sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
3ae4d4027c70b7781eed00bf91edf7e28875f305d74a155f561f52feba46037a | Python | 7,316 | 157 | import numpy as np
import pandas as pd
from anndata import AnnData
import pkgutil
import io
from typing import Optional, Union, List, Iterable
def ligand_receptor_database(
database: str = "CellChat",
species: str = "mouse",
signaling_types: Union[str,Iterable[str]] = ["Secreted Signaling", "Cell-Cell Cont... |
4a5eb2d47f10e2762c29eed6212c190a54709edc3ce01c1f136bce6d901473a6 | Python | 7,316 | 181 | # -*- coding: utf-8 -*-
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import torch
from torch import nn
from torch.nn import functional as F
from typing import Any, Di... |
155b1a69ba51cd6ae3b987e6b50d64688d17ca32ccf3015d5d279df3b01742c2 | Python | 7,317 | 150 | import matplotlib.pyplot as plt
import numpy as np
import json
def display_average_scores_among_search(json_file, saving_title='average_scores_among_search.png'):
search_idx = []
after_mean_dice = []
after_mean_instance_dice = []
before_mean_dice = -1
before_mean_instance_dice = -1
with open(js... |
9e62cd782005a13f28389ca992d4e53ab6fcf24269d65aac31f8b7721f8f6dcb | Python | 7,317 | 234 | # score_bcf.py
import os
import logging
import numpy as np
import pandas as pd
import pysam
from collections import deque
from joblib import Parallel, delayed
from .utilities import (
configure_logging,
check_bed_type,
get_samples,
determine_bcf_type,
normalize_bed_contigs,
)
from .bcf_parallel impo... |
e4c954fcbf22c63817fd54914d6089a40b5e9dfc7eb44bbc3159b09d3923dbe0 | Python | 7,318 | 166 | import warnings
warnings.filterwarnings("ignore", message="It is not recommended to directly access")
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
def index_select_ND(source: torch.Tensor, index: torch.Tensor) -> torch.Tensor:
"""
Selects the message features from source corre... |
a1953fe3c50265b75bd3787d6c984bbbd7fb95626353e146c26f2ded2895bfe4 | Python | 7,319 | 182 | """A short timing run, so a batch can be split by how fast each machine is.
Two computers rarely run at the same speed, and the split has to reflect
that or the faster one sits idle at the end. Core counts are a poor guide —
a laptop's eight cores and a workstation's eight cores are not the same
eight cores — so this ... |
56e0e78d82f257fb892d713d8fc3e8faf900ab447b20b0fdc53103180fdd19a7 | Python | 7,320 | 153 | #!/usr/bin/env python3
"""Generate a synthetic fixture with UL-DD's file layout.
THIS IS A TEST FIXTURE, NOT DATA. Anything computed from it is a check that the
code runs, never a scientific result. It exists so the pipeline can be exercised
end to end -- including the degraded-signal paths -- before the real restrict... |
452483b27ff2e3da69cf22ea06228069a110d6d56b9bdd947e2e0158abb8246d | Python | 7,321 | 259 | import os
import pickle
from dataclasses import dataclass
import numpy as np
import pandas as pd
def save_fit(
G1_file,
fit_,
fit_str,
lags,
meta,
min_g1,
min_lag_points,
out_hdf5_path,
times,
tofs,
):
import h5py
with h5py.File(out_hdf5_path, "w") as h5:
fits... |
cedfbd84f39048060b3f4d75c53573c55a3c4bd52a5b2dad4085a8acd82f16b0 | Python | 7,322 | 172 | import shutil
import subprocess
import nibabel as nib
import numpy as np
import pytest
import importlib_resources
from comet import cifti, utils
# Parameter space
ATLASES = ["schaefer", "yan", "glasser", "gordon"]
RESOLUTIONS = [100, 200, 300, 400, 500, 600, 700, 800, 900, 1000]
NETWORKS = [7, 17]
SUBCORTICALS = [None... |
0b13c6124089921d5d2b8ed7f2282da65d9ca46e69be5734bbc9a0bfb75334bc | Python | 7,325 | 164 | from brainscore_core.supported_data_standards.brainio.packaging import package_data_assembly
from pathlib import Path
from shutil import copy
from brainscore_core.supported_data_standards.brainio.stimuli import StimulusSet
from brainscore_core.supported_data_standards.brainio.packaging import package_stimulus_set
from ... |
00735891cfa24cd2ccfa913b50e2e2b108d4ec2c1ca0566e47ff320d4baaa414 | Python | 7,326 | 159 | '''
NO2
'''
import numpy as np
import sys
def intro():
print("""
SHORT List of potential energy surfaces for NO2:
P: potential energy, G: Gradient, D: Nonadiabatic coupling vector
This is listed at the end of description to show the availability.
