sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
9f7ec370dcee3501cf0f549f852dcf65222c4fe6c66424866c07e4ae404eb6be | Python | 4,994 | 125 | # source:https://github.com/zhuogege1943/dgc/blob/439fde259c/layers.py
# arxiv:https://arxiv.org/abs/2007.04242
import torch
import torch.nn as nn
import torch.nn.functional as F
class DynamicMultiHeadConv(nn.Module):
global_progress = 0.0
def __init__(self, in_channels, out_channels, kernel_size, stride=1,
... |
e4de91f7598a63ed350f7cc6677dfe92fff3fa24b4d80245ceabaa01819c199f | Python | 4,996 | 123 | """Featurize the GFN-FF-relaxed polymorphs with the OCE Wave-1.5 basis.
Reuses the validated builders:
data/build_features.py -> 1F, 2F, 3F, MAD, CT2F (features.npz)
data/perovskites/build_wave15 -> CT2F_A, MADCT2F, CT3F (features_wave15.npz)
MADCT2F uses the formal charges (A=+2, B=+4, O=-2) carried in ... |
4ce4c5d087a60db2ad9722514dba5f0edb82f6370e00ffbf9095db53099b8b5e | Python | 4,998 | 169 | # -*- coding: utf-8 -*-
import nibabel
import os
import sys
from glob import glob
from .utils import add_suffix, run_shell, run_matlab, TPL_PATH
class Realign(object):
def __init__(self, petPath, dataset, ignore):
self.dataset = dataset
self.ignore = ignore
self.petPath = petPath
... |
5bb991874caf8859d9615b26099376dd3a262df534e9f51c2473e67fcf204fef | Python | 4,998 | 198 | """Culture-collection accession shape, gating what a StrainInfo match may join.
`fix_missing_strains.py` is the only caller. `apiadapters.straininfo.
StrainInfoAdapterBase.retrieve_strain_models` joins a record StrainInfo
returns to whichever BRENDA strain shares its *first* matching designation,
with no organism cons... |
d91a9b7e399cab75a84b1418928a3f1391c5300f5125e4935580ab094a85345f | Python | 4,998 | 93 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'UI\AnimalWindow.ui'
#
# Created by: PyQt5 UI code generator 5.15.9
#
# WARNING: Any manual changes made to this file will be lost when pyuic5 is
# run again. Do not edit this file unless you know what you are doing.
from PyQt5 import QtCo... |
147b7d24703ea6b65cacdf428be95890f02532415348b4c1fdaa715516cda71e | Python | 5,000 | 128 | import os
import importlib
import numpy as np
import matplotlib.pyplot as plt
from sklearn.manifold import TSNE
import torch
import torchvision
from torchvision import datasets, transforms
from torch import nn, optim
from torch.utils.data import DataLoader
from torchvision.utils import save_image, make_grid
from tqdm i... |
90b02d258ebf4ff03c238cbeacf46aa03e00820171ab741628aae82726e3faa9 | Python | 5,000 | 153 | """
Utility functions for neurotransmitter analysis
Author: Yuan Zhang
Date: 2025-07-25
This module provides helper functions for:
- Generating surrogate brain maps using spatial null models (Burt2020 or Moran).
- Computing adjusted R² values for linear regression models.
- Performing spin-tests (permutation-bas... |
2f4618047878a2b67348d0167af34953ff59461825cbb21f2a8d3ac675ab4347 | Python | 5,002 | 146 | 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... |
3b312224ba7ad252178f481c40125a771ff7302ebfb30286196fbd40c6fb4aca | Python | 5,002 | 163 | # scSGL - a python package for fene regulatory network inference using graph signal processing based
# signed graph learning
# Copyright (C) 2021 Abdullah Karaaslanli <evdilak@gmail.com>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as pu... |
44668721616f969ce0f1adb77322181b2adcf77cf962cb5f111f82bd5ec6d523 | Python | 5,002 | 145 | # 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 contextlib
from typing import Optional
import torch
from fairseq.dataclass.configs import DistributedTrainingConfig
from fairseq.distr... |
7dd3e32276336a6479f639edf6adf53f1ba9c3cd65fe6552cdee41d93cba289f | Python | 5,002 | 136 | import torch
import torchvision.transforms as transforms
from torch.utils.data import DataLoader, Subset
from pipelines.dataloader import JacquardDataset
from modules.vgg16_baseline_even_longer import VGG16Baseline
from grasping_pvgg16_feedback_conn_4_2PC_even_longer_bb import PVGG16SeparateHP as PVGG16
import toml
fro... |
5a4ba8245a6dc3769a2e31fa20ba5910233ad0b389478319608cbbf0491117be | Python | 5,004 | 147 | #!/usr/bin/env python
import gzip
import os
import io
import string
import numpy
import pandas
from sqlalchemy import create_engine
#for reproducibility
numpy.random.seed(100)
sample_size = 100
def to_line(x):
return "{}\n".format("\t".join([str(_x) for _x in x]))
def variant_name(chrom, pos, a, b):
return... |
e7ad5dded041d726ecb799c78c0d134b14e248865a64abc5f2c0ce9d263858e1 | Python | 5,005 | 125 | import numpy as np
import os
from argparse import Namespace
from typing import Optional
import tqdm
