sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
e21351623039af2268073478345ee2e00386b9d04b18916c25f3cff21f6abdfd | Python | 2,574 | 71 | from goatools.base import download_go_basic_obo
obo_fname = download_go_basic_obo()
from goatools.base import download_ncbi_associations
fin_gene2go = download_ncbi_associations()
from goatools.obo_parser import GODag
obodag = GODag("go-basic.obo")
from goatools.anno.genetogo_reader import Gene2GoReader
# Read NCB... |
e8c470f5c3c3960c71584938d6c884140ba00745901bf857c8daeeb322edd10e | Python | 2,574 | 78 | ## ------------------------------------------------------------
## IMPORTS
## ------------------------------------------------------------
## ----- OS ----- ##
import os
import gc
import io
## ----- MATH / STATS ----- ##
import cv2
import heapq
import random
import natsort
import scipy.io
import numpy as np
## -----... |
4a4e0ba7c35ea78f5303db67130b67df5139b816ff3da60754252f15acabf4ee | Python | 2,575 | 104 | # Copyright 2014-2015 Numenta Inc.
#
# Copyright may exist in Contributors' modifications
# and/or contributions to the work.
#
# Use of this source code is governed by the MIT
# license that can be found in the LICENSE file or at
# https://opensource.org/licenses/MIT.
import os
import pkg_resources
import warnings
fr... |
6a69c128fecb566112c5f0462a6e1457b71b1891193173d9a6cd01ca956cd14e | Python | 2,575 | 70 | import numpy as np
import random
import torch
import torch.nn as nn
import torch.optim as optim
import datetime
from src.model import Net
def set_seed(seed):
random.seed(seed)
np.random.seed(seed)
torch.random.manual_seed(seed)
torch.manual_seed(seed)
if torch.cuda.is_available():
torch.cuda.... |
90170b73aae2b3c7d347e2afc6af181e66dd79e48991904c306a7267e87b37d0 | Python | 2,575 | 78 | #!/usr/bin/env python
from __future__ import print_function
import logging
from itertools import groupby
import argparse
# Create a logger
logging.basicConfig(format="%(name)s - %(asctime)s %(levelname)s: %(message)s")
logger = logging.getLogger(__file__)
logger.setLevel(logging.INFO)
def is_header(line):
return... |
e7fb73d5c8a671d38e39f9dcf8a097886facc3390597bfcdb8501d97af9dba6c | Python | 2,575 | 88 | # Training module
# Imports
import json
from pathlib import Path
import joblib
from modules.train_steps.train_model import train_model
def run_all(
ml_algorithm: str,
features_path: str,
property_path: str,
output_folder: str,
hp_path: str | None,
scale_data: bool,
):
"""Run every step ... |
2e1022bdb306ab8dc8150904678bb1fa215e075b3baeb18da10c9a0971c3d76b | Python | 2,576 | 70 | import os
import warnings
import numpy as np
import tifffile as tiff
import skimage.io as skio
# Registry for supported formats
FORMAT_REGISTRY = {}
def register_writer(*formats):
"""Decorator to register a new format writer."""
def decorator(func):
for fmt in formats:
FORMAT_REGISTRY[fmt... |
836946128c1293316cb330fd0e1fafca2d92d7382b48c32e6f7eee0b7b3537fe | Python | 2,576 | 80 | import unittest
import logging
import numpy as np
from heig.fpca import FPCA
log = logging.getLogger()
log.setLevel(logging.INFO)
def get_batch_size(n_top, max_n_pc, n_sub):
"""
Adaptively determine batch size
Parameters:
------------
max_n_pc: the maximum possible number of components
n_su... |
af9a2bb78f48e661945e39716afe54fd3f6df115b2a31e1fed4dc226b4e318f2 | Python | 2,576 | 72 | import json
from argclz import AbstractParser
from neuralib.util.verbose import fprint
from rscvp.util.cli import SQLDatabaseOptions, StimpyOptions
from rscvp.util.database import FieldOfViewDB
__all__ = ['InsertFOVDBOptions']
class InsertFOVDBOptions(AbstractParser, StimpyOptions, SQLDatabaseOptions):
DESCRIPT... |
85453d26f112edce27fc42fae5ec8ca9bc6475f74ad382fb94cda51d117bc6b0 | Python | 2,577 | 54 | import argparse
import torch
from tqdm import tqdm
from model import ProTact
from utils.deepinteract_utils import calculate_top_k_prec, calculate_top_k_recall
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Predict the Contact map.")
parser.add_argument("--dataset", type=str, defaul... |
8fbc5573daeecdd3779a495286dbfd7da59da3ad45b5d032e2420c1de1f816e4 | Python | 2,577 | 79 | import os
os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")
import pytest
pytest.importorskip("PySide6")
from PySide6.QtWidgets import QApplication
output_dir_dialog = pytest.importorskip("musclex.ui.widgets.output_dir_dialog")
from musclex.utils.association_store import AssociationStore
@pytest.fixture(scop... |
19394f042f956c33e4cfbc428b6cfb964686f767c213b37a5b38f547d377a386 | Python | 2,578 | 77 | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from UBSIM.blind_SIM_functions import reshape_psf, convolve_with_psf, forward_model, calc_residual, calc_obj_grad, calc_ill_grad
from UBSIM.models import UNet
def IterationBlock(network, obj, ill, M, psf, num_frames, I0):
"""
... |
893bbde74f88655c6a7929e0f937c1001a99417d5c3590f43333419f0a57d067 | Python | 2,578 | 100 | import pandas as pd
import time
import sys
import os
def main(argv):
if argv[1] == '--datasets':
try:
name = argv[2]
return name
except:
return "Wrong command!"
