sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
48078ebde0e3cc437f08a21204dd38da0c1c2a9096372995399e471d26ea1c59 | Python | 1,226 | 47 | # Autogenerated by configen, do not edit.
# If encountering an error, please file an issue @
# https://github.com/romesco/hydra-lightning
# fmt: off
# isort: skip_file
# flake8: noqa
# Hydra + Lightning
from dataclasses import dataclass
from dataclasses import field
from typing import Any
from typing import Optional
f... |
6bb180ff084b6ce892e16c5476d0eba8a39486c7eaab74cbd27921a8f71cbacb | Python | 1,226 | 36 | import numpy as np
from pandas import (
IntervalIndex,
date_range,
)
class TestEquals:
def test_equals(self, closed):
expected = IntervalIndex.from_breaks(np.arange(5), closed=closed)
assert expected.equals(expected)
assert expected.equals(expected.copy())
assert not expe... |
7cd9e823fb25ffd1203d66d079626480c6877c5077f253c62e35fb0a03852058 | Python | 1,226 | 38 | '''
Created on 2014.11.13
@author: Liang Qian
'''
class Synapse():
'''
synapsis class is used to create a synapsis structure
members are as follows:
@param pre: pre-synapsis neuron
@param post: post-synapsis neuron
@param locationlayer: layer where this synapse locate in
'''
def _... |
80c86da231f529d470c4c98cfd495b9719382f4f68ed62d4b172e9eaa7544be2 | Python | 1,227 | 53 | """
All of pandas' ExtensionArrays.
See :ref:`extending.extension-types` for more.
"""
from pandas.core.arrays import (
ArrowExtensionArray,
ArrowStringArray,
BooleanArray,
Categorical,
DatetimeArray,
FloatingArray,
IntegerArray,
IntervalArray,
NumpyExtensionArray,
PeriodArray,
... |
65812e44409c9b340495c94704291cd1c49ddac3d98818e4998d2701e8af6fb3 | Python | 1,229 | 40 | import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import os
# Create output directory
os.makedirs('paper_graphs/Deletion_Distance_Plots', exist_ok=True)
# Read the data
df = pd.read_csv('CT2_log/euclidean/high_variation_genes/deletion_distance.csv')
# Create figure
fig, ax = plt.subplots(figsize... |
91e1835398743dd0f6ec909cdcb90abd4e38a39ef37a717f3627530ca58a9761 | Python | 1,229 | 46 | """Plots the voltage along a fiber, as well as its first and second spatial differential.
The copyrights of this software are owned by Duke University.
Please refer to the LICENSE and README.md files for licensing instructions.
The source code can be found on the following GitHub repository: https://github.com/wmglab-... |
950313464b624dfdc2d0cf3864cbdf80f2109aeab5bc505b17f8e7ee193b8ced | Python | 1,229 | 39 | import numpy as np
import matplotlib.pyplot as plt
from matplotlib import pyplot
import matplotlib as mpl
from scipy.ndimage import gaussian_filter1d
plt.figure( figsize=(8,8) )
steps=1000
t = [i for i in range(steps)]
plt.style.use('seaborn-whitegrid')
palette = pyplot.get_cmap('Set1')
font1 = {'family': 'T... |
6709be69242030106149ee7b6e81cf2817edecdb41153b9d8267e9185f09edff | Python | 1,230 | 44 | ##########################################################################
# NSAP - Copyright (C) CEA, 2019
# Distributed under the terms of the CeCILL-B license, as published by
# the CEA-CNRS-INRIA. Refer to the LICENSE file or to
# http://www.cecill.info/licences/Licence_CeCILL-B_V1-en.html
# for details.
##########... |
34095797ddafe26ce103845dd37739ebe30df91c42ca3134224080c5c80be061 | Python | 1,231 | 29 | from CrystalTracer3D.plot import *
from CrystalTracer3D.io import *
from CrystalTracer3D.band import *
import yaml
from tqdm.contrib.concurrent import process_map
with open('../vessel_density_local/config.yml', 'r') as ymlfile:
cfg = yaml.safe_load(ymlfile)
def main(in_dir):
reader = CrystalReader(Path(cfg['... |
ac846a533ae3456b6f4fcddb4cde0eb84646d1e73ba19289628b14fb0c2dc465 | Python | 1,233 | 41 | '''
Related Figures:3b-c
'''
import numpy as np
class kalman_filter():
def __init__(self,trainX,trainY):
X1=trainY[:,0:-1]
X2=trainY[:,1:]
A=np.dot(((X2)@(X1.T)),np.mat(X1@(X1.T)).I.A)
H=np.dot((trainX@(trainY.T)),np.mat(trainY@(trainY.T)).I.A)
n=trainY.shape[1]
W=((... |
c74387e3f80dc7ed77ab0d7f1988a115e9754b86d61336eb47f553f87f71e2d4 | Python | 1,233 | 44 | """
Check the numpy config is valid.
"""
import numpy as np
import pytest
from unittest.mock import patch
pytestmark = pytest.mark.skipif(
not hasattr(np.__config__, "_built_with_meson"),
reason="Requires Meson builds",
)
class TestNumPyConfigs:
REQUIRED_CONFIG_KEYS = [
"Compilers",
"Mach... |
b65d72af7879d11d2deeebf04dc7ec456fa3b759fdbeca9fe015a9e1d35375df | Python | 1,234 | 50 | from datetime import datetime
import numpy as np
from pandas import (
DataFrame,
Index,
MultiIndex,
Period,
Series,
period_range,
to_datetime,
)
import pandas._testing as tm
def test_multiindex_period_datetime():
# GH4861, using datetime in period of multiindex raises exception
... |
855ffa08b7683e6d2f6b6d96a70e332aa334458b33dd36715e3d0fa12fbd7834 | Python | 1,236 | 43 | from typing import Iterable, Tuple, TypeVar
T = TypeVar("T")
def loop_first(values: Iterable[T]) -> Iterable[Tuple[bool, T]]:
"""Iterate and generate a tuple with a flag for first value."""