For example: P/G means both potential energy and g... |
3a8599adddf74c7869dc6217d925e6ecac6b7a8fd8f444712ef9dd7e390f9f72 | Python | 7,330 | 194 | import random
from collections.abc import Sequence
from dataclasses import dataclass
from pathlib import Path
from typing import TYPE_CHECKING
import pandas as pd
from tests.setup_tests.setup_modelling_test_data.setup_targets_test_data import (
get_current_test_label_values,
get_test_label_file_fieldnames,
... |
dce9b838bf1bac9d0069356a469fd78ce3715d7d944a934a7c26b5b1f98af38e | Python | 7,330 | 202 | from deepcardio.neuralop_core.transforms import DataProcessor
from torch_geometric.data import Data
import torch
from torch_cluster import radius
from torch_scatter import scatter
import os
from deepcardio.neuralop_core.transforms import UnitGaussianNormalizer
DataScaler = UnitGaussianNormalizer
GINO_NEIGHBOR_RADIUS ... |
671a8f76902da7b8c6f4bb2c4fcef6ce6b9dd96cab0f2f8a1b8e2c95a0177098 | Python | 7,331 | 191 | import matplotlib.pyplot as plt
import numpy as np
from scipy.ndimage import gaussian_filter, gaussian_filter1d
from scipy.stats import poisson
def plot_poisson_distribution(n: int = 50,
lam_range: tuple[int, int] = (5, 50),
n_lines: int = 4):
x = np.ara... |
af3a73db00cbadd33bf0fcf84615044d604b19e064d3f004fe1189f99ebc211e | Python | 7,331 | 200 | import math
import os
import torch
import torch.nn as nn
import torch.utils.model_zoo as model_zoo
bn_mom = 0.0003
class SeparableConv2d(nn.Module):
def __init__(self,in_channels,out_channels,kernel_size=1,stride=1,padding=0,dilation=1,bias=False,activate_first=True,inplace=True):
super(SeparableConv2d,se... |
e63b22747480cb186a52f4ea158822dd5bcc46042f36cf9c9d5011f330d5bedf | Python | 7,332 | 167 | import pandas as pd
import os
import numpy as np
import matplotlib.pylab as plt
import sys
def plot_seq(fg, df, agent=0, n_steps=1, block=0):
fg.clf()
seqdf = df.query('agent == {} & n_steps == {} & block == {}'.format(agent, n_steps, block))
cmap_tab = plt.get_cmap('tab10')
ax = fg.add_subplot(1, 1, 1... |
8f0a9bbb9b54c28e919413a7b53db12aa8b01f0cd07e15b35d00806df1f3c806 | Python | 7,334 | 206 | import numpy as np
from scale.utils import (
select_best_lambdas,
spatial_sample_split,
preprocess,
check_for_raw_counts,
)
from scale.training import train
from scale.clustering import calc_clusterings
from scale.search import calc_stability, calc_entropy
from scale.config import Config
import scanpy ... |
4065502040694b47eb24787e57b6cfaf6c1db7d1eeccadcc48f315d7d4ca4dfa | Python | 7,335 | 191 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Evaluate pair-wise similarity measures of masks and atlas.
All volumes must be co-registered in the same space.
Support multiple input volume. The following command will compare all
combinations of the input volumes (1-2, 1-3, 2-3):
scil_volume_pairwise_comparison m... |
f585bc351f0da9084b1aa765862e82c056aa3e8b4626538e54a578a3cce8bb58 | Python | 7,335 | 211 | from __future__ import annotations
from typing import TYPE_CHECKING
import napari
import napari.layers
import numpy as np
from napari.qt.threading import FunctionWorker
from PyQt5.QtWidgets import QApplication
from brainways.pipeline.brainways_params import BrainwaysParams
from brainways.ui.controllers.base import C... |
d79618f18abba187df71bc93d1642384b47db6c2895e0b1c976a8219cf762370 | Python | 7,337 | 232 | from torchvision import transforms
import torch.utils.data as data
import numpy as np
import random
import torch, torchvision
from torchvision import datasets, transforms
from torch import nn, optim
from torch.nn import functional as F
from PIL import Image, ImageFilter
import os
import scipy.io as sio
class EyeData(da... |
08ac50f921c4753c8b70a96d85f98fdbbe44cd7260bbfb526fd4bed27da62117 | Python | 7,340 | 255 | """Support backcompatibility for configs at v0.1.1."""
from copy import deepcopy
from typing import Dict
from deepreg.constant import KNOWN_DATA_SPLITS
def parse_v011(old_config: Dict) -> Dict:
"""
Transform configuration from V0.1.1 format to the latest format.
V0.1.1 to latest.
