sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
37e6b16a390a522846799184aed45fcfbe48323a36ea405b425b9351855830ad | Python | 918 | 33 | # -*- coding: utf-8 -*-
import numpy as np
from .red_blue import RedBlueMove
__all__ = ["StretchMove"]
class StretchMove(RedBlueMove):
"""
A `Goodman & Weare (2010)
<https://msp.org/camcos/2010/5-1/p04.xhtml>`_ "stretch move" with
parallelization as described in `Foreman-Mackey et al. (2013)
<h... |
fff3e5390809a8d28b2662a0c60797ea0ad98e111a79f1a8c2eb2ee17cce98eb | Python | 918 | 25 | def scale_apical(cell, scale = None):
'''
This is the function used to scale the apical dendrite in the following
optimizations:
20190117_fitting_CDK_morphologies_Kv3_1_slope_variable_dend_scale.ipynb
20190125_fitting_CDK_morphologies_Kv3_1_slope_variable_dend_scale_step.ipynb
... |
7e2dd849b4735dfb4bd117c46585e34939fdb87adac4caf6e4936ada950f1f39 | Python | 919 | 33 | import sys, argparse
import pyqtgraph as pg
from kilosort.gui import DarkPalette, KiloSortGUI
from PyQt5 import QtWidgets
# TODO: figure out how to fix margin/padding around tooltip text.
# property-margin, margin-right not working as expected.
_QSS = """
QToolTip {
color: #aeadac;
backgrou... |
b7ba1901b947c20389f87768ab55a182c7669874b43375a5f025cb9a82449981 | Python | 919 | 19 | import sys
import os
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from app.models import Condition
def get_oasis_dx(visit_cdr, visit_dx1):
condition = None
if visit_cdr == 0:
condition ... |
beffb503a24dbd2c27e2168cfa19205cc4556884dbf7d512d817241a5933ba04 | Python | 920 | 38 | # IMPORTS
from os.path import join, split, splitext
from VINNA.config import get_cfg_defaults
def get_config(args):
"""
Given the arguemnts, load and initialize the configs.
"""
# Setup cfg.
cfg = get_cfg_defaults()
# Load config from cfg.
if args.cfg_file is not None:
cfg.merge_f... |
d0c28c231a485474d1e69d9859f1db49feeeda88862be5215e0da3f0c851ab73 | Python | 921 | 20 | import numpy
import bionetwork
import pandas
#Load network
networkList, nodeNames, modeOfAction = bionetwork.loadNetwork('viabilityModel/ligandScreen-Model.tsv')
annotation = pandas.read_csv('viabilityModel/ligandScreen-Annotation.tsv', sep='\t')
uniprot2gene = dict(zip(annotation['code'], annotation['name']))
nodeNam... |
77d345b3281c286b69fa9c3e6693af231321a6c46a775b8f05596a7a31e43665 | Python | 922 | 27 | import numpy as np
from pandas._libs.tslibs.dtypes import abbrev_to_npy_unit
from pandas._libs.tslibs.vectorized import is_date_array_normalized
# a datetime64 ndarray which *is* normalized
day_arr = np.arange(10, dtype="i8").view("M8[D]")
class TestIsDateArrayNormalized:
def test_is_date_array_normalized_day(s... |
378e55bc97e4d2302f2b1d5c4d655ffc7bda80fc41adc8f4e7a2de9b6894c801 | Python | 923 | 29 | import pyqtgraph as pg
class ShapeOutColorBarItem(pg.ColorBarItem):
def __init__(self, yoffset, height, label, colorMap, *args, **kwargs):
"""pg.ColorBarItem modified for Shape-Out
- Added option to define height
- translate the colorbar so that it is aligned with the plot
- show ... |
b16da62cfb8b115e4e552365cb12583913e1d66982e2504ac72cecde25b3b818 | Python | 923 | 38 | """
Extracted from alphapept.io
https://github.com/MannLabs/alphapept/blob/master/alphapept/io.py
under the Apache License 2.0
https://github.com/MannLabs/alphapept/blob/master/LICENSE
"""
__all__ = ["index_ragged_list"]
import functools
from typing import List, Sequence, TypeVar
import numpy as np
import numpy.typ... |
6f0dd79e3532078385c35068cd1ed23666bf6c3454584b16a0c41817deebe785 | Python | 925 | 19 | from datetime import datetime
import sys
sys.path.append("..")
from app import db
class Condition(db.Model):
__tablename__ = 'condition'
id = db.Column(db.Integer, primary_key=True)
designation = db.Column(db.String(255))
subject = db.relationship('Subject', backref='condition', lazy='dynamic', cascad... |
0a2c777699ccaac81f0d1326bdcf745e271ee3cf92d9061de6c6e2a926bb6fc4 | Python | 927 | 24 | ##########################
### Utilities Function ###
##########################
# one-hot encoding (only allowable set)
def one_of_k_encoding(x, allowable_set):
# Maps inputs only in the allowable set
if x not in allowable_set:
raise Exception("input {0} not in allowable set {1}:".format(x, allowable... |
f89bacd3d960c72a04baf5d97ef6d904d213ebfcc6549b044f4b3a222d2fd6e3 | Python | 927 | 20 | import sys, argparse, pandas as pd
argparser = argparse.ArgumentParser('''
Adds lag metrics to user-specified columns in space-delimited data table.