iter_values = iter(values)
try:
value = next(iter_values)
except StopIteration:
return
yiel... |
e407a77cd0042951957a28886601b7a7d4a8772071ef6b81d16f82769186cb0c | Python | 1,236 | 40 | import torch
from tqdm.auto import tqdm
from functools import wraps
def parse_device(gpu_id):
if torch.cuda.is_available() and gpu_id >= 0:
device = torch.device(f"cuda:{gpu_id}")
else:
print("GPU index not provided or no GPU support currently available.")
print("!!! Running on CPU !!!... |
285a3968e5a18f497351d0e1b05c9633306e30e9cd9d5f636a55bdf9a45416ae | Python | 1,237 | 51 | # Copyright (C) 2012,2013 Bernd Feige
# This file is part of avg_q and released under the GPL v3 (see avg_q/COPYING).
"""
avg_q unit testing.
Usage example:
from avg_q.unittests import avg_q_test_case
class avg_q_test_case1(avg_q_test_case):
script='xx'
expected_output='yy'
import unittest
unittest.main()
"""
imp... |
3541de9317c814dc5a251597bc2a78156bf35cb6141cb754376f0cf44fdb22b8 | Python | 1,237 | 39 | from xgboost import XGBClassifier
from shap.datasets import adult
from shap.explainers import PermutationExplainer
from shap.maskers import Partition
class PermutationSuite:
# Adapted from tests/explainers/test_permutation.py
max_samples = 100
def setup(self):
self.model = XGBClassifier(tree_met... |
b2ac492448ee6cb74396673e386e9c651b58c719f5f6dcff74e25f11b1576f4f | Python | 1,237 | 51 | import pytest
import cedalion.data
import cedalion.nirs
import cedalion.sigproc.motion as mc
import cedalion.sim.synthetic_artifact as synthetic_artifact
from cedalion import units
@pytest.fixture
def rec():
rec = cedalion.data.get_snirf_test_data()[0]
rec["amp"] = rec["amp"].pint.dequantify().pint.quantify(... |
0e1cf2766515385ef52e1f3691246651d8d952bd274d65e748a03fe7a0a69910 | Python | 1,238 | 35 | import yaml
from tqdm.contrib.concurrent import process_map
from skimage.util import img_as_ubyte
from skimage.io import imsave
import nrrd
from skimage.transform import rescale, resize
from CrystalTracer3D.segment import *
from CrystalTracer3D.util import *
from CrystalTracer3D.plot import *
with open('config.yml',... |
8e743091ed00162c42c0d590cfb4a5aacb13f56e0f287fc201a5eeab4a5632d5 | Python | 1,239 | 41 | import matplotlib.pyplot as plt
import seaborn as sns
from tqdm.contrib.concurrent import process_map
from pathlib import Path
import nrrd
from skimage.io import imsave
import numpy as np
from skimage.transform import resize
from CrystalTracer3D.io import CrystalReader
from CrystalTracer3D.util import stitch_tiles
... |
5d6e518b2a9d04182eaa25bb9e5e8b1522ae19964ba003a236f33d094478f676 | Python | 1,240 | 47 |
import datetime
import pickle
import cloudpickle
def reformat_timestamp(timestamp):
if len(timestamp)==10:
return timestamp
# Parse the input timestamp into a datetime object
dt_object = datetime.strptime(timestamp, '%d-%b-%y')
# Format the datetime object into the desired output format
... |
6605b0d40ffd3c96d9c67b27a8a3211f2bbeb4271f9ae190af275df4ce5a290f | Python | 1,240 | 29 | #!/usr/bin/env python
# ============================================ #
# Getting hamiltonians.h5 using trained models #
# ============================================ #
# Usage: python <path-to-this-file>/eval.py <your_config>.ini [-n NUM_THREADS] [--debug]
# Default config file for evaluation is DeepH-E3/deephe3/defa... |
2cd39fd9526c575ec50d3f688040db6ba95ae35e325269b9cffec1f7b9cb376e | Python | 1,241 | 42 | from datetime import datetime
from pandas import DataFrame
import pandas._testing as tm
class TestInferObjects:
def test_infer_objects(self):
# GH#11221
df = DataFrame(
{
"a": ["a", 1, 2, 3],
"b": ["b", 2.0, 3.0, 4.1],
"c": [
... |
202e3f6668ec5f8f34e0d9eefa540371c42bd33b799b321911a07707376f6bc6 | Python | 1,244 | 55 | """
Public API classes that store intermediate results useful for type-hinting.
"""
from pandas._libs import NaTType
from pandas._libs.missing import NAType
from pandas.core.groupby import (
DataFrameGroupBy,
SeriesGroupBy,
)
from pandas.core.resample import (
DatetimeIndexResamplerGroupby,
PeriodInde... |
f4606e7de9dca3174817d6a5b69d815f40c9bf8fe83fd03f15f8a388eb1b1330 | Python | 1,244 | 46 | from __future__ import annotations
from stimuli.trigger._base import BaseTrigger
from .utils._docs import copy_doc
from .utils._imports import import_optional_dependency
class SerialTrigger(BaseTrigger):
"""Trigger using a serial port for micromed iEEG amplifiers."""
