sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
78c7638a1d6f2c9e0bc3972f37f89e3520df7b8f96a7090de58e93dc4d0eee7e | Python | 5,922 | 196 | """
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 math
from typing import Optional
import torch
from ocpmodels.common.utils import scatter_det
from ocpmodels.modules.scaling import Sc... |
21a29a324df74964346f6e1607f2bcc66f6e28cacc22195437d330fff76b50cd | Python | 5,925 | 155 | import matplotlib.pyplot as plt
import sys
import pyspike as spk
import pandas as pd
import numpy as np
import os
import math
import matplotlib.pyplot as plt
import seaborn as sns
ac_spks = pd.read_pickle('ic_spks_full.pkl')
freq_ls = [1000., 1500., 2000., 3000., 4000., 6000., 8000., 12000.,
16000., 2000... |
308b0be8b3b3f021b3d1ca74566d1ffd39777c829e4dc49d5fa569191ee363db | Python | 5,927 | 223 | import os
import pytest
from medperf.entities.benchmark import Benchmark
from medperf.entities.cube import Cube
from medperf.entities.dataset import Dataset
from medperf.entities.execution import Execution
from medperf.tests.entities.utils import (
setup_benchmark_fs,
setup_benchmark_comms,
setup_cube_fs,
... |
5707267467f799270a1f4df6eb862739b82dff24f08c32e485547453d8c70acb | Python | 5,928 | 181 | import argparse
import os
import re
import sys
from typing import TextIO
import cpplint
from cpplint import _cpplint_state
CXX_SUFFIX = set(["cc", "c", "cpp", "h", "cu", "hpp"])
def filepath_enumerate(paths: list[str]) -> list[str]:
"""Enumerate the file paths of all subfiles of the list of paths"""
out = [... |
5f5e337af50bc7bfdf98fa26633013dece0d9635a0173f12ab0f8791d4a0be8a | Python | 5,929 | 155 | import matplotlib.pyplot as plt
import sys
import pyspike as spk
import pandas as pd
import numpy as np
import os
import math
import matplotlib.pyplot as plt
import seaborn as sns
ac_spks = pd.read_pickle('acx_spks_full.pkl')
freq_ls = [1000., 1500., 2000., 3000., 4000., 6000., 8000., 12000.,
16000., 200... |
9f8fe611e7800bfd2a651fc976ba9c533f806b2528b0d0681e79e68b538c4d5d | Python | 5,930 | 191 | """Demonstrates active learning molecular dynamics with constant temperature."""
import argparse
import os
import time
import ase.io
import numpy as np
from ase import units
from ase.md.langevin import Langevin
from ase.md.velocitydistribution import MaxwellBoltzmannDistribution
from mace.calculators.mace import MAC... |
22cdfcea62c14e0bd2a481ac33e91fc9541cdcfd376fa88a01b4eadc73f2591b | Python | 5,932 | 159 | import logging
from pathlib import Path
from sys import stdout
from openff.interchange import Interchange
from openff.toolkit import Molecule
from openff.toolkit.typing.engines.smirnoff import ForceField
from openff.toolkit.utils.exceptions import UndefinedStereochemistryError
from openmm import System, app, unit
from... |
a778be00d67c393c5a62869e7acfb7bd9b6568ba7bfaff8522105b7bbc575c31 | Python | 5,933 | 181 | #!/usr/bin/env python
# coding: utf-8
import os.path as op
import random
import time
import matplotlib.pyplot as plt
import numpy
import sklearn
import torch
import torch.nn.functional as nn_func
from sklearn import preprocessing
from sklearn.metrics import adjusted_rand_score
from torch.nn import Linear
from torch_g... |
c3951356dae68561e0bd54da8f3df1680eefba6b85e43c3637da2bcaf14c4f3b | Python | 5,933 | 105 | import os
import pickle as pkl
import shutil
from src.nnunet_v1 import train_nnunet
from nnunet.paths import default_plans_identifier
def train_on_task(task, network, network_trainer, fold, cuda_device, plans_identifier, continue_training=False, current_epoch=0):
os.environ['CUDA_VISIBLE_DEVICES']=cuda_device
... |
c1fd431e511eb461239e9c8371436cfa8c6a2d0a84b503fa496940e050465372 | Python | 5,937 | 156 | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import glob
import math
import os
import os.path as osp
import tempfile
import zipfile
import mmcv
import numpy as np
from mmengine.utils import ProgressBar, mkdir_or_exist
def parse_args():
parser = argparse.ArgumentParser(
description='Con... |
857150dc46cf76c1df0c07c255ac0eafe41affeeba9573c8caa442710c45d537 | Python | 5,941 | 214 | import re
import typer
from getpass import getpass
from yaspin import yaspin
from contextlib import contextmanager
from .interface import UI
class CLI(UI):
def __init__(self):
self.spinner = yaspin(color="green")
self.is_interactive = False
self.is_parsed_output = False
def print_url... |
e221fb4903c26abb1d3f132c2d26d649002c3c9b1bbec239ca8e51d82b7b35fc | Python | 5,944 | 228 | import numpy as np
import pandas as pd
from tqdm import tqdm
import time
import matplotlib.pyplot as plt
import py4DSTEM
# import seaborn as sns
from bayes_opt import BayesianOptimization
print(py4DSTEM.__version__)
n_dim = 8
init_points=20
n_iter=4000
dataset = py4DSTEM.read("ptycho_Si-110_18nm.h5")
dataset.calibr... |
ca3eb54db8f9cdf02e6d99328d07b971471e71c5d502c577082d55c3334f3d22 | Python | 5,945 | 185 | import pytest
import os
import base64
from medperf.commands.certificate.utils import (
current_user_certificate_status,
check_matching_certificates,
load_user_private_key,
)
from medperf.tests.mocks.certificate import TestCertificate
from medperf import config
from medperf.enums import CryptoKeyType
PATCH_... |
4f4fd9e325cc73b2c9c606652cc85c2b30993eb1ba6f896d11079c26929f459d | Python | 5,946 | 167 | # -*- coding: utf-8 -*-
import tensorflow as tf
import numpy as np
import pandas as pd
from scipy.spatial import distance_matrix
from qtools.encoding import onehot_encoding
#https://github.com/keras-team/keras/pull/10856
#puts four identical models besides each other and concatenates the output.
