sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
70cdb31208645ea9345a1eafe759c9a9d74ba1273c9928b1b69e83d75b1cb3b9 | Python | 1,744 | 54 | from sklearn.datasets import make_regression
from sklearn.ensemble import RandomForestRegressor
from siapy.optimizers.configs import OptimizeStudyConfig, TabularOptimizerConfig
from siapy.optimizers.optimizers import TabularOptimizer
from siapy.optimizers.parameters import TrialParameters
from siapy.optimizers.scorers... |
48fa578cf39d50d4ae95e3fe985f26d519480fc6536285a31e2bfb9f221ab097 | Python | 1,745 | 54 | """
Provides the Augmentations and Transforms used by the
:class:`rising.loading.DataLoader`.
Implementations include:
* Transformation Base Classes
* Composed Transforms
* Affine Transforms
* Channel Transforms
* Cropping Transforms
* Device Transforms
* Format Transforms
* Intensity Transforms
* Kernel Transforms
*... |
4f0a8fe515b24b774580abfed9fab6f5374de5f3abb53bae9e588d916eb082a1 | Python | 1,745 | 48 | import rdkit
from rdkit import Chem
from rdkit.Chem import rdMolDescriptors
from rdkit.Chem import AllChem
from rdkit.Chem import rdFingerprintGenerator
import copy
import pandas as pd
import numpy as np
from cddd.inference import InferenceModel
from cddd.preprocessing import preprocess_smiles
size=512
apgen = rdFinge... |
a19ca09f1bfa728b730c88df951bfa2336fb9d9c126dca7cdda299399cdc6df6 | Python | 1,745 | 72 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
This code checks the total number of detected UMIs and CBCs in a tagged bam file.
The expected format of the tags is a sfollows:
XM: UMI
XC: cell barcode (CBC), a concatenation of the three splitseq barcodes
gn: gene symbol, as attached by the Dropseqtools TagReadWithI... |
fd6fd1d8ec46c125d0ed7f00ad9eba04a462c5b90a3add94dacb1d6b8292f8ed | Python | 1,745 | 41 | r"""Bonsai integration — driver only, no upstream source.
Bonsai reconstructs a maximum-likelihood *tree* over cells instead of a 2-D
embedding: cells are leaves, internal vertices are inferred ancestral states,
and branch lengths are distances in expression space. It consumes the
measurement error on each feature, so... |
0eb1da5c3d84106a6358afd0b19ea6a3d416a32fade40687684a91438a4a5273 | Python | 1,746 | 45 | import logging
from datetime import datetime
from agent.data.entities.config import ROOT_LOGGER_ID
from agent.classifiers.data.liwc_management import export_item_data_for_liwc_features, get_item_liwc_features
from agent.classifiers.tree_classifiers import tree_classifier
logging.basicConfig(format='%(levelname)s : %... |
ad8e023933c085b145c73dc1b67f37d3f3d9320f3ad569bd4dcf692a20867956 | Python | 1,746 | 56 | from torch.nn.utils.clip_grad import clip_grad_norm_
from auxilearn.implicit_diff import Hypergrad
class MetaOptimizer:
def __init__(self, meta_optimizer, hpo_lr, truncate_iter=3, max_grad_norm=10):
"""Auxiliary parameters optimizer wrapper
:param meta_optimizer: optimizer for auxiliary paramet... |
b9fbd1581c8b67c7142058f64a233e1f6588a8bb70b436429ec671a5cf53b367 | Python | 1,749 | 43 | import csv
import os
import re
DATADIR='../data'
PARSER = '^page (?P<page>[0-9]+) has (?P<pixels>[0-9]+) pixels that differ$'
PARSED_LIST = [
['Page', 'Pixels Differ [N]', 'Differing Pixels Proportion', 'Date', 'Environment'],
]
# This should be dynamically/empirically determined, perhaps with a blank page o... |
0d91e6208fe52d15971cf1b6cb38ce6adbe57c3bb9d4216f5045305806f31b82 | Python | 1,750 | 48 | import torch
from .augmentations.leads import derive_limb_leads
# P, Q, R, S, T waves: (offset from R peak in s, amplitude, width in s)
WAVES = (
(-0.2, 0.15, 0.025),
(-0.03, -0.15, 0.01),
(0.0, 1.0, 0.012),
(0.03, -0.25, 0.01),
(0.3, 0.3, 0.05),
)
def synthetic_ecg(
duration=10.0, fs=500, h... |
cb2ab0a038c39a3c5d2802946a882f1e74b0c68fb4e7cea2846ed2eac61cda8b | Python | 1,750 | 68 | # %% a script for summarizing fit_result3 data