def __init__(
self,
por... |
665e966e46e74d6569e852f6ad1db5a811ac2e885ea081195ea5992b17e90d1b | Python | 1,245 | 42 | import sys
import os
import numpy as np
import tensorflow as tf
thisfile = os.path.abspath(__file__)
modulepath = os.path.dirname(os.path.dirname(thisfile))
sys.path.insert(0, modulepath)
from tensorcircuit.applications.vags import double_state, reduced_density_matrix
def test_double_state():
s = double_state(... |
b3ae1d6793ba32b060d4d94884e04ecb9dbd0bbcc4bd8e9474efbd4980faa92c | Python | 1,245 | 45 | #!/usr/bin/env python
# Copyright (C) 2008-2012,2017 Bernd Feige
# This file is part of avg_q and released under the GPL v3 (see avg_q/COPYING).
import sys
import voglps
import cairo
# Derived class with cairo plotting operators
class cairovogl(voglps.voglps):
def __init__(self,psfile,surface,width,height):
voglps... |
e85f15757cab455e6368c6937aeaf17b06973885fd90ac6da8d3dd2ef478126d | Python | 1,245 | 51 | """Contains code to create and manage comparison objects"""
from .binning import (
RecordPairGenerator,
MissingRecordPairGenerator,
QueryRecordPairGenerator,
QueryMissingRecordPairGenerator,
ConnectedComponentPairGenerator,
generate_mix_bin,
legacy_bin_generator,
legacy_weights_from_cla... |
d7a0033d05e6b8fe89ae2e21030448b1a8508e9cac5950b8940ec028888cb99e | Python | 1,247 | 39 | """
Model architectures: frequency-domain CNN only (MLP support removed).
"""
import torch
import torch.nn as nn
class CNNModel(nn.Module):
"""CNN model for processing frequency-domain features."""
def __init__(self, num_classes, num_channels=3, drop_prob=0.3):
super().__init__()
self.num_chan... |
23c220d79f064d8b6a2f07aba3b342e72077caab9e3bf9392ac29e72f433ab46 | Python | 1,249 | 37 | import os
from typing import Any
from github_utils import gh_post_pr_comment
from gitutils import get_git_remote_name, get_git_repo_dir, GitRepo
from trymerge_explainer import BOT_COMMANDS_WIKI
def parse_args() -> Any:
from argparse import ArgumentParser
parser = ArgumentParser("Comment on a PR")
parser... |
27d7b85a56751426dff741014ce1abae6813a792ad457b69d48f99de82a8dbc3 | Python | 1,250 | 42 | from pymatgen.core import Structure
import numpy as np
import sys
def get_kgrid_from_spacing(poscar_file, k_spacing=0.05):
"""
Compute Monkhorst-Pack k-point grid dimensions for a given structure
and target reciprocal spacing.
Args:
poscar_file (str): Path to POSCAR/CONTCAR.
k_spacing ... |
900c1ac0b58642f392924865cc6ecad28f0a103af623ff97a5e3d2c9b064118d | Python | 1,250 | 47 | from __future__ import annotations
from typing import TYPE_CHECKING
from fonticon_mdi6 import MDI6
from pymmcore_widgets import LiveButton, SnapButton
from qtpy.QtCore import QSize
from superqt.fonticon import icon
if TYPE_CHECKING:
from pymmcore_plus import CMMCorePlus
from qtpy.QtWidgets import (
Q... |
c587aa9d249d9cf4a69b332a3de21676eecb0254f75dad3af6fec3eace9ffe5c | Python | 1,251 | 32 | import torch
import torch.nn as nn
import torch.nn.functional as F
from ..functional import cutoff_function, softplus_inverse
"""
computes radial basis functions with exponential Gaussians
"""
class ExponentialGaussianRadialBasisFunctions(nn.Module):
def __init__(self, num_basis_functions, cutoff, ini_alpha=0.5... |
14cd7a4617b8cba1c3ab0827cfd63fdacceb37bab163fa82a9da5d391d7de61c | Python | 1,252 | 38 | from typing import Optional
from app.config.recording import RecordingConfig
class RecordingConfigValidator:
@classmethod
def _validate(cls, recording_config: RecordingConfig) -> Optional[str]:
if recording_config is None:
return "Config is null"
if recording_config.mode is None:... |
753f2cd253dd0914ec20b897a75902f70229ab72fc87ce9bc5b20955f79429d0 | Python | 1,252 | 29 | import time
from pytorch_lightning.callbacks import Callback
class EpochTimeLogger(Callback):
def __init__(self):
super().__init__()
self.train_start_time = None
self.predict_start_time = None
self.training_iter = 1
self.predict_iter = 1
def on_train_epoch_start(self, ... |
2f58003236183c1e9e6264a9a577dbc0f54a6b71c23687ea3d5519de0c4b95d0 | Python | 1,253 | 36 | import pytest
from pandas import (
DataFrame,
Index,
MultiIndex,
)
import pandas._testing as tm
class TestDropLevel:
def test_droplevel(self, frame_or_series):
# GH#20342
cols = MultiIndex.from_tuples(
[("c", "e"), ("d", "f")], names=["level_1", "level_2"]
)
... |
e512cffc5fe236c43c5f4fd97995df137b75e0daa2f2eeeaf7df411b1b72a75e | Python | 1,255 | 57 | #!/usr/bin/env python3.7
"""Plot a sample.
The copyrights of this software are owned by Duke University.
Please refer to the LICENSE and README.md files for licensing instructions.
The source code can be found on the following GitHub repository: https://github.com/wmglab-duke/ascent.
RUN THIS FROM REPOSITORY ROOT
""... |
f88da1cacdbf027417a7e718e70ef07ef65282e4bdca02ea1afb16e51995e668 | Python | 1,255 | 48 | #!/usr/bin/env python3.7
"""Plots the voltage along a fiber, as well as its first and second spatial differential.
The copyrights of this software are owned by Duke University.
Please refer to the LICENSE and README.md files for licensing instructions.
The source code can be found on the following GitHub repository: ... |
d691284ba8d1b8a7c8bede0ecd556620b8e3ba69c6fe76f7070445fa8e4d614a | Python | 1,257 | 49 | #!/usr/bin/env python3
"""Build a macOS arm64 PyTorch wheel.
