sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
3ec7b4f64c334f64c12ec9922574bb4ddb35ba8cbb914d9e34e27ba61067aa57 | Python | 1,058 | 36 | from dig.ggraph.dataset import QM9
import shutil
def test_qm9():
root = './dataset/QM9'
dataset = QM9(root, prop_name='penalized_logp')
assert len(dataset) == 133885
assert dataset.num_features == 4
assert dataset.__repr__() == 'qm9_property(133885)'
assert len(dataset.get_split_idx()) == 2
... |
ae969784339191a96841c8d4d47e8334c34d481678f4f061e87f0ad5fdfd645b | Python | 1,058 | 45 |
from navec.pq import PQ
def quantize(matrix, qdim, centroids, sample, iterations):
import numpy as np
import pqkmeans
encoder = pqkmeans.encoder.PQEncoder(
iteration=iterations,
num_subdim=qdim,
Ks=centroids
)
matrix = np.array(matrix)
vectors, dim = matrix.shape
... |
dd199c034e41c6c5d9f0543a006f6d02db911d1b5abbb5d481f76f825118e064 | Python | 1,059 | 37 | # -------------------------------------------
# Miscellaneous helper functions
# -------------------------------------------
def make_flat(old_list):
''' Takes as argument a list of lists and flattens it (i.e. returns a 1D list with all the elements) '''
new_list = []
for elem in old_list :
if type... |
2ff6022c4b42eeab255386f3c5f5ba40104d4df8917023ed013baa334f777931 | Python | 1,061 | 37 | """Define a state-aware base class for DANDI NiceGUI widgets."""
from __future__ import annotations
from abc import ABC, abstractmethod
from gui.app_state import DandiAppState, DandiAppStateStore
class DandiWidget(ABC):
"""Subscribe a NiceGUI widget to immutable application state changes."""
def __init__(... |
453930cb466fd782570605152313f7e3a893ba2ad314255bebc7fd1fd8c4888a | Python | 1,061 | 40 |
from sleepy.gui.tagging.model.event.point import PointEvent
from functools import partial
import pdb
class UserPointEvent(PointEvent):
def __init__(self, point, dataSource, applicationSettings):
super().__init__(point, dataSource, applicationSettings)
self.artist = None
se... |
52cdb5b19f022c12c3c5037eaffff7289c34c9ae4f55c2b31875b8806aa03d96 | Python | 1,061 | 31 | import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
data = pd.read_excel('compare_test.xlsx')
indicators = ['Accuracy', 'Precision', 'Recall', 'Specificity', 'F1-Score', 'AUC', 'AUPRC']
data_matrix = data.loc[:, indicators].values
data.set_in... |
ac502a6dea6596848b16573f04c51c24ba84c70f256c31de13c4a17293c70411 | Python | 1,065 | 29 | import unittest
import pytest
import torch
from reinvent.models import TransformerAdapter, SampledSequencesDTO, Mol2MolModel
from reinvent.runmodes.utils.helpers import set_torch_device
from tests.test_data import ETHANE, HEXANE, PROPANE, BUTANE
@pytest.mark.integration
@pytest.mark.usefixtures("device", "json_conf... |
eb15beb476240f62c8f660eb544040d1ad771cec6df2bd1016abc93b6631031e | Python | 1,066 | 33 | """Focused tests for the public analysis-directory API."""
from pathlib import Path
import shutil
import sanpy
def test_analysis_dir_discovers_default_loaders(tmp_path: Path) -> None:
"""Scan a fresh folder without requiring a loader dictionary.
Args:
tmp_path: Pytest-managed temporary directory.
... |
85f82f446c85f21c92bad1755b1f53813d9062fe4232fb28e134deb12ec74f23 | Python | 1,068 | 34 |
import os
import numpy as np
def test_loss_log_plot():
from mlspm.logging import LossLogPlot
loss_log_path = "loss_log.csv"
plot_path = "test_plot.png"
log_path = "test_log.txt"
info_log = open(log_path, 'w')
if os.path.exists(loss_log_path):
os.remove(loss_log_path)
loss_log = ... |
a821eacf50abf1e4ad0913f288e26f2b1a5feebfebc7cc0b871cfc311122306d | Python | 1,068 | 33 | import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
data = pd.read_excel('compare_newTest.xlsx')
indicators = ['Accuracy', 'Precision', 'Recall', 'Specificity', 'F1-Score', 'AUC', 'AUPRC']
data_matrix = data.loc[:, indicators].values
data.se... |
b6f03b4bddac5e4968c23add7589e0f64a13b0396e60a87edb950b4b1dc8b741 | Python | 1,070 | 34 | import re
import subprocess
import time
import os
def _get_gpu_memory_in_use():
success = True
try:
nvidia_smi_output = subprocess.check_output(["nvidia-smi"]).decode("utf-8")
except:
success = False
return success, []
gpu_memory_in_use = []
for l in nvidia_smi_output.split(... |
1dc0c5cb03af6b0c70ff913652d1851026f8150f577ce896df7c4a0e071af02a | Python | 1,072 | 35 | from __future__ import annotations
import logging
from reinvent.runmodes.RL import memories
from reinvent.runmodes.RL.validation import SectionDiversityFilter
logger = logging.getLogger(__name__)
def setup_diversity_filter(config: SectionDiversityFilter, rdkit_smiles_flags: dict):
"""Setup of the diversity fil... |
9822142ac0b2fa2da054252ee4718d771a882b3ea26919bb4e6248f345bf5c8d | Python | 1,073 | 30 | import pytest
import unittest
import torch
from reinvent.models import LinkinventAdapter, SampledSequencesDTO
from reinvent.runmodes.utils.helpers import set_torch_device
from tests.test_data import ETHANE, HEXANE, PROPANE, BUTANE