else:
return "Wrong command!"
def is_same(df1, df2, val):
df1_val = df1[val]
df2... |
ee72b065524425fab5e1c89cadd780163be4b375516c1bb678431ee9021ba7b0 | Python | 2,578 | 87 | # The ImpedanceFitter is a package to fit impedance spectra to
# equivalent-circuit models using open-source software.
#
# Copyright (C) 2018, 2019 Leonard Thiele, leonard.thiele[AT]uni-rostock.de
# Copyright (C) 2018, 2019, 2020 Julius Zimmermann,
# julius.zimmermann[AT]un... |
49e695dca7c983b0ed70b87ed6fdf92bce72b1cd2645e2d1e157cfbbce4fe324 | Python | 2,579 | 57 | import torch
from tqdm import tqdm
import numpy as np
from transformers import pipeline
import os
import json
each_user_tweets=json.load(open("id_tweet.json",'r'))
feature_extract=pipeline('feature-extraction',model='roberta-base',tokenizer='roberta-base',device=2,padding=True, truncation=True,max_length=50, add_spec... |
51cbc6c14a82ead97d6aa5cfa393e88a0630b952a9849d1b8271ee11f0c66853 | Python | 2,579 | 60 |
import torch
import shutil
import logging
from typing import Type, List
from argparse import Namespace
from cosface_loss import MarginCosineProduct
def move_to_device(optimizer: Type[torch.optim.Optimizer], device: str):
for state in optimizer.state.values():
for k, v in state.items():
if tor... |
269de91912981e36b3a685bc9be0d2bc3697e61ba39d74a216dcf3ba0adcde72 | Python | 2,580 | 63 | # -*- coding: utf-8 -*-
################################################################################
## Form generated from reading UI file 'add_stream_dialog.ui'
##
## Created by: Qt User Interface Compiler version 6.4.2
##
## WARNING! All changes made in this file will be lost when recompiling UI file!
#########... |
211475ae3a2eaeb61554e486e303e86c2cbb535a0ac96cfaf423d3c90ff0b439 | Python | 2,581 | 100 | import pandas as pd
import time
import sys
import os
def main(argv):
if argv[1] == '--datasets':
try:
name = argv[2]
return name
except:
return "Wrong command!"
else:
return "Wrong command!"
def is_same(df1, df2, val):
df1_val = df1[val]
df2... |
2dc5bf4b9b4e4a8c4092950b3115d71235020675b581d8284f4f3421318f854b | Python | 2,582 | 68 | import os
import pickle
import shutil
from pathlib import Path
from typing import List
import pytest
from brainways.project.brainways_subject import BrainwaysSubject
from brainways.project.info_classes import ProjectSettings, SliceInfo
from brainways.utils.io_utils import ImagePath
@pytest.fixture
def brainways_tmp... |
cd95b3518eaae021b87051a723dbdacd797d08bf6f7cd4eaa3dd7f4c619c8245 | Python | 2,582 | 61 | import shutil
import os
#from ...bids_data.rename_bids_file import rename_bids_file
from cvdproc.bids_data.rename_bids_file import rename_bids_file
from nipype.interfaces.base import CommandLineInputSpec, File, TraitedSpec, CommandLine, BaseInterfaceInputSpec, BaseInterface
from traits.api import Str, Int, Directory, D... |
55a874415ebac67dafffa8664f9a775e6847e5b36ef7223872cf6607ddd7d4b1 | Python | 2,583 | 85 | # Copyright 2015 Numenta Inc.
#
# Copyright may exist in Contributors' modifications
# and/or contributions to the work.
#
# Use of this source code is governed by the MIT
# license that can be found in the LICENSE file or at
# https://opensource.org/licenses/MIT.
"""
This file contains plotting tools for NAB data and ... |
678c20e931c4ecfbdd2dcfb5f73e23db5e117332f0d549247d5eb407ab11c6f2 | Python | 2,583 | 71 | import base64
import json
import os
import shutil
from io import BytesIO
from pathlib import Path
from typing import Any
import numpy as np
import requests
from eir.setup.input_setup_modules.setup_image import default_image_loader
from eir.utils.logging import get_logger
logger = get_logger(name=__name__)
def load... |
241e592bff9c09873753613a55da51b77c1f19832794d5a3acc337a47ef03171 | Python | 2,585 | 84 | """
Tests for `bx.align.maf.sitemask`.
"""
import tempfile
from io import StringIO
import bx.align.maf
from bx.align.sitemask import cpg
test_maf_cpg = """##maf version=1 scoring=none
a score=0
s apple 34 64 + 110 AGGGA---GTTCGTCACT------GTCGTAAGGGTTCAGA--CTGTCTATGTATACACAAGTTGTGTTGCA--ACCG
s orange 19 61 - 100 AGG... |
38c22b0a373c02cd0f8568fd493fa560bef239c24c90153dd054e7d68130b0c1 | Python | 2,585 | 77 | import nrrd
import numpy as np
import pytest
from ccf_streamlines.projection import BoundaryFinder
@pytest.fixture
def boundary_finder(tmp_path):
"""A BoundaryFinder over a tiny two-region atlas.
