sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
3d62984abbaf13458054569ecfd519d4bf4169ec0353155340f360d0c3bbed38 | Python | 2,072 | 57 | import torch.nn as nn
import torch
from typing import List, Dict
class ClosedFormLinearModel(nn.Module):
def __init__(self, n_cells: int, height: int, width: int,
train_with_gradient_descent: bool = False):
super(ClosedFormLinearModel, self).__init__()
self.linear_filters = nn.... |
a2d397d0fc1b6521b30a0dc4891c269a270dcbcbc34218e98ea69771618a6d6b | Python | 2,073 | 67 | import unittest
import numpy as np
import pytest
import torch
import pfrl
assertions = unittest.TestCase("__init__")
@pytest.mark.parametrize("in_size", [1, 5])
@pytest.mark.parametrize("out_size", [1, 3])
@pytest.mark.parametrize("hidden_sizes", [(), (1,), (1, 1), (7, 8)])
@pytest.mark.parametrize("normalize_inpu... |
7c1f9001f8bf801d02413d898bfbc61436e588dccc10f96ea020ce8cda2e957c | Python | 2,074 | 73 | r"""
Copy from scglue: https://github.com/gao-lab/GLUE/
"""
import pandas as pd
import numpy as np
import anndata as ad
from anndata import AnnData
import scipy.sparse
from sklearn.preprocessing import normalize
from typing import Optional
import sklearn.utils.extmath
from typing import Optional, Union
Array = Union[... |
ecc86ee88b073d23649e566c9aa17023baa2a6317fe21bc3581558653807ee46 | Python | 2,074 | 46 | import os
import itertools
# Get the root path of the directory
ROOT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))
# Return the absolute path of a relative path
def absolute_path(path, isdir=True):
return os.path.abspath(path) + ("/" if isdir else "")
# Take a JSON config file, with <t... |
3f83f03a0da48da8ad7e818d092955846abf8acafbf09fe113331c453c2e8585 | Python | 2,077 | 75 | ## Nicolas Servant
##
## HiC-Pro
## Copyright (c) 2015 Institut Curie
## Author(s): Nicolas Servant, Eric Viara
## Contact: nicolas.servant@curie.fr
## This software is distributed without any guarantee under the terms of the BSD-3 licence.
## See the LICENCE file for details
import re
... |
6cc81ade4f3dc35102ff50243826167088420662b4d2ebb3a311c8164b93c927 | Python | 2,077 | 52 | import numpy as np
import collections as c
import torch
class Buffer(object):
def __init__(self, o_dim, a_dim, bs, device='cpu'):
self.o_dim = o_dim
self.a_dim = a_dim
self.bs = bs
self.device = device
self.o_buf, self.a_buf, self.r_buf, self.logpb_buf, self.distb_buf, sel... |
4740a7af9836d537c3d3f19a486dadb46a741256339b81a948db0573bd2a2f7d | Python | 2,078 | 68 | """
Suite of functions that help display movie
"""
import matplotlib
import matplotlib.pyplot as plt
import tifffile as tiff
import cv2
import numpy as np
from csbdeep.utils import normalize
def display(filename, display_length, norm_min_percent, norm_max_percent):
"""
Display movie using o... |
6b2bf028550432f9af58c7abb996500106211449d845ec7b355ca73e014bb42b | Python | 2,078 | 52 | from multiprocessing import Pool, Manager
import subprocess
import os
import pandas as pd
import code
# code.interact(local=dict(globals(), **locals()))
def run_bash(bash_cmd):
"""
Run bash command.
Return a list containing standard output, line by line.
"""
popen = subprocess.Popen(bash_cmd, st... |
9fb5302da5e9a70f8a19ff36e0460a2a81fde58d4e7d2fc439311c9b63e6e55c | Python | 2,078 | 67 | # built-in dependencies
from typing import Any, List, Union
# project dependencies
from deepface.commons.onnx_utils import build_session
from deepface.models.facial_recognition.onnx.OnnxFacialRecognition import OnnxFacialRecognition
from deepface.commons.logger import Logger
logger = Logger()
# pylint: disable=line-... |
d1641fef2b055143332fe6ad13eb0c5d6f442f847248e3bd7ef5a1891d4fd854 | Python | 2,078 | 49 | import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def deprecate(*args, take_from: Optional[Union[Dict, Any]] = None, standard_warn=True):
from .. import __version__
deprecated_kwargs = take_from
values = ()
if not isinstance(args[0], tuple):
... |
dda1eba7e811ac273563474cca268af58f8380b7ab59d0e9de5566acbb4ccfcd | Python | 2,079 | 69 | #!/bin/python
# file: Doxytag.py
# brief: Parse doxygen.tag file
# author: Andrea Vedaldi
"""
DOXYTAG parses doxygen.tag files.
"""
import xml.dom.minidom
import sys
import os
import re
__mpname__ = 'Doxytag'
__version__ = '0.1'
__date__ = '2013-07-09'
__description__ = 'Doxygen t... |
5ea5aace5cb0be6c883e51b15203669976180b8d030d16e5f1626bc329213e63 | Python | 2,080 | 71 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""Utilities for the AIHW Composer API."""
from os import getenv, path
from typing import Dict
from configparser import ConfigParser
DEFAULT_URL = "https://api... |
32bf8844fd3cd95e2c1ddd36f26c13cfd71d37de9b63cb82f54df1635950f5ba | Python | 2,081 | 51 | import Utility_working as Utility #custom-made utility file, contains lengthy functions
from constant import *
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.pyplot as plt
import sys
import os
#These should all be pulled from the constant file. Only change this if it's not set in the cons... |
4dd3f332864111b5e8f99c851ff0e20fbae2a3ff4942b273a39391c0f47722e8 | Python | 2,081 | 57 | """Vendored SAMap (Tarashansky et al. 2021, eLife) + sam-algorithm.
