sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
80362e28d45ebc7c227bb34367840b9d8c5ebedeac6711d60a2ea8c881256228 | Python | 1,069 | 43 | import pytest
import pandas as pd
from pandas.core.arrays.floating import (
Float32Dtype,
Float64Dtype,
)
@pytest.fixture(params=[Float32Dtype, Float64Dtype])
def dtype(request):
"""Parametrized fixture returning a float 'dtype'"""
return request.param()
@pytest.fixture
def data(dtype):
"""Fixt... |
a079dde0498568aec94509dc10c207247727282230596c4b5991474036eb0385 | Python | 1,070 | 31 | """Tests of split index calculation."""
import pytest
import torch
from einops import repeat
from mrpro.utils import RandomGenerator, split_idx
@pytest.mark.parametrize(
('ni_per_block', 'ni_overlap', 'cyclic', 'unique_values_in_last_block'),
[
(5, 0, False, torch.tensor([3])),
(6, 2, False, ... |
1294c425436784f6eb6252c2183209425d33b29168626e19b579c57c769bde3b | Python | 1,071 | 27 | import logging
import numpy as np
import nibabel as nib
def save_estimations_as_nifti(estimations, model, powder_average_path, mask_path, out_path):
aff, hdr = nib.load(powder_average_path).affine, nib.load(powder_average_path).header
powder_average = nib.load(powder_average_path).get_fdata()
if powder_a... |
46c77199df82bd13dc2e94ce68755af3d8bd9b8d464487b21928e79ec2eaaf00 | Python | 1,071 | 28 | import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import os
excitatory = ['L6cc', 'L2', 'VPM', 'L4py', 'L4ss', 'L4sp', 'L5st', 'L6ct', 'L34', 'L6ccinv', 'L5tt']
inhibitory = ['SymLocal1', 'SymLocal2', 'SymLocal3', 'SymLocal4', 'SymLocal5', 'SymLocal6', 'L45Sym', 'L1', 'L45Peak', 'L56Trans', 'L... |
8d1890d33b4a401856f261d967470aac72ba959992fe11ff0b3c8b43c66d9759 | Python | 1,071 | 30 | import pytest
import pandas.util._test_decorators as td
import pandas as pd
@pytest.mark.parametrize(
"values, dtype, expected_dtype",
(
([1], "int64", int),
([1], "Int64", int),
([1.0], "float64", float),
([1.0], "Float64", float),
(["abc"], "object", str),
(... |
f911c8728a987d9e9fe9726e2a5171b61227a090ca0c983b1c9483a72f799ac9 | Python | 1,072 | 45 | import pytest
import pandas as pd
from pandas.tests.extension.list.array import (
ListArray,
ListDtype,
make_data,
)
@pytest.fixture
def dtype():
return ListDtype()
@pytest.fixture
def data():
"""Length-10 ListArray for semantics test."""
data = make_data(10)
while len(data[0]) == len(... |
080f9327116fec2da43aa3de5099f32f4d6519ddbc5601564d8f9c7b68da34bb | Python | 1,073 | 35 | default_param = {
"Autofluo channel": '488nm',
"Staining channel": '561nm',
'voxel_size': '4',
'Brain_weight': '3500',
'Brain_height': '2500',
"Thickness": '75',
"Network_input_z": '64',
"Network_input_x_y": '256',
'Train_total_num': '40',
'Cut_index_x': '470',
'Cut_index_y':... |
5ca393cdeabc169653a73af9e966f01b84b16dc055ee5cfea03dbc92fb4de79f | Python | 1,073 | 41 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Feb 20 12:04:14 2023
@author: tomas
"""
import glob
from cine import Cine
import tube2
from meniscus3 import locate_objects, find_real_measurements, get_stem
from matplotlib import pyplot
filenames = glob.glob("data2/unsuitableVideos/*.cine")
def pro... |
ae946ce615dedc022950a5acc74d66ff97b29c41fe218f0b6fd03cf385a69053 | Python | 1,073 | 38 | import argparse
import matplotlib.pyplot as plt
from osgeo import gdal
parser = argparse.ArgumentParser(description='Rescale a geotiff')
parser.add_argument('-i', dest='input', required=True, help='Input geotiff')
parser.add_argument('-o', dest='output', required=True, help='Output geotiff')
parser.add_argument(
'... |
acf36265c1a661a24e0fa7787d99ba932dbe7b170b2490f9595ca4ed792d2490 | Python | 1,074 | 44 | import numpy as np
import pandas as pd
import time
import datetime
def es_mu(esws: list, verbose: bool=False) -> pd.DataFrame:
"""Compute ESmu
Computes mean of ESWs, i.e. ES_mu, for each gene / cell-type.
Parameters
----------
esws : list
List of ESw dataframes to compute mean from.
... |
96ea42cc71c00310d2a746dff6051a04ee28927be766cfd4ca9125c49265fcd5 | Python | 1,075 | 32 | # Copyright 2018-2020 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... |
059b7763b8e079c12c2c20b6af033869277874c086073a2f8c0cffb3a00c06be | Python | 1,076 | 38 | """TaskType — the enum of ML tasks PyCaret supports.
Using a real Enum instead of a string makes it easy for an LLM agent or a React
UI to enumerate what's available without guessing.