from tests.models.unit_tests.linkinvent.RNN.fixtures import mocked_linkinvent_model
@... |
5c5f027b82604f48b19f548c6a6e48a451ba093d0251c725f724f1b911148b9c | Python | 1,074 | 39 | import geomstats.backend as gs
from ._base import BaseEstimatorTestData, TestData
class PairwiseDistsTestData(TestData):
def dists_among_selves_test_data(self):
return self.generate_random_data()
def symmetric_test_data(self):
return self.generate_random_data(exclude_single=True)
def ma... |
9c720f57749fd76e024d2c1d2e6be72b83183ff21761bfcc58b3a30affd015e6 | Python | 1,075 | 31 | import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
data = pd.read_excel('compare_test_pseudo.xlsx')
indicators = ['Accuracy', 'Precision', 'Recall', 'Specificity', 'F1-Score', 'AUC', 'AUPRC']
data_matrix = data.loc[:, indicators].values
data... |
eeccd8f05b20bb33430f9797534466263c660315c06026a0efb96fd2959a81d4 | Python | 1,076 | 32 | from collections import OrderedDict
from typing import Any, Callable, Generic, Optional, TypeVar
K = TypeVar("K")
V = TypeVar("V")
class LRUCache(Generic[K, V]):
"""A simple LRU cache implementation, based on the OrderedDict class, which allows
for a callback to be invoked when an item is evicted from the c... |
f6317b839a24190810b5667953f690be8b53b249c7d7da6412d31721aa916d5a | Python | 1,076 | 33 | #!/usr/bin/env python3
import argparse
import matplotlib.pyplot as plt
import numpy as np
from odil import plotutil
plotutil.set_extlist(["png"])
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--data", type=str, default="out_poisson/train.csv")
parser.add_argument("-... |
37a278766c90e80e557087fb9689841ab98ed22f1db34cdd318e812800ea9322 | Python | 1,077 | 28 | import glob
import platform
directory_split = "\\" if platform.system() == "Windows" else "/"
def generate_training_data(save_location, msd_directory, target_platform):
target_split = "\\\\" if target_platform.lower() == "windows" else "/"
with open(save_location, 'w+') as f:
print(msd_directory)
... |
66e1d2117d262aaeb7adf8db7235211f1c274d2c326b8ef591479f6c8b607f69 | Python | 1,081 | 32 | import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
data = pd.read_excel('compare_newTest_pseudo.xlsx')
indicators = ['Accuracy', 'Precision', 'Recall', 'Specificity', 'F1-Score', 'AUC', 'AUPRC']
data_matrix = data.loc[:, indicators].values
d... |
06a17b325eb5f11c2bc233bc6bd882f5fd4282d1fb22a020b15e861677950cdb | Python | 1,082 | 49 | import sympy.physics.units as units
from sympy.physics.units import convert_to, second, seconds
def eq_split(eq):
str = eq.replace(" ", "")
parts = []
str_buf = ""
for s in str:
if s in ["*", "/", "+", "-", "%", ":", ";", "=", "!", "(", ")", "[", "]"]:
parts.append(str_buf)
... |
ad1c35d0f27cb7afdb670b972af1746a36eb0890eb9ad6aa4f15269178ab0fb2 | Python | 1,082 | 30 | # Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
# SPDX-License-Identifier: MIT-0
"""
Utils for transfer learning
"""
from torch.nn.parameter import Parameter
def load_state_dict_to_model(model, state_dict):
"""Initialize a model with parameters in `state_dict` (inplace)
from a pretrained ... |
53bfb96dbbfebc12343718f75dfa4608300839329fab7364792edd759e4b10a7 | Python | 1,083 | 23 | """Atlas registry, lazy loading, and coordinate labeling.
Atlases are hosted at `huggingface.co/datasets/nltools/niftis` under
`atlases/` and fetched on first use via `fetch_resource`, then cached locally.
The labeling logic was adapted from
[atlasreader](https://github.com/miykael/atlasreader) (BSD-3-Clause); please... |
a071c64e69cfc6a718d7eefaab6f809c7040c701e501a49154c0305ca0b9b6b3 | Python | 1,083 | 47 |
import json
from collections import OrderedDict
from .record import Record
class Meta(Record):
__attributes__ = ['id', 'protocol']
PROTOCOL = 1
def __init__(self, id, protocol=PROTOCOL):
self.id = id
self.protocol = protocol
@property
def as_json(self):
return OrderedD... |
226dba93f6e93849afe34b023b5b08a056c7aefd57e18aa0522bcaa8e0c63927 | Python | 1,086 | 35 | # Usage: python3 splitScaffolds.py inFile species type_of_variant (indels or snps) type_of_comparison (e.g. huch, hugo, hurh etc. where huch indicates that the MAF was a human chimp alignment)
import os
import sys
import pandas as pd
# Read arguments
inFile = sys.argv[1]
species = sys.argv[2]
type_of_variant = sys.ar... |
569ba7dc45094fe7975897988cff14dcce0e8a0564b07a0bd72a7f7aa66cee6e | Python | 1,086 | 42 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2023/10/7 16:09
# @Author : lvtongxuan
# @File : setup.py
# @Software: PyCharm
# @Email : lvtongxuan@genomics.cn
import setuptools
from wheel.bdist_wheel import bdist_wheel
__version__ = "1.0.5"
class BDistWheel(bdist_wheel):
def get_tag(self):
... |
772160038b8d2857377e1afe91fc60eb86877229cfee1f80b9d6407845907c75 | Python | 1,086 | 36 | # 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
import os
import sys
sys.path.insert(0, os.path.abspath('../..'))
