"repo": "nicksan2c/diskover",
"path": "/diskover/diskover.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nicksan2c/diskover path: /diskover/diskover.py
fsize = f_stat.st_size
# calculate allocated file size (du size)
if IS_WIN:
fsize_du = fsize
elif options.altscanner:
fsize_du =... | code_fim | hard | {
"lang": "python",
"repo": "nicksan2c/diskover",
"path": "/diskover/diskover.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if not exc_empty_files or (exc_empty_files and fsize > 0):
if fsize >= minfilesize and \
fmtime_sec > minmtime and \
fmtime_sec < maxmtime and \
fctime_sec > minctime and \
... | code_fim | hard | {
"lang": "python",
"repo": "nicksan2c/diskover",
"path": "/diskover/diskover.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jan25/code_sorted path: /leetcode/weekly171/1_no_zero.py
'''
https://leetcode.com/contest/weekly-contest-171/problems/convert-integer-to-the-sum-of-two-no-zero-integers/
'''
class Solution:
def getNoZeroIntegers(self, n: int) -> List[int]:
<|fim_suffix|> return a == 0 or (a % 10 !=... | code_fim | easy | {
"lang": "python",
"repo": "jan25/code_sorted",
"path": "/leetcode/weekly171/1_no_zero.py",
"mode": "psm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|> return a == 0 or (a % 10 != 0 and noz(a // 10))
for a in range(1, n + 1):
if noz(a) and noz(n - a):
return [a, n - a]<|fim_prefix|># repo: jan25/code_sorted path: /leetcode/weekly171/1_no_zero.py
'''
https://leetcode.com/contest/weekly-contest-171/... | code_fim | easy | {
"lang": "python",
"repo": "jan25/code_sorted",
"path": "/leetcode/weekly171/1_no_zero.py",
"mode": "spm",
"license": "Unlicense",
"source": "the-stack-v2"
} |
<|fim_suffix|>
batch_size = 32
best_accuracy = {}
for seed in range(n_trials):
best_accuracy[seed] = 0.0
for seed in range(n_trials):
print('We are currently training on seed:', seed)
# for each iteration of the hyperparameter search, return a set of parameters
# and feed them into the relevant parts
# ... | code_fim | hard | {
"lang": "python",
"repo": "bilal841/DNNorDermatologist",
"path": "/DataSplit_HpSearch.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|># Define a Callback class that stops training once accuracy reaches 90%
#class myCallback(tf.keras.callbacks.Callback):
#def on_epoch_end(self, epoch, logs={}):
# if(logs.get('acc')>0.87):
#print("\nReached 90% accuracy so cancelling training!")
#self.model.stop_training = True
# make ... | code_fim | hard | {
"lang": "python",
"repo": "bilal841/DNNorDermatologist",
"path": "/DataSplit_HpSearch.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: bilal841/DNNorDermatologist path: /DataSplit_HpSearch.py
import pandas as pd
import numpy as np
import os
import sys
from sklearn.model_selection import train_test_split
from sklearn.metrics import confusion_matrix, roc_auc_score
from sklearn.utils import class_weight
import skopt
from keras.a... | code_fim | hard | {
"lang": "python",
"repo": "bilal841/DNNorDermatologist",
"path": "/DataSplit_HpSearch.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: yanhuay/seisflows path: /seisflows/seistools/specfem2d.py
from seisflows.tools.code import findpath
from seisflows.seistools.shared import getpar, setpar
### input file writers
def write_sources(par, hdr, path='.', suffix=''):
""" Writes source information to text file
"""
file = ... | code_fim | hard | {
"lang": "python",
"repo": "yanhuay/seisflows",
"path": "/seisflows/seistools/specfem2d.py",
"mode": "psm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> # write interfaces file
file = 'DATA/interfaces.dat'
lines = []
lines.extend('2\n')
lines.extend('2\n')
lines.extend('%f %f\n'%(par.XMIN, par.ZMIN))
lines.extend('%f %f\n'%(par.XMAX, par.ZMIN))
lines.extend('2\n')
lines.extend('%f %f\n'%(par.XMIN, par.ZMAX))