"""
from __future__ import annotations
from enum import StrEnum
class TaskType(StrEnum):
"""The machine-learning task a PyCaret... |
07004b1c93d19126df615e2fc8207221a3070a14efc38414f9b170c65c4555ef | Python | 1,076 | 28 | from isaacgymenvs.pbt.launcher.run_description import ParamGrid, RunDescription, Experiment
from isaacgymenvs.pbt.experiments.allegro_kuka_pbt_base import kuka_env, kuka_base_cli
from isaacgymenvs.pbt.experiments.run_utils import version
_pbt_num_policies = 8
_name = f'{kuka_env}_throw_{version}_pbt_{_pbt_num_policie... |
bc7c017c0804b0efe7ab13f46b10a159f3c44ee97316037d18cdaa66911949e8 | Python | 1,076 | 38 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Feb 27 14:13:57 2023
@author: tomas
"""
import meniscus_rate as mr
import glob
from sklearn.ensemble import IsolationForest
from matplotlib import pyplot
def no_skinny(data):
return data[data[:,7] - data[:,5] > mr.MIN_WIDTH]
def remove_outliers(d... |
dcaceddcbfe9ab5f6281218bdd890b04cd09a1298bbbca75988d9ab8524bb982 | Python | 1,077 | 25 | from Environment import *
from Parameter 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}_seg.tif'.format(i)))
image_array = sitk.GetArrayFro... |
4058139912420d0bf7f13dcb34a8c6315b651b00e1ded4220906f4393c200f4f | Python | 1,078 | 37 | from multiprocessing import Array, Process, Event
import time
import random
def test_ring_buffer_array(eno1_buffer, event):
while (True):
time.sleep(4)
# Generate a list of 10 random integers between 1 and 100 (inclusive)
random_integers = [random.randint(1, 1000) for _ in range(10)]
... |
1f1940bed47875b591322e78358df75fc38a4b9d71b2b078092026003d3d1e97 | Python | 1,081 | 35 | import numpy as np
allocentric_color = '#{:02x}{:02x}{:02x}{:02x}'.format(109, 47, 255, 248) # a.k.a task-anchored
egocentric_color = '#{:02x}{:02x}{:02x}{:02x}'.format(0, 220, 184, 255) # a.k.a task-independent
null_color = '#{:02x}{:02x}{:02x}{:02x}'.format(128, 128, 128, 255) # a.k.a aperiodic
alt_egocentric_color ... |
0b6fd54b938d0eff4882179601d8dd446c55edf89524c49085757b1851582ebf | Python | 1,082 | 36 | """Fixtures for scripts/hyper-sweep tests.
`scripts/hyper-sweep` uses a hyphen in its directory name, so it is not a valid Python
package and its modules cannot be reached with a normal `import` statement. Load them
from their file path instead.
"""
import importlib.util
import sys
from pathlib import Path
from types... |
b4f1bab1b9668f30ade1545ee692c4f0bd71dfec05ba11b7cdce8b67c32edb9b | Python | 1,083 | 30 | from isaacgymenvs.pbt.launcher.run_description import ParamGrid, RunDescription, Experiment
from isaacgymenvs.pbt.experiments.run_utils import version, seeds, default_num_frames
kuka_env = 'allegro_kuka_two_arms_regrasp'
_frames = default_num_frames
_name = f'{kuka_env}_{version}'
_params = ParamGrid([
('seed',... |
92b5b772db5e67400f667c18dd46465e9a3bf828a817f0ea1b080c2f92d5fc34 | Python | 1,085 | 28 | #
# a script to go from berkeley's .grammar file format to our CKY parser's format
import re
import sys
#startsyms = 1
for line in sys.stdin:
arr = line.split(' ')
if len(arr) == 4:
arr[0] = arr[0].replace("&","-")
arr[2] = arr[2].replace("&","-")
#una... |
29bee3f4c4aff4ede053ccec603bc76ad6076e40af70a97371022fdb527929fd | Python | 1,086 | 36 | import pandas as pd
import pandas._testing as tm
class TestDataFrameCount:
def test_count(self):
# corner case
frame = pd.DataFrame()
ct1 = frame.count(1)
assert isinstance(ct1, pd.Series)
ct2 = frame.count(0)
assert isinstance(ct2, pd.Series)
# GH#423
... |
05f9e9c293735a101dc00d32a8b3a4c3e83a0f4f84c52e346fbc8722b38c6a60 | Python | 1,087 | 36 | import sys
import pandas as pd
import argparse
argparser = argparse.ArgumentParser('''
Tiles stimuli by subject into experiment data.
''')
argparser.add_argument('stimuli', help='Path to data table containing stimuli')
argparser.add_argument('responses', help='Path to data table containing by-subject responses... |
2c2cd788d77e8f6bf0946e2951411496a5aaa6685728ece3e02629d99ebeec84 | Python | 1,087 | 29 | import sys
import os
sys.path.append(os.path.join(os.path.dirname(__file__), '..', '..', 'resource-gcg', 'scripts'))
import model
import argparse
argparser = argparse.ArgumentParser(description='''
Counts and divides model-formatted files.