Source: https://github.com/atarashansky/SAMap (Tarashansky, Musser, Khariton,
Li & Wang, Stanford University). Upstream is MIT-licensed; the license is
carried verbatim beside this file in ``LICENSE`` and applies to every source
file in this directory... |
e7252ea6f8e1bfb625a443c3ae80d0ee8ebb9f0e9b98494fae152c7f76b22878 | Python | 2,081 | 59 | r"""Lazy-import dependency gates for :mod:`omicverse.mol`.
The structural-biology stack is optional — heavy backends are imported
*inside* the functions that use them, and a missing one raises a clean,
actionable :class:`ImportError` naming the pip extra to install.
"""
from __future__ import annotations
import impo... |
07a2059d0516035db29e72d091fbf5ef2ecc003d2f5135ef3a2b06188477220b | Python | 2,082 | 61 | """Configuration options for pytest
See Also:
* https://docs.pytest.org/en/latest/example/simple.html#control-skipping-of-tests-according-to-command-line-option
"""
import pytest
def pytest_addoption(parser):
"""Define customized pytest flags.
Examples:
>>> pytest tests/test_sklearn.py --runfas... |
bc65a8f458b744b69b053ee19e8e8c6089b3e75dbb6179da3832eabc05c4de5a | Python | 2,082 | 43 | import logging, os, datetime
import pandas as pd
from Embedding.retrospective_validation import single_model_term_similarity, is_in_dataset
from misc.save_files import write_pickle, read_DocTermDict, read_pickle
from Embedding.load_w2v_models import load_current_joined_model
def specific_term_validation(config: dict)... |
022236784db9cd9b8a86a49e0a5b83ce20145fb40f1d34f687727c7bc0b78a7e | Python | 2,084 | 71 | import serial
from time import sleep
import numpy as np
class OpticalPower:
open_flag = False
def __init__(self, port='COM8', flag=True):
self.port = port
if flag:
self.open()
def query_hex(self, hex_ord):
self.op.write(bytes.fromhex(hex_ord))
s... |
7ef7521bfab63ee63e8b1c54d7e31eef8d5d398cb0005593cd9d6bbfb1a53cf4 | Python | 2,084 | 62 | import json
from pathlib import Path
import numpy as np
import pandas as pd
from data_profiling import ProfileReport
from data_profiling.config import Dataset
from data_profiling.utils.cache import cache_file
if __name__ == "__main__":
file_name = cache_file(
"census_train.csv",
"https://archive.... |
95c70c2bbebe93628ec54850cc7685b5f573fe3d9779b3bda48b219bd2e513bd | Python | 2,084 | 71 | # !/usr/bin/python
# -----------------------------------------
# Extract the celltype read count matrices:
# -----------------------------------------
import glob
import h5py
import re
import gzip
import pickle
import numpy as np
import pandas as pd
import time
import gc
import sys
# If these matrices already exist, m... |
bd41e92725211004cada5cd1b196500f07f05d6ba8ef5591ef4f3b80bf6515f3 | Python | 2,084 | 61 | import os
import torch
import inspect
import pickle as pk
import numpy as np
from glob import glob
from src.data.load_data import load_params
def check_path(path, verbose=True):
"""Check if given path (file or dir) already exists, and if so returns a
new path with _<n> appended (n being the number of paths wi... |
354a9506552e1ef4f1d6fe1bc95b68b8997d05ad1fa4ee6c262497af93f14919 | Python | 2,085 | 63 | r"""
NoCD: Non-overlapping Community Detection for single-cell data.
This module implements non-overlapping community detection algorithms specifically
designed for single-cell omics data. It provides neural network-based approaches
for identifying discrete cell populations and communities in high-dimensional
biologic... |
4793ad93fbcc32f34d8fc555ed99b07409ade9cb5918238cfbe5464a371dcc8f | Python | 2,085 | 61 | import unittest
import numpy as np
import torch
from rising.transforms import OneHot, TensorOp, ToDevice, ToDtype, ToTensor
class MyTestCase(unittest.TestCase):
def setUp(self) -> None:
self.device = "cuda:0"
self.batch_dict = {
"data": torch.arange(1, 10).reshape(1, 1, 3, 3).float()... |
0e6868a2717b440d3fe3fbd04310ecf405cb57842e6e5fe48320839f1c0ed770 | Python | 2,086 | 53 | import argparse
import ast
import os
import sys
import torch
from torch2trt import torch2trt, TRTModule
sys.path.insert(1, os.getcwd())
from models_.hrnet import HRNet
def convert_to_trt(args):
"""
TensorRT conversion function for the HRNet models using torch2trt.
