sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
db213a6e28f6be3fa096cc2f4622df369cdcb6d6f437ab0577e7b1393d4011f5 | Python | 1,304 | 42 | #!/usr/bin/env python
"""Parse job info from sacct. The output is two lines - the header row and the
job info row with the largest MaxRSS value.
"""
import argparse
from common import fileopen, parse_profile, parse_size
import csv
from subprocess import check_output
def main():
parser = argparse.ArgumentParser()
... |
f4e3e1b2aea1533b080e970dff2b4344d880f5167564705a165e5a4642ff41c9 | Python | 1,304 | 50 | import sys
sys.path.append('.')
import time
from StimulationSystem.VtkinterProcess.VtkinterThread import VtkinterThread
from CommonSystem.Config import Config
from StimulationSystem.stimulationOperator import stimulationOperator
from StimulationSystem.ApplicationProcess.AppController import AppController
from... |
452d14f321add6c9aadb47312ea72c512008f838648ff5bbad6cfe23020c5dbf | Python | 1,306 | 37 | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
# Created by Roberto Preste
from mtoolnote.human import HumanAnnotator
from mtoolnote.nonhuman import NonHumanAnnotator
def annotate(input_vcf: str, output_vcf: str, species: str = "human",
csv: bool = False,
crossref: bool = True, predict: bool ... |
c764a0513d736043e89347fef69193508690612ea6c15a669b3420f833fb5cab | Python | 1,307 | 40 | # Copyright 2018-2025 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
de16b94d461919bf3cd0c47dd27cfffb8cbf6eb14e9a21a0a205e2cf390b7400 | Python | 1,307 | 47 | import os
import sys
import numpy as np
import pandas as pd
import scipy.io as spio
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap
data_fname = '' # BSDS model statematch results path
ofname = '' # figure output file name
data = spio.loadmat(data_fname)
co... |
9389e61dbd4a323ae4056e6e00e5ec940ee900d344214d4af01d2d23a6261566 | Python | 1,308 | 41 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
class TestRepeat:
def test_repeat(self):
ser = pd.Series(
np.random.default_rng(2).standard_normal(3), index=["a", "b", "c"]
)
reps = ser.repeat(5)
exp = pd.Series(ser.values.repeat(5), ... |
e4f967f8b952cdb4d03881ce187f02005b46e5221fd193cdff165b1b86495fad | Python | 1,308 | 26 | # Copyright 2019 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://w... |
5ab70d91bddc51db9d70ff82b3db69ea74eaca1895a86f8cc5f3f3ad428ea776 | Python | 1,309 | 36 | """Add a colab badge and pip install to notebooks."""
import sys
from pathlib import Path
# the filename is the name of temp file created by jupytext, not an original notebook
file = Path(sys.argv[1])
# the temp filename for "iteratitive_sense_reconstruction.py" is like "iterative_sense_reconstruction-42_5f4kv.py"
ba... |
e5512a4e82ea9f19bd0270ffcae40bdeeecaaeea60566fc61e86100a46c5c42b | Python | 1,310 | 39 | # Copyright 2018-2025 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
375d2a959de138b911043ad2b5331a4dece35d0532a0477c5c7590eebc8aaa35 | Python | 1,311 | 47 | import os
import sys
import numpy as np
import pandas as pd
import scipy.io as spio
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap
data_fname = '' # BSDS model statematch results path
ofname = '' # figure output file name
data = spio.loadmat(data_fname)
cl... |
658f5c9c20ae449dd50c0d70a104030dc5c46043e8f5a13d5e3daf5083e9b827 | Python | 1,311 | 40 | import shutil
import tempfile
import time
from PyQt6 import QtCore
TMPDIR = tempfile.mkdtemp(prefix=time.strftime(
"shapeout2_test_%H.%M_"))
pytest_plugins = ["pytest-qt"]
def pytest_configure(config):
"""This is ran before all tests"""
# disable update checking
QtCore.QCoreApplication.setOrganiza... |
b6e60f441009faf152dc996989be10464c40a7b32970d8ff8fd35489a059accf | Python | 1,311 | 45 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
from pandas.io.pytables import (
HDFStore,
read_hdf,
)
pytest.importorskip("tables")
class TestHDFStoreSubclass:
# GH 33748
def test_supported_for_subclass_dataframe(self, temp_h5_path):
data = {"a": [1, 2], "... |
f98c92efd89b9bcc2763d63ea074b6801118ba5df5555b7d0103c051bc1e15ce | Python | 1,311 | 36 | #%%
from pathlib import Path
from src.fs_roi_lut import read_rois
from src.paths import Paths
import pandas as pd
import nibabel as nib
import numpy as np
import shutil
#%% set paths
data_dir = Path(__file__).parent.parent.parent / 'data'
paths = Paths(data_dir / "paths.json")
worklist_file = data_dir / 'derivatives'... |
098eb08efdc5182c69c9fb1ee8c17134617deed383c3d9a3c932fbded468494f | Python | 1,313 | 32 | import sys, argparse
import pandas as pd
argparser = argparse.ArgumentParser(description='Generates naturalstoriesmaze.evmeasures data table.')
argparser.add_argument('f1', type=str, nargs=1, help='Path to itemmeasures data table')
args, unknown = argparser.parse_known_args()
def main():
data1 = pd.read_csv(sys.s... |
0c6cc12c1d0db4da5af1ea6b64d0d0f454c691c7c1adbf36eec786ed32e117fe | Python | 1,313 | 46 | from collections import deque
import gymnasium
import numpy as np
class FrameStack(gymnasium.Wrapper):
def __init__(self, env, k):
"""Stack k last frames.