''')
argparser.add_argument('-n', '--no-normalization', dest='nonorm', action=... |
7f509de4203532b48bdd23604ea4948d11f73a80d1c515ce165225ec4a913758 | Python | 1,088 | 37 | from docutils import nodes
from docutils.statemachine import ViewList
from docutils.parsers.rst import Directive
from sphinx.util.nodes import nested_parse_with_titles
import os
class RTDPDF(Directive):
def run(self):
if "READTHEDOCS" in os.environ:
project = os.environ["READTHEDOCS_PROJECT"]... |
aa19b73bd71b1ce24131038bf8b625d7ea3374c6db9dc039c3610bd32aa03724 | Python | 1,088 | 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... |
7979235edf2ff5a7afd41a38c404e854ae2b63131f6fc225ca8127a372a79fb4 | Python | 1,089 | 51 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Feb 27 20:21:38 2023
@author: tomas
"""
from cine import Cine
import glob
import align
import numpy as np
import random
from skimage.filters import sobel, threshold_li
from skimage.io import imshow
from matplotlib import pyplot
def difference(left, r... |
a5da682662d53986167c14b19f9b5b48be84f5e6219e72ed792c0fd24606dfed | Python | 1,089 | 19 |
def test_detect_ref():
import pheweb.load.detect_ref, os
default_builds = pheweb.load.detect_ref.get_default_builds()
filepath = os.path.join(os.path.dirname(__file__), 'input_files/', 'assoc-files', 'has-fields-ac-af-maf.txt') # has only chr10
variant_iterator = pheweb.load.detect_ref.make_variant_ite... |
0fc819cf4aa7eb1d7a7eb658b7a4f24381283fdd61e6bc0ebe8761e96770ab3a | Python | 1,090 | 29 | # 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... |
a0337a98c369df1d05d550e485a4482b4feb76aedab0d6bf0126d8832792d922 | Python | 1,090 | 32 | import pandas as pd
import pandas._testing as tm
class TestToDictOfBlocks:
def test_no_copy_blocks(self, float_frame):
# GH#9607
df = pd.DataFrame(float_frame, copy=True)
column = df.columns[0]
_last_df = None
# use the copy=False, change a column
blocks = df._to_d... |
320b4538e0d6b8dd68c51ce21503463b358c3a5e98a67bbeb517ebe53238a8be | Python | 1,092 | 39 | import multiprocessing
import threading
import os
import time
import concurrent.futures
# 多线程反编译函数
# @Jully_xiaoman
def multi_decompile(apk_list):
threads = []
for filename in apk_list:
inputpath = os.path.join(path, filename)
outputpath = os.path.join(outpath, filename)
threads... |
b6d198ab8314a0743cffa76a20736260db2d85d5d9606f06a8e23210d3979775 | Python | 1,093 | 40 | import logging
import os
# Directly modified from the OT-flow Github Depository
def get_logger(logpath, filepath, package_files=[], displaying=True, saving=True, debug=False, mode="a"):
logger = logging.getLogger()
if debug:
level = logging.DEBUG
else:
level = logging.INFO
logger.setLe... |
d5859e7c2efe3de84bed280154fb3d8f13def12856309018af8431cc1b57be25 | Python | 1,093 | 35 | from pgen.utils import parse_fasta
import argparse
import sys
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("-i", default=None)
parser.add_argument("-o", default=None)
parser.add_argument("--clean_strategy", type=str, default=None, choices={"delete", "upper", "unali... |
d239603f5795c494980be23a1d7ee73bd66931b5257e282bd7206035e758e719 | Python | 1,094 | 40 | import sys
import pandas as pd
import argparse
argparser = argparse.ArgumentParser('''
Add Natural Stories document ID's to item-level tokenization
''')
argparser.add_argument('src', help='Path to source tokenization table <NSDIR>/naturalstories_RTS/all_stories.tok')
args = argparser.parse_args()
docnames = [None, 'B... |
4b83846db348c4aedccda29d2ddab957d2cb2162c38b496a7200bed664c5068e | Python | 1,095 | 44 | import numpy as np
import pandas as pd
import time
import datetime
def es_sd(esws: list, verbose: bool=False) -> pd.DataFrame:
"""Compute ESsd
Computes standard deviation of ESWs, i.e. ES_sd, for each gene / cell-type.
Parameters
----------
esws : list
List of ESw dataframes to comput... |
5f6f827f59bce15c273ac75ad4519b567cbfa23124609187271952d1c574e3da | Python | 1,096 | 48 | """
transforms.py is for shape-preserving functions.
"""
from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
if TYPE_CHECKING:
from pandas._typing import Scalar
def shift(values: np.ndarray, periods: int, fill_value: Scalar) -> np.ndarray:
new_values = values
if per... |
e2561d6ca6c3d7117f944743c9582c40dea198f8a7d6e90f55d7999fc24e7a4e | Python | 1,097 | 31 | import pandas
import numpy
cellLineList = pandas.read_csv('cellLine.tsv', sep='\t', low_memory=False, index_col=0)
cellLineList = cellLineList.columns
cellLineData = pandas.read_csv('data CCLE/CCLE_RNAseq_genes_rpkm_20180929.gct ', sep='\t', low_memory=False, index_col=1, skiprows=2)
cellLineName = cellLineData.col... |
01ae73d54946127e5773cb1bbb965c4d9b4d8556df0f572481da0fac7a8cf3b9 | Python | 1,098 | 38 | import torch
from torch import nn
# Typing
from torch import Tensor
from typing import List, Optional, Tuple
class MLP(nn.Module):
"""Multi-layer perceptron.
