sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
4b02725744a4578260621f251a96289116647761f03f505dc091f1f97a8d1f5e | Python | 20,466 | 516 | import torch
import os
import numpy as np
import dgl
import logging
import datetime
import math
import sys
import gc
import networkx as nx
import igraph as ig
from igraph import Graph
import time
import csv
import warnings
import pandas as pd
import itertools
from collections import OrderedDict
from torch.utils.data im... |
203c647b8cbfcc6e7622b88b30b09fc1d68df772d63454cdca7f988a7581eeb8 | Python | 20,467 | 664 | """Location classes"""
"""
Copyright (c) 2016-2020, EPFL/Blue Brain Project
This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
This library is free software; you can redistribute it and/or modify it under
the terms of the GNU Lesser General Public License version 3.0 as published
by the Free... |
bcddf7b58ec6a5e77bd8e09f91aecac18e54f60455d474c7c3db6398d492fa66 | Python | 20,482 | 524 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat May 13 11:30:53 2023
@author: schwab
"""
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import Dataset, DataLoader
from torchvision import utils, models
import torch.nn.functional as F
import torchvision.transform... |
15b5560c7e422fd3a09e5e1d88a9565c503aa9b1cd2fada25d43db2124e47da6 | Python | 20,486 | 768 | """Utilities for backend functionality checks."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import scipy.signal as signal
import scipy as sp
from .common import floatx
from keras.utils.generic_utils import transpose_shape
from keras.... |
b33cc2aba5df3068bbc3840b63c0ccde6984d16cd11ce891ce150c3251696d68 | Python | 20,501 | 689 | # Copyright DST Group. Licensed under the MIT license.
import enum
class TernaryEnum(enum.Enum):
TRUE = enum.auto()
UNKNOWN = enum.auto()
FALSE = enum.auto()
IN_PROGRESS = enum.auto()
@classmethod
def parse_bool(cls, state_bool):
if isinstance(state_bool, bool):
if state_b... |
e553db4f36ab4691d4a09de0cef78e111167647ebe2592da4e5c391a7291dd57 | Python | 20,516 | 511 | # MCNN model
import tensorflow.keras as keras
import tensorflow as tf
import numpy as np
import time
from utils.utils import calculate_metrics
from utils.utils import create_directory
class Classifier_MCNN:
def __init__(self, output_directory, verbose, build=True):
self.output_directory = output_directo... |
81f2ad87cb39d6c5bbb2d72c384e7596260f066ba7bd28ac076c3d6c82fc0d89 | Python | 20,523 | 545 | import bisect
import copy
import functools
import glob
import logging
import os
import warnings
from abc import ABC, abstractmethod
from pathlib import Path
from typing import List
import ase
import numpy as np
from torch import tensor
from torch.utils.data import Dataset
from tqdm import tqdm
from ocpmodels.common.r... |
fba9a62e220fa030cccc39d624a13aa05851f61d0251676d0a69650f03f7c939 | Python | 20,531 | 503 | """Single and multi-threaded executors."""
import datetime
import functools
import logging
import math
import os
import sys
import threading
from abc import ABCMeta, abstractmethod
from collections.abc import Iterable, MutableSequence
from threading import Lock
from typing import Optional, cast
import psutil
from cwl... |
a60fb1e3bce1a8a0899a15d5295eaca5f8b36b3fa209a608a1ec15c53db723fb | Python | 20,539 | 511 | from PyQt5 import QtGui, QtWidgets, QtCore
import pyqtgraph as pg
from copy import deepcopy
# Feature interface
class Feature(QtWidgets.QWidget):
def __init__(self, name, data, parent=None, liveplot=None, display_name_label=True):
if parent is not None and isinstance(parent, QtWidgets.QStackedWidget):
... |
577494c203086cb943ecf02607bdb3066fb905df2a70a18f5259e6ab32ff4081 | Python | 20,546 | 442 | from global_setting import *
from scipy.ndimage import gaussian_filter
import tensorflow as tf
from sklearn.model_selection import train_test_split
from scipy.stats import norm
from scipy.stats import multivariate_normal
from sklearn.covariance import ledoit_wolf
import copy
import matplotlib.pyplot as plt
from scipy.o... |
863d540e12824908152e1f390c10c04d7b5ec4a0af69988a1341304ee3826ed3 | Python | 20,560 | 550 | # -*- coding: utf-8 -*-
# General Django settings for mysite project.
import os
import sys
import django.conf.global_settings as DEFAULT_SETTINGS
import logging
import mysite.pipelinefiles as pipelinefiles
import mysite.utils as utils
from celery.schedules import crontab
try:
import psycopg2
except ImportError:
... |
a670954aa828fdabf89cf32df761294983a63d6327d68b2590241b25c713c7e0 | Python | 20,569 | 587 | import yaml
import os
import pickle
from copy import deepcopy
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import torch
import datetime
import time
import networkx as nx
import matplotlib.pyplot as plt
# from matplotlib.offsetbox import OffsetImage, AnnotationBbox
import matplotlib.image as m... |
e2563cb148d5373b24c6e7eb79e7d79d5f3fe42b41b98629c4985aca32f71789 | Python | 20,571 | 549 | # /// script
# requires-python = ">=3.10"
# dependencies = [
# "matplotlib",
# "numpy",
# ]
# ///
"""Generate SVG figures for the z-score normalisation explanation page.