from abc import ABC, abstractmethod
class BaseMSIToNumpy(ABC):
def __init__(self,
min_mz: Optional[float] = None,
max_mz: Optional[float] = None,
bins_per_mz: int = 1,
mz_... |
fd86aa12177520add66991614708eb0fff6b9965ea32406abf7c6134e48d3e75 | Python | 5,009 | 124 | from neuron import h
import numpy as np
## define the CA1 cell
class CA1(object):
def __init__(self):
h('xopen("simulator/model/CA1.hoc")')
propsCA1(self)
# self._geom()
self._topol()
self._biophys()
def _topol(self):
self.soma = h.soma
self.hill = h.hi... |
46e24866049f7a4be136a1b0fc14b8a70adc00201cee6c8d22026fe89093c51f | Python | 5,010 | 152 | # 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 itertools
import logging
import os
import numpy as np
from fairseq import tokenizer, utils
from fairseq.data import ConcatDataset, Dic... |
06ebbad9e2582698c187ab6c7d36cf09be197f70a7bdbf130927cf1b56aaa554 | Python | 5,013 | 139 | import os
import torch
import numpy as np
import pandas as pd
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import seaborn as sns
from torch_geometric.loader import DataLoader
from sklearn.metrics import mean_absolute_error, mean_squared_error
from scipy.stats import pearsonr
from tqdm impor... |
ad6d651ab8e7a05457d42e03e62016510a91eabd2c7d41af7c8426aa92cf7ec0 | Python | 5,014 | 128 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
from argparse import Namespace
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
import torch.nn.fu... |
9074aac0e2b908a001d1526b9eb2de168afb1eada5778578169f3e65cb948777 | Python | 5,015 | 136 | # 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 fairseq import utils
from fairseq.models import (
FairseqLanguageModel,
register_model,
register_model_architecture,
)
from f... |
515d2dbc215645ac16684211fc5dde03e3d9843c2e6ab069056eafaf9d7de204 | Python | 5,017 | 133 | """Command-line interface to create an initial Python sections file
Usage:
goatools wr_sections [GO_FILE]
goatools wr_sections [GO_FILE] [options]
Options:
-h --help show this help message and exit
-i <file.txt>, --ifile=<sections_in.txt> Read or Write file name [default: sec... |
4d13693afa6b81ee45e3a69232ae355b06e22ca4ad095389ba5e64e3a3bdccf1 | Python | 5,018 | 160 | from scipy.interpolate import griddata
from scipy.signal import correlate
import numpy as np
from .spike_ISI import *
def find_depth(template):
"""
Finds depth based on channel with maximum range.
"""
return np.argmax(np.max(template,0)-np.min(template,0))
def find_height(template):
... |
96b4faa7c6ce2a180ba3b5014e2e2ced1b96e405553325244a9cb9d943533066 | Python | 5,019 | 130 | from sfcn import SFCN
from monai.networks.nets import ResNet, ResNetBottleneck
import torch
from fdataset import FetalBrainDataset
from pathlib import Path
import random
import warnings
import torch.nn as nn
from math import sqrt
from torch.nn import functional as F
import numpy as np
import os
from torch.utils.data ... |
aeeecb56efbf5d21c72e1b2dd92b69c045980b5b6ac30d4ec505038937d40430 | Python | 5,019 | 140 | import base64
import random
from pathlib import Path
from ... import options as opts
from ... import types
from ...charts.chart import Chart
from ...commons.utils import JsCode
from ...exceptions import WordCloudMaskImageException
from ...globals import ChartType
SHAPES = ("cardioid", "diamond", "triangle-... |
4a56fb62bd8806afeaf508f083d03d10ae55546edf98a6ed43a1b7f8d0bb7113 | Python | 5,020 | 175 | import pickle as pkl
import scipy.sparse
import numpy as np
import pandas as pd
from scipy import sparse as sp
import networkx as nx
from collections import defaultdict
from scipy.stats import uniform
import tensorflow as tf
from sklearn import preprocessing
def masked_softmax_cross_entropy(preds, labels, mask):
... |
4ff41b26e8897c0aa97c2b0ea3ff08b13a9b3857a878eb5107c21f9ec6c1478a | Python | 5,021 | 141 | #!/usr/bin/env python3
import argparse
from pathlib import Path
import polars as pl
import pybedtools
from scipy.stats import spearmanr, gaussian_kde
import numpy as np
def read_bed(path, extra_column=None):
if extra_column is None:
return pl.read_csv(
path,
separator="\t", has_hea... |
88c899cb8fb360d5ee2cb4397f7c3fbd366a403c7ca6f2809b2282955a34c8a7 | Python | 5,022 | 136 | import torch
import torchvision.transforms as transforms
from torch.utils.data import DataLoader, Subset
from pipelines.dataloader import JacquardDataset
from modules.vgg16_baseline_even_longer import VGG16Baseline
from grasping_pvgg16_feedback_conn_4_2PC_spec_targ_even_longer_bb import PVGG16SeparateHP as PVGG16
impor... |
92cef0abd84c2fdc54d95f527d4c396098be8c68ab0f8b01bc37b7912ba97c82 | Python | 5,023 | 129 | """A layer-boundary cache hit must agree with a live forward under `train()`.
