sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
6486623b4aec66a964e46ba86b35040ec34b036bc19469a80b6e73332d21e888 | Python | 4,070 | 120 | import numpy as np
# Colours and types
Types = np.array(["T4", "T5"])
Type_colours = np.array(["#17becf", "#ff7f0e"])
Subtypes = np.array(["T4a", "T4b", "T4c", "T4d", "T5a", "T5b", "T5c", "T5d"])
Subtype_colours = np.array(
[
"#1f77b4",
"#9edae5",
"#98df8a",
"#bcbd22",
"#d6... |
af8231f337507021c3a2c2408c18c20bbcc30beb94b5ec9dd316391082729276 | Python | 4,070 | 136 | import os
import sys
import argparse
from pathlib import Path
import numpy as np
import matplotlib.pyplot as plt
# Parse command-line arguments
parser = argparse.ArgumentParser(description='Compute Directional Index (DI) from fMRI forecasting model')
parser.add_argument('--method', type=str, default='flow', choices=['... |
f4807c538d86bc94b0f1bcbcf8f7634038380d441673b671c8ab554fc89239ff | Python | 4,070 | 114 | #!/usr/bin/env python
#
# Copyright 2007, 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... |
5e76b2d37ec785e10145a77a18bd085324479442bded599871d193d55179d1cd | Python | 4,071 | 113 | import warnings
import numpy as np
from anndata import AnnData
from pandas.api.types import CategoricalDtype
from scvi import settings
from scvi.data._utils import _make_column_categorical, _set_data_in_registry
from ._dataframe_field import CategoricalObsField
from ._mudata import MuDataWrapper
class LabelsWithUn... |
876749dc0109384d0202a702f2e49a4a59446f8ebee0a60f41aa1603a4bf5cf3 | Python | 4,072 | 122 | import numpy as np
# Colours and types
Types = np.array(["T4", "T5"])
Type_colours = np.array(["#17becf", "#ff7f0e"])
Subtypes = np.array(["T4a", "T4b", "T4c", "T4d", "T5a", "T5b", "T5c", "T5d"])
Subtype_colours = np.array(
[
"#1f77b4",
"#9edae5",
"#98df8a",
"#bcbd22",
"#d6... |
726cf78950cb52678cb0b035d2bd07b43e0fcb5f520d952ac34fe19d4fc62729 | Python | 4,075 | 111 | #!/usr/bin/env python3
"""Compare isolated current and 1.6.5 combination-matrix runs."""
from __future__ import annotations
import argparse
import json
from datetime import datetime, timezone
from pathlib import Path
try:
from .common import compare_csv
except ImportError:
from common import compare_csv
de... |
e097b263b539fa53934be48fc15f1f90df026a2410ea9fa5e9c34730614b6bfa | Python | 4,075 | 167 | """Common API for torch and numpy backends."""
from copy import deepcopy
import numpy as np
from skbase.utils.dependencies import _check_soft_dependencies, _safe_import
from pgmpy import config
torch = _safe_import("torch")
def _is_torch_tensor(obj):
if not _check_soft_dependencies("torch", severity="none"):
... |
26bee165eafdd1618861d8096cff8d058c8df8f4365a549686f35e9a094ee296 | Python | 4,076 | 143 | import matplotlib.pyplot as plt
import glob, os
from pathlib import Path
import pathlib
import numpy as np
from matplotlib.lines import Line2D
import matplotlib.patches as mpatches
# from scipy.interpolate import make_interp_spline, BSpline
import matplotlib.lines as mlines
import pandas as pd
import scipy as sp
import... |
e2417aef8a71ef40717933e351c62975d5cfd780ad6feb6129ad9c1acf58f429 | Python | 4,076 | 135 | from scipy.s
def nn_PMFs(ax, group, df, x0, x1, n_bins, n_boots):
"""Nearest neighbour PMF plot"""
# get data arrays
a = df.loc[df.Subtype == group + "a", ["Root_x", "Root_y", "Root_z"]]
b = df.loc[df.Subtype == group + "b", ["Root_x", "Root_y", "Root_z"]]
c = df.loc[df.Subtype == group + "c", ["R... |
0fba3be193fbdc9361adab67fbaf5ec3d1059d4cddfea5de7d2b2b1614e51d39 | Python | 4,077 | 99 | import pandas as pd
import numpy as np
from neuron import h
import simulator.model.saveClass as sc
import simulator.model.simulation as simulation
from simulator.model.ca1_model import CA1
from simulator.model.ca1_functions import init_activeCA1, addClustLocs, genRandomLocs, add_syns
from simulator.model.sim_functions... |
f134b1f202966f4b0b8685406f143c44537d4b698e8d7966ef512b92a17c93b1 | Python | 4,077 | 110 | """
moosez label -> standardized coding for DICOM Segmentation (DICOM SEG).
The mapping is sourced from the curated table ``moose_snomed_mapping.csv`` that
ships next to this module, and is exposed as the module-level dictionary
``moose_to_snomed`` (keyed by moosez label name).