Region 1 occupies the top two rows, region 2 the bottom two; the middle
rows are background (0), which `_val... |
82958457325582bbbdda3968bf78d6ce0d6be167c1c41e0b30ce5444fab75a26 | Python | 2,585 | 68 | #!/usr/bin/env python
"""
Phresh photonics QPD functionality
Hazen 05/17
"""
import numpy
from PyQt5 import QtCore
import storm_control.hal4000.halLib.halMessage as halMessage
import storm_control.sc_hardware.baseClasses.hardwareModule as hardwareModule
import storm_control.sc_hardware.baseClasses.lockModule as loc... |
bf6ea9b2d206014bc32b201b6583c8b75e6b1168851fb12eb2800775c4a0c933 | Python | 2,585 | 79 | """ Position Embedding Utilities
Hacked together by / Copyright 2022 Ross Wightman
"""
import logging
import math
from typing import List, Tuple, Optional, Union
import torch
import torch.nn.functional as F
from .helpers import to_2tuple
_logger = logging.getLogger(__name__)
def resample_abs_pos_embed(
po... |
f7dd1c6a74154b24fc7b1206fb5d21f03771d63c34a3f5a60b7f22ec0756aa1b | Python | 2,587 | 68 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
import torch
from ultralytics.utils import LOGGER, YAML
def torch2ncnn(
model: torch.nn.Module,
im: torch.Tensor,
output_dir: Path | str,
quantize: int | str | None = Non... |
ff3c083534eeb5307b42eab8db5998c38690a10ac0d0f4c1b0ba1afffaa999ef | Python | 2,588 | 86 | import pytest
import numpy as np
from chemgraph.models.calculators.emt_calc import EMTCalc
from chemgraph.models.calculators.mace_calc import MaceCalc
from chemgraph.models.calculators.tblite_calc import TBLiteCalc
from chemgraph.models.calculators.orca_calc import OrcaCalc
from ase import Atoms
def test_emt_calculat... |
143cb86d2a24073a99dd78b6735f5b7840ca119a10d2c52e14c264688c6e19ca | Python | 2,589 | 74 | import os
from sys import argv
from pathlib import Path
import rpy2.robjects as robjects
import numpy as np
import pandas as pd
from sklearn import linear_model
def rank_gene_dropouts(DataPath, CV_RDataPath, OutputDir):
'''
Script to rank the genes in the training set of the inputfile based on th... |
280955e081f297724298cf0b1c390b7114223857852dfabcf3e8831fce01b41e | Python | 2,589 | 57 | import pyvisa as visa
import pyvisascope
import multitimer
import time
import yaml
import logging
visa.log_to_screen('INFO')
logger = logging.getLogger('pyvisa')
log2file = logging.FileHandler('experiment.log')
logger.addHandler(log2file)
def main():
# enter here the ID of your device. On windows, VISA you c... |
09fe73da4f896846e7c1cb906122cf917b8927059526d4e2e8fc58aadfe1a0d3 | Python | 2,590 | 97 | """
Logging utilities for DHG-LGB framework.
Provides standardized logging across all modules with file and console output.
"""
import logging
import os
import sys
from datetime import datetime
from typing import Optional
def setup_logger(
name: str = 'DHG-LGB',
log_dir: Optional[str] = None,
log_level:... |
468d6bc0aa1f629d369cecaace7ce2fad39d37fb3c058849d7c4aee0443da331 | Python | 2,590 | 84 | import os.path as op
import dipy.data as dpd
import nibabel as nib
import nibabel.tmpdirs as nbtmp
import numpy as np
import numpy.testing as npt
import pytest
from dipy.reconst.shm import calculate_max_order
from AFQ.models import csd
from AFQ.models.asym_filtering import unified_filtering as pyafq_unified_filtering... |
74189b9f0aca8db56738b3ca4c3ff774b7b4669f770cd0502bbad1a6b889e647 | Python | 2,590 | 80 | from collections import OrderedDict
from torch import nn
from torch.nn.init import xavier_normal
import torch
from torch.nn import functional as F
import torch.nn.init as init
from attorch.regularizers import LaplaceL23d, LaplaceL2
from torch.autograd import Variable
from attorch.module import ModuleDict
from staticn... |
aa79d8c77786ad849d4f072998358af057c73d83e6de77a07593d4722eadb87a | Python | 2,590 | 54 | from brainscore_vision.model_helpers.check_submission import check_models
import functools
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vision.model_helpers.activations.pytorch import load_preprocess_images
from brainscore_core.supported_data_standards.brainio.s3 import... |
fe5686f9a20b0217d33e9f9d2f12581cc8f36b5bdfe9c743c588350fed1451d8 | Python | 2,590 | 93 | #!/usr/bin/env python3
"""
Base64 Image Remover for Markdown Files
This script removes base64-encoded images from markdown files,
deleting the image references and updating the markdown in place.
"""
import re
import argparse
from pathlib import Path
def remove_base64_images(markdown_content: str) -> str:
"""
... |
175e2c1babce77344a1d36e13efe0fa83ca9f61b093798aac42a99e9be350af2 | Python | 2,592 | 83 | # The ImpedanceFitter is a package to fit impedance spectra to