''')
argparser.add_argument('-c', '--columns', dest='c', nargs='+', action='store', help='Columns for which to add metrics.')
argparser.add_argument('-n', '--numlag', dest... |
97fe4a7d7c575f2fdcbe7a422e8fb57cf0f67109fd1e0ddd9d230b3612afd03f | Python | 928 | 31 | import logging
# A simple implementation of gradient descent with
# heuristic changing of descent step (eps)
def descend(opt, verb = True, maxIter=1000, TestGradient = False, epsInit=10.):
eps = epsInit
gradCoeff = 1.0
epsDoubleIterations = 10
obj = opt.objectiveFun()
logging.info("***** iteratio... |
eb3ecf22412dc00d4bee19fa7a89923655a834cd1b76332dc39084a890a198a7 | Python | 929 | 27 | import setuptools
with open("README.md", "r") as f:
long_description = f.read()
setuptools.setup(
name="progres",
version="1.1.0",
author="Joe G Greener",
author_email="jgreener@mrc-lmb.cam.ac.uk",
description="Fast protein structure searching using structure graph embeddings",
long_descri... |
163cd4c94f24cd099da23bf6fc257f2125cebda3c7617c641d553bbf4962c6eb | Python | 930 | 30 | __all__ = ["get_logger"]
import logging
import os
import sys
from typing import Optional
def get_logger(
name: Optional[str] = None, console: bool = True, file: Optional[str] = None
):
logger = logging.getLogger(name=name)
logger.setLevel(logging.INFO)
formater = logging.Formatter(
"%(asctime... |
132be4a54d7a7b17266aafc6bf1026283c6522275e5cb84ebd114264189cee70 | Python | 931 | 23 | # 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... |
cf9356df39bf785050ef3cf9db373d041b041fbd747354ff1dde2f2bf2dabbff | Python | 933 | 26 | import imageTimeSeries, imageTimeSeriesConfig
import optparse
import os
import shutil
import logging
from base import loggingUtils
output_directory_base = imageTimeSeriesConfig.compute_output_dir
# set options from command line
parser = optparse.OptionParser()
parser.add_option("-o", "--output_dir", dest="output_dir")... |
25a6fdf0aeb742aff28a1e003d985dadc806de5338aa86d48f1d1d0bce3e3014 | Python | 934 | 36 | import sys
import os
import re
import collections
import tree
import morph
def validate( t, W, L ):
## apply morph rules...
if len( t.ch )==1 and len( t.ch[0].ch )==0:
s = morph.getLemma( t.c, t.ch[0].c )
cat,base = s.split( ':' )
W[ re.sub( '^(.)[^:]*', '\\1', re.sub('-[lx].*','',t.c) ) + ':' + t.ch... |
ca27129aee6fb6cd85239525738e838e7da52d22dfa27214934e3144fa11716a | Python | 935 | 36 | """Set COLRv1 fontRevision from CBDT.
Used for bugfix, should fix to set properly on build instead.
"""
from fontTools import ttLib
from pathlib import Path
import sys
NAME_ID_VERSION = 5
def name(font, name_id):
return ",".join(n.toUnicode() for n in font["name"].names if n.isUnicode() and n.nameID == name_i... |
10771e2b75f0f1479d1bb7880e082da853a95bd64a1cbde9221c215fd66f6e06 | Python | 938 | 21 | #!/usr/bin/env python
import pandas as pd
from sys import argv
EIci = pd.read_table(argv[1])
IR = pd.read_table(argv[2])
EIci_out = argv[3]
EIci = EIci.rename(columns={'#chr': 'chr', 'gene_name': 'gene_id'}).query(
'tx_score >= 1')
EIci['intron_start'] = EIci['intron_start'].str.split(',')
EIci['intr... |
576532f421d6a8f791200adfd1f8b1f094180c22fc995d6b2ea14d78018930df | Python | 938 | 28 | import numpy as np
import random
import os
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.axes_grid1 import make_axes_locatable
import time
# import sklearn.linear_model
# from sklearn.model_selection import train_test_split
# from sklearn.linear_model import Perceptron, LogisticRegression
... |
f93653d653f4e6a7f47cda6124c1313440ea28238f59bdaea949b157921fc1a7 | Python | 938 | 33 | """
We also test Series.notna in this file.
"""
import numpy as np
import pandas as pd
import pandas._testing as tm
class TestIsna:
def test_isna_period_dtype(self):
# GH#13737
ser = pd.Series([pd.Period("2011-01", freq="M"), pd.Period("NaT", freq="M")])
expected = pd.Series([False, Tru... |
18e344d4bd0a629c909d18c3d6cc743cf7dbaaa90df91511244c2a33e48da0ae | Python | 939 | 21 | """Classes for calculating k-space trajectories."""
from mrpro.data.traj_calculators.KTrajectoryCalculator import KTrajectoryCalculator
from mrpro.data.traj_calculators.KTrajectoryRpe import KTrajectoryRpe
from mrpro.data.traj_calculators.KTrajectorySunflowerGoldenRpe import KTrajectorySunflowerGoldenRpe
from mrpro.da... |
667cad9e81eb13354e0607aca4daedf918ed99ba722b107000dd8649b9379b5c | Python | 939 | 37 | import numpy as np
import pytest
import pandas as pd
@pytest.fixture(params=[None, False])
def sort(request):
"""
Valid values for the 'sort' parameter used in the Index
setops methods (intersection, union, etc.)