Compared with the previous hand-maintai... |
61f5b6e94185312fe576b9ea7121a9ebb15513e17b0cb6a88e567bedd637185f | Python | 4,078 | 109 | from __future__ import annotations
from typing import TYPE_CHECKING
import torch
if TYPE_CHECKING:
from collections.abc import Callable, Iterator
from typing import Any
from torch import Tensor
from ._module import NicheLossOutput
def compute_composition_error(
module: Callable[[dict[str, Ten... |
b1cd8ec0455f5d165e5a5914dfc8353709558799940f1c2afc12e8c99cbdcf6d | Python | 4,079 | 132 | import logging
import pandas
import numpy
from numpy import dot as d
from scipy import stats
from .. import Constants
from .. import Exceptions
from ..PredictionModel import WDBEQF, WDBQF
class ARF(object):
"""Association result format"""
GENE = 0
ZSCORE = 1
EFFECT_SIZE = 2
SIGMA_G_2 = 3
N_SN... |
05b930d0f160695ace5985d3ae5a6c656e2643ed731541a18fda02c3b23a843f | Python | 4,080 | 117 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import os
import numpy as np
import torch
import CBIG_pMFM_basic_functions as fc
def CBIG_mfm_test_desikan_main(gpu_index=0, weight=0.5):
'''
This function is to implem... |
eb1acd6c39577ff251a4e84478bc349c49c9bb503b7c3b8acc9ee46ece9b309d | Python | 4,080 | 102 | import os
from pathlib import Path
import pandas as pd
from numcodecs import Blosc
#set this for multiple processing
Blosc.use_threads = False
#distributed processing of masks
import dask
from dask.distributed import Client
from WSIAnnotation import WSIAnnotation
from ROIAnnotation import ROIAnnotation
def dask_ag... |
46c64b73387689021d09a67969f3b6c06ddbdfea7f061db097bca97bbe97cf86 | Python | 4,081 | 99 | #!/usr/bin/env python
"""Compare pattern-similarity maps to Neurosynth meta-analytic maps (R6, Fig 5).
Correlates each condition's parcel z-map (from run_neural_pattern_sim.py) with the
auditory / sensorimotor / language / default Neurosynth association maps, and
reports, for every condition x term:
r = Pear... |
90d1fd3718ffed5a9c14df175e2398c72c0fc363a0510aba81842c91ef37b546 | Python | 4,084 | 180 | from enum import Enum
from torch import nn
class TrainMode(Enum):
# manipulate mode = training the classifier
manipulate = 'manipulate'
# default trainin mode!
diffusion = 'diffusion'
# default latent training mode!
# fitting the a DDPM to a given latent
latent_diffusion = 'latentdiffusion... |
f377bb61b00c87f5938e0fbbd907f72fa1e8433cd47261d877cda4f374275720 | Python | 4,084 | 112 | import networkx as nx
from pgmpy.base import DAG
from pgmpy.identification import Adjustment, BaseGraphicalIdentification
from pgmpy.utils.sets import _powerset
class Frontdoor(BaseGraphicalIdentification):
"""
Given a causal graph, finds the set of variables satisfying frontdoor criterion.
Given a caus... |
7df3dec3018d90f4f988f7d9dd794eb9055bdf68a7ebc897f8a7237331ddda9d | Python | 4,085 | 79 | import numpy as np
from mot.sample.base import AbstractRWMSampler
from mot.lib.kernel_data import Array
__author__ = 'Robbert Harms'
__date__ = '2018-08-14'
__maintainer__ = 'Robbert Harms'
__email__ = 'robbert@xkls.nl'
__licence__ = 'LGPL v3'
class FSLSamplingRoutine(AbstractRWMSampler):
def __init__(self, ll_... |
227df2d0021178410ace47b2d3afa16bde6fa0908391b1569c5937a6204de5bf | Python | 4,086 | 95 | from abc import ABC, abstractmethod
from typing import Type
import numpy as np
from numpy import number
class ImageNormalization(ABC):
leaves_pixels_outside_mask_at_zero_if_use_mask_for_norm_is_true = None
def __init__(self, use_mask_for_norm: bool = None, intensityproperties: dict = None,
... |
c3ef9003d7844977770148d797f4523c13cb34d68c4284400aa295dd38ffce90 | Python | 4,086 | 82 | #!/usr/bin/env python3
"""A simple tool to generate a bed file that tiles a genome."""
import argparse
import pybedtools
import pysam
from bpreveal import logUtils
from bpreveal import bedUtils
def getParser() -> argparse.ArgumentParser:
"""Generate the parser."""