The dF/F formula and z-score formulas mirror src/guppy/analysis/z_score.py:
deltaFF: (signal - control_fit) / control_fit... |
4ad1e51c5610d2e6e92ec6a364770309dff0130468f4e571ed2e84b14861bd61 | Python | 20,574 | 477 |
from sklearn.linear_model import Ridge
from sklearn.metrics import r2_score
import pandas as pd
import numpy as np
from tqdm import tqdm
'''
Predict total brain volume (change) on the basis of either
- time between visits
- time between visits + demographics (age, sex, etc)
- time between visits + baselin... |
80fffa729166723d81ee512224937af2463fd30532f4f0e3c5a8b35e89af138a | Python | 20,576 | 634 | """
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.
---
This code borrows heavily from the DimeNet implementation as part of
pytorch-geometric: https://github.com/rusty1s/pytorch_geometric. Licens... |
30e3d492c22ac173455b096afaa2cf5a39c9099a6d50e8936234c82e3df2c41b | Python | 20,578 | 486 | import shutil
import types
from pathlib import Path
import pytest
import guppy.testing.api as testing_api
from guppy.orchestration.store_labeling import (
build_store_labeling_template,
read_header,
)
from guppy_test_data import STUBBED_TESTING_DATA
class FakeTemplate:
def __init__(self, *, hooks=None, ... |
6c03b5dd49737258718b543dc4973f2983085842b189aff83467171f47f7dab9 | Python | 20,581 | 491 | """
Functions for plotting mRS distributions as horizontal bars.
"""
import numpy as np
import matplotlib.pyplot as plt
# ---------------------------------------------------------------------
# ---------------------------------------------------------------------
# ---------------------------------------------------... |
399571d6f2e72c855005a282f33df1b63455a56a9c967f36807990f154438908 | Python | 20,600 | 1,119 | """
CGCNN-like embeddings using continuous values instead of original k-hot.
Properties:
Group number
Period number
Electronegativity
Covalent radius
Valence electrons
First ionization energy
Electron affinity
Block
Atomic Volume
NaN stored for unavaialable parameters... |
a490c4d0e0fc71dc73ec507d1750d04d4a57bded9fbbab73d94bb61351be5316 | Python | 20,610 | 495 | # Thomas Lavigne
# 18-09-2024
#
#------------------------------------------------------------#
# Libraries #
#------------------------------------------------------------#
#
try:
from porous_fenicsx import constitutive_laws, variational_forms, functions
except:
print("Please run ... |
0edf80c348c4e9ff08a003fab57cd782f31eda48657b696fd34b83126fdd78bd | Python | 20,620 | 627 | """Ecode module."""
# Copyright (c) 2022 EPFL-BBP, All rights reserved.
#
# THIS SOFTWARE IS PROVIDED BY THE BLUE BRAIN PROJECT ``AS IS''
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
# THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVEN... |
220a386583854b983d439e7d085bcc7d6d7d27e6854ff2982e3fa4244335b02b | Python | 20,624 | 576 | # -*- coding: utf-8 -*-
import ujson
from typing import Dict
from django.db import connection
from catmaid.error import ClientError
from catmaid.control.authentication import requires_user_role
from catmaid.models import UserRole
from rest_framework.decorators import APIView, api_view
from rest_framework.request imp... |
6ca4432fa3f8dc8a825a3e0dbf07c8942d90d7357fcfc2d907b57fa35886acc2 | Python | 20,631 | 543 | # -*- coding: utf-8 -*-
# encodermap/kondata.py
################################################################################
# EncoderMap: A python library for dimensionality reduction.
#
# Copyright 2019-2024 University of Konstanz and the Authors
#
# Authors:
# Kevin Sawade
#
# Encodermap is free software: you ca... |
34083768ac8456d8081fd5dc90b2fbc013b1cabb92f63c108d43c533985470a3 | Python | 20,634 | 474 | import numpy as np
import torch
import random
from torch_geometric.data import Data
from torch_geometric.loader import DataLoader
def discount_cumsum(x, gamma):
discount_cumsum = np.zeros_like(x)
discount_cumsum[-1] = x[-1]
for t in reversed(range(x.shape[0]-1)):
discount_cumsum[t] = x[t] + gamma ... |
334b38d829f091c78b977c052c64972a6fcbad0bd4d8906c774be592776aadeb | Python | 20,635 | 566 | import gzip
import json
import typing
import ijson
from itertools import chain
from typing import Dict, Tuple, Generator, Optional, Any, List
from kgx.source.json_source import JsonSource
from kgx.config import get_logger
log = get_logger()
class TrapiSource(JsonSource):
"""
TrapiSource is responsible for r... |
25bc4ddc7c9d828a1f79e4d895d3c0e34353498dc6626fe472ec2489e5d1fca2 | Python | 20,636 | 752 | import struct
from openbabel import openbabel
import pandas as pd
from openbabel import pybel
from Bio.SeqUtils import seq1
from biopandas.pdb import PandasPdb
# saves info about specific atom type
class Info:
def __init__(
self,
sm,
smina_name,
adname,
anum,
ad_rad... |
753f4e5c7232ed61d129e27a2ddfcb89023ed84c0e83cb6ff3f832b71dcc6317 | Python | 20,649 | 625 | import numpy as np
import multiprocessing
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