Usage: build_wheel.py <output_dir>
Mirrors .ci/wheel/linux/build_wheel.py. Build flags are expected in the
environment (set by build_env_setup.py and sourced by build.sh); this script
adds only the macOS host-platform plumbing and runs `python -m build`.
""... |
799367cc6ac8e248bfe78a606373a3d13fb1de5c5d5d3621e3faf20c1db8c015 | Python | 1,258 | 42 | from typing import TYPE_CHECKING
from .measure import Measurement
from .segment import Segment
from .style import StyleType
if TYPE_CHECKING:
from .console import Console, ConsoleOptions, RenderResult, RenderableType
class Styled:
"""Apply a style to a renderable.
Args:
renderable (RenderableTy... |
f526f858eca48fdf619f731039f9bf32a611c4ee6400366de8eb9a9214ae929e | Python | 1,258 | 42 | from pandas import (
Period,
PeriodIndex,
)
def test_is_monotonic_increasing():
# GH#17717
p0 = Period("2017-09-01")
p1 = Period("2017-09-02")
p2 = Period("2017-09-03")
idx_inc0 = PeriodIndex([p0, p1, p2])
idx_inc1 = PeriodIndex([p0, p1, p1])
idx_dec0 = PeriodIndex([p2, p1, p0])
... |
e864bfc92751d92aec0508ed455752657570465f5b9da678c0ec1b5f11640d70 | Python | 1,259 | 40 | import numpy as np
import pandas as pd
from pycisTopic.iterative_peak_calling import get_consensus_peaks
from pycisTopic.pseudobulk_peak_calling import peak_calling
import scanpy as sc
import pyranges
import os
# Read in narrow peak dictionaries
peak_files = snakemake.input.narrow_peaks
# List of cell types
cells = [... |
04aedac2d2cc2ea7c54c266789831b1f71d0a669ca02c97da2b02ee627af6c5f | Python | 1,262 | 47 | import torch
from braincog.base.connection.CustomLinear import *
from braincog.base.node.node import *
from braincog.base.learningrule.STDP import *
from braincog.base.brainarea.IPL import *
from braincog.base.brainarea.Insula import *
if __name__ == "__main__":
num_neuron = 4
num_vPMC = num_neuron
num_STS... |
f4a02cac5a2a10852d59bf2d4504ac92aa9ecef74b3da1e04ca33614d5ac0f13 | Python | 1,262 | 62 | # %%
import mne
from autoreject import AutoReject
import utility_funs as uf
from sys import argv
# config
# load data and set channel names, montage
data_dir = '/Users/kbas/sci_data/harmonicity_modulation/'
p = int(argv[1])
data_id = uf.participant_fname(p)
fname = data_dir + data_id + '.bdf'
ar_path = '../results/au... |
70c312fae6fea612797218f8c24ecf08510fc2a1f96a45074fcee598543f1946 | Python | 1,264 | 38 | import logging
from pathlib import Path
LOGGER = logging.getLogger("cali_logger")
LOGGER.setLevel(logging.DEBUG)
# Create formatter
formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
# File handler
log_file = Path(__file__).parent / "cali_logger.log"
file_handler = logging.FileHand... |
9b7207dba4c2ccb0e94bc72dbf324a2c0f31e35e2eaf98e55f7b1d4f8b01e26f | Python | 1,264 | 50 | from collections.abc import Generator
from contextlib import contextmanager
import pathlib
import tempfile
import pytest
from pandas.io.pytables import HDFStore
tables = pytest.importorskip("tables")
# set these parameters so we don't have file sharing
tables.parameters.MAX_NUMEXPR_THREADS = 1
tables.parameters.MAX_... |
c3b531dd4f0f23e49e3f5de10f73cc8d631fdd86ce1a883acc20ea8f49df9e92 | Python | 1,264 | 65 | """
Data IO api
"""
from pandas.io.clipboards import read_clipboard
from pandas.io.excel import (
ExcelFile,
ExcelWriter,
read_excel,
)
from pandas.io.feather_format import read_feather
from pandas.io.gbq import read_gbq
from pandas.io.html import read_html
from pandas.io.json import read_json
from pandas.... |
1970d65d8654d9cc02cad9e876227badcf25a46eaf93ff583ba98b1232ddc8cb | Python | 1,265 | 64 | """
DQAS for QFT QEM circuit design, deprecated DQAS implementation
"""
from functools import partial
import cirq
import numpy as np
import tensorflow as tf
from tensorcircuit.applications.vags import qft_qem_vag
from tensorcircuit.applications.dqas import (
set_op_pool,
DQAS_search,
verbose_output,
)
de... |
b1d642db1b570a6dba98892896572dc1d5f8d4201fdfbb55a63e38defdfad0ac | Python | 1,265 | 21 | """Re-select the number of latent factors for the Replogle tutorial on the
raw-count subset (the cached results/replogle-r-legacy.csv was computed on log-normalised
values). Same grid as the tutorial; writes results/replogle-r.csv."""
import sys, time
sys.path.insert(0, '../../../..')
import numpy as np, pandas as pd, ... |
6e805c4b0efc87e969db461b697489b2a900236b8dfe60ff4ed0b27697aae705 | Python | 1,267 | 48 | import typing as t
from .filters import FILTERS as DEFAULT_FILTERS # noqa: F401
from .tests import TESTS as DEFAULT_TESTS # noqa: F401
from .utils import Cycler
from .utils import generate_lorem_ipsum
from .utils import Joiner
from .utils import Namespace
if t.TYPE_CHECKING:
import typing_extensions as te
# de... |
489c8231a1226f6e8cb6ae85286b32e7cbb9bb405ce339ee46a7e3b46b68253a | Python | 1,268 | 39 | from __future__ import annotations
import argparse # noqa: TC003
import logging
from cli.lib.common.cli_helper import register_targets, RichHelp, TargetSpec
from cli.lib.core.vllm.vllm_build import VllmBuildRunner
logger = logging.getLogger(__name__)
# Maps targets to their argparse configuration and runner
# it ... |
26eb091fa955bedc2333d7e1c79966888f92bd6364efa77f0738994614df851f | Python | 1,269 | 47 | import numpy as np
class ArrayWithMetadata(np.ndarray):
"""
Notes
-----
https://docs.scipy.org/doc/numpy-1.13.0/user/basics.subclassing.html
Some functions don't work so we need a manual implementation:
https://github.com/numpy/numpy/issues/11671
"""
def __new__(cls, input_array, met... |
2a93b3ee5731294d13ae87eb802b39387840ea10afb34eb388ffb0764a220d71 | Python | 1,269 | 33 |
import sys
sys.path.append('.')
