sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
f2f29d0161feecdb5a3c6ae1b1b5ae3e0c6e33c04e5a5d5bd18431431746094e | Python | 1,165 | 47 | """
Tests to make sure the example SeqData object works
"""
import os
import eugene as eu
import pytest
from pathlib import Path
HERE = Path(__file__).parent
@pytest.fixture
def sdata():
sdata = eu.datasets.random1000()
eu.pp.ohe_seqs_sdata(sdata)
eu.pp.reverse_complement_seqs_sdata(sdata)
eu.pp.tra... |
5d6653c40825ed7c097b58bf553ddb5669b8f5f29f2934b1280b3b6828071aea | Python | 1,166 | 28 | from gluoncv.auto.tasks import ImageClassification
import autogluon.core as ag
from nose.tools import nottest
IMAGE_CLASS_DATASET, _, IMAGE_CLASS_TEST = ImageClassification.Dataset.from_folders(
'https://autogluon.s3.amazonaws.com/datasets/shopee-iet.zip')
def test_torch_image_classification():
from gluoncv.a... |
912427dd827711a6f3bca3a06830da3ecd77e6e050163a5a548dd14fae202805 | Python | 1,166 | 37 | import sys
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from ._domain import Domain
from ._hoverlabel import Hoverlabel
from ._insidetextfont import Insidetextfont
from ._legendgrouptitle import Legendgrouptitle
from ._marker import Marker
from ._outsidetextfont import Outsidetextfont
... |
9efe1d5dc6551a55dea045a57870fef2d9683aae97aabdcad2ba53d8bc2e4326 | Python | 1,166 | 43 | import sys
from openbabel import openbabel, pybel
def main():
if len(sys.argv) == 3:
process(sys.argv[1], sys.argv[2])
else:
print("Usage: convert_pdbqt_to_sdf.py <input-pdbqt-file> <output-sdf-file>")
exit(1)
def add_property(mol, prop_name, prop_value):
newData =... |
fbbcfdb7bbc298836a789b20dfdbcc95e5f599a724544be69aa1f2a200cb74c7 | Python | 1,166 | 38 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"]["motif_width"] = 13
msp.architecture["motif_model_spec"]["motif_feature... |
132671a246938dc50138ff87890e3ea157688f57188acdf38de57cd4dfe508f0 | Python | 1,167 | 32 | from os.path import abspath, join
def run():
from spitfire.chemistry.mechanism import ChemicalMechanismSpec
from spitfire.chemistry.tabulation import build_nonadiabatic_defect_eq_library
import spitfire.chemistry.analysis as sca
test_xml = abspath(join('tests', 'test_mechanisms', 'h2-burke.yaml'))
... |
dc6e138411b31f8450fdadeb8d193cedfa49d54936bf61fa3579de8800864021 | Python | 1,167 | 40 | import numpy as np
from gym.spaces import Discrete
def test_space_legacy_pickling():
"""Test the legacy pickle of Discrete that is missing the `start` parameter."""
legacy_state = {
"shape": (
1,
2,
3,
),
"dtype": np.int64,
"np_random": np.r... |
a8152f842520b447aa3cbe6ea6dd95acdde3da1cf38a02e5ee111d965967a183 | Python | 1,168 | 39 | import math
import torch
import torch.nn as nn
class PositionalEncoding(nn.Module):
"""
from the tutorial https://pytorch.org/tutorials/beginner/transformer_tutorial.html
Input: (L, N, C)
Output: (L, N, C)
"""
def __init__(self, d_model, dropout=0.1, max_len=5000):
super(PositionalE... |
ab2deea50cd287001b40b003084054ea7cab088881ba955b5b9b71b7b473fa70 | Python | 1,168 | 39 | """Utilities for working with functions, inlcuding input / outputs."""
###################################################################################################
###################################################################################################
def resolve_aliases(kwargs, aliases):
"""Ch... |
a495082179f63dfab88a53acd9f8f5f578c120f8e15cd971022e2b2ad9ad7991 | Python | 1,169 | 42 | """add label, requires_path_in_url and requires_path_in_header_named columns to interactivetool_entry_point
Revision ID: 8a19186a6ee7
Revises: ddbdbc40bdc1
Create Date: 2023-11-15 12:53:32.888292
"""
from sqlalchemy import (
Boolean,
Column,
Text,
)
from galaxy.model.migrations.util import (
add_col... |
c66929ea02611650efcb5ca562aa6f0359be288b73a29b21ec2e499cb8c775b0 | Python | 1,170 | 32 | from os.path import abspath, join
def run():
from spitfire.chemistry.mechanism import ChemicalMechanismSpec
from spitfire.chemistry.tabulation import build_nonadiabatic_defect_bs_library
import spitfire.chemistry.analysis as sca
test_xml = abspath(join('tests', 'test_mechanisms', 'h2-burke.yaml'))
... |
13195772b2a05236e1e4f191f85bea27e08674389130b81d7912738439bc6868 | Python | 1,171 | 33 | import setuptools
with open("README.md", "r", encoding="utf-8") as fh:
long_description = fh.read()
setuptools.setup(
name="gradient-accumulator",
version="0.3.1",
author="André Pedersen and David Bouget",
author_email="andrped94@gmail.com",
description="Package for gradient accumulation in Te... |
2559531e8e6d6c4fe5fb33e3b4da8c64bd9cc680e2f602a8a2c5d9c1e56966fb | Python | 1,171 | 40 | """Tests for minimal static export helpers."""
from __future__ import annotations
from pathlib import Path
import torch
from torch import nn
import torchlens as tl
def test_export_html_minimal_self_contained_without_viewer(tmp_path: Path) -> None:
"""tl.export.html should write pan/zoom/hover HTML without vie... |
445a666a0242e6c485b0ad8ceda4b36de0a64b27958a17b70267c6cc9358ffd6 | Python | 1,171 | 33 | """
Integration tests configuration.