Requires the definition of the image re... |
2421d87f8ec43316dc62efd7e9d4bd963d14ec44501f21cfa57fb22ad96355d9 | Python | 2,086 | 92 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
All the hard-coded, SFARI-specific filtering
"""
import argparse
import sys
import pysam
import svtk.utils as svu
# Samples with allosomal aneuploidies
ANEUPLOIDIES = set([
'13706.p1',
'14100.p1',
'11554.s1',
'12412.p1',
'12860.p1'
])
# Dosage... |
3b7bdcf5b2fe426b606882cc3ddfbd1b9f3575979a21ce7617938f60c79cc47c | Python | 2,086 | 72 | # __pattern_start__
import ray
import time
from numpy import random
def partition(collection):
# Use the last element as the pivot
pivot = collection.pop()
greater, lesser = [], []
for element in collection:
if element > pivot:
greater.append(element)
else:
less... |
59d49101e14d70c4039c431e951ad75d37f979111a85b258314e3b76e841d026 | Python | 2,086 | 56 | import torch
from ..distances import LpDistance
from ..utils import common_functions as c_f
from ..utils import loss_and_miner_utils as lmu
from ..miners.base_miner import BaseTupleMiner
# adapted from
# https://github.com/chaoyuaw/incubator-mxnet/blob/master/example/gluon/embedding_learning/model.py
class DistanceW... |
9b2725b24fcffc769d8a2c83eec0399624d1218cd9c295616e8aba055f232d3c | Python | 2,087 | 62 | '''Register composite max to MP2RAGE'''
import nibabel as nb
import subprocess
import os
import glob
CURRDIR = os.getcwd()
ROOT = '/Users/sebastiandresbach/data/neurovascularCouplingVASO/Nifti/derivatives'
TRANSFORM = f'{CURRDIR}/code/temp-faruk/sub-06_uni-to-megre_registered1_0GenericAffine.mat'
MOVINGFILE = f'{RO... |
169dbb5e17301db4fa23e7c29f8fac24d5c146c5ead70cee7f4a767b74224541 | Python | 2,089 | 91 | import torch
import numpy as np
from torch.nn.functional import smooth_l1_loss
'''helpers'''
eps = np.finfo(np.float32).eps.item()
def compute_returns(rewards, gamma=0, normalize=False):
"""compute return in the standard policy gradient setting.
Parameters
----------
rewards : list, 1d array
... |
79c99109fa6af77be838b73a7ecca1275e9ed667413be56395d9028185f9f799 | Python | 2,090 | 62 | # -*- coding: utf-8 -*-
from model.models import PepCA
from model.models import PeptideComplexes, PepCA_dataset
from time import time
import numpy as np
import torch
import argparse
import torch.nn.functional as F
import datetime
import os
import random
import pickle
from trainer import *
from sklearn.metrics import r... |
82966833155baa98a64581900264027847ed3931a5dbdb8ee34000315d660611 | Python | 2,090 | 75 | from dataclasses import dataclass, field
from typing import Any, Dict, Optional
import numpy as np
from .node import NIRNode
@dataclass(eq=False)
class Affine(NIRNode):
r"""Affine transform that linearly maps and translates the input signal.
This is equivalent to the
`Affine transformation <https://en.... |
1d4d47d43d3c55e0f2943a38790a185a11f09b8d515eb88737cbaf1f0a607618 | Python | 2,092 | 65 | """
Cropping functional images to decrease number of voxels (and therefore
processing demands)
"""
from nipype.interfaces.fsl import ExtractROI
import glob
import os
# Set data path
ROOT = '/Users/sebastiandresbach/data/neurovascularCouplingVASO/Nifti'
# Set subjects to work on
subs = ['sub-06']
# Loop over parti... |
1a15ca14e470da6f4fad226297fd170c4c74ac37344e1d9f45f9b56f807525ab | Python | 2,093 | 49 |
import numpy
from scipy import optimize
def gaussian(amplitude, center_x, center_y, width_x, width_y):
"""Returns a gaussian function with the given parameters"""
width_x = float(width_x) + 1e-3 # numerical stability
width_y = float(width_y) + 1e-3 # numerical stability
return lambda x,y: amplitude *... |
1fe729861225e144defcab66db82e2710477cabb740225e980561fd4c7c06dbf | Python | 2,093 | 79 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Created on Thu Oct 20 15:18:21 2016
@author: agiovann
"""
from builtins import map
import caiman as cm
#%%
def pre_preprocess_movie_labeling(dview, file_names, median_filter_size=(2, 1, 1),
resize_factors=[.2, .1666666666], diameter... |
6e66c55261b605bc66881d127feeb1af19849773fafd650c5c57b51e7755d9b5 | Python | 2,093 | 46 | from model import (IntraEncoder, InterEncoder, ProteinInteractionNet, Trainer, Tester)
from uncertaintyAwareDeepLearn import VanillaRFFLayer
from utils import (
load_configuration,
initialize_logging,
set_random_seed,
get_computation_device,
initialize_scheduler,
train_and_validate_model
)
def... |
da3c588beff8b8343e138cfa9c6b12154cf4894e821f48a373605a4d03429da2 | Python | 2,093 | 77 | import basetest_dqn_like as base
import torch.nn as nn
from basetest_training import _TestBatchTrainingMixin
import pfrl
from pfrl.agents import CategoricalDoubleDQN
def make_distrib_ff_q_func(env):
n_atoms = 51
v_max = 10
v_min = -10
return pfrl.q_functions.DistributionalFCStateQFunctionWithDiscrete... |
50397d84b71f884c20a42e1f740d63473ea565cef9cd55361f6ebdb60b8cd653 | Python | 2,094 | 59 | import os
import argparse
import numpy as np
"""Compute the test accuracy obtained by K-fold cross validation"""
def main(path):
# Count the number of folds
kfold_dir_runs = []