`unfrozen_top_layers` makes the frozen bottom of the trunk a candidate for
caching only if its output is a pure function of the input -- which needs
its dropout off even while `Model.train()` is engaged, since that is the
only mode the train... |
3896448e12a661379b8000d9d6917ea9c0ca214f43a4c215cd304fb85875de32 | Python | 5,024 | 139 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
from dataclasses import dataclass, field
import torch
import torch.nn.functional as F
from fairseq import utils
from fairseq.log... |
9b77cfa96d36d4e53e322347d07b0f783cf1d44c60357d62741579cae9378d00 | Python | 5,024 | 148 | from __future__ import annotations
import re
from typing import TYPE_CHECKING
import pytest
from poetry.repositories.pypi_repository import PyPiRepository
if TYPE_CHECKING:
import responses
from cleo.testers.command_tester import CommandTester
from poetry.poetry import Poetry
from poetry.reposit... |
07e1dd611dff030551ad5fbb24759713a179bfb45bfaeeff31114361183823d0 | Python | 5,026 | 146 | from typing import Dict, Optional, Tuple
import torch
import torch.nn as nn
import wandb
from utils.data.dataholder import DataHolder
class LossFunction(nn.Module):
"""TrainLoss class for computing and logging training metrics.
Attributes:
train_position_mse (MeanSquaredError): Mean squared error for... |
2570c7356d08cf12e9d122a550c54dd1505c08e56e182aeade74e256f70ab3fb | Python | 5,027 | 107 | # 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.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the r... |
7afd30aeca8ca7791bc13662e685d298e0e381cf80b1ed7e80584666fff879e9 | Python | 5,027 | 127 | """
Simple check list from AllenNLP repo: https://github.com/allenai/allennlp/blob/master/setup.py
To create the package for pypi.
1. Change the version in __init__.py, setup.py as well as docs/source/conf.py.
2. Commit these changes with the message: "Release: VERSION"
3. Add a tag in git to mark the release: "git... |
f28e2c509181d7c4d9715d51ef3bee6e732404929476f42be1437a28a954df56 | Python | 5,028 | 160 | # encoding: utf-8
"""
@author: chenjiayang
@contact: chenjiayang@163.com
"""
import sys
import collections
import random
import torch
import numpy as np
if sys.version_info < (3, 3):
Sequence = collections.Sequence
Iterable = collections.Iterable
else:
Sequence = collections.abc.Sequence
Iterable = ... |
14fe0af51a9ddb1502482f4a2752b20105d4f4b549214da439ddc70ff5d7da4f | Python | 5,031 | 143 | import os
import shutil
import tempfile
import unittest
from fairseq import options
from fairseq.dataclass.utils import convert_namespace_to_omegaconf
from fairseq.data.data_utils import raise_if_valid_subsets_unintentionally_ignored
from .utils import create_dummy_data, preprocess_lm_data, train_language_model
def ... |
1faae043741fc6392a99a5cfcd683cfd97f15a7b4ece892d497265b378236a10 | Python | 5,032 | 107 | #!/usr/bin/env python3
"""Quanta variância a SELEÇÃO de alpha injeta no número do artigo?
Descoberto por acidente ao montar a curva de aprendizado: permutar as linhas do
treino, sem mudar QUAIS estruturas o compõem, movia o RMSE de 0,1423 para 0,1589 —
11 %. A causa é que `ridge_alpha_and_fit` parte a CV interna por P... |
c1caa6b54b3b5077b123a60dabb5205576be794df200b8e23156e408389a2c38 | Python | 5,034 | 136 | import cv2
import numpy as np
import torch
import tqdm
from pytorch_grad_cam.base_cam import BaseCAM
class AblationLayer(torch.nn.Module):
def __init__(self, layer, reshape_transform, indices):
super(AblationLayer, self).__init__()
self.layer = layer
self.reshape_transform = reshape_trans... |
fc75a1d4c78981059db94817c1726bd9cf416bb6db638ccb3494fc7c8c076b42 | Python | 5,037 | 111 | # -*- coding: utf-8 -*-
"""
.. _tutorial04_ref:
Tutorial 4: Layouts and Views
=============================
This tutorial covers the layout and view options provided by ``surfplot``.