# the data structure is
# solutions['G' or 'H'][0-50] (each 10 of them have different value of penalty)
# the penalty values are 1 to 100 in log space
import numpy as np
import pickle
import pandas as pd
from numba import njit
# penalties = np.logspace(0, 2, 5) this is ... |
2f2b434bfb37542a06848893b130d5a80b12dc3e5ddfe15858d401ec5228f326 | Python | 1,753 | 70 | import numpy as np
import matplotlib.pyplot as plt
from spinnaker2 import snn, hardware, brian2_sim
n_stim = 10
n_nrns = 20
neuron_params = {
"threshold":2.,
"alpha_decay":0.9,
}
neuron_params2 = {
"threshold": [2.+0.001*i for i in range(n_nrns)],
"alpha_decay": [0.9+0.001*i f... |
59222387686503b1819d2635fd37d26c440e2eccc6fdc8297c2400555422628d | Python | 1,755 | 55 | # -*- coding: utf-8 -*-
"""
Created on Wed Sep 14 12:18:00 2022
@author: ju-bar
TTX file I/O
This code is part of the 'emilys' repository
https://github.com/ju-bar/emilys
published under the GNU General Publishing License, version 3
"""
def write_table_txt(str_filename, tab, header, str_sep = ' ', str_fmt = '{:12.... |
2ca46b057b261449b03870fcea90b1232422e7795d871d3c5e9774619a67e816 | Python | 1,756 | 50 | #!/usr/bin/env python
from __future__ import print_function
import argparse
import glob
import gzip
import math
import numpy as np
import os
def parse_args():
parser = argparse.ArgumentParser("Analyzes chunks from curated marginPhase output and logfiles")
parser.add_argument('--log_dir', '-l', dest='log_dir', ... |
4f60103057ce18c0942c0a91004f337f5544e63ec6171c6ced27c4ba14d8e250 | Python | 1,756 | 47 | # Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... |
d1ec3f7f6d1fa434852f9dca4708df272bdc4789dbc4bf02d240d9e070b4e5c0 | Python | 1,756 | 49 | from typing import List
import torch
from tqdm import tqdm
from GR_pKa.data import MoleculeDataLoader, MoleculeDataset, StandardScaler
from GR_pKa.models import MoleculeModel
def predict(model: MoleculeModel,
data_loader: MoleculeDataLoader,
disable_progress_bar: bool = False,
sc... |
edaba626add988ac12b36dd670c40ca4ab5b94b45813a52dd085acc42fd93165 | Python | 1,756 | 61 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""Base drift compensation for inference."""
from typing import Tuple, TYPE_CHECKING
from torch import Tensor
from torch.autograd import no_grad
if TYPE_CHECK... |
78d320f0a0b58cfc638ef1f3066b01ec5e9c5bbb6b223227b6d33d6686cde7e5 | Python | 1,758 | 61 | #!/usr/bin/env python3
import argparse
from pathlib import Path
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Extract Resnet18 imagenet features from slide."
)
parser.add_argument(
"slide_tile_paths",
metavar="SLIDE_TILE_DIR",
type=Path,
n... |
8d5a419dd2e1790e36b5fb5ced27373c0c283924929d43d51edcf703524ce017 | Python | 1,758 | 58 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
import pandas as pd
from behaviopy.plotting import qualitative_times
from behaviopy.utils import full_subsets
from os import path
import matplotlib.pyplot as plt
data_dir = path.abspath(path.expanduser('~/ni_data/ofM... |
e575fcc61407b2ced36a03bd330f22869a6c87da269be5a8cab154297cbfdbf5 | Python | 1,758 | 78 | # -*- coding: utf-8 -*-
"""
"""
import time
import numpy as np
import pytest
import vtkplotlib as vpl
pytestmark = pytest.mark.order(11)
def test_qfigure():
vpl.QtFigure._abc_assert_no_abstract_methods()
self = vpl.QtFigure("a Qt widget figure")
assert self is vpl.gcf()
dir... |
0ea4d7027122b590dc4fa64dd593106dc5472a69726008266b560927672d1066 | Python | 1,759 | 39 | from tests.objects import test_node, test_tree
from neuron_morphology.validation import resample_validation as rev
from neuron_morphology.validation.result import InvalidMorphology
from tests.validation.validation_test_case import ValidationTestCase
from neuron_morphology.constants import *
import unittest
from mock im... |
bd294b3f72b5d14694a53ade645484bbd1ee117ac31603ea0acf3236c7dd32a9 | Python | 1,759 | 58 | import random
import string
import ray
def random_text(length: int) -> str:
"""Generate random text of specified length."""