class quartetm... |
d9ec23a2d0c2ec0184dad2cf3621c63278e2ca619ef857b244b1e87c8d2c5368 | Python | 5,946 | 141 | # The following code is modified based on https://github.com/pytorch/text/blob/master/torchtext/vocab.py
import array
import zipfile
from tqdm import tqdm
from six.moves.urllib.request import urlretrieve
import os
import os.path as osp
import torch
import io
def reporthook(t):
"""https://github.com/tqdm/tqdm"""
... |
6a18d68817b95d36f33a4264627338301dfe7c6f2159de89b846e4e9ce6ddf2a | Python | 5,950 | 193 | #!/usr/bin/env python3
"""
Aggregate unblinding analysis for the CICADA smoothing blinded-review packet.
Reads:
* BLINDED_SCORING.csv
* PRIVATE_UNBLINDING_KEY.csv
Prints ONLY aggregate results by default. It does not print subject IDs,
task names, or IC numbers.
All inputs/outputs remain PRIVATE human-subject-de... |
867bd85217b95685a890a68b1a148717db0ea4bd4fda0d526466b9132b64a5ab | Python | 5,950 | 171 | """
Functions for building libxgboost
"""
import logging
import os
import pathlib
import shutil
import subprocess
import sys
from platform import system
from typing import Optional
from .build_config import BuildConfiguration
def _lib_name() -> str:
"""Return platform dependent shared object name."""
if sys... |
10d4df585e03dc1442e07f73f3f1d63eee02a0befff751c9c3450fa512032c20 | Python | 5,953 | 195 | # -*- coding: utf-8 -*-
# @Author: Theo Lemaire
# @Date: 2023-08-17 16:10:10
# @Last Modified by: Theo Lemaire
# @Last Modified time: 2024-10-20 15:00:50
''' General utility functions. '''
import os
import numpy as np
import pandas as pd
from scipy.interpolate import interp1d
import datetime
import matplotlib.bac... |
ce64eab1e51e4ec0387b4095736504fe9b2e9ef99fdea16b74cedf8ad5cee49c | Python | 5,953 | 127 | import pytest
from CybORG import CybORG
from CybORG.Shared.Session import Session
from CybORG.Simulator.Scenarios.EnterpriseScenarioGenerator import EnterpriseScenarioGenerator
from CybORG.Agents.SimpleAgents.ConstantAgent import SleepAgent
from CybORG.Simulator.Actions.ConcreteActions.RemoveOtherSessions import Remov... |
17ab23c98ad012685a53df46c86cb074ed4aabc688fd931b5d775bb22ee1a523 | Python | 5,955 | 157 | import sys
import shutil
import os
import math
import numpy as np
from cloudvolume import CloudVolume
from cloudvolume.exceptions import EmptyVolumeException
import logging
import argparse
from PIL import Image
import pathlib2 as pathlib
from tqdm import tqdm
import imageio
logging.basicConfig(level=logging.INFO)
logg... |
c398596627c37617d1ee87b4222f617eaab22b95f61a53d997f4d30ecb7aae9d | Python | 5,955 | 140 | import torch
import pandas as pd
from sklearn.linear_model import LogisticRegression, LogisticRegression
from sklearn.model_selection import cross_val_score, LeaveOneOut
import numpy as np
import os
from tqdm import tqdm
import sys
features = ['sonority','manner','voicing','place']
def feature_decodability(state_dict... |
64aaaf9ae4e41a56b223957116e5178de19181e97c6343ee405ec4c12d06a199 | Python | 5,957 | 166 | import os
import tempfile
import numpy as np
import pytest
import xgboost as xgb
from xgboost import testing as tm
from xgboost.testing.continuation import run_training_continuation_model_output
rng = np.random.RandomState(1337)
class TestTrainingContinuation:
num_parallel_tree = 3
def generate_parameters... |
c9522b051ee81688f0da7c54c7e4159c953def2343f7639f52db194719ee0526 | Python | 5,960 | 178 | # -*- coding: utf-8 -*-
import json
import logging
from typing import List
from urllib.request import Request, urlopen
from urllib.error import HTTPError, URLError
from django.conf import settings
logger = logging.getLogger(__name__)
def load_json(url):
logger.debug("janelia_render.models.load_json: entry, ur... |
b1445d088254892cdfe58deb79506d9fa397197c3f4b3800bfaaea0ad263eab3 | Python | 5,961 | 198 | #*******************************************************#
# Classes used as configuration files
#*******************************************************#
class datasetConfig:
'''
Class for defining dataset parameters: shape, split ratio, augumentation etc.