Returns lazy array, which is much more memory efficient.
See Also
--------
baselines.common.atari_wrappers.LazyFrame... |
7f4d0dd5574419d384b8b503a70da8d6f2c89e551e47eae37ae5152f987d1f09 | Python | 1,314 | 43 | from pandas.core.arrays.arrow import ArrowExtensionArray
from pandas.core.arrays.base import (
ExtensionArray,
ExtensionOpsMixin,
ExtensionScalarOpsMixin,
)
from pandas.core.arrays.boolean import BooleanArray
from pandas.core.arrays.categorical import Categorical
from pandas.core.arrays.datetimes import Dat... |
bc9b513b98f19885c062fa3f69f869b60cc8b800fc84b345b4a69042035de610 | Python | 1,314 | 41 | # Copyright 2024 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agre... |
66604231e0d8a73b91c7763c25296a838042a07ff1c21a92b77ab355604ec3a6 | Python | 1,315 | 56 | #!/usr/bin/env python3
# JN 2015-06-08
"""
mark all clusters in a channel as artifacts
"""
from __future__ import print_function, division
import os
import tables
from combinato import TYPE_ART, TYPE_NO
def make_artifact(h5fname):
"""
mark the artifacts
"""
print('Setting all classes in {} to Artifac... |
728b981232f164375d535a04c3bb18edf6d3bac1ebd2c5c3e56016d1103d8405 | Python | 1,315 | 28 | # Copyright 2018-2021 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
81b18462f71962b82edda05e4b99a3df59a4ffda60e3e459267f6bd5094afa26 | Python | 1,315 | 42 | import sys, argparse
argparser = argparse.ArgumentParser('''
Outputs sentences from line-separated RT tokens and a target sentence tokenization.
''')
argparser.add_argument('targ_sents_file', action='store', nargs=1, help='Target sentence tokenization file')
argparser.add_argument('-w', '--word', dest='w', action='sto... |
0f9da8b1900712e636c3719dcc7d39cbd583fe084b2324a07ca6882699cb640c | Python | 1,316 | 36 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
from pandas.core.construction import sanitize_array
@pytest.mark.parametrize(
"values, dtype, expected",
[
([1, 2, 3], None, np.array([1, 2, 3], dtype=np.int64)),
(np.array([1, 2, 3]), None, np.array([1, 2, 3]))... |
3242aebefded92e1fcedc3fea2092c2c96d2a7f3d7bc552be42a25c33b27e018 | Python | 1,316 | 38 | import sys
roi_mapping = {
"Lang_LH_AngG": "LangLAngG",
"Lang_LH_AntTemp": "LangLAntTemp",
"Lang_LH_IFG": "LangLIFG",
"Lang_LH_IFGorb": "LangLIFGorb",
"Lang_LH_MFG": "LangLMFG",
"Lang_LH_PostTemp": "LangLPostTemp",
"MD_LH_antParietal": "MDlanglocLAntPar",
"MD_LH_insula": "MDlanglocLInsu... |
8197fd9e7d32793d50107dc51b0c1ce43d8ce2d40004d4d6de5b5c7496c3f7cd | Python | 1,316 | 42 | from datetime import datetime
import sys
import enum
sys.path.append("..")
from app import db
class GenderEnum(enum.Enum):
male = 1
female = 2
undefined = 3
class HandEnum(enum.Enum):
left = 1
right = 2
ambidextrous = 3
undefined = 4
class RaceEnum(enum.Enum):
white_non_latino = 1
... |
d50600f5d617414d697e3ff6153820374331f1374f0315324d0bf21fdd4c3610 | Python | 1,316 | 41 | import numpy as np
import matplotlib.pyplot as plt
import argparse
import os.path
def read_logs(filelist):
loaded_data = np.loadtxt(filelist[0])
X = np.zeros((loaded_data.shape[0], len(filelist)+1))
X[:, 0:2] = loaded_data
var_names = [os.path.basename(filelist[0])]
for i, file in enumerate(filelis... |
3c6c9134e1adffb5bfa72ae8293bc31d1b46c17ae73281a8717ee37578181f6d | Python | 1,318 | 34 | from aigarmic.process_plate_image import find_threshold_value, split_by_grid
from tests.conftest import plates_images_paths
import cv2 # pylint: disable=import-error
import pytest
@pytest.mark.assets_required
def test_find_threshold_value(plates_images_paths, growth_image):
# successfully find a valid threshold ... |
c6063401d528a212a55a83e914bb2bd26ecd1a739c2bdaf97d81b50080e509a9 | Python | 1,318 | 48 | """DatasourceDriver factory.