from matplotlib.offsetbox import OffsetImage, AnnotationBbox
from matplotlib.colors import LinearSegmentedColormap
from matplotlib import animation
from PIL import Image, ImageOps
from scripts imp... |
16d1c2300fe0e747e151fbc86212a1ab128177871a7da7389c713cdc409bb07e | Python | 20,671 | 460 | # 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... |
3fe204c2dbe87ffece75e707e554031ca9c4b594c0143860ca311ed4c5251127 | Python | 20,702 | 518 | import torch
import os
import numpy as np
import dgl
import logging
import datetime
import math
import sys
import gc
import networkx as nx
import igraph as ig
from igraph import Graph
import time
import csv
import warnings
import pandas as pd
import itertools
from collections import OrderedDict
from torch.utils.data im... |
69f0ab8890cdd622a5603aaf6a0a644c4126f887a446cc629acb0e4da5e45222 | Python | 20,704 | 529 | # Thomas Lavigne
# 02-08-2024
#
# From https://doi.org/10.1016/j.jmbbm.2023.105902
# Terzaghi Problem
#
# Boundary conditions:
# p=0
# --------
# | |
# | |
# | |
# | |
# | |
# | |
# ux=0| |ux=0
# | |
# | |
# | |
# | |
# | |
# |... |
51b4e3bb64f181592280f8b3855b7f393f15d0fcf0863d03269741250f29ad8d | Python | 20,706 | 683 | import shutil
from abc import ABC, abstractmethod
import re
from collections import defaultdict
import nibabel as nib
import scipy.ndimage
import nilearn.image
import nilearn.masking
import nilearn.regions
import numpy as np
from pyalfe.interfaces.c3d import C3D
class ImageProcessor(ABC):
"""
Abstract class... |
e4c86de5d1aeb1298c53f583faef6109a2f931e8d660a0084b516eba7c42bc97 | Python | 20,710 | 391 | import os
import tqdm
import torch
import torch.nn as nn
import numpy as np
import argparse
import json
import cv2
import scipy.io as sio
import pandas as pd
import time
from scipy.interpolate import interp1d
from skimage import io
from nns.model import ISOSNet
from utils import fix_random_seeds
from data.datasets impo... |
c555109e2f3e33a1cb5c0b16450cfaba360b0ece605fd89fe7cfa470a3dd22db | Python | 20,726 | 613 | """Functions to create neuroml biophysiology"""
"""
Copyright (c) 2016-2022, EPFL/Blue Brain Project
This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
This library is free software; you can redistribute it and/or modify it under
the terms of the GNU Lesser General Public License version 3.0 as... |
efe811f024aaea7873d1d744ad67dd3299c5ecdef045c372d184b3b1921c5c40 | Python | 20,727 | 524 | """NWB recording extractor for GuPPy fiber photometry pipeline."""
import logging
from pathlib import Path
from typing import Any
import numpy as np
from hdmf.common import DynamicTable
from pynwb import NWBHDF5IO, NWBFile
from guppy.extractors.base_recording_extractor import BaseRecordingExtractor
from guppy.utils.... |
f9430890040afe5e731fb0906319653c3a90de73f3714d05f581d6e1216b6da5 | Python | 20,737 | 428 | #!/usr/bin/env python
#
# Extract metrics within spinal labels as defined by the white matter atlas and the template
# The folder atlas should have a .txt file that lists all tract files with labels.
#
# Copyright (c) 2014 Polytechnique Montreal <www.neuro.polymtl.ca>
# License: see the file LICENSE
# TODO: fetch vert... |
20f0db72869bb052b064c02d8e345c42910f1684bd1b0653affe9172d15c3733 | Python | 20,741 | 565 | import os
import argparse
import pickle
import math
import random
import numpy as np
import pandas as pd
import torch
import torch.nn as nn
import torch.nn.functional as F
import scipy.stats
from Bio.PDB.Polypeptide import one_to_index
def seed_all(seed):
torch.backends.cudnn.deterministic = True
torch.manual... |
c421f0fd26158378c47561effb6f62b7dda98b02e6cd7491aed8cd0641be763e | Python | 20,744 | 468 | import json
from pathlib import Path
import h5py
import numpy as np
import pandas as pd
import pytest
from guppy.orchestration.psth import (
_validate_events_overlap_signal,
_validate_psth_window_parameters,
execute_compute_cross_correlation,
execute_compute_psth,
execute_compute_psth_peak_and_are... |
40cf4d848b495161d8936e132899ef029fe8b0d35d2f9667575516e663053d4f | Python | 20,779 | 454 | import numpy as np
import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms
from fig_utils import *
import os
import seaborn as sns
from matplotlib import gridspec
def panela_experiment(fig, grid, dat, il, transl):
ax = plt.subplot(grid[0, 0])
ax.axis('off')
il = plot_label(ltr, il, ax, ... |
d71c7c84cf9f8e059b4406e8bd8d40eebfef43e38158ccd307569e2b6a27179e | Python | 20,793 | 577 | """
System related utilities
Copyright (c) 2020 Polytechnique Montreal <www.neuro.polymtl.ca>
License: see the file LICENSE
"""
import io
import sys
import os
import shutil
import logging
import subprocess
import shlex
import smtplib
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
... |
4859f8f1fb8faab27eabb5f1b4f2b1663e5d0cf0e5e8dbad7c723afe1ddd1249 | Python | 20,794 | 487 | """Panel page for defining tonic/basal analysis epoch windows.