lines.e... | code_fim | hard | {
"lang": "python",
"repo": "yanhuay/seisflows",
"path": "/seisflows/seistools/specfem2d.py",
"mode": "spm",
"license": "BSD-2-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>for region_i in region_list:
plot_param=plottingDictionary[region_i]#setup_plot_parameters(region=region_i)
fig_hall=plt.figure(figsize=(6,6))
ax_hall = fig_hall.add_subplot(111)
v_hall_max=np.max(plot_param['rms_max'])
v_hall_min=np.min(plot_param['rms_min'])
nbin_hall=int(np.ceil... | code_fim | hard | {
"lang": "python",
"repo": "GBTAmmoniaSurvey/DR1_analysis",
"path": "/map_rms.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> data, hd=fits.getdata(file_rms, header=True)
fig=plt.figure(figsize=(6,6))
ax = fig.add_subplot(111)
# the histogram of the data
nbin=int(np.ceil( np.abs(v_max-v_min)/ bin_size))
myarray=data[np.isfinite(data)]
weights = n... | code_fim | hard | {
"lang": "python",
"repo": "GBTAmmoniaSurvey/DR1_analysis",
"path": "/map_rms.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: GBTAmmoniaSurvey/DR1_analysis path: /map_rms.py
import matplotlib.pyplot as plt
import astropy.units as u
import warnings
import numpy as np
import os
from astropy.io import fits
import aplpy
from config import plottingDictionary
region_list=['L1688', 'B18', 'NGC1333', 'OrionA']
line_list=['NH... | code_fim | hard | {
"lang": "python",
"repo": "GBTAmmoniaSurvey/DR1_analysis",
"path": "/map_rms.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jailukanna/Python-Projects-Dojo path: /05.More Python - Microsoft/07.working_with_files_read.py
stream = open('./test.txt',mode='rt')
print('\nIs is readable: ' + s<|fim_suffix|>to the end of the file: \n' + str(stream.readlines()))
stream.close()<|fim_middle|>tr(stream.readable()))
print('\nRead... | code_fim | medium | {
"lang": "python",
"repo": "jailukanna/Python-Projects-Dojo",
"path": "/05.More Python - Microsoft/07.working_with_files_read.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>to the end of the file: \n' + str(stream.readlines()))
stream.close()<|fim_prefix|># repo: jailukanna/Python-Projects-Dojo path: /05.More Python - Microsoft/07.working_with_files_read.py
stream = open('./test.txt',mode='rt')
print('\nIs is readable: ' + str(stream.readable()))
print('\nRead one char: ' +... | code_fim | medium | {
"lang": "python",
"repo": "jailukanna/Python-Projects-Dojo",
"path": "/05.More Python - Microsoft/07.working_with_files_read.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: idaholab/raven path: /scripts/conversionScripts/toOutStreamsNode.py
# Copyright 2017 Battelle Energy Alliance, 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
#
# h... | code_fim | hard | {
"lang": "python",
"repo": "idaholab/raven",
"path": "/scripts/conversionScripts/toOutStreamsNode.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|> if stepsNode is not None:
for outputNode in stepsNode.iter('Output'):
if 'class' in outputNode.attrib and outputNode.attrib['class'] == 'OutStreamManager':
outputNode.attrib['class'] = 'OutStreams'
return tree
if __name__=='__main__':
import convert_utils
import sys
convert_... | code_fim | medium | {
"lang": "python",
"repo": "idaholab/raven",
"path": "/scripts/conversionScripts/toOutStreamsNode.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: simondaout/PyGdalSAR path: /NSBAS-playground/utils/plot_hist_dphi_r4.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
############################################
#
# PyGdalSAR: An InSAR post-processing package
# written in Python-Gdal
#
############################################
# Author ... | code_fim | hard | {
"lang": "python",
"repo": "simondaout/PyGdalSAR",
"path": "/NSBAS-playground/utils/plot_hist_dphi_r4.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>#f = ax1.lines[0]