"""
def __init__(self, dims: List[int], act=None) -> None:
"""
Args:
dims (list of int): Input, hidden, and output dime... |
c97bca8cfd3d524b50cb1307c2aa57e31d34b87f03c262b75ee4871729214e8f | Python | 1,098 | 41 | import torch
import torch.nn as nn
from darts.api import Model
from darts.genotypes import PRIMITIVES
from darts.modules.operations.conv import OPS
class MixedLayer(Model):
""" A mixture of 8 unit types
We use weights to aggregate these outputs while training.
and softmax to select the strongest edges w... |
32a658b3dd6faa8b8aa07564d528cffbe2299c1306eaecd56ec029c774d21ee0 | Python | 1,099 | 33 | import functools
from PyQt6.QtWidgets import QApplication
from PyQt6.QtGui import QCursor
from PyQt6.QtCore import Qt, QEventLoop
class ShowWaitCursor(object):
def __enter__(self):
QApplication.setOverrideCursor(QCursor(Qt.CursorShape.WaitCursor))
# This overloaded function call makes sure that a... |
b118e7ade2d00b0af992e98d481059b364f051d598cf9dff34a788fcf9fc6c5f | Python | 1,099 | 27 | # 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... |
e5c61e05edde57a1bee7ebc8315fb3b9e5b671660e8541faec5b6ce612b22f89 | Python | 1,099 | 34 | #! /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... |
18bf3266621f4a8dfe24643cb9a2faf840b25f88af1a0bf0847be975af8dbc80 | Python | 1,101 | 32 | import pandas as pd
import sys
names = ['subject','word','sentid','sentpos','fdurFP','fdurGP','wdelta','wlen', 'resid', 'prevwasfix', 'startofsentence', 'endofsentence']
cumwdelta = 1
def calccumwdelta(row):
global cumwdelta
tmp = cumwdelta
if row['RTfirstfix'] == 0:
cumwdelta += 1
else:
... |
8b9bdad2ad9677b492744cda9d6160b23e91be8f240230a107387859851280b8 | Python | 1,102 | 42 | __all__ = ["zip_content"]
import os
from typing import Literal, Optional, Tuple
try:
from zipfile_deflate64 import ZipFile
except ModuleNotFoundError:
from zipfile import ZipFile
def resolve_zip_content_path(path: str) -> Tuple[str, Optional[str]]:
if os.path.exists(path):
return path, None
... |
72518d37cbb377c1dcbaa36c42ad1fbd21f95bbefa84450ef512b634f13135bc | Python | 1,103 | 46 |
import torch
from tnn.loss import t_softmax
import matplotlib.pyplot as plt
import imageio
tmp = imageio.v3.imread('elephant.jpeg')
img = torch.tensor(tmp).float() / 255.0
M = 1.0 * torch.tensor([[-1, 1, 1], [0, 1, 1], [0, 0, 1]])
M_inv = 1.0 * torch.tensor([[-1, 1, 0], [0, 1, -1], [0, 0, 1]])
f = [lambda x: torc... |
b1ac462f4dd6bf17c7619b7d93a37953df054cbb81c1e9020e74fac61d933c5c | Python | 1,103 | 29 | from circlemap.utils import start_realign,insert_size_dist
import multiprocessing as mp
from circlemap.realigner import realignment
import os
from tqdm import *
input = "/home/iprada/faststorage/projects/6_aged_yeast/working_directory/aligned/BM3/sort_circle_qname_BM3.bam"
qbam = "/home/iprada/faststorage/projects/6_a... |
2d24665d972c68ebe36ed05fb19df5fcf3f3f2e68f3925edd1d0a5d233a5135e | Python | 1,104 | 30 | import setuptools
from glob import glob
# Will load the README.md file into a long_description of the package
with open("README.md", "r", encoding="utf-8") as fh:
long_description = fh.read()
# Load the requirements file
with open('requirements.txt') as f:
required = f.read().splitlines()
if __name__ == "__mai... |
3320e217a8a0e42500207ba4aeed01a3b956a2ef87d198b8e01067e73732b6e5 | Python | 1,104 | 29 | """Basic plugin
This plugin defines two simple features by calculating them in the
`compute_some_new_features` function and setting the plugin metadata in the
`info` dictionary. It is used for testing in dclab.
"""
def compute_some_new_features(rtdc_ds):
"""The function that does the heavy-lifting"""
circ_pe... |
46ba69dd9bc3d5fd877050335d6985167a83a9f218bd8de4d3b534b282c3bedf | Python | 1,104 | 40 | import sys
sys.path.append('')
import numpy as np
class s2t(object):
def __init__(self, filename):
self.t2v = {}
self.dim = None
for line in open(filename):
line = line.strip().split('\t')
t = line[0]
v = np.array([float(x) for x in lin... |
558eeb243b3f5cd3e3a812121080d2d180ef7dcdaa02a87e1e8d3c9b9dd5f061 | Python | 1,105 | 40 | from datetime import timedelta
import pandas as pd
class TestAsOf:
def test_asof_partial(self):
index = pd.date_range("2010-01-01", periods=2, freq="ME")
expected = pd.Timestamp("2010-02-28")
result = index.asof("2010-02")
assert result == expected
assert not isinstance(re... |
a058af856b3e0f4401518fa58eda12a3f9705355953751202bee2a1e10456d62 | Python | 1,106 | 40 | import pytest
import pandas as pd
import pandas._testing as tm
@pytest.fixture
def range_index():
return pd.RangeIndex(3, name="range_index")
@pytest.fixture
def interval_index():
return pd.IntervalIndex.from_tuples(
[(0.0, 1.0), (1.0, 2.0), (1.5, 2.5)], name="interval_index"
)
def test_join_... |
2790bd4f897bc1f14b73447c679397861321dffc198af2c265d5f27e03a5d0c1 | Python | 1,107 | 48 | """Installation script for the 'isaacgymenvs' python package."""