# equivalent-circuit models using open-source software.
#
# Copyright (C) 2018, 2019 Leonard Thiele, leonard.thiele[AT]uni-rostock.de
# Copyright (C) 2018, 2019, 2020 Julius Zimmermann,
# julius.zimmermann[AT]un... |
45c836bedfcee98484a04b39082dbc4834f85a9a72107a0e31c6ee11574d2abf | Python | 2,593 | 57 | import torch
from tqdm import tqdm
import numpy as np
from transformers import pipeline
import os
import json
each_user_tweets=json.load(open("id_tweet.json",'r'))
feature_extract=pipeline('feature-extraction',model='roberta-base',tokenizer='roberta-base',device=1,padding=True, truncation=True,max_length=50, add_spec... |
647cf309cb958430d5c4a508a14d4008a3c603cdff1398e740679ec4c4c41b2b | Python | 2,593 | 57 | import torch
from tqdm import tqdm
import numpy as np
from transformers import pipeline
import os
import json
each_user_tweets=json.load(open("id_tweet.json",'r'))
feature_extract=pipeline('feature-extraction',model='roberta-base',tokenizer='roberta-base',device=3,padding=True, truncation=True,max_length=50, add_spec... |
84057b9a43186ce78cf7cf73ed4cf8bb65d99b7326fafb52cb3b01afb897c57f | Python | 2,593 | 57 | import torch
from tqdm import tqdm
import numpy as np
from transformers import pipeline
import os
import json
each_user_tweets=json.load(open("id_tweet.json",'r'))
feature_extract=pipeline('feature-extraction',model='roberta-base',tokenizer='roberta-base',device=3,padding=True, truncation=True,max_length=50, add_spec... |
8da09555cdf2242d4e66c8e633f88e89fca0816503b715fe6b3911a640b9ba60 | Python | 2,593 | 57 | import torch
from tqdm import tqdm
import numpy as np
from transformers import pipeline
import os
import json
each_user_tweets=json.load(open("id_tweet.json",'r'))
feature_extract=pipeline('feature-extraction',model='roberta-base',tokenizer='roberta-base',device=2,padding=True, truncation=True,max_length=50, add_spec... |
8da2ab9db27225dfdf0184371f024c3e0a2844020d7c3acf15fea1215ba46d05 | Python | 2,593 | 57 | import torch
from tqdm import tqdm
import numpy as np
from transformers import pipeline
import os
import json
each_user_tweets=json.load(open("id_tweet.json",'r'))
feature_extract=pipeline('feature-extraction',model='roberta-base',tokenizer='roberta-base',device=3,padding=True, truncation=True,max_length=50, add_spec... |
c4290039015db07cd0400c376ca50da22489574434c3a9b09e4a1c520a83ef78 | Python | 2,593 | 60 | from typing import Generator, Callable, List
class Stage:
"""Abstract superclass for Runnables"""
def __init__(self, list_of_callables: List[Callable], **kwargs):
"""
:param list_of_callables: a list of callables, that must have a signature compatible with this __init__ function
(list... |
d9d88f3346c0d532ddb27f1b3522b721b8fa47afd0a179355ef4897b5b86af15 | Python | 2,593 | 95 | """
I/O utility functions.
Author: florian.birk@tuebingen.mpg.de
"""
import numpy as np
import pandas as pd
import nibabel as nib
import h5py
# ===== MULTIUSE =====
def load_nifti_float64(file_path):
"""Load NIfTI file data as float64 array.
Args:
file_path: Path to NIfTI file
Returns:
... |
e646057c70ca293ecff39217305171e62d60313e8fe8eba33a8b025e9406c293 | Python | 2,593 | 57 | import torch
from tqdm import tqdm
import numpy as np
from transformers import pipeline
import os
import json
each_user_tweets=json.load(open("id_tweet.json",'r'))
feature_extract=pipeline('feature-extraction',model='roberta-base',tokenizer='roberta-base',device=2,padding=True, truncation=True,max_length=50, add_spec... |
f5cbf12941fef377aed98a16eec89309283902814c2dff62a7747b34d29603fd | Python | 2,593 | 57 | import torch
from tqdm import tqdm
import numpy as np
from transformers import pipeline
import os
import json
each_user_tweets=json.load(open("id_tweet.json",'r'))
feature_extract=pipeline('feature-extraction',model='roberta-base',tokenizer='roberta-base',device=1,padding=True, truncation=True,max_length=50, add_spec... |
fbfe14ae06873a9c54bdf3ce4d6e674fefe2e9e8efbc5a6cdb530ed72fd65da3 | Python | 2,593 | 57 | import torch
from tqdm import tqdm
import numpy as np
from transformers import pipeline
import os
import json
each_user_tweets=json.load(open("id_tweet.json",'r'))
feature_extract=pipeline('feature-extraction',model='roberta-base',tokenizer='roberta-base',device=2,padding=True, truncation=True,max_length=50, add_spec... |
4532a7c5053079c3275728a638909ce1d77dd408b698a9c225c0c535d343ea42 | Python | 2,594 | 77 | import os
import numpy as np
from PIL import Image
from scipy.signal import convolve2d
def matlab_style_gauss2D(shape=(3, 3), sigma=0.5):
# 高斯加窗
m, n = [(ss - 1.) / 2. for ss in shape]
y, x = np.ogrid[-m:m + 1, -n:n + 1]
h = np.exp(-(x * x + y * y) / (2. * sigma * sigma))
h[h < np.finfo(h.dtype).... |
7401a2718767d09d3b8f8f1d8d7a01342cefc26bdc2060b35404b26edc9f0a1b | Python | 2,594 | 82 | """
ROI-specificity analysis.
This script runs the same moderation model across multiple ROI-level
cooperation-related IBS change variables and summarizes the interaction term.
Expected input:
data/processed_main_analysis_data.csv
"""
from pathlib import Path
import pandas as pd
import statsmodels.formula.api as... |
09dbfa460c1956f1814c4d79ed932edea5eb3d60cb8bff7b21a73e68901f23e0 | Python | 2,595 | 117 | # Copyright 2015 Numenta Inc.