from plotting.utils import load_results, set_plotting_defaults, efcolor, pvscolor, ecscolor, dpi
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
set_plotting_defaults()
if __name__ == '__main__':
sim_name = sys.argv[1]
mesh_name = sys.argv[2]
results ... |
85f4855f2dbc3a82d82a5001ce73cc1e2ef6d3ca52bc7460f1964c87753e451b | Python | 1,269 | 35 | # License: GNU Affero General Public License v3 or later
# A copy of GNU AGPL v3 should have been included in this software package in LICENSE.txt.
""" Handles generation of a separate HTML page for knownclusterblast's MiBIG hits
"""
import os
from typing import List
from jinja2 import FileSystemLoader, Environment,... |
b59b639b20320167a785e1d3190db1b0ba3e2e843e25e0b4979e38db30cc0b39 | Python | 1,271 | 40 | import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import os
# Create output directory
os.makedirs('paper_graphs/Control_Distance_Plots', exist_ok=True)
# Read the data
df = pd.read_csv('CT2_log/euclidean/false_positive/high_variation_genes/control-control_distance.csv')
# Create figure
fig, ax =... |
2a9024444b89c169e50c10b8e51beaa2053fa353521b4938e2831001b81608dc | Python | 1,273 | 45 | import ctypes
import pytest
import pandas.util._test_decorators as td
import pandas as pd
pa = pytest.importorskip("pyarrow")
@td.skip_if_no("pyarrow", min_version="14.0")
def test_dataframe_arrow_interface():
df = pd.DataFrame({"a": [1, 2, 3], "b": ["a", "b", "c"]})
capsule = df.__arrow_c_stream__()
... |
eb904e693df39b286f34379dd3678f489ebf53aaea4527f69c1d2a8ed84fcaa3 | Python | 1,273 | 42 | from .sequencelayer import SequenceLayer
from .tempocluster import TempoCluster
from .synapse import Synapse
class TempoSequenceLayer(SequenceLayer):
'''
classdocs
'''
def __init__(self, neutype):
'''
Constructor
'''
SequenceLayer.__init__(self, neutype)
def addNe... |
1564647a41aa675345e1860d7e6e3a98e00ef6edefe1962db3f95cf328107ea6 | Python | 1,275 | 32 | """
The `numpy.core` submodule exists solely for backward compatibility
purposes. The original `core` was renamed to `_core` and made private.
`numpy.core` will be removed in the future.
"""
from numpy import _core
from ._utils import _raise_warning
# We used to use `np.core._ufunc_reconstruct` to unpickle.
# This is... |
92802ec345b84d6ca7839e7c0956998443017b40033ece73f50772250bce7bbe | Python | 1,275 | 49 | """
This is the discriminator D for ESPRESO.
TODO: recode
"""
import torch
import math
from torch import nn
import torch.nn.utils.spectral_norm as sn
import torch.nn.functional as F
class ConvSpectnormLReLU(nn.Module):
def __init__(self, in_c, out_c, kernel_size, alpha):
super().__init__()
self.b... |
43624a07d773318eb2dc15fcf52f7198fb31065b7d6601b21647b6183f81cd15 | Python | 1,277 | 36 | #!/usr/bin/env python3
"""Prints welcome message for ASCENT software.
The copyrights of this software are owned by Duke University.
Please refer to the LICENSE and README.md files for licensing instructions.
The source code can be found on the following GitHub repository: https://github.com/wmglab-duke/ascent
"""
d... |
63c9e9529210334952748c18edab8670b25a176d4939bf8a95553772f48bb0e8 | Python | 1,277 | 36 | import pytest
from pandas import DataFrame
import pandas._testing as tm
class TestSwaplevel:
def test_swaplevel(self, multiindex_dataframe_random_data):
frame = multiindex_dataframe_random_data
swapped = frame["A"].swaplevel()
swapped2 = frame["A"].swaplevel(0)
swapped3 = frame["... |
9895decd35c351b76e842c151807c0047a440115a19e3f212d6f44394deb9fce | Python | 1,277 | 43 | from numpy.testing import assert_
import numpy.distutils.fcompiler
customizable_flags = [
('f77', 'F77FLAGS'),
('f90', 'F90FLAGS'),
('free', 'FREEFLAGS'),
('arch', 'FARCH'),
('debug', 'FDEBUG'),
('flags', 'FFLAGS'),
('linker_so', 'LDFLAGS'),
]
def test_fcompiler_flags(monkeypatch):
mo... |
b6579170afa92bf989a6077407aabc11532bf1ba864792e555b8176ca8894688 | Python | 1,278 | 38 | import json
import os
import subprocess
import time
subid = raw_input('Enter subject id (i.e. s999): ')
training = raw_input('Enter 0 for training, 1 for main tasks: ')
if training == '1':
run_file = 'scanner_tasks_order1'
else:
run_file = 'practice_tasks'
taskset = raw_input('Enter task group (1, 2 or 3): '... |
4ba4dca50975b59351bcaa47ee939b1ae8b42c4a88936f8dc5d2e100545c0819 | Python | 1,279 | 36 | import time
from typing import List
import cv2
import numpy as np
import torch
from grimace.grimace_scorer_model import GrimaceScoreModel
class GrimaceScorer:
def __init__(self, grimace_scorer_model: GrimaceScoreModel):
self.grimace_scorer_model = grimace_scorer_model
def preprocess(self, frame: np... |
b7b16a97265210b517484421c6edcaf4a2695b203d99b12eba0d2d9e3dce2eac | Python | 1,279 | 40 | """
%load_ext autoreload
%autoreload 2
"""
import logging
from yass.batch import IndexGenerator
logging.basicConfig(level=logging.ERROR)
# init indexer for a matrix with int16, 1 million observations and
# 512 columns with maximum memory usage of 124 bytes
ig = IndexGenerator(1000000, 512, 'int16', '10MB')
# index... |
baf1980a0424c5bc9371d4d848d6742488abcdb7b3b9d86ca6510a7a801db464 | Python | 1,279 | 41 | """Runtime version lookup for gcmi.