For variety, let's import the left and right Conte69 midthickness surface
directly using :func:`~brainspace.datasets.load_conte69`. Th... |
2fbdda8ca8079feb46e985f8814a7b7ed0d5f179fe0e3d909c6491ef5f131317 | Python | 5,038 | 167 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
import os
import contextlib
import numpy as np
import torch
from fairseq.data import FairseqDataset, data_utils
logger = l... |
73702f5f680a96a64507edb91ba9b6f9908f0348574727717fde46dc9015dd40 | Python | 5,038 | 150 | # 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... |
50df14631abba44dceac0cb972e5a719acb0c89e51fcc9b76b04815df48d1da5 | Python | 5,039 | 148 | #!/usr/bin/env python
import urllib.request
from urllib.parse import urlparse
import os
import anndata
import argparse
import shutil
import pandas as pd
import scipy
import json
import tempfile
# 6 available but only 2 contain region label and coordinates
sample_name = ['E9.5_E1S1', 'E9.5_E2S1', 'E9.5_E2S2', 'E9.5_E... |
276fc1ebdd5682a8133d84e86c382b94290813d6114a69904b728d98a9bd124c | Python | 5,040 | 108 | import argparse
import random,os,sys
import numpy as np
import pandas as pd
import argparse
import torch
from tqdm import tqdm
import os
import sys
sys.path.append("../pretrain/")
from load import *
####################################Settings#################################
parser = argparse.ArgumentParser(descri... |
bae40d14aadaa8a68f115d336c1d15686dd89cc1a93dc3604a8e066bd8cd3b25 | Python | 5,041 | 136 | # -*- coding: utf-8 -*-
"""
Created on Thu Nov 11 14:17:10 2021
@author: wyz & yh
Batch processing script for calcium imaging data analysis:
1. Processes multiple Excel files in a directory
2. Applies temporal smoothing to fluorescence traces
3. Performs spike deconvolution using constrained FOOPSI
4. Optionally visua... |
4da2c6c1d9909d61458a69e0fe8674af060d4b3a055001eed6ea985b90d9c11a | Python | 5,042 | 185 | from pgmpy.datasets._base import BaseDataset
class SachsMixed(BaseDataset):
_tags = {
"name": "sachs_mixed",
"n_variables": 20,
"n_samples": 7466,
"has_ground_truth": True,
"has_expert_knowledge": True,
"has_missing_data": False,
"has_index_col": False,
... |
8ed329e717bc0927cdcf94bd551a3660695f46856793496161021d145598051f | Python | 5,042 | 146 | import argparse
import os
import pickle
from pathlib import Path
import h5py
import numpy as np
from spacestream.analyses.effective_dimensionality import (compute_eigvals,
effective_dim)
from spacestream.core.feature_extractor import get_features_from_layer
f... |
f3ce065009acd17a05b175557d2734fefbccf69ef69d7eff2f61ca011359bd03 | Python | 5,042 | 154 | import torch
import torch.nn as nn
try:
from torch.distributed.fsdp.fully_sharded_data_parallel import checkpoint as fsdp_checkpoint
except ImportError:
from torch.utils.checkpoint import checkpoint as fsdp_checkpoint
class PerceiverAttention(nn.Module):
"""
Single cross-attention layer for Perceiver... |
c304f3a2e58d2fe6ea0c08aa6ff296eb95a0bd894a6bc68dfb7fe89150a4eb59 | Python | 5,044 | 120 | # _*_ coding: UTF-8 _*_
# Version information START --------------------------------------------------
VERSION_INFO = \
"""
Author: ZHANG YUBO
Version-01:
2019-08-18 simulate four-taxon data set
Version-02:
2019-11-04 simulate four-taxon data set, with variable mutation rates, recombi... |
d22a0ae43a57838c1d6d0e41419b1a0f78b2f9fdf1b1ddb50ef2090c9b263801 | Python | 5,044 | 127 | """
This is a module that contains the timer facility for gmx_MMPBSA. It's
useful for profiling the performance of the script.
"""
# ##############################################################################
# GPLv3 LICENSE INFO #
# ... |
532013131eb8f5eba562b3cb9621e9552eb45daef7246f09b8dc569ca7801877 | Python | 5,045 | 199 | # Copied from https://github.com/manzt/zarrita.js/blob/ac2559c310bd945470a2651526f730a505b2d5c9/fixtures/v2/generate-v2.py
#
# MIT License
#
# Copyright (c) 2020 Trevor Manz
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Softw... |
6fd79ebf57d551593edb0ac6ffa31e9a1b7418da7e9bb56531c19497a3a93f65 | Python | 5,045 | 178 | import numpy as np
def RSE(pred, true):
return np.sqrt(np.sum((true - pred) ** 2)) / np.sqrt(np.sum((true - true.mean()) ** 2))
def CORR(pred, true):
u = ((true - true.mean(0)) * (pred - pred.mean(0))).sum(0)
d = np.sqrt(((true - true.mean(0)) ** 2 * (pred - pred.mean(0)) ** 2).sum(0))
return (u / d... |
b5a7bb4fd5c5a3ff67e198f2f81fafd470f978475d67de2cd71012fe7e7cce2b | Python | 5,045 | 153 | import numpy as np
import pandas as pd
import pytest
from pgmpy.base import PDAG
from pgmpy.estimators import GES
from pgmpy.example_models import load_model
@pytest.fixture
def random_data_estimator():
rand_data = pd.DataFrame(
np.random.randint(0, 5, size=(int(1e4), 2)),
columns=list("AB"),
... |
6616f81b9480208136080f237c7f0ab7336e77b193c9688af4590cc15f23d14c | Python | 5,047 | 143 | # 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 dataclasses import dataclass, field
from typing import List
import torch.optim.lr_scheduler
from omegaconf import II
from fairseq.datac... |
89af4d1d3aa5e87bd206950d6a7aaa3861583eca0525a42e549992797781040e | Python | 5,047 | 125 | from pathlib import Path
import requests
import pandas as pd
import logging
from typing import List
from src.data.manager import DatasetManager
log = logging.getLogger(__name__)
class SCOPeManager(DatasetManager):
def __init__(self, filepath: str):
"""
Initialize the SCOPe handler with the file p... |
f9795e95de02f0f37e0e9e896fbdb842bd43a8575db071f5bf84533d67e663c4 | Python | 5,048 | 111 | import cv2
import numpy as np
import matplotlib.pyplot as plt
from sklearn.cluster import KMeans
from skimage.segmentation import mark_boundaries
def convert(image_rgb, color_space):
if color_space == 'Lab':
image_preprocessed = cv2.cvtColor(image_rgb, cv2.COLOR_RGB2Lab)
l, a, b = cv2.split(image_p... |
b77afd98774d139d4ebfe0a91a1fb920636a97858688748df82d856d69eb9032 | Python | 5,049 | 137 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, 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 cop... |
f7f29e23455f3de259a66220406d5db80e8b21074689e28beefe59aaa6a32408 | Python | 5,049 | 169 | import os
import sys
import pandas as pd
import numpy as np
import argparse
import csv
# import motif_utils as utils
def kmer2seq(kmers):
"""
Convert kmers to original sequence
Arguments:
kmers -- str, kmers separated by space.