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
from setuptools import setup, find_packages
import os
root_dir = os.path.dirname(os.path.realpath(__file__))
# Minimum dependencies required... |
89479e19a5a2f21cf95b29a41f61fac5d2f5d091fb9f8d388acb7b82e64ec228 | Python | 1,107 | 36 | from .DropDownMenu import DropDownMenu
class SelectROI(DropDownMenu):
"""
Class for selecting Region of Interest (ROI) from a dropdown menu.
"""
def __init__(self, default_msg):
"""
Initialize the SelectROI class.
Args:
default_msg (str): The default message to di... |
b3acf86421f0c3f4fb3c92a543d70ce2d2f99022c7fbec84ab1521b94ff4b08c | Python | 1,107 | 39 | import numpy as np, matplotlib.pyplot as plt, sys
import pumpprobe as pp
folder = sys.argv[1]
fconn = pp.Fconn.from_file(folder)
# Times on which to look for the peak time
tmax = 60
time = np.linspace(0,tmax,1000)
# Iterate over stimulations and responding neurons
peak_times = []
integrals = []
for ie in np.arange(... |
c239e5481701dfe3900827b48c205b2cb492f98d3124cbec93c00eee030e2a6a | Python | 1,108 | 33 | import pytest
import torch
from lightning_pose.models.heads.regression import LinearRegressionHead
class TestLinearRegressionHead:
@pytest.fixture
def basic_head(self):
"""Create a basic LinearRegressionHead instance for testing."""
return LinearRegressionHead(
in_channels=512,
... |
c9e2447e231f18cf738ac3706126282a974f9aba55445edd2bf35b6b12be55c8 | Python | 1,108 | 31 | from sys import path as sys_path
sys_path.append('..')
sys_path.append('../base')
from base.loggingUtils import setup_default_logging
from base.kernelFunctions import Kernel
from base import surfaceMatching
from base import surfaces as surfaces
from base import secondOrderMatching as match
setup_default_logging('../O... |
8be738faceae07bee4ca337ad55d5138b76da0b5926b0bf22243e5a41d471578 | Python | 1,109 | 40 | # Model save path
SAVE_PATH = "../../models/"
# Check point for encrypter
ENC_LARGE_CHK = SAVE_PATH + "encrypter_large_chk"
DEC_LARGE_CHK = SAVE_PATH + "decrypter_large_chk"
# Actual models go here !
ENC_LARGE_MODEL = SAVE_PATH + "encrypter_large.h5"
ENC_LARGE_JSON = SAVE_PATH + "encrypter_large.json"
DEC_LARGE_MODE... |
70d8218e8ecac2b36fe00b5def6f4b41aceb39df1cb373f80ce93b6bcd070939 | Python | 1,110 | 41 | import io
import pytest
import pandas as pd
class BasePrintingTests:
"""Tests checking the formatting of your EA when printed."""
@pytest.mark.parametrize("size", ["big", "small"])
def test_array_repr(self, data, size):
if size == "small":
data = data[:5]
else:
d... |
3fd69c5b70b5cb7da6b67e9975a6aa26996c1da9993560b919e1f49a1a0f5a52 | Python | 1,112 | 41 | import torch
import torch.nn as nn
from darts.api import Model
from darts.genotypes import LINEAR_PRIMITIVES
from darts.modules.operations.linear import OPS
class MixedLayer(Model):
""" A mixture of 8 unit types
We use weights to aggregate these outputs while training.
and softmax to select the stronges... |
a4eaa96c9c9f9b0e84fa916d882dc81c4097aa5b038c23fdcc7d3688a4a34574 | Python | 1,112 | 21 | """Diagnostics for treatment/control chromosome-name compatibility."""
def check_chromosome_names(treatment_names, control_names, error_stream):
"""Require at least one shared name, reporting both sets on failure."""
treatment_names = set(treatment_names)
control_names = set(control_names)
if treatmen... |
dfdbc098c5bba3b02a7e79624c63cb768468458c43f8535cb29c60527c276e79 | Python | 1,114 | 35 | '''
Created on Feb 16, 2019
@author: abast
This package is contains functions, that modify the cell after
it is initalized.
Such a function can for example be used to scale the apical dendrite.
These kind of modifying functions have caused a lot of trouble in the past, as it
has not been specified in t... |
e840af78bfeea79f24fef793be6118a3ca3bd3f3f1cd48b97618483550ca4a08 | Python | 1,114 | 28 | from aigarmic.train import train_binary, train_softmax
from tests.conftest import TRAIN_ANNOTATIONS_PATH
from aigarmic._nn_design import model_design_spectrum_2024_binary_first_step
import pytest
@pytest.mark.assets_required
def test_train_binary(binary_model_trained):
# not checking performance here, just that a... |
60c67d5abebb2ff76ea8af0bae940678322107933c83c448b131fbece3e4f17f | Python | 1,115 | 26 | # this file will be interpreted as python3
urlprefix = '/test'