Tonic analysis averages the preprocessed z-score / dF/F trace over user-defined
absolute-time windows. Because injection timing can differ per recording site
(e.g. an ICV injection reaches sites at different times), windows are defined
per recording site. ... |
00dc2069fd93549c2e52e3fc31184a90cbabf985397974d4692e45068e0b5bdd | Python | 20,804 | 539 | """Open one DANDI NWB asset and report what it holds.
Where :mod:`guppy.utils.dandi_filter` answers yes or no, this reads the detail the source panel
shows before a file is chosen: the channels of each fiber photometry response series, the brain
region, indicator and wavelengths behind each one, the store names Step 1... |
458133bdd328c9a019f771fc16a829b155425ae369fb00f5959ad50245a3a9b6 | Python | 20,805 | 465 | import numpy as np
import random
import cv2
import torch
from typing import Dict
from PIL import Image
from scipy.ndimage import gaussian_filter1d
from torchvision.transforms import v2
from torchvision.transforms import functional as F
def smooth_cone(cone_label, sigma, scale):
cone_label = np.clip(gaussian_filte... |
f481dbca1f4880554e5be7cd7aa771bda87d4cd25a4df7879ccf569dfcb3d8b7 | Python | 20,812 | 574 | """Shared input-validation helpers for the GuPPy pipeline.
This module is the canonical home for reusable validation logic that several
layers of the pipeline (frontend, orchestration, analysis) need. Validation
that is genuinely one-off — i.e. coupled to a specific extractor or step —
should stay where it is used; on... |
2c0aff950639973885633c4936897f687f60476d63c18cca46c7088af2749ef2 | Python | 20,825 | 469 | import torch
import torch.nn as nn
import torch.nn.functional as F
import sys, os, json
import argparse
import time
import numpy as np
from tqdm import trange
from torchvision import datasets, transforms
import matplotlib.pyplot as plt
import csv
from PIL import Image
from Adversarial_Observation.Swarm import PSO as... |
16fc998904fa5f6385aa3b9ce1b788b632950acf90a5a2f1e09c469af4fe4343 | Python | 20,826 | 469 | import torch
import torch.nn as nn
import torch.nn.functional as F
import sys, os, json
import argparse
import time
import numpy as np
from tqdm import trange
from torchvision import datasets, transforms
import matplotlib.pyplot as plt
import csv
from PIL import Image
from Adversarial_Observation.Swarm import PSO as... |
f5f86e02212da5058311a2b984110e682ddcf1ce80919b4d0c502457da6c6f99 | Python | 20,855 | 471 | import torch
import torch.nn as nn
import torch.nn.functional as F
import math
import copy
import numpy as np
from utils import int2onehot
from utils import get_enc_len, split_and_batchify_graph_feats, batch_convert_len_to_mask
from embedding import OrthogonalEmbedding, NormalEmbedding, EquivariantEmbedding
from filter... |
3a35096f07694b3dc70dcb56398658f41af16ab724d5ab8d61515916ee081ffc | Python | 20,856 | 483 | import json
import os
import duckdb
import pytest
from src.exporters.duckdb_exporters import (
_metadata_subject_filename,
export_compendia_to_parquet,
export_conflation_to_parquet,
export_intermediates_to_parquet,
log_duckdb_settings_on_error,
)
from tests.conftest import CONFLATION_FIXTURE_ROWS
... |
48923195b3afa86f31bf65161045ca23baa34b42648598dcafb7ce28e33441b0 | Python | 20,906 | 536 | # Thomas Lavigne
# 02-08-2024
#
# From https://doi.org/10.1016/j.jmbbm.2023.105902
# Terzaghi Problem
#
# Boundary conditions:
# p=0
# --------
# | |
# | |
# | |
# | |
# | |
# | |
# ux=0| |ux=0
# | |
# | |
# | |
# | |
# | |
# |... |
a65b3260aced8120a700127ec2193968ac3f040de8c3cb8571b72c137602e468 | Python | 20,945 | 527 | import csv
from pyhealth.datasets import MIMIC3Dataset, MIMIC4Dataset
from graphcare_.task_fn import drug_recommendation_fn, drug_recommendation_mimic4_fn, mortality_prediction_mimic3_fn, readmission_prediction_mimic3_fn, length_of_stay_prediction_mimic3_fn, length_of_stay_prediction_mimic4_fn, mortality_prediction_mim... |
752bd162c9f7b470af34db5ecdedb9836b24d0cd52806d62a10ca89e03633a67 | Python | 20,982 | 759 | import struct
from openbabel import openbabel
import pandas as pd
from openbabel import pybel
from Bio.SeqUtils import seq1
from biopandas.pdb import PandasPdb
# saves info about specific atom type
class Info:
def __init__(
self,
sm,
smina_name,
adname,
anum,
ad_rad... |
d665373f18f4a998c92a0b8b98ba09f0434838a7d1b668b5c44254e40cb6d4e4 | Python | 20,999 | 467 | # -*- coding: utf-8 -*-
import json
import logging
import sys
import networkx as nx
from networkx.algorithms import weakly_connected_components
from collections import defaultdict
from functools import partial
from itertools import chain
from math import sqrt
from numpy import subtract
from numpy.linalg import norm
... |
f4894518d16cfa2a0d7bb62c5c156b9193188b46316a0503fe796cedfb485755 | Python | 21,005 | 687 | # This file is part of h5py, a Python interface to the HDF5 library.