:param old_config... |
7e661122c3da069c3806e62b7492c8f6a779cf2579e69fa6dfeb9c083ba3276d | Python | 7,341 | 176 | # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import torch
from torch import nn
from torch.nn import functional as F
from typing import Any, Dict, List, Tuple, Union
... |
cae86ad40a3c78e09bc328804f5e4eb5269fdba9105c708e34a9423492105bfe | Python | 7,341 | 204 | import os
import glob
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import scipy.stats as sist
import ast
from statsmodels.stats.multitest import fdrcorrection
def fix_string_format(string):
# Split the string by spaces
values = string.split()
# Join the valu... |
6cb67111772999dea1dffebd8d577fb176d7350b9c7537f431cb6e3cec1e64fb | Python | 7,342 | 187 | # -*- coding: utf-8 -*-
import os
import re
import sys
def find_reference_pcr_file(pcr_file_path):
current_dir = os.path.dirname(pcr_file_path)
for i in range(5): # Try up to 5 levels up
ref_path = os.path.join(current_dir, 'dat_vestacif_files', 'reference_pcr_format', 'tbbaco.pcr')
if ... |
7b35a7f9211fc31d5ee1f42d037ca920c887d89a39597682faf453d63384f7c5 | Python | 7,342 | 229 | #!/usr/bin/env python
import argparse
import collections
import datetime
import json
import math
import sys
import uuid
from pathlib import Path
from typing import Any
from typing import Final
import imgviz
import numpy as np
try:
import pycocotools.mask # type: ignore
except ImportError:
print("Please inst... |
663cb0fc50b4f0d8b803054cb6115f902795c836698a8f65c82f8a635061ed58 | Python | 7,344 | 190 | ######################################################################
# Copyright (C) 2020-2026 MEmilio
#
# Authors:
#
# Contact: Martin J. Kuehn <Martin.Kuehn@DLR.de>
#
# 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... |
2457c5a3d1b257c3683c83cd6d409a18bd20d4e794f19d4e6952c40e35fcbb72 | Python | 7,345 | 222 | import sys
import yaml
import os
import numpy as np
import h5py
import matplotlib.pyplot as plt
import matplotlib as mpl
pathpath,myrun,ncluststr,cmethod = sys.argv[1:]
#pathpath = 'PATHS/filepaths_carlen.yml'
#myrun = 'runCrespZP_brain'
#ncluststr = '8'
#cmethod = 'ward'
ncl = int(ncluststr)
with open(pathpath) as ... |
a1f2550564834de7eaa7bb6dc4bcdd06503be35ab2243628256a51412d2ea581 | Python | 7,345 | 201 | from zigzag.classes.hardware.architecture.memory_instance import MemoryInstance
from zigzag.classes.hardware.architecture.operational_array import OperationalArray
from zigzag.classes.hardware.architecture.memory_hierarchy import MemoryHierarchy
import networkx as nx
class Core:
"""
The Core class houses the ... |
a452efb07f4e4bcbbcf514fa24f181f279ada3d9cb952ca1d5fba191e3713e05 | Python | 7,345 | 203 | import argparse
import torch
import torch.nn.functional as F
from torch.utils.data import DataLoader
from ogb.linkproppred import PygLinkPropPredDataset, Evaluator
from logger import Logger
class LinkPredictor(torch.nn.Module):
def __init__(self, in_channels, hidden_channels, out_channels, num_layers,
... |
a33f9ce3486f7738a2e3f7211103c7cd0a3f7458c7afd1cbb898432eca912155 | Python | 7,346 | 208 | import inspect
import logging
import warnings
from typing import Any, Dict, Optional, Union
import torch
from torch import Tensor
from torch_geometric.explain import Explanation, HeteroExplanation
from torch_geometric.explain.algorithm import ExplainerAlgorithm
from torch_geometric.explain.algorithm.captum import (
... |
0d1347bfe166bbd298778bf59e9c8288dc11cf4968d2c061883d8612abaeb6da | Python | 7,347 | 231 | import re
from pathlib import Path
from typing import Optional
import click
import numpy as np
import pandas as pd
import simple_mri as sm
import tqdm
import gmri2fem.segment_tools as segtools
from gmri2fem.segment_tools import find_label_description, read_lut
from gmri2fem.segmentation_groups import default_segmenta... |
ee95e45b9d6c14ad952cfbcc14bea5665f7547872b0773ac6ab9adaa8a96d922 | Python | 7,347 | 142 | #! /usr/bin/env python
"""Step three of the pipeline
Take a series of triange graphs in gt format from pycurv and measure
distances within and between surfaces as well as orientations relative to
the growth plane and to each other.
Two usage options:
1. Measure distances and orientations on a single **tomogram** wort... |
f2df3915715ed199bf1ab36af2d02095e776e76983d3cf8b2219c98ddefe2423 | Python | 7,347 | 175 | from torch_geometric.data import InMemoryDataset
import pandas as pd
import shutil, os
import os.path as osp
import torch
import numpy as np
from ogb.utils.url import decide_download, download_url, extract_zip
from ogb.io.read_graph_pyg import read_graph_pyg, read_heterograph_pyg
from ogb.utils.torch_util import replac... |
59ba2022958b9f847ce5a3f2d6e11bf54076809709853efc61ccb12abdb8de6a | Python | 7,348 | 200 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from __future__ import annotations
import numpy as np
from PIL import Image
from rest_framework import status
from rest_framework.exceptions import ValidationError
class ROIHelper:
"""
Utilities for running automatic annotations functions ... |
947570831ab8732ba6d6901a92b7a7e5baf880de38066a2cc7419ce336cd4f39 | Python | 7,349 | 199 | """Pooling every machine's part into one output folder.
Each machine's part is an ordinary output folder for its share of the batch.
Bringing them together is a file-level union of the things that belong to
*one recording* — its spike times, adjacency, checks, and figures — plus a
key-level union of step 4's ``netmet_... |
bc59758e9cd928c2f0fe7fb54ee2500e5b8cf94a07184009d25c0154f0ecb892 | Python | 7,350 | 228 | from typing import cast, Sequence
import numpy as np
import scipy
from matplotlib import pyplot as plt
from matplotlib.axes import Axes
from scipy.stats import sem
from neuralib.plot.colormap import insert_colorbar
from neuralib.typing import AxesArray
from rscvp.util.typing import SIGNAL_TYPE
__all__ = [
'plot_... |
3835dd687c3cd06ae94d060910138b503defcd6181dde1b1326318a746cc2baf | Python | 7,352 | 210 | import os.path as op
import dipy.data.fetcher as fetcher
import nibabel as nib
import numpy as np
import numpy.testing as npt
from dipy.io.stateful_tractogram import Space, StatefulTractogram
import AFQ.data.fetch as afd
import AFQ.recognition.cleaning as abc
import AFQ.recognition.curvature as abv
import AFQ.recogni... |
5221a8688fde717c7d158a56204e9ee40e1fa4cf0b270273c93fc61188dc48ad | Python | 7,353 | 187 | import os
import os.path as osp
import pandas
from tqdm import tqdm
import ijson
import json
from datetime import datetime
import numpy as np
from gensim.models import word2vec
from nltk import tokenize
dataset = 'Twibot-22'
if not osp.exists('tmp/{}'.format(dataset)):
os.makedirs('tmp/{}'.format(dataset))
proper... |
69c877d1f888be1f14314cfdb73fb220499cbb128650b866f6d093da40683328 | Python | 7,354 | 230 | """
Train and evaluate multiple DLIM (Deep Latent Interaction Model) instances
in parallel with and without spectral regularization.
