sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
582292d89d36e8e12e00898352a1b62112cfb5033619e984762114d42e4693eb | Python | 4,570 | 122 | # Copyright 2018-2021 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
36fd2e4165a8878c90262042984724751818993e7585365a625faca0482797f3 | Python | 4,571 | 106 | import os
import sys
from copy import deepcopy
import torch.nn as nn
import torch
from evaluators.evaluator import Evaluator
from datasets.scar import SCAR
import datetime
from tables.generate_token_counts import count_neural_tokens
def neural_main(model_name, model_class, model_trainer, args):
"""
Moved the... |
3e27f2fbd78b92bb1b00106a89463c6f4f22baad295e4fa20e4715cfd87650c6 | Python | 4,571 | 137 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Jun 27 13:44:03 2023
@author: fm02
"""
import numpy as np
import pandas as pd
import pickle
import os
import mne
from mne.minimum_norm import read_inverse_operator
import warnings
warnings.filterwarnings('ignore')
path = '/imaging/hauk/users/fm02/De... |
3a41b1163124475f1333d15aef1086dc187f910271c4e70c2d9cc28ea877a114 | Python | 4,572 | 139 | import pytest
import torch
from mrpro.operators import IdentityOp, MagnitudeOp, Operator, ZeroOp
from mrpro.operators.LinearOperator import LinearOperatorSum
from mrpro.utils import RandomGenerator
from typing_extensions import assert_type
from tests import (
dotproduct_adjointness_test,
forward_mode_autodiff_... |
69f223c69d42941c252d5f50f95b74ecb2b0b0c5240295310de0c2a867591e2b | Python | 4,573 | 111 | """
=========================================================
Compute SESAME inverse solution on high-density EEG data
=========================================================
In the present example we shall show how to perform a source modeling analysis
using SESAME as a standalone software.
The data belongs to a r... |
7232dc9f4033c457da53f8ccb7b7a61f36300d318f70b317cb6461d966566969 | Python | 4,574 | 87 |
from ..utils import PheWebError
from ..file_utils import VariantFileReader, VariantFileWriter, get_filepath, get_pheno_filepath, with_chrom_idx, get_tmp_path, convert_VariantFile_to_IndexedVariantFile
from .load_utils import parallelize_per_pheno, get_phenos_subset, get_phenolist
import argparse, os
from typing impor... |
6c5e1364d9f04cdce0aee8624d94e02d3707883580545e92685c5e9ca9bfea3a | Python | 4,575 | 173 | # Copyright 2018-2021 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
0ac91689c8355475c12b234c1da66f4f01cebb14550d0446e9880843f94f1fd8 | Python | 4,578 | 133 | import numpy as np
import cv2
import torch
import torchvision.transforms as T
def normalise_adc(adc_image_in):
"""
Normalize an apparent diffusion coefficient (ADC) image.
Parameters:
- adc_image_in (numpy.ndarray): Input ADC image.
Returns:
- adc_image_out (numpy.ndarray): Normalized ADC ima... |
30989c8bf6402dca859b0b7e40d1a902f4e1bd54538aaa2d603021fae68b6c07 | Python | 4,579 | 125 | from __future__ import print_function
import tensorflow as tf
import numpy as np
import copy
npa = np.array
class Synthesizer(object):
def __init__(self, model, losses):
self._graph = model.graph
self._sess = model.sess
self._image = model.image_ph
self._losses = losses
self._model = model
... |
9ab13afa386ccfd4f0ff1a8acb3bbff8a43994d94400e2dd09d14c048616a18e | Python | 4,579 | 145 | import sys
sys.path.append('.')
from CommonSystem.Config import Config
from EventController import EventController
from tqdm import tqdm
from psychopy import event, visual, core
import os
import time
import math
import numpy as np
config = Config()
config.addSTI = 'StimulationSystem/pics'
config.addTG =... |
a2d4ff710ade954a57f34e77244e8b8f35b3cb0a311d7b8d880e210efa59cf4b | Python | 4,579 | 140 | import torch
import numpy as np
class SequenceAccuracy(object):
"""Computes accuracy between two sequences.
Inputs:
pred (N, L, C)
tgt (N, L)
ignore_index (int): index of token to mask out
"""
def __init__(self, ignore_index=-100):
self.ignore_index = ignore_index
... |
8f31c9ce900331b2b6ca9aa8980566ee24cc1ec2b332d514e7472a301c8cb245 | Python | 4,581 | 121 | #!/usr/bin/env python3
"""
Description:
Parallel SPIT parameter search using Python multiprocessing.
Usage:
./run_SPIT_search_params_python.py -m <tx2gene_file> -j <num_jobs> -e <num_experiments>
Author:
Beril Erdogdu
Date:
September 2025
"""
from multiprocessing import Pool, cpu_count
from functools ... |
711f6a84ee572cb1aabefe2bfd93f71e6fa1dce4638f74c24fa7a3116f5d2540 | Python | 4,584 | 138 | import sys
import math
from scipy.stats import norm
import numpy as np
from .util import stderr
def permutation_test(a, b, n_iter=10000, n_tails=2, mode='loss', agg='mean', nested=False, verbose=True):
"""
Perform a paired permutation test for significance.