Resolves a driver by ``DataSource.kind``. Drivers register themselves
here so adding a new backend is a single new import + ``register()``
call.
"""
from __future__ import annotations
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from pycaret_server.datasources.base import Data... |
6810cf9ea07983061b7a6408cf4c6b10c37e30b62a2705a3ba13effec06c1126 | Python | 1,319 | 53 | from datetime import datetime
import pytest
import pandas as pd
import pandas._testing as tm
class TestDatetimeIndexOps:
def test_infer_freq(self, freq_sample):
# GH 11018
idx = pd.date_range(
"2011-01-01 09:00:00", freq=freq_sample, periods=10, unit="ns"
)
result = p... |
da3328f9de82fb21d0309882df36cfd513b97a65831d17e6916733d9b41dc79f | Python | 1,319 | 53 | # -*- coding: utf-8 -*-
from importlib.metadata import PackageNotFoundError, version
try:
__version__ = version("emcee")
except PackageNotFoundError:
__version__ = "unknown version"
# General stuff
extensions = [
"sphinx.ext.autodoc",
"sphinx.ext.intersphinx",
"sphinx.ext.napoleon",
"sphinx.... |
93764fd2e4f9fe5183e4eb6088a5570bc2b8973e3d2d3552b677882d5fda496e | Python | 1,321 | 35 | import torch
def add_edges(edge_index, new_edge_index, num_nodes):
# Adjacency matrix of the original graph
A = torch.zeros((num_nodes, num_nodes), dtype=torch.bool, device=edge_index.device)
A[edge_index.split(1)] = True
# Add the new edges to adjacency matrix
A[new_edge_index.split(1)] = True
... |
9ea1b5f6037db52ae649336ebcbab965bf0708dcd4203615d8c50ca9b1d3511d | Python | 1,322 | 33 | import os, sys
import apnet
import pickle
import argparse
import numpy as np
from atom_model import AtomModel
from pair_model import PairModel
parser = argparse.ArgumentParser(description='Train single model with provided train and test set')
# Mandatory arguments
parser.add_argument('training_path', help='[string] P... |
d98134c56ffdfd9a502859e299be672b97de5077417fa0e599c5f6408c9715aa | Python | 1,322 | 34 | #if an unannotated region neighbors two regions with the same annotation, then it should also have that annotation
def check_previous_next(file_path):
lines = []
with open(file_path, 'r') as file:
lines = file.readlines()
outputfile.write(lines[0])
for i in range(1, len(lines) - 1):
#e... |
dce7d60fc9a9168bb9c0325dc1fe2eb7bde188dd3da1a22d52a4727c4d8bf591 | Python | 1,322 | 37 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
class TestValues:
@pytest.mark.parametrize(
"data",
[
pd.period_range("2000", periods=4),
pd.IntervalIndex.from_breaks([1, 2, 3, 4]),
],
)
def test_values_object_extension_dty... |
2c5ce6903361f151b3a3205f8e0fdf256785c46c74184c970b7c92ff87d62af9 | Python | 1,323 | 42 | # Copyright 2018-2023 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
9305ce4fa120b27436ec56b59ffb794f629f650d7c43476cbb5bf5653ae20482 | Python | 1,323 | 43 | from setuptools import setup
from setuptools import find_packages
with open("README.md", "r") as f:
long_description = f.read()
setup(
name="neuroxai",
version="0.1",
description="Interpretability Callbacks for Tensorflow 2.0",
long_description=long_description,
long_description_content_type=... |
10c1557ea8f040f01a58fe646ce35f9909442fb118f1386defca2f73a79e14e9 | Python | 1,325 | 44 | import sys, os, re, collections
sys.path.append(os.path.join(os.path.dirname(__file__), '..', '..', 'resource-gcg', 'scripts'))
import tree
for line in sys.stdin:
Q = [ ]
f = 0
j = 0
p = ''
w = ''
def calccontext ( tr, s=1, d=0 ):
global Q, f, j, p, w
#### at preterminal node...
if len(tr.ch)... |
14987b19df3ae910b9ef5914792b34f843500018f4d85122a99901dade65ff3d | Python | 1,325 | 37 | from CommonSystem.MessageReceiver.EventManager import Event
import time
def operate_fcn(message_queue, event_manager, stop):
while True:
if message_queue.qsize() > 0:
message = message_queue.get()
if len(message) > 4:
event = Event(type_=message[0:4])
... |
a3d59e94552d781859214af998bfb50c584c678952da1a69359498f0b381b4ae | Python | 1,325 | 48 | """Removes regional indicators from a font."""