Caution:
Don't confuse this one with the "sort" fixture used
for concat... |
9aec90670bf65df0dcfaa7ad1e4654f54efa59ed6b394d4e17f234077b695a61 | Python | 939 | 41 | import pandas as pd
df = pd.read_csv('~/data/ET_geco/EnglishMaterialInterestAreas.csv', keep_default_na=False)
df2 = df.WORD_ID.str.split('-', expand=True)
df2.columns = ['part', 'trialid', 'trialpos']
df2['sentid'] = df.SENTENCE_ID
df4 = df2.drop_duplicates(['trialid', 'sentid'])
trialid = df4.trialid.astype(int).v... |
94b9afbc8ee8b5cf42dca21c8ec34e0260ce405758799fc6bbdc89cb9a0f89e6 | Python | 940 | 38 | import sys, re
spill = re.compile('(.+)S[0-9]+$')
cli = sys.argv[1].strip().split('_')
preds = []
restrdomain = ''
for i in xrange(len(cli)):
s = cli[i]
if s in ['-a', '-A', '-x']:
P = cli[i+1].split('+')
for p in P:
if p not in preds:
preds.append(p)
elif s ==... |
9b63ef58e935b4e39e217f2a8f88419bef7f6e75ddd9868ae6769c3024d5e510 | Python | 940 | 25 | """Test nimare.annotate.lda (LDA)."""
import numpy as np
import pandas as pd
from nimare import annotate
def test_lda(testdata_laird):
"""A smoke test for LDA."""
N_TOPICS = 5
model = annotate.lda.LDAModel(
n_topics=N_TOPICS,
max_iter=100,
text_column="abstract",
)
new_dset... |
388ab753244d644864aefc25903a567c537a5e022176f0ffbd4d3be7c6c97361 | Python | 941 | 23 | # Copyright 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 agre... |
7fabcac07bec4743af1be571558cbee5eda92c73cdd19264e4be24284cb24291 | Python | 941 | 26 | import pandas as pd, numpy as np, os, shutil
from dask import dataframe as dd, array as da
def set_files(param):
if not param['recovery']:
main_path = os.getcwd()
path = os.path.join(main_path, param['matrices_folder'])
if os.path.exists(path): shutil.rmtree(path)
os.mkdir(path)
... |
bb3da189565e0c4a06385ed29285c277211f76c4afd25f7aab233ee7d1c0d506 | Python | 941 | 26 | """Test nimare.annotate.lda (LDA)."""
import numpy as np
import pandas as pd
from nimare import annotate
def test_lda(testdata_laird):
"""A smoke test for LDA."""
N_TOPICS = 5
model = annotate.lda.LDAModel(
n_topics=N_TOPICS,
max_iter=100,
text_column="abstract",
)
new_dse... |
d5393bb880163aa12ffcc29424bec00f4af7bf234e1dcd7e25148ef638ff3e0f | Python | 941 | 43 |
import sys,os
from setuptools import setup, find_packages
with open('README.md') as readme_file:
readme = readme_file.read()
def read(name):
with open(os.path.join(this, name)) as f:
return f.read()
this = os.path.dirname(os.path.realpath(__file__))
__description__ ='None'
__version__ = '0.1.0'
... |
5e669a80741c4ded57706bb5f926da876b0151953c6b6702461b55dff936b12e | Python | 942 | 33 | """session 26: trial notes (free-form annotation)
Revision ID: d4e5f6a7b8c9
Revises: c3d4e5f6a7b8
Create Date: 2026-05-09 10:00:00.000000+00:00
Adds a free-form ``notes`` column on ``trials`` so users can annotate
candidates straight from the trial-detail page. Optional, nullable —
existing rows just stay empty until... |
90f2b056ebd69a5cc6799e1bcc3025085f67a6f84c1fe0a282b8e84a5fceb820 | Python | 942 | 40 | # -*- coding: utf-8 -*-
"""
NeatMS library
~~~~~~~~~~~~~~
NeatMS is a peak filtering library for Mass Spectrometry data.
The code is open-source and available at
Full documentation is available at
:licence: MIT, see LICENCE for more details.