:param a: ``numpy`` array; first error/loss/pr... |
51b8ebbbe14627032defa963b7b3dc807e8bd317b3df463004b32cada59e2118 | Python | 4,586 | 157 | import numpy as np
from numba import njit
import math
from kilosort.CCG import compute_CCG, CCG_metrics
def count_elements(kk, iclust, my_clus, xtree):
n1 = np.isin(iclust, my_clus[xtree[kk, 0]]).sum()
n2 = np.isin(iclust, my_clus[xtree[kk, 1]]).sum()
return n1, n2
def check_split(Xd, kk, xtree, iclust, m... |
6469648b6668542850d5631b50c278dc9efc81d7f903a24e8079b2012167fddb | Python | 4,586 | 115 | import torch
from torch.utils.data import Dataset
import copy
import random
class PPODataset(Dataset):
def __init__(self, batch_size, minibatch_size, is_discrete, is_rnn, device, seq_length, permute=False):
if batch_size % minibatch_size != 0:
raise ValueError("Batch size must be divisible by ... |
f574b239640a982338db2e108dba723ee3ba172bd680912ad7b269dfb840d8b8 | Python | 4,586 | 171 | import os
from pathlib import Path
import pandas as pd
from nilearn.maskers import NiftiLabelsMasker, NiftiMapsMasker
from sklearn.utils import Bunch
ATLAS_METADATA = {
"schaefer7networks": {
"atlas": "Schaefer2018",
"template": "MNI152NLin2009cAsym",
"resolution": 2,
"dimensio... |
704d32df5a379fb040f533584058de0aee1541e26126ad8cef2e5d4b71c1fd17 | Python | 4,587 | 129 | """`RegressionExperiment` — the PyCaret 4.0 regression engine.
Canonical import:
from pycaret.tasks import RegressionExperiment
# or (backward-compat):
from pycaret.regression import RegressionExperiment
Example
-------
>>> from pycaret.datasets import get_data
>>> from pycaret.tasks import RegressionEx... |
deee4c05d46f068a3ac5c129c66e2721225339bd7b86cd62146e7b66dfe0855e | Python | 4,587 | 116 |
from typing import Callable, Optional, Union
import torch
from torch import Tensor
from torch_sparse import SparseTensor, matmul
from torch_geometric.nn.conv import MessagePassing
from torch_geometric.nn.dense.linear import Linear
from torch_geometric.typing import Adj, OptPairTensor, OptTensor, Size
from torch_geo... |
2f60d62590272e5a02bc4901459d6542408160efd58046bbab4e8cbbc3e92e19 | Python | 4,590 | 128 | #####################################################################################################################
# Date created : 10/21/2022
# Date modified: 5/3/2023
# Purpose : This program reads and loads inputs data and passes them to the inference program
##############################################... |
5ea4c50d8f57fe87baf162c8fa4eac1f7eda0bcadea7541d072f5b0585cef82d | Python | 4,590 | 113 | """Tests for sliding windows."""
import pytest
import torch
from mrpro.utils import RandomGenerator
from mrpro.utils.sliding_window import sliding_window
def alternative_implementation(data, window_shape, axis, stride):
"""
Alternative implementation of sliding window for testing purposes.
No error handl... |
a5b9174caa8326e3f41bf11b423db2e2b1a9e726bd821905fde367e78a236857 | Python | 4,591 | 123 | import datetime as dt
import os
from typing import List, Optional
import ngs_tools as ngs
from typing_extensions import Literal
from . import config, constants, preprocessing
from .logging import logger
from .stats import Stats
@logger.namespaced('consensus')
def consensus(
bam_path: str,
gtf_path: str,
... |
4780a53a5dd6afe00c54d859cac16aa2f85815071932504d076975afa46d2cf1 | Python | 4,602 | 133 | import matplotlib
# matplotlib.use('Agg')
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
import numpy as np
import os
import argparse
import matplotlib as mpl
label_size = 16
#mpl.rcParams['xtic... |
8fc8af30584067220d1b1a23d9865ee82d29042150f6b2c7e987341f55d88b10 | Python | 4,602 | 126 | import glob
import os
import parserix
from cptools2 import utils
def detect_plate_layout(plate_dir, ext=".tif", clean=True, truncate=True, sanitise=False):
"""
Detect whether a plate directory follows the old or new ImageXpress layout.
Old layout (is_new_ix=False): plate_dir/*/*/*/*.tif (3 levels)
... |
eb7fbf8c14578d34f594c0750501421459a77bd2b619edc3dc998710d71fc9f9 | Python | 4,605 | 151 | import numpy as np
from scipy.stats import norm
def bw_nrd0(x: np.ndarray) -> float:
x = np.asarray(x, dtype=float)
x = x[np.isfinite(x)]
n = x.size
if n < 2:
raise ValueError("Need at least 2 finite observations.")
sd = np.std(x, ddof=1)
q75, q25 = np.percentile(x, [75, 25], method="... |
db60f31c3f360b176d722455bda14613a064a9ed352b87f172f474f39a22d758 | Python | 4,606 | 105 | #
# Python module to implement equivariant neural network
# based on Clebsch-Gordan networks. This module uses linearity.py
# and nonlinearity.py to implement the linear and nonlinear operations
# of CG networks. Then it implements a dense layer at the end to
# classify the scalar output of every layer in the CG netwo... |
dbec3e3ca1bb7d600bb4d7b0cf4fa55841dd7790e0a4a3fd883d5c563c0b3fd3 | Python | 4,606 | 150 | """
EA-compatible analogue to np.putmask
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
)
import numpy as np
from pandas._libs import lib
from pandas.core.dtypes.cast import infer_dtype_from
from pandas.core.dtypes.common import is_list_like
from pandas.core.arrays import ... |
1714558e9c38a9ed8f87a9715a75fb4a9d310810a7615b7c6a104a3002c3e9ca | Python | 4,609 | 117 | # -*- coding: utf-8 -*-
"""Average Attention module."""