from fontTools import subset
from fontTools import ttLib
import functools
from pathlib import Path
import sys
from typing import Set
def codepoints(font: ttLib.TTFont) -> Set[int]:
unicode_cmaps = (t.cmap.keys() for t in font['cmap'].tables if t.isUnicode())
ret... |
aed43e48fb103a4b1c9ecf922640f8555c93353800207f6923a7ba4de2ddaad2 | Python | 1,325 | 48 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
class TestPeriodRepresentation:
"""
Wish to match NumPy units
"""
@pytest.mark.parametrize(
"freq, base_date",
[
("W-THU", "1970-01-01"),
("D", "1970-01-01"),
("B", "... |
d8c6920407d476fba84535b03b5c6c006a990a1021e3325a2925954a19eac7ee | Python | 1,326 | 42 | txt_file = '../string/preprocessed/shk148.txt'
inp = txt_file
ofile = 'string_vec_partial.txt'
#train
import logging
import os.path
import sys
import multiprocessing
import time
from gensim.corpora import WikiCorpus
from gensim.models import Word2Vec
from gensim.models import Phrases
from gensim.models... |
1d7a004ddfab56c19c0f672429e80048f74e9fb6070dd660ae4d0d6200c7b12d | Python | 1,327 | 53 | """Screenshots for quick guide R-lme4"""
import pathlib
import sys
from PyQt6 import QtCore
from PyQt6.QtWidgets import QApplication
from shapeout2.gui.main import ShapeOut2
from shapeout2.gui import compute
test_data = pathlib.Path(__file__).parent / ".." / ".." / "tests" / "data"
app = QApplication(sys.argv)
QtC... |
8e0ea864df0ce1450ef5f40ecd0bafdf3f23628bb633bb0f13186acaf309c980 | Python | 1,327 | 37 | # Copyright 2018-2025 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
65d0fa50166ecfbf0f64204a06ac26e6e500bd34f752ca165773d33f33a419db | Python | 1,328 | 48 | import sys
import glob
import pandas as pd
import numpy as np
import h5py
file_list = sys.argv[2:]
print(file_list)
LABEL = 'cell.type'
total_data = pd.DataFrame()
for ff in file_list:
data = pd.read_csv(ff, sep='\t', index_col=0)
total_data = total_data.append(data)
print(total_data.shape)
gene_anno = ... |
879fc48178357a2a8e86f17329bfce2b0c79711585b8247bdbdacdc5572b47b7 | Python | 1,331 | 37 | """End-to-end test for scripts/hyper-sweep/run_single_job.py.
Downloads the real, ~1MB `paninski-lab/mirror-mouse-tiny` test-fixture dataset from
HuggingFace and runs a tiny (`--debug`) training job through it, checking that the whole
pipeline -- dataset download/extraction, `litpose train`, and checkpoint cleanup -- ... |
fcee8ec7d93f2310f2c225e30f8e320dbc173cb6f7da338fed239ecd689d2fba | Python | 1,331 | 41 | # Copyright 2018-2023 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
199efb47706d89c0e4111531d373d5525f471135908f6300ff71e457806318b5 | Python | 1,332 | 41 | from msmfcode.core.config import *
from msmfcode.evaluation.plot import plot_optimization_results_3d, plot_optimization_results_3d_sequential
from msmfcode.models.cann import DMSMF, FMSMF
import plotly.io as pio
pio.renderers.default = 'browser'
# Config
plot_sequentially = False
net = FMSMF
experiment_nums = [15]
... |
da9eda16bb48a1464dcb07749264891dfe63e7cee6f84ce6c459151a09592758 | Python | 1,332 | 32 | import numpy as np
class SelfPlayManager:
def __init__(self, config, writter):
self.config = config
self.writter = writter
self.update_score = self.config['update_score']
self.games_to_check = self.config['games_to_check']
self.check_scores = self.config.get('check_scores', ... |
7d92581e8522fa609271b732fa63942e2b5ed86595eaf7f73e1de97761d182cb | Python | 1,333 | 39 | from . import dm_element
class MatrixElement(dm_element.MatrixElement):
def mousePressEvent(self, event):
# toggle selection
if not self.invalid:
self.active = not self.active
self.element_changed.emit()
self.update_content()
event.accept()
def ... |
9c33b5574618d1702cf4961851d0f95e7d91b9032a376e508c449095f8659403 | Python | 1,333 | 44 | def main(splash=True):
import importlib.resources
import sys
from PyQt6.QtWidgets import QApplication
from PyQt6.QtCore import QEventLoop
# import before creating application
import pyqtgraph # noqa: F401
app = QApplication(sys.argv)
if splash:
from PyQt6.QtWidgets import QSp... |
5b57325004c1ec6f2c74a8bbbc716d87aa33cf779d615f4c601367aff02a9ba3 | Python | 1,334 | 37 | # Copyright 2026 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agre... |
0663e5d78dab9e5fc64c1b11474bf5d3914650a6b3e039ee7ab765d63a8e4373 | Python | 1,336 | 53 | """
ipython analogue:
tr = TimeResolution()
mi = pd.MultiIndex.from_product(tr.params[:-1] + ([str(x) for x in tr.params[-1]],))
df = pd.DataFrame(np.nan, index=mi, columns=["mean", "stdev"])
for unit in tr.params[0]:
for size in tr.params[1]:
for tz in tr.params[2]:
tr.setup(unit, size, tz)
... |
0bd03c465f7b9cdd74e914747931d6cc91f54b7fe0ffea47685dc2903d5379f6 | Python | 1,336 | 27 | #
# Copyright (c) 2020 Gabriel Nogueira (Talendar)
# Copyright (c) 2023 Martin Kubovcik
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the... |
5e5d40e9ac05c090e3f62170cba395fdcc0a6b63b95706a56f2fcccb7cae5c0e | Python | 1,336 | 47 | #! /usr/bin/env python