"""
import pymzml
import numpy as np
import pandas as pd
import pathli... |
e28c80ec2826f14e2d0961dc0bf56256f1ac04538d428181344c8fc9402a2203 | Python | 943 | 27 | # Tests for internal components of the atropos commands
from pytest import raises
from atropos.commands.trim.multicore import OrderPreservingWriterResultHandler
from atropos.commands.trim.writers import Writers
import tempfile
import os
def test_order_preserving_writer():
path = tempfile.mkstemp()[1]
try:
... |
b27b45c3a566219625e09ca21346b21960c05e1a8b800a804427c80104f7aa36 | Python | 945 | 36 | class IVecEnv:
def step(self, actions):
raise NotImplementedError
def reset(self):
raise NotImplementedError
def has_action_masks(self):
return False
def get_number_of_agents(self):
return 1
def get_env_info(self):
pass
def seed(self, seed):
p... |
041dfb0aee3005a2ce36df342854c005518b57c4b4a83a4635f1a0f03aae9550 | Python | 946 | 29 | #!/usr/bin/env python3
from SALib.sample import saltelli
from SALib.analyze import sobol
import numpy as np
import sys, getopt
import utils
data_folder = '../data/'
nsamples = 8000
outputfile = "param_values.csv"
opts, args = getopt.getopt(sys.argv[1:], "h:n:o:", ["nsamples=", "ofile="])
for opt, arg in opts:
if ... |
335cfa2c58c9f1d358c27466f121d923f985debbb3d00d41921eda69c3a6d58a | Python | 946 | 22 | from Environment_ui import *
def seg3d_to_2d(data_path, save_path, index=0):
os.makedirs(save_path, exist_ok=True)
for i in range(1, len(os.listdir(data_path)) + 1):
image = sitk.ReadImage(os.path.join(data_path, 'Z{:05d}_filter.tif'.format(i)))
image_array = sitk.GetArrayFromImage(image)
... |
40255884972d05c91fa56182c057e39bc7270fc9efbe1b7b66115579fb83cf6b | Python | 946 | 47 | #
# File for testing the Batch Normalization layer
#
import numpy as np
import tensorflow as tf
import protein_holography.network.L_batch_norm as lbn
s = [100,3,100]
bnl = lbn.LBatchNorm()
#print(bnl.__dict__)
bnl.build(s)
print('\nMoving mean')
print(bnl.moving_mean)
print('\nMoving Variance')
print(bnl.moving_v... |
0aa05cbac9e0dd7f4710661efbc645b1caa6543282a562c6e10f878224804d00 | Python | 947 | 26 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
class TestSearchSorted:
def test_searchsorted_different_argument_classes(self, listlike_box):
idx = pd.TimedeltaIndex(["1 day", "2 days", "3 days"])
result = idx.searchsorted(listlike_box(idx))
expected = np... |
3532c12fb861c05bebc68d266bd9f6fa478ac61caa05e0be56e969c4ebc1d17f | Python | 947 | 35 | STATS_PREFIX = 'run_info'
STAR_SOLO_DIR = 'Solo.out'
STAR_GENE_DIR = 'Gene'
STAR_RAW_DIR = 'raw'
STAR_FILTERED_DIR = 'filtered'
STAR_VELOCYTO_DIR = 'Velocyto'
STAR_BAM_FILENAME = 'Aligned.sortedByCoord.out.bam'
STAR_BAI_FILENAME = 'Aligned.sortedByCoord.out.bai'
STAR_BARCODES_FILENAME = 'barcodes.tsv'
STAR_FEATURES_FI... |
b4e5aa0e83903e6f9306a83e49d44bc6340b87930797909c2268af70d8079e74 | Python | 947 | 28 | # coding: utf-8
from atropos.adapters import Adapter, ColorspaceAdapter, PREFIX, BACK
from atropos.commands.trim.modifiers import AdapterCutter
from atropos.io.seqio import ColorspaceSequence, Sequence
def test_cs_5p():
read = ColorspaceSequence("name", "0123", "DEFG", "T")
adapter = ColorspaceAdapter("CG", P... |
04ed25b26c123944ce38fbd37f4d89d2ea2764d92600cce52292b816ea5ea7c9 | Python | 948 | 26 | import sys
import pandas
offset = 230
X1 = pandas.read_csv( sys.argv[1], index_col=False )
X2 = pandas.read_csv( sys.argv[2], index_col=False )
W = pandas.read_csv( sys.argv[3], sep='\t', index_col=False )
X = X1.append(X2)
## Remove the 231st item, which was an empty token in the orig expt that resulted in the mis... |
80a9ad3821c5f2313e65a0a4245e7fc78f576f230a51ef0a4cd6de0f2805010c | Python | 950 | 26 | # 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... |
490adfd18d56dc1a42bb7a7d060ebc41a0b4735d09717cad8b62a0af1c4c8f32 | Python | 951 | 22 | import os
import numpy as np
import pandas as pd
pwd = os.path.abspath(os.path.dirname(os.path.dirname(__file__)))
df = pd.read_csv(pwd+"/dataset/taste_dataset/bitter_sweet/bs_test.csv", header=0, sep="\t")
df['Smiles'].to_csv(pwd+"/contrast_predictors/virtual_taste_test.dat", index=False, header=False)
def get_virtu... |
4bff105418279de049c7184955c023a28c9d84809a88863c6d3e4d5df4d06e95 | Python | 951 | 25 | import os
# import cloudpickle
import compatibility
import pandas as pd
from . import parent_classes
import pandas_msgpack
def check(obj):
'''checks wherther obj can be saved with this dumper'''
return isinstance(obj, (pd.DataFrame, pd.Series)) #basically everything can be saved with pickle
class Loader(paren... |
76799b28c0b077bb66cba53373f8a7abb54603ecfa7c599bb4200e4dcaa2628c | Python | 951 | 19 | """Typed data pipeline for MRI/PET scan ingestion, labeling, and splitting.
Ports the scientifically meaningful behavior of `Dataset_MRI.ipynb` /
`Dataset_PET.ipynb` (see `docs/legacy-notebooks-inventory.md`) into current,
typed Python. Modules:
- `manifest`: the canonical typed scan manifest / data contract.