#
# http://www.h5py.org
#
# Copyright 2008-2013 Andrew Collette and contributors
#
# License: Standard 3-clause BSD; see "license.txt" for full license terms
# and contributor agreement.
"""
Tests the h5py.Dataset.__getitem__ method.
... |
1eae6a062179aba125dce81f87203640827b70cf68eac8c136b4ccc0753d248f | Python | 21,013 | 449 | # 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... |
9ef148e7081679b8ab4d4dc5733ed889086341e82a099c27a187b3305ff1ec7a | Python | 21,064 | 553 | import logging
import os.path
import glob
from medutils.mri import mriForwardOp, mriAdjointOp
import numpy as np
import json
import argparse
import yaml
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import h5py
import copy
from skimage.morphology import erosion, dilation
from mr_utils.motion_tra... |
a6d385a5c39592bcc85af926c01d8e904cf9bfe7e68b78d3a69b54a8994882f6 | Python | 21,100 | 475 | import torch
import torch.nn as nn
import torch.nn.functional as F
import math
import copy
import numpy as np
from utils import int2onehot
from utils import get_enc_len, split_and_batchify_graph_feats, batch_convert_len_to_mask
from embedding import OrthogonalEmbedding, NormalEmbedding, EquivariantEmbedding
from filter... |
c9b28807fc377cd79d0db72e1b73c5df573152fdee79baa4217a1ec6393aa4fc | Python | 21,108 | 476 | import SimpleITK as sitk
import pandas as pd
import numpy as np
import os
import sys
import shutil
import subprocess
import platform
# We use the multiprocess package instead of the official
# multiprocessing as it currently has several issues as discussed
# on the software carpentry page: https://hpc-carpentry.github... |
5f10b97491ce20f151f8cc93f1a2f4fd710a4588133f5f2cf85a824e8df12a34 | Python | 21,115 | 427 | import catmaid.fields
import django.contrib.postgres.functions
from django.db import migrations
class Migration(migrations.Migration):
"""Update the default values for most timestamp fields so that the
database's transaction start time is used (CURRENT_TIMESTAMP or now()). This
doesn't include any actual ... |
c1286a2990f0714a34579cebf40832358852647480a2ef9fef9369bdfb315719 | Python | 21,124 | 506 | import matplotlib.pyplot as plt
import numpy
from importlib import reload
import sys
import os
import importlib
import types
# print(sys.modules.keys())
import multiprocessing
import multiprocessing.pool
original_packs = sys.modules.copy()
#import currents_visualization
import math
from neuron import h
import neuron
... |
0a2e79bc1a0f091611d09b76f7654417b8c62242bbdd188e4774c0f3688d2284 | Python | 21,137 | 540 | from inspect import stack
from itertools import count
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import re
from RiboGraphViz import RGV
from RiboGraphViz import LoopExtruder, StackExtruder
from draw_rna.ipynb_draw import draw_struct
from nnn import util
##### Helper Functions #####
def sor... |
9510c942e7b62cb60c7fd5e33f6b2348cece216fad861b5ff11f8489ac034098 | Python | 21,215 | 447 | # load Modules
from PyQt5 import QtGui, QtWidgets, QtCore
import pyqtgraph as pg
import numpy as np
import math
from scipy.signal import firwin, lfilter, lfilter_zi, hilbert, correlate
from util.functions import movingAverage
from features.Feature import Feature
from util.conf import cc_train_params, cc_amplitude_para... |
4937e8464d908e784a959d66682417e72395641dc7e0863b1211027d77022ee3 | Python | 21,236 | 722 | import numpy as np
import pathlib as pl
from myphdlib.interface.factory import SessionFactory
from scipy.optimize import curve_fit as fitCurve
import h5py
def convertGratingMotionToSaccadeDirection(
gratingMotion=-1,
referenceEye='left'
):
"""
"""
saccadeDirection = None
if referenceEye ==... |
17ebdf5e113a9ce3f478e34e99370bdce11f2b02cb7f1f7cbdd71008f817996f | Python | 21,257 | 505 | import matplotlib.pyplot as plt
import numpy
from importlib import reload
import sys
import os
import importlib
import types
# print(sys.modules.keys())
import multiprocessing
import multiprocessing.pool
original_packs = sys.modules.copy()
#import currents_visualization
import math
from neuron import h
import neuron
... |
1a44a4b4f282247482d57a9d7a9fdb4b8a1e222a5699192bd13caf5c2b5acedc | Python | 21,266 | 538 | ###########################################################################################
# Training script
# Authors: Ilyes Batatia, Gregor Simm, David Kovacs
# This program is distributed under the MIT License (see MIT.md)
###########################################################################################