##############################################################################
## DendroPy Phylogenetic Computing Library.
##
## Copyright 2010-2015 Jeet Sukumaran and Mark T. Holder.
## All rights reserved.
##
## See "LICENSE.rst" for terms and conditions of usage.
##
## If you use this wo... |
5e6b8a77abcb600328a74dad6439094ae30036f926f0699ecdd2ebe93701ce21 | Python | 1,336 | 47 | import inspect
import logging
import os
import sys
class SingleLevelFilter(logging.Filter):
def __init__(self, passlevel, reject):
super().__init__()
self.passlevel = passlevel
self.reject = reject
def filter(self, record):
if self.reject:
return record.levelno != ... |
9e0d33c22fb3982924f9c2544b42712bfe2ebbffa5ac4126f1e669ce731c89c7 | Python | 1,336 | 31 | # from cellPLATO.cellPLATO.initialization.config_trackmate import *
from initialization.config import *
from initialization.initialization import *
from data_processing.cell_identifier import *
from data_processing.cleaning_formatting_filtering import *
from data_processing.clustering import *
from data_processing.dat... |
dc54657f1ed0c777ef6915b79fd74c2c7abe90826fa4bfa159dc4236fdbb1d72 | Python | 1,336 | 36 | # Code taken from post by Stack Overflow user alex.forencich (https://stackoverflow.com/users/839411/alex-forencich)
import sys
from os.path import basename
try:
from StringIO import StringIO
except ImportError:
from io import StringIO
from docutils.parsers.rst import Directive
from docutils import nodes, st... |
024f74e9820f70782e7752ae30779a8894f96af342b3b68cd1b9ef9a35c7b1d5 | Python | 1,337 | 43 | #! /usr/bin/env python
##############################################################################
## DendroPy Phylogenetic Computing Library.
##
## Copyright 2010-2015 Jeet Sukumaran and Mark T. Holder.
## All rights reserved.
##
## See "LICENSE.rst" for terms and conditions of usage.
##
## If you use this wo... |
19ba493728f634ce7da56ad6d744335d4a8d04784c44e00982eebf48e17850ea | Python | 1,337 | 43 | import numpy
import pandas as pd
def updateNames(nameList, dictionary):
for i in range(len(nameList)):
if nameList[i] in dictionary:
nameList[i] = dictionary[nameList[i]]
return nameList
#%%
stimName = 'LPS'
control = 'PBS-BSA'
metaData = pd.read_csv('filtered/metaData.tsv', sep='\t')
met... |
9ace921080e8351afbbfae9b6e90d78b859e80ea1c529609479b95ec653c3d8e | Python | 1,337 | 24 | import sys
import re
#remove F model features where antecedent is null and k is a pronoun k such as f[01]&Top?&X-xX:he_1
#he, him, his, she, her, they, them, their, its
#multiple models for different subtypes of coreference?
#example F model line - "F <comma-sepfeatvals> : fresponse = count
#F d0&tT=1,d0&&Top&=1,acor... |
6cc8600ec68e98479e944f7b6239df5b0370833592c4b5e9506d2b5e16ddb238 | Python | 1,339 | 34 | from setuptools import setup, find_packages
import treeshrink
param = {
'name': treeshrink.PROGRAM_NAME,
'version': treeshrink.PROGRAM_VERSION,
'description': treeshrink.PROGRAM_DESCRIPTION,
'author': treeshrink.PROGRAM_AUTHOR,
'url': treeshrink.PROGRAM_WEBSITE,
'license': treeshrink.PROGRAM_LI... |
37941b57e675fb9a7184df81af29e9c82107374fa716e36b75fad009877adb3e | Python | 1,340 | 39 | import pandas as pd
def _format_test_results(
result: pd.DataFrame, test: str, test_name: str
) -> pd.DataFrame:
"""Formats the results of a test into a multiindex dataframe with first
level = "test" and second level = "name". The final dataframe has a column
called value corresponding to the "name"
... |
d9bb938d75eb3dbde030af182e00282d63b518fbc04edf67db9c9675aacd28ff | Python | 1,340 | 41 | import pytest
import tempfile
import yaml
from sklearn.dummy import DummyRegressor
from src.model_builder import ModelBuilder, ModelRepresentation
from src.test_config import model_config
def test_model_representation():
name = 'dummy'
model = DummyRegressor(strategy='mean')
paramgrid = {'C': [0.1, 1.0, 1... |
66a3449dad8480d820c8992b0852154ead191e61efb49d199306431a37a087f5 | Python | 1,343 | 50 | import sys
import rdkit
from argparse import ArgumentParser
from rdkit import Chem, DataStructs
from rdkit.Chem import AllChem
import pandas as pd
pred_mols = pd.read_csv('',
header=None).values.reshape(-1)
ref_path = 'actives.txt'
with open(ref_path) as f:
next(f)
true_mols = [line.... |
e6c3da38c2b74ef94ef2f10a090e8737a3bff7cb3b7c33a7ff5cc63e0f8ed5ec | Python | 1,343 | 36 | # -------------------------------------------------------------------------------------------------------------------------------------
# Following code curated for GCPNet (https://github.com/BioinfoMachineLearning/GCPNet):
# ----------------------------------------------------------------------------------------------... |
20dfd33f9d866fa0566db78334154999e1f2f32f83cb1ca581a09f7d78ade478 | Python | 1,346 | 33 | class TestIteration:
def test_keys(self, datetime_series):
assert datetime_series.keys() is datetime_series.index
def test_iter_datetimes(self, datetime_series):
for i, val in enumerate(datetime_series):
assert val == datetime_series.iloc[i]
def test_iter_strings(self, string_s... |
4aaa03e5dd714b38fd98c6514aa545c58c3e505e459bf0df8582062684d2e663 | Python | 1,347 | 39 | """
.. module:: ui_imgui
:platform: Linux, Windows
:synopsis: Helper functions for ImGui styling, etc.