# Minor allele frequency (MAF) filters:
# Note:
# "Association" means an association between a variant and a phenotype.
# Every association has a p-value. It may also have other attributes.
# MAF-filters will apply to allele frequency (AF) and ... |
7edbfbefe60961472964b5d7b4115d7778bfc34d086d74f55d3feceacf023854 | Python | 1,115 | 40 | from Surfaces import surfaces
from vtk import *
import argparse
def main():
parser = argparse.ArgumentParser(description='replaces points from a vtk file by those read from a byu or vtk file')
parser.add_argument('vtkFile', metavar='vtkFile', type = str, help='original vtk file')
parser.add_argument('point... |
8d3d56456a99df1fc8b0755d7806b11a3b4214a884fd701a7787e65cade16095 | Python | 1,116 | 29 | import os
import yaml
import pathlib
import warnings
code_dir = str(pathlib.Path(__file__).parent.resolve())
yaml_path = os.path.join(code_dir, 'glm_config.yaml')
with open(yaml_path, 'r') as f:
cfg = yaml.load(f, Loader=yaml.FullLoader)
cfg['yaml_path'] = yaml_path
cfg['code_dir'] = code_dir
# Check LEMON
cfg[... |
d62d9c999f521d7a5b9d44eb609f48df5fb72d7cd5fabaf854bb1f1fdf9745f1 | Python | 1,116 | 25 | '''
library for analysis of simulation data
(voltage traces, spike shapes, currents etc...)
and anatomical data (synapse distances etc...)
'''
from .membrane_potential_analysis import SpikeInit
from .membrane_potential_analysis import vm_mean
from .membrane_potential_analysis import vm_std
from .membrane_potential_an... |
4a788f4c97267ceed4987883ab8db269c16ff979f45e63104240761f4dfb7725 | Python | 1,117 | 40 | import numpy as np
from values import *
from defs import *
def Pendrin(cell,memb_id,xPendrin,area):
ph=np.zeros(NC)
for j in range(NC):
ph[j] = -np.log(abs(cell.conc[11][j])/1.0e3)/np.log(10.0)
Pbiiclepd = Pbieclepd*Pcliclepd
Pohiclepd = Poheclepd*Pcliclepd
ohe = 1.0e-11/cell.conc[11,0]
ohi = 1.0e-11/cell.c... |
17f354b78a96aecb4fca228d44c3fe2719dbdd3885131c5dad855ac9fe2efe19 | Python | 1,118 | 32 | # 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... |
ce2bcd22c7c89f50b92f324571b7f19b791f2379d400cdfa49d93d10b1c4ae64 | Python | 1,118 | 35 | from pathlib import Path
from setuptools import find_packages, setup
try:
from cellex import __author__, __email__
except ImportError:
__author__ = __email__ = ""
setup(
name="cellex",
version="1.2.2",
author=__author__,
author_email=__email__,
description="Compute single-cell cell-type ex... |
73410f0f43b943cf1d72df2f06d3a8a6ce54b2e5f07fb2bad8907c67750c3e89 | Python | 1,119 | 35 | import os
import cv2
import numpy as np
import nibabel as nib
def write_nifti(path,volume):
'''
writeNifti(path,volume)
Takes a Numpy volume, converts it to the Nifti1 file format, and saves it to file under
the specified path.
'''
#path = path.replace("/", "\\")
if(path.find('.nii')... |
d161c661bd90ecf46c813d26d8ef134415f07128d0e65ae67c166fb674965004 | Python | 1,119 | 27 | import torch
from torch.linalg import cross
def bond_angles(bond_vec, edge_index_bnd_ang):
bond_vec /= torch.linalg.norm(bond_vec, dim=-1, keepdim=True)
i = edge_index_bnd_ang[0]
j = edge_index_bnd_ang[1]
cos_ang = (bond_vec[i] * bond_vec[j]).sum(dim=-1, keepdim=True).clamp(min=-1., max=1.)
sin_an... |
66b8fccc30918369d078ea8d1fb35349a50a89665b73248736d9b1c261717a93 | Python | 1,120 | 35 | # 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... |
79f29790667d73fec6c07c76ebd34c3d78fe8b655e48db09ae60c45a09fcf62c | Python | 1,120 | 43 | '''
@Author: your name
@Date: 2020-01-06 17:08:52
@LastEditTime : 2020-01-07 13:25:31
@LastEditors : Please set LastEditors
@Description: In User Settings Edit
@FilePath: /KGCN_Keras-master/utils/io.py
'''
# -*- coding: utf-8 -*-
import os
import json
import pickle
def pickle_load(filename: str):
try:
w... |
aa3bffaa64af78699e96af11df9a0526850e9977a523cb660fcc671dcde99ae0 | Python | 1,120 | 30 | import torch
from torch_geometric.utils import scatter
# Typing
from torch import Tensor
from typing import List, Optional, Tuple
def graph_softmax(src: Tensor, index: Tensor, dim_size: int) -> Tensor:
src_max = scatter(src, index=index, dim=0, dim_size=dim_size, reduce='max')
out = src - src_max[index]
... |
336ea12c2d35cdaa41a5ae3e4073b8385f0447f0c96e794563abf33a0c713e1f | Python | 1,122 | 33 | from skimage.filters import threshold_multiotsu
from skimage.morphology import dilation, ball
import torch
from typing import List
from ...image import Stack, Image
def otsu_thresholding(stacks: List[Stack], nbins: int = 256) -> List[Stack]:
for stack in stacks:
thresholds = threshold_multiotsu(
... |
d003528400ada73c50fc282e6cd7a588942f3c8af592f5618a2731f9708374e1 | Python | 1,122 | 36 | import os.path
import shutil
import tarfile
import zlib
import zipfile
from time import gmtime, strftime
refuseddirs = ['CVS','images']
refuseddirsextra = ['CVS','small']
source = 'V:\\\\cvs\\porting24\\qwtplot3d\\doc\\'
sourceim = 'V:\\\\cvs\\porting24\\qwtplot3d\\doc\\images\\'
zipname = 'V:\\\\cvs\\upl... |
38ba91e0ad2fbb5377f82807157fa5da350165a3fb91986cb3c342ba010b0630 | Python | 1,123 | 40 | """Example model training script."""
import hydra
from omegaconf import DictConfig
from lightning_pose.train import train
@hydra.main(config_path="configs", config_name="config_mirror-mouse-example")
def train_model(cfg: DictConfig):
"""Main fitting function, accessed from command line.