ap = argparse.ArgumentParser(
descrip... |
20ad71d927eba3af6bf6496bcf9434ea9f03052459bb0a618929b7e189187b0f | Python | 4,087 | 138 | # -*- coding: utf-8 -*-
"""
Created on Sat Aug 3 11:43:24 2019
@author: 俊男
"""
# In[] Define the Class for Checking Linear Regression Assumption
import matplotlib.pyplot as plt
import scipy.stats as stats
from pandas.plotting import autocorrelation_plot
import pandas as pd
import seaborn as sns
import numpy as np
c... |
8004322da26bbb0bfd7023ca35008a435787f7799248a04a1b6436b6e7db0893 | Python | 4,089 | 124 | import os
import numpy as np
import pytest
from scvi.data import synthetic_iid
from scvi.model import AmortizedLDA
@pytest.mark.parametrize("n_topics", [5])
def test_lda_model_single_step(n_topics: int):
adata = synthetic_iid()
AmortizedLDA.setup_anndata(adata)
mod1 = AmortizedLDA(adata, n_topics=n_topi... |
f6eea02da3d52b44fc99f6978e19a840217f29696052348e3e6da06c439b2d77 | Python | 4,089 | 104 | import re
import os
import logging
import numpy
from .Genotype import GF
from .. import Utilities
from ..misc import Genomics
class DTF:
"""Format of dosage"""
CHR = 0
ID = 1
POSITION = 2
ALLELE_0 = 3
ALLELE_1 = 4
FREQ= 5
FIRST_DATA_COLUMN = 6
def dosage_file_geno_lines(file, variant... |
0eb5fe9a447395b1a41935fe525e901c33be73f665dff34197de795f07e64602 | Python | 4,090 | 135 | from scipy.spatial import
def nn_PMFs(ax, group, df, x0, x1, n_bins, n_boots):
"""Nearest neighbour PMF plot"""
# get data arrays
a = df.loc[df.Subtype == group + "a", ["Root_x", "Root_y", "Root_z"]]
b = df.loc[df.Subtype == group + "b", ["Root_x", "Root_y", "Root_z"]]
c = df.loc[df.Subtype == gr... |
bce7a4c5b2bde652fb60e3b112904a6adc87365b58a245d5aa9733cf6e597ec6 | Python | 4,090 | 129 | import os
import sys
# Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Project information -----------------------------------------------------
# https://www.sp... |
8aac789e72a43928bd4a9a819e9aef80310f707908fde400ca5e09fcc2995942 | Python | 4,091 | 118 | # 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.
from collections import Counter
from typing import List
import torch
def align_bpe_to_words(roberta, bpe_tokens: torch.LongTensor, other_to... |
faa35eda60572c4cd3cc817ed91565d964ec2149085bff0f417ff5b5ef69226c | Python | 4,091 | 118 | #
# Copyright 2017-2023 Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000 with
# Sandia Corporation, the U.S. Government retains certain rights in this software.
#
# See LICENSE for full license details
#
import numpy as np
import time
import os
# Use this file to produce a list of ADC (min... |
016184a0d165197cf90059de650304522720a11b36bab13468e83536b9c87b39 | Python | 4,092 | 110 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import torch
import torch.nn as nn
from tractseg.libs.pytorch_utils import conv3d
from tractseg.libs.pytorch_utils import deconv3d
class UNet3D_Pytorch_DeepSup_sm(torch.nn.Module):
def __init__(self, n_... |
3d2a81dbd4171d4619bad4a46eaf13387fd38a5f755fa26d706e42a3a2e85235 | Python | 4,092 | 121 | """Configuration for deployment-oriented logit knowledge distillation."""
from __future__ import annotations
from dataclasses import asdict, dataclass, field
from typing import Any, Dict, List, Optional
import yaml
@dataclass
class DistillationConfig:
"""Configuration consumed by :class:`DistillationTrainer`.
... |
93aea995c71599c461f9e607e79980d87df0eecb9014346ed161701640fb80f0 | Python | 4,095 | 136 | import logging
import pandas
from patsy import dmatrices
import statsmodels.api as sm
from .. import Exceptions
class Context(object):
def __init__(self): raise Exceptions.ReportableException("Tried to instantiate abstract Multi Tissue PrediXcan context")
def get_genes(self): raise Exceptions.NotImplemented... |
389d7dabf1794f52ea06e071a0322dd36f49b358cf32abe4072f2954a636778a | Python | 4,096 | 115 | #!/usr/bin/env python
"""Example of displaying interactive image-to-image "inference" results.
shift+mousedown0 triggers the inference result to be computed for the patch
centered around the mouse position, and then displayed in neuroglancer.
In this example, the inference result is actually just a distance transfor... |
42b65f62db3ab2fe0b45fee29e868ff07f6430fe05a100cb3c333b4b8d65d537 | Python | 4,096 | 135 | from scipy.spatial import KDTree
def nn_PMFs(ax, group, df, x0, x1, n_bins, n_boots):
"""Nearest neighbour PMF plot"""
# get data arrays
a = df.loc[df.Subtype == group + "a", ["Root_x", "Root_y", "Root_z"]]
b = df.loc[df.Subtype == group + "b", ["Root_x", "Root_y", "Root_z"]]
c = df.loc[df.Subtype... |
63149036a08249ea51f370bb524324cbe44df558c054a2036892180646333f44 | Python | 4,098 | 113 | # @license
# Copyright 2020 Google Inc.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in... |
0b7e80a4fd3845a44243e51768cfdfb11a0d7bb713e442f4dcfe6465f4a39d75 | Python | 4,099 | 117 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import os
import numpy as np
import torch
import CBIG_pMFM_basic_functions as fc
def CBIG_mfm_test_desikan_main(gpu_index=0):
'''
This function is to implement the test... |
9090fbeef0d2c23356bf588986ae2562d17f1fd01ba55a805bc01405365499f1 | Python | 4,100 | 96 | # -*- coding: utf-8 -*-
"""
.. _tutorial01_ref:
Tutorial 1: Quick Start
=======================
This tutorial gives a quick overview of ``surfplot`` before diving into more
detail in subsequent tutorials. The aim here is to get a flavour of how
``surfplot`` works and what can be plotted.