The authoritative version lives in ``python/pyproject.toml``. Installed
packages read it from package metadata; source-tree imports fall back to the
local pyproject file.
"""
from __future__ import annotations
from importlib.metadata import PackageNotFoundError, version as dist_ve... |
c9ca44574d86170f373229979aa9355b692871abb89281a02f9196a3a84afe2b | Python | 1,279 | 59 | import pandas as pd
import sys
import numpy as np
sys.path.append("../")
wm = None # pd.read_csv("somePath/WM_run1_TAB.txt", sep='\t')
procedures = wm["Procedure[Block]"]
trialTypes = wm["TargetType"]
trialOnsetTimes = wm["ExperimenterWindow.OnsetTime"]
initialOnsets = wm["SyncSlide.OnsetTime"]
initialFinishes = wm["... |
a08598d5bf9199ef96ca8d9ac89e92a2e558839399d9746eb1711406b79f8f0d | Python | 1,282 | 43 | import os
import yass
from yass import preprocess
from yass import detect
# def test_can_detect_with_threshold(path_to_config_threshold,
# make_tmp_folder):
# yass.set_config(path_to_config_threshold, make_tmp_folder)
# (standardized_path,
# standardized_params,
# ... |
087270b3be74555090d8fb04a21c7cf7bbea274445ebe81e3565d8fd9beb5721 | Python | 1,284 | 41 | from __future__ import annotations
from typing import Callable
import pytest
from textstat.backend import utils, counts, metrics
from .. import resources
@pytest.mark.parametrize(
"inner_func, outer_funcs",
[
(
counts.count_words,
[metrics.sentences_per_word, metrics.words_per... |
f92f03149a3f004db7ef8e691be94607224941759e00025ac4ee8a685c4554ce | Python | 1,285 | 37 | from pathlib import Path
import typer
from .._qt.components.tomogram_browser import TomogramBrowserWidget
from .._metadata_models.relion.tilt_series_set import RlnTiltSeriesSet
from ..view._cli import cli
COMMAND_NAME = 'tomograms'
@cli.command(name=COMMAND_NAME, no_args_is_help=True)
def view_tomograms(
tilt_s... |
d5520fb82f0082d296adc9dc42b8c1758a80dc9556cacbba8d9a35aeb87b73b4 | Python | 1,288 | 37 | from typing import Optional, TYPE_CHECKING
from .jupyter import JupyterMixin
from .measure import Measurement
if TYPE_CHECKING:
from .console import Console, ConsoleOptions, RenderableType, RenderResult
class Constrain(JupyterMixin):
"""Constrain the width of a renderable to a given number of characters.
... |
d79a51a667a593c33d1f708027916b557a483fb867f5edd20e16bf3b29d2c9ec | Python | 1,288 | 39 | """
Generated by CHARMM-GUI (http://www.charmm-gui.org)
addCrystPdb.py
This program is to add CRYST1 information into PDB file.
Correspondance: jul316@lehigh.edu or wonpil@lehigh.edu
Last update: October 5, 2020
"""
from __future__ import print_function
import argparse
def addCryst(pdbfile, boxinfo):
inp_pdb ... |
a0f1b4b40e91b5dc58a7c80201ed240429beb2e3b44658a31055c3fab40dec4a | Python | 1,289 | 53 | """scvelo - RNA velocity generalized through dynamical modeling."""
from anndata import AnnData
from scvelo import datasets, logging
from scvelo import plotting as pl
from scvelo import preprocessing as pp
from scvelo import settings
from scvelo import tools as tl
from scvelo import utils
from scvelo.core import get_d... |
7824009dbca46f908de7842a32f706e0c8ca9ae697bdfe7c709223a4debdb565 | Python | 1,290 | 49 | # Autogenerated by configen, do not edit.
# If encountering an error, please file an issue @
# https://github.com/romesco/hydra-lightning
# fmt: off
# isort: skip_file
# flake8: noqa
# Hydra + Lightning
from dataclasses import dataclass
from dataclasses import field
from typing import Any
from typing import Callable
fr... |
83fdfeb30bc1d5fb77a8e8e4fe43567737ed98486ef64a6b412204a3f626c68e | Python | 1,290 | 43 | #!/usr/bin/env python3.7
"""Generate mock sample morphology.