- `labe... |
aa68e89bc6fb0370ea27d1c68e773980f31c103cd68b22d5e0b0d4d66d7aa968 | Python | 951 | 33 | #Run sweeps over number of fields
import numpy as np
from placerg.funcs import *
from placerg.funcsrg import *
from placerg.objects import *
from placerg.runfunc import *
N0 = 1024 # number of cells
N = 256 # number of cells after removing silent ones
percell= 1.0 # probability that each field is accepted
phi=1.0 #... |
1f31c3215423ab5aadd789f17e763dc288bd022ee3e6a6cb7ba8ef3c39461699 | Python | 952 | 20 | #!/usr/bin/env python
import os, sys
from cupcake.io import GFF
def get_gff_from_list(gff_filename, listfile, partial_ok=False):
seqs = [line.strip() for line in open(listfile)]
for r in GFF.collapseGFFReader(gff_filename):
if r.seqid in seqs or r.seqid.split('|')[0] in seqs or (partial_ok and any(r.se... |
8eaecd64e319bc5a8de8d20bc2a6f8891c47e9e3ddccccdecbcb540c107b1c1d | Python | 952 | 35 | import linecache
from functools import cached_property
from typing import Any, List
import numpy as np
import pandas as pd
import torch
from scipy.sparse import issparse
from torch.utils.data import Dataset
import anndata as an
from typing import Union
class DatasetForInference(Dataset):
def __init__(self, adata:... |
a6402ece31576180b1fdbcf3d9cd2a2ea4b6169336f0db1dfe81c1f8e8849430 | Python | 952 | 36 | from __future__ import absolute_import
__author__ = 'Todd Young'
__email__ = 'youngmt1@ornl.gov'
__version__ = '0.1.0'
# Essential pieces
from .architecture import Architecture
from .modules.network import Network
from .modules.conv.network import ConvNetwork
from .modules.linear.network import LinearNetwork
from .st... |
a9e8d6d8d4a822b93cbd2df06d7e15df7b1c8c35b3b02608471b52b0417a5005 | Python | 952 | 36 | #! /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... |
26008f042a50b51bee62a15d23013a84c9d77e067ccd4c1e7c32e18c77c8b5ed | Python | 953 | 41 | # pyaging/predict/__init__.py
from ._cache import ClockCache
from ._pred import predict_age
from ._pred_utils import (
add_pred_ages_and_clock_metadata_adata,
check_feature_ranges,
check_features_in_adata,
cleanup_clock_memory,
load_clock,
predict_ages_with_model,
set_torch_device,
)
from .... |
3ffd48131ce4be53244df91128760f6f49bfa211097a9a0c9052edd21a432236 | Python | 953 | 38 | import pandas as pd
class TestReductions:
def test_min_max(self):
arr = pd.PeriodIndex(
[
"2000-01-03",
"2000-01-03",
"NaT",
"2000-01-02",
"2000-01-05",
"2000-01-04",
],
freq... |
e39c7f6d3ba8f50ce76cb9aaf6287a67771bde5330f2187e3e6a4e48b88a8602 | Python | 953 | 40 | import numpy as np
import pytest
import pandas as pd
@pytest.mark.parametrize(
"data, expected",
[
(np.random.default_rng(2).integers(0, 10, size=1000), False),
(np.arange(1000), True),
([], True),
([np.nan], True),
(["foo", "bar", np.nan], True),
(["foo", "foo... |
49a4da946b07d7262f948e88041fadc2ad8b3eb1bc9e8ac52b872232edb08bd6 | Python | 955 | 42 | # %%
from subprocess import Popen
from pathlib import Path
# %%
method_names = ["att", "lstm", "tf", "acs", "2_5d", "3d", "mp", "avg"]
dataset_names = ["organ", "nodule", "fracture", "adrenal", "vessel", "synapse"]
configs = {
d_name: [f"{d_name}_{m_name}.yaml" for m_name in method_names]
for d_name in datase... |
feeb6d5e4efbc2115245a9bd33cab0dda2596d90d399ccbe739451babe8dda5e | Python | 955 | 38 | # -*- coding: utf-8 -*-
#
# Sphinx configuration
# Cribbed from <https://github.com/ondrejsika/sphinx-autodoc-example> and
# <http://breathe.readthedocs.io/en/latest/readthedocs.html>
import sys
import os
import subprocess
read_the_docs_build = os.environ.get('READTHEDOCS', None) == 'True'
if read_the_docs_build:
... |
7fbd7c792db24bdb88e6cb1ee6774c5833b82cfea0c7f2503daa0fa15e0fe25b | Python | 956 | 42 | import argparse
import pandas as pd
from pathlib import Path
from sklearn.metrics import r2_score, mean_absolute_error
def main(direc, output=None):
direc = Path(direc)
csv_file = direc/'test_results.csv'
if not csv_file.exists():
raise ValueError(f'{csv_file} must be exists')
df = pd.re... |
83f18719613f5dea7f31a27532db2b5c294094bbd43cca94d39bfbf6e8e778d6 | Python | 957 | 38 | import vegas
import numpy as np
from cfcn_cffi import ffi, lib
def f(x):
_x = ffi.cast('double*', x.ctypes.data)
return lib.fcn(_x, x.shape[0])
@vegas.batchintegrand # 5 times faster for neval=1e6
def alt_batch_f(x):
n, dim = x.shape
_x = ffi.cast('double*', x.ctypes.data)
ans = np.empty(n,... |
dbea14e4570f9135104af2771b3a30f5889bb29f6eb12a733bcb6cc5de0b2f76 | Python | 957 | 19 | import os
from sbrnet_core.utils import full_read_tiff, write_tiff, linear_normalize
# The sbrnet-core package does not have a script to generate the synthetic ground truths.
# This script takes existing ground truths, beads and vasculature, and combines them.
# TODO: migrate synthetic data generation to sbrnet-core f... |
52cf734d1995293a6192ddfdfee22b6a93ce5c89c3c20f6021dcaeb5562a924e | Python | 959 | 39 | #!/usr/bin/python3
# mark_secondaries.py: Mark all but the first alignment with a given name as secondary
"""
Mark duplicate alignments for a given read name as secondary. Useful for GraphAligner output which does not mark its secondaries. Assumes that the first alignment is the primary alignment, ignoring score.