# -- Project information ------------------------... |
6cafa3d5a907aa15c2eea2c9ff0e1f04fe09c839bef4048f27e3262e4a43c15e | Python | 1,088 | 39 | import nibabel as nb
import numpy as np
import pytest
from pydfc.data_loader import nifti2timeseries
@pytest.fixture
def simulated_bold_and_label(tmp_path):
# Simulated BOLD data
bold_data = np.random.rand(10, 10, 10, 100)
affine = np.eye(4)
bold_img = nb.Nifti1Image(bold_data, affine)
bold_file ... |
a1893b47028b880ca8ac697ed21b8f2db9fe7f4dd892a5d067b07e75f87432aa | Python | 1,089 | 37 | # Copyright (c) 2020 PaddlePaddle 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
#
# Un... |
f78069a3fea481b6db3b4ed46c6c4135d4dfcf94374ebcee9f611c6c45610f1e | Python | 1,089 | 53 | import sys
sys.path.append('../../')
import time
t=time.time()
from PymoNNto import *
from PymoNNto.Exploration.Network_UI.Basic_Tabs import *
from NetworkBehavior.EulerEquationModules.VariableInitializer import *
from NetworkBehavior.EulerEquationModules.Equation import *
from NetworkBehavior.EulerEquationModules.Eu... |
3b62f1b912e3d7c8a228ba3d787a3c302fcb9b956ac14eb1861948ec4050d68f | Python | 1,090 | 43 | import geomstats.backend as gs
from geomstats.test.data import TestData
from .base import LevelSetTestData
from .riemannian_metric import RiemannianMetricTestData
class HyperboloidTestData(LevelSetTestData):
tolerances = {"projection_belongs": {"atol": 1e-8}}
class Hyperboloid2TestData(TestData):
def belon... |
9065983127f8a611f17627d44a57304141e6f80f8832598a3c78543e25313769 | Python | 1,091 | 38 | """Compatibility API. New code should use Proj2ProjReconstructor."""
import warnings
from .proj2proj import Proj2ProjReconstructor
class N2SelfReconstructor(Proj2ProjReconstructor):
def __init__(
self,
name,
net="skip",
lr=0.001,
n2self_n_iter=8000,
n2self_weights... |
bebaebbeedef5814193cd519b748e98201e05f8cb68fb95157b24c99f77c67c0 | Python | 1,091 | 49 | import pytest
from corgie.helpers import BoolFn
@pytest.mark.parametrize(
"exp, result",
[
(
{
"inputs": [
{"val": 1},
{"val": 1},
],
"threshold": 2,
},
False,
),
... |
98ec643ca4cf6843b47fa37d2cf30ae790e11ed71c01c0dd55e22963301f7783 | Python | 1,092 | 32 | import sys, os
def readAndLabelStats(statFileName, label):
examples = []
with open(statFileName) as statFile:
first = True
for line in statFile:
if first:
header = "classLabel\t"+line
first = False
else:
examples.append(str... |
5faddb99d205fcac33e852d0a181c3738a8d7e2f7661d03f8d442fa2d8bcbcc1 | Python | 1,093 | 25 | # Copyright (c) 2020 PaddlePaddle 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
#
# Un... |
b740713eb16e4bcf10d0dc3769c5078240d11ddcd17691aea7547e41c4d06a28 | Python | 1,093 | 40 | from geomstats.test.data import TestData
class _ManifoldMixinsTestData:
def belongs_vec_test_data(self):
return self.generate_vec_data()
def not_belongs_test_data(self):
return self.generate_random_data()
def random_point_belongs_test_data(self):
return self.generate_random_data(... |
1edbe1b4a5c085e2269f964c7a82d81538a307f6fa62950824175b6347ae9b8d | Python | 1,095 | 32 | from __future__ import annotations
import importlib.metadata as impm
import re
import jinja2.parser
import requests
from jinja2.ext import Extension
class SnakebidsVersionExtension(Extension):
"""Retrieve the latest snakebids version from pypi.
Stores value in the ``snakebids_version`` global variable.
... |
583beae61d8b7ff68664e6f8ac1d45a3f9c8db441abec86dd32251570fae57b0 | Python | 1,095 | 37 | import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt
from src.data.files import get_file_path
tau_df = pd.read_csv(get_file_path("new_tau", "data", ext="csv")).infer_objects()
tau_types = tau_df["tau type"].unique()
fig, axs = plt.subplot_mosaic([list(tau_types)], figsize=(8, 4)) # type: i... |
c4163f573aaa58d8d9999e97acf693662b64ba804ee0af1fb148953a517df52d | Python | 1,095 | 44 | # Author: Youzhi Luo (yzluo@tamu.edu)
# Updated by: Anmol Anand (aanand@tamu.edu)
BATCH_SIZE = 'batch_size'
INITIAL_LR = 'start_lr'
GENERATOR_STEPS = 'g_steps'
TEST_INTERVAL = 'test_interval'
LOSS_INTERVAL = 'loss_interval'
FACTOR = 'factor'
PATIENCE = 'patience'
MIN_LR = 'min_lr'
MAX_NUM_EPOCHS = 'max_num_epochs'
REW... |
60ae275cf7082b27f024122605b8bf402d2b8b1ad67e80dc16676bcbbf11111f | Python | 1,097 | 29 | from conftest import TrainingInvarianceBaseTest
import pytest
import torch
from nequip.utils.versions import _TORCH_GE_2_4
@pytest.mark.skipif(not _TORCH_GE_2_4, reason="OpenEquivariance requires torch >= 2.4")
@pytest.mark.skipif(not torch.cuda.is_available(), reason="OEQ requires CUDA")
class TestOEQTrainingInvaria... |
73203c51acda2c10a5ca3772e9620afa9bb7c814cd9c994feb0e0be80746132a | Python | 1,097 | 34 | from numpy import zeros, corrcoef, arange
def corr_slide(series, size, slide = None):
"""Run cofluctuation analysis for BOLD signal.