The copyrights of this software are owned by Duke University. Please
refer to the LICENSE and README.md files for licensing instructions. The
source code can be found on the following GitHub repository:
https://github.com/wmglab-duke/ascent
"""
import os
i... |
979fa2a472af306ec9bd7f998fb9da8381ea083140ff632631eada924d6cf293 | Python | 1,290 | 41 | import torch
import torch.nn as nn
from myutils.common import heaviside
from config import AdaLiConfig
def piecewise_quadratic_backward(grad_output: torch.Tensor, x: torch.Tensor, alpha: float):
x_abs = x.abs()
mask = (x_abs > (1 / alpha))
grad_x = (grad_output * (- (alpha ** 2) * x_abs + alpha)).mas... |
018b364b05796a7920c27bca23d4523b58d9724d75f27bb74b26789e0cd936ca | Python | 1,291 | 46 | from operator import mul
from functools import reduce
import numpy as np
from numpy.random import randint
from numpy.lib import Arrayterator
from numpy.testing import assert_
def test():
np.random.seed(np.arange(10))
# Create a random array
ndims = randint(5)+1
shape = tuple(randint(10)+1 for dim in... |
6aa861c11299bdf1b16b7bf4f57e6f67bb81ba9f27e4e8da51a75f26957a1682 | Python | 1,292 | 40 | import numpy as np
from pandas import (
TimedeltaIndex,
factorize,
timedelta_range,
)
import pandas._testing as tm
class TestTimedeltaIndexFactorize:
def test_factorize(self):
idx1 = TimedeltaIndex(["1 day", "1 day", "2 day", "2 day", "3 day", "3 day"])
exp_arr = np.array([0, 0, 1, 1... |
89f2f7f186669b76f4e3540e3c9689b69119c7e87950ee0fec11624bd11e1fc1 | Python | 1,292 | 54 | import anndata as ad
import scvi
import scanpy as sc
import torch
import pandas as pd
import scipy
import numpy as np
import sys
print(torch.cuda.is_available())
scvi.settings.seed = 0
torch.set_float32_matmul_precision('high')
# Read in AnnData atlas object
filtered_adata = ad.read_h5ad(sys.argv[1])
# Setup SCVI o... |
9076cc1782116de3c650004bb5c094ce3a339a2c774a1890b2baa1024230b612 | Python | 1,292 | 43 | # -*- coding: utf-8 -*-
"""
Created on Fri Sep 14 15:19:13 2018
Plotting function container
@author: danilo
"""
import numpy as np
from matplotlib import pyplot as plt
def set_size(w,h, ax=None):
""" w, h: width, height in inches """
if not ax: ax=plt.gca()
l = ax.figure.subplotpars.left
r = ax.figure... |
0a53954cec65c8d2e5b8362688ccb47a9d659378a0e212326163f9b9800505a9 | Python | 1,293 | 34 | import tifffile
import numpy as np
import os
from os.path import join
from scipy.ndimage import zoom
def MaskToSwc():
# imgPath = r'E:\NeronSegDataSet\HaiNanDataSet1\OriDataSet\mask\43_23_12.tif'
# swcPath = r'F:\viif01-config\SelectTifLs001\TestResMask\GMM\43_23_12_mask.swc'
imgPath = r'E:\NeronSegDataSet... |
1d3082d747472f0b1b3ba10619e4f2aefacda2663d7721ab04afce99ac1a9300 | Python | 1,293 | 57 | """Plot a sample.
The copyrights of this software are owned by Duke University.
Please refer to the LICENSE and README.md files for licensing instructions.
The source code can be found on the following GitHub repository: https://github.com/wmglab-duke/ascent.
RUN THIS FROM REPOSITORY ROOT
"""
import os
import sys
s... |
2a6d3479a6e3d991c34b2b02a36ac0aeb208d2dae6916b865ab10866f4c3cacb | Python | 1,293 | 41 | from .layer import Layer
from .cluster import Cluster
from .synapse import Synapse
class SequenceLayer(Layer):
'''
This class mainly stores the musical sequential elements, including pitches and durations
'''
def __init__(self, neutype='LIF'):
'''
Constructor
'''
self.... |
0f6603d9552ba6e906a92297f5539df1764cda46cdd469d3555aa49a1e44ec09 | Python | 1,294 | 58 | """Plot a sample.
The copyrights of this software are owned by Duke University.
Please refer to the LICENSE and README.md files for licensing instructions.
The source code can be found on the following GitHub repository: https://github.com/wmglab-duke/ascent.
RUN THIS FROM REPOSITORY ROOT
"""
import os
import sys
s... |
52b59bc345a1086960a4892779eccb1dba3ad72b895326ce2992e8313a1bab7f | Python | 1,297 | 38 | from typing import Iterable
from torch.nn import Module
def get_parameters(modules: Iterable[Module]):
"""
Given a list of torch modules, returns a list of their parameters.
:param modules: iterable of modules
:returns: a list of parameters
"""
model_parameters = []
for module in modules:
... |
acadd5556dbec197d814054cf2041ff9062da37e3edf8f83b885e4ddcb3adcdc | Python | 1,297 | 42 | import gym
import gym_stag_hunt
from ray import tune
from ray.rllib.env.wrappers.pettingzoo_env import PettingZooEnv
from gym_stag_hunt.envs.pettingzoo.hunt import raw_env
if __name__ == "__main__":
def env_creator(args):
return PettingZooEnv(raw_env(**args))
tune.register_env("StagHunt-Hunt-PZ-v0", e... |
8d63746d14ea76f6f663d76472dfd3b6c83f4e1f72dc29ef599f9eb65b9d60ac | Python | 1,298 | 35 | import numpy as np
import torch
from radifox.utils.degrade.degrade import select_kernel
from math import ceil
def parse_kernel(blur_kernel_file, blur_kernel_type, blur_fwhm):
if blur_kernel_file is not None:
blur_kernel = np.load(blur_kernel_file)
else:
window_size = int(2 * round(blur_fwhm) ... |
1dde49c57c29bb8fc5b7662c70541242b0d2dd1a61e008406422cec7a0f3191c | Python | 1,299 | 41 | """For testing calculate.py file."""
import urllib.request
import numpy as np
import pytest
from scipy.io import loadmat
from phyid.calculate import calc_PhiID
from phyid.utils import PhiID_atoms_abbr
@pytest.fixture(scope="session")
def PhiID_test_simple_1(tmp_path_factory):
"""Load test data."""