import torch
import torch.nn as nn
from onmt.modules.position_ffn import PositionwiseFeedForward
from onmt.modules.position_ffn import ActivationFunction
class AverageAttention(nn.Module):
"""
Average Attention module from
"Accelerating Neural Tran... |
7e0496fb7f69c7734d5646b919221b9d1caabb665c1c8b1306cf77aa9d4f6ec8 | Python | 4,610 | 117 | import os
import logging
import argparse
import numpy as np
from .powderaverage.powderaverage import powder_average, save_data_as_npz
from .models.nexi import Nexi
from .models.parameters.acq_parameters import AcquisitionParameters
from .models.parameters.save_parameters import save_estimations_as_nifti
from .nls.nls i... |
62451f3823ba9a3890b81015e0a39cdb8486a010e2ee9e5fdbf2eb1324eaea7d | Python | 4,611 | 142 | import numpy
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from sklearn.decomposition import PCA
def updateColumnName(df, dictionary):
allIndex = df.columns.values
for i in range(len(allIndex)):
if allIndex[i] in dictionary:
allIndex[i] = dictionary[allIndex[i]]
... |
7c741677308f9a95d0677a9544cf105ce22c5ad72406026455532e828cf93a7f | Python | 4,613 | 128 | # -*- coding: utf-8 -*-
"""
Created on Fri Oct 13 14:46:54 2023
@author: nrq2
"""
## ssh rachel@nostromo.ncl.ac.uk
## spyder-scenic-ad3
# cd /data/rachel/Linda_Lako/Retina/AD3/ATAC_analysis/SCENIC/
# conda activate scenicplus
# python -m spyder_kernels.console
# /home/rachel/.local/share/jupyter/runti... |
ee364589faacd865e74573f4dd384c11108771bccf4649118665076c83c673d3 | Python | 4,616 | 144 | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import argparse
from pathlib import Path
class Flags:
def __init__(self):
self.parser = argparse.ArgumentParser(
de... |
87e90b8edafced0e5f1effbbf42277a5471c46655fd8329f327d5fefc9f597df | Python | 4,617 | 158 | import pathlib
from textwrap import dedent
import tomllib
import pytest
import yaml
from scripts.validate_min_versions_in_sync import (
get_operator_from,
get_toml_map_from,
get_versions_from_ci,
get_yaml_map_from,
pin_min_versions_to_yaml_file,
)
DATA_PATH = pathlib.Path(__file__).parents[2] / "... |
227a4cf8223f119d3543c340c86489254385b0ebd2fbe02ff104be67fc9d13b0 | Python | 4,619 | 160 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
@pytest.fixture
def ser():
return pd.Series([1, 2, 3], index=["x", "y", "z"])
@pytest.mark.parametrize(
"mask",
[
[False, True, True],
np.array([False, True, True]),
pd.array([False, True, True], d... |
2d8b48a74b03ef7c5cf264c5b9b50b43d2dfe54f29daac3b4087913982545eb4 | Python | 4,619 | 121 | """Run under Windows CPython3.9 with the unchanged author pre.pyd.
Usage: python generate_oracle.py SOURCE_DIR OUTPUT_DIR
SOURCE_DIR contains pre.cp39-win_amd64.pyd, original model.bin, and extracted
Conventional.txt (checksum checked). Only pickle.loads is substituted, providing
an object with the same fitted estimat... |
446af67ffd675fccb4fed238df991e961429b16d6a202d779803179c8090ad56 | Python | 4,619 | 169 | # Copyright 2018-2026 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or ... |
d4a46c2a700edf36d4fe1f26da0a58d94525fc63cb6fa5e358ba958bf12fb2bf | Python | 4,622 | 147 | import csv
import os
import pytest
from aigarmic.model import BinaryModel, BinaryNestedModel
from aigarmic.plate import Plate
from aigarmic._img_utils import get_image_paths
from aigarmic.file_handlers import get_concentration_from_path
from aigarmic.train import train_binary
from aigarmic._nn_design import model_desi... |
94daaee1c1a5ea2f9c84a5ed4c7f58071876603c9237297f964e60beb48dc24b | Python | 4,623 | 115 | import datetime
class OperationState:
def __init__(self):
self.receiver_state = 'INIT'
self.control_state = 'INIT'
self.current_detect_state = 'INIT'
class operationOperator:
def __init__(self):
self.messenager = None
self.streaming = None
... |
829be65eee8c4d248051a565acf2604a5405f9715017464bda82dfb423609043 | Python | 4,625 | 105 | """Tests for finite difference operator."""