Returns:
seq -- str, original sequence.
"""
kme... |
718986c990f42885286dabd75a89159d5575841c6578050f7d20e0d6c5a4cbbe | Python | 5,050 | 166 | """
* author: Abolfazl Danayi
* created on 01-01-2026-07h-48m
* copyright 2026
"""
import tools
import numpy as np
from keras import models as KM
from keras import layers as KL
from keras import backend as KB
from keras import optimizers as KO
import numpy as np
import tensorflow as tf
import os
# import analysis as ... |
d10a8d7e38394744cfc9123ff872dd12a879c292866fefa989434797013cce3e | Python | 5,051 | 129 | # 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... |
cdd4d6623f12887f18dd4fa53a773681125ea062461efc8c1c62b5a274c07199 | Python | 5,052 | 145 | import collections
from os.path import join
import numpy as np
import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt
from sklearn import metrics
from config_path import PROSTATE_LOG_PATH, PLOTS_PATH
from utils.stats_utils import score_ci
def read_predictions(dirs_df):
model_dict = {}
... |
69a63379849d67de857e73a43056b3db703bb5af8623c32634d400d8d301ab51 | Python | 5,053 | 162 | import copy
import torch
import logging
from argparse import Namespace
import yaml
from fairseq import options
from examples.speech_to_speech.benchmarking.core import (
Processing,
SpeechGeneration,
Cascaded2StageS2ST,
Cascaded3StageS2ST,
S2UT,
)
from examples.speech_to_speech.benchmarking.data_util... |
0411d63adbcf7dde00d4e418b13cb553cab98030dda85f3b430103463b0f15a4 | Python | 5,054 | 109 | import utils.gpu as gpu
from modelR.lodet import LODet
from tensorboardX import SummaryWriter
from evalR.evaluator_fs import Evaluator
import argparse
import os
import config.cfg_lodet as cfg
from utils.visualize import *
import time
import logging
from utils.utils_coco import *
from utils.log import Log... |
1c4251095a7dcd9b884ac5eab7815fc6d014ea50bb2704fe6820fa61e9eae36c | Python | 5,055 | 102 | """Unit tests for the live-service availability probes in ``tests/__init__.py``.
These probes gate the ``@pytest.mark.skipif(not <SERVICE>_AVAILABLE, ...)`` network tests. A probe
that reports a *healthy* service as unavailable silently skips real coverage on every CI run, so the
probes themselves are worth pinning do... |
4d91c3c40510ca890f4945954b25e9de7c4fc0fe751e0873c6880441c3dae4b9 | Python | 5,056 | 162 | from pathlib import Path
from typing import Optional
import numpy as np
import torch
import torchvision
from pytorchvideo.transforms import ShortSideScale, UniformTemporalSubsample
from torchvision.transforms._transforms_video import (CenterCropVideo,
NormalizeVide... |
f7c5550026adf4ef11ecdcf8efd8ae896a1215b4cb143b5c8bb49738e8a2d79e | Python | 5,056 | 126 | import pytest
from rnalysis.gui.gui_report import *
def test_Node():
# Test creating a node object
predecessors = [1, 2, 3]
node = Node(4, 'Node 4', predecessors, 'popup', 'Count matrix', 'filename.txt')
assert node.node_id == 4
assert node.node_name == 'Node 4 (#4)'
assert node.predecessors ... |
4cdaa532c02c2319ae43c78461c6bae58f87e02f9493cedae4cda1467727e144 | Python | 5,058 | 136 | import torch
import torchvision.transforms as transforms
from torch.utils.data import DataLoader, Subset
from pipelines.dataloader import JacquardDataset
from modules.vgg16_baseline_even_longer import VGG16Baseline
from grasping_pvgg16_feedback_conn_3_2PC_spec_targ_fixed_dist_PC2_fb_even_longer_bb import PVGG16Separate... |
76f3c24060be7c39a2d2f0a52bc7aa143fa6f796b16366138b476337afbef1f1 | Python | 5,059 | 126 | from ... import options as opts
from ... import types
from ...charts.chart import Chart
from ...globals import ChartType
class MapMixin:
"""
<<< Map >>>
Map are mainly used for visualization of geographic area data.