for item in os.listdir(path):
full_path = os.path.join(path, item)
if os.path.isdir(full_path): kfold_dir_runs.a... |
0053fd2e64a7d99eba7bbcc25cb6466b07d8a7b357b44f2df9e4f5701580684e | Python | 2,095 | 51 | #!/usr/bin/env python
import argparse
def parse_args():
parser = argparse.ArgumentParser("Produces BED file of bam where read depth is at or above a threshold")
parser.add_argument('--input_fasta', '-i', dest='input_fasta', required=True, type=str,
help='Input fasta file')
parser.... |
233fcad4aec4bddbe40ad4a43285e6442f0f1a8bbe6651aa8612a8c1fe3a3542 | Python | 2,095 | 67 | GENCODE = 'hg38_gencode27.bed'
LONGREAD_ONLY = 'gencode.longread_only_1k.txt'
LONGREAD_ONLY_FULL = 'hg38_gencode27.longread_only_1k.bed'
def generate_longread_only():
longread_only = list()
with open(LONGREAD_ONLY) as input:
for line in input:
longread_only.append(line.strip())
gencod... |
390764319e43f5c1ebaa19372231c8884a0becd137194b1c2831e05088546339 | Python | 2,095 | 65 | import numpy as np
import sys, pathlib
sys.path.append(str(pathlib.Path(__file__).resolve().parents[1]))
from params_library.cell_library import get_neuron_params
from params_library.syn_and_connec_library import get_connectivity_and_synapses_matrix
from params_library.params_reformat import reformat_syn_parameters_egl... |
441a927ccc7899a558237a913b5731e9cc4c29f38bc1edeb567c83b35543ae30 | Python | 2,095 | 49 |
from lisa.core.data_interface import DataInterface
import argparse
import os
import numpy as np
import pandas as pd
def main(species, window_size, cistrome_metadata, motif_metadata, index_files):
cistrome_metadata = pd.read_csv(cistrome_metadata, sep = '\t').set_index('DCid')
cistrome_metadata.index = cistro... |
6d21fd8d978fab7f3ba2434f0aef8927e90f864a8340d45c20d8c55018be5796 | Python | 2,095 | 75 | import sys
from typing import List
from unittest import mock
import pytest
from ci.ray_ci.container import _DOCKER_ENV
from ci.ray_ci.windows_container import WindowsContainer
def test_install_ray() -> None:
install_ray_cmds = []
def _mock_subprocess(inputs: List[str], stdout, stderr) -> None:
inst... |
39dcdfcff3d801132511966b37e0daa756de02d4e5e1ff1aad3f6195bf75d338 | Python | 2,098 | 54 | from __future__ import print_function, unicode_literals, absolute_import, division
import numpy as np
from scipy.ndimage.interpolation import zoom
from .care_standard import CARE
from ..data import PercentileNormalizer, PadAndCropResizer
from ..utils import _raise, axes_dict
class UpsamplingCARE(CARE):
"""CARE ... |
c8e53bb362a066be37b358508d54816a5544ccf25c03945e113529e3175d12a5 | Python | 2,098 | 68 |
import matplotlib.pyplot as plt
import numpy as np
import scipy.io.wavfile
import torch
import utils
font = {"size": 10, "family": "Arial"}
plt.rc("font", **font)
def rms_normalise_audio(x):
x = x - torch.mean(x)
rms = torch.sqrt(torch.mean(torch.pow(x, 2)))
return x / (10 * rms)
def plot_signal_and_... |
f7aedb994c2e85b8d9eddff8b2c04d9a8f9d4ff4fb5b6803a1ab953af437f971 | Python | 2,099 | 62 | import os
import glob
import argparse
import numpy as np
from utils import rtstruct_utils, metadata_utils
from config import config
parser = argparse.ArgumentParser()
parser.add_argument('--dir', type=str,
default="/gpfs/data/oermannlab/private_data/temporalMRI/gammaplan/",
he... |
d89dde0a9ab70f947b7445c13d54b0fd902fb65c16efd3ffda3ca2260fbd2aba | Python | 2,101 | 58 | import pandas as pd
from data_profiling import ProfileReport
from data_profiling.utils.dataframe import hash_dataframe
def test_custom_sample():
df = pd.DataFrame({"test": [1, 2, 3, 4, 5]})
# In case that a sample of the real data (cars) would disclose sensitive information, we can replace it with
... |
ab72cbe501ec1e008242a56573db251241b86535f45b2d3f8487f782e8e7df67 | Python | 2,102 | 71 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import os
import ase.io
import matplotlib
import numpy as np
from matplotlib import pyplot as plt
def v0_check(full_traj, initial):
"... |
1c80160a182796d7683218f439f7dc0543d67a7d6b66b97d1a4557e58eefc808 | Python | 2,105 | 64 | import rdkit
from rdkit import Chem
from optparse import OptionParser
from rdkit import RDLogger
lg = RDLogger.logger()
lg.setLevel(4)
BOND_TYPE = [0, Chem.rdchem.BondType.SINGLE, Chem.rdchem.BondType.DOUBLE, Chem.rdchem.BondType.TRIPLE, Chem.rdchem.BondType.AROMATIC]
def copy_edit_mol(mol):
new_mol = Chem.RWMo... |
6f503760658b69ae110f41d23175802fc11a2604fb76430b60efcee1890bf44f | Python | 2,105 | 65 | # -*- coding: utf-8 -*-
import gseapy
import csv
import numpy as np
import pandas as pd
import gseapy as gp
import matplotlib.pyplot as plt
import seaborn as sns
from gseapy.plot import barplot, dotplot
names = gseapy.get_library_name()
print(names)
# After running Fatecode and detecting the import... |
55bacab0a23949a6d6055be104cc8f90aab90ae04c842798577d9d06126b07f7 | Python | 2,106 | 62 | # -*- coding: utf-8 -*-
"""
This is implementation of model of push-pull connectvity:
Jens Kremkow: Correlating Excitation and Inhibition in Visual Cortical Circuits: Functional Consequences and Biological Feasibility. PhD Thesis, 2009.