Getting surfaces
---------... |
6d0b9abd8b8ebd484649f3564b93b019cd0949dae5ff4cdb38935f79a99abd72 | Python | 4,103 | 135 | # 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 librosa
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
import torchaudio
EMBEDDER_PARAMS... |
90e7b26efa0f988115b8ee9782ed46c6e5aa621d00c08b6e2cb2e0cf0fd0fab4 | Python | 4,103 | 117 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import os
import numpy as np
import torch
import CBIG_pMFM_basic_functions as fc
def CBIG_mfm_test_desikan_main(gpu_index=0):
'''
This function is to implement the test... |
15af72f1452be6de9cd0b21733290f9a07c4b5793037618b73d6e169f0a327b3 | Python | 4,105 | 101 | # 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 fairseq import utils
from fairseq.criterions import register_criterion
from fairseq.criterions.label_smoothed_cross_entropy ... |
2cf21d9a24afedfc7a8626a2b275e28b3a6c6534a590c0f3a69efd7a8f5e766a | Python | 4,105 | 117 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import os
import numpy as np
import torch
import CBIG_pMFM_basic_functions as fc
def CBIG_mfm_test_desikan_main(gpu_index=0):
'''
This function is to implement the test... |
9e9327e335ea5eb7da63644f63b56836e26ab99c9366c5c9db2f6a02d7e04ab7 | Python | 4,105 | 117 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import os
import numpy as np
import torch
import CBIG_pMFM_basic_functions as fc
def CBIG_mfm_test_desikan_main(gpu_index=0):
'''
This function is to implement the test... |
7e205a2dc58e67891ed82570c94c068b033849d0400d8fe5be4323e813d44d2c | Python | 4,106 | 129 | # Copyright 2015 Google Inc. 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 applicable law or a... |
fbd44be878693fb3aa27476a9ce9b6eeab6ec0dfcbc974b0a2843f4136dfed8c | Python | 4,106 | 120 | # Originally from Microsoft Corporation.
# Licensed under the MIT License.
""" Wrapper for ngram_repeat_block cuda extension """
import math
import warnings
from typing import List
import torch
from torch import nn
try:
from fairseq import ngram_repeat_block_cuda
EXTENSION_BUILT = True
except ImportError:
... |
0fe6d247e9498de9b28296b207b343d9ba76cabb8e3c3616e415610a368bc2c0 | Python | 4,109 | 117 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import os
import numpy as np
import torch
import CBIG_pMFM_basic_functions as fc
def CBIG_mfm_test_desikan_main(gpu_index=0):
'''
This function is to implement the test... |
4781a369ea5a1d3981ffd73c98e3322e70829308335d6d05c5bf7574fed5ba46 | Python | 4,109 | 117 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import os
import numpy as np
import torch
import CBIG_pMFM_basic_functions as fc
def CBIG_mfm_test_desikan_main(gpu_index=0):
'''
This function is to implement the test... |
be3d04810e7af4b30d43410f26d255b1f649a626658bf06e2cc8f7e953dff86b | Python | 4,110 | 82 | """A wrapper around the ushuffle C implementation."""
import threading
import numpy as np
from bpreveal.internal import libushuffle
from bpreveal.internal.constants import ONEHOT_AR_T
# The ushuffle implementation in C makes heavy use of global variables.
# To avoid multiple threads trampling over each other and causi... |
62eac885202f6c489331b630f7f93c370aebf88f7697b0a4ff61cf53a090c778 | Python | 4,113 | 117 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import os
import numpy as np
import torch
import CBIG_pMFM_basic_functions as fc
def CBIG_mfm_test_desikan_main(gpu_index=0):
'''
This function is to implement the test... |
792d28dc740f2289197cfe5b7ff7a51b25ab6aef33cc0014ab5c2d3da7b03869 | Python | 4,113 | 118 | """Deprecated GPN-MSA model definitions for inference compatibility."""