if length <= 0:
return ""
if length <= 3:
return "".join(random.choices(string.ascii_lowercase, k=length))
words = []
current_length = 0
while current_l... |
9fb275e57cd189c97aa5672aba14fcb6a2baebce34cccd39af3e8ee209548d15 | Python | 1,760 | 50 | import torch
from ..utils import loss_and_miner_utils as lmu
from ..miners.base_miner import BaseTupleMiner
class PairMarginMiner(BaseTupleMiner):
"""
Returns positive pairs that have distance greater than a margin and negative
pairs that have distance less than a margin
"""
def __init__(self, p... |
f57480456b74713cd9e06d3d0ad3903df685a6ff4dbbfcef18be26c7e06bd542 | Python | 1,760 | 58 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
import pandas as pd
from behaviopy.plotting import qualitative_times
from behaviopy.utils import full_subsets
from os import path
import matplotlib.pyplot as plt
data_dir = path.abspath(path.expanduser('~/ni_data/ofM... |
20f4a01e15f559c954204b021fede69d283cded5c4cd2509a3c1a4da4274bd61 | Python | 1,762 | 35 | from typing import Union
import pandas as pd
from numpy import log2
from scipy.stats import entropy
def column_imbalance_score(
value_counts: pd.Series, n_classes: int
) -> Union[float, int]:
"""column_imbalance_score
The class balance score for categorical and boolean variables uses entropy to calculat... |
5a53eda3e1938dcb785cbf6fb2bf22f96102c07f0633a9e52af49b3d394474c7 | Python | 1,762 | 64 | """Deprecated plotting compatibility wrappers for ``omicverse.utils._scatterplot``."""
from __future__ import annotations
import importlib
import warnings
_REMOVAL_VERSION = "2.2"
_MESSAGE = (
"`ov.utils.{old_name}` is deprecated and will be removed in omicverse "
"{version}. Use `{replacement}` instead."
)
... |
9b83fa667dbead4240121dad4b94c023c5e099c7e6ae077f0a7fd299bd746c22 | Python | 1,762 | 75 | import os
import torch
import numpy as np
from scipy.linalg import qr
ID2CHAPTER = dict({
'1' : 'breakfast',
'2' : 'exercising',
'3' : 'cleaning',
'4' : 'bathroom'
})
def split_video_id(video_id, to_int=False):
actor_id, chapter_id, run_id = video_id.split('.')
if to_int:
return int(a... |
f26bc3ad412da1a508125101f7b95ee66992f315c275799150299a699e84fe8f | Python | 1,763 | 66 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import glob
import multiprocessing
import os
import shutil
import sys
import zipfile
from datetime import datetime
import ase.io
def extr... |
3aebb8b22132ee291bec9d0c6daef987680629186c8e31988a5f16d18789a196 | Python | 1,764 | 52 | import os
import subprocess
import sys
from importlib import resources
from flyvis.network.directories import NetworkDir
TRAIN_SINGLE = str(resources.files("flyvis_cli") / "training" / "train_single.py")
def train_single(root_dir, sintel_path, *overrides):
return subprocess.run(
[
sys.execut... |
494099e88718cdae6f3a6cb5b3921601308b7f4d7a4f2bfec194900222fa8fdb | Python | 1,765 | 54 | import os
import os.path as osp
import numpy as np
import torch
from torch_geometric.data import InMemoryDataset
from torch_geometric.data import Data
from tqdm import tqdm
"""
Code to load in the processed InteractionGraphs to pytorch geometric.
"""
# TODO: Convert to work with args object
class FingerprintDataset(... |
d9fd927d8f0c79cb207b6321d5c4accc4123bd9e2fc07b09ac91117c32c06b65 | Python | 1,765 | 67 | import os
import sys
import tempfile
import pytest
import ray
def test_basic_dag_with_names_plot():
@ray.remote
def a(*args, **kwargs):
pass
tmp1 = a.options(name="tmp1").bind()
tmp2 = a.options(name="tmp2").bind()
tmp3 = a.options(name="tmp3").bind(tmp1, tmp2)
tmp4 = a.options(name... |
30390cadd986e17231b37d2c91a501790b6fd8d687bd8b4c22aadd7083170ce5 | Python | 1,767 | 48 | import torch
from Config import class_number
SEED = 1234
torch.manual_seed(SEED)
torch.backends.cudnn.deterministic = True
import DataSet
import torch.nn as nn
import torch.nn.functional as F
class TextRNN_Attention(nn.Module):
def __init__(self):
super(TextRNN_Attention, self).__init__()
Vocab =... |
96adfa5beb88c4db38a2d8b92b51a8c6aa872e93395f7f0319d7729e6bb60545 | Python | 1,767 | 72 | """
Example for running multiple experiments with same snn.Network using reset
mechanism.