Args:
series (double): BOLD signal array for all parcels/voxels in the format [N, Tmax].
size (int): Size of sliding window.
slide (int, optional): Shift... |
739bc922aa19c7c66f119d2e28084f5a2875c9b8588dd588588c82a9bcb625ae | Python | 1,097 | 53 |
# Parse ALL input files and collect information about how many
# entities there are (BCIO, external, etc.)
# Relies on there being an ID column with either a BCIO ID or
# an external ID to count
# Needs specification of the root directory in which to find input files
ROOT_DIR = '../inputs/'
import os
import o... |
779929e4e912f7d2196e2771fc42066761b5942ead7b784d9fed56f3e065b0e8 | Python | 1,102 | 56 | from pathlib import Path
from neurodesign import Experiment, Optimisation, report
output_dir = Path(__file__).parent / "output"
output_dir.mkdir(parents=True, exist_ok=True)
exp = Experiment(
TR=2,
n_trials=100,
P=[0.33, 0.33, 0.33],
C=[[1, 0, 0], [0, 1, 0], [0, 0, 1], [1, -1, 0], [0, 1, -1]],
n_... |
319fe64b10b1fccdbcac59ac4132849a3afa0b91b913ee617a414ddd093879c9 | Python | 1,104 | 30 | # -*- coding: utf-8 -*-
#
#
# PyRates software framework for flexible implementation of neural
# network models and simulations. See also:
# https://github.com/pyrates-neuroscience/PyRates
#
# Copyright (C) 2017-2018 the original authors (Richard Gast and
# Daniel Rose), the Max-Planck-Institute for Human Cognitive Bra... |
d69936c5a033fb65bfe319231e1b7fb6c1f0b526d3cc45667cc67f3987606827 | Python | 1,105 | 44 | import pytest
import reinvent.utils.logmon as logmon
from reinvent.utils.logmon import RemoteJSONReporter, get_reporter, setup_reporter
@pytest.fixture(autouse=True)
def reset_reporter():
"""Reset the module-level reporter before and after each test."""
logmon._reporter = None
yield
logmon._reporter ... |
97343890ecd3ed1ff2a37ecb24e83b25d7d24049037c5d13c392dd619fac015e | Python | 1,108 | 32 | import numpy as np
import os
import pdb
base_folder = '' # save folder
config_folders = [] # configuration subfolders
models = ['student']
for config in config_folders:
for model in models:
load_folder = os.path.join(base_folder, config)
metrics = []
roc_auc = []
for fold in range(5):
fold_met... |
35718978164ad4ec8464c3c3c0b860893bc262d1076ff35da56ff9a744cab197 | Python | 1,109 | 36 | """Module that defines common errors."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
def check_valid_range(value, name, valid_range):
"""Raises a ValueError exception if value not in valid_range"""
if value > valid_range[1] or value ... |
9edc15c91de8cd0bfa8e61ceb598bea2ad938e1e7fa861b64319b809513bbfa9 | Python | 1,109 | 27 | import argparse
import pandas as pd
# Create an argument parser
parser = argparse.ArgumentParser(description='Extract columns from a DataFrame based on the content of another file.')
parser.add_argument('first_file', type=str, help='Path to the first file')
parser.add_argument('second_file', type=str, help='Path to th... |
eadec254e25b073df75e8335e9333441f0cd91818d9068fe5efc17698c54a17c | Python | 1,109 | 36 | from dig.ggraph.dataset import ZINC250k
import shutil
def test_zinc250k():
root = './dataset/ZINC250k'
dataset = ZINC250k(root, prop_name='penalized_logp')
assert len(dataset) == 249455
assert dataset.num_features == 9
assert dataset.__repr__() == 'zinc250k_property(249455)'
assert len(da... |
d0ee92906e8ef8b608f92aec3d272d53e23c6ced8e55fb4bc3754ebc80fb724f | Python | 1,110 | 35 | # 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
import os
import sys
import sphinx_rtd_theme
sys.path.insert(0, os.path.abspath('../../'))
# -- Project information -... |
a1e53ffe4bdf1899ec41cd07cc8bb6c7b919b454b8fb1fc9fe9e8968bf9518c6 | Python | 1,112 | 32 | from geomstats.test_cases.geometry.lie_algebra import MatrixLieAlgebraTestCase
class SkewSymmetricMatricesTestCase(MatrixLieAlgebraTestCase):
def test_baker_campbell_hausdorff_with_basis(self, atol):
# valid for n > 2
if self.space.n < 3:
return
fb = self.space.basis[0]
... |
b134cb9545e60fe31ba34e3af0af7b114bf5990bb51826f8ed86b89510cbf6c6 | Python | 1,112 | 46 | import PymoNNto as pymonnto
from brian2 import *
import brian2
from PymoNNto.NetworkCore.Behavior import *
class Brian2_embedding(Behavior):
def initialize(self, neurons):
self.add_tag('Brian2_embedding')
brian2.defaultclock.dt = 1 * ms
eqs = self.parameter('eqs', '')