#xf = f.get_xydata()[:,0]
#yf = f.get_xydata()[:,1]
#ax1.fill_between(xf, yf, color="dodgerblue", alpha=0.5, where=(xf>(diff_med-1*diff_std)) & (xf<(diff_med+1*diff_std)))
def linear_f(x, a, b):
return a*x + b
interval = 20
ax2.scatter(dem_clean[::interval], diff[::interval], color... | code_fim | hard | {
"lang": "python",
"repo": "simondaout/PyGdalSAR",
"path": "/NSBAS-playground/utils/plot_hist_dphi_r4.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>def linear_f(x, a, b):
return a*x + b
interval = 20
ax2.scatter(dem_clean[::interval], diff[::interval], color='dodgerblue', alpha=0.05,
marker = 's', s = 5, edgecolor = 'none',rasterized=True,
)
popt, pcov = curve_fit(linear_f, dem_clean, diff)
ax2.plot(dem_clean, linear_f(dem_clean... | code_fim | hard | {
"lang": "python",
"repo": "simondaout/PyGdalSAR",
"path": "/NSBAS-playground/utils/plot_hist_dphi_r4.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: din982/Courant-News path: /courant/core/genericadmin/templatetags/genericadmin.py
from django import template
from django.contrib.contenttypes.models import ContentType
<|fim_suffix|> def __init__(self):
pass
def render(self, context):
return_string = "var MODEL_URL_ARRAY = {"
fo... | code_fim | medium | {
"lang": "python",
"repo": "din982/Courant-News",
"path": "/courant/core/genericadmin/templatetags/genericadmin.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> Syntax::
{% get_generic_relation_list %}
"""
tokens = token.contents.split()
return do_get_generic_objects()
register.tag('get_generic_relation_list', get_generic_relation_list)<|fim_prefix|># repo: din982/Courant-News path: /courant/core/genericadmin/templatetags/g... | code_fim | medium | {
"lang": "python",
"repo": "din982/Courant-News",
"path": "/courant/core/genericadmin/templatetags/genericadmin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> """
tokens = token.contents.split()
return do_get_generic_objects()
register.tag('get_generic_relation_list', get_generic_relation_list)<|fim_prefix|># repo: din982/Courant-News path: /courant/core/genericadmin/templatetags/genericadmin.py
from django import template
from django.contrib... | code_fim | hard | {
"lang": "python",
"repo": "din982/Courant-News",
"path": "/courant/core/genericadmin/templatetags/genericadmin.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> the_template = None
self.logger.debug(module, "Jinja template requested: >%s<" % template_name)
self.logger.debug(module, "Jinja template directory: >%s<" % template_directory)
try:
self.jinja_environment = jinja2.Environment(loader=jinja2.FileSystemLoader(templ... | code_fim | hard | {
"lang": "python",
"repo": "jacbeekers/excel2json",
"path": "/excelform2json/utils/helpers.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> self.jinja_environment = None
def get_jinja_template(self, template_directory, template_name):
module = __name__ + ".get_jinja_template"
if template_name is None:
return messages.message["jinja_template_name_not_provided"], None
the_template = None
... | code_fim | medium | {
"lang": "python",
"repo": "jacbeekers/excel2json",
"path": "/excelform2json/utils/helpers.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jacbeekers/excel2json path: /excelform2json/utils/helpers.py
from lineage_excel2meta_interface.utils import messages, check_schema
import logging
import jinja2
import json
class UtilsHelper:
logger = logging.getLogger(__name__)
logger.setLevel(logging.DEBUG)
def __init__(self):
<|f... | code_fim | hard | {
"lang": "python",
"repo": "jacbeekers/excel2json",
"path": "/excelform2json/utils/helpers.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: LaplaceKorea/aboleth path: /tests/test_initialisers.py
"""Test the initialisation functions."""