"""
def add(
self,
series_name: str,
dat... |
e93b201250be118e73f628d1372c37eca034b2136aa692631ef9387c381a647c | Python | 5,060 | 152 | import torch
import matplotlib.pyplot as plt
import seaborn as sns
import argparse
import os
import numpy as np
from transformers import BertTokenizer, BertModel, DNATokenizer
from process_pretrain_data import get_kmer_sentence
def format_attention(attention):
squeezed = []
for layer_attention in attention:
... |
70c926230d1634c5d174c32e5727218e20dff8c02cfd5f826e128fb201645a38 | Python | 5,061 | 132 | from PIL import Image
from sklearn.cluster import KMeans
import cv2
import numpy as np
from matplotlib import pyplot as plt
import torch
from msi_visual.visualizations import visualizations_from_explanations
from sklearn.metrics.pairwise import euclidean_distances, cosine_similarity
import cmapy
from msi_visua... |
14cfd7cf829100d3b597702259c8d98cbf22dc578d23444faaa9760af250cf4d | Python | 5,071 | 126 | import os
import json
import pandas as pd
import numpy as np
from tqdm import tqdm
def get_correlation_matrix(data_dir, correlation_pairs):
corr_results = {f'{pair[0]} ~ {pair[1]}': [] for pair in correlation_pairs}
for f in tqdm(os.listdir(data_dir)):
df = pd.read_csv(os.path.join(data_dir, f))
... |
4d2ad0aa4aa501107fe38c60b449c32f6eb72b7040bcf2f92aa3800a9eabb7d3 | Python | 5,075 | 168 | from __future__ import annotations
from subprocess import CalledProcessError
from typing import TYPE_CHECKING
from typing import Literal
from typing import cast
import pytest
from poetry.core.constraints.version import Version
from poetry.console.exceptions import PoetryRuntimeError
from poetry.utils.env.python.ins... |
85386de2bfbe1800813f2ed88ed96d5ff6a2181f4883fb6990c990b42aac58bd | Python | 5,079 | 123 | # _*_ coding: UTF-8 _*_
# Version information START --------------------------------------------------
VERSION_INFO = \
"""
Author: ZHANG YUBO
Version-01:
2019-08-18 simulate four-taxon data set
Version-02:
2019-11-04 simulate four-taxon data set, with variable mutation rates, recombi... |
057140ca31c7b0a1baad2debc484b69ab749afe6fa09767cad2ef143f7dbe3cd | Python | 5,080 | 143 | import numpy as np
from tqdm import tqdm
from functools import partial
import torch
import torch.nn as nn
from torch.nn import functional as F
from ..common.data_utils import (
lattice_params_to_matrix_torch,
lattice_params_from_matrix,
)
from ..gnn.embeddings import MAX_ATOMIC_NUM
from .base import BaseMode... |
1c2f46903d3a4a090aac5dbe28aaa1f1ce7da572f89122b593c764975066be45 | Python | 5,080 | 127 |
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 conv2d
from tractseg.libs.pytorch_utils import deconv2d
class UNet_Pytorch_DeepSup(torch.nn.Module):
def __init__(self, n_input_... |
786b6e38100861ad5df8276ac67a81957843ac8300708a4067c4b3eb501f1317 | Python | 5,080 | 147 | 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... |
b1f77b04387413e516cd949412dde94fba08d470af3b28c295ea253620e9df8b | Python | 5,081 | 158 | """Tests for ``aestetik.modules.aestetik_module.AESTETIKModel``.
We construct a real ``AESTETIKDataModule`` so that ``configure_model``
has a populated ``X_st_grid`` to read its input-channel count from.
"""
from __future__ import annotations
import pytest
import torch
from aestetik.data_modules.data_module import A... |
665af84bd7cc221e15c9859f7df4af19f12c984c5d70e2eba1b59dd97b9a1122 | Python | 5,084 | 146 | import datetime
import uuid
import simplejson as json
from jinja2 import Environment
from ..commons import utils
from ..globals import CurrentConfig, Locale, RenderType, ThemeType, DefaultLocale
from ..options import InitOpts, RenderOpts
from ..options.series_options import BasicOpts, AnimationOpts
from ..render impo... |
b22113f5bb634b4704bebcb7364d64efb996ca891111345388fc1d0450649b7c | Python | 5,085 | 131 | import torch
import torch.nn as nn
import torch.nn.functional as F
from core.modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d
from core.modeling.aspp import build_aspp
from core.modeling.decoder import build_decoder
import timm
from core.modeling.attention import SAGate
class DeepLab(nn.Module):
d... |
3b0b9204b8751781970b7f7a33f21b6e1654b662c69fbd8b8dd737e5223e3255 | Python | 5,089 | 147 | import warnings
import numpy as np
import rich.table
from anndata import AnnData
from scvi import REGISTRY_KEYS, settings
from scvi.data import _constants
from scvi.data._utils import (
_check_fragment_counts,
_check_nonnegative_integers,
_verify_and_correct_data_format,
)
from ._base_field import BaseAn... |
b068e30270fbaea39a4db8a02c5d14ff91b2a8165274940770204fdeb2a448e6 | Python | 5,089 | 152 | """Functions for shortening GO names."""