self.G = ... |
f7acc0b49bd7aff1e78365b8e27a6f0c5f5bc344d7a66ac768dc5755770b856c | Python | 1,113 | 35 | import os
import json
input_dir = 'instances/atlas/parcellationEntityVersion/JBA-v2-9'
output_dir = 'instances/atlas/parcellationEntity/JBA'
def main():
existing_dict = {}
def get_existing(pev_filename: str):
jba_version, space, areaname, version, hemisphere = pev_filename.split('_')
if arean... |
4a462b5a79ec53bf07c863f9de2cc3da19b2856b55e4fb32634809e89766f6dd | Python | 1,115 | 43 | """
Tests for variance schedules
"""
import unittest
import torch
from foldingdiff import beta_schedules
class TestLinearVarianceSchedule(unittest.TestCase):
def test_strictly_increasing(self):
"""
Test that betas should be strictly increasing
"""
betas = beta_schedules.linear_b... |
f6905df0605ef7694803a4b7d782ce51ce2d53811083fee979f2d8c9e8a98d80 | Python | 1,115 | 28 | import numpy as np
from reinvent.models.model_factory.sample_batch import SmilesState, SampleBatch
def common_report(sampled: SampleBatch, **kwargs):
valid_mask = np.where(
(sampled.states == SmilesState.VALID) | (sampled.states == SmilesState.DUPLICATE),
True,
False,
)
unique_mas... |
ba2855fed6952ee9ef5448b5b2fce6b71d834452452c76137ad34bbfde96f6d3 | Python | 1,117 | 62 | # Author: Youzhi Luo (yzluo@tamu.edu)
# Updated by: Anmol Anand (aanand@tamu.edu)
from enum import Enum
class FuseType(Enum):
ABS_DIFF = 'abs_diff'
CONCAT = 'concat'
COSINE = 'cosine'
ADD = 'add'
MULTIPLY = 'multiply'
class AugType(Enum):
NODE_FM = 'node_fm'
NODE_DROP = 'node_drop'
ED... |
6d72c5c7e2e5e5957cd2145bd87a67acc38ab0f3a889b38deff3937fd35542a6 | Python | 1,118 | 32 | from ..abstract_dataset import AbstractDataset
import os
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.tri as mtri
class ElasticBlockDataset(AbstractDataset):
parametric = True
time_dependent = False
description = "elastic block TODO"
data_directory = os.path.join(os.path.dirna... |
a8467806ccba2a9ab9b84efb813394ba039926ccb96ce972b46fd953c0509dde | Python | 1,120 | 38 | """Send information to a remote server"""
from __future__ import annotations
__all__ = ["SamplingRemoteReporter"]
import collections
from typing import TYPE_CHECKING
from reinvent.runmodes.samplers.reports.common import common_report
if TYPE_CHECKING:
from reinvent.models.model_factory.sample_batch import Sampl... |
1497922a9a8cfa2227210e9291812e97b671b3b4cc8dea7840d511199e726188 | Python | 1,121 | 47 | from __future__ import annotations
import textwrap
import warnings
from colorama import Fore, Style
WARN_TEMPLATE = f"""\
{Fore.YELLOW}{Style.BRIGHT}[{{category}}]{Style.NORMAL} {{filename}}:{{lineno}} \
{Fore.RESET}{{line}}
{{message}}
"""
def formatwarning(
message: Warning | str,
category: type[Warning... |
33ad5bd1d9848f6ae7a598aec391e79ae234d84c944136186d2199f16d1ae714 | Python | 1,123 | 36 | import pytest
import numpy as np
from reinvent_plugins.components.Lilly.comp_medchem_rules import Parameters
from reinvent_plugins.components.Lilly.comp_medchem_rules import LillyMedchemRules
SMILIES = [
"Cc1ccc(-n2[nH]c(C)c(N=Nc3cccc(-c4cccc(C(=O)O)c4)c3O)c2=O)cc1C",
"CC(=O)Oc1ccccc1C(=O)O",
"Cc1ccc(-c2... |
4da1bea1003552f168c7d4fdf4c295a63f6091c710d829ba7188478d6e7a1a53 | Python | 1,124 | 34 | # Copyright (c) 2020 PaddlePaddle 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 appli... |
2d4e768356e190e92a90bd5a8fe35d9f0247ac7e03c5a8430c92c8c0d11a6d0a | Python | 1,126 | 33 | # Test if bilateral filtering of batch of images works (visual check required)
# GPU OP must be compiled with SPATIAL_DIMS=2 INPUT_CHANNELS=3 REFERENCE_CHANNELS=3
import tensorflow as tf
import numpy as np
from PIL import Image
from os import sys, path
sys.path.append(path.dirname(path.dirname(path.abspath(__file__))... |
a65f48932d1140d84725d970e6d2643e4e7b1c04f0a38438bf0095492cc742fa | Python | 1,126 | 42 | """Send information to a remote server"""
from __future__ import annotations
__all__ = ["TLRemoteReporter"]
from collections import Counter
import logging
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from reinvent.runmodes.TL.reports import TLReportData
logger = logging.getLogger(__name__)
class TLRemot... |
12e504a5ef23d87ca3bde6235f61f2554c454299f80b502ecde493f88875cace | Python | 1,127 | 32 | """Tests for SanPy text acquisition snapshot extraction."""