#
# Copyright may exist in Contributors' modifications
# and/or contributions to the work.
#
# Use of this source code is governed by the MIT
# license that can be found in the LICENSE file or at
# https://opensource.org/licenses/MIT.
import os
import unittest
try:
import simplejson as ... |
1a4b9fcdbdece387b9f21563a3e9732b30045bccb74807320a2246087922d68a | Python | 2,595 | 81 | # -*- coding: utf-8 -*-
#
# test_contexts.py
import unittest
import arbor as arb
"""
all tests for non-distributed arb.context
"""
class TestContexts(unittest.TestCase):
def test_default_allocation(self):
alloc = arb.proc_allocation()
# test that by default proc_allocation has 1 thread and no ... |
1cf27d9cf6bfa73e8aa68dd58c7e5c52e63e9e938f95b4061dd5e86136fe4d84 | Python | 2,596 | 124 | # Configuration file for the Sphinx documentation builder.
# -- Project information
import sys
import os
import subprocess
import memilio
project = 'MEmilio'
copyright = '2020-2026 MEmilio'
author = ''
release = ''
version = '1.3.0'
read_the_docs_build = os.environ.get('READTHEDOCS', None) == 'True'
if read_the_d... |
32b4f979e83431cdddd8ba22c49921c9c05ef6c616890bec88b1a41cb5f2c7ce | Python | 2,596 | 94 | """Class definitions and utility functions specifically related to
experimental design and organization.
"""
import pandas as pd
class Trial:
"""
Experimental trial container.
This class is a placeholder for trial-specific metadata and methods.
"""
pass
class Session:
pass
class Cue:
... |
49c5433805f035aae712e0c3150e2a3c7e81f3604cf40bd5f2961e20e9035a06 | Python | 2,596 | 82 | """Tests for `mmsplice` package."""
import pandas as pd
from numpy.testing import assert_almost_equal
from mmsplice import MMSplice
from mmsplice.utils import encodeDNA, delta_logit_PSI_to_delta_PSI
from mmsplice.vcf_dataloader import SplicingVCFDataloader
from mmsplice.exon_dataloader import ExonDataset
from mmsplice ... |
b8146d6f8a0c1328b696579fc3e46af3c820cffb2da99213c5c4379f9fb4e825 | Python | 2,596 | 85 | """Step 5: Parcellation."""
from pathlib import Path
import mne
import matplotlib
matplotlib.use("Agg")
from osl_dynamics.meeg import parallel, source_recon, parcellation
from osl_dynamics.utils.filenames import OSLFilenames
# ----------------------------------------------------------------------------
input_dir = Pa... |
cb5087a980b728fef4b3425793992e7433e2032c625d49f4825b278e2df515aa | Python | 2,596 | 70 | # Keywords and parameters obtained from QCEngine: https://github.com/MolSSI/QCEngine
# MOPAC parameters for CompChemAgent
from pydantic import BaseModel, Field
class MopacCalc(BaseModel):
"""MOPAC calculator configuration.
This class defines the configuration parameters for the MOPAC calculator,
which i... |
4cc0d33f4f0ef70745eab5ab50c3e9775d88cd5405c349f8fee820a0832606a6 | Python | 2,597 | 77 | import torch
from transformers import AutoTokenizer
class DNABertTokenizer:
# The Tokenizer actually performs the encoding
def __init__(self, k=3):
super(DNABertTokenizer, self).__init__()
self.k = k
if k not in [3, 4, 5, 6]:
raise Exception(
f"There does n... |
bd1f0e0383f9d17686dd87c582ad1ff54131a65dcbf021f055396d60dfe5c7f5 | Python | 2,598 | 80 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
# Generated by Django 5.2.14 on 2026-07-31 08:28
from django.conf import settings
from django.core.management.base import CommandError
from django.db import migrations, models
SERVER_WEBHOOKS_EXIST_ERROR = """\
Cannot roll back: found {count} webho... |
362bcf1e7669411120ad38b2fb840ec9c069b48b5d3107e5cc2b396c793b4e39 | Python | 2,599 | 67 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""This file is the main file that highjacks a model to make it do what we want
"""
import material
import numpy as np
import pandas as pd
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squared_error, r2_score
PI = 3.14159265359
def c... |
5075e447376bc5adaf3e54de7c612f124436c39e223a491734912394d859f828 | Python | 2,599 | 63 | #!/usr/bin/env python3
import sys
import getopt
import time
############################################################################
# Main gateway:
#############################################################################
# usage
def main_usage():
print("""
Usage : MIRROR.py action [options]
Actions:
... |
51b35046c3e7c40b7202d8a1b1165b2fe631a7000cd0f0efc089ff2a6aa09d84 | Python | 2,599 | 72 | # Copyright (C) 2020-2022 Intel Corporation
#
# SPDX-License-Identifier: MIT
import cv2
import numpy as np
from openvino.inference_engine import IECore
class ModelLoader:
def __init__(self, model, weights):
ie_core = IECore()
network = ie_core.read_network(model, weights)
self._network = ... |
d507ed1551c127729dd54e39829fd2a9e230984a6454e2d8b8ed0ae94f67abdf | Python | 2,599 | 91 | # 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 os
import subprocess
import threading
from pathlib import Path
import numpy as np
import torch
def fasta_file_path(prefix_path):
... |
3533eb1a663fa3e136534273ba9dd8d992ed764aaed64d40f60b7bda4a7c11e0 | Python | 2,600 | 74 | from os import PathLike
import numpy as np
from argclz import AbstractParser
from neuralib.suite2p import Suite2PResult, get_neuron_signal, sync_s2p_rigevent
from neuralib.util.utils import ensure_dir
from neuralib.util.verbose import publish_annotation, print_save
from rscvp.util.cli import SelectionOptions
from sti... |
3769b2fb5ebd5ed3ffa6d24bdb4e193e27884639857371bf0215a9047bee6b83 | Python | 2,601 | 76 | """ Parts of the U-Net model """
import torch
import torch.nn as nn
import torch.nn.functional as F
class DoubleConv(nn.Module):
"""(convolution => [BN] => ReLU) * 2"""
def __init__(self, in_channels, out_channels, mid_channels=None):
super().__init__()
if not mid_channels:
mid_c... |
45e7a6cdc97512ce6e64a7240da4e0a247a24d925b70d5d70cd44c48bb40beb1 | Python | 2,601 | 82 | import os
import cv2
import sys
sys.path.append("/LiNet")
import torch
import numpy as np
from torch.autograd import Variable
import argparse
import random
from lib_alban.utils_analyse import def_masks_extract
import os.path as osp
os.environ["OPENCV_IO_ENABLE_OPENEXR"] = "1"
import lib_alban.utils_test as utils_tes... |
016ce5cc3109b6083ddfa8b00c926f80c0d91977d044549c558b046f485841bc | Python | 2,602 | 92 | """
Support for masking potential CpG sites in *pairwise* alignments.