__copyright__ = "Copyright (C) 2016-2017, DV Klopfenstein, H Tang, All rights reserved."
__author__ = "DV Klopfenstein"
greek2uni = {
"alpha": "α",
"beta": "β",
"gamma": "γ",
"delta": "δ",
}
greek2tex = {
"alpha": r"$\alpha$",
"beta": r"$\beta$",
"... |
5fd373d12b42941e4d0e92b7c409c9e6760838ed7e41e8dc74a649a551214015 | Python | 5,090 | 102 | #!/usr/bin/env python3
"""Microarray harmonization (track 2) — read the 6 array series_matrix expression tables,
map platform probe IDs -> HGNC symbol (GPL570 via mygene reporter; GPL10558/GPL17586/GPL23126
via the GEO platform SOFT annotation), assign MS/HC from series_matrix metadata."""
import os, re, gzip, io, requ... |
8e1d366fe4f645c8741cc7292fa74055d13a3da8c6b08ae0fe2f84d83299f76e | Python | 5,093 | 171 | import argparse
import os
import re
import sys
from typing import Optional
import pandas as pd
def get_args():
parser = argparse.ArgumentParser(description="Subset fastq files for a specific sample.")
indexes_group = parser.add_mutually_exclusive_group(required=True)
parser.add_argument(
"-f",
... |
cab662405782e6c4993abaed0b70ecb74454cbec920ad7b0ceaa57e572381525 | Python | 5,094 | 151 | """Tests for the validation surface of the sklearn-style ``AESTETIK``
estimator.
These tests poke the lightweight validation paths (param checks, obsm /
obs presence checks, fit-vs-predict dim guards, sklearn ``check_is_fitted``
behavior). They never run Lightning training so they live in the fast
suite.
"""
from __fu... |
5c9b04481ade2577f7f2d4428b62d88005abc62a93e11dce2782d9909891fa4e | Python | 5,095 | 135 | """Map Hydra OmegaConf to a flat namespace for the training loop and get_gene_celltype."""
from __future__ import annotations
from types import SimpleNamespace
from omegaconf import DictConfig, OmegaConf
from dlbase.training.standard_lightning import early_stopping_patience_epochs
def hydra_cfg_to_args... |
12de7b0ff09c8903515bbd1322d4933676f21386db65bc5ecc24ebbdf235dcfa | Python | 5,098 | 178 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Image filters. Intended for internal use only."""
from typing import Optional
import warnings
import numpy as np
import matplotlib.pyplot as plt
from scipy import ndimage
from skimage.restoration import rolling_ball
__all__ = [
"apply_gaussian_filter",
"remov... |
e7d24a90426de8068022d5cb909862d5f25da4d946715cfe8faff89b872f57b5 | Python | 5,098 | 127 |
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 conv2d
from tractseg.libs.pytorch_utils import deconv2d
class UNet_Pytorch_DeepSup_TEST(torch.nn.Module):
def __init__(self, n_i... |
ade52542d18c9b9f5ff4ae772b2ef729e1aa5835fb57f3d837257bc843a343f4 | Python | 5,099 | 153 | import collections
import os
from os.path import join, basename, dirname
import numpy as np
import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt
from sklearn import metrics
from config_path import PROSTATE_LOG_PATH, PLOTS_PATH
from utils.stats_utils import score_ci
def read_predictions(dir... |
9ada2c0732111b7e04dbe8f016a49078b157d8fbcb3c217f57bff28be8c88144 | Python | 5,100 | 139 | #!/usr/bin/env python3
"""
@file test_neural.py
@author Simon Yu
@date 02/12/2024
@brief Script for testing neural models.
"""
import argparse
import dataset
import header
import logger
import model
import torch
import tqdm
import utility
import wandb
def initializeRunName(run_name = ""):
if run_name != "":... |
66ade7f5501a4e6afdb175a7fe0a058ef32a0227581057840aa6e35fd745f7c5 | Python | 5,101 | 134 | import pysam
import argparse
import os
def sort_and_index_bam(input_bam, sorted_bam, n_threads=1):
pysam.sort("-@", str(n_threads), "-o", sorted_bam, input_bam)
pysam.index(sorted_bam)
def parse_fasta(reference_fasta):
"""
Parses a multi-FASTA file into a dict {seq_name: seq_string}.
"""
seque... |
a57eae867506423286bf3aa2fdb1854455bd8584ee952207d187fd4e3e55083c | Python | 5,101 | 155 | import sys
import timsdata
import sqlite3
import numpy as np
from PIL import Image
import cv2
import tqdm
from bisect import bisect_left, bisect_right
from typing import Optional
import os
import math
import os
from multiprocessing import Pool
import argparse
def get_args():
parser = argparse.Argum... |
abb4f8082500148848198479c2cb7c4cdfbf2bd9f169bd28ddd480aeaaa6c467 | Python | 5,101 | 137 | """Atomic orbital eigenenergy table at ωB97M-D3BJ / def2-TZVPPD.
DFT analogue of `atomic_table.py` (which uses GFN2-xTB single atoms).