Auto-applies ensure_datasets_ready fixture to all tests in this folder.
This solves the timing issue where imports trigger dataset loading before
the fixture has a chance to run.
"""
import os
import pytest
@pytest.fixture(autouse=True, scope="session")
def _auto_en... |
65055ae8c0fe98d27c0ee047fc8dfb6c470362770ef97965faf0d1b2f805c3da | Python | 1,171 | 35 | #### Modified from TAURUS Lee et al., Nat Methods 2019 (https://github.com/dixonlab/Taurus-MH)
import sys
fn=sys.argv[1]
dfh=open(fn,'r')
dfh.readline()
rfh=open(fn+'_man_dedupped.txt','w')
stat=open(fn+'_Aligned_Fragment_count.txt','w')
pre=''
duplicate=0
total=0
First_aligned=0
Second_aligned=0
Used_Frag=0
for i in... |
f69404414017bf2aba5ac409bf5ff999b9cb66cc39d987f594b5b1f40769ce3c | Python | 1,171 | 30 | class EarlyStopping():
"""
Early stopping to stop the training when the loss does not improve after
certain epochs.
"""
def __init__(self, patience=5, min_delta=0):
"""
:param patience: how many epochs to wait before stopping when loss is
not improving
:param m... |
bef16b2ae24bd3917539a662b52c8f3b77c4ed2b97f952d62baffa07bef18a80 | Python | 1,172 | 43 | from anndata import AnnData
def annotation(
adata: AnnData,
label_list: list[str],
use_label: str = "leiden",
copy: bool = False,
) -> AnnData | None:
"""\
Adding annotation for cluster
Parameters
----------
adata
Annotated data matrix.
label_list
List of the l... |
552506e8f19121c3f94e39ccd181e41c643c4685c1d8c3f7e828095fbe006d74 | Python | 1,173 | 38 | '''
str(np.ndarray(stuff)) returns a different string depending on numpy version.
develop a standard way to print arrays and multidimensional arrays which
will never change.
'''
import numpy as np
def standardNumpyText(data):
"""return a numpy array as a standard string regardless of numpy version."""
if isi... |
55fa3b8863667541077df2b2093eb8257b9966c056b9a9e25314b4a00023d225 | Python | 1,173 | 49 | #!/usr/bin/env python3.4
import sys
import getopt
def usage():
print('''Useage: python script.py [option] [parameter]
-l/--list input the filter bed list
-o/--results the results
-h/--help show possible options''')
#######################
opts, args = getopt.getopt... |
6a7f86a891c683ff5158f80d5373c29d44516f9b15ead5ff7de512c317512492 | Python | 1,173 | 33 | # Copyright 2019 Novartis Institutes for BioMedical Research 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... |
721a37cbed0ac6718cb75c60c3deefab5c5e5455582bcea3687af7241c08a0d9 | Python | 1,173 | 27 | # Copyright 2018 The Sonnet Authors. All Rights Reserved.
#
# 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 l... |
0a55d81dc5c8dff99a23bf6bf7d6e542294b3a85dbe3a4ae79c9fe25c2c581e2 | Python | 1,174 | 35 | __version__ = "0.6.0dev"
__author__ = "PyTorchLightning et al."
__author_email__ = "name@pytorchlightning.ai"
__license__ = "Apache-2.0"
__copyright__ = f"Copyright (c) 2020-2021, {__author__}"
__homepage__ = "https://github.com/PyTorchLightning/lightning-bolts"
__docs__ = "PyTorch Lightning Bolts is a community contri... |
0f0cf759ce457900b872001cb74d37f663ba9d191c05bcc12a09c4af54c588d5 | Python | 1,174 | 45 | """Add unique constraint to user_role_association
Revision ID: 349dd9d9aac9
Revises: 1cf595475b58
Create Date: 2024-09-09 16:14:58.278850
"""
from alembic import op
from galaxy.model.migrations.data_fixes.association_table_fixer import UserRoleAssociationDuplicateFix
from galaxy.model.migrations.util import (
c... |
c7e7a02f3c9357fe683b0874d25428e9deebcc1ed6cd7fca4a369e93b38618bf | Python | 1,174 | 32 | from typing import List
from carbonserver.api.errors import NotAllowedError, NotAllowedErrorEnum, UserException
from carbonserver.api.infra.repositories.repository_experiments import (
SqlAlchemyRepository,
)
from carbonserver.api.schemas import ExperimentReport
from carbonserver.api.services.auth_context import A... |
f7855be7650a87819b8696dd0045342b822906fa806d58e1c773e8a8e04075ac | Python | 1,174 | 38 | from typing import Tuple
import torch
from torch import Tensor
class IRFFT2DTransform:
"""Inverse 2D Fast Fourier Transform (IRFFT2D) Transformation.
This transformation applies the inverse 2D Fast Fourier Transform (IRFFT2D)
to an image in the frequency domain.