'''
'''
Imgs_png_home_path = Root direc... |
8a159ee3ffbf8184e64099d48bc240c63dc868dcc8032e6d0d6087b80789adc6 | Python | 5,964 | 167 | import torch
from torch import nn
from torch_geometric.nn import GCNConv, GATConv, HypergraphConv
from torch_geometric.utils import add_self_loops
from collections import OrderedDict
import numpy as np
class GCN(nn.Module):
def __init__(self,
in_features,
depths,
... |
fa54ca23a80c01941819af74cce2b54f3d648a36846d16a8df05ac32a819f95f | Python | 5,967 | 171 | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmseg.models.backbones.twins import (PCPVT, SVT,
ConditionalPositionEncoding,
LocallyGroupedSelfAttention)
def test_pcpvt():
# Test normal input
... |
5b373608ba4848df0ec5476bfdc409c00e46939a7df3fca9e6a892b36e6cc341 | Python | 5,971 | 133 | """What acquisition format a session holds, and what that implies for NWB export.
Shared by Step 6 (which needs to know whether the user must supply a session start time) and
Step 7 (which needs to tell the converter how to read the raw folder), so it lives apart from
either step's orchestration.
"""
from .utils impo... |
7f7dafe27bf0eec6befebe1e3e2738af931080560fe59b12c13c318e04440980 | Python | 5,972 | 155 | import numpy as np
from dataclasses import dataclass
from typing import Union, Optional
import torch
@dataclass(frozen=True)
class Flatten:
def __call__(self, data: np.ndarray):
return data.reshape(data.shape[0], -1)
@dataclass(frozen=True)
class TakeEventByTime:
"""Take events in a certain time inter... |
f1835fd7cc6f399b03884698ede3600f465d15866277a3e0073e2886e4d124ff | Python | 5,973 | 144 | import shutil
from pathlib import Path
from unittest.mock import patch
import holoviews as hv
import pandas as pd
import panel as pn
import pytest
from guppy.frontend.parameterized_plotter import ParameterizedPlotter
from guppy.frontend.visualization_dashboard import VisualizationDashboard
from guppy.testing.api impo... |
0452eb6b069b44075c32b62a593ec5539609c911994ed07e8e5eacd7762da312 | Python | 5,981 | 128 | # SPDX-License-Identifier: Apache-2.0
import mxnet as mx
def Conv(**kwargs):
body = mx.sym.Convolution(**kwargs)
return body
def Act(data, act_type, name):
#ignore param act_type, set it in this function
body = mx.sym.LeakyReLU(data = data, act_type='prelu', name = name)
return body
def get_fc1... |
2c869be9943c46db5151fd240b90d157e25a1a83912a924bd2ab6a7cb5f4d4fb | Python | 5,985 | 126 | import os
from pathlib import Path
import moviepy.editor as mpy
from matplotlib import pyplot as pl, colors
from moviepy.video.io.bindings import mplfig_to_npimage
def plot_kinematics(timeindex, motion, contraction_peaks: list, relaxation_peaks: list,
file_name: Path, contraction_bases: dict = No... |
64ae90d7e2e1b6627cd64e0ef521dd84801febdfc9e0934b9fca254fe38c8b66 | Python | 5,985 | 155 | import shutil
from pathlib import Path
from unittest.mock import patch
import h5py
import holoviews as hv
import numpy as np
import pytest
from guppy.frontend.visualization_dashboard import VisualizationDashboard
from guppy.testing.api import locate_run_folder, step1, step2, step3, step4, step5
from guppy.utils.store... |
3063a75667b07c9b00ee1891ab4d3a1f6fb2978dff589318b56350792926c785 | Python | 5,989 | 155 | # -*- coding: utf-8 -*-
from collections import defaultdict
from django.http import JsonResponse
import json
from typing import Any, DefaultDict, Dict, List
from urllib.request import Request, build_opener
from urllib.error import HTTPError, URLError
from catmaid.models import Stack
# These DVID instance types are s... |
c8b80374cd0ab5068688adb884ef64c71ca0a1be11d3101353f605f553e8f102 | Python | 5,992 | 167 | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import gzip
import os
import os.path as osp
import tarfile
import tempfile
import mmcv
from mmengine.utils import mkdir_or_exist
STARE_LEN = 20
TRAINING_LEN = 10
def un_gz(src, dst):
g_file = gzip.GzipFile(src)
with open(dst, 'wb+') as f:
... |
5255d9ac471a23cc3cb1849b46014a0ed5589021248311afdd9849b8aa5c9893 | Python | 5,993 | 239 | """Built-in activation functions.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import six
import warnings
from . import backend as K
from .utils.generic_utils import deserialize_keras_object
from .engine import Layer
def softmax(x, axis=-1):
"""... |
a2c52ada7908d825f7ed4475b711cf993a35161de2783002b66ae72322592ee6 | Python | 5,993 | 194 | import os
import time
import argparse
from datasets import load_dataset
# from auditory_cortex import cache_dir
def is_not_speech_or_music(sample):
"""Returns true if 'speech' is not one of the labels."""