To train a model on... |
82c3af3d631e1afff8699b244ac3e58f2e9f97f6f03433397c8cfc989d4e9c85 | Python | 1,123 | 55 | """
Tests for offset behavior with indices.
"""
import pytest
import pandas as pd
from pandas.tseries.offsets import (
BMonthBegin,
BMonthEnd,
BQuarterBegin,
BQuarterEnd,
BYearBegin,
BYearEnd,
MonthBegin,
MonthEnd,
QuarterBegin,
QuarterEnd,
YearBegin,
YearEnd,
)
@pyt... |
8e5dd02ce570d4060dc637d4606abb5bd8cb16da234d658f07b988d00a90068e | Python | 1,123 | 22 | import time
#This function is the countup timer, the count is set to 0 before the script
# waits for a second, otherwise the beep will sound several times before the second
# changes.
def timer(second, completion_event, test_duration):
# First we initialize a variable that will contain the moment the timer began ... |
ede63e0e424b538d9d7d666e2c27c6e29136ec7fcc7a651af258d3b44103393e | Python | 1,124 | 45 | # JN 2015-01-11
from __future__ import print_function, division, absolute_import
import logging
import numpy as np
import pywt # scipy doesn't have the flexibility yet
from .. import options
logger = logging.getLogger(__name__)
WAVELET = pywt.Wavelet(options['Wavelet'])
OUT_DTYPE = np.float32
LEVEL = 4
def wavelet_... |
2d06e92a0c11bdc24808443ade9eb1a8527e26b85b6fa3994781890516b5f261 | Python | 1,126 | 44 | import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from mat4py import loadmat
import scipy as sp
from matplotlib import cm
from helper_make_data import make_data
from matplotlib.ticker import FormatStrFormatter
import sys
import os
def make(whichdelay, whichITI, delay, ITIs): #, hit
# define a ... |
76768bb1ec400be7e91e789da243aedb6b8b5be19a5762bcfb900e5863eb62b7 | Python | 1,126 | 36 | # 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... |
1f49fecdd9714157b1d0b4cb1b3d9d9d267e4a965337afc216cfefa3a6b1dcc9 | Python | 1,127 | 33 | # -------------------------------------------------------------------------------------------------------------------------------------
# Following code curated for GCPNet (https://github.com/BioinfoMachineLearning/GCPNet):
# ----------------------------------------------------------------------------------------------... |
6f7ee0a6c758e35a91d7fca991ac1b3f126521d1f63513f2e888ab8d12528837 | Python | 1,128 | 35 | # Copyright 2023 Image Analysis Lab, German Center for Neurodegenerative Diseases (DZNE), Bonn
#
# 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... |
754ad8c3d3d32961d2305a3b30843ef12fd16b37e1c7158d6c6e6c02395338eb | Python | 1,130 | 45 | from datetime import datetime
import numpy as np
import pandas as pd
import pandas._testing as tm
def test_series_set_value(using_infer_string):
# GH#1561, GH#51363 as of 3.0 we do not do inference in Index.insert
dates = [datetime(2001, 1, 1), datetime(2001, 1, 2)]
if using_infer_string:
index... |
dafe53121ff0d37c8083d61740e18f8ab7f58ad35b63570278847d2a95c61b27 | Python | 1,130 | 51 | # pyaging/logger/__init__.py
from ._logger import (
Logger,
LoggerManager,
format_logging_message,
main_critical,
main_debug,
main_exception,
main_finish_progress,
main_info,
main_info_insert_adata,
main_info_insert_adata_layer,
main_info_insert_adata_obs,
main_info_inse... |
6e28e677bc03a460892611525941043be2afdb26d0b25196ac39e7f6ffa3363a | Python | 1,132 | 29 | from subprocess import check_output
# Hyper-parameters
table = "cnn_tuning" # _post_spec_fix"
target = "dspln_PSYCHIATRY_12"
channels = [500]
# dropouts = [0.2, 0.5, 0.8]
# dropouts = [0.4, 0.5, 0.6, 0.7, 0.8, 0.9] # , 0.9] [0.55, 0.65]
dropouts = [0.85, 0.875, 0.9]
# dropouts = [0.5, 0.6, 0.65, 0.7, 0.8, 0.85, 0.9,... |
5dc35194516465bdbd676a89e2a2744e12f3cc4ecac91ba51cf9b26b06492654 | Python | 1,133 | 44 | # Copyright 2024-2026 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... |
9ccd1da212afbe24ea048cc250a1d2de9b12dbdd3cf06fcf3b43c69867ba9726 | Python | 1,133 | 46 | """
Tests for np.foo applied to Series, not necessarily ufuncs.