"""
from bx.align.sitemask import Masker
from ._cpg import (
list_cpg,
list_cpg_restricted,
list_non_cpg,
)
# Restricted. Only mask out sites that are defitely CpG
class Restricted(Masker):
def __init__(self, mask="?"):
su... |
02d92ff754ad8d71fa892a002181f27a72fad25edacf392cea4b7ad7a57eac6e | Python | 2,603 | 78 | # FetMRQC: Quality control for fetal brain MRI
#
# Copyright 2023 Medical Image Analysis Laboratory (MIAL)
#
#
# 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/lice... |
14f43778c8ba25023bd1257c8fe7ff1b5609c9dd398c19376a7a7afb2efc04bd | Python | 2,603 | 77 | from math import exp
import torch
import torch.nn.functional as F
from torch.autograd import Variable
def gaussian(window_size, sigma):
gauss = torch.Tensor([exp(-(x - window_size // 2) ** 2 / float(2 * sigma ** 2)) for x in range(window_size)])
return gauss / gauss.sum()
def create_window(window_size, cha... |
c6904d8d53942d6c350bc262b696672cb1e459ae2f3b518aed8bb0acd4be9afa | Python | 2,603 | 110 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Sep 14 13:19:13 2022
@author: proussel
"""
import os
import shutil
from glob import glob
import datetime
import socket
import fcntl
import json
from importlib.resources import files
from pathlib import Path
import numpy as np
# list subdirectories o... |
4be066258e0e1c9d2dac1fecf5f2631f983a5d9fe23daf41dfa89c8342af5252 | Python | 2,604 | 69 | import numpy as np
import pandas as pd
from . import ELA_Network_functions
#-----------------------------------------------------------------------------------
from pyvis.network import Network
def plot_Graph_by_pyvis(path_read_info_ALLState:str, SS_color_dict:dict, path_save:str=False) -> None:
#---------------... |
bd1e8891c59a5cf29f4c75014aaa7f2a043ae8066badd6c2dcf2bbc4702e80eb | Python | 2,604 | 73 | import pickle
import mne
import pandas as pd
import numpy as np
import glob
from update_sub_lists import *
import mido
def load_pickle(filepath):
with open(filepath, 'rb') as file:
return pickle.load(file)
def onsets_pitch_from_midi(file):
"""
Extracts the midi values from a file and returns... |
f026b48f33fe62320c3100b3da2719ac3719aadee238ba99381939c6122590e6 | Python | 2,604 | 72 | import sys
from setuptools import find_packages, setup
# package requirements
if sys.version_info[:2] < (3, 6):
raise RuntimeError("Python version >= 3.6 required.")
with open("requirements.txt", "r") as f:
requirements = f.read().splitlines()
if sys.version_info[:2] == (3, 6):
requirements = [x for x in ... |
3b29b6562fc9526102e6e7f1665c10fbec79f6442ef3b680c8b87eeef02783bc | Python | 2,606 | 60 | import os
import numpy as np
from scipy.io import wavfile
from tqdm import tqdm
from basic_filter.HighPassFilter import HighPassFilter
from basic_filter.LowPassFilter import LowPassFilter
from basic_filter.BandPassFilter import BandPassFilter
import re
def read_wav_files_from_folder(audio_dir, scale=None):
folder_... |
b1c8eee451381ff503e8ee187c8dd50b3a3b8cee11f8d1e73c9d0a0027dffc0c | Python | 2,606 | 110 | # Tools to deal with specific kinds of strings (like paths)
import re
import collections
import numpy as np
def get_atoms_and_amount(formula: str) -> list[tuple[str, int]]:
"""Return a list of tuples of elements and amount
Params
------
formula: chemical formula as a string
Returns
------... |
2db8970bf29256575e55e48ce0287e920ca9af9196aaf35f5284cf66b2fa414f | Python | 2,608 | 89 | from types import SimpleNamespace
import numpy as np
import pandas as pd
from skspatial.objects import Line
from napari_dmc_brainmap.results.results_helpers.tract_calculator import (
TractCalculator,
)
def test_get_linefit3d_preserves_fitted_line_and_voxelization():
calculator = TractCalculator.__new__(Trac... |
aab89a99f923ef3d9cb1961e20c9b5feecebfd779e97f87fb6582a3f7e77e432 | Python | 2,608 | 84 | """ Dataset reader that wraps Hugging Face datasets
Hacked together by / Copyright 2022 Ross Wightman
"""
import io
import math
from typing import Optional
import torch
import torch.distributed as dist
from PIL import Image
try:
import datasets
except ImportError as e:
print("Please install Hugging Face data... |
4a1986eee080fdffcfca27637f108c0fe06706489fe28300694e3e06e7a4580d | Python | 2,609 | 70 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Nov 29 10:21:18 2023
@author: natalia
Script to compute MIND networks
Copyright (C) 2026 University of Seville
Written by Natalia García San Martín (ngarcia1@us.es)
This file is part of Hierarchy Longitudinal MIND Gradients Psychosis to... |
ae595ece1c5d45ebc1d4801bd3985a061e884c3b5a58b65b64341d715173c623 | Python | 2,609 | 85 | """Shared parsing utilities for extracting structured JSON from LLM output.