from collections.abc import Sequence
from typing import Literal
import pytest
import torch
from einops import repeat
from mrpro.operators import FiniteDifferenceOp
from mrpro.utils import RandomGenerator
from tests import (
dotproduct_adjointness_test,
forward_mode... |
5e509093bacb234dfe6919734044bc41a387b170508256707bc96d2517c6bafa | Python | 4,627 | 166 | """
collection of helper functions
"""
from __future__ import print_function, division, absolute_import
import logging
import os
from glob import glob
from collections import defaultdict
import tables
from .. import NcsFile, options
logger = logging.getLogger(__name__)
def check_sorted(channel_dirname):
"""
c... |
b04c67b051d2283d0eba5a16c4bc9f93717b99f148b4fe959a0baa2a14611714 | Python | 4,627 | 119 | """Multi-discrete regression tests: masked path with heterogeneous head sizes
(np.split chunked equally and mis-sliced e.g. [3,5,7] heads), batch-size-1
forward coverage, and the DiscretizeActions wrapper."""
import gymnasium as gym
import numpy as np
import pytest
import torch
from rl_games.algos_torch.model_builder... |
ab655c472d9a1e576a232d7add9879204798fe1afbd588983e02437609751241 | Python | 4,629 | 130 | import torch
import numpy
import bionetwork
import plotting
import pandas
import argparse
import seaborn as sns
from scipy.stats import pearsonr
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
folder = 'figures/SI Figure 10/'
#Get data number
testCondtions = pandas.read_csv('synthNetTime/conditi... |
b9fff2eea45fe506a00705518d9869085323655b3b53d736980ecf35b2fde3c7 | Python | 4,633 | 107 | import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
import tensorflow as tf
from tensorflow.keras import backend as K
from tensorflow.keras.models import load_model
from tf_explain.core.grad_cam import GradCAM
from functions.OneDCNN_Utils import *
from scipy.io import loadmat
from sklearn.model_selection import Strati... |
7c9a07cb7bbc6369c5e2deaa5095cc4b822658be0d95b5ecd2bda212727215de | Python | 4,634 | 134 | import os
import pandas as pd
from deepglyco.chem.common.elements import ElementCollection
from deepglyco.chem.gpep.fragments import GlycanFragmentTypeCollection
from deepglyco.chem.gpep.glycans import MonosaccharideCollection
from deepglyco.chem.gpep.gpmass import GlycoPeptideMassCalculator
from deepglyco.chem.pep.am... |
2ff83e20fa6017fa94182778faec8b43c2f0931df363309f16bd5f69e555335c | Python | 4,635 | 84 | '''This module contains methods to compare the result of the SingleCellInputMapper to
the neuronet population.'''
import glob
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from ..IO.roberts_formats import read_InputMapper_summary
from ..utils import select
from ..analyze import excitatory, ... |
45cf2be4d98726673783d4171ec92794a8d3c3dde157c82fc5a84200a25ea6a4 | Python | 4,635 | 116 | import datetime
import sys
class OperationState:
def __init__(self):
self.receiver_state = 'INIT'
self.control_state = 'INIT'
self.current_detect_state = 'INIT'
class operationOperator:
def __init__(self):
self.messenager = None
self.streaming = ... |
4688e872c3f50501fa7866e0bac6b0d28d6bdd64f9062e600198cfb4083353e2 | Python | 4,636 | 119 | from datetime import timedelta
import numpy as np
import pytest
from pandas.errors import OutOfBoundsTimedelta
import pandas as pd
import pandas._testing as tm
from pandas.core.arrays import TimedeltaArray
class TestTimedeltaArrayConstructor:
def test_other_type_raises(self):
msg = r"dtype bool cannot ... |
e2051910334d95f4c97c8e2650f8e6ba4d3fc9073323aac2af53ba39a9469ab6 | Python | 4,636 | 143 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
01084385df95344ac1982ccc46c944ac7ea86fb4bdc116abd04e11c07a4ee292 | Python | 4,637 | 153 | """Unit test for parellel cooridnate-gathering routine"""
import os
import sys
import numpy as np
from pathlib import Path
import h5py
#import pyrosetta
import logging
import pytest
import protein_holography
from protein_holography.coordinates.get_structural_info import (
get_structural_info_from_dataset)
from p... |
6b9394c932f029986346ba473ea247d89b35600e530fb0807e19a64cf3eb7448 | Python | 4,638 | 155 | # -*- coding: utf-8 -*-
"""
Created on Thu Mar 10 16:05:07 2022
This file contains convenience loading functions for different situations and
analysis scenarios. However, this repository only contains the subset
necessary for reproducing the manuscript results
@author: Simon Kern
"""
import logging
import numpy as n... |
7614f80a67fbe2dbe7cc13a066dab1487bf6a9480a5c362a6a3700d3e49e8db1 | Python | 4,638 | 164 | """
Run the base extension tests against an EA whose ``dtype.na_value`` is None.
See GH#44602.
"""
from __future__ import annotations
import decimal
import functools
import numpy as np
import pytest
from pandas.api.extensions import (
register_extension_dtype,
take,
)
from pandas.api.types import (
is_... |
3494a69209cd37407e77954b30173fa04e041e6713d2de011423df53ecefe865 | Python | 4,642 | 166 | """Extract features for temporal action detection datasets"""
import argparse
import os
import random
import numpy as np
import torch
from timm.models import create_model
from torchvision import transforms
# NOTE: Do not comment `import models`, it is used to register models
import models # noqa: F401
from dataset.l... |
80c9f766bc4d22c130a88b88beaff228cb02e378c1b2f692b428ea28157608cc | Python | 4,644 | 109 | #!/usr/bin/env python3
"""Derive a hybrid-type -> hydration (waters) lookup from somo.residue.