"""
import numpy as np
import pytest
import pandas.util._test_decorators as td
import pandas as pd
import pandas._testing as tm
class TestPtp:
def test_ptp(self):
# GH#21614
N = 1000
arr = np.random.default_rng(2).standard_... |
31d284c3e2f0c20af2341a4d300163944c4a0d74893337f1de42c71276f6b4a3 | Python | 1,134 | 36 | import sys
import os
import argparse
if __name__ == '__main__':
argparser = argparse.ArgumentParser('''
Print usage for CDR executables.
''')
argparser.add_argument('names', default=[], nargs='*', help='Names of executables to show.')
args = argparser.parse_args()
bin_dir = os.path.dirname(os.p... |
2dcc187c5991705b1a1f243056617732762f60d2426c05cda8fcc391c6b3dd9d | Python | 1,137 | 34 | # NB: This is for the Timestamp.timestamp *method* specifically, not
# the Timestamp class in general.
from datetime import UTC
import pytest
from pandas._libs.tslibs import Timestamp
from pandas.compat import WASM
import pandas.util._test_decorators as td
import pandas._testing as tm
class TestTimestampMethod:
... |
99cb92204fb93fbaa821410704885a61d4cd4ac3d847196539af8e72f77d81d9 | Python | 1,137 | 23 | import torch
# Prints model summary
def model_summary(model):
model_params_list = list(model.named_parameters())
print("--------------------------------------------------------------------------")
line_new = "{:>30} {:>20} {:>20}".format(
"Layer.Parameter", "Param Tensor Shape", "Param #"
... |
e10520c0fb6626c7b8f71e2c0e52fe168285e8b4b1f27091a67d00964b1a4ee0 | Python | 1,137 | 32 | """Phase 8 notebook runtime package.
A ``NotebookManager`` spawns isolated JupyterLab containers per session.
Two drivers ship:
- ``LocalManager`` — for dev. Doesn't actually spawn a container; just
marks the session ``running`` with a fake port + token so the rest of
the system can be exercised end-to-end withou... |
763a640c65908dfd44ecdd3f139937b4957bd867adab14863ae4e10c7ed3c930 | Python | 1,140 | 41 | import tensorflow as tf
@tf.custom_gradient
def gradient_reversal(x,alpha):
def grad(dy):
return -dy * alpha, None
#return -dy * alpha
return x, grad
def loss_domain(label,domain):
domain = tf.clip_by_value(domain,0.001,0.999)
p2 = 1. - domain
loss = -label * tf.math.log(domain) -... |
fa6ee872825ee117801613584ab8908ec6914b400de4da88dd26eeff8305eb5f | Python | 1,140 | 33 | #!/usr/bin/python3
### positional comparison script useful for tagging alignments with their true position
# length.bp unaligned.bp known.nodes known.bp novel.nodes novel.bp
import sys
threshold = int(sys.argv[1])
for line in sys.stdin:
fields = line.split(' ')
# every input has a t... |
00afdf0a81c027abff89a4d17f610395a37c619d5f95d9c7ef25b6cc37659183 | Python | 1,141 | 40 | #python querydataframe.py --input FILE [--i colheader ...]
# each --i argument specifies a column header whose column will be output to stdout
# outputs columns in order specified by input file
import sys
targetcols = []
OPTS = {}
for aix in range(1,len(sys.argv)):
if len(sys.argv[aix]) < 2 or sys.argv[aix][:2] != ... |
46c3710d2ce496d7e98295736571c7a92be268ca80815e96d0d5c0e9322a5312 | Python | 1,144 | 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... |
d880fc28f80fe4c4b69508e36f7ac1bcfc871f33ae49678916e8be474de9df1b | Python | 1,144 | 48 | ##########################
#### Weidong Cai, 2021
import os
import sys
import numpy as np
import pandas as pd
import scipy.stats as spss
import sklearn
import seaborn as sns
import matplotlib.pyplot as plt
from sklearn import preprocessing
from sklearn.cross_decomposition import CCA
### read BSDS state OR data
state_... |
5308732d0096b6dc8504aeea0f18ba543f4c2c8968886ca0f2651d3b2901bee4 | Python | 1,145 | 33 | from base.surfaces import *
def compute():
fv0 = Surface(filename='/Users/younes/Data/sculptris/shape1.obj')
fv0.updateVertices(10*fv0.vertices)
center = fv0.vertices.sum(axis=0)/fv0.vertices.shape[0]
a = np.sign(fv0.vertices[:,0] - center[0] - 5) + 1
a = a[:,np.newaxis]
print(fv0.normGr... |
8de66ae48833244b9ebc4f9d2d34bbfb25d822c83b1e062cb32d568855af037c | Python | 1,145 | 38 | """Fixtures that load the scripts/inference-timing/*.py modules by file path.
scripts/inference-timing is not a valid Python package name (it has a
hyphen), so its modules can't be imported with a normal `import` statement.
Mirrors the pattern used in tests/scripts/hyper_sweep/conftest.py for
scripts/hyper-sweep.
"""
... |
ce8ec9d90a99b758f19d244d13086b49c47109dd7305e2b7bf504ed648539c8f | Python | 1,145 | 47 | """Test the initialization and training of regression models."""
import copy
import pytest
pytestmark = pytest.mark.gpu
def test_supervised_regression(
cfg,
base_data_module,
video_dataloader,
trainer,
run_model_test,
):
"""Test the initialization and training of a supervised regression mod... |
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