.. moduleauthor:: Fredrik Nysjo
"""
import imgui
def set_style_color_rgb(idx, r, g, b):
"""Update global ImGui style color without changing alpha"""
style = imgui.get_style()
tmp = style.colors[... |
9f006181ebd94836a6702a0235a8b9d0586a4e7beb37e749b003e2d73f4aa307 | Python | 1,347 | 38 | from CommonSystem.MessageReceiver.EventManager import Event
import time
import json
def operate_fcn(message_queue, event_manager, stop):
while True:
if message_queue.qsize() > 0:
message = message_queue.get()
if len(message) > 4:
event = Event(type_=messag... |
d7ee6f4a8a725e486ef673594e94a463c358eb93db98b98b4467a071faea91f7 | Python | 1,347 | 52 | import numpy as np
def pandas_collumn_to_numpy_array(pandas_series):
new_array = []
for i in range(len(pandas_series)):
element = pandas_series.iloc[i]
if len(np.shape(element)) == 0:
new_array.append(element)
else:
new_array.extend(element)
return np.array... |
bbc0714108e49fc7fcb10ec82e531421d3e933fe73344d026dd6758393bdc2bd | Python | 1,348 | 49 | import pytest
import pandas as pd
import pandas._testing as tm
def test_take_validate_axis():
# GH#51022
ser = pd.Series([-1, 5, 6, 2, 4])
msg = "No axis named foo for object type Series"
with pytest.raises(ValueError, match=msg):
ser.take([1, 2], axis="foo")
def test_take():
ser = pd.... |
ec080f4bc20254a20efa5b2dae7cca3cdd657d008cfa328b4f0b310c0738f307 | Python | 1,351 | 33 | # Copyright 2019 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://w... |
0502a5057382e0bb177bb793d822b9991191ff6e60f6a63291067aa23a068db1 | Python | 1,352 | 40 | import numpy as np
import pytest
from pandas._libs.tslibs import fields
import pandas._testing as tm
@pytest.fixture
def dtindex():
dtindex = np.arange(5, dtype=np.int64) * 10**9 * 3600 * 24 * 32
dtindex.flags.writeable = False
return dtindex
def test_get_date_name_field_readonly(dtindex):
# https... |
7b5d51e1d33bd9dcafe94557c5b03c937ae94fa525b03a417f1ad8a8e3993789 | Python | 1,352 | 43 | # Copyright 2026 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agre... |
84abf87c18eef54a6018845a93e29ff872cbfbbead49474bf2938c67000c4dff | Python | 1,352 | 42 | import pathlib
from PyQt6 import QtCore, QtWidgets
def get_directory(
parent: QtWidgets.QWidget,
identifier: str,
caption: str = "Select directory",
force_dialog: bool = True,
):
"""Retrieve the path for a given identifier
When called for the first time, a directory dialog is... |
016c81e52168bd984475eef078634bcc22d461a0700bc50ef72db5bda7c17e73 | Python | 1,353 | 55 | # Copyright 2024 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agre... |
3482e398843a47a1d64d28f0868816f0874078d02a66db73d1d7bbfa7fbc67f0 | Python | 1,353 | 43 | import argparse
import os
import numpy as np
import pandas as pd
def get_args():
"""
Get arguments from command line with argparse.
"""
parser = argparse.ArgumentParser(
prog='GTDBTk-Organize.py',
description="""Grab all summary files from GTDB-Tk and merge.""")
parser.add_argument(... |
91ca2cfd17939c081a3a11bee0c29f4f88b8d22af7a6a6beddd80405a0fe93f4 | Python | 1,353 | 46 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from setuptools import setup, find_packages
with open('README.md') as readme_file:
readme = readme_file.read()
requirements = [
"tensorflow",
"numpy",
"matplotlib",
"seaborn",
"jupyter",
"scikit-learn==0.23.2",
#"brain-score @ git+https://git... |
a8747b9a1c6d75ece10d05002649b120633242953d74bfa2e73321bc3d93e470 | Python | 1,353 | 50 | import torch
from tnn.tensor_utils import modek_product
def facewise(A, B):
r"""
Batch multiply frontal slices of tensors (first two dimensions)
:param A: (n_1, p, n_3, ..., n_d) array
:type A: torch.Tensor
:param B: (p, n_2, n_3, ..., n_d) array
:type B: torch.Tensor
:return: (n_1, n_2, n... |
cb954432e5ed48a6a43349e2ca2fd9a69ed956e3dd0fb6b084a90dbb8cf76576 | Python | 1,353 | 72 | #####################################################################################################################
# Date created : 10/21/2022
# Date modified: 10/21/2022
# Purpose : This program calculates the volume and area of virtual convex hull formed by all-atoms in residues
###########################... |
08a0250a4d55f146a5d25811e692c66339519af55d085603a5ecd4a50bd920fa | Python | 1,354 | 64 | """
Reversed Operations not available in the stdlib operator module.