for label in sample['human_labels']:
if 'speech' in label.lower() or 'music' in label.lower():
return Fals... |
06fa61e8d77266820ff50d85f7a2da61e14d4c340db078bf9400e4a12187c839 | Python | 5,999 | 127 | # SPDX-License-Identifier: Apache-2.0
import argparse
import check_model
from pathlib import Path
import subprocess
import sys
import test_utils
import os
tar_ext_name = ".tar.gz"
onnx_ext_name = ".onnx"
def get_all_models():
model_list = []
for directory in ["text", "vision"]:
for root, _, files i... |
8f8eeec9bf6e2164eba9089a50f96003d3f73443101f2e03c3494e378621894a | Python | 5,999 | 180 | #!/usr/bin/env python
#
# Copyright 2008, Google Inc.
# 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
# notice, this list... |
c7c10c697d155414c92f2f8e52dd111dc5221e29c94f5b5844c6794e19625460 | Python | 6,000 | 168 | import os
from medperf import config
from medperf.account_management.account_management import get_medperf_user_data
from medperf.entities.ca import CA
from medperf.entities.event import TrainingEvent
from medperf.exceptions import (
CleanExit,
ExecutionError,
InvalidArgumentError,
MedperfException,
)
f... |
e43b685d7916f357e4298d44e7bac5d09af61906966f313e145e39289121d19d | Python | 6,000 | 185 | """Tests for create_hoc.py"""
# pylint: disable=W0212
import os
from bluepyopt.ephys.acc import ArbLabel
from bluepyopt.ephys.locations import NrnSomaDistanceCompLocation
from bluepyopt.ephys.parameterscalers import NrnSegmentSomaDistanceScaler
from bluepyopt.ephys.parameterscalers import NrnSegmentSomaDistanceStepS... |
7b89f42ecff0f6ade8dc20c117d96a02e1aa9a4624104ccdce351dee24011b05 | Python | 6,004 | 171 | from ipaddress import IPv4Address
from CybORG.Shared import Observation
from CybORG.Shared.Session import RedAbstractSession
from CybORG.Simulator.Actions import RemoteAction
from CybORG.Simulator.Actions.ConcreteActions.Portscan import Portscan
class DiscoverNetworkServices(RemoteAction):
"""
A high level R... |
c83b91e0dfac5af77de28951c647f411aa2e9b4ee0ee22f703615d4e344bab5d | Python | 6,005 | 157 | # -*- coding: utf-8 -*-
# Generated by Django 1.11.14 on 2018-07-20 14:27
import logging
from django.conf import settings
from django.core.exceptions import ImproperlyConfigured
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
from catmaid.apps import get_system_u... |
24f1175e33a9a728f09f2bd57366836e01ac0d977f3bddad489293eaabb69f4a | Python | 6,006 | 181 | #!/usr/bin/env python
#
# Compute TSNR using inputed anat.nii.gz and fmri.nii.gz files.
#
# Copyright (c) 2014 Polytechnique Montreal <www.neuro.polymtl.ca>
# License: see the file LICENSE
import sys
import os
from typing import Sequence
import numpy as np
from spinalcordtoolbox.image import Image, add_suffix, empty... |
234fea75488ed2b875428e653d3b40def75664fa6f9ea7af207abd98bbedcecb | Python | 6,011 | 173 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Plotting subroutines
"""
from nilearn import plotting
import matplotlib.pyplot as plt
from matplotlib import gridspec, cm
import numpy as np
import os
from neuromaps.datasets import fetch_atlas
surfaces = ['fsaverage', 'fsLR']
def vrange(scalars, pv=5.):
# check... |
3d221f75d68e8023790c776c2418592308a460a457c6be78922ab8b73e65172a | Python | 6,019 | 164 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import argparse
import os
import shutil
import itertools
from multiprocessing import Pool
import numpy as np
from dmriqcpy.analysis.stats import stats_mask_volume
from dmriqcpy.io.report import Report
from dmriqcpy.io.utils import (add_online_arg, add_overwrite_arg,
... |
aa25c58dd60bbbf0088a33242f2ba8b4aad8738a63bc3e3bed07ca2167a5cf15 | Python | 6,027 | 185 | # Standard library imports
import os
import random
from collections import defaultdict
from io import StringIO
from typing import Dict, List, Tuple
from pathlib import Path
from Bio import SeqIO
import sys
import math
import time
# Third-party library imports
import matplotlib.pyplot as plt
import numpy as np
import t... |
733c0c1103c73b39a949176b012ed05d21165cb9885fb86bc456e9058e08fb5e | Python | 6,028 | 180 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jun 7 09:37:11 2021
Inport and export data handler
@author: leupinv
Helper functions for working with directories and subdirectories
"""
#%% Scan directories and sub directories
import os
import mne
import time
def filter_list(list_,value):
filt... |
bbc4fc7cc99ab40686e0b7d377b4664234c4b7f4f24cbfe3c7c0b5d68107fd46 | Python | 6,033 | 170 | """
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 logging
import torch.optim as optim
from torch.nn.parallel.distributed import DistributedDataParallel
from ocpmodels.common import d... |
c474860eec75fd33df783f5a9b616eebedbb4b3393fac8478bc0182152a67299 | Python | 6,034 | 136 | import numpy as np
import tensorflow as tf
import time
import datetime
import os
import sys
import h5py
from pathlib import Path
import evidential_deep_learning as edl
from .util import normalize, gallery
class Gaussian:
def __init__(self, model, opts, dataset="", learning_rate=1e-3, tag=""):
self.loss_fu... |
9bbe1edb91371fd6d94ae67982fac522e465ca2d995b36a7d73708d568dde0ec | Python | 6,035 | 166 | """This script runs a comparison in terms of similarity on the sbml-test-suite for increaising functionality"""
import os
import pandas as pd
import datetime
from jaxkineticmodel.load_sbml.sbml_model import SBMLModel
import jax.numpy as jnp
from jaxkineticmodel.utils import get_logger
import numpy as np
import roadru... |
48dad4a97c2589e742536a7c49c4b9288732a71d3fab6e25000f02cb84283c92 | Python | 6,037 | 195 | """Testing conversion with conversion saved on datalad"""
from __future__ import annotations
from glob import glob
import os
import os.path as op
from pathlib import Path
import re
from typing import Optional
import pydicom as dcm
import pytest
from heudiconv.cli.run import main as runner
from heudiconv.parser impo... |
7c5fd28b81a86574637753be74ec30fa95cbe3d3bf760043f91caa33317b95f4 | Python | 6,037 | 136 | """Unit tests for detecting a Cloudflare bot-challenge response during download.