"""
from pyNN import nest
import sys
sys.path.insert(0,"/home/jan/cluster/mozaik/m... |
9366d559642cbc0d821dfad6f316185cc39afa7fbf888dea9af6824820e6a80e | Python | 2,106 | 51 | #!/usr/bin/env python
# alternative promoter and alternative terminator
import pandas as pd
from prepare_and_parse import class_by_transcript_pd
def identify_alternative_promoter(df, gencode, All_FilteredParsed):
'''
Transcripts with first exons that match first exons of shorter reference downstream are not a... |
dbb656b749175b5f7cfb3d0d751004a22fc7ce15961e3199a6cf4f3a57a492e1 | Python | 2,106 | 55 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
import math
import torch
class SO3_Linear(torch.nn.Module):
def __init__(self, in_features: int,... |
7c6c5e22bdeb3b92af924b1bc831a50890f1273f96aabbc6af06b8cad02a3522 | Python | 2,107 | 47 | # import from plugins/custom_unitmatch_probability.py
"""Show how to add a custom unitmatch probability measure."""
from operator import itemgetter
import numpy as np
from phy import IPlugin
from phy.apps.template import from_sparse
def load_probability_templates(controller):
try:
out = controller.model.... |
c99990ccb0d0aeaac684a656da013f5da7fb0d8389f25939ab17a331a6b632a6 | Python | 2,107 | 61 | from torch.nn import Module, BatchNorm1d, LazyBatchNorm1d, ReLU, LeakyReLU, Conv1d, LazyConv1d, ModuleList, Softmax, Sigmoid, Flatten, Dropout2d, Linear
import numpy as np
CL_max = 10000
CARDINALITY_ITEM = 16
class ResidualUnit(Module):
def __init__(self, l, w, ar, bot_mul=1):
super().__init__()
... |
abca4f288938cd9bd7b855e57d8f95106e0acc36d891900db48eab311b741276 | Python | 2,108 | 49 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
7b43061972b55e193b44f25332922bfacd04d36f97378ce17a36d0fb6e769c23 | Python | 2,110 | 65 | # built-in dependencies
from typing import Any, List, Union, cast
# 3rd party dependencies
from numpy.typing import NDArray
# project dependencies
from deepface.modules import verification
from deepface.commons.onnx_utils import build_session
from deepface.models.facial_recognition.onnx.OnnxFacialRecognition import O... |
9517d32b560f3c126758a09846e7e254e932d6dbc366c1c3caf7286a670b85bf | Python | 2,110 | 47 | import numpy as np
def model_predict_latents(model, dataset, dataset_test):
"""
Generate latent representations from a given model using training and testing datasets.
This function passes batches of data through the model to obtain latent representations. It concatenates
these representations for al... |
d228caca3c052e71ef08eb17b1e3efb3016acac9f8e851ead9e2ed5de18f5435 | Python | 2,110 | 57 | import pytest
from siapy.optimizers.parameters import (
CategoricalParameter,
FloatParameter,
IntParameter,
TrialParameters,
)
def test_init():
float_params = [FloatParameter(name="fp1", low=0.0, high=1.0)]
int_params = [IntParameter(name="ip1", low=0, high=10)]
cat_params = [CategoricalP... |
dd7fb43c912208c9d3c7fd22270476d72b4e34733ee886ad5b7f79f3cc46ffc5 | Python | 2,110 | 64 | """Code in this file is heavily based on the code from the following repository: https://github.com/CompVis/invariances"""
import numpy as np
import torch
class AbstractDistribution:
def sample(self):
raise NotImplementedError()
def mode(self):
raise NotImplementedError()
class DiracDistri... |
7a79f4e60d0ebfd2340b995e0953d8ebcea654c4d384ee38d756420ae92204dc | Python | 2,111 | 82 | # flake8: noqa
# fmt: off
# __example_objective_start__
def objective(x, a, b):
return a * (x ** 0.5) + b
# __example_objective_end__
# fmt: on
# __function_api_report_intermediate_metrics_start__
from ray import tune
def trainable(config: dict):
intermediate_score = 0
for x in range(20):
interm... |
ad45a0888654929e3d126a4b19a9b839f7c76a1e80a99e26494f5e3550679cc8 | Python | 2,112 | 48 | import torch
import torch.nn as nn
from lop.utils.ltu import LTU
class FixLTUNet(nn.Module):
def __init__(self, num_inputs=20, num_features=80, beta=0.75):
"""
A feed forward neural network with just one hidden layer of LTU activation
This network is used as the date-generating (target) ne... |
ae879c41f05a9f365e471123092f62d4e0fd813ebe01338761f36c4d444bcb61 | Python | 2,113 | 58 | import numpy as np
import pandas as pd
import tensorflow as tf
from tensorflow import keras
from keras.models import Sequential
from keras.layers import Conv1D, MaxPooling1D, GRU, Dense, Flatten, Reshape, Dropout
class ProposedModelFrameWork:
def __init__(self, classes,input_shape):
self.classes=class... |
a3740cfba50602dfa0102b9a20406987e3d9c30af39dac05f4e8ce030879764f | Python | 2,115 | 56 | #!modify filter label of SR only PASS SVs:
import argparse
import pysam
def revise_filter_Large_SR_only(vcf, fout, size_cutoff=500, sample_proportion_cutoff=0.1):
records = []
for record in vcf:
if 'PASS' in record.filter.keys():
if record.info['SVLEN'] > size_cutoff:
SR_o... |
2f05e949ee4de4c54c3229d36cd118eb5981f540378034070a5b8a117249e5ef | Python | 2,116 | 51 | # camera-ready
import torch
import torch.nn as nn
import torch.nn.functional as F
import os
from .resnet import ResNet18_OS16, ResNet34_OS16, ResNet50_OS16, ResNet101_OS16, ResNet152_OS16, ResNet18_OS8, ResNet34_OS8
#from aspp import ASPP, ASPP_Bottleneck
from torchvision.models.segmentation.deeplabv3 import DeepLab... |
a641646451e2b9a45e4f7eecdd8c4d4c3fcd27d98710aa4009aa4455804181e3 | Python | 2,116 | 64 | """
Recode lumbar rootlets values to be consecutive starting from 0 (zero represents background).