Input:
- Tensor of shape (C,... |
a10057ccb18cadbe6ae2a109478198def0ee5c2a025ccf23b1f786689f0d232b | Python | 1,175 | 34 | from modular_splicing.psams.motif_types import motifs_types
from modular_splicing.utils.construct import construct
def get_motif_names(motif_names_source):
"""
Get the names of the motifs for the given motif names source.
"""
from modular_splicing.eclip.test_motifs.names import peak_names
psam_na... |
f1327d3654edac69eb498b6f45040e56a957c007e40117868de2f8a676c4f5f7 | Python | 1,176 | 54 | import os
from enum import Enum, auto
# scales of parameters
class EnumTrans(Enum):
transNone = 0
transLog = auto()
transLogit = auto()
transLogitAndSample = auto()
# indices of model parameters
class EnumModelParams(Enum):
EmissionRate = 0
ParticleDensity = auto()
ParticleSig = auto()
... |
41e929fe958bb25dde6ccf69db0d26de5fe1bea5d5e8b024d8da689351798fd5 | Python | 1,177 | 38 | """
Generate source estimate and BEM solution.
"""
import sys
sys.path.append('..')
import mne
from config import fname
import argparse
# Be verbose
mne.set_log_level('INFO')
# Handle command line arguments
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('subject', type=int, metavar='sub###'... |
41e9dd9cca87f054ca92f0ede4c08892e7dc0cb4caa9155d405b33f22893cc2e | Python | 1,177 | 43 | """Root __init__ of the gym module setting the __all__ of gym modules."""
# isort: skip_file
from gym import error
from gym.version import VERSION as __version__
from gym.core import (
Env,
Wrapper,
ObservationWrapper,
ActionWrapper,
RewardWrapper,
)
from gym.spaces import Space
from gym.envs impo... |
59e907b1c9cbf2536217a451b986fe0e23f287faf294f3c6906e103ade7c10be | Python | 1,177 | 36 | from __future__ import annotations
import pytest
from pybind11_tests import unnamed_namespace_a as m
from pybind11_tests import unnamed_namespace_b as mb
XFAIL_CONDITION = (
"(m.PYBIND11_INTERNALS_VERSION <= 4 and (m.defined___clang__ or not m.defined___GLIBCXX__))"
" or "
"(m.PYBIND11_INTERNALS_VERSION ... |
b12e2df80ffe39fcb46d35618495750007a0be0234e3de3b6e7d9bcab906a8e9 | Python | 1,177 | 38 | """Minify a JSON file and write it as a C++ raw string literal .inc file.
Usage: minify_json_to_inc.py <input.json> <output.inc>
The output file contains a single raw string literal expression suitable for
use with #include inside a C++ variable declaration:
static const char kFoo[] =
#include "output.inc"
... |
d30c78cb9b51d67d324afcc834a5388caec892c38a946efa915110df1308caa3 | Python | 1,177 | 37 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
This script:
Extracts face encodings from training images.
Saves image features, labels, and addresses into a Pandas DataFrame.
Stores this DataFrame in a pickle file.
"""
import pickle
import glob
import face_recognition
import pandas as pd
training_folder = './fea... |
af14294ba61768ac32b5ac4958f1a63a3c940b35a326b6d4730ed35b4d5eeabe | Python | 1,178 | 39 | import numpy as np
from permacache import permacache, stable_hash
from modular_splicing.data_for_experiments.standardized_sample import (
standardized_sample_memcache,
model_motifs_on_standardized_sample,
)
@permacache(
"modular_splicing/other_experiments/motif_positioning/compute_motif_positioning_relat... |
bd5e10cfcf7681d93e99cdce9db151fdaab5dc481a00de4baea64bf8abe57c69 | Python | 1,178 | 43 | """SimCLR Model"""
# Copyright (c) 2020. Lightly AG and its affiliates.
# All Rights Reserved
import warnings
import torch
import torch.nn as nn
from lightly.models.modules import SimCLRProjectionHead
class _SimCLR(nn.Module):
"""Implementation of SimCLR used by the command-line interface.
Provides backw... |
24299c0217d8d5fe844137c585b5a42f8afe433f7cd3e53c152f20ed6fb2b56c | Python | 1,179 | 28 | import numpy as np
from .metrics._multiclass_classification import calculate_auroc, calculate_aupr
from .metrics._regression import calculate_mse, calculate_pearsonr, calculate_spearmanr
def evaluate_model(y_test, pred, task, verbose=True):
if (task == "regression"):
mse = calculate_mse(y_test, pred)
... |
d6984d88800cff342d3e9fc08a90218754ec6a4581d2dedb84cb5ee32dd1ea21 | Python | 1,179 | 42 | from pathlib import Path
from typing import Literal
from pydantic import PositiveInt
from neurogym.config.base import ConfigBase
class MonitorPlotConfig(ConfigBase):
"""Plotting configuration during monitoring.