Built with PySCF UKS:
- functional: base ωB97M semilocal XC (libxc `wb97m_v` with the VV10
NLC switched OFF). ωB97M-D3BJ uses the *same* semilocal XC as
ωB97M-V but replace... |
33911dd06147fcf46930065c7de0b701186ddf19dbcd724199755f048424afcb | Python | 5,104 | 136 | import scipy.signal as signal
import numpy as np
import itertools
import scipy.ndimage as filters
def butter_bandpass(lowcut, highcut, fs, order=5):
sos = signal.butter(order, [lowcut, highcut],fs=fs, analog=False, btype='band', output='sos')
return sos
def butter_bandpass_filter(data, lowc... |
9faa6061e5adfb5428d133a17e79109ab9534dcb6f613ab05de684ac0e07d14c | Python | 5,104 | 104 | import streamlit as st
import joblib
from msi_visual.saliency_opt import SaliencyOptimization
from msi_visual.spearman_opt import SpearmanOptimization
from msi_visual.nmf_3d import NMF3D
from msi_visual.nonparametric_umap import MSINonParametricUMAP
from msi_visual.kmeans_segmentation import KmeansSegmentation
... |
4a2532a892abe004c5b5182c084278de3a067126a008e9e7bab901d45950881e | Python | 5,105 | 144 | import logging
from pathlib import Path
import numpy as np
import pandas as pd
import scanpy as sc
import scipy as sp
from gsMap.config import CauchyCombinationConfig
logger = logging.getLogger(__name__)
# The fun of cauchy combination
def acat_test(pvalues, weights=None):
"""acat_test()
Aggregated Cauchy ... |
c9b948c9b5e1682c8095f7dcdfc98b55fb567f3962b716128bf57e9468dd86fd | Python | 5,105 | 144 | import logging
from functools import partial
from typing import Literal
import jax
import jax.numpy as jnp
from jax.experimental import pallas as pl
from .utils import (
big_number,
compiler_params,
compute_q_and_kv_block_len,
create_grid,
get_lse_block_spec,
get_mask_block_spec,
get_value... |
c2b04e420bb79647d4461b8753466276fd0553353c216ea360d0702975614711 | Python | 5,109 | 130 | import re
import logging
import os
re_db = re.compile(".db$")
re_tw = re.compile("^TW_")
re_0_5 = re.compile("_0.5$")
re_g_ = re.compile("^gtex_v7_")
re_i_ = re.compile("_imputed_europeans_tw_0.5_signif.db$")
def extract_model_name(path, name_pattern=None):
p = os.path.split(path)[1]
if name_pattern:
... |
dc5ab053327186ecbc3a627c2b5f8317048228f2d2846a391b3a02e09393419d | Python | 5,115 | 179 | """
This module contains thread workers to recieve or plot measurement data
"""
from PyQt5.QtCore import QObject, QThread, pyqtSignal as Signal, pyqtSlot as Slot
import time
from Sensors.Measurements import MeasObj
from Sensors.GravityMeasurements import GravitySensor
from queue import Queue
from Sensors.PlotControl i... |
953dbd15d5aded7bbf329cd4cadef7aa6231dc766066831eedcc8cae3a93dcbd | Python | 5,116 | 127 | from ... import options as opts
from ... import types
from ...charts.chart import RectChart
from ...globals import ChartType
class Line(RectChart):
"""
<<< Line Chart >>>
Line chart is a graph that connects all data points
with single line to show the change trend of data.
"""
... |
fd442cbe54c0fd540b89cb7ff895e4f7a3bc36bfbfdc57a9bf6df1295f2ea07d | Python | 5,119 | 112 | import keras.backend as K
from keras.models import Model, Sequential
from keras.layers import Input,InputLayer,Multiply,ZeroPadding2D
from keras.layers import Conv2D, MaxPooling2D,Conv1D,MaxPooling1D
from keras.layers import Dense,Activation,Dropout,Flatten,Concatenate
from keras.layers import BatchNormalization
from k... |
3748388b65571c661c54d00f5d071994b507d167442ab87dbd0845135bdac16a | Python | 5,120 | 134 | import numpy as np
import pandas as pd
import pytest
from skbase.utils.dependencies import _check_soft_dependencies
from pgmpy import config
from pgmpy.estimators import MirrorDescentEstimator
from pgmpy.factors import FactorDict
from pgmpy.factors.discrete import DiscreteFactor
from pgmpy.models import FactorGraph, J... |
3d384ef6281346e573850a4980706304bb220b0bfb71c7c34d380a57b539be49 | Python | 5,121 | 148 | from distutils.util import strtobool
from pathlib import Path
def bool_from_str(value):
if isinstance(value, bool):
return value
elif isinstance(value, str):
return bool(strtobool(value))
def expanded_user_path(value):
return Path(value).expanduser()
def range_str(range_str, sort=True)... |
70ef1cf53e042a7cf6dee3f0040214899da92e392c9998873cd7b29a398ef1db | Python | 5,122 | 158 | """tests for vak.eval.parametric_umap module"""
import pytest
import vak.config
import vak.common.constants
import vak.common.paths
import vak.eval.frame_classification
def assert_eval_saves_one_csv(model_name, output_dir):
eval_csv = sorted(output_dir.glob(f"eval_{model_name}*csv"))
assert len(eval_csv) == ... |
02401985d97f37b7f8d12538787b1d384a216b93077194710ea603befaf67e99 | Python | 5,123 | 145 | import unittest
from unittest.mock import patch
from pyecharts import options as opts
from pyecharts.charts import Line
class TestLineChart(unittest.TestCase):
@patch("pyecharts.render.engine.write_utf8_html_file")
def test_line_base(self, fake_writer):
c = (
Line()
.add_xaxis... |
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