Both ``single_agent.py`` and ``multi_agent.py`` need to parse free-form
LLM text into Pydantic models (``ResponseFormatter``, ``PlannerResponse``).
This module centralises the common helpers so they stay in sync.
"""
import re
from chemgraph... |
164491f2e518375d6ff9c169637b633e096dee46b860ff89e9ced155a44eb9c9 | Python | 2,611 | 89 | # %%
# imports up top, babies
import os
from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
import pandas as pd
import torch
import torchvision
from tqdm import tqdm
# %%
# Argle parser
parser = ArgumentParser(
prog='calc_alexnet_activations',
description='Get PyTorch AlexNet predictions for a ... |
75ec27c1a22a40564dc4845082fed5fa0c21913b461e59641d2133bf8df77448 | Python | 2,611 | 67 | from typing import Set
import numpy as np
import torch
from batchgeneratorsv2.transforms.base.basic_transform import BasicTransform
class TransposeAxesTransform(BasicTransform):
"""
A transformation class to permute specified spatial axes of an image and related data.
Attributes:
allowed_axes (S... |
ee01d474a2a4c437d285263c406ab05787132526b452a4e85e87e5798eafcb8f | Python | 2,611 | 86 | """
Support for "biological sequence" files.
:Author: Bob Harris (rsharris@bx.psu.edu)
See seq.py for more information
"""
import struct
from . import (
fasta,
nib,
qdna,
)
# DNA reverse complement table
DNA_COMP = (
" - "
" TVGH CD... |
ff815fb1f748a7e332ede4b3906f12a74543c4f1d236e2fa542b5fe8da5397dc | Python | 2,612 | 73 | import torch
from reducers import AvgNonZeroReducer
from utils import loss_and_miner_utils as lmu
from losses.base_metric_loss_function import BaseMetricLossFunction
class TripletMarginMMDLoss(BaseMetricLossFunction):
"""
Args:
margin: The desired difference between the anchor-positive distance and t... |
6d537aa4a18519bfd7dfff7785ca87a7dc769165c88df2c845c886f477cdd03e | Python | 2,613 | 61 | import glob
import os
import argparse
import numpy as np
import pandas as pd
import xarray as xr
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--directory', type=str, default=os.path.join('V1Data', 'NatRev'))
args = parser.parse_args()
print("Running with args {}".format(vars(ar... |
b2afb13845c3bda5953c1690355756d55c769460fc0e4306381c9c8196a62ec0 | Python | 2,613 | 53 | from brainscore_vision.model_helpers.check_submission import check_models
import functools
import torch
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vision.model_helpers.activations.pytorch import load_preprocess_images
from brainscore_core.supported_data_standards.brai... |
e964b96a480f7e8936b497aa06b2148199e3c457426e7fde54832361cf2d84c8 | Python | 2,613 | 73 | import os
import rpy2.robjects as robjects
import numpy as np
import pandas as pd
from sklearn import linear_model
def rank_gene_dropouts(DataPath, CV_RDataPath, OutputDir):
'''
Script to rank the genes in the training set of the inputfile based on their dropout level.
This rank is written to a ... |
715c2ac5947665ebee516fe0c910a4693e118813005aeda26645fb73c6040870 | Python | 2,614 | 63 | import numpy as np
import numpy.testing
from brainways.pipeline.brainways_params import AffineTransform2DParams
from brainways.transforms.affine_transform_2d import BrainwaysAffineTransform2D
def test_affine_transform_keypoints():
params = AffineTransform2DParams(angle=0, tx=1, ty=0, sx=1, sy=1)
transform = ... |
d0278b1ad952d2fe0bdd010f2b52baf1c40df56b450dcd961584f4a53819403e | Python | 2,614 | 70 | # This file is part of Mooney computational modeling project.