Mattia's step 3: "We could potentially build a table of atom hybridizations from our
somo.residue table linked to their hydration numbers. Based on this, for the new residue ...
proposed atomic hydration are shown, to be int... |
c1ed53089863e0e5d3d10e09a1df8227870861532fbe61d1c2210c656f40c2fc | Python | 4,644 | 121 | import numpy as np
import matplotlib.pyplot as plt
import sys
import os
from kcsd import sKCSD
from kcsd import sKCSD_utils as utils
import kcsd.validation.plotting_functions as pl
import sKCSD_utils
n_src = 512
R = 16e-6/2**.5
lambd = .1/((2*(2*np.pi)**3*R**2*n_src))
if __name__ == '__main__':
fname_base = "Figure... |
51ee9630a7dc8ccd49641a4baf87784b1183bb53577557d1d1e5b21fadeda0ff | Python | 4,645 | 138 | import numpy as np
from scipy import stats
from ._test import MantelResult
try:
import matplotlib.pyplot as plt
from matplotlib.axes import Axes
except ImportError:
plt = None
def plot(
result,
axis=None,
alpha=0.05,
hist_color="lightgray",
gaussian_color="black",
acceptance_color... |
73254a3f0d6436361bf6b5e6d3f005e993a5fc0ab11012b197c6c13547a04066 | Python | 4,646 | 112 | import os
import numpy as np
import torch
import random
from sklearn import metrics
from torch.utils.data import DataLoader
import torch
import torch.nn as nn
from sklearn.metrics import roc_auc_score, average_precision_score,accuracy_score
from tqdm import tqdm
from utils.graph_utils import collate_dgl, move_batch_to_... |
2d60ea7187c4e4b99a562772c67ff26c06908715fe295a3f0a9e6050319a9a2e | Python | 4,648 | 103 | import numpy as np
import pygalmesh
from .curveExamples import Circle
from .surfaceExamples import Sphere
import loggingUtils
from .meshes import Mesh, select_faces__
class TwoDiscs(Mesh):
def __init__(self, largeRadius = 10., smallRadius = 4.5, targetSize=250):
f = Circle(radius=largeRadius, targetSize=t... |
5e6b8755134c124e489b3beb8ab2200037f54d4564c537a68b60b300d49d4fd0 | Python | 4,648 | 158 | from __future__ import annotations
import json
import locale
import os
import platform
import struct
import sys
from typing import TYPE_CHECKING
from pandas.util._decorators import set_module
if TYPE_CHECKING:
from pandas._typing import JSONSerializable
from pandas.compat._optional import (
VERSIONS,
ge... |
5fdd14209bd955dbd7ce975ba1774f073dc7c32038be732692e31db135c6519c | Python | 4,649 | 176 | """
Tests for the `deprecate_nonkeyword_arguments` decorator
"""
import inspect
from pandas.errors import _CurrentDeprecationWarning
from pandas.util._decorators import deprecate_nonkeyword_arguments
import pandas._testing as tm
WARNING_CATEGORY = _CurrentDeprecationWarning
@deprecate_nonkeyword_arguments(
WA... |
bc0f64a62e1e2083e111c97e72e888dd79b2693344071bc9a75a2e64be97df5e | Python | 4,650 | 145 | """
Tests for plotting compatibility.
"""
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Literal,
)
if TYPE_CHECKING:
from matplotlib import (
axes as maxes,
axis as maxis,
lines as mlines,
)
from pandas.core.arrays import ExtensionArray
import num... |
46f1051437ce5789e66ab84710bf5ef182aea819724c3070006346dc73b38ad9 | Python | 4,655 | 158 | import random
import time
from deepglyco.chem.common.elements import ElementCollection
from deepglyco.chem.pep.aminoacids import AminoAcidCollection
from deepglyco.chem.pep.mods import ModificationCollection, ModifiedSequenceParser
from deepglyco.deeplib.pep.rt.data import PeptideRTDataConverter, PeptideRTDataset
from... |
98b0721e7cd82e448ffc91f9c793b7606e58bb74cb5371cfcb060e90b497ec45 | Python | 4,658 | 89 | import pandas as pd
import os
import warnings
from eLife_Grid_anchoring_2024 import analysis_settings
from eLife_Grid_anchoring_2024.Helpers.array_manipulations import *
warnings.filterwarnings("ignore")
def add_shuffled_cutoffs(recordings_folder_to_process):
recording_list = [f.path for f in os.scandir(recordin... |
187fea317bce927c7b39fb91c2b1a1d0bef6cb20ce0f78d0bf162559d405274a | Python | 4,660 | 153 | import decimal
import warnings
import numpy as np
import pytest
from pandas.core.dtypes.cast import (
maybe_downcast_numeric,
maybe_downcast_to_dtype,
)
import pandas as pd
import pandas._testing as tm
@pytest.mark.parametrize(
"arr,dtype,expected",
[
(
# This is a judgement cal... |
0994afb9b61b6d80ca4d08e874e0c44404c3e44ccb2fd8a5aa8450df9d53fe3a | Python | 4,662 | 125 |
# -*- coding: utf-8 -*-
"""
Created on Thu Dec 16 17:09:27 2021
@author: Daniel Hulsey
this script aligns a ccf to an individual session, and extracts dff data for each indicated region.