... |
4766db3797f5eb2d2255f21301781444295facff0342b0637f818d057053a804 | Python | 21,273 | 617 | import json
import os
import random
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import rankdata
from mr_utils.motion_transforms import (transf_from_parameters,
parameters_from_transf,
transform_sphere)
from scipy.int... |
90ba569708497b182345e7594bdcd50ce3fe679f44ac2de3178f7e660978f94d | Python | 21,283 | 505 | import matplotlib.pyplot as plt
import numpy
from importlib import reload
import sys
import os
import importlib
import types
# print(sys.modules.keys())
import multiprocessing
import multiprocessing.pool
original_packs = sys.modules.copy()
#import currents_visualization
import math
from neuron import h
import neuron
... |
47d314bab18e57ebba588fb2ebde72eb61e1b698fd8d706ba1d95abc5f18890c | Python | 21,292 | 505 | import matplotlib.pyplot as plt
import numpy
from importlib import reload
import sys
import os
import importlib
import types
# print(sys.modules.keys())
import multiprocessing
import multiprocessing.pool
original_packs = sys.modules.copy()
#import currents_visualization
import math
from neuron import h
import neuron
... |
4956fcce0e2249d588060b0bbfef7129fd37beb2816e2562de335ccb3f66973e | Python | 21,320 | 222 | import os, argparse, time, json
import numpy as np
from collections import OrderedDict
import nearl
import nearl.data
from nearl.io.traj import MisatoTraj
# Define the way to generation labels for the misato trajectories
def parser():
parser = argparse.ArgumentParser(description="Featurize the misato trajectori... |
dea1b5ddd3e26a370b09347abeaebf97b04e1d25ff8b4efeff1eeaa2f6fcccd0 | Python | 21,325 | 636 | #!/usr/bin/env python
#
# Copyright 2005 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 of... |
e1fca8ab75cef09cca5bd05c283dad253bcd5b7e64b10a2cf92d46b812ef4643 | Python | 21,332 | 430 | """End-to-end test of NWB export over GuPPy's native stubbed data, one acquisition format at a time.
Uses the session-scoped ``step5_output_*`` fixtures (tests/integration/conftest.py), which copy a
stubbed session to a temp dir and run the real pipeline to produce a populated
``<session>_output_<run>`` dir. Everythin... |
05a6bcc2791a371b0c34d2f0adf37a1d419da39991c20dedf8cf7ecca640edfa | Python | 21,335 | 499 |
import numpy as np
import nibabel as nib
from nilearn import datasets as ds
import pandas as pd
import os, re
HO_atlas_cort = ds.fetch_atlas_harvard_oxford('cort-maxprob-thr25-1mm', symmetric_split=True)
HO_atlas_sub = ds.fetch_atlas_harvard_oxford('sub-maxprob-thr50-1mm', symmetric_split=True)
#Load in stored atlas... |
f3c6b08159b35cf3b1d76f9ce96342ea53119444360c1f1f1d0b8ded5ad6905a | Python | 21,337 | 456 | import sys
sys.path.append("/home/lab-macbook/LabExperiment/Codes/TIS/SnapAnImageAndConverttoOpenCV/")
import os
import cv2
import numpy as np
import math
import random
import time
import TIS
import csv
from datetime import datetime
from screeninfo import get_monitors
from collections import deque
#python3 6_1_detect_... |
15355252341cc7fb526f8b6558f8035fdee57075beb5a4d18a41e0dbdcc45272 | Python | 21,346 | 542 | # Thomas Lavigne: chargement instantanné pose problème
# 02-08-2024
#
# From https://doi.org/10.1016/j.jmbbm.2023.105902
# Terzaghi Problem
#
# Boundary conditions:
# p=0
# --------
# | |
# | |
# | |
# | |
# | |
# | |
# ux=0| |ux=0
# | |
# | |
# | ... |
6683e1356c484b8db6ad8998e6cf98bbc2f02787ba1d09c11654ba57f469e4fe | Python | 21,347 | 662 | #!/usr/bin/env python3
"""
CICADA FIX-training smoothing-scale development curve.
Evaluates the historical CICADA smoothness implementation and prespecified
candidate Gaussian smoothing scales on ONLY the historical FIX-training
development set.
Default curve:
6, 8, 10, 12 mm FWHM
plus the historical CICADA basel... |
a5e132284cd182e968fed71fa2b338adeebfc0cab2484b48ccae3e054d932f62 | Python | 21,363 | 657 | """Test that all temporary directories respect the --tmpdir-prefix and --tmp-outdir-prefix options."""
import copy
import logging
import os
import re
import shutil
import subprocess
import sys
from pathlib import Path
from typing import cast
import pytest
from cwl_utils.types import CWLObjectType
from ruamel.yaml.com... |
60a618ac59153b47915e5419ca2c578c6d80c5adb4ed19d52d7b7eb99595dc3e | Python | 21,371 | 435 | #!/usr/bin/env python