import numpy as np
import tensorflow as tf
import aboleth as ab
def test_glorot_std():
result = ab.initialisers._glorot_std(10, 21)
assert np.allclose(result, 1. / np.sqrt(3 * 31))
def te... | code_fim | hard | {
"lang": "python",
"repo": "LaplaceKorea/aboleth",
"path": "/tests/test_initialisers.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_suffix|>def test_initialise_stds(mocker):
mocker.patch.dict("aboleth.initialisers._PRIOR_DICT",
{"foo": lambda x, y: y + 10 * x})
init_val = "foo"
learn_prior = False
suffix = "bar"
std, std0 = ab.initialisers.initialise_stds(1, 2, init_val, learn_prior,
... | code_fim | hard | {
"lang": "python",
"repo": "LaplaceKorea/aboleth",
"path": "/tests/test_initialisers.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: peterhinch/micropython_eeprom path: /flash/flash_spi.py
# flash_spi.py MicroPython driver for SPI NOR flash devices.
# Released under the MIT License (MIT). See LICENSE.
# Copyright (c) 2019-2020 Peter Hinch
import time
from micropython import const
from bdevice import FlashDevice
# Supported ... | code_fim | hard | {
"lang": "python",
"repo": "peterhinch/micropython_eeprom",
"path": "/flash/flash_spi.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> mvp = self._mvp
for cs in self._cspins: # For each chip
mvp[0] = _WREN
cs(0)
self._spi.write(mvp[:1]) # Enable write
cs(1)
mvp[0] = _CE
cs(0)
self._spi.write(mvp[:1]) # Start erase
cs(1)
... | code_fim | hard | {
"lang": "python",
"repo": "peterhinch/micropython_eeprom",
"path": "/flash/flash_spi.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> for o in model.objects.all():
path = o.get_json_path()
assert path
assert isinstance(path, str)<|fim_prefix|># repo: nocproject/noc path: /tests/models/test_0009_get_json_path.py
# ----------------------------------------------------------------------
# Test .get_json_path() m... | code_fim | medium | {
"lang": "python",
"repo": "nocproject/noc",
"path": "/tests/models/test_0009_get_json_path.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: nocproject/noc path: /tests/models/test_0009_get_json_path.py
# ----------------------------------------------------------------------
# Test .get_json_path() method
# ----------------------------------------------------------------------
# Copyright (C) 2007-2020 The NOC Project
# See LICENSE fo... | code_fim | medium | {
"lang": "python",
"repo": "nocproject/noc",
"path": "/tests/models/test_0009_get_json_path.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|>
UNDERSCORE_RE = re.compile(r'''
^
_{5,}
\s*
$
''', re.VERBOSE)
### Paragraph Identification ###
def is_reply_lines(lines):
reply_lines = 0
empty_lines = 0
for line in lines:
if len(line.strip()) == 0:
empty_lines += 1
elif line.strip()[0] in ... | code_fim | hard | {
"lang": "python",
"repo": "xwyangjshb/recodoc2",
"path": "/recodoc2/apps/codeutil/reply_element.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> text = su.merge_lines(lines, False).strip()
return (WROTE_RE.match(text) is not None, 1.0)
def is_rest_reply(lines):
#print('Considering stop: {0}'.format(lines))
is_stop = False
for line in lines:
line = line.strip()
if ORIGIN_RE.match(line) or DASH_RE.match(line) or... | code_fim | hard | {
"lang": "python",
"repo": "xwyangjshb/recodoc2",
"path": "/recodoc2/apps/codeutil/reply_element.py",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: xwyangjshb/recodoc2 path: /recodoc2/apps/codeutil/reply_element.py
from __future__ import unicode_literals
import re
import docutil.str_util as su
### CONSTANTS ####
REPLY_LANGUAGE = 'r'
STOP_LANGUAGE = 's'
REPLY_START_CHARACTERS = set(['>'])
THRESHOLD_REPLY = 0.40
### REPLY REGEXES ###
WROT... | code_fim | hard | {
"lang": "python",
"repo": "xwyangjshb/recodoc2",
"path": "/recodoc2/apps/codeutil/reply_element.py",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> return new_im
def sem(im, axis=0): # pragma: no cover
r"""
Simulates an SEM image looking into the porous material.