Defining these instead of using lambdas allows us to reference them by name.
"""
from __future__ import annotations
import operator
from typing import Any
def radd(left: Any, right: Any) -> Any:
return right + left
def rsub(left: Any, right:... |
21636f89c07c1cf6f28aeb7e9249a7e7bdd0fbf48adb5c844ab37d0d95f60fb8 | Python | 1,355 | 47 | from OperationSystem.AnalysisProcess.TestingProcess import TestingProcess
from OperationSystem.AnalysisProcess.WaitAnalysisProcess import WaitAnalysisProcess
class AnalysisController:
def __init__(self):
self.current_process = None
self.algorithm = None
self.actualWin = None
d... |
52c0f750b8dfdf87291eb5b966b3e7569b8210cb3c6be9fdda53d74491d87522 | Python | 1,355 | 44 | from torch import nn
import torch
import torchvision
"""pretrained models"""
class DualFC(nn.Module):
def __init__(
self, num_ftrs: int, num_classes: int, p: float = 0, is_dual: bool = True
) -> None:
super().__init__()
self.is_dual = is_dual
self.fc1 = nn.Linear(num_ftrs, nu... |
97b998752018130d262aa57a10c87413284f45a8158e401fcaa693f6e54cdf47 | Python | 1,355 | 32 | """
@author: mkowalska
"""
import os
import numpy as np
from figure_properties import *
from kCSD_with_reliability_map_2D import matrix_symmetrization
from reliability_map_2D import generate_reliability_map
if __name__ == '__main__':
path = os.path.join(os.path.expanduser('~'), 'Dropbox', 'kCSDrev-pics')
lar... |
e6a3f9ebd7946c660566a35a59f3ef27518c1b4fd9a387e7af80d33f34fe1ddd | Python | 1,355 | 42 | # Copyright 2026 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agre... |
5a81ab1eef3a54b70b10e0cd1bd997e15933836d38df7b042bc749aa3fdddb7b | Python | 1,356 | 41 | from setuptools import find_packages, setup
def read(path):
with open(path, 'r') as f:
return f.read()
setup(
name='dynast-release',
version='1.0.1',
url='https://github.com/aristoteleo/dynast-release',
author='Kyung Hoi (Joseph) Min',
author_email='phoenixter96@gmail.com',
descr... |
772476e6b14b3c35a4460711ba46cb85657a1cc59e531e12e72518e5bd2d240d | Python | 1,359 | 42 | #! /usr/bin/python3
# -*- coding: utf-8 -*-
# @FileName: config.py.py
# @Author: Li Chengxin
# @Time: 2023/6/30 22:12
# Global configuration variables. If you are not sure what these parameters are, please do not modify them,
# except for those marked with *
from __future__ import annotations
from typing import Li... |
86bdfc3b3e2dc57707519a70d988b9f310dc3594a48f4d4b0caa8b5b168ee191 | Python | 1,361 | 28 | # Guided Grad-CAM
from .grad_cam import get_grad_cam
from .guided_backprop import get_guided_backprop
from ..utils.process import get_last_conv_layer
import numpy as np
import tensorflow as tf
from tensorflow.keras.layers import Conv2D, Conv3D
from skimage.transform import resize # for N-dimensional images
def get_gu... |
896a81e9bfd1cb98ddffde0f5033da042e05d282af55e9de6aedc568df3ea047 | Python | 1,361 | 54 | import numpy as np
import pytest
import pandas as pd
@pytest.mark.parametrize(
"data, expected",
[
# empty
(pd.DataFrame(), True),
# multi-same
(pd.DataFrame({"A": [1, 2], "B": [1, 2]}), True),
# multi-object
(
pd.DataFrame(
{
... |
b7be41645083679a7d5f5c9d23e2a0e09744b90dfe898999714520743b39a1bd | Python | 1,361 | 40 | # -*- coding: utf-8 -*-
"""
Created on Thu Dec 16 17:09:27 2021
@author: Daniel Hulsey
this script is used to align a CCF to a multimodalmapping session. Points selected to align the ccf will be saved for future use.