from typing import Any
import torch.nn as nn
from jaxtyping import Float, Int, Num
from torch import Tensor
from transformers import PreTrainedModel, RoFormerConfig
from transformers.modeling_outputs import BaseModelOutput, MaskedLMOutput
from tr... |
cbc78e7f6b377bfc5a4fa85d2113f908a4bf174d204c50f655026da03a5b5898 | Python | 4,113 | 117 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import os
import numpy as np
import torch
import CBIG_pMFM_basic_functions as fc
def CBIG_mfm_test_desikan_main(gpu_index=0):
'''
This function is to implement the test... |
d85c3c49dcf38d24a23c6748cdf13625e78b4c69277075c09c94e991a6512cfb | Python | 4,114 | 111 | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... |
0efae07f115c8edb17ef7d3702c38b83f574f1b70b47ca3c4f50963b35762b2a | Python | 4,115 | 108 | import os
import pandas as pd
from config_path import GENE_PATH
from os.path import join, dirname, exists
current_dir = dirname(__file__)
processed_dir = 'processed'
data_dir = 'external_validation'
processed_dir = join(current_dir, processed_dir)
data_dir = join(current_dir, data_dir)
if not exists(data_dir):
o... |
3b7e5ddcfdac055d9c5abd4bdc0d79706fdbb67280157f7306bbe76d1f031963 | Python | 4,115 | 117 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import os
import numpy as np
import torch
import CBIG_pMFM_basic_functions as fc
def CBIG_mfm_test_desikan_main(gpu_index=0):
'''
This function is to implement the test... |
48300cfe5df3dd6ceb69cf35bb7afe3c8de7c82b80ccd0749ec48dfb0ef61268 | Python | 4,115 | 136 | from scipy.spatial import KDTree
import numpy as np
def nn_PMFs(ax, group, df, x0, x1, n_bins, n_boots):
"""Nearest neighbour PMF plot"""
# get data arrays
a = df.loc[df.Subtype == group + "a", ["Root_x", "Root_y", "Root_z"]]
b = df.loc[df.Subtype == group + "b", ["Root_x", "Root_y", "Root_z"]]
c ... |
583abb58a682509a6c113a75741d8a5c0afd5e45c96bd82cb5f11ea5a9214d87 | Python | 4,115 | 117 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import os
import numpy as np
import torch
import CBIG_pMFM_basic_functions as fc
def CBIG_mfm_test_desikan_main(gpu_index=0):
'''
This function is to implement the test... |
993d46efed23a41107c4741414c1fd436f9e36c456647d2f8bff21168275ae0e | Python | 4,115 | 117 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import os
import numpy as np
import torch
import CBIG_pMFM_basic_functions as fc
def CBIG_mfm_test_desikan_main(gpu_index=0):
'''
This function is to implement the test... |
f061db46d558a20c877728585af60201f062408ae0bfeb2e98b2d046830b8709 | Python | 4,115 | 117 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import os
import numpy as np
import torch
import CBIG_pMFM_basic_functions as fc
def CBIG_mfm_test_desikan_main(gpu_index=0):
'''
This function is to implement the test... |
fbb34db5908f232ce6f3d5567f33f88e0bb3451326b8d95194a710979802631c | Python | 4,115 | 112 | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... |
5275b7cd7e91613aad6bf7fce58ac946350f8a72e45e2ed2e3c00d46a7351950 | Python | 4,116 | 114 | import numpy as np
import torch
import pytest
from pathlib import Path
from neurovfm.pipelines.preprocessor import StudyPreprocessor
import neurovfm.pipelines.preprocessor as preproc_mod
import neurovfm.data.io as io_mod
import neurovfm.data.preprocess as pp_mod
@pytest.fixture(autouse=True)
def _patch_io_and_prepr... |
c1db097c21e63617de1024ca86ce2b1ad91cdf29cb37b84575512fb8c07e989c | Python | 4,116 | 122 | from __future__ import annotations
from typing import TYPE_CHECKING
from typing import ClassVar
from cleo.helpers import argument
from cleo.helpers import option
from poetry.core.version.exceptions import InvalidVersionError
from poetry.console.commands.command import Command
if TYPE_CHECKING:
from cleo.io.inp... |
fa016b84fe300b5fd05e94e235b883579c37c163b757706e723a7a40c93ae189 | Python | 4,116 | 89 | import os
import csv
import subprocess
from concurrent.futures import ThreadPoolExecutor
import time
# Function to run DrugReAlign.py for each PDB entry
def run_drugrealign(pdb_name):
try:
# Run the DrugReAlign.py script with the PDB name as an argument
subprocess.run(['python', 'DrugReAlign.py', '-... |
2485c36f871da1ddccd7d2078dc9d6314af9700bded5a74857ec1d26d2c3d8ae | Python | 4,117 | 138 | from scipy.spatial import KDTree
import numpy as np
def nn_PMFs(ax, group, df, x0, x1, n_bins, n_boots):
"""Nearest neighbour PMF plot"""
# get data arrays
a = df.loc[df.Subtype == group + "a", ["Root_x", "Root_y", "Root_z"]]
b = df.loc[df.Subtype == group + "b", ["Root_x", "Root_y", "Root_z"]]
... |
ae39021d21884ceed64ef6056352e02f0aeedc96b95813f13c0d93f61c32caa3 | Python | 4,119 | 97 | from ... import options as opts
from ... import types
from ...charts.chart import Chart
from ...globals import ChartType
class TreeMap(Chart):
"""
<<< TreeMap >>>
TreeMap are a common visual representation of "hierarchical data" and "tree data".