Features are colored according to their depth into the image, so
darker features are further away.
Parameters
----------
im : array_like
ndarray ... | code_fim | hard | {
"lang": "python",
"repo": "PMEAL/porespy",
"path": "/porespy/visualization/_views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def xray(im, axis=0): # pragma: no cover
r"""
Simulates an X-ray radiograph looking through the porous material.
The resulting image is colored according to the amount of attenuation an
X-ray would experience, so regions with more solid will appear darker.
Parameters
----------... | code_fim | hard | {
"lang": "python",
"repo": "PMEAL/porespy",
"path": "/porespy/visualization/_views.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: PMEAL/porespy path: /porespy/visualization/_views.py
import numpy as np
import scipy.ndimage as spim
import matplotlib.pyplot as plt
# from mpl_toolkits.mplot3d.art3d import Poly3DCollection
__all__ = [
'show_3D',
'show_planes',
'sem',
'xray',
]
def show_3D(im): # pragma: no ... | code_fim | hard | {
"lang": "python",
"repo": "PMEAL/porespy",
"path": "/porespy/visualization/_views.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> services["garminconnect"].update({"email": OPTIN, "password": OPTIN, "tokens": NO, "metadata": YES, "data":NO})
services["garminconnect2"].update({"email": OPTIN, "password": OPTIN, "tokens": NO, "metadata": YES, "data":CACHED})
services["strava"].update({"email": NO, "password": NO, "tokens... | code_fim | medium | {
"lang": "python",
"repo": "cpfair/tapiriik",
"path": "/tapiriik/web/views/privacy.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: cpfair/tapiriik path: /tapiriik/web/views/privacy.py
from django.shortcuts import render
from tapiriik.services import Service
from tapiriik.settings import WITHDRAWN_SERVICES, SOFT_LAUNCH_SERVICES
from tapiriik.auth import User
import itertools
def privacy(request):
OPTIN = "<span ... | code_fim | medium | {
"lang": "python",
"repo": "cpfair/tapiriik",
"path": "/tapiriik/web/views/privacy.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: fendaq/Text_Annotation path: /demo.py
from Text_Annotation import Data_process, train, annotate
import pickle
import os
DIR = os.path.dirname(os.path.abspath(__file__))
params = {
'num_units': 128,
'num_layers': 2,
'num_tags': 5
}
<|fim_suffix|>annotate(model_path=DIR + '/model/',
... | code_fim | hard | {
"lang": "python",
"repo": "fendaq/Text_Annotation",
"path": "/demo.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>train(x=texts_seq,
y=target,
num_words=data_process.num_words,
batchsize=64,
epoch=1,
max_seq_len=data_process.max_seq_len,
**params)
annotate(model_path=DIR + '/model/',
data_process_path=DIR + '/model/data_process.pkl',
**params)<|fim_prefix|># repo... | code_fim | hard | {
"lang": "python",
"repo": "fendaq/Text_Annotation",
"path": "/demo.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> def config_bfd_on_vsrx(
self,
src_vm=None,
dst_vm=None,
target_ip=None,
gw_ip=None,
lo_ip=None):
'''
Pass BFD config to the vSRX
'''
cmdList = []
cmdList.extend(('set system arp aging-timer... | code_fim | hard | {
"lang": "python",
"repo": "sarath0/tf-test",
"path": "/common/maciplearning/base.py",
"mode": "spm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: sarath0/tf-test path: /common/maciplearning/base.py
from builtins import range
import re
import time
from common.base import GenericTestBase
from common.connections import ContrailConnections
from common import isolated_creds