This script:
1. Loads real datasets (e.g., 'harry', 'elife') for a given environment.
2. Trains multiple DLIM models using multiprocessing.
3. Compares training performance (MSE loss) a... |
807c74ae3eb78412257b0046688b9f31e610d2d0d423f1cc06a543d3f5d3781e | Python | 7,358 | 241 | import os
from tqdm import tqdm
import glob
import numpy as np
from scipy.interpolate import interp1d
from scipy.stats import pearsonr
from scipy.ndimage import gaussian_filter1d
from fiberpipeline.utils import get_basename
from nicety.conf import get_conf
from joblib import Parallel, delayed
import optuna
import wa... |
e75fa47acc46c9655dfecd1d34c17e7c126146a440701c6c16d52d3047d444ce | Python | 7,360 | 157 | """Default calculator behavior on core-only and Polar-enabled installations."""
import json
from pathlib import Path
import subprocess
import sys
from types import ModuleType
from unittest.mock import Mock
import pytest
import toml
from chemgraph.schemas.calculators import mace_calc
from chemgraph.utils import calcu... |
49f2bf8230076a341c706eb852211a9520a56ad32c11f1abcbbf8822d9dbb652 | Python | 7,362 | 227 | """Single-channel Dynamic Network Modes (SC-DyNeMo)."""
from dataclasses import dataclass
from typing import Dict
import numpy as np
import tensorflow as tf
from osl_dynamics.models.dynemo import Config as DynemoConfig
from osl_dynamics.models.dynemo import Model as DynemoModel
from osl_dynamics.inference.layers imp... |
00ae2f26e799afd1fc8a03c4e9a8452884ff90f2d7876e5d6502420ba058606f | Python | 7,363 | 233 | import pandas as pd
import scanpy as sc
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import seaborn as sns
def tracks_plot(
adata,
marker_genes,
width=12,
track_height=0.25,
fontsize=None,
use_raw=False,
exp_transform=False,
labels=None,
... |
04d7d1214b100f2cea1af2520d59d54e4c2f2e79a2605e36387c80cde67b6f41 | Python | 7,364 | 203 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Aug 24 08:49:51 2023
@author: rl05
Suppress artifact - filter, ICA, identify bads, epoch, epoch rejection
"""
import os.path as op
import pickle
import json
from mne import pick_types, find_events, Epochs
from mne.preprocessing import ICA, create_eog... |
8fcf8296eb1e870df1b2a7b763e06ff71c3b57d0a2c4eb1be78f3cf3c6594610 | Python | 7,366 | 229 | import functools
import typing
import bisect
import pdb
import logging
from ..qt import *
from ..config import *
LOGGER = logging.getLogger(__name__)
class Delegate(QItemDelegate):
def createEditor(self, parent: QWidget, option: QStyleOptionViewItem, index: QModelIndex) -> QWidget:
if index.column() == 4:
... |
2058639983763b61a9d0b00ccb6d235aff827d58f3bd2baf42e4fb7aea6c9926 | Python | 7,367 | 227 | """Shared, internal types for the endpoint × protocol model-loading pipeline.
The pipeline is::
caller -> load_chat_model -> endpoint spec -> protocol builder -> client
An *endpoint* declares only what makes it different from other endpoints that
speak the same protocol: its base URL, credential policy, model-na... |
ea7db9acd456b1444eb893dcdecac6dbb4df5dc462ac03738fddf26b124ecf81 | Python | 7,369 | 195 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import json
import re
from os.path import join as pjoin
from io import StringIO
import numpy as np
import pandas as pd
import os
import sys
from glob import glob
from natsort import natsorted
LABDATA_FILE= pjoin(os.path.expanduser('~'),'labdatatools','preferences.json')
... |
f6553af83cc781d24338d21779eda930b697fba9132dff439771d463742ca0be | Python | 7,369 | 167 | #############################################################################
# Copyright (C) 2020-2026 MEmilio
#
# Authors: Martin J. Kuehn, Maximilian Betz
#
# Contact: Martin J. Kuehn <Martin.Kuehn@DLR.de>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compl... |
1d4767adbb557fe1c0bacec8130855d5fe4d0153f6ac7f890c4d6d251407441e | Python | 7,373 | 176 | from PUMI.engine import QcPipeline, GroupPipeline
from PUMI.engine import NestedNode as Node
import nipype.interfaces.fsl as fsl
from nipype.interfaces.utility import Function
from PUMI.utils import get_reference
import nipype.interfaces.ants as ants
@QcPipeline(inputspec_fields=['mask', 'template'],
outp... |
a2677524185923841ac8022a848e503795258789449278b8ea5141217d5655a4 | Python | 7,376 | 206 | """ Classifier head and layer factory
Hacked together by / Copyright 2020 Ross Wightman
"""
from collections import OrderedDict
from functools import partial
from typing import Optional, Union, Callable
import torch
import torch.nn as nn
from torch.nn import functional as F
from .adaptive_avgmax_pool import SelectAd... |
55d7141a5aa6d2ab22645e0f008b0cd2b11180874491dff98e5ec25d2f67c072 | Python | 7,377 | 203 | """
This script plots the results of the single-session predciton of switches from
neural data.