HMDB (and possibly other sources later) now fronts its download URL with a Cloudflare
challenge page instead of a plain 403 -- see docs at
https://developers.cloudflare.com/cloudflare-challenges/challenge-types/challenge-pages/detect-resp... |
b30b97c02419e674f73ab10bcb875af543e4c38f3fa37729a724cd3636c636a2 | Python | 6,037 | 180 | import numpy as np
import os
import random
import time
import torch
from os import path as osp
from .dist_util import master_only
from .logger import get_root_logger
def set_random_seed(seed):
"""Set random seeds."""
random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual... |
7a119c99b55c76f44712f19daab0e07863a41c7545570040b1232d6dd73e4399 | Python | 6,038 | 202 | """Shared fixtures and test extensions for worker E2E tests."""
import threading
from collections.abc import Callable
from pathlib import Path
from typing import Any, ClassVar
import ase
import ase.io
import pytest
from zndraw import ZnDraw
from zndraw_joblib.client import Category, Extension
from zndraw_joblib.sche... |
c8d1f05218a89a552af3c44a4e833dbf974ab3f2abc63a54013255137c368a62 | Python | 6,040 | 146 | import pandas as pd
import numpy as np
import math
from primo.models.simulator import Simulator
#Predicted Cas9 Activity
def get_activation_score(seq1, seq2):
"""
Given two DNA sequences of length 20,
Returns a float between 0 and 1 of the Cas9 activity between them if one were gRNA and one were the DNA se... |
304e42779165930da15efa84328438b4b2da713d43a95eecf0ed48387418f2ed | Python | 6,042 | 168 | #-*- coding: utf-8 -*-
#setting##############################################
n_jobs=16 #並列処理の数
t_n_jobs=16
PARAMETER_DIR='/Volumes/Siena/CP/parameter'
#n_jobs=40 #並列処理の数
#t_n_jobs='cuda'
#PARAMETER_DIR='/home/takeiyuuichi/Dropbox (MEG)/CP/parameter'
set_environment='main'
SET_EVENTID=[2,3]
event_id = dict(control=2... |
f38b2de39e4d6d47c0e893f033aeb8a395119dc6c51f0387853dd9a1a78121cd | Python | 6,045 | 155 | from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import os
import sys
sys.path.remove(os.path.abspath(os.path.dirname(sys.argv[0])))
import numpy as np
import torch
import torch.nn as nn
from datasets import load_dataset
from peft import LoraConfig, TaskType, get_peft_model
... |
66c97b0e0610e1979dfa60fa98dfab9c223330c0198bce4c6c5f1dbc671b4b02 | Python | 6,046 | 173 | import sys
sys.path.append("/tudelft.net/staff-bulk/ewi/insy/DBL/plent/NeuralODEs/jax_neural_odes")
sys.path.append("/home/plent/Documenten/Gitlab/NeuralODEs/jax_neural_odes")
import pandas as pd
import numpy as np
import diffrax
import jax.numpy as jnp
import jax
import optax
import argparse
jax.config.update("jax_... |
6f741dda1f556e0b002eab28ac36b627d9bc396cbb6b96fc7bef362a2a8e48ed | Python | 6,048 | 175 | #!/usr/bin/env python
"""
MetaWIBELE: prepare_domain_databases module
Extract the Pfam name for each Pfam item
Copyright (c) 2019 Harvard School of Public Health
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal... |
bbabada2b794f290632dc6cf8611cc3f4f1b46161b046d5fb62d572b3b935003 | Python | 6,048 | 177 | """E2E tests for #906 — global extension cleanup after worker disconnect.
Covers the two acceptance criteria:
1. After ``jobs.disconnect()``, ``GET /v1/joblib/rooms/@global/jobs`` no
longer includes the extension (graceful path).
2. After SIGKILL, the background sweeper removes the extension within
``worker_tim... |
0ef456677ba1e7b02ad63ff629b3af65120cf94d5eb58a3703eb0ff293c5fde9 | Python | 6,055 | 227 | """Unified state file for server registry and token storage.
Replaces separate PID files (~/.zndraw/server-{port}.pid) and
tokens.json with a single ~/.zndraw/state.json (mode 0600).
All writes use tempfile + os.rename for atomicity.