It mainly uses area to highlight the important nodes in... |
78c1e1d3a36a1ef2a0e28f171c4aeb385aba178adfc2c77d099740fdbcc1cec7 | Python | 4,122 | 114 | """Align embeddings using Procrustes method
"""
import numpy as np
def match_coords(C1, C2):
idx = []
idxlist = range(C2.shape[0])
for pt1 in C1:
idxremain = np.setdiff1d(idxlist, idx)
idxmatch = np.argsort(np.sum((C2[idxremain, :] - pt1) * (C2[idxremain, :] - pt1), axis=1))[0]
id... |
febb7637733623a640206489d7c89bc38a74faa08881dbcc79cae8294a5f5bd8 | Python | 4,122 | 137 | import json
import logging
import os
import urllib
import xml.etree.ElementTree as ET
from collections.abc import Iterable
import pandas as pd
import xmltodict
from Bio import Entrez
from tqdm import tqdm
import config
Entrez.email = config.entrez_email
references = pd.read_csv(config.references_file)
logging.basi... |
243744cfa624a48460d70f7b5e6964b4e8bf78b2600692f0d76e7e734fa9d227 | Python | 4,124 | 115 | import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
"""
This script summarizes how many independent components are found
across a population of chromatophores. It loads the combined ICA output file,
extracts a single component count for each chromatophore, and builds a clean
distribution of how many... |
c92403ec7d62d953aec73f83abb2560c0e0bc6064101c06014e3ef38b345cc8d | Python | 4,129 | 94 | import numpy as np
from common.utils import _arctanh_tanh_converter, _log_exp_converter
class UnivariateParams_obsolete(object):
def __init__(self, pi, sig2_beta, sig2_zeroA):
self._pi = pi
self._sig2_beta = sig2_beta
self._sig2_zeroA = sig2_zeroA
self._validate()
def copy(sel... |
d6606eed1034473de5f9dc4e48e742a802ef1a83f63515b7d20172ff26a29b96 | Python | 4,129 | 95 | """Controller for static behaviour settings and visibility toggles."""
from __future__ import annotations
import logging
from src.data.behaviour_settings_io import save_behaviour_static_inputs
from src.persistence.app_paths import config_file_path
logger = logging.getLogger(__name__)
class BehaviourStaticInputsSe... |
5d11f0aa84003256c157a63e362e46923663bf8b5269143ac38c57fdb5bf2033 | Python | 4,130 | 106 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
import unittest
from tempfile import TemporaryDirectory
from fairseq import options
from fairseq.binarizer import FileBinarizer, Vo... |
65f7dc2cafaa856a273390988fe37ec8da50e4cfecac889c7781faf699628f79 | Python | 4,132 | 88 | """
============================================================================
fig03or_perfusion_channel_split_merge__fig_3o-r_local_perfusion_eeb3073b.py — Fig 3r perfusion
============================================================================
What this script does: Jython for ImageJ: 3-channel deinterleave/m... |
f26d0f6c1b7d87b5a1a36578fb5ae60cbfe5ec89cb636cc9168f62d6d40e61d5 | Python | 4,137 | 116 | import torch
import torch.nn.functional as F
import torch.nn as nn
import torch.optim as optim
import matplotlib.pyplot as plt
import numpy as np
from scipy.io import savemat
from .math import fft, ifft, conv_fft, wrap_phase, calculate_psnr
from .math import nm, um, mm, cm, m
from .light import Light
from .propagator i... |
8fd779d13ec0dbd8c1d94770603985dd16bf1bf0e999addfd143fe186b03228d | Python | 4,138 | 100 | """Shared statistics helpers.
All permutation / z / FDR math is transcribed verbatim from the original scripts
(`pattern_similarity/utils.py`, `paper_revision_analyses/emotion_ratings_specificity.py`,
`format_parcel_results/parcels_to_brain_fdr_revision.py`). The only change is that
stochastic helpers take an explicit... |
1642d4b6db3522b7105839636ac0cb4bb9bc5553877a0964cd9743221ff6c34e | Python | 4,140 | 121 | """Shared cell morphology metrics: area, convexity, elongation.
Works on integer instance segmentation maps (0 = background, 1..N = cell IDs).
Uses ``cv2`` for contour extraction and ``numpy`` for covariance eigenvalue analysis.
"""
from __future__ import annotations
from typing import Dict, List, Tuple
i... |
a950dc8b6aa2bb933e4a94693fc59a3cfbb1f71ec0e04c7ab2de69d5f32740df | Python | 4,140 | 123 | # 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 unittest
import tests.utils as test_utils
import torch
from fairseq.data import (
BacktranslationDataset,
LanguagePairDataset,... |
0b5353c1ad1cac94e202add12eb5175b3c604efd59bc7f22b763441c6c5c8228 | Python | 4,141 | 79 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'runtime_settings_dialog.ui'
#
# Created by: PyQt5 UI code generator 5.10.1
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_RuntimeSettingsDialog(object):
def setupUi(self, Ru... |
3bf8952a95fba014bbc5e0f7233660bed0cbe865f990b7f113701246260016fd | Python | 4,141 | 108 | #!/usr/bin/env python3
"""Compara as referencias atomicas recem-calculadas com as versionadas.
Existe para fechar a divida de procedencia: os rotulos de cristal de 2026-07-26
vieram do CENAPAD, mas as referencias atomicas corrigidas (caixa de 16 A,
SCF.Mix hamiltonian) foram medidas na estacao local. Onde ha comparaca... |
c45f0df64e26e3cbff8e918e39c255b432eaacd0769ce8b90341f72a56cb3572 | Python | 4,142 | 109 | """Normalize and validate the Windows GPU DLL layout after PyInstaller.