Attributes:
create: Whether to generate plots.
step: Number of steps to visualiz... |
ec905f98eabc249d9780f8559a1f809314b70ad40867a6eb9e6fede24e8ad108 | Python | 1,179 | 52 | from __future__ import annotations
import os
import pytest
import env # noqa: F401
from pybind11_tests import eval_ as m
def test_evals(capture):
with capture:
assert m.test_eval_statements()
assert capture == "Hello World!"
assert m.test_eval()
assert m.test_eval_single_statement()
... |
1386e04dd7e9573c35de24fd89d402878fbf6a2b556bcefe05e0373611319201 | Python | 1,180 | 27 | # coding: utf-8
# Name: logger2file
# Author: tyler
# Data: 2022/4/19
import logging
def init_logger(log_file=None, log_file_level=logging.NOTSET):
log_format = logging.Formatter("[%(asctime)s %(levelname)s] %(message)s") # 设置输出格式
logger = logging.getLogger()
logger.setLevel(logging.INFO) ... |
2a400e844d1800c405f333d507998e4eb26ac9fbb830ee0ba9baa92fae7af33b | Python | 1,180 | 25 | """
Transformers for autoregressive normalizing flows in PyTorch.
All the layers defined in this module are invertible and implement an
``inverse()`` method (not to be comfused with the ``Tensor``'s ``backward()``
method which backpropagate the gradients).
The forward propagation of the modules here return both the t... |
53615c80e4ed61c7a56687a239bd6880e19d09e9b9c0dec41f65778874f0d8b4 | Python | 1,180 | 42 | # Copyright (c) 2021. Lightly AG and its affiliates.
# All Rights Reserved
import numpy as np
from PIL import ImageOps
from PIL.Image import Image as PILImage
class RandomSolarization(object):
"""Implementation of random image Solarization.
Utilizes the integrated image operation `solarize` from Pillow. Sol... |
54ef9c08d2937a0ca6739670269806fe7b22766b9f4cd865a7b4027c142a6fbb | Python | 1,180 | 45 | """Add unique constraint to user_group_association
Revision ID: 56ddf316dbd0
Revises: 1fdd615f2cdb
Create Date: 2024-09-09 16:10:37.081834
"""
from alembic import op
from galaxy.model.migrations.data_fixes.association_table_fixer import UserGroupAssociationDuplicateFix
from galaxy.model.migrations.util import (
... |
77da44120f9d94a89cdaee01bebd7343051f75ffd313c422f380c1af1ee75c6c | Python | 1,180 | 49 | """
test_metadata.py
Unit tests for metadata.
"""
import unittest
import pathlib
import pandas as pd
from fused_org_ephys import FusedOrgSpikes
################################
class TestMetdata(unittest.TestCase):
def setUp(self):
# default dir to tc metadata
metadata_path = pathlib.PurePat... |
8e3dc51c4bc1404b9e7d9f3fbdc00cd440826e8833cef8c7f22be706117f2af1 | Python | 1,180 | 45 | # All these transforms are taken from brainbox but copy-pasted because prednet requires older packages not
# compatible with brainbox :(
import torch
class BBTransform:
@property
def hyperparams(self):
hyperparams = {"name": self.__class__.__name__}
return hyperparams
class ClipGrayscale(B... |
967282088b6778093e5f2aa38911ec7920bd96b15b305c03f3adae161ce41017 | Python | 1,180 | 38 | # Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
"""Feather data format reader
After https://arrow.apache.org/docs/python/_modules/pyarrow/feather.html
"""
from pyarrow.lib import FeatherReader, DictionaryType
import numpy as np
from .._data_obj import Dataset, Factor, Var
class Reader(FeatherReader):
... |
17a07e8aa9d02a82863f11e08806c0a47f68260581c8c37876c8ddb10c218f0a | Python | 1,181 | 45 | """Add unique constraint to group_role_association
Revision ID: 9ef6431f3a4e
Revises: 13fe10b8e35b
Create Date: 2024-09-09 15:01:20.426534
"""
from alembic import op
from galaxy.model.migrations.data_fixes.association_table_fixer import GroupRoleAssociationDuplicateFix
from galaxy.model.migrations.util import (
... |
6adbf6710193a481e4afc8507b9770578c969e7962101fb68d0dd476d142cc5e | Python | 1,181 | 43 | """
This code demonstrates how to perform measurements on small ranges of sweeps.
"""
# import the pyabf module from this development folder
import os
import sys
PATH_HERE = os.path.abspath(os.path.dirname(__file__))
PATH_SRC = os.path.abspath(PATH_HERE+"/../src/")
PATH_DATA = os.path.abspath(PATH_HERE+"/../data/abfs/... |
7d9dede61f4f617ce2085878b44df5b7632d4dbbf030ca802f399b7c86d13c9e | Python | 1,181 | 34 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Project information -----------------------------------------------------
# https://www.sphinx-doc.org/en/master... |
fc442328dcb7a742d94537fafbca193f573fb688e00a2d21aac7fab54fcb0d6e | Python | 1,181 | 42 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.batch_size = 10
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"] = dict(
type="AdjustedMotifModel",
model_to_adjust_spec=dict(
type="PS... |
351ded47512f7c751c3c917c958031969f36fc16584f072e7da79db718b575a7 | Python | 1,182 | 38 | import pytest
from PCA.src.utils import *
def test_img_to_casorati_matrix():
# Create a sample image and mask
img = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])
mask = np.array([[1, 0], [1, 1]])
# Call the function with the sample image and mask
casorati_matrix = img_to_casorati... |
0156d9b03578671c2a9d1477843b3161f2ecc1b3b5ce053165ee25a13ecea59a | Python | 1,183 | 38 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"]["motif_width"] = 13
msp.architecture["motif_model_spec"]["motif_feature... |
433b59706c69d67d495a9fc7c81e82d26e3030e6536c413d287a2177756d77d9 | Python | 1,183 | 47 | """add project tokens
Revision ID: caf929e09f7c
Revises: 7ace119b161f
Create Date: 2024-07-25 19:51:43.046273
"""