from pathlib import Path
import numpy as np
import sanpy
from sanpy.io.zarr_export.sanpy_file_adapter import snapshot_sanpy
def test_snapshot_sanpy_preserves_sweep_epochs(sanpy_data_folder: Path) -> None:
"""Copy every text sweep and its sweep-specifi... |
154aa57647aa1501393b64be687e3311bdbb270653436fcf2bbb2a3111e937be | Python | 1,130 | 38 | import os
import random
import gc
import time
# Borrowed from https://github.com/rogerbinns/apsw/blob/master/apsw/tests.py#L224
# Used to delete sqlite files on Windows, since Windows file locking
# behaves differently to other operating systems
# This should only be used for test or non-production code, such as in r... |
ac04e09a6cc8c5ebb7b8742e4586128c095cbfae25381c71ff60f3c52a3a7a16 | Python | 1,130 | 39 | import numpy as np
from reinvent_plugins.components.comp_custom_alerts import CustomAlerts
from reinvent_plugins.components.comp_custom_alerts import Parameters
def test_comp_custom_alerts():
endpoint1_smarts = [
"[*;r8]",
"[*;r9]",
"[*;r10]",
"[*;r11]",
"[*;r12]",
... |
fd3f78d3742b353577f98714b25f8d6cdeb543679387860f8d8fa37f5e50175f | Python | 1,131 | 31 | from pynetdicom import AE, evt, AllStoragePresentationContexts, debug_logger, build_context
from pynetdicom.sop_class import Verification
import os
debug_logger()
def handle_store(event):
"""Saving Incoming DICOM series based on Patient ID"""
ds = event.dataset
root = r"YOUR PATH TO \Dicom_receiver"
... |
5ae204ab4e215a33f345d493fb45883abea51813b2571df7d4146f05d8ef845d | Python | 1,133 | 31 | from setuptools import setup, find_packages
setup(
name='Humatch',
version='1.0.1',
description='Fast, gene-specific joint humanisation of antibody heavy and light chains.',
license='BSD 3-clause license',
maintainer='Lewis Chinery',
long_description_content_type='text/markdown',
maintainer... |
ad53dd89b545529078b6df0c4b8d1c61ac7c963916ebec1190e073bd42936ced | Python | 1,134 | 38 | # import sys
# import os
# from pathlib import Path
# import shutil
# install_dir = Path(sys.argv[0]).resolve().parent
# user = os.getlogin()
# out_lines = []
# with open('sssort.sh', 'r') as fH:
# for line in fH.readlines():
# if line.startswith('INSTALL_DIR'):
# out_lines.append('INSTALL_DIR... |
135aff89e5cc203d7059a8e3a25deace7d64a74b36f3f87c32fb377e7be36a7f | Python | 1,135 | 24 | import pandas as pd
from uniprotparser.betaparser import UniprotSequence
import re
df = pd.read_csv(r"C:\Users\Toan Phung\Downloads\supp_RA118.000696_136158_1_supp_105958_p6rjww.txt", sep="\t")
pattern = re.compile("r(\d+)")
new_df = []
for i, r in df.iterrows():
mods = r["Variable modifications identified by spec... |
e9d4fdebc50ebc609aa61608401847be540fecd0fd0364cfaa9c68efc8c7f20a | Python | 1,135 | 44 | import pandas as pd
import os
# List of input files and output files
input_files = [
"CD16p_Mono_SNP.txt",
"CL_Mono_SNP.txt",
"CM_CD8_SNP.txt",
"DN_B_SNP.txt",
"EM_CD8_SNP.txt",
"Fr_I_nTreg_SNP.txt",
"Fr_II_eTreg_SNP.txt",
"Fr_III_T_SNP.txt",
"Int_Mono_SNP.txt",
"LDG_SNP.txt",
... |
56e13f0ae82805b1b1b2c087d031687efbfc604dcac9103600acc16f6ff1d5ce | Python | 1,136 | 56 | import time
class Timer:
"""
Timer class.
if autoreset=True, timer is reset after any member function call
"""
def __init__(self, autoreset=False):
self.autoreset = autoreset
self.reset()
def sec(self):
"""
Provide the time since reset in seconds.
"""... |
2aed05e7ca26b027cf4c35ee7bbeb49a7b774ff5bfd520a9dbf349620eaa49d1 | Python | 1,137 | 33 | # SPDX-License-Identifier: BSD-3-Clause
# Copyright (c) 2020-2026, Christian Gaser. See LICENSE.
"""Exact TFCE and permutation inference.
The core is deliberately framework-free: arrays in, arrays out, numpy and scipy
and nothing else. The pieces are
* :mod:`tfce.core` -- the exact TFCE transform (max-tree, no ste... |
7ed878f340d1c81e58a20df6d3198c34d2d161e40e278945557619e251452bf4 | Python | 1,138 | 40 | import experiment as exp
class MyExperiment(exp.Experiment):
default_params = {
"color": "blue",
}
default_blocks = [
{"color": "red"},
{"color": "green"},
{}
]
def run_trial(self):
if exp.state["video", "record", "is_recording"]:
self.log.info(... |
dc2401aacb851f580ad7b52a1e77d1ca1e9744656c82e6dcdddcb0fb6049d4fb | Python | 1,138 | 38 | from pathlib import Path
import pytest
from cookiecutter.main import cookiecutter
import snakebids
from snakebids.app import SnakeBidsApp
from snakebids.cli import SnakebidsArgs
def test_template_dry_runs_successfully(tmp_path):
cookiecutter(
str(Path(snakebids.__path__[0]) / "project_template"),
... |
2ebee3845235957e3eb4dac95df6e1d338475434bd2c2597ed412ef941898350 | Python | 1,139 | 30 | import experiment as exp
from canvas import Canvas
class CanvasSimpleExperiment(exp.Experiment):
async def run(self):
# Create a new Canvas instance to communicate with a Canvas app with ID "my_canvas" and start listening for incoming messages.
self.canvas = Canvas("my_canvas")
# Wait unti... |
1e41024e67427723c9eddf32899aeaac9f70f57eaad5ca64741f261b16539ba4 | Python | 1,140 | 41 | import pytest
from torch import nn
from reinvent.models.transformer.core.network.encode_decode.model import EncoderDecoder
from reinvent.models.transformer.core.vocabulary import build_vocabulary
from reinvent.models.transformer.pepinvent.pepinvent import PepinventModel
from reinvent.models import meta_data
from tests... |
9760ab5cfe2529f0f42e41c87986cff4414fba6cfb659ad6a8bdf06996e25ce5 | Python | 1,140 | 30 | from torch.utils.data import Dataset
from PIL import Image
from torchvision import transforms
class MultiModalDataset(Dataset):
def __init__(self, face_image_paths, tongue_image_paths, fundus_image_paths, labels, transform=None):
self.face_image_paths = face_image_paths
self.tongue_image_paths = to... |
fca580c82da84d3978502c8dc0612f163024a7b7071dae87537791d8d76c27c7 | Python | 1,140 | 37 | # Copyright 2020-2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
"""openfl.federated package."""