PyQt6-Qt6 6.9.1 ships legacy MSVC runtime copies in Qt6/bin. They conflict
with the newer official runtime collected by PyInstaller at _internal root and
cause PyTorch c10.dll to fail initialization with WinError 1114.
"""
from __future__ import... |
564126d469a87b535cd3ecf0ebe26b620515d8f62f389c41fbef91a780a4cdd4 | Python | 4,143 | 131 | """ This python file contain utility functions to use embeddings.
author: Vishnu Vardhan Dadi
credits: [Leyla Jael Castro, Dietrich Rebholz-Schuhmann]
copyright: GENERAL PUBLIC LICENSE Version 3, 29 June 2007
maintainer: Vishnu Vardhan Dadi, Lukas Geist
"""
import os
import warnings
import pickle as pkl
from typing ... |
603c26fc3d8613c4ec4e106a636e2062cec28102370277716799cd12b5d6bf33 | Python | 4,143 | 120 | # 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.
"""
Linformer: Self-Attention with Linear Complexity
"""
import logging
import torch
from fairseq import utils
from fairseq.models import reg... |
788c7a5a9311126a781969f3933a5068f81e082794f7c19e55859518834d4ec9 | Python | 4,143 | 106 | # coding=utf-8
# Copyright 2010, The T5 Authors and HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... |
95333fdf6e1d5d0ca4f34297d2339bba324762d3e9802ec93d3428b3db8e92ba | Python | 4,144 | 107 | # coding=utf-8
# Copyright 2010, The T5 Authors and HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... |
97da3d254e383a463bace74fdd49b82fde29a04674de3d80522ee9287f6a1a49 | Python | 4,145 | 125 | import os
import pandas as pd
import numpy as np
from neuron import h
def measure_AMPA_current(model):
"""
Measures AMPA receptor-mediated synaptic currents.
Parameters:
model (object): The NEURON model containing a list of AMPA synapses (`AMPAlist`).
Returns:
tuple:
- AM... |
d8487e191523194d19b74f76b831605333de0332a3b80184991dd2eac2493664 | Python | 4,145 | 98 | from abc import ABC, abstractmethod
from typing import Type
import numpy as np
from numpy import number
class ImageNormalization(ABC):
leaves_pixels_outside_mask_at_zero_if_use_mask_for_norm_is_true = None
def __init__(self, use_mask_for_norm: bool = None, intensityproperties: dict = None,
... |
e485a90e6af521938c9f7aa307dd78bafaadff78249b654c21299ba297a67fc0 | Python | 4,148 | 106 | # Copyright 2021 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
e87801900d172d8076ca38d902a7086333b8b988e2cac79d8ac4737254fd9157 | Python | 4,148 | 138 | from scipy.spatial import KDTree
import numpy as np
from .figure_ import ANOVAModel
def nn_PMFs(ax, group, df, x0, x1, n_bins, n_boots):
"""Nearest neighbour PMF plot"""
# get data arrays
a = df.loc[df.Subtype == group + "a", ["Root_x", "Root_y", "Root_z"]]
b = df.loc[df.Subtype == group + "b", ["Roo... |
3c3ebe08fef812c2bdf3e0b6074e333da199f8a94a8e39ff2b16c8c3da4c765d | Python | 4,149 | 131 | # 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.
"""
Signal processing-based evaluation using waveforms
"""
import csv
import numpy as np
import os.path as op
import torch
import tqdm
from... |
0d93301f4985f7c2bbcad86d9ae0c03a10d39bccff3c4fdc5a944810e3580415 | Python | 4,150 | 120 | # 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 argparse
import unittest
import tests.utils as test_utils
import torch
from fairseq.sequence_scorer import SequenceScorer
class Test... |
002c8f557e7dd46223e34eaf6400b3e3379b7a8022405ed6d22fa10a66f36fab | Python | 4,151 | 120 | # -*- coding: utf-8 -*-
import pdb
import os
import glob
from multiprocessing import Pool
import sys
import glob
import time
import subprocess, re
import numpy as np
import pandas as pd
def run_command(cmd):
"""Run command, return output as string."""