from vm_test import VMFixture
from vn_test import VNFixture
from tcutil... | code_fim | hard | {
"lang": "python",
"repo": "sarath0/tf-test",
"path": "/common/maciplearning/base.py",
"mode": "psm",
"license": "Apache-2.0",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: vshulyak/ts-eval path: /tests/viz/test_data_containers.py
import numpy as np
import pytest
from ts_eval.viz.data_containers import xr_2d_factory, xr_3d_factory
from ts_eval.viz.utils import time_align
"""
xarray format checks
"""
def test_xr_2d_factory__xarray_fmt(dataset_2d):
xarr = xr... | code_fim | medium | {
"lang": "python",
"repo": "vshulyak/ts-eval",
"path": "/tests/viz/test_data_containers.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # 3d array => 2d array
with pytest.raises(AssertionError):
xr_2d_factory(dataset_3d)
def test_xr_3d_factory__nan(dataset_3d):
dataset_3d = dataset_3d.copy()
dataset_3d[:] = np.nan
with pytest.raises(AssertionError):
xr_3d_factory(dataset_3d)
def test_xr_3d_factory_... | code_fim | hard | {
"lang": "python",
"repo": "vshulyak/ts-eval",
"path": "/tests/viz/test_data_containers.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|>
def test_xr_2d_factory__shape(dataset_3d):
# 3d array => 2d array
with pytest.raises(AssertionError):
xr_2d_factory(dataset_3d)
def test_xr_3d_factory__nan(dataset_3d):
dataset_3d = dataset_3d.copy()
dataset_3d[:] = np.nan
with pytest.raises(AssertionError):
xr_3d_... | code_fim | hard | {
"lang": "python",
"repo": "vshulyak/ts-eval",
"path": "/tests/viz/test_data_containers.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: gen4438/vtk-python-stubs path: /typings/vtkmodules/vtkFiltersSources/vtkOutlineSource.pyi
"""
This type stub file was generated by pyright.
"""
import vtkmodules.vtkCommonExecutionModel as __vtkmodules_vtkCommonExecutionModel
class vtkOutlineSource(__vtkmodules_vtkCommonExecutionModel.vtkPolyDa... | code_fim | hard | {
"lang": "python",
"repo": "gen4438/vtk-python-stubs",
"path": "/typings/vtkmodules/vtkFiltersSources/vtkOutlineSource.pyi",
"mode": "psm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_suffix|> def SetBoxType(self, p_int):
"""
V.SetBoxType(int)
C++: virtual void SetBoxType(int _arg)
Set box type to AxisAligned (default) or Oriented. Use the method
SetBounds() with AxisAligned mode, and SetCorners() with Oriented
mode.
"""
... | code_fim | hard | {
"lang": "python",
"repo": "gen4438/vtk-python-stubs",
"path": "/typings/vtkmodules/vtkFiltersSources/vtkOutlineSource.pyi",
"mode": "spm",
"license": "BSD-3-Clause",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: Mohit-2007/issue-reporter path: /reporter/migrations/0008_auto_20200910_0950.py
# Generated by Django 3.1.1 on 2020-09-10 04:20
from django.db import migrations, models
<|fim_suffix|> operations = [
migrations.AlterModelOptions(
name='report',
options={'orderi... | code_fim | medium | {
"lang": "python",
"repo": "Mohit-2007/issue-reporter",
"path": "/reporter/migrations/0008_auto_20200910_0950.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> dependencies = [
('reporter', '0007_vote'),
]
operations = [
migrations.AlterModelOptions(
name='report',
options={'ordering': ['-timestamp']},
),
migrations.AddField(
model_name='report',
name='cr_line',
... | code_fim | medium | {
"lang": "python",
"repo": "Mohit-2007/issue-reporter",
"path": "/reporter/migrations/0008_auto_20200910_0950.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: H2020-newTRENDs/FLEX path: /dash_visualization/dash_figures.py