#
# Mooney computational modeling project 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) an... |
3fcc9c974dcb1bca56b346f855274ff149e3b944fd81cc16c41940d4de238e34 | Python | 2,615 | 69 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import json
import os
import tempfile
from scilpy import SCILPY_HOME
from scilpy.io.fetcher import fetch_data, get_testing_files_dict
# If they already exist, this only takes 5 seconds (check md5sum)
fetch_data(get_testing_files_dict(), keys=['bundles.zip'])
tmp_dir = t... |
451e597f906204e31d8dd8f0678dcff22b9fdbe734fe7a0db334f97acbb32fa4 | Python | 2,615 | 77 | import matplotlib.gridspec as gridspec
from src.convert_spectrum_to_colour import *
# Visualise absorption spectra at different pH values for a set of 4 natural colourants
colourants = ["Emodin", "Quinalizarin", "Orcein", "Biliverdin"]
colourants_titles = ["Emodin", "Quinalizarin", "Alpha-hydroxyorcein", "Biliverdin"... |
25cf7fddcf693fb1b68f7dfc9c39659ca4339e6e6ea604e3d0cac07081c6e3cb | Python | 2,617 | 99 | # -*- coding: utf-8 -*-
#
# test_simulator.py
import unittest
import arbor as A
from .. import cases
mpi_enabled = A.__config__["mpi"]
"""
test for MPI distribution of spike recording
"""
class lifN_recipe(A.recipe):
def __init__(self, n_cell):
A.recipe.__init__(self)
self.n_cell = n_cell
... |
271402858de72c822c2d9c640e8258df4d0923945d8ade2920674ad32870a9c8 | Python | 2,617 | 64 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import tempfile
from scilpy import SCILPY_HOME
from scilpy.io.fetcher import fetch_data, get_testing_files_dict
# If they already exist, this only takes 5 seconds (check md5sum)
fetch_data(get_testing_files_dict(), keys=['filtering.zip'])
tmp_dir = tempfile.Te... |
6baf0656fad2db6fe35e82684f149a0f328b7c0302c27534908f5fe2282c62dc | Python | 2,617 | 75 | import numpy as np
from PIL import Image
import os
#---------------------------------------------------------#
# 将图像转换成RGB图像，防止灰度图在预测时报错。
# 代码仅仅支持RGB图像的预测，所有其它类型的图像都会转化成RGB
#---------------------------------------------------------#
def cvtColor(image):
if len(np.shape(image)) == 3 and np.shape(image)[2] == 3:... |
f0fdcd1272502c990d05a1b7a20a3db63ad91bcf8227f1a478983527e528d971 | Python | 2,617 | 75 | # Copyright (C) 2022 Intel Corporation
# Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from http import HTTPStatus
from time import sleep
from typing import Any
import pytest
from shared.utils.config import get_method, post_method
def _post_task_remote_data(username, task_id, resources):
d... |
fae05835f9ecddc7d069f58e1a2c6dc907c3721710b4db1f0a73fa9765f9354b | Python | 2,617 | 72 | import torch
import torch.nn as nn
# from .utils import load_state_dict_from_url
__all__ = ['AlexNet', 'alexnet']
# model_urls = {
# 'alexnet': 'https://download.pytorch.org/models/alexnet-owt-4df8aa71.pth',
# }
class AlexNet(nn.Module):
def __init__(self, num_classes=1000, in_chans=1):
super(Ale... |
8e9bcd44af07408e02bce346d3ca9bd946d95a37e2ec661ed7174dd0513b0df3 | Python | 2,618 | 70 | import os
from datetime import datetime
class Logger(object):
def __init__(self, verbose=0, log_path=None, file_prefix=""):
self.verbose = verbose
self.filename = None
if log_path is not None:
if not os.path.exists(log_path):
os.makedirs(log_path)
s... |
f93a7d708efd41831abef39d62708eaea5a0288953fbc89605f24b0c567043d0 | Python | 2,618 | 98 | import numpy as np
from fancyimpute.dictionary_helpers import (
dense_matrix_from_pair_dictionary,
dense_matrix_from_nested_dictionary,
reverse_lookup_from_nested_dict,
transpose_nested_dictionary,
)
from nose.tools import eq_
def test_dense_matrix_from_nested_dictionary():
d = {
"a": {"b... |
839d115c439fb2e1de78bfaba94deee086ef2abee4ecbd8325c30171a896e58e | Python | 2,619 | 77 | # 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... |
4ae6e2a1ec30c71911dec1b9abf9dd075ea5acc0c5e662b1baf23e79d5b40476 | Python | 2,620 | 69 | import functools
import importlib
from brainscore_vision.model_helpers.activations.pytorch import load_preprocess_images
from brainscore_vision.model_helpers.check_submission import check_models
import torch.hub
import ssl
from brainscore_core.supported_data_standards.brainio.s3 import load_weight_file
from torch.nn im... |
4d8de7cf9f690ea253f6f40d2853447ed306c331d331e79ecafa3a7bb0c374dd | Python | 2,620 | 67 | import torch
from torch_geometric.nn import MessagePassing
from torch_geometric.nn import global_add_pool, global_mean_pool, global_max_pool, GlobalAttention, Set2Set
import torch.nn.functional as F
from torch_geometric.nn.inits import uniform
from conv import GNN_node, GNN_node_Virtualnode
from torch_scatter import ... |
7e8e6d66c9bc3672bb09bee608ea2981a8d09ddfedd3272971425240b8e34317 | Python | 2,620 | 93 | """
Calculate the compression
"""
import os
import sys
from pathlib import Path
from tqdm import tqdm
import numpy as np
import pandas as pd
import torch
from neuralcompress_v3.models import BiModel
from enuralcompress_v3.utils import load_tpc_wedges
# uncomment if multiple GPU is available
# and you want to use an ... |
a6f55a2bf78d854a94ce49b09d229d6d8b41e7ca95fbae2affb3cd0a6b732d58 | Python | 2,620 | 67 | import torch
from torch_geometric.nn import MessagePassing
from torch_geometric.nn import global_add_pool, global_mean_pool, global_max_pool, GlobalAttention, Set2Set
import torch.nn.functional as F
from torch_geometric.nn.inits import uniform
from conv import GNN_node, GNN_node_Virtualnode
from torch_scatter import ... |
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