import sqlalchemy as sa
from alembic import op
from sqlalchemy.dialects.postgresql import UUID
# revision identifiers, used by Alembic.
revision = "caf929e09f7c"
down_revision = "7ace119b161f"
branch_la... |
ad72b142e307b300a987edafcd352e381f7b0322ec20895133cb0b6125bf288c | Python | 1,183 | 44 | """add_utilization_metrics_to_emissions
Revision ID: 20251119_add_utilization
Revises: 3212895acafd
Create Date: 2025-11-19 18:52:00.000000
"""
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision = "20251119_add_utilization"
down_revision = "3212895acafd"
branch_labels =... |
fe3803fe6027e73c879db15b11372417149626639ec9eee085a5eba41c1fe944 | Python | 1,183 | 43 | import numpy as np
from numpy import testing as npt
from tns.astrocyte import context as tested
def _input_params():
return {
'endfeet_targets': np.array([[0., 0., 0.], [1., 1., 1.]]),
'space_colonization': {
'point_cloud': np.array([[2., 0., 0.], [2., 1., 1.]]),
'kill_dist... |
8e224dfc848435b929dc9dc780d6cea5b8d89b2b4907d5edf7ada23cb74dfc7a | Python | 1,184 | 37 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
try:
from ray import tune
assert hasattr(tune, "get_context") # verify Ray>=2.41 Tune API, also required by tuner.run_ray_tune
except (ImportError, AssertionError):
tune = None
def on_fit_epoch_end(trainer):
"""Report training metr... |
4cca631077dedf998f80a6b3af1c377518325b5cec5ecb12d993030c2ac23f59 | Python | 1,185 | 39 | import glob
import os
import os.path as osp
from setuptools import find_packages, setup
from torch.utils.cpp_extension import BuildExtension, CUDAExtension
this_dir = osp.dirname(osp.abspath(__file__))
_ext_src_root = osp.join("pointnet2_ops", "_ext-src")
_ext_sources = glob.glob(osp.join(_ext_src_root, "src", "*.cpp... |
fe0ee6acfed0c806db175a8600e7cb180cf8fdf19822fd8a67abc56fad6db0a0 | Python | 1,185 | 34 | """Helpers for emitting deprecation warnings."""
from __future__ import annotations
import warnings
def warn_deprecated(
name: str, alternative: str, removed_in: str, stacklevel: int = 3
) -> None:
"""Warns that ``name`` is deprecated and will be removed.
Uses ``FutureWarning`` rather than ``Deprecatio... |
40b5626ea7429a2f653dfea83e213e279dcbe61bd5bd4c927a3aaab46f42932f | Python | 1,186 | 32 | # __init__.py
# Copyright (C) 2013 Bastian Venthur
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program i... |
a27532fdcc1306f6c884b0f140f5f57c9a21c8d59cf7cb0c52bfd2ac06e0fe64 | Python | 1,186 | 36 | """
DataProvider related exceptions.
"""
class InvalidDataProviderSource(TypeError):
"""
Raised when a unusable source is passed to a provider.
"""
def __init__(self, source=None, msg=""):
msg = msg or f"Invalid source for provider: {source}"
super().__init__(msg)
class NoProviderAv... |
9ed0a8f16e516d89faaa7adb9d44cea2607043474e1d18a2372f60379169833a | Python | 1,187 | 44 | import sys
if sys.version_info >= (3, 9):
from importlib.resources import files
else:
from importlib_resources import files
from ._nmodl import *
RESOURCE_DIR = "ext/example"
def list_examples():
"""Returns a list of examples available
The NMODL Framework provides a few examples for testing
R... |
ab4414b8941fb6bc792c96b9f7eaec9d54587efae36422a167dd794b30b54a55 | Python | 1,187 | 36 | """Shared machinery for the real-model tree (testing MEMO; lanes P04+B1).
Registers the realism SELECTION markers (memo D8: orthogonal to the
smoke/heavy/slow/rare cost tiers). The pyproject marker declarations are
P03's single-owner territory (declared once in its first commit); this
in-tree registration keeps the tr... |
598aef7b1f0e41a8dbec48eda0f8165c704fc282bff5e422f47802c6a8e15fb4 | Python | 1,188 | 38 | import sys
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from ._caps import Caps
from ._colorbar import ColorBar
from ._contour import Contour
from ._hoverlabel import Hoverlabel
from ._legendgrouptitle import Legendgrouptitle
from ._lighting import Lighting
from ._lightposition import... |
94a503ba4f5a6357da4479a477e025faa0f16c460b5e0dcda3dd75eb965b1963 | Python | 1,188 | 42 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"]["motif_width"] = 13
msp.architecture["motif_model_spec"]["motif_feature... |
9874a917153d1053b3cf9e824ab2ab7edf8218d302efd647d10e0ffdfcef977f | Python | 1,188 | 42 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"]["motif_width"] = 13
msp.architecture["motif_model_spec"]["motif_feature... |
bcd24b86bb1b343d068a1d55a198a51f56d3679995ed700179556d7a03b3fffe | Python | 1,188 | 43 | import torch
import torch.nn as nn
from models.dymn.dy_block import DynamicConv
def get_values(x):
return (x, x) if isinstance(x, int) else x
def receptive_field_cnn(model, spec_size):
kernel_sizes = []
strides = []
dilation = []
def conv2d_hook(obj, input, output):
kernel_sizes.append(... |
dd0d91a1c485307375fc0faeca046e916e93af5d8297c81c73310ceb8bc61b97 | Python | 1,188 | 43 | """
--- Distance measures ---
"""
import numpy as np
from scipy import stats
def minkowski(p1,p2,k):
'''Minkowski distance between points p1 and p2
if k equals 1, it is a Manhattan (cityblock) distance
if k equals 2, it is a Euclidean distance
'''
if isinstance(p1, np.ndarray) and isinstance(p2... |
35ba1c755fda26340c66cf43259ad2b694e7905670fcaf1220210cc1a96c3ea2 | Python | 1,189 | 35 | """Private keys for the security serializer."""