Running it fully requires:
1. saved dff trace for the session being analyzed
2. saved points to align CCF to multim... |
c8ab85558f5fc5bf26ba81d7815535b61723ff4e0e5f08dfbc2e3b59eeef7efc | Python | 4,663 | 137 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
def test_isin_nan():
idx = pd.MultiIndex.from_arrays([["foo", "bar"], [1.0, np.nan]])
tm.assert_numpy_array_equal(idx.isin([("bar", np.nan)]), np.array([False, True]))
tm.assert_numpy_array_equal(
idx.isin([("bar", ... |
cf9425969f271c1a20acd63cb07dd5c3b6337d7a193886f5b01da1314566bcbc | Python | 4,663 | 139 | from typing import Optional
import torch
import torch.nn.functional as F
from torch import nn, Tensor
from .functional import label_smoothed_nll_loss
class SoftBCEWithLogitsLoss(nn.Module):
"""
Drop-in replacement for nn.BCEWithLogitsLoss with few additions:
- Support of ignore_index value
- ... |
7513f39fe0885f4ab9340637310f9c0c9d7c757d9ce48f30c78e3bb5d00251ef | Python | 4,664 | 139 | # -*- coding: utf-8 -*-
"""
Created on Thu Dec 17 13:14:28 2020
@author: derek.bickhart-adm
"""
import matplotlib
from matplotlib import pyplot as plt
matplotlib.use('Agg')
from matplotlib.collections import BrokenBarHCollection
from matplotlib import cm
from itertools import cycle
from collections import defaultdict... |
35392806cadbf268771399eab9437a4aa33497b3968f0a2ffedee2ea413a02ea | Python | 4,665 | 99 | import os
import numpy as np
from draw import draw_angle_stimulus
from result_plotter import ResultPlotter
from utils import mkdir_experiment_setup, Observable, downsample_data
from network import AngleSpatialConnectivity, RandomClusterConnectivity
from model import IzhikevichKorndoerfer
from image_preprocessor import... |
5a97c45d2d415ecc461929349e6fcb7569b3b407e9ac00c2d51127f565a6ddba | Python | 4,667 | 115 | import torch.nn as nn
import math
import torch.utils.model_zoo as model_zoo
import torch
import torch.nn.functional as F
class Bottle2neck(nn.Module):
expansion = 4
def __init__(self, inplanes, planes, stride=1, downsample=None, baseWidth=26, scale = 4, stype='normal'):
super(Bottle2neck, se... |
ba63210194a093ed39f381875836d7f4b9c669a2ad4194c875a68ad38a973984 | Python | 4,668 | 143 | # -------------------------------------------------------------------------------------------------------------------------------------
# Following code curated for GCPNet (https://github.com/BioinfoMachineLearning/GCPNet):
# ----------------------------------------------------------------------------------------------... |
fa0334bf51b26484228cbde465410edce5384a8b12ffab63fa7e7a7be4571800 | Python | 4,669 | 95 | #!/opt/local/bin/python2.7
from os import path
import argparse
from Common.kernelFunctions import *
from affineRegistration import *
from Surfaces.surfaceMatching import *
def main():
parser = argparse.ArgumentParser(description='runs surface matching registration and exports labels from subregions')
parser.a... |
0fd71ad866ed055722cc95630a3d5dea19ac234b675601a462ebd45180a89a9d | Python | 4,670 | 147 | ## Works the best so far! Curve fits nicely and ymin/ymax don't have to be 0 and 1!
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from scipy.optimize import curve_fit
import sys
import matplotlib.ticker as ticker
import matplotlib.transforms as transforms
from pathlib import Path
from statisti... |
2a0fe31879973babbe98a7e27c0f8645f75037d4526e16f37e8df0b8f93fcf7a | Python | 4,671 | 115 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Dec 2 21:24:41 2021
Script to prune the original set of brain imaging files from PPMI to select
those that will be uploaded to the cloud. Two steps are applied:
1. Get rid of entire sessions which had corrupted or missing files (DTI
and resting... |
3dc4882814c6daffeccf150f9c5f9fe59c68fbeed270af0f76643c9fa903de70 | Python | 4,673 | 107 | #! /usr/bin/env python
##############################################################################
## DendroPy Phylogenetic Computing Library.
##
## Copyright 2010-2015 Jeet Sukumaran and Mark T. Holder.
## All rights reserved.
##
## See "LICENSE.rst" for terms and conditions of usage.
##
## If you use this wo... |
e3a4a7ebfe9f3b03bfad635e8e63559e46193825ebbf0fad42ea12b0fc580cde | Python | 4,674 | 121 | import sys
import argparse
from Bio import SeqIO, BiopythonWarning, BiopythonParserWarning
import sys
import re
import random
import statistics
import warnings
def clean_name_func(name):
"""
converts all: " " (space), ";" (semicolon), ":" (colon), "," (comma), "()" (parentheses), "'" (quote) charact... |
8782007a7a8d193e8408a559ab8850536660208b49db83704b94701678809b5c | Python | 4,675 | 95 | import argparse
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
def get_args():
"""
Get arguments from command line with argparse.