import os
from importlib import util
from openfl.federated.data import DataLoader # NOQA
from openfl.federated.plan import Plan # NOQA
from openfl.federated.task import TaskRunner # NOQA
if util.find_sp... |
bd756cda36d394583d827108c46379562e8caa9cded57b4a0c2315c78cb4f146 | Python | 1,142 | 38 | # Usage: python3 splitScaffolds.py inFile species type_of_variant (indels or snps) type_of_comparison (e.g. huch, hugo, hurh etc. where huch indicates that the MAF was a human chimp alignment)
import os
import sys
import pandas as pd
# Read arguments
inFile = sys.argv[1]
species = sys.argv[2]
valid_chr = ["chr2A", "... |
ecb00655e989d8fa0d284b3d51ed21511bb6d04d879991161a2c0c08f1d0993d | Python | 1,142 | 37 | """Display application information in a NiceGUI side panel."""
from __future__ import annotations
from nicegui import ui
from gui.app_state import DandiAppState, DandiAppStateStore
from gui.widgets.base import DandiWidget
class AppInfoWidget(DandiWidget):
"""Render a small application-information placeholder."... |
dc3fe17acaa9cb9efa85cf88b4fe57205a4f11f6326fa55ab62f6119c84aeed7 | Python | 1,143 | 34 | import unittest
from reinvent.models.linkinvent.dataset.paired_dataset import PairedDataset
from reinvent.models.linkinvent.model_vocabulary.paired_model_vocabulary import (
PairedModelVocabulary,
)
from tests.test_data import (
SCAFFOLD_SUZUKI,
ETHANE,
HEXANE,
PROPANE,
BUTANE,
)
class TestPa... |
f5b4cc5b8e06c1ff2034a37e6d8e3ffe84a23018253dbf7de109d57f28a95cfe | Python | 1,143 | 32 | from PymoNNto.Exploration.Network_UI.TabBase import *
class sidebar_module_quick_access(TabBase):
def __init__(self, module_tags=[]):
self.module_tags = module_tags
def module_on_off(self, cb, Network_UI):
module_tag=cb.module_tag
print(module_tag)
Network_UI.network.set_behav... |
b348b4da26752d0286071b6e016a408bf84a913aa6b7a3efdccd7599fcd20e3d | Python | 1,144 | 28 | # -*- coding: utf-8 -*-
import unittest
import odl
from dival.data import DataPairs
class TestDataPairs(unittest.TestCase):
def test(self):
reco_space = odl.uniform_discr([0, 0], [1, 1], (2, 2))
observation_space = odl.uniform_discr([0, 0], [1, 1], (1, 1))
ground_truth = [reco_space.one(),... |
4ffbdf399f4ab7dce33c87afbc240033555e002532ea1b519b1e54f37c7a49e9 | Python | 1,147 | 41 | import numpy as np
from split_dataset import Blocks
from fimpy.roi_extraction.merging import merge_rois
def test_merging_rois():
test_0 = np.array(
[
[-1, -1, -1, -1, -1],
[-1, 0, 0, 0, -1],
[0, 0, 0, -1, 1],
[-1, -1, 2, 2, 2],
[-1, -1, 2, -1, -1... |
5bcc68ba5641c57329c8bfc7e208b68afa86204c255ecebe1220937d5389b5b5 | Python | 1,147 | 38 | from video_stream import ImageSource
import time
import numpy as np
class NoiseImageSource(ImageSource):
default_params = {
**ImageSource.default_params,
"frame_rate": 30, # add an additional parameter with default value 30.
}
def _on_start(self):
try:
self.log.info(f... |
82d3b368abcade60e1227f860abe75e68a9441b266dce809ee54878dfef2a34c | Python | 1,147 | 44 | from typing import List, Union
import numpy as np
from scipy.stats import gaussian_kde
from reinvent.runmodes.utils.decorators import extra_dependencies
@extra_dependencies("matplotlib")
def plot_histogram(data: List[Union[int, float]], xlabel: str, bins=50, title=None):
import matplotlib
matplotlib.use("Agg... |
f08d71909b8fa132b7f3938eba1afe22f6195b8c50b6b6a27c5f015de09e8c4f | Python | 1,147 | 30 | import os
import runCmdAsJob
import stdpopsim #just to make sure we are in an env with it
baseDir = ""
slimScriptDir = baseDir + "slimScripts"
rawSlimScriptDir = baseDir + "rawSlimScripts"
outDir = baseDir + "slimOutput"
logDir = baseDir + "slimLogs"
os.system(f"mkdir -p {rawSlimScriptDir} {slimScriptDir} {outDir} {l... |
0af2c62b055cbdb719430c98dfc2dadb3a8434d0c6ffcf1cc75f35410cb39db2 | Python | 1,148 | 26 | """The published consumer must read the user-selected build without downloading a release."""
import polars as pl
import pytest
from vdjmatch.db import vdjdb
def test_local_build_reference_is_current_and_offline(tmp_path, monkeypatch):
def no_download(**kwargs):
pytest.fail("a local build must not fetch ... |
3794cc713e75ac6354418f17ae79920a48bfb79a284d1bf6067b6e2842ab187e | Python | 1,148 | 39 | import logging
class CustomFormatter(logging.Formatter):
bold = "\033[1m"
normal = "\033[22m"
lightblue = "\x1b[36;20m"
yellow = "\x1b[33;20m"
red = "\x1b[31;20m"
bold_red = "\x1b[31;1m"
reset = "\x1b[0m"
format = f"[ %(asctime)s ] [ {bold}%(levelname)s{normal} ][ %(name)s:%(funcName)... |
5b4a189026a54028a2d2c4be7b5226c917ba5cdde6bbe56021809671e5258cee | Python | 1,151 | 45 | from subprocess import STDOUT, Popen, PIPE
def execute(command, cwd=None, shell=False, logger=None):
"""
Run external program as a subprocess and return its output
Args:
- command: (str) the command that will be executed.