from cryptography.hazmat.backends import default_backend
from cryptography.hazmat.primitives import serialization
from cryptography.hazmat.primitives.asymmetric import padding, rsa
from kombu.utils.encoding import ensure_bytes
from .utils import reraise_errors
__all__ =... |
47fdc3a666bac4a6abfb7043bf6f5bb8e753ec5cdc8e54f872c951d104e44532 | Python | 1,189 | 49 | from MarkovModels import common
from MarkovModels.BeattieModel import BeattieModel
import matplotlib.pyplot as plt
import argparse
import numpy as np
import pandas as pd
import os
from matplotlib.gridspec import GridSpec
from matplotlib import rc
rc('font', **{'family': 'serif', 'serif': ['Computer Modern'], 'size'... |
dc27db9556a76b6fb8edd8147ba21a8cbae9e67def8a119d9af1ed83ddd9f59f | Python | 1,189 | 56 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
import tpot
import pandas as pd
import numpy as np
from tpot import TPOTRegressor
from sklearn.model_selection import TimeSeriesSplit
from sklearn.model_selection import train_test_split
# In[2]:
features = pd.read_csv('SCADA-FINAL-1daybiogas-lags.csv')
features['T... |
affa380e0b08eb2bbe70c853c64e5ae6273c2914b1d2e0f1c26c30d8a177832b | Python | 1,191 | 44 | import tensorflow as tf
from tensorflow.keras.callbacks import Callback
from codecarbon import EmissionsTracker
"""
This sample code shows how to use CodeCarbon as a Keras Callback
to save emissions after each epoch.
"""
class CodeCarbonCallBack(Callback):
def __init__(self, codecarbon_tracker):
self.co... |
f902924bd5c5822b574dfe24cd3906a0fb310cfb5222093a5bb8c8ea535e2425 | Python | 1,191 | 39 | import tensorflow as tf
from cvnn import logger
import cvnn.initializers as initializers
from pdb import set_trace
import sys
shape = (3, 3, 3)
dtype = tf.dtypes.float32
def compare(key, tf_init, my_init):
tf_version = tf_init(seed=100)(shape=shape, dtype=dtype)
my_version = my_init(seed=100)(shape=shape, dt... |
6f59dbc0e65bb6957ae97670f4b116b7986ec45f19eb747f97bc336858113f9b | Python | 1,192 | 45 | import numpy as np
def gaussian_preprocess_filter(
orig_vox,
orig_spacing,
sample_spacing=None,
param_beta=0.98,
mode="nearest",
separate_slices=False
):
from scipy.ndimage import gaussian_filter
# If no sample spacing is provided, assume original spacing. Not... |
8f2af6a11c5a118c18f5429a390cb985fb5942518381fde05f48b814a530f811 | Python | 1,192 | 39 | from __future__ import annotations
import unittest
from coco_froc_analysis.utils import build_gt_id2annotations
from coco_froc_analysis.utils import build_pr_id2annotations
class TestId2Annotation(unittest.TestCase):
def setUp(self):
self.gt = {
'images': [{'id': 1}, {'id': 2}],
... |
4194c4d46d65fdf0b5833f5e9f66827d3a1436fedbd09c34cb9230057884f87f | Python | 1,193 | 43 | from sklearn.metrics import roc_auc_score, roc_curve
import numpy as np
import matplotlib.pyplot as plt
def auc(scores, contributions):
"""
function to obtain the AUC values based on
ground truth and feature attribution scores
Args:
scores (_type_): Feature attribution scores
contribu... |
6ba68e140c486381b97d9c58d799d0704883e728f636303ebc0a8fa5fc5cb114 | Python | 1,193 | 34 | from local_extractor.states.DL import DelhiExtractor
from local_extractor.states.GA import GoaExtractor
from local_extractor.states.HR import HaryanaExtractor
from local_extractor.states.KA import KarnatakaExtractor
from local_extractor.states.KL import KeralaExtractor
from local_extractor.states.MH import MaharashtraE... |
8ad383668f7cad13f99930936c64fb6aa641c3270cfe60d8fd2299bc6528c16d | Python | 1,193 | 42 | import numpy as np
import torch.nn as nn
from .sparsity import SparseLayer
from .spatially_sparse_by_channel import SpatiallySparseByChannel
class SpatiallySparseAcrossChannels(SparseLayer, nn.Module):
"""
Like SpatiallySparseByChannel but uses the same threshold for all channels.