output = subprocess.Popen(cmd, stdout=subproc... |
6f5d717258a6ab8c0e7c524524e723f4cbdc9bf85e93f0bacd91259a53052edf | Python | 4,151 | 125 | #!/usr/bin/env python
# ENCODE DCC MACS2 call peak wrapper
# Author: Jin Lee (leepc12@gmail.com)
import sys
import os
import argparse
from encode_lib_common import (
assert_file_not_empty, human_readable_number,
log, ls_l, mkdir_p, rm_f, run_shell_cmd, strip_ext_ta)
def parse_arguments():
parser = argpa... |
bbcb3ffdb49b14a86e854ac898b1d20456687d0222f56133aa7bae6703d2fd20 | Python | 4,151 | 139 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import os
import numpy as np
import scipy.io as sio
from sklearn.mixture import GaussianMixture
def CBIG_pMFM_fitmodel_empirical():
'''
This function is to implement th... |
287877bbb0d391fe7eaa81d55731a222b423f0d852c4be6b46e2214b39dd3143 | Python | 4,152 | 138 | from scipy.spatial import KDTree
import numpy as np
from .paper_ANOVA import ANOVAModel
def nn_PMFs(ax, group, df, x0, x1, n_bins, n_boots):
"""Nearest neighbour PMF plot"""
# get data arrays
a = df.loc[df.Subtype == group + "a", ["Root_x", "Root_y", "Root_z"]]
b = df.loc[df.Subtype == group + "b", [... |
6d0099d905268c59e6b4747b5bb6d7064166c026df9cd27939c50fc484a9e8ca | Python | 4,153 | 138 | from scipy.spatial import KDTree
import numpy as np
from .figure_Tools import ANOVAModel
def nn_PMFs(ax, group, df, x0, x1, n_bins, n_boots):
"""Nearest neighbour PMF plot"""
# get data arrays
a = df.loc[df.Subtype == group + "a", ["Root_x", "Root_y", "Root_z"]]
b = df.loc[df.Subtype == group + "b", ... |
d30dd14532ce0e5ab06d80fc9527268d5d72ecfcff28189b96130f83bb584e6c | Python | 4,153 | 139 | # -*- coding: utf-8 -*-
"""
Created on Thu Feb 6 20:52:01 2025
@author: hanna
"""
# from datetime import datetime
import os
import pickle
import numpy as np
from tqdm import tqdm
def run_main_get_trial_inds(root_path, pickle_path, modes, dSubject):
#File path to save results.
# root_path = r'C:\Users... |
f603f8c30ed31cad95087b94a31b1eec2abc8f606294507b6f8ebf66685dab34 | Python | 4,154 | 138 | from scipy.spatial import KDTree
import numpy as np
from .figure_Tools import point_value
def nn_PMFs(ax, group, df, x0, x1, n_bins, n_boots):
"""Nearest neighbour PMF plot"""
# get data arrays
a = df.loc[df.Subtype == group + "a", ["Root_x", "Root_y", "Root_z"]]
b = df.loc[df.Subtype == group + "b",... |
f66c57cd5c62c5d172be784ee78519fa1286655fbd7bdc61fb99981c077516f1 | Python | 4,154 | 153 | #!/usr/bin/env python3
"""Sweep launcher for convenient reproduction of data for SymmNet paper figure
Runs dataset × algo × seed combinations.
Sequential run (default):
python sweep.py
Parallel run with 4 workers:
python sweep.py --n-workers 4
Subset example:
python sweep.py --datasets cifar10 --algos b... |
86ddaaa991fdeaa0a08d8641fb147e25b8adcd1dfc730ed0aeacf1e6130d3393 | Python | 4,155 | 100 | import csv
import tempfile
import unittest
from pathlib import Path
from GMXMMPBSA.exceptions import InputError, MMPBSA_Error
from GMXMMPBSA.membrane import (AUTOMATIC, calculate_parameters, diagnostic_paths,
needs_automatic_parameters, parse_atom_names,
... |
fdf9114137c73bacf6a98fa87848c053705b989c4c297c84cdc38f931a5c97aa | Python | 4,155 | 141 | from typing import Optional
import logging
from dataclasses import dataclass, field, fields
import torch
from torch import nn
import torch.nn.functional as F
logger = logging.getLogger(__name__)
class BaseClassifier(nn.Module):
def __init__(
self, in_features: int, mid_features: int | list[int] = 128
... |
6b9d973502e9dcb5d671cf43ee60a254a40614474b2b7f745c1f8ac7fe66e916 | Python | 4,161 | 96 | # call py.test from <PROJECT_ROOT> folder.
import os, sys
sys.path.append(os.getcwd())
import pandas as pd
import numpy as np
from scipy.sparse import coo_matrix
from precimed.common import libbgmg
import random
data = 'precimed/mixer-test/data'
_base_complement = {"A":"T", "C":"G", "G":"C", "T":"A"}
def _complement... |
dc33207b6878dda0d5bb543875fcbfdbaeb7ea1af62bdd3bae5dd9c06bfb0a7a | Python | 4,161 | 112 | import logging
import os
import anndata
import h5py
import numpy as np
import scipy.sparse as sp_sparse
from scvi.data._download import _download
logger = logging.getLogger(__name__)
def _load_brainlarge_dataset(
save_path: str = "data/",
sample_size_gene_var: int = 10000,
max_cells_to_keep: int = None... |
83417929feb87ef483488a4023bac343f097f60bf76b3a625eae7402cac39c91 | Python | 4,162 | 85 | from nnunetv2.dataset_conversion.generate_dataset_json import generate_dataset_json
from nnunetv2.paths import nnUNet_raw, nnUNet_preprocessed
import tifffile
from batchgenerators.utilities.file_and_folder_operations import *
import shutil
if __name__ == '__main__':
"""
This is going to be my test dataset for... |
dfbdcc0a837cbea121f1fd526fd7c80b13229a3e701d384b72d707b2aa25de72 | Python | 4,162 | 115 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import os
import numpy as np
import torch
import CBIG_pMFM_basic_functions as fc
def CBIG_mfm_test_desikan_main(gpu_index=0, subject=1):
'''
This function is to impleme... |
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