#
# Register a volume (e.g., EPI from fMRI or DTI scan) to an anatomical image.
#
# Copyright (c) 2013 Polytechnique Montreal <www.neuro.polymtl.ca>
# License: see the file LICENSE
# TODO: if user specified -param, then ignore the default paramreg
# TODO: check syn with shrink=4
# TODO: output na... |
2f02dd8205d41623c554d1ea83f2460e0b8dc1731563b01843ce146b80352c8f | Python | 21,377 | 530 | #%%
import numpy as np
import cv2
import sys
import os
import pickle
import torch
import torch.nn as nn
import SimpleITK as sitk
from torch import optim
from torch.utils.data import DataLoader, Subset, Dataset
from PIL import Image
import random
from albumentations import (
GridDistortion,
ElasticTransform,
... |
696ea4c2d9416e88a4e4dbe7f8b6a05a45874e50d256474e90168d303758dfa0 | Python | 21,383 | 488 | #!/usr/bin/env python
# encoding: utf-8
"""
# if Glob physiology df / ERROR if physiological doesn’t exist
# Check if we already ran the analysis / if so, abort
# Open physiology df
# Open corresponding behavioral df / ERROR if corresponding behavioral df doesn’t exist
# Clean fixation columns
# Baseline correct
# Extr... |
a699aba4384425f261c77d1ee710efea23bf31bf8227a6eb4756b1ba1158dd6d | Python | 21,402 | 659 | """Callback library containing training routines. See :doc:`Callback Functions
</python/callbacks>` for a quick introduction.
"""
import collections
import os
import pickle
from abc import ABC
from typing import (
Any,
Callable,
Dict,
List,
Optional,
Sequence,
Tuple,
TypeVar,
Unio... |
0bd9f20a377873ffe6b1a8816b35e5f770cd850cb14d3ae4987a9ada4fa2e528 | Python | 21,410 | 420 | # 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... |
2d01e46ab38cae98ea697041801c19534fac73dc028fa7eadbc16244f1c6f56b | Python | 21,434 | 449 | import os, sys, argparse, time, random, json
import scipy.stats
import numpy as np
import pandas as pd
import h5py as h5
import matplotlib.pyplot as plt
import seaborn as sns
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.tensorboard import SummaryWriter
from sklearn.preprocessing i... |
f6f6fd42cbede59252e43d622909c6fbc29549eac7351b3f580919fadf7c5f61 | Python | 21,434 | 522 | # -*- coding: utf-8 -*-
import json
from django.db import connection
from catmaid.models import Connector, Treenode
from catmaid.state import make_nocheck_state
from catmaid.tests.common import round_list
from .common import CatmaidApiTestCase
class NodesApiTests(CatmaidApiTestCase):
def test_most_recent_tree... |
f8c669dd82600dc02233dbc9880f66cac76bfc22ee7c0621060a7c6cd78f57ef | Python | 21,443 | 478 | import numpy as np
from collections import Counter, defaultdict
from time import time
import re
from glob import glob
from sklearn.base import clone as CLONE
import sklearn.metrics as metrics
# Imputation
from sklearn.experimental import enable_iterative_imputer
from sklearn.impute import IterativeImputer
from pickle ... |
046c0a44d5752df5842449a0ab6e2a6476ed00f6683dc2cf0c9c489dcbd2fd41 | Python | 21,477 | 607 | # pylint: disable=too-many-locals, too-many-arguments, invalid-name
# pylint: disable=too-many-branches, too-many-statements
"""Training Library containing training routines."""
import copy
import os
import weakref
from typing import Any, Dict, Iterable, List, Optional, Sequence, Tuple, Union, cast
import numpy as np
... |
63a9959ff855746340755c59e04675a477a0e185cf2b701c7012329d0978ed23 | Python | 21,498 | 642 | import math
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.loss import _WeightedLoss
from torch_geometric.nn import knn
from torch_geometric.nn.pool import knn_graph
from torch_scatter import scatter_add, scatter_max, scatter_mean
def split_tensor_by_batch... |
fabfc8de28ca584d2d1115d0fde634a441c578af198414cb4a3192db87d7d241 | Python | 21,514 | 446 | from multiprocessing import dummy
from collections import OrderedDict
from typing import Tuple
import numpy as np
import torch
import shutil
from nnunet_mednext.training.loss_functions.deep_supervision import MultipleOutputLoss2
from nnunet_mednext.utilities.to_torch import maybe_to_torch, to_cuda
from nnunet_mednext.... |
deabfc5aa2dfed8593bff19c65f03b884aaf22c4f768db479d9ec2f41a4178d2 | Python | 21,519 | 578 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.distributions import Normal
from TD3.TD3_GNN import GNN_Feature_Extractor
from torch_geometric.nn import GCNConv, global_mean_pool, global_add_pool
from torch_geometric.nn import global_mean_pool
import numpy as np
LOG_SIG_MAX = 2
LOG_SIG_MI... |
3a60ac7ac376c2da1c4a8141a590d5b509e91859336717968e978236e6c905f6 | Python | 21,524 | 546 | # import math
import os
import numpy as np
from scipy.signal import resample
from abc import ABC, abstractmethod
import gc
import naplib as nl
import torch
import torch.nn as nn
from collections import OrderedDict
import librosa
from pycochleagram import cochleagram as cgram
from auditory_cortex.dataloader import Data... |
48d8e5ef1ae9ab29aee5a5ae5260956fa629ccd3d071ea91727793fbc09a0542 | Python | 21,529 | 667 | """E2E tests for @global job scope.
Workers use ZnDraw.jobs exclusively for register, claim, submit, disconnect,
and status updates. Raw httpx is ONLY for read-only GET assertions.