The consecutive labels order is required by the nnUNet framework.
For example, the script can recode:
[ 0. 20. 21. 22. 23. 24. 25. 26. 27.]
Into:
[0. 1. 2. 3. 4. 5. 6. 7. 8.]
Example usage:
python recode_nii.... |
c521a2defd3cbd5c319340e228274313815ccfbdd80c0154b1ee87390f74fbaf | Python | 2,116 | 52 | from lisa.core.utils import LoadingBar
from lisa.core.assays import LISA_RP_Assay, get_delta_RP, get_deltaRP_activation
from multiprocessing import Pool
import numpy as np
from scipy import stats, sparse
import os
class ISD_Assay(LISA_RP_Assay):
def predict(self, gene_mask, label_vector,*,region_scores,**kwargs):... |
0617f7141855f32b599028b7ab775fc19329b92c5ef1e0d7b3ecbe04b0034960 | Python | 2,117 | 47 | #!/usr/bin/env python
# Matching Exons
from prepare_and_parse import class_by_transcript
def identify_all_matching_exons(gencode, df, All_FilteredParsed):
'''
Aim:
1/ Identify transcripts with complete matching coordinates to known exons, must contain all exons
2/ Identify transcripts with misma... |
17e44aba3ca937d5305092d746812d15331bbde1a1e7cae09a77d79fd76d384b | Python | 2,117 | 61 |
"""Split each echo to prepare for registration."""
import os
import subprocess
import numpy as np
import nibabel as nb
import glob
# =============================================================================
DATADIR = '/Users/sebastiandresbach/data/neurovascularCouplingVASO/Nifti'
# Set subs to work on
SUBS = ['s... |
1d57d0cfb265074944fa9985897016d054a78b06b76642dd49030fbd1fe411c4 | Python | 2,118 | 73 | # Copyright (c) 2017-present, Facebook, 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 agreed... |
7afe39386eb7c9acd84ee78d8e72c05e9797a49f3ad1f291715a0d4c9f14e136 | Python | 2,118 | 82 | r"""
This module contains several low level plotting function used mainly in simple_plot module.
"""
import pylab
import mozaik
from matplotlib.ticker import FuncFormatter
logger = mozaik.getMozaikLogger()
def disable_top_right_axis(ax):
for loc, spine in ax.spines.items():
if loc in ['right', 'top']:
... |
632b03cb91f5eb8c3fba48878db115ab1824bc9884f04435670a2e9f16405eb4 | Python | 2,120 | 108 | import sys
import numpy as np
try:
import cupy as cp
except ImportError:
pass
# --------------------------------------------------------
# Defalut is to use numpy, not cupy
# --------------------------------------------------------
gpu_mode = False
# --------------------------------------------------------
... |
5b91450a05424ea8c34da41144a236bd6e431a0ae2efbe1262d5b44685b717bd | Python | 2,121 | 105 | category_dictionaries = {
'view': {
'PLAX': 0,
'Ascending_aorta': 1,
'RV_inflow': 2,
'RV_focused': 3,
'Pulmonary_artery': 4,
'PSAX_AV': 5,
'PSAX_MV': 6,
'PSAX_papillary': 7,
'PSAX_apex': 8,
'A4C': 9,
'A5C': 10,
'A3C': 11... |
f79bf363e9c982c011bad671c5ef2fbda2e1d006e5fef2b582a8f2339409b2f9 | Python | 2,121 | 82 | import os.path as op
import os
import subprocess
def overwrite_check(file):
"""Checks whether a file exists. If so, aborts the function.