"""
from __future__ import annotations
import contextlib
import json
import loggin... |
12bf1806740645dc05a3c6d72d2f7c74127c3c838e7168cb431f0976fb713c6f | Python | 6,055 | 132 | import os
import torch
import torchvision
# from tensorboardX import SummaryWriter
import numpy as np
from PIL import Image
import shutil
import torch.nn as nn
import logging
# tensor to PIL Image
from optimizer import logger
def tensor2img(img):
img = img.cpu().float().numpy()
if img.shape[0... |
78982587d33cf8966c2856ceabffdd2e09e169fb3dd5472e8f1743d4d83aaf20 | Python | 6,055 | 166 | from ..common import ut, make_name
import h5py as h5
import numpy as np
class TestVirtualSource(ut.TestCase):
def test_full_slice(self):
dataset = h5.VirtualSource('test','test',(20,30,30))
sliced = dataset[:,:,:]
self.assertEqual(dataset.shape,sliced.shape)
# def test_full_slice_inve... |
2cb930f9ef2417fe4405a2a0dc0535828f60a661676cfd153780a98f3afd0af5 | Python | 6,056 | 175 | import torch.nn
from torch import nn as nn
import numpy as np
class ResHetEncoder(torch.nn.Module):
def __init__(self, box_size, latent_dim):
super().__init__() # call of torch.nn.Module
# self.down = nn.AvgPool2d(2,stride = 2)
self.lin1 = nn.Linear(in_features=box_size ** 2, out_feature... |
7768c56d398475b9adf3e681c467dc0cf7ae42305b58c6a1733b006c9a11c0f5 | Python | 6,058 | 186 | """FastAPI-Users configuration and exported dependencies.
This module exports the key dependencies that other packages should import:
- current_active_user: Depends() for authenticated active user
- current_superuser: Depends() for authenticated superuser
- fastapi_users: The FastAPIUsers instance for including router... |
1c4a7abc4d29af44e05d9dca03b6faaaf25f20616cb5b84dcb7347a4c25a7fd8 | Python | 6,061 | 168 | #-*- coding: utf-8 -*-
#setting##############################################
n_jobs=16 #並列処理の数
t_n_jobs=16
PARAMETER_DIR='/Volumes/Siena/CP/parameter/'
#n_jobs=40 #並列処理の数
#t_n_jobs='cuda'
#PARAMETER_DIR='/home/takeiyuuichi/Dropbox (MEG)/CP/parameter'
set_environment='main'
SET_EVENTID=[2,3]
event_id = dict(control=... |
1c563f879b9d0bde2ae93a33d2fe3fb31e5d3d6278824e7753c4922aa6be269e | Python | 6,062 | 136 | #!/usr/bin/env python2.7
import os, sys
import shlex
import argparse
import subprocess as sp
from multiprocessing import Lock, Value, Pool
from collections import defaultdict
from Utils import *
def parse_args():
description = "Cell-specific allele counting for a given list of point mutations." #which must be ... |
540a5665eaa17123c33350a8b626ccea42561a91725f23d5dc5a9f6044e8b6d6 | Python | 6,062 | 153 | # Profile settings
# Author: David Young, 2019, 2020
"""Profile settings for grid search hyperparameter tuning."""
from collections import OrderedDict
import dataclasses
from typing import Dict, List, Sequence
import numpy as np
from magmap.settings import profiles
def make_hyperparm_arr(start, stop, num_steps, nu... |
63051f9a7c7a82734855347b20279ea686661fbf08070f7961b3a9d0dbf303d7 | Python | 6,064 | 185 | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import numpy as np
import torch
import torch._C
import torch.serialization
from mmengine import Config
from mmengine.runner import load_checkpoint
from torch import nn
from mmseg.models import build_segmentor
torch.manual_seed(3)
def digit_version(ver... |
1e683f111af17731b48caff4d820a2a33469b7fd7244a8fd0c49b6d559acc0de | Python | 6,073 | 156 | #!/usr/bin/env python
"""
MetaWIBELE: combine_abundance_annotation module
Combine abundance details to specific features
Copyright (c) 2019 Harvard School of Public Health
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software")... |
1ee55896063fb5866d60704d98416def7fc8cd13ff80e8033e332345ea91fbfc | Python | 6,075 | 186 | '''
Demo for creating customized multi-class objective function
===========================================================
This demo is only applicable after (excluding) XGBoost 1.0.0, as before this version
XGBoost returns transformed prediction for multi-class objective function. More details
in comments.