ear in years]
fig = CountryResultPlots(countries=countries, years=year_list, project_prefix=main.PROJECT_PREFIX).plotly_EU27_shifted_electricity()
return html.Div(dcc.Graph(figure=fig), id=ids.EU27_SHIFTED_ELECTRICITY)... | code_fim | hard | {
"lang": "python",
"repo": "H2020-newTRENDs/FLEX",
"path": "/dash_visualization/dash_figures.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: H2020-newTRENDs/FLEX path: /dash_visualization/dash_figures.py
ds.EU27_LOAD_FACTOR_CHART)
def EU27_pv_self_consumption(app: Dash) -> html.Div:
@app.callback(Output(ids.EU27_PV_SELF_CONSUMPTION, "children"),
Input(ids.ALL_COUNTRIES_DROP_DOWN, "value"),
Inp... | code_fim | hard | {
"lang": "python",
"repo": "H2020-newTRENDs/FLEX",
"path": "/dash_visualization/dash_figures.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> return html.Div(id=ids.SHARE_HEATING_STORAGE)
def share_pv(app: Dash) -> html.Div:
@app.callback(Output(ids.SHARE_PV, "children"),
Input(ids.COUNTRY_BUILDING_NUMBER_DROP_DOWN, "value"))
def update_figure(country: str):
big_df = pd.DataFrame()
for year in mai... | code_fim | hard | {
"lang": "python",
"repo": "H2020-newTRENDs/FLEX",
"path": "/dash_visualization/dash_figures.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # 判断左右是否靠近墙,取中间部分，然后再判断左右两边是否有blackwall (超过wall_factor比率是墙可以认为靠近墙)
img_width = ori_img.shape[1]
img_height = ori_img.shape[0]
thresh_hold = wall_factor*img_height*img_width/4
up_left_part = ori_img[int(0.20*img_height):int(0.65*img_height), 0:img_width/2, :]
up_right_part = or... | code_fim | hard | {
"lang": "python",
"repo": "YingshuLu/AI-Formula-Racing",
"path": "/auto_drive/rule_drive/TrafficSignType.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: YingshuLu/AI-Formula-Racing path: /auto_drive/rule_drive/TrafficSignType.py
pixel_count = len(rgwall_nonzero_index)
#print black_pixel_count, rg_pixel_count
average_x = 0
if black_pixel_count>rg_pixel_count and black_pixel_count>thresh_hold:
average_x = blackwall_nonzero_inde... | code_fim | hard | {
"lang": "python",
"repo": "YingshuLu/AI-Formula-Racing",
"path": "/auto_drive/rule_drive/TrafficSignType.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> # first find the region that has at least 120 red pixels
# choose the one in the medium if there are three, otherwise, choose the one has largest pixels
traffic_sign_img_list = []
largest_pixels_count = 3000
largest_pixels_sign_img = None
sign_img_to_check =... | code_fim | hard | {
"lang": "python",
"repo": "YingshuLu/AI-Formula-Racing",
"path": "/auto_drive/rule_drive/TrafficSignType.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_suffix|> while self.connections:
await asyncio.sleep(0.1)
async def _run(self):
for sock in self.sockets:
self.servers.append(await serve(
sock=sock,
connections=self.connections,
**self._server_settings
... | code_fim | hard | {
"lang": "python",
"repo": "jeamland/guvnor",
"path": "/guvnor/sanic_worker.py",
"mode": "spm",
"license": "MIT",
"source": "the-stack-v2"
} |
<|fim_prefix|># repo: jeamland/guvnor path: /guvnor/sanic_worker.py
import os
import sys
import signal
import asyncio
import logging
try:
import ssl
except ImportError:
ssl = None
try:
import uvloop
asyncio.set_event_loop_policy(uvloop.EventLoopPolicy())
except ImportError:
pass
import gunicorn.w... | code_fim | hard | {
"lang": "python",
"repo": "jeamland/guvnor",
"path": "/guvnor/sanic_worker.py",
"mode": "psm",
"license": "MIT",
"source": "the-stack-v2"
} |
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