"""
import time
import numpy as np
import matplotlib.pyplot as plt
from spinnaker2 import snn, hardware
# track execution time excluding plotting
t_start = time.time()
neuron_params = {
"threshold":1.5,
"alpha_de... |
cf9c30bced5d35669fd03ef5485aa8fa16ba8865d3458b89c42262bf6632a8b6 | Python | 1,767 | 63 | from django.urls import path
from django.conf import settings
from django.conf.urls.static import static
from django.shortcuts import redirect
from . import views
def redirect_result(request, result_id):
return redirect("proteome_report", result_id=result_id)
urlpatterns = [
path("", views.infer_index, nam... |
f06e1d2c5b5b24046b02f7c98469d86a842a3b26e1426c64ddd8671f1e8b52de | Python | 1,767 | 62 | # -*- coding: utf-8 -*-
"""
"""
from vtkplotlib.interactive import pick, call_super_callback
from vtkplotlib.figures.QtFigure import QtWidgets
class CursorTracker(object):
def __init__(self, fig):
self.fig = fig
self.init_labels()
self.fig.style.AddObserver("MouseMoveEvent",... |
34bd12d6141f4c9ac77540130757d70ae20f97423de390ee9ea825a06c170bec | Python | 1,768 | 78 |
import numpy, random
import json, os
from gym_sted.utils import BleachSampler
ROUTINES = {
"high-signal_low-bleach" : {
"bleach" : {
"p_ex" : 10e-6,
"p_sted" : 150e-3,
"pdt" : 30.0e-6,
"target" : 0.2
},
"signal" : {
"p_ex" : 10.0... |
91984a9d4816135f833c1bfd8c943b6ec2fd11f376243646c6a4b890facac94f | Python | 1,769 | 49 | #!/usr/bin/env python2
# This script shows boxes in the stimulus locations for the conflict task
# Press "q" to exit
# This can be put on the screen while putting the subject in the scanner
# in order to make sure the relevant locations are visible and centered.
from __future__ import division # so that 1/3=0.333 in... |
3b311333a4f1b32282e7d47e2fec5a10f1f25172ad7502e1486858671e0cdf16 | Python | 1,770 | 55 | """Create design files for analysis in FSL"""
import pandas as pd
import subprocess
import os
import numpy as np
import glob
# define ROOT dir
ROOT = '/Users/sebastiandresbach/data/neurovascularCouplingVASO/Nifti'
subs = ['sub-06']
for sub in subs:
# make folder to dump statistocal maps
designFolder = f'{ROO... |
4603a3795619fd13772ec3fca1c697583022824be68592e260d44ed413479de6 | Python | 1,770 | 43 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
586b91fbd1f788a3fda8175e14169a586229534c9347d4e050b58738799c6e1d | Python | 1,771 | 40 | import torch
from torch.utils.data import BatchSampler
class MultiEpochsDataLoader(torch.utils.data.DataLoader):
"""
The MultiEpochsDataLoader is a PyTorch dataloader that re-uses worker processes rather than re-initializing the every epoch (see https://github.com/pytorch/pytorch/issues/15849#issuecomment-5181... |
ba1cc42e2081fa8303b9a66a26e621c4ded09cc0920de5f919022b96d959f27b | Python | 1,771 | 45 | import pandas as pd
import scanpy as sc
import numpy as np
def spatial_plot(adata, info, color_by="type", size=None, mode=1, palette=None, save_path=None, figsize=None):
"""
Plots original/mapped spatial coordinates.
Args:
adata: Spatial dataset to be plotted.
info: A DataFrame containing ... |
40aec84eddff392b1c438946e7bc5f5220e9b110641f12d23a1e0de1a8b96cb3 | Python | 1,772 | 57 |
import argparse
from lisa.core.data_interface import DataInterface
import numpy as np
import pandas as pd
import os
def main(args):
cistrome_metadata = pd.read_csv(args.cistrome_metadata, sep = '\t').set_index('DCid')
cistrome_metadata.index = cistrome_metadata.index.astype(str)
data = DataInterface(arg... |
aed73dc19c24a5b267d252214cae272328122be39e6faa58ba40c807a0c14252 | Python | 1,772 | 39 | import matplotlib.pyplot as plt
import numpy as np
def plotcluster2(X, lab):
"""
This function plots the embedding.
Parameters are:
'X' - N by D matrix. Each row in X represents an observation.
'lab' - True annotations of data X.