"""
def __init__(... |
c121fda100b70e65bf93fd8289dce369fe9ba444310cb15f1a526faded2b11fc | Python | 1,193 | 56 | import torch as ch
import cox
from cox import store
# dog (117), cat (5), frog (3), turtle (5), bird (21),
# monkey (14), fish (9), crab (4), insect (20)
RESTRICTED_IMAGNET_RANGES = [(151, 268), (281, 285),
(30, 32), (33, 37), (80, 100), (365, 382),
(389, 397), (118, 121), (300, 319)]
CKPT_NAME =... |
d9b50e0b0ebab5428fefbe6918f7794938f452646ec2f06d2390a063c1de1ca2 | Python | 1,193 | 28 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Tests for random projection"""
import unittest
from sknetwork.data.test_graphs import test_graph, test_bigraph, test_digraph, test_disconnected_graph
from sknetwork.embedding import RandomProjection
class TestEmbeddings(unittest.TestCase):
def test_random_projec... |
4dc1c98f5b4872bf1d0d205b9c0823abb04b59004596bd40caaed67751a48231 | Python | 1,194 | 41 | # Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
from contextlib import ContextDecorator
import os
import sys
IS_OSX = sys.platform == 'darwin'
IS_WINDOWS = os.name == 'nt'
if IS_OSX:
from . import macos as c
else:
from . import dummy_os as c
class ActivityContext(ContextDecorator):
"""Context d... |
2754b4896d35638a42e01ed7918d5c80ed0294fc1d8ca09e3afcf8ff45dbe571 | Python | 1,195 | 39 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"]["motif_width"] = 13
msp.architecture["motif_model_spec"]["motif_feature... |
307e3a1e05a8906ca1d4903ec60baa5698f57b4791ad3b2e3d6c908734963db7 | Python | 1,195 | 47 | from setuptools import setup, find_packages
from distutils.command.install import install
import os
HOME = os.path.expanduser('~')
# this is where the non-python dependencies will be installed.
DEFAULT_INSTALL_DIR = os.path.join(HOME, 'split_seq_reqs')
class CustomInstall(install):
"""Customized setuptools ins... |
3ae6e395d1c91f528613508ab7591153e439e6479fb474f779ad58a0bd1949ca | Python | 1,195 | 55 | import dis
import array
import collections
try:
import html
except ImportError:
html = None
from setuptools.extern import six
from setuptools.extern.six.moves import html_parser
__metaclass__ = type
OpArg = collections.namedtuple('OpArg', 'opcode arg')
class Bytecode_compat:
def __init__(self, code):
... |
3e466f205f3349a61f7cde7171c41b24e8d016be432e75dafacff7a1c9dc5030 | Python | 1,195 | 36 | """
core.metrics — Balanced accuracy and PPV/NPV.
"""
from __future__ import annotations
import numpy as np
def balanced_accuracy(y_true, y_pred) -> float:
"""Balanced accuracy = mean of per-class recall."""
y_true = np.asarray(y_true, int)
y_pred = np.asarray(y_pred, int)
n0 = int((y_true == 0).sum()... |
3e6b1239f336d430ee09ca52c51e1b0eddd699ca0c654619e683f063a46cbaf0 | Python | 1,195 | 39 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"]["motif_width"] = 13
msp.architecture["motif_model_spec"]["motif_feature... |
dfbc84d37e89baf0fb69f46dee94011a401ab2923e77224a7047f139a0b284df | Python | 1,196 | 41 | #!/usr/bin/env python
"""
Input: molecular input file.
Output: Molecule file with removed ions and fragments.
Copyright 2013, Bjoern Gruening and Xavier Lucas
"""
import argparse
from openbabel import openbabel, pybel
openbabel.obErrorLog.StopLogging()
def parse_command_line():
parser = argparse.Arg... |
a0e0f3471ff2d5546f99c0d4ac8a854b3d91f8fc365054c014c28c81c4e668ea | Python | 1,197 | 27 | import chcochleagram
cochleagram_1 = {'rep_type': 'cochleagram',
'signal_size':40000,
'sr':20000,
'env_sr': 200,
'pad_factor':None,
'use_rfft':True,
'coch_filter_type': chcochleagram.cochlear_filters.ERBCosFilters,
... |
f96024ba4097f45a2e51977fa1d9b18b0f586b7bb92dcc89fb841d97d13d7c34 | Python | 1,197 | 49 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 20
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"] = dict(
type="AdjustedMotifModel",
model_to_adjust_spec=dict(
... |
3715973a0f57fa9a71dae73187f97a9f9a3c7f371bbd5f7690ea9d31e7ecb51b | Python | 1,198 | 47 | #from cox_nnet_v2 import *
import numpy
import sklearn
import sklearn.model_selection
import pandas as pd
import time
import dill
from sklearn.preprocessing import MinMaxScaler
d_path = "BRCA/"
#x = numpy.loadtxt(fname=d_path+"259p_phenotypic27.csv",delimiter=",",skiprows=1)
#x = numpy.loadtxt(fname=d_path+"259p_mic... |
3ef747d77a5439ee2c1e7418b98405dd6c1838e6c3ce6b7a7683b68a242c70e0 | Python | 1,198 | 38 | import os
from modular_splicing.data_pipeline.create_dataset import create_dataset
datafiles_from_chenxi = {
"fly": "../data/drosophila_model_and_data/drosophila_datafile_test_0.h5",
"mouse": "../data/mouse_model_and_data/musculus_datafile_test_0.h5",
}
def dataset_for_species(species):