vg... |
7853d31769ac66aac15d2f92ad68d14d5616b6797157bed302edeabd6a848293 | Python | 959 | 25 | # 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... |
bc23473d5133cc0fb74767c14650a8ad97950b751f4e0acf16ddcbe2077b6ba2 | Python | 961 | 26 | import zoneinfo
import numpy as np
import pytest
from pandas._libs.tslibs.tzconversion import tz_localize_to_utc
class TestTZLocalizeToUTC:
def test_tz_localize_to_utc_ambiguous_infer(self):
# val is a timestamp that is ambiguous when localized to US/Eastern
val = 1_320_541_200_000_000_000
... |
bd4bb8bc7ef8df7407241532e3cc07504252e524ac2e3009dcf388f6c21bbd9c | Python | 962 | 38 | ######################
### Import Library ###
######################
import numpy as np
import networkx as nx
##########################
### Utilities Function ###
##########################
# nodes and edges to nx
def g_to_nx(nodes, edges):
G = nx.Graph()
for n in nodes:
G.add_node(n,idx=n)
for... |
f1cb2be733539f91be9b5f0b718c8ee5ed8c60cc14a82c874e34f1abf82aa8f3 | Python | 962 | 25 | import pandas as pd
import os
import sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from app import create_app, db
from app.models import Condition
from config.globals import ENVIRONMENT
from pathlib ... |
8fd38ad14f2b43adb286d1aed074740e83a74f2032b18439586811e46b0ef276 | Python | 964 | 34 | # Copyright 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 agre... |
fc2ab07e78a6198e978fc11f314e1112c165d20728951b4c0aa61ec82d500415 | Python | 964 | 35 | #!/usr/bin/env python
import os
pwd=os.getcwd()
def git_clone(repo_url, max_attempts=3):
for attempt in range(1, max_attempts + 1):
result = os.system(f'git clone {repo_url}')
if result == 0:
return
else:
print(f"Attempt {attempt} failed.")
if attempt ==... |
421b7ad437bad2fe0d99b56aa6dd8553bdd2d2f803cf9018f5c461a1c907bd45 | Python | 965 | 34 | # libraries
import pandas as pd
import numpy as np
import sys
import samalg
import scanpy as sc
# output
out_fn = "results_alignment_samap/"
## Preprocess ##
# query species
for spj in ["Xboc","Hmia","Spur","Isopu","Nvec"]:
# read
print("# loading %s" % (spj))
mat_j = sc.read_mtx("data/expression/%s_UMI_table.... |
4d0173e32448c8d4d0e54f7d90b86d130e2b103e2ead69fd866abf168e9346d9 | Python | 965 | 31 | __all__ = ["PeptideReportParserBase"]
import abc
from typing import Iterable, Union
import pandas as pd
from ....util.config import Configurable
from ..spec import PeptideMS2Spectrum
from ....util.table import filter_dataframe
class PeptideReportParserBase(abc.ABC, Configurable):
def __init__(self, configs: U... |
9ac1a5fc0c50dbc734ab47bfbb76b7d4c30b93342f9d8d9d84644393800afd21 | Python | 966 | 36 | #!/usr/bin/env python
__version__ = '1.0'
from Bio import SeqIO
import os, sys
def main():
from argparse import ArgumentParser
parser = ArgumentParser("Convert fasta to fastq")
parser.add_argument("fasta_filename", help="input fasta (must end with .fasta or .fa)")
args = parser.parse_args()
inpu... |
bf28e66afaab9d73b866f7f8f6c8ab5902fb6fcff2621488864b8a3ca587caee | Python | 967 | 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... |
1a6516b5e9713ea1ba21c0744e122b2c69fa250984dd2c175faaff2435ae99a1 | Python | 968 | 24 | import pandas as pd
import pandas._testing as tm
class TestToFrame:
def test_to_frame_datetime_tz(self):
# GH#25809
idx = pd.date_range(start="2019-01-01", end="2019-01-30", freq="D", tz="UTC")
result = idx.to_frame()
expected = pd.DataFrame(idx, index=idx)
tm.assert_frame_... |
53f5fed166eb1973c9ce7a3fbf7b94813b8ad1623c382e1baeda36618fb9b0f6 | Python | 969 | 36 | import os
import unittest
from unittest import TestCase
from evcouplings.utils import check_required, MissingParameterError
class TestUtilsConfig(TestCase):
def setUp(self):
self.config = {
"global": {
"prefix": "test"
},
"management": {
... |
a344d0d094b568ab698ed51290bb7f518619dff0644329feca0732a29aa3442d | Python | 969 | 21 | # -------------------------------------------------------------------------------------------------------------------------------------
# Following code curated for GCPNet (https://github.com/BioinfoMachineLearning/GCPNet):
# ----------------------------------------------------------------------------------------------... |
eb51fe9bf00a0a3a17a13005169c10e41dbf08c9ecca09affafec6d90e5ad04d | Python | 969 | 27 | from sys import path as sys_path
sys_path.append('..')