"""
import os
from skimage import io
import uobrainflex.utils.image_utilities as im_util
imp... |
a80ae8294ca7e2a518b5343d5586a3eaade527d756a970457eea9de5cf01c1bc | Python | 1,362 | 62 | import pickle
import tree
import re
import sys
def readStrFromTree(f):
strDic = {}
for line in file(f):
t = tree.Tree()
t.read(line)
s = re.sub(" +", " ",t.leaf())
strDic[s]=line
return strDic
chtb = sys.argv[1]
devSent = readStrFromTree("genmodel/chgcg.same.dev.linetre... |
d48f1121826343b73ae6d360ab99d02e4b5ae889f4323e5501ec9f614d182c03 | Python | 1,362 | 37 | # Copyright 2026 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agre... |
dc038ff46496536f02307044836da78000806f8d63faeae6658ebb9e3226d769 | Python | 1,363 | 38 | import pandas as pd
import numpy as np
import os
import scipy.stats as st
def get_pvals(df_magma):
'''
usage: convert Z stats to p-values
'''
df_magma["P"] = 1-st.norm.cdf(df_magma["ZSTAT"]) # https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.norm.html
# subtracting an array from 1 g... |
ed7e9e1a532cdd15a79396c89bf6d902db484b9d6d1f1bd21553315d9182db9f | Python | 1,363 | 58 | from os import listdir
import re
def get_diff(last, new):
last_map = {}
new_map = {}
with open(last) as f:
lines = f.readlines()
headers = lines[0].split('\t')
last_content = lines[1].split('\t')
c = 0
while (c < len(headers)):
last_map[headers[c]] = last_content[c]
c+=1
with open(new) as f:
line... |
1e3e9f2f3dadaa7c288139e76fe33916c5794aa1a8e8252956486edf396a99a7 | Python | 1,365 | 62 | import numpy as np
from nilearn.connectome import vec_to_sym_matrix
from bct import modularity_louvain_und_sign
from math import sqrt
def louvain_modularity(vect):
"""
Wrapper for `modularity_louvain_und_sign` from the Brain Connectivity
tool box.
Parameters
----------
vect : np.ndarray
... |
b854f2d70aa637efdedfa3196509d15c0cc4b7e8da352a7994949c411ac54f3e | Python | 1,365 | 53 | # load our stimulus set, natural images, and white noise images
# useful packages:
import scipy
import scipy.io as sio
import os
from PIL import Image
import numpy as np
import matplotlib.pyplot as plt
import cv2
import pickle
# set random seed
np.random.seed(42)
# number of images
num_imgs = 2025
img_size = (224,22... |
a9fe4f1b708dae278136b072712f4f7feed8af07c7bdaa696a40644db7a3614d | Python | 1,366 | 46 | import pandas as pd
class TestIsLexsorted:
def test_is_lexsorted(self):
levels = [[0, 1], [0, 1, 2]]
index = pd.MultiIndex(
levels=levels, codes=[[0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 1, 2]]
)
assert index._is_lexsorted()
index = pd.MultiIndex(
levels=l... |
0bf23fdf60d2dce8dd4649d6975a11504c5970a2f807e567961ed7092342200c | Python | 1,367 | 51 | __author__ = 'etseng@pacb.com'
"""
Misc APIs for reading BED format
UCSC BED format:
https://genome.ucsc.edu/FAQ/FAQformat#format1
SimpleBED --- chr, 0-based start, 1-based end
"""
class SimpleBED(object):
def __init__(self, chrom, start, end, name=None):
self.chr = chrom
self.start = start
... |
97c547a0249cc0c02266c8bdacfb60b6e902641762319095e35984e51884891c | Python | 1,367 | 50 | import json
import numpy as np
import random
AUG_PARA = ['001001',
'001101',
'001201',
'001301',
'102001',
'102101',
'102201',
'102301',
'202001',
'202101',
'202201',
'202301',
... |
ca686d70841d6c81e18345715291deff98ea8e067dc55d829b848d73d0a3e1d8 | Python | 1,367 | 39 | # Copyright 2018-2024 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
8dbbf23aef96fd228cd5c1f61d649f4963c74df97a42075e714596edbf49bc97 | Python | 1,368 | 28 | import models.args
import os
def get_args():
parser = models.args.get_args()
parser.add_argument('--max-tokens', type=int, default=512,
help="Maximum number of tokens to use with BERT, max 512")
parser.add_argument('--lr', type=float, default=0.0001) # thesis 0.00001
parser.ad... |
2865188f5a529fc2f797ff6b00e42cefddbf314a31226cdd9d2cbd366638930d | Python | 1,371 | 36 | """Module contains statistical routines."""
from scipy import stats
import numpy as np
def compute_kde(data, mask, a1, a2, extents, res=100j):
"""Compute a 2D KDE."""
if extents is None:
xx, yy = np.mgrid[np.min(data.T[a1]) : np.max(data.T[a1]) : res, np.min(data.T[a2]) : np.max(data.T[a2]) : res]
... |
4d75185389e8c33ccb36a536c4b2dff85f56f4a3c2ae9eaf4c2e641026c19682 | Python | 1,371 | 53 | #from pymatgen import MPRester
from pymatgen.ext.matproj import MPRester
from pymatgen.io.cif import CifWriter
import csv
import sys
import os
print('start')
###need 2 files: csv containing materials project IDs and atom_init.json (generic)
###get API key from materials project login dashboard online
API... |
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