"""
import sys
import os
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import matplotlib.pyplot as plt
from scipy import stats
import json
import numpy as np
from pathlib import Path
fro... |
f29033adadcd7c633d040ba56b255435338953192a7f37bae7266b4ff5d4911d | Python | 7,377 | 136 | """This scripts generates 3 examples where we now use multi-modal data to regress HR synthetic scans. Specifically we
regress HR synthetic T1 scans from LR T1 and T2 scans. Thus this script produces synthetic HR T1 scans as regression
target, and aligned HR synthetic scans (input channels) simulating T1 and T2 scans ac... |
54d58b103ba51480fc98bb3180df2ad53f8edccda2d27d128b9212c0465eccc5 | Python | 7,379 | 228 | import os
import os.path as osp
import re
import warnings
from typing import Callable, Dict, Optional, Tuple, Union
import torch
from torch_geometric.data import InMemoryDataset, download_url, extract_gz
from torch_geometric.utils import from_smiles as _from_smiles
class MoleculeNet(InMemoryDataset):
r"""The `M... |
d6330bd15399f5ec062c179275ac33f2256d2628dec3dc547bf0ee691a934f4e | Python | 7,379 | 73 | import argparse
def ArgParserPatch(commandline,do_exit,flag=0):
parser = argparse.ArgumentParser()
exp=['experiment','--exper']
parser.add_argument(exp[flag], type=str, help = 'give name of h5 file, for example: ')
parser.add_argument('-headstages', type=str, nargs="+", help='which headstage to analyze... |
0c38df582d121f90fdd73adc49e11448a10bb2c30e54eb6d649ceffad05471f9 | Python | 7,382 | 213 | """
Apply Machine Learning Classifiers to OpenPBTA data
Modified from PDX PPTC Machine Learning Analysis
https://github.com/marislab/pdx-classification
Rokita et al. Cell Reports. 2019.
https://doi.org/10.1016/j.celrep.2019.09.071
Gregory Way, 2018
Modified by Krutika Gaonkar for OpenPBTA, 2019
In the following not... |
0626238808833b97bd3467a2873fe61efa5eeb9163d3c2ccdf7974d14e5bdac4 | Python | 7,383 | 221 | #!/usr/bin/python3
#
import os
import sys
import argparse
import numpy as np
from uac import utils
# Create the parser
my_parser = argparse.ArgumentParser(description="Calculation of old atrial coordinates")
# Add the arguments
my_parser.add_argument("target_path", metavar="path", type=str, help="Path for the new ta... |
303cc4535134e9280eee7420d214ee912610107b5ec1594cf6e4946f30b9726f | Python | 7,383 | 197 | #!/usr/bin/env python3
"""
Centroid geometry similarity via pairwise Euclidean distances (label-matched):
Given two centroid CSVs (from plot_scatter_centroids), this script:
1) Loads centroids and matches rows by (layer, network)
2) Computes within-dataset pairwise Euclidean distances between all centroids:
DA(i... |
1770fdb8a3f65e751d6c21b703f41a9045fe1745633d004af2f2ef4e2943f889 | Python | 7,384 | 170 | #!/usr/bin/env python3
import sys
import getopt
import time
############################################################################
# Main gateway:
#############################################################################
# usage
def main_usage():
print("""
Usage : GEM_toolkit.py action [options]
Actio... |
33f41a0b22c9d0e44da51c77ed254ac58078bcb7f480f0fb86647d6a5b53e93f | Python | 7,385 | 179 |
""" Classes and functions for fitting ivim model """
import numpy as np
from scipy.optimize import curve_fit
from dipy.reconst.base import ReconstModel
from dipy.reconst.multi_voxel import multi_voxel_fit
from dipy.utils.optpkg import optional_package
class IvimModelSegmented3Step(ReconstModel):
def ... |
db8ff8b542d0e0cfa3813b0922d827d413a7e0f1fe56913dc3e4d30722d703f8 | Python | 7,385 | 213 | """
A set of helper functions for TIMBRE.
@author: Gautam Agarwal
"""
import numpy as np
from random import sample
from keras import models
from scipy import signal
def test_train(lapID, which_phase, n_folds=5, which_fold=0):
"""
Returns test and train samples
Parameters:
- lapID: contains info ... |
e21afecc778c86266a18a9e4e56eec8515a1f99a7f5689c3940227ed6d9fb9b1 | Python | 7,385 | 237 | from typing import Any
import torch
import torch.nn as nn
import torch.nn.functional as F
import seisbench.util as sbu
from .base import WaveformModel
class CRED(WaveformModel):
"""
Note: There are subtle differences between the model presented in the paper (as in Figure 1) and the code on Github.