from base import loggingUtils
from base.imageMatchingMetamorphosis import Metamorphosis
from base.imageMatchingBase import ImageMatchingParam
import matplotlib
matplotlib.use("QT5Agg")
import matplotlib.pyplot as plt
import pyfftw
pyfftw.config.NUM_THREADS = -1
l... |
a0658d8e5410c30a2f6086e87b07da3742c573f1e306ed223b8517e771492f8c | Python | 970 | 41 | # -*- encoding: utf-8 -*-
# JN 2016-02-16
"""
Plot a spectrum from the first 1000 records of data
"""
import sys
import scipy.signal as sig
import matplotlib.pyplot as mpl
from combinato import NcsFile, DefaultFilter
def plot_spectrum(fname):
fid = NcsFile(fname)
rawdata = fid.read(0, 1000)
data = rawda... |
5ba9bfe105eee84b98ffc774d8827a42e85dc8e53433c142b4b559730637f56a | Python | 971 | 29 | # Author: Anastasios Nikolas Angelopoulos, angelopoulos@berkeley.edu
# https://github.com/aangelopoulos/im2im-uq/blob/main/core/models/losses/pinball.py
# pinball loss class
import torch
# pinball loss class
class PinballLoss:
def __init__(self, quantile=0.10, reduction="mean"):
self.quantile = quantile
... |
a136a6e05c382d86a4621a1f6ca94e3f73cb4747ee62d8b99721c3c8ebcb465d | Python | 972 | 28 | #! /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... |
5223845c9b5607f379d2869b5506eb4e5be2b8077a87749b151fbcb8436dec1c | Python | 974 | 28 | # 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... |
20024f81f4949b6a12008e6047d951e7ae73c0446f04dc3945aeb06cb46b63a8 | Python | 975 | 21 | # 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... |
a6a83b1decb3c6054a198374f19066f982a37397d5a6394f5ae82caa674de5f6 | Python | 976 | 35 | # From: http://stackoverflow.com/questions/12090503/listing-available-com-ports-with-python
import sys
import serial
import glob
def list_ports():
'''
Lists serial ports.
:raises EnvironmentError:
On unsupported or unknown platforms
:returns:
A list of available serial ports
'''
... |
dbbcff8f2853acfc4cb54790a016639a98d94273d9dd349a4c3722563cf4671d | Python | 978 | 25 | import single_cell_analyzer as sca
def silence_synapses_by_somadist(cell, evokedNW, soma_dist_ranges = None):
'''
This allows to silence synapses active at a certain soma distance.
Parameters:
soma_dist_ranges: dict, with synapse types as keys (e.g. L5tt_C2) and the range
in which it s... |
d881e9d5a12e0f77dee05703e19ac967ea012b484fb1123ceb7386d6ec5d4b3c | Python | 979 | 40 | # JN 2015-05-28
"""
convenience script to show how many groups there are in each channel
"""
from __future__ import print_function, division, absolute_import
import os
from combinato import Combinato, h5files
def main(sign, label):
"""
show group sizes in h5files
"""
files = h5files(os.getcwd())
... |
5c8322469f7a7ed76a749d9c88d8bcb567975fb406f9c8f868244dda464c75a1 | Python | 980 | 41 | import pytest
jinja2 = pytest.importorskip("jinja2")
import pandas as pd
from pandas.io.formats.style import Styler
@pytest.fixture
def df():
return pd.DataFrame(
data=[[0, -0.609], [1, -1.228]],
columns=["A", "B"],
index=["x", "y"],
)
@pytest.fixture
def styler(df):
return St... |
86b2ab6b7234170a8240dd0885a853520819f6f055b441b02286c7ef7599dc53 | Python | 980 | 31 | # 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... |
1cfa1a55f2a5970ca8b8394e1e4cba495ba0fff5f9065585a134aaf453429373 | Python | 981 | 29 | """
Test possibility of formulating polynomial fit as a least-square fit, accounting for NaNs
"""
import numpy as np
# Mimics 500 subjects aged between 1 and 100 years old, for which 4 metrics are taken
np.random.seed(238237)
age = np.random.uniform(1, 100, (500, 1))
A = np.hstack((np.ones(age.shape), age, age**2, ag... |
da08bb09cc6e5fb0f48398bdea7ffc7256f9491b4944e860756862120eea1b6b | Python | 982 | 34 | import setuptools
from glob import glob
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name="imagenet_c",
version="0.0.2",
author="Dan Hendrycks",
author_email="hendrycks@berkeley.edu",
description="Access to ImageNet-C corruption functions",
long_descrip... |
1930b4fc62c223d177c008c146f5904cf91a02e947df5061e9740daa876de7b1 | Python | 983 | 22 | import dgl
import torch
import torch.nn as nn
import torch.nn.functional as F
from dgllife.model.readout import WeightedSumAndMax
from dgllife.model.gnn import WLN
class WLNPredictor(nn.Module):
def __init__(self, node_in_feats=74, edge_in_feats=12, node_out_feats=100, n_layers=2, project_in_feats=True, set_compa... |
b32d3f8a8d438bfc4f5046275110293d1f6e75fefa0ebea452f7ed84c1e52612 | Python | 983 | 31 | """PyCaret 4.0 structured event-stream logger.