- cwd: Current working directory. cwd argument for subprocess.Popen
- s... |
3f08044b20cc00c10d72f50b0bc95799e9b4f9ff3efef8330094c6c6ee7bbae1 | Python | 1,152 | 32 | """OpenEquivariance backend: e3nn parity. OEQ JIT-compiles CUDA/HIP kernels,
so execution requires a GPU (capability gpu); works on NVIDIA and AMD.
"""
# pylint: disable=wrong-import-position
import os
os.environ["TORCH_FORCE_NO_WEIGHTS_ONLY_LOAD"] = "1"
import pytest
from mace.cli.convert_e3nn_oeq import run as run... |
e6557f1fa8f0d3345277210b8aa9cd850dbfab1d328ce5f3d1c504234e8f8d08 | Python | 1,153 | 50 | import numpy as np
class AlignerTransformException(Exception):
"""Exception class for AlignerTransforms"""
pass
def aff_matrix(theta, offs=None):
"""affine matrix or augmented affine matrix
given a rotation angle.
Parameters
----------
theta : float
rotation angle in radians
... |
13af21bbf80ec590131970bee34614cd95f7a3eccede9ebeee0cd72e2fe0c8bb | Python | 1,157 | 33 | import pytest
import unittest
import torch
from reinvent.models import LibinventAdapter, SampledSequencesDTO
from reinvent.runmodes.utils.helpers import set_torch_device
from reinvent.models.libinvent.models.model import DecoratorModel
from tests.test_data import ETHANE, HEXANE, PROPANE, BUTANE
@pytest.mark.integra... |
465986e7339684f4488c9ac3c1d72cadb89523a9ff461bf93ed70b5959b73125 | Python | 1,157 | 31 | #
# For licensing see accompanying LICENSE file.
# Copyright (C) 2022 Apple Inc. All Rights Reserved.
#
from torch import nn, Tensor
from typing import Union, Tuple
class AdaptiveAvgPool2d(nn.AdaptiveAvgPool2d):
"""
Applies a 2D adaptive average pooling over an input tensor.
Args:
output_size (O... |
77af97de16a54565f3e8f3af0b1ddb5277d953b00f2086a1047dbb81a638a391 | Python | 1,157 | 31 | from dig.xgraph.dataset import SynGraphDataset
import shutil
def test_SynGraphDataset():
root = 'datasets'
dataset_names = ['ba_shapes', 'ba_community', 'tree_grid', 'tree_cycle', 'ba_2motifs']
dataset_length = [1, 1, 1, 1, 1000]
dataset_x_shape = [(700, 10), (1400, 10), (1231, 10), (871, 10), (25000,... |
2cac5e10faddeb54a66bd499ae6e97b5108621cb85591f3f763ef90a83033739 | Python | 1,159 | 30 | import os
import numpy as np
import h5py
from scipy.io import savemat, loadmat
from scipy import sparse
import glob
if __name__ == '__main__':
# Set the path of the 'GT Masks' folder, which contains the manual labels in 3D arrays.
dir_Masks = '../data/GT Masks'
# %%
dir_all = glob.glob(os.path.join(d... |
964a4585790ce7dce349a339d83bb59dbee1a942dab881f4db002de88a2284ea | Python | 1,159 | 37 | from pathlib import Path
from SimpleITK import ReadImage, WriteImage
from tqdm import tqdm
input_path: Path = Path("M:/Dataset/Loki")
output_path: Path = Path("S:/data/Loki/ref")
label_names: list[str] = ["tumor", "brain", "skin", "ventricles"]
patients = [x.resolve() for x in input_path.glob("*") if x.is_dir()]
pa... |
6ad9ed185d791d8a45e79922ad3cadc4ba9dce97bac9cee7ff779200ab9f8040 | Python | 1,161 | 39 | from typing import Any, Dict
_UNSAFE_KWARG_KEYS = frozenset({"trust_remote_code"})
_LOCAL_MODEL_LOADER_EMBEDDING_FUNCTIONS = frozenset(
{
"fastembed_sparse",
"huggingface_sparse",
"sentence_transformer",
}
)
def _contains_unsafe_kwarg(value: Any) -> bool:
if isinstance(value, dic... |
7f5749333f1e35727c5b7db439e54da2aa82b2858d55416e07b90cd68653d251 | Python | 1,161 | 43 | import numpy as np
from reinvent_plugins.components.RDKit.comp_tpsa import TPSA, Parameters
smilies = (
"Cc1[nH]c(=O)[nH]c(=S)c1C(=O)NC(C)(CO)CO",
"CC(c1cccc(F)n1)c1c(CCN(C)C)sc2ccccc12",
"N=c1[nH]cnc2c1cnn2CCC(=O)O",
)
def test_comp_tpsa():
expected_results = [np.array([118.21, 16.13, 107.65]), np.... |
231331dbe1c5958bf86c05bf4da0a29400a3d4c753591e86c7eada89ec97ea89 | Python | 1,162 | 32 | """Tests for plot-time data-loader key handling."""
import pytest
# mace.tools first on purpose: mace.tools.train imports TrainingPlotter, so
# importing mace.cli.visualise_train before it hits a partially initialised
# module. The cycle predates this test.
import mace.tools # noqa: F401 # pylint: disable=unused-im... |
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