"""
Provide t... |
8fda9406dad51a6c48eaf5bf75989ef2694a25eb114f5a507178dc4dcc6f5751 | Python | 1,198 | 46 | from typing import (
cast,
TYPE_CHECKING,
)
from galaxy.files.models import FileSourcePluginsConfig
from galaxy.util.plugin_config import (
load_plugins,
PluginConfigSource,
plugins_dict,
)
if TYPE_CHECKING:
from galaxy.files.sources import BaseFilesSource
class FileSourcePluginLoader:
d... |
c6d9e6d6f5c9f7eea2432ead749d71fc1253d7a36c9bf0b17f017f38d9bce46e | Python | 1,198 | 39 | #!/usr/bin/env python
# Dan Blankenberg
import sys
import bx.align.maf
from galaxy.datatypes.util import maf_utilities
def __main__():
output_name = sys.argv.pop(1)
input_name = sys.argv.pop(1)
count = 0
with open(output_name, "w") as out, open(input_name) as infile:
for count, block in enu... |
cd24ccdc9772f4e7c1d6f7f21f9d60f3665737ace34ca0a683ae1e0742004960 | Python | 1,198 | 49 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 32
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"] = dict(
type="AdjustedMotifModel",
model_to_adjust_spec=dict(
... |
8f76183343f7c56a959c19de3ff36ea18996e10751106b0d99073a38a35be827 | Python | 1,199 | 59 | import numpy as np
from neuron import h, gui
from neuron.units import ms
def assert_equal(a, b):
assert a == b, f"{a} != {b}"
def test_for_netcons():
nseg = 1
soma = h.Section()
soma.nseg = nseg
syn1 = h.ForNetconsSyn(soma(0.5))
syn1.a0 = 1.0
syn2 = h.ForNetconsSyn(soma(0.5))
syn... |
953203eebe2a532e0281fc3e8590b25819a309928d516e762911ed4b1bc42970 | Python | 1,199 | 43 | import os
import sqlite3
class Database(object):
def __init__(self, datadir):
self.datadir = datadir
self.db_name = os.path.join(datadir, 'covid-india.db')
self.conn = self.make_conn()
def init_tables(self):
self.tables = {}
def make_conn(self):
conn = sql... |
992b4ae1988dd6155d66bf10f51efc005068bae03d4488674389f01ab7c28c26 | Python | 1,199 | 40 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
""""tests for search.py"""
import unittest
import numpy as np
from sknetwork.data import cyclic_digraph
from sknetwork.data.test_graphs import *
from sknetwork.path import breadth_first_search
class TestSearch(unittest.TestCase):
def test_bfs(self):
adjac... |
4c5568c0b45bab5f4b16794a196b1a28495c22c0c0cfe22ff31dda9123a9b3a6 | Python | 1,200 | 45 | """project tokens hashed
Revision ID: 54d9cae546ad
Revises: 711ce9f88326
Create Date: 2024-10-15 10:03:34.722490
"""
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision = "54d9cae546ad"
down_revision = "711ce9f88326"
branch_labels = None
depends_on = None
def upgrade()... |
61906ac5e60f4fbf5ce9a8bcaf4d5bd8251ce69c579d121890fe9fd1f7bd4e5f | Python | 1,200 | 55 | from neuron import h
def check_defaults(obj, parameters):
defaults = {
"b": 0.1,
"y": 2.1,
}
for p in parameters:
actual = getattr(obj, f"{p}_default_parameter")
expected = defaults.get(p, 0.0)
assert actual == expected
def test_default_values():
nseg = 10000... |
c533531e3edd0714cafb9aff510069adc9fba2a436035162126798e9093d75a7 | Python | 1,200 | 42 | """Tests for specparam.reports.save."""
import os
from specparam.tests.tsettings import TEST_REPORTS_PATH
from specparam.reports.save import *
###################################################################################################
#########################################################################... |
3dc4439d406144c4270bb643a0b8608e2842d67aaf114a6e4b8637d4cb925c42 | Python | 1,201 | 38 | # Copyright Niantic 2019. Patent Pending. All rights reserved.
#
# This software is licensed under the terms of the Monodepth2 licence
# which allows for non-commercial use only, the full terms of which are made
# available in the LICENSE file.
from __future__ import absolute_import, division, print_function
import o... |
6e5eb305eb4f92e845ebfb89dbabb1a0aeca83e6df442d36aadf32305ca77fdb | Python | 1,201 | 44 | import os
import pandas as pd
pd.set_option('display.max_columns', 10)
from tqdm import tqdm
tqdm.pandas()
from drug_interactions.utils.calc_metrics import calc_metrics
test_df = pd.read_csv('./data/csvs/data/test_new_old_chemprop_similar.csv')
test_df = test_df.sort_values(by=['Drug1_ID', 'Drug2_ID'], ascending=Tr... |
9ffce6c5dfa7a3bfc86d011e214b7cb565ce2c16e9128a6e7cc60d3a3020b373 | Python | 1,201 | 39 | """Check changed translation units using their CMake compilation commands."""
import json
from pathlib import Path
import subprocess
import sys
base, build_directory, clang_tidy = sys.argv[1:]
commands = json.loads((Path(build_directory) / "compile_commands.json").read_text())
compiled_files = {
(Path(command["d... |
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