Replaces the 3.x mlflow/comet/wandb/dagshub tracker adapters with a lean
in-process event stream designed to be consumed by:
- The forthcoming PyCaret React UI (over websocket or polling).
- LLM agents that reason over engine traces.
- Notebook users who want a human-rea... |
1bf86d079192892a7fa27ad4a88825052753910c388de1a1742bc6b034e9de6c | Python | 984 | 26 | import os
# import cloudpickle
import compatibility
import pandas as pd
import numpy as np
from . import parent_classes
import pandas_msgpack
def check(obj):
'''checks wherther obj can be saved with this dumper'''
return isinstance(obj, np) #basically everything can be saved with pickle
class Loader(parent_c... |
8335d26e162016529be9f1094c4d4a363b26f0e45a5731dc68edea90d95f5b31 | Python | 984 | 36 | import numpy as np
import torch
from torch.utils.data import Dataset
class ICUDataset(Dataset):
def __init__(self, df, pat_ids, config, mode = "train", hours = 14*24):
self.df = df
self.pat_ids = pat_ids
self.mode = mode
self.hours = hours
self.config = config
... |
c96db31f40abdbb67c6b9a2f515aa5879e864b7c02820b8d4dd8316737a59acf | Python | 984 | 36 | import dclab
import matplotlib.pylab as plt
# dataset
ds = dclab.new_dataset("fluorescence/fluorescence.rtdc")
evts = {"reference": 397,
"extremely porous": 8228,
"porosity above 1.05": 347,
"invalid event": 4740,
}
# plot
fig = plt.figure(figsize=(7, 3))
for ii, key in enumerate(e... |
20ded7eae187899e4d7ed048498a00d814809e84de6e0f72940654b1bc3dab5f | Python | 985 | 24 | # Copyright 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 agre... |
5d00c51242ef72b65b30d339b0565dec686df0e7088b096a490cfc1f46ab08c0 | Python | 985 | 37 | import numpy as np
def generate_label(X_test_geneid, positive_Gene):
y_test = np.array([])
last_gID = ''
for gID in X_test_geneid:
if gID != last_gID:
if gID in positive_Gene:
y_test = np.hstack((y_test, np.ones(1)))
else:
y_test = np.hstack(... |
8406c770ebabfccf7364bd03060839603b8f377ce44d5b13b5f537491cb0aa1d | Python | 985 | 30 | # 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... |
95e8d7e97d08c58e92cecbbc7036dd2309eecbf3d19e94fb1f4d217c02002535 | Python | 987 | 24 | import pandas as pd
import os
import numpy as np
pwd = os.path.abspath(os.path.dirname(os.path.dirname(__file__)))
# df = pd.read_csv(pwd+"/dataset/taste_dataset/bitter_sweet/bs_test.csv", header=0, sep="\t")
# df['Smiles'].to_csv(pwd+"/contrast_predictors/bs_test_VirtuousSweetBitter.csv", header=None, index=False)
... |
97415f12b5f762f1cd7dacd1227dee70164e3675073f2b2ac9f4bc5fadcbd63e | Python | 987 | 32 | """Phase 4 datasource driver layer.
Each backend (CSV upload, Postgres table, S3 file, …) implements the
``DatasourceDriver`` protocol. The factory resolves the right driver by
``DataSource.kind`` and the API/orchestrator never touches a backend
SDK directly.
Phase 4 ships two drivers end-to-end:
- ``csv_upload`` — ... |
a52a80fced8c96555356b94fe3a1ce3b6cf3d568047405daba3773a9796b5ee8 | Python | 987 | 36 | """Screenshots for quick guide dcor"""
import sys
from PyQt6 import QtCore, QtTest
from PyQt6.QtWidgets import QApplication
from shapeout2.gui.main import ShapeOut2
from shapeout2.gui import dcor
app = QApplication(sys.argv)
QtCore.QLocale.setDefault(QtCore.QLocale(QtCore.QLocale.Language.C))
mw = ShapeOut2()
mw.se... |
ddde1824cc63b7ad41cfcd0912f60bd05b00e1483f950cf5e6ccc6b7160aa765 | Python | 987 | 36 | import dclab
import matplotlib.pylab as plt
# dataset
ds = dclab.new_dataset("fluorescence/fluorescence.rtdc")
evts = {"reference": 397,
"small inertia ratio": 445,
"debris": 4429,
"large inertia ratio": 1893,
}
# plot
fig = plt.figure(figsize=(7, 3))
for ii, key in enumerate(evts.... |
8de60158732efaca29ce1fc8f3b552971d0955d117a36b3156f5944e62433690 | Python | 990 | 24 | # 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... |
a818594b072937e886e261b5494351ac15cfcc6ed11f8d7e75d2bcc8ecdf8006 | Python | 990 | 33 | import os
import unittest
from evcouplings.utils.update_database import symlink_force, download_ftp_file
from unittest import TestCase
import tempfile
class TestUtilsUpdateDatabase(TestCase):
def test_symlink_force_createSymlink(self):
"""
tests whether a symlink is correctly created
"""
... |
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