"""
from typing import Any, ClassVar
import ase
import pytest
from zndraw import ZnDraw
from zndraw_joblib.client import Category, Clai... |
24897fe89a60742d06ddf8ca0863bfe318e1bd8c9bd3504ba236e2d36d5a7f42 | Python | 21,542 | 612 | import gzip
from collections import OrderedDict
from typing import Optional, Union, Tuple, Any, Dict
import rdflib
from linkml_runtime.linkml_model.meta import Element, ClassDefinition, SlotDefinition
from rdflib import URIRef, Literal, Namespace, RDF
from rdflib.plugins.serializers.nt import _nt_row
from rdflib.term i... |
4d240ecbda5e72972576c03d5a922a35f3db4970721e55dff7e9d88134a40f11 | Python | 21,546 | 512 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jun 7 13:08:00 2021
marker files helping functios
@author: leupinv
"""
import markers.markers_constants as cs
from itertools import product
import pandas as pd
import feather
import mne
import numpy as np
def get_DF_centerd(df,cent_column,srate,metho... |
d5b1429afee2be134cdfd516cf0b22414371055e2d2dbe9c50fa2108a5d38311 | Python | 21,551 | 438 | # -*- coding: utf-8 -*-
# Generated by Django 1.11.8 on 2018-01-22 01:52
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import django.utils.timezone
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(setting... |
fa4c3b5b3db265ba68b760e8e48f6c69c497e7facd7a9e9e0d82226e893f034f | Python | 21,561 | 553 | from functools import partial
import numpy as np
from pip import main
import torch
import torch.nn as nn
import torch.nn.functional as F
import timm
from timm.models.layers import drop_path, to_2tuple, trunc_normal_
from timm.models.registry import register_model
from collections import OrderedDict
MODEL_PATH = '/mnt/... |
ae03e8e51fc69953f35828206a48f71b61ff597612a1d00a1049e733425cf005 | Python | 21,564 | 740 | import copy
import os
import pytest
from neo4j import GraphDatabase
import neo4j
from kgx.transformer import Transformer
from tests import TARGET_DIR, RESOURCE_DIR
from tests.integration import (
check_neo4j_container,
NEO4J_CONTAINER_NAME,
DEFAULT_NEO4J_URL,
DEFAULT_NEO4J_USERNAME,
DEFAULT_NEO4J_P... |
a3806a4c437a48851e936a09e2f8397a53d231afe2089cdc51814dc47c382810 | Python | 21,569 | 449 | # coding=utf-8
# Copyright 2021 The IDEA Authors. All rights reserved.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by a... |
77bf606ab818e38259a1d486e0682d1733c5b6a60f02b3d72a3dcaa68e3cc5e7 | Python | 21,574 | 555 | #!/usr/bin/env python
"""Evaluate every trained Poison26 checkpoint and report clean-test-set statistics.
Scans models/{MNIST,CIFAR10,audioMNIST}/*.pt, infers (arch, training regime, aug)
from each filename using the naming convention in 00_train_models.sh
(e.g. mnist_mobilenet_fgsm_aug.pt), evaluates each checkpoint ... |
8b3ae6c6b685b9a1582d469f31310eac21ea96cfba3153271b8a6d991e75078c | Python | 21,600 | 623 | """Python utilities required by Keras."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import binascii
import numpy as np
import time
import sys
import six
import marshal
import types as python_types
import inspect
import codecs
import collections
_GLOB... |
4c66e56a4c572f09403985c0a24b0a103547dee7c92e674b786d0c5937039935 | Python | 21,604 | 481 | from PyQt5 import QtGui, QtWidgets, QtCore
import pyqtgraph as pg
import numpy as np
from view.Plot import Plot
from util import colors
class PlotManager(QtWidgets.QSplitter):
def __init__(self, data_manager, cell_selection_imv, parent=None):
QtWidgets.QSplitter.__init__(self, QtCore.... |
8b56f738ecd11e53d5cc70392267852c4eafd1270b35e0ef1d911cfb82ffd1c7 | Python | 21,644 | 566 | import copy
import itertools
import multiprocessing
import os
import shutil
import tempfile
from os.path import exists
from sys import stderr
from typing import Dict, Generator, List, Optional, Callable, Set
from kgx.config import get_logger
from kgx.error_detection import ErrorType, MessageLevel, ErrorDetecting
from ... |
ab3cc0ec554a5ec8cf70c1b1eb7570f7006574ab90735a132676827029813bbf | Python | 21,651 | 511 | """
Author : Alexis Lebrun (PhD student)
School : Université Laval (Qc, Canada)
This module provides functions to preprocess vibrational spectra. These features
improve spectrum quality and can improve performance for machine learning applications
"""
import numpy as np
from scipy import interpolate, sparse
from scip... |
1ae9ababf4945a84a012ae56dbd1b413aeacb102a6ca6875377801ddc2dd3418 | Python | 21,653 | 566 | """
Helper functions for loading and processing results.
License: BSD-3-Clause
Author: Hanna M. Tolle
Date: 2024-10-31
"""
import os
import torch
import pandas as pd
import random
import numpy as np
from torch_geometric.seed import seed_everything
import importlib
import logging
from torch_geometric.data import Data
... |
d1d8bab4f0c1e631afa50b9e17d5044dd6949296001d824dda275214d07128bc | Python | 21,692 | 517 | # -*- coding: utf-8 -*-
from typing import List
from django.db import connection, transaction
from django.core.management.base import CommandError
from catmaid.models import Project
def rebuild_edge_tables(project_ids=None, log=None) -> None:
"""Rebuild edge tables for all passed in project IDs. If no project I... |
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