Parameters
==========
file: str
name of file to look for
Outputs
=======
None
"""
if op.exists(file):
raise Exception(
... |
08c5ec296b6fb77b6b5be5550fb20c4ff58442907884223120756195dfeaf738 | Python | 2,122 | 60 | import copy
import warnings
from typing import List
from mmengine.model import BaseDataPreprocessor
from mmengine.structures import BaseDataElement
from torch import Tensor
from lqit.registry import MODELS
from lqit.utils import ConfigType, OptConfigType
SampleList = List[BaseDataElement]
@MODELS.register_module()... |
ee18e4f33d99a842b501dc719caf97b4bc44bd1c44e397aa951f14767697b8f7 | Python | 2,122 | 57 | import logging
from datetime import datetime
from agent.data.entities.config import ROOT_LOGGER_ID
from agent.data.augmentation.data_augmentation_mgmt import process_train_items, TRANSFORMER_TYPE
# from agent.data.augmentation.data_augmentation_mgmt import process_single_item, do_back_translation, get_back_translatio... |
1a91414f58356c3f539b78287b9a2973387143df1ef0ea6b5ef90a0d8465d394 | Python | 2,123 | 114 | """
Test for issue 282:
https://github.com/Data-Centric-AI-Community/data-profiling/issues/282
"""
import pandas as pd
from data_profiling import ProfileReport
from data_profiling.model import BaseDescription
def test_issue282():
index = [
"BJ110",
"BJ126",
"BJ163",
"BJ054",
... |
273fd56b7422d333372c7e2ed1f51cd3e899bd318b2d00444432eb7ff8f99128 | Python | 2,123 | 60 | from typing import List, Optional, Protocol, runtime_checkable
from ray.data._internal.execution.interfaces import ExecutionResources
@runtime_checkable
class ClusterAutoscalingMetrics(Protocol):
"""Protocol that defines the metrics required for cluster autoscaling.
Attributes:
average_num_inputs_pe... |
c9ba4c98dd138a33af5acee93fce09958e80ad48e2f14ff4a9477d29b4036cb3 | Python | 2,123 | 54 | import numpy as np
import pickle
import sys
from collections import namedtuple
import argparse
GridSearchParams = namedtuple('GridSearchParams', ['lambda_start', 'lambda_end', 'prior_weight'])
GridSearchReconstructions = namedtuple('GridSearchReconstructions',
['ground_truth', ... |
e804144bd639fd91c1e6869e186ceeb317863d599a0d45405ca6d7416b77ea9a | Python | 2,123 | 57 | from typing import Any, Callable, Dict, Optional
import pyarrow
from ray.data._internal.arrow_block import _is_user_visible_column
from ray.data.block import BlockAccessor
from ray.data.datasource.file_based_datasource import _resolve_kwargs
from ray.data.datasource.file_datasink import BlockBasedFileDatasink
class... |
2ac15214992dd1178c0b29a2caab74fc0a1c04694788a7b041f04af54e951cde | Python | 2,125 | 68 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""Helper for retrieving Metrics of an Experiment."""
from datetime import datetime
import json
from typing import Dict
class InferenceLocalMetric:
"""Met... |
54ddb0bcfac871e5a749311a4782d30c5fd5cd346b307b6804190d638f64f61d | Python | 2,125 | 51 | from neuromaps.parcellate import Parcellater
from neuromaps import datasets
import numpy as np
from nilearn.datasets import fetch_atlas_aal
from neuromaps import nulls
import os
from scipy.io import savemat
PERMS=20
#aal = fetch_atlas_aal(version='SPM12')
aal_path = "/home/ivan.mindlin/Repos/neuromaps/AAL_90.nii.gz"
ma... |
a0ada91b4d4437fa3dfd10dd1fc56fc767b6fecc92034a2f57c3071571af6c42 | Python | 2,125 | 102 | # flake8: noqa
# fmt: off
# __crosslang_init_start__
import ray
ray.init(job_config=ray.job_config.JobConfig(code_search_path=["/path/to/code"]))
# __crosslang_init_end__
# fmt: on
# fmt: off
# __crosslang_multidir_start__
import ray
ray.init(job_config=ray.job_config.JobConfig(code_search_path="/path/to/jars:/path... |
a86ba626fa1bdee6ef0e7377aa34fda8972fb6e7496d5b7ae5a06b1ac1706b68 | Python | 2,126 | 77 | from typing import Tuple
import numpy as np
import pandas as pd
from data_profiling.config import Settings
from data_profiling.model.summary_algorithms import (
chi_square,
describe_date_1d,
histogram_compute,
series_handle_nulls,
series_hashable,
)
from data_profiling.model.typeset_relations impo... |
13bc4e06ddae654c3a1e750547e07a29e067912945fccad4ad0eb5de076c027c | Python | 2,127 | 69 | import subprocess
from typing import List, Optional
from ci.ray_ci.bisect.validator import Validator
from ci.ray_ci.utils import logger
from ray_release.test import Test
class Bisector:
def __init__(
self,
test: Test,
passing_revision: str,
failing_revision: str,
validato... |
99a9986db17509c98614b970084b86cfe1ed4d4397106820096bebe59f39e43f | Python | 2,129 | 48 | """LLM-assisted scoping: split objectives, expand queries, add constraints.
Uses an OpenAI-compatible chat-completions endpoint if available; otherwise
falls back to a simple heuristic splitter.