... |
589d95a64a784bb4ef338796723569f2de545687a3f0af29db56c543be493a06 | Python | 7,386 | 152 | import torch
import os
import glob2
from tqdm import tqdm
import pathlib
def check_early_stopping(val_loss, previous_val_loss, early_stopping_counts, early_stopping_threshold, epoch, model,
optimizer, scheduler, path):
exit_training = False
if val_loss.item() > previous_val_loss:
early_... |
d0bcbf481214b1dca6d936181753bfa94ce1364b83c729041fcf7481a6caed3a | Python | 7,388 | 139 | """
If you use this code, please the SynthSR paper in:
https://github.com/BBillot/SynthSR/blob/master/bibtex.bib
Copyright 2020 Benjamin Billot
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:... |
e974f0f621c6d74ceed5f82e0f7087ec2cc0a021314b07181b267684f30a247e | Python | 7,389 | 192 | # This file is part of connectome-manipulator.
#
# SPDX-License-Identifier: Apache-2.0
# Copyright (c) 2024 Blue Brain Project/EPFL
"""Auxiliary classes to process many nodes split into chunks"""
from dataclasses import dataclass
from functools import reduce
from operator import and_
from typing import Union
import ... |
6d3b9eec2749716e76beffa57b03dc43744e83fd3b4bd918ee0e576ae6d633f5 | Python | 7,391 | 206 | import argparse
import torch
import torch.nn.functional as F
from torch.utils.data import DataLoader
from ogb.linkproppred import PygLinkPropPredDataset, Evaluator
from logger import Logger
class LinkPredictor(torch.nn.Module):
def __init__(self, in_channels, hidden_channels, out_channels, num_layers,
... |
e43ee15aea25163e73c9dd8a2f4e0302644ecfe010335be0748010a3f97922f6 | Python | 7,391 | 148 | import pandas as pd
import xarray as xr
from brainscore_core.supported_data_standards.brainio.stimuli import StimulusSet
from brainscore_vision import load_dataset, load_metric
from brainscore_vision.benchmark_helpers.neural_common import (
TrainTestNeuralBenchmark, RSABenchmark, average_repetition,
filter_rel... |
fbcbee7a2d82c5bc2e50981c91e95e1bb0fd8c17706949010cb8d62614f580eb | Python | 7,391 | 140 | from brainvoice.data.brainvoice_dataset import BrainVoiceDataset
from brainvoice.data.datasplit import DataSplit
from brainvoice.data.standard_scaler import StandardScaler
from brainvoice.data.minmax_scaler import MinMaxScaler
import os
import torch
class BrainVoiceStream(object):
"""
Subset part ... |
bf8b85c94bde5af115b409b2c82adfffdef1cc943a270114a2895fc061bfc8ff | Python | 7,394 | 327 | # Copyright 2017 Calico LLC
# 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, sof... |
3aec00a8b4a733177b0c0a07baaa285f7ec5dc5febe4bfa8e6eb8ca7f32e706c | Python | 7,397 | 187 | """Custom state initializers with permanent properties between trials"""
import numpy as np
import collections
from moog import sprite
from . import poll_generator
from moog.state_initialization import distributions as distribs
class ParentStateInitializer():
def __init__(self, agent_0_factors, agent_1_factors,
... |
f8a10d3751cd3ec020959c757774cded09645195a0a2c602505e60086cb8d369 | Python | 7,397 | 160 | from pathlib import Path
from typing import List, Tuple
import numpy as np
from PIL import Image
from brainscore_core.supported_data_standards.brainio.assemblies import NeuroidAssembly, PropertyAssembly
from brainscore_vision import load_benchmark
from brainscore_vision.model_interface import BrainModel
from brainsco... |
3a171840849779128422e6fa716f739bbc3279e10d7c37b00079b2c465243610 | Python | 7,399 | 243 | from pathlib import Path
from types import SimpleNamespace
import numpy as np
from napari_dmc_brainmap.registration.sharpy_track.sharpy_track.model.AtlasModel import (
AtlasModel,
)
from napari_dmc_brainmap.results.probe_vis.probe_vis.view.ProbeVisualizer import (
ProbeVisualizer,
)
from napari_dmc_brainmap.s... |
4983acc421c4c65bc768b5546025b7a17168c194a913db28edff80b541bedcab | Python | 7,400 | 236 | import re
from pathlib import Path
from typing import Literal, Optional
import numpy as np
import pandas as pd
import scipy as sp
import skimage
import tqdm
def apply_affine(T: np.ndarray, X: np.ndarray) -> np.ndarray:
"""Apply homogeneous-coordinate affine matrix T to each row of of matrix
X of shape (N, 3)... |
5c704486fe5b597367d364b540627e665c199931a727c2f05b44ea8d2b33a9c5 | Python | 7,405 | 197 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Script to compute signal to noise ratio (SNR) in a region of interest (ROI)
of a DWI volume.
It will compute the SNR for all DWI volumes of the input image seperately.
The output will contain the SNR which is the ratio of
mean(signal) / std(noise).
The mean of the sig... |
03e96dbc2d8aacda5395bc7352616c07fdb85aa45da364eb6e325efcb569a16e | Python | 7,407 | 204 | """
Cross-Modal Fusion Module for AVPENet.
Transformer-based bidirectional cross-modal attention fusion.