"""
parser = argparse.ArgumentParser(
prog='Plot-Main.py',
description="""Make informative figures from pre- and post-filtered bin... |
c3cf6d5007b46f391cae3f6cc4fedbbd26992eb2bdb79ac8bb203eafa808cce7 | Python | 4,675 | 150 | """
Tests for the following offsets:
- Easter
"""
from __future__ import annotations
from datetime import datetime
from dateutil.easter import (
EASTER_ORTHODOX,
EASTER_WESTERN,
)
import pytest
from pandas.tests.tseries.offsets.common import assert_offset_equal
from pandas.tseries.offsets import Easter
c... |
f2372287bd10cdc1954259fde7ff0b3971c17c2b9608090e8a4a149b767e2a82 | Python | 4,675 | 124 | import torch
from torchvision import datasets, transforms
from tnn.layers import Permute, View, LinearLayer, tLinearLayer
from tnn.networks import FullyConnected
# from tnn.training.batch_train import train
from autoencoder_batch_train import train
from tnn.utils import seed_everything, number_network_weights, get_logg... |
edb3285db1cb3c23e8dd3041f3fef593de081b9ca2964512d8354b95fe5090dc | Python | 4,676 | 123 | import os
import numpy as np
from sdna.net.functional import utils
class BitEncodeStream(object):
def __init__(self, inp_, outp_, blocksize, index_size):
self.input = inp_
self.output = outp_
self.blocksize = blocksize
self.index_size = index_size
self.padding = self.get_p... |
89d86a78c23ca9fa3cf06c7560262a16bfcb60e1e63ff5a9422ef30bdf765a93 | Python | 4,677 | 126 | import sys
import re
import numpy as np
import pandas as pd
import librosa
import argparse
argparser = argparse.ArgumentParser('''
Utility for computing sound power metrics from the Natural Stories audio stimuli
''')
argparser.add_argument('files', nargs='+', help='Paths to audio files for processing')
argpars... |
4ce100af265be057e59bbc250f0a97c0d618657d67167eb4d25875c59c11c775 | Python | 4,679 | 160 | from abc import ABC, abstractmethod
from typing import Optional, Type, Union
import tqdm.notebook
import tqdm.std
from pycaret.internal.display.display_backend import (
DatabricksBackend,
DisplayBackend,
JupyterBackend,
)
from pycaret.internal.display.display_component import DisplayComponent
class Prog... |
7f1e15bb1490f9f81664448044cac27fa2cb436cb310fa33cac45057f865d30c | Python | 4,679 | 152 | """Superuser-only admin routes.
Routes (mounted under ``/api/v1``):
GET /admin/users list all users (superuser-only)
PATCH /admin/users/{id} toggle is_superuser / is_active
These are the cross-workspace controls — anything scoped to a single
workspace lives under ``/workspaces/{id}/...`` (see memb... |
01b51a643cb52a5f6b4d6fa332fc26025d2f5567a320390f296bd5ddb1bc0f26 | Python | 4,681 | 153 | from typing import Iterable
import numpy as np
import pandas as pd
from scipy.spatial.distance import squareform, pdist
from sequence_models.constants import STOP, START, MASK, PAD
from sequence_models.constants import PROTEIN_ALPHABET
def warmup(n_warmup_steps):
def get_lr(step):
return min((step + 1) ... |
5a884a19d3fa3ac7910b3a33af62428477c7d04e3f42ff8d68daeff2c0ab5482 | Python | 4,681 | 182 | import matplotlib.pyplot as plt
import matplotlib
from matplotlib.colors import LinearSegmentedColormap
import numpy as np
import matplotlib.ticker as ticker
import pandas as pd
import seaborn as sns; sns.set()
from statistics import mean, stdev
import matplotlib.transforms as transforms
import matplotlib.font_manager ... |
7ac72c93e6f4b8d4812dec6f56922c690056f208f839c136197e9ef3f8d1be7d | Python | 4,682 | 144 | # Configuration file for the Sphinx documentation builder
import os
import sys
sys.path.insert(0, os.path.abspath(".."))
# Project information
project = "PCNToolkit"
copyright = "2025, Andre Marquand"
author = "Andre Marquand"
release = "1.0.0"
# Extensions
extensions = [
"autoapi.extension",
"sphinx.ext.aut... |
31a0f511a62de52aac90c8b4368efc240cfd608b8935ea67b9405743f095037d | Python | 4,683 | 107 | """
Display (and eventually generate) a set of correlated phenotypes as generated from an external pipeline
This information will be shown on phenotype summary pages. This is an OPTIONAL feature-
if information is not available, it will usually skip this step without failure.
"""
import logging
import os
from bolt... |
a8262c2f032472d316f101cb3c0551c9ba699b9f03c71d003a7ba1366834717c | Python | 4,683 | 101 | """Tests for DirectReconstruction."""
import pytest
import torch
from mrpro.algorithms.reconstruction import DirectReconstruction
from mrpro.data import CsmData, DcfData, KData
from mrpro.operators import DensityCompensationOp, FourierOp
def test_direct_reconstruction_automatic(cartesian_kdata: KData) -> None:
"... |
352347975b9f2da9e8652e61997dee8067e57724d0f1b0aea2a178483a2fc4ba | Python | 4,685 | 127 | # -*- coding: utf-8 -*-
# Copyright (C) 2019 Andrea Vázquez Varela
# 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 3 of the License, or
# (at your option) any later version.
#... |
e355925a7ebe1579c0f6faeb8973784981fd80bbb03ca7a2c269c733c857e9aa | Python | 4,685 | 153 | import numpy as np
from numpy import linalg as LA
from typing import Dict, List, Tuple
def trace(img_dict: Dict[str, np.ndarray]) -> Tuple[np.ndarray, np.ndarray]:
"""
Compute the trace of the diffusion tensor at b-value 50 and 1000.