"""
from __future__ import annotations
from typing import Dict, List
import os
def suggest_brief(request: str) -> Dict[s... |
3d2fa26746448691cd31a6288aa777bc8592cc92853f3cf9d16e20b16a08282c | Python | 2,130 | 50 | #!/usr/bin/env python3
# Copyright (c) 2020-2022, NVIDIA CORPORATION. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without modification, are permitted
# provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright ... |
3ffe56c161d985f731be0bdc888cd477cae2a38c4ef152c4e834ad245acb7777 | Python | 2,131 | 67 | import torch
from torch.nn.utils.rnn import pad_sequence
def reverse_pad_list(ys_pad, ys_lens,
pad_value: float = -1.0):
r_ys_pad = pad_sequence([(torch.flip(y.int()[:i], [0]))
for y, i in zip(ys_pad, ys_lens)], True,
pad_value)
ret... |
e582bc89607447dbb0e63f43b51708fc37bba825dba30a078cff88a6fb9cf071 | Python | 2,131 | 64 | from torch import nn, zeros
from config import TARGETS, FORECAST_HORIZON
class GRU(nn.Module):
def __init__(
self,
n_input_ts: int = len(TARGETS),
hidden_size: int = 100,
num_layers: int = 1,
dropout: float = 0.0,
n_output_ts: int = len(TARGE... |
1aca229d427f3dd7c4f63c5ec49e25db51a51d07f8819e7c82090671783d5952 | Python | 2,132 | 72 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
# pylint: disable=too-many-locals, too-many-arguments
"""Low level implementation of torch-based tile."""
from typing import TYPE_CHECKING
from torch import T... |
fd879eb5d60d43331462910c3f8941a13ce1bb1297703bd7a27da557badb17de | Python | 2,132 | 73 | import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import utils
font = {"size": 10, "family": "Arial"}
plt.rc("font", **font)
# Load in full nested cross-validation results
full_df = pd.read_csv("anon_results.csv", index_col=[0, 1, 2])
# Remove post-operation visits from test results
full_df = f... |
1c2cfdc5d8a6ef1da9d15d551ab75df7687bbc1429cee0537060813e8341f75a | Python | 2,133 | 60 | # Ultralytics YOLO 🚀, GPL-3.0 license
from ultralytics.yolo.utils import LOGGER, TESTS_RUNNING
from ultralytics.yolo.utils.torch_utils import get_flops, get_num_params
try:
import clearml
from clearml import Task
assert clearml.__version__ # verify package is not directory
assert not TESTS_RUNNING ... |
90f8a692ba0b0df45c0d492fe43ce6403f38906a318282cc92a44c133561c9c0 | Python | 2,133 | 89 | #!/usr/bin/env python
"""
Collect BAF file metrics. Writes stats to stdout.
Metrics:
baf_qN_<sample> : Nth percentile BAF
baf_count_<sample> : total BAF record count
If the provided sample list has more than one id, <sample> will be "_merged".
"""
import gzip
import argparse
import sys
import numpy as np
im... |
a1d2cebd768b9409376809e5362862cddab95b194aad8977b7e8237a6dc626bd | Python | 2,133 | 98 | ################################################################
# filename: pglCalibration.py
# purpose: Handles calibration of display
# by: JLG
# date: September 18, 2025
################################################################
#############
# Import modules
#############
import numpy as ... |
00f100ed7c421db7f7af2a1984e4914a551b1e4a25abbed7cdb9909f74f22146 | Python | 2,134 | 48 | """Spatial entry point for the unified communication API (``ov.space.run_ccc``)."""
from __future__ import annotations
from collections.abc import Mapping, Sequence
import anndata
from .._registry import register_function
@register_function(
aliases=["space.run_ccc", "空间细胞通讯", "spatial cell communication", "sp... |
09653c834c5657f10370aba4f84a6be777c1c2ea8d9b97087c2e126d954fa7c2 | Python | 2,134 | 70 | import argparse
import sys, os
sys.path.insert(0, os.getcwd())
import ecg_plot
import matplotlib.pyplot as plt
from src.evaluations.traces import plot_trace
from src.dataset.ages import get_single_trace
from warnings import warn
import json
import socket
import numpy as np
import h5py
from scipy import signal as sgn
d... |
e0301669feffc269bea69d3a99813f7f1c1950691bf830bb3e74484789a73eee | Python | 2,134 | 62 | import torch
from ..reducers import AvgNonZeroReducer
from ..utils import loss_and_miner_utils as lmu
from ..losses.base_metric_loss_function import BaseMetricLossFunction
class TripletMarginLoss(BaseMetricLossFunction):
"""
Args:
margin: The desired difference between the anchor-positive distance an... |
62b40064d97780a6d05cfaecdfba9e44487fc44e8f77160b2cbe906100712ff5 | Python | 2,135 | 62 | # 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... |
bd46672ee7918e700bf51bd5792c46512f04dec9d796f26bf15b51eb08369add | Python | 2,135 | 62 | from typing import Any
import numpy as np
from numpy.typing import NDArray
from PIL.Image import Image
from siapy.core.exceptions import InvalidInputError, InvalidTypeError
from siapy.core.types import ImageSizeType, ImageType
from siapy.entities import SpectralImage
__all__ = [
"validate_image_to_numpy_3channel... |
0616650c27d47c4611ec8c18cd091744362bda9d0fbe887521540ccc3809e70b | Python | 2,136 | 75 | """
Structured error hierarchy for OmicVerse Agent (P0-3).
Replaces bare RuntimeError / ValueError with typed exceptions that carry
context (provider, retryable, status_code) and separate control-flow
signals (WorkflowNeedsFallback) from real bugs.
"""
from __future__ import annotations
class OVAgentError(Exception... |
dd6ec0db04c4f83599a3d21c50f0a12b442b2f717b544c842a829d4d471e287d | Python | 2,137 | 65 | import numpy as np
import os
import json
import argparse
from typing import cast
def get_cluster_score_bin_path(
path_checkm_all: str, path_bins: str, bins: set[str]
) -> tuple[dict[str, tuple[float, float]], dict[str, str]]:
"""Given CheckM has been run for all samples, create 2 dictionaries:
- {bin:pat... |
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