See :do... |
41ec61dd2a4e72a529c6dc4a921a9f6aee94a526e005738d597d4721bbc6152b | Python | 6,076 | 157 | import tensorflow.keras as keras
import tensorflow as tf
import numpy as np
import time
from utils.utils import save_logs
from utils.utils import calculate_metrics
from utils.utils import save_test_duration
class Classifier_INCEPTION:
def __init__(self, output_directory, input_shape, nb_classes, verbose=False, ... |
81708aa8d44390e0566a9378ffd83dc5ef88b71cb0fef961c6233a95dc0342cb | Python | 6,076 | 181 | import argparse
import glob
import math
import os
import os.path as osp
import mmcv
import numpy as np
from mmengine.utils import ProgressBar, mkdir_or_exist
def parse_args():
parser = argparse.ArgumentParser(
description='Convert GID dataset to mmsegmentation format')
parser.add_argument('dataset_im... |
8b1d82bf323ce6819a7a998e279c17caf2fe606a51a82c494df0f0b0978807ff | Python | 6,083 | 164 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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://w... |
d6eac22135c7a75767b8cf850a9ede163f8d025e7224803efa74d51988fd92f5 | Python | 6,084 | 134 | import shutil
from pathlib import Path
import numpy as np
import pandas as pd
import pytest
from guppy.analysis.io_utils import read_hdf5
from guppy.analysis.standard_io import read_binned_metrics_from_hdf5
from guppy.testing.api import step1, step2, step3, step4
from guppy.utils.utils import parse_run_name
from gupp... |
c44e4fb659f50d9db4fc6422312e8ec2303245020c28354efb911d5a0fab8e0e | Python | 6,085 | 157 | import torch
import numpy as np
from data import gen_data
import os
import deepxde as dde
from modelGc import FourierDeepONet as Gc
from modelGp import FourierDeepONet as Gp
# ensure that the device is set to GPU or CPU
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
# load pretrained neural oper... |
e4a50395ddfa7ac1b0daf0636a2f95927a6756e22e9c6570f0d7caa6058a47c8 | Python | 6,086 | 187 | # -*- encoding: utf-8 -*-
'''
Copyright 2022 The International Digital Economy Academy (IDEA). CCNL team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.o... |
5830650fde536c0be35dbdc48fec0250fa3f3d50eb25ef314d83bdd8073bc406 | Python | 6,087 | 187 | ##
## CPCantalapiedra 2020
# This is an adaptation of ete3 NCBITaxa module
# to embed it directly within eggnog-mapper
import os
import pickle
import sqlite3
from ...emapperException import EmapperException
from ...common import get_ncbitaxadb_file
ncbi = None
def get_ncbi(usemem = False, dbfile = None):
globa... |
b45989d0234970a9fd0de428fd5fe2e32cf2bf6856eec981da5ac9bb843a1dfd | Python | 6,088 | 139 | import numpy as np
import tensorflow as tf
import tensorflow_probability as tfp
import time
import datetime
import os
import sys
import h5py
from pathlib import Path
import evidential_deep_learning as edl
from .util import normalize, gallery
class BBBP:
def __init__(self, model, opts, dataset="", learning_rate=1e... |
2a8b0199d12d25d0020b5d2fca6ac7918998b3d0ed2985ab53bbcb7c95ea8159 | Python | 6,090 | 140 | #!/usr/bin/env python
#
# Copyright 2017, Daehwan Kim <infphilo@gmail.com>
#
# This file is part of HISAT-genotype.
#
# HISAT-genotype 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 Li... |
e11527b644b4f2ef45229ad2f5cb0f5a2c26fdc05bffa3369e876c8559862337 | Python | 6,090 | 159 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
# pyre-strict
import logging
import os
from typing import Any, Callable, Dict, IO, List, Union
import yaml
from iopath.common.file_io import g_pathmgr
from yacs.config import CfgNode as _CfgNode
BASE_KEY = "_BASE_"
class CfgNode(_CfgNode):
... |
3ace844af67795ca16aa6a6eb3d469881e3644a96118bc9c42884f24fd67b71e | Python | 6,094 | 167 | from dataclasses import dataclass, field
import os
import json
import logging
from argparse import Namespace
from typing import List, Literal, Optional, Union
from pydantic import AnyHttpUrl, BaseSettings, HttpUrl, validator, BaseModel
CURRENT_DIR_PATH = os.path.dirname(os.path.abspath(__file__))
# request body
# 使用... |
79022578e9c3336ce342c6e9555513bab95196140604cd6b0b4458d1adcf2765 | Python | 6,095 | 162 | import mne
import sys, os
from tqdm import tqdm
from glob import glob
import numpy as np
import itertools
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
# go to base directory and import globals
base_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
#ptmp_dir = "/ptmp/kroma/... |
42fe9cad59aad703e6f1d64375401d65a7f5faf401db3db7413ace1ac59c53b5 | Python | 6,099 | 223 | #!/usr/bin/env python3
"""
Create blinded time-series and power-spectrum PNGs for CICADA IC review cases.
This script works ONLY from the already-blinded Review_###_timeseries.txt files.
It does not read the unblinding key and therefore does not expose subject,
task, consensus label, historical CICADA label, or 11-mm ... |
49e5f89f71e47041a7284a41bafd18b63d508e240d75cd17bb19b76aa67f06b6 | Python | 6,101 | 161 | """
Parallel-specific integration tests for GuPPy.
These tests exercise the multiprocessing code paths (Step 2 and Step 4) with
``number_of_cores=2``. They are kept separate from the main test suite so that
the main suite can run under pytest-xdist (``-n auto``) without interference
from nested worker pools. Run these... |
4a0fc8def6ec00dffbdb744b6f5b0e0184bd3cb69d247b3a7a1c67829068db02 | Python | 6,103 | 196 | #!/usr/bin/env python3
"""
Rica Local Server - Serves tedana output for Rica visualization
Usage:
python rica_server.py [--port PORT] [--no-open]
Options:
--port PORT Port to serve on (default: 8000)
--no-open Don't auto-open browser
Place this script in your tedana output folder and run it to vi... |
a8f7b62bfba1f5d1fa10e704a83f62f42d3bba9e4ac5a210046e3c0b53bb4d18 | Python | 6,104 | 194 | import torch
import torch.nn.functional as F
from torch import nn
from torch.nn.parameter import Parameter
class var_norm(nn.Module):
def __init__(self, num_features, eps=1e-3):
super().__init__()
self.num_features = num_features
self.running_var = Parameter(torch.ones(num_features), requ... |
2d67a0f4eac615454cddd6f3e05a86e80331ffa01c9261a3b5c9a44f6a24a679 | Python | 6,106 | 185 | # Code adapted from https://github.com/Sage-Bionetworks-Challenges/brats-dream-challenge-infra/blob/main/Docker/score.py
from pathlib import Path
from typing import Dict, Union
import re
import yaml
import os
import subprocess
from loguru import logger
import numpy as np
import pandas as pd
from sklearn.metrics impor... |
a4f09f4bfbca0bad07e184f5fe6e935515939f6d0d854ce149298c9a93d623f2 | Python | 6,109 | 168 | from typing import Union
import numpy as np
from scipy.io.matlab import mio5_params # For mat_struct
from abc import ABC, abstractmethod
NEURAL_DATASETS_REGISTRY = {}
def register_dataset(name: str):
"""
Decorator to register a neural dataset class.