Parameters
----------
img_dict : dict
A dictionary conta... |
e5efa0882676aa6edf5f97029a16d15c2d2b914d2d554dd93815958ac868bac6 | Python | 4,686 | 104 | import pandas as pd
from rdkit.Chem import PandasTools
import torch
from pytorch_classes_and_functions import AmesDataset, DNN
from captum.attr import LayerIntegratedGradients
from local_evaluation_functions import attribution_auc, get_attribution_for_hidden_layer
from helper_functions import string_to_int_list,d... |
bf985e804a926826ad701a5bdb4066adcc91ebd7ac40883b5ddc6edcd2724251 | Python | 4,690 | 121 | import logging
import numpy as np
from pathlib import Path
from time import time
from typing import Dict, Tuple
import xml.etree.ElementTree as etree
from fastmri_prostate.reconstruction.dwi.regridding import trapezoidal_regridding
from fastmri_prostate.reconstruction.dwi.diffusion_metrics import compute_trace_adc_b15... |
f6d4ffb8c84868389969758e2e1d0361406cf8d1b639683ffc51457f5da18adf | Python | 4,692 | 112 | """Methods for encoding text into brain maps."""
import numpy as np
from nilearn.masking import unmask
from sklearn.feature_extraction.text import CountVectorizer
from nimare import references
from nimare.decode.utils import weight_priors
from nimare.due import due
@due.dcite(references.GCLDA_DECODING, description="... |
a97a9bac57cdda965ba72a06fba2811b3772935b888a9714961e752ffc172281 | Python | 4,693 | 87 | import pandas as pd
import os
import warnings
import matplotlib.pylab as plt
from eLife_Grid_anchoring_2024.Helpers.array_manipulations import *
warnings.filterwarnings("ignore")
def plot_field_shuffle_false_assay(recordings_folder_to_process):
recording_list = [f.path for f in os.scandir(recordings_folder_to_pr... |
d8a3249f5361acea089b83f68032a891dba88544ca5cd61cc8a4dc11b2dc495e | Python | 4,693 | 120 | """
Creates CA1 pyramidal cell model, sets parameters, runs simulation in NEURON and shows figures.
Title: main_TBS_SLM.py
Author: Matus Tomko
Mail: matus.tomko __at__ savba.sk
"""
import libcell as lb
from neuron import h, gui
from CA1_plasticity.io.figures_shower import FiguresShower
from CA1_plasticity.io.io_helper... |
e2d1e13e722a3b68bf31cb3f0f868f5848e324165876a25308c683b9d9cd16fb | Python | 4,694 | 208 | import numpy as np
import cv2
import os
from os import listdir, makedirs
from os.path import join
from PIL import Image
import shutil
import sys
import logging
def crop_numpy(dim1, dim2, dim3, vol):
return vol[
dim1 : vol.shape[0] - dim1,
dim2 : vol.shape[1] - dim2,
dim3 : vol.shape[2] - d... |
2713a4a719804d39321ed827dbfd0d270d7b1f06797b3e2c1f7f1758c44b30b2 | Python | 4,696 | 113 | # -*- coding: utf-8 -*-
"""
Created on Thu Jul 18 16:39:53 2019
@author: Wladek
"""
import scipy.stats as st
import os
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from figure_properties import *
def set_axis(ax, x, y, letter=None):
ax.text(x,
y,
... |
07bf796ed7319dab986243e74c430576ee3e780ede1e8d5fa620aebc1b0a5e6f | Python | 4,699 | 143 | """Authentication routes: login, refresh, logout, me."""
from __future__ import annotations
from datetime import UTC, datetime
from typing import Annotated
from fastapi import APIRouter, Depends, HTTPException, status
from sqlalchemy import select
from sqlalchemy.orm import Session
from pycaret_server.api.schemas i... |
edba25a6b2488af10986fe7782e0ca248211c6fd2a21cdaa0065db36081c18c9 | Python | 4,699 | 129 | import os
os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
import math
import numpy as np
import tensorflow as tf
from tensorflow.keras import layers
import logging
tf.get_logger().setLevel(logging.ERROR)
class Envelope(layers.Layer):
"""
Envelope function that ensures a smooth cutoff
"""
def __init__(self... |
a3562272bfc3d44caa6f946e0fa8e302389821eabce5a25d2be85194052157d9 | Python | 4,700 | 133 | # Copyright 2018-2021 Xanadu Quantum Technologies Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
1ba4d1941e891617685d8ae7b17e16450cec6a5b34d9d5b61438dd1c00f14c81 | Python | 4,702 | 137 | import os
from functools import cached_property, cache
from typing import Tuple
from pandas import DataFrame, read_parquet
import numpy as np
import torch
import zarr
from tifffile import imread, TiffFile
from torch.utils.data import Dataset
class CustomDataset(Dataset):
def __init__(self, config: dict):
... |
61da39409d8923556259ee8109baad157d45a2e1e0d2429aa99bf7b8375538c0 | Python | 4,702 | 192 | from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
ClassVar,
)
import numpy as np
from pandas.util._decorators import set_module
from pandas.core.dtypes.base import register_extension_dtype
from pandas.core.dtypes.common import is_float_dtype
from pandas.core.arrays.numeric imp... |
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