Given audio embedding ea ∈ R^512 and visual embedding ev ∈ R^512:
1. Project into shared space with learnable positional encodings
2. Audio-to-visual attention: queries from audio, keys/values from visual
3.... |
476a8f3ec1578f6cba9dcce056357d723ba6e830921501c5fe002001f8de1e8d | Python | 7,407 | 219 | """Torch Module for E(n) Equivariant Graph Convolutional Layer"""
# pylint: disable= no-member, arguments-differ, invalid-name
import torch
import torch.nn as nn
import dgl.function as fn
from dgl.nn.functional import edge_softmax
class EGNNv2Conv(nn.Module):
def __init__(self, in_size, hidden_size, out_size, edg... |
7f75df646cdeb11de1b952cde06197f8a582128992d05e535a6044e470eb4d44 | Python | 7,409 | 202 | # Created by David Coggan on 2024 06 25
import numpy as np
from brainscore_core.supported_data_standards.brainio.assemblies import DataAssembly, NeuroidAssembly
from brainscore_vision import load_dataset
from brainscore_vision.benchmarks import BenchmarkBase
from brainscore_vision.benchmark_helpers.screen import place... |
afbf0de027df0165fd331036c3b7b15cd5155ff907d93f4b908ef5fb49c5b7fc | Python | 7,409 | 244 | # The ImpedanceFitter is a package to fit impedance spectra to
# equivalent-circuit models using open-source software.
#
# Copyright (C) 2023 Julius Zimmermann,
# julius.zimmermann[AT]uni-rostock.de
#
# This program is free software: you can redistribute it and/or modify
# ... |
faaa5aa3442ac40d3f5c9d2299b1af1e5ec80f783feac83dba36f1958cde1665 | Python | 7,410 | 200 | # Copyright (c) OpenMMLab. All rights reserved.
import os
import os.path as osp
import platform
import shutil
import sys
import warnings
from setuptools import find_packages, setup
def readme():
with open('README.md', encoding='utf-8') as f:
content = f.read()
return content
version_file = 'mmseg/ve... |
014a563cf3b660b73cfdcb6ec487fd6c5fc5354fe7b08fa59be1967216eaf082 | Python | 7,411 | 211 | import numpy as np
from math import log
from collections import defaultdict
from logging import info
from data import Token, inverse_target_map
from util import as_scalar
def transition_probabilities(sequences, smoothing=None, binarize=True,
log_prob=True, verbose=False):
"""Estimate... |
cd17eedf191ac33c0164aba0909a27721bf632ecd4607957a523b7db8b218e59 | Python | 7,411 | 201 | """
Deprecated
HierarchicalEventClassifier LOO version
@ 2022 Knowblesse
Using the preprocessed Neural Ensemble dataset with behavior labels, build and test the SVM.
Along with the accuracy, feature importance is calculated.
Two classification is done.
1) Is it HE or HW?
2) Is it data from Avoidance trial or E... |
eda89c4ed4aee3d2d8eef3af44c6c30f9559a86e5b0f7230cb061f2674d27bab | Python | 7,412 | 171 | from typing import Dict
from math import prod
from zigzag.classes.workload.layer_node import LayerNode
from zigzag.utils import pickle_deepcopy
class TemporalMapping:
"""
Class that collect all the info related to temporal mapping.
"""
def __init__(self, temporal_mapping_dict: Dict, layer_node: Layer... |
5b1182161bd18eda3ce1a2a0befc2e978d8fbe3c713b25a29277f3585d470ac2 | Python | 7,416 | 159 | # Copyright (c) 2026 Rohit Jena. All rights reserved.
#
# This file is part of FireANTs, distributed under the terms of
# the FireANTs License version 1.0. A copy of the license can be found
# in the LICENSE file at the root of this repository.
#
# IMPORTANT: This code is part of FireANTs and its use, reproduction, or... |
9dfbeb148182879707e4d50b4a08ab42809c87179044093fcaae237a2dfc2538 | Python | 7,416 | 232 | # coding=utf-8
# Copyright (c) 2021, NVIDIA CORPORATION. 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 re... |
fdd1e7a3e15ea49629b1f87d0e7490127b79eb477d83c3f900ef5c2b81be281f | Python | 7,416 | 227 | """
Support for reading and writing the `AXT`_ format used for pairwise
alignments.
.. _AXT: http://genome.ucsc.edu/goldenPath/help/axt.html
"""
from bx import interval_index_file
from bx.align import (
Alignment,
Component,
src_split,
)
# Tools for dealing with pairwise alignments in AXT format
class ... |
1377684ddf54b29335fcbb8180c83fe9d9ea789fc5a4a7643b02df7d31f50f9a | Python | 7,418 | 177 | ######################################################################################################
### Script to compute the firing rate over time via fixed time windows from spike raster data; ###
### computes the firing rates for all subpopulations in an "equal overlap" paradigm ###
###########... |
34ba7ba655d2cd4d4b9d31f0e4914f2a4c4212db06759f1c8ad830ce1565a03f | Python | 7,419 | 170 | import os
import torch
import gc
import numpy as np
import matplotlib.pyplot as plt
from Bio.Phylo.TreeConstruction import DistanceMatrix, DistanceTreeConstructor
from Bio import Phylo
from scipy.ndimage import zoom, gaussian_filter
from scipy.stats import spearmanr, pearsonr, mannwhitneyu, false_discovery_control
from... |
1e9961587008feb5d9695d328fafcbc76c19bccd4454de88349fd541997e4b97 | Python | 7,420 | 152 | """Exports a YOLOv5 *.pt model to ONNX and TorchScript formats
Usage:
$ export PYTHONPATH="$PWD" && python models/export.py --weights yolov5s.pt --img 640 --batch 1
"""
import argparse
import sys
import time
from pathlib import Path
sys.path.append(Path(__file__).parent.parent.absolute().__str__()) # to run '$ ... |
29be60ad41d8aabe90c6e78eddcf8ae4f4f3c69462d418775134cf0b2d9b53b4 | Python | 7,421 | 167 | # Copyright (c) 2026 Rohit Jena. All rights reserved.