fn = tmp_... |
29b41c461939930a90b8ded4c7af62bc1e590365cef5c09ebac4a8a88d508f0c | Python | 1,301 | 40 | from fastapi import APIRouter, Depends
from redis.asyncio import Redis
from app.utils.database import get_redis_connection
router = APIRouter()
@router.get(
"/hello_world",
tags=["Testing"],
description="A simple test endpoint that returns 'Hello, World!'",
summary="Hello World Test Endpoint",
r... |
2fc5d426bb22ea43937a8153b473e6c0f40e2b55a2adc3682a80143844afa1b6 | Python | 1,301 | 35 | """Evaluate a set of vectors for a given language."""
import os
import argparse
from .norms import evaluate_norms
from .analogies import evaluate_analogies
from .similarities import evaluate_similarities
import logging
logging.basicConfig(format='[{levelname}] {message}', style='{', level=logging.INFO)
def evaluate_l... |
678b53ba85b15285e2315abcb09c763cf188c91a33d5dcf34480b5c3c9e90ca4 | Python | 1,303 | 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]))... |
7a065ed8fd437be1ac60a8a9b4fa802c7c6c390836a8f48569072eb4d0a6a5e5 | Python | 1,304 | 52 | # %%
from matplotlib import pyplot as plt
import pandas as pd
import seaborn as sns
import numpy as np
# %%
pids = [
303, 309, 310, 312,
314,315,317,318,319,320,
321,322,323,324,326,327,328,329,330,
332,333,334,335,336,
341,342,404,406,407,408
]
flist = [f'p{i}_log.csv' for i in pids]
ddf_l... |
80ccf7da2ca653f61aa4ff12fb771f79ef922bb15f455564e7ac064aa9e4a8b7 | Python | 1,304 | 25 | import pytest
@pytest.mark.parametrize("test_num", [1, 2, 3, 4, 5, 6,7, 8, 9, 10, 11, 12, 13, 14, 15])
def test_cli_simulation_regressions(run_simulation_testset, expected_output_data,
expected_line_counts, test_num):
_, observed_final_lines, observed_line_counts = run_simulatio... |
b679b4555fb9e75f1adaa2819dab9ed9c1dcf7c3682e8a9a88c33f67e99e6c52 | Python | 1,304 | 34 | import torch
import torch.distributions as td
import torch.nn as nn
from networks.ToCM.utils import build_model_snn
class DenseModel(nn.Module):
def __init__(self, in_dim, out_dim, layers, hidden, activation="nn.ELU"): # TODO activation=nn.ELU
super().__init__()
self.model = build_model_snn(in... |
7e3a55f04a7756d2cb58023cdb4ac07be08c9165736db7211bff46be09dd2fa4 | Python | 1,305 | 30 | # License: GNU Affero General Public License v3 or later
# A copy of GNU AGPL v3 should have been included in this software package in LICENSE.txt.
# for test files, silence irrelevant and noisy pylint warnings
# pylint: disable=no-self-use,protected-access,missing-docstring
from unittest import TestCase
from antism... |
b26c1f5af377dc1e9480b6a029a050925953b86026ed689aabceccf67c6ef20f | Python | 1,305 | 47 | import pytest
from pandas import (
DatetimeIndex,
date_range,
)
import pandas._testing as tm
@pytest.mark.parametrize("tz", [None, "Asia/Shanghai", "Europe/Berlin"])
@pytest.mark.parametrize("name", [None, "my_dti"])
@pytest.mark.parametrize("unit", ["ns", "us", "ms", "s"])
def test_dti_snap(name, tz, unit):... |
b5f7d605e1b8bb275fd10f41132f077562bb90aa65365fdc35f490a956dc4fc6 | Python | 1,305 | 41 | import numpy as np
import tensorflow as tf
def compute_entropy_pretrain(X: np.ndarray, n_bins: int = 20) -> float:
"""
Compute a dataset-level entropy proxy for input complexity.
This is computed ONCE before training (pre-training), not iteratively.
"""
eps = 1e-12
entropies = []
for j in r... |
9ad820783ea06d27f9e7c7e7554bf140c1aba72de5134b4349685c182a7b256b | Python | 1,306 | 39 | class IndexesGenerator:
def __init__(self, size: int, step: int, position: str = "last"):
self.size = size
self.step = step
if position == "first":
self.behind = 0
self.ahead = self.size - 1
elif position == "middle":
self.behind = self.size // 2
... |
5ff487b6df67fd6cc0fc2db03e54491d14bc2d49a334d9abdbe5cbe80b3325dd | Python | 1,307 | 44 | import pytest
import pandas._testing as tm
from pandas.core.arrays import DatetimeArray
class TestAccumulator:
def test_accumulators_freq(self):
# GH#50297
arr = DatetimeArray._from_sequence(
[
"2000-01-01",
"2000-01-02",
"2000-01-03",
... |
3f5bd8bbd08a87a07e4527bed7ce1d77674ab553af1064bb49c5732247829b7a | Python | 1,308 | 50 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Sep 1 18:04:35 2019
@author: charleshen
fragments number of 86 fragments: https://www.rdkit.org/docs/source/rdkit.Chem.Fragments.html
ref: https://github.com/rdkit/rdkit/blob/master/Data/FragmentDescriptors.csv
"""
from rdkit.Chem import Fragments
fr... |
4284d76c28aa8cae2d0431d46ead5328fa7436ba1891e85e16346af95c65b0fd | Python | 1,310 | 45 | import numpy as np
import pytest
import pandas as pd
from pandas import (
DatetimeIndex,
Index,
)
import pandas._testing as tm
dtlike_dtypes = [
np.dtype("timedelta64[ns]"),
np.dtype("datetime64[ns]"),
pd.DatetimeTZDtype("ns", "Asia/Tokyo"),
pd.PeriodDtype("ns"),
]
@pytest.mark.parametrize("... |
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