Args:
name (str): name of the dataset to... |
10ac44e93029b68321556a711f1746c609373e3ecc4bd1b31a7d535e34123e4c | Python | 6,111 | 121 | # pytest unit tests for sct_compute_ascor
import pytest
import logging
import csv
from spinalcordtoolbox.image import Image
from spinalcordtoolbox.scripts import sct_compute_ascor, sct_crop_image, sct_deepseg, sct_label_utils
from spinalcordtoolbox.utils.sys import sct_test_path
logger = logging.getLogger(__name__)
... |
0b3f9296140948d8d10de4fbbabdfa7274b5697eb682c74fee70b8eb660abba6 | Python | 6,112 | 163 | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List, Tuple
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmengine.model import BaseModule
try:
from mmdet.models.dense_heads import \
Mask2FormerHead as MMDET_Mask2FormerHead
except ModuleNotFoundError:
MMDET... |
5b87e0fd1e2029e05eb8f027d04b2482f8a4eb6cbb1941d55db848329dc492e5 | Python | 6,112 | 177 | # -*- coding: utf-8 -*-
import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.model_selection import cross_val_score
from sklearn.preprocessing import MinMaxScaler
from sklearn.ensemble import RandomForestClassifier
from sklearn.naive_bayes import GaussianNB
from skle... |
bb01a7382491b774d4f3b04d6f05596f714dfc6c9b04f5555fa066da77ea9bd7 | Python | 6,115 | 213 | #!/usr/bin/env python
# coding=utf-8
# Copyright 2023 Statistics and Machine Learning Research Group at HKUST. All rights reserved.
"""A simple shell chatbot implemented with lmflow APIs.
"""
import logging
import json
import os
import sys
sys.path.remove(os.path.abspath(os.path.dirname(sys.argv[0])))
import torch
impo... |
ff573d14b7a0faf60459c107ae08085d809c82be6ed030cdd8e4b92ef24ea5fa | Python | 6,117 | 144 |
import os,sys
import torch
import argparse
import warnings
import numpy as np
import pandas as pd
sys.path.append("/home/xuchang/Project/STMAP/SEDR/SEDR-master")
from src.graph_func import graph_construction
from src.utils_func import mk_dir, adata_preprocess, load_ST_file
import anndata
from src.SEDR_train... |
1a9cba52fcb3095d3e85bec5ede4d432980546856ada42fc49ba83dbe202650d | Python | 6,119 | 192 | #
# calculation of synthetic accessibility score as described in:
#
# Estimation of Synthetic Accessibility Score of Drug-like Molecules based on Molecular Complexity and Fragment Contributions
# Peter Ertl and Ansgar Schuffenhauer
# Journal of Cheminformatics 1:8 (2009)
# http://www.jcheminf.com/content/1/1/8
#
# seve... |
3f24ac6cdb61a74946351b773f2f63750d0a40019c46c1d3ab3e75989ce1ed4f | Python | 6,119 | 181 | from collections import defaultdict
import json
import logging
import select
import signal
import time
from typing import Dict, List, Set
from django.conf import settings
from django.core.management.base import BaseCommand
from django.db import connection
from catmaid.control.edge import get_intersected_grid_cells
f... |
c68d7cc24e827677f3c30ed023236235bae73cda2083dc45998eefe38880773e | Python | 6,120 | 166 | import pytest
import numpy as np
from keras import initializers
from keras import backend as K
# 2D tensor test fixture
FC_SHAPE = (200, 100)
# 4D convolution in th order. This shape has the same effective shape as FC_SHAPE
CONV_SHAPE = (25, 25, 20, 20)
def _runner(init, shape, target_mean=None, target_std=None,
... |
99187fd700351cb8ddd55850e4d1b17bf97b888be17aed4f245d26ea172c9b80 | Python | 6,122 | 99 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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://w... |
3dfabf1ef51a47237283965fc47cde299086b4d2d3277dee8d1fba2ec5d97daa | Python | 6,123 | 189 | """Tests for frame selection REST API endpoints."""
import json
import pytest
from helpers import MockSioServer, auth_header, create_test_room, create_test_user_in_db
from httpx import AsyncClient
from sqlalchemy.ext.asyncio import AsyncSession
# ======================================================================... |
29e145b10913ceabc62f101c9a4c36cb9bd99e1f3e12d3d28a2749954978798b | Python | 6,125 | 177 | """
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 torch
from torch_geometric.nn import SchNet
from torch_scatter import scatter
from ocpmodels.common.registry import registry
from ocp... |
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