#
# This file is part of FireANTs, distributed under the terms of
# the FireANTs License version 1.0. A copy of the license can be found
# in the LICENSE file at the root of this repository.
"""Tests for the optional lite_lncc LNCC backend (loss_type='lite_lncc').
... |
523f46cfacb4d910fe398919bc214645a7eb2bfc8b492eca8fd25d6719d2d843 | Python | 7,421 | 225 | # Copyright (c) 2023 Khaleelulla Khan Nazeer, Anand Subramoney, Mark Schöne, David Kappel
#
# 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
#... |
30d4d62849e911318d180c9cac4784f7807de10ba7d6d2acdf7d8120f180dfe4 | Python | 7,422 | 177 | ######################################################################################################
### Script to compute the firing rate over time via fixed time windows from spike raster data; ###
### computes the firing rates for all subpopulations in an "equal overlap" paradigm ###
###########... |
1f12a9fa1dfa463aba96a0fc51f810bf7b84439f09588a1ada04597f25ddd76f | Python | 7,423 | 242 | from ..qt import *
from .. import thalamus_pb2_grpc
from ..observable_item_models import FlatObservableCollectionModel, TreeObservableCollectionModel, TreeObservableCollectionDelegate, get_selected_rows
from ..config import ObservableDict
from ..task_controller.util import create_task_with_exc_handling
import datetime
... |
c525df7e9db390d9016e56ad51c2cbec389666f4fb81b9b1597da03e488f6cf1 | Python | 7,429 | 282 | """Train DyNeMo on Nottingham movie data.
"""
print("Setting up")
import pickle
import numpy as np
import os.path as op
from os import makedirs
from osl_dynamics import analysis, data, inference
from osl_dynamics.models.dynemo import Config, Model
from osl_dynamics.utils import plotting
#%% Settings
# GPU settings
... |
823abbe5c3f5a66bc81ee35ed2d582b92a21abf0ef8a0ceb0d043ea1b38ad08f | Python | 7,435 | 241 | # Copyright (c) Meta Platforms, Inc. and affiliates. All Rights Reserved
import atexit
import functools
import logging
import sys
import uuid
from typing import Any, Dict, Optional, Union
from hydra.utils import instantiate
from iopath.common.file_io import g_pathmgr
from numpy import ndarray
from sam3.train.utils.... |
43158e6e0383f16c177f33ffd6769c470111842cb9e213e2b4b7077232aeafed | Python | 7,436 | 183 | # this python file is used to import, not for running directly
import os
import time
import cv2
import numpy as np
import torch
from .models.experimental import attempt_load
from .utils.datasets import LoadImages, LoadStreams
from .utils.general import (check_img_size, check_requirements,
n... |
06c2c318e765605d3d7612e414537982ebf86eb378ede9e6d4820384b77c90be | Python | 7,439 | 211 | import numpy as np
import tensorflow as tf
from tensorflow import keras as K
from tensorflow.keras import Model
from tensorflow.keras.layers import Dense
from tensorflow.keras import initializers
from tensorflow.keras.regularizers import l2
import custom_transform
from my_loss import MyLoss
from DFTlayer import DFTLay... |
0b36d14c3d193ac397080b96f4069329a1ce37301fc361a4ec7dbc1fdc7260e7 | Python | 7,439 | 199 | from .SampleAnnotation import SampleAnnotation
from .Genome import Genome
from .SampleParams import SampleParams
from .submodules import *
from .ExportCounts import ExportCounts
from drop import utils
from pathlib import Path
import wbuild
from snakemake.logging import logger
class DropConfig:
CONFIG_KEYS = [
... |
2da46f2c7a33e68f18f0aa81b1111bd329002d8435c9b265a41a249f806f6a23 | Python | 7,439 | 256 | """shufflenet in pytorch
[1] Xiangyu Zhang, Xinyu Zhou, Mengxiao Lin, Jian Sun.
ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
https://arxiv.org/abs/1707.01083v2
"""
from functools import partial
import torch
import torch.nn as nn
class BasicConv2d(nn.Module):
de... |
4804b961acc9839adaf47cad1db2c5154316f2dda4e36346d56eb32669845081 | Python | 7,440 | 153 | from torch.optim.lr_scheduler import MultiplicativeLR, SequentialLR as _SequentialLR, \
ReduceLROnPlateau as _ReduceLROnPlateau
from torch.optim import Optimizer
from typing import Union, Callable, List
import warnings
from bisect import bisect_right
from ..util.util import has_argument
__all__ = ['WarmUp', 'Sequ... |
40e87b022cb74fd500ba9e9de5c5c0681647a3a313400248d075af86a2a74f5e | Python | 7,445 | 236 | #!/usr/bin/python
import sys
import argparse
import numpy as np
import nibabel as nb
import logging
try:
from due import due, BibTeX
except ImportError:
# Adapted from
# https://github.com/duecredit/duecredit/blob/2221bfd/duecredit/stub.py
class InactiveDueCreditCollector(object):
"""Just a stub... |
820da7e5869a86abf23ed3777b7024915cd1b0c9f1be5506a10fd37ff94ee224 | Python | 7,445 | 257 | import atexit
import inspect
import json
import subprocess
import textwrap
import threading
import time
from collections.abc import Callable, Sequence
from dataclasses import dataclass
from functools import partial
from pathlib import Path
from typing import Any
import requests
from docs.doc_modules.experiments impor... |
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