"""
if np.all(lab >= 0) and n... |
b7cfa29fec673751e36d7808b7aca35695e1d6f98ac5baa94d3978f714544b18 | Python | 1,772 | 67 | import os
import requests
import numpy as np
import pickle
import shutil
import tarfile
def load_batch(file_path):
with open(file_path, 'rb') as f:
dict = pickle.load(f, encoding='bytes')
x = dict[b"data"]
y = dict[b"labels"]
# Reshape and invert channel dimension
x = x.reshape(x.shape[0],... |
13e63c194f2e62da816a99a6c1199c9a57ca39f02323e95b187ef6bb0ae07e48 | Python | 1,773 | 50 | """
This module contains tests that run mozaik models and compare their output to a
saved reference.
"""
import numpy as np
import os
from mozaik.storage.queries import *
from mozaik.storage.datastore import PickledDataStore
from mozaik.tools.distribution_parametrization import PyNNDistribution
from parameters import ... |
180888c435cd4ada4380bd00bd31d96418cc10347ad4fec315f69e8ff2f73662 | Python | 1,773 | 48 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
import torch
from torch.nn import functional as F
def linear_with_folded_batch(
x: torch.Tensor,
... |
f9a956e813878838baffa0f3c75522be34076c410eb7e3e26be17480d3c8b6d6 | Python | 1,773 | 50 | #!/usr/bin/python
# Create bitmaps to check defacing of all NIFTI images
# python bids_deface_bitmaps.py
from pathlib import Path
import os
import os.path
import glob
import sys
import shutil
import fnmatch
def remove_after_final_underscore(input_string):
# Find the last underscore index
last_underscore_ind... |
4f0b0a1d191210eb2d5715fee223ac2f9e4a7983f2a73c224b9882484928ac53 | Python | 1,774 | 62 | from numbers import Number
import torch
from torch.distributions import Distribution, constraints
class Delta(Distribution):
"""Delta distribution.
This is used
Args:
loc (float or Tensor): location of the distribution.
"""
arg_constraints = {"loc": constraints.real}
# mypy complai... |
e819df628d1b6782bcbb589ce2de1c461324285e3c2003fadf5178139e5621d3 | Python | 1,774 | 28 | class parameter:
def __init__(self):
self.paradic = None
def para_load(self, zone):
if zone == 'Single':
para = {"type": "Single", "Task":"loadpred", "encoLen": 8, "decoLen": 96,
"encoder_pHVAC_in": 6, "encoder_pHVAC_h": 20, "encoder_pHVAC_out": 4,
... |
3d356f397ecfcd13f8e2b3d50dfe2b619543f8c95f8cdecd2d31c4dbb74e47aa | Python | 1,775 | 62 | import numpy as np
import re
from rdkit import Chem
def clear_map_number(smi):
"""Clear the atom mapping number of a SMILES sequence"""
mol = Chem.MolFromSmiles(smi)
for atom in mol.GetAtoms():
if atom.HasProp('molAtomMapNumber'):
atom.ClearProp('molAtomMapNumber')
return canonical... |
8b9f02168d3f15fae714cb953a0a8115471db3a8e81be0039f7681590fda4bcb | Python | 1,775 | 61 | import tensorflow as tf
# from tensorflow.keras import backend as K
import os, sys
import h5py
import matplotlib.pyplot as plt
from utils import *
import gc
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import matplotlib.pyplot as plt; plt.rcdefaults()
from tqdm import tqdm
import warni... |
334f629b53de37d267943cff985e236386433a6978f1e17fe3b56d0bfdce4285 | Python | 1,776 | 43 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jun 29 11:13:29 2022
@author: Yao Meng
"""
# import numpy as np
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from brainsmash.mapgen.stats import spearmanr
# import matplotlib.pyplot as plt
sns.set_theme(s... |
92d5a1a170d5fa10e9a4156f31735f0f25e99de4c9c8a212b6ff7b7ca76bf69b | Python | 1,776 | 56 | from setuptools import setup, Extension
from Cython.Build import cythonize
import numpy
import os
import sys
# 查找是否存在.pyx文件而不是.py文件
force_dir = os.path.dirname(os.path.abspath(__file__))
has_pyx = os.path.exists(os.path.join(force_dir, "fa2util.pyx"))
source_file = "fa2util.pyx" if has_pyx else "fa2util.py"
# 定义编译参数
... |
56807414b06407e0467e441295f494c2db6bdca672227bf2c824606f2460765b | Python | 1,779 | 58 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
import tempfile
from pathlib import Path
import pytest
from tests.core.testing_utils import launch_ma... |
ffef98be1967ee18e02682888dc6de9a4572bd170df83021d29e982d02f3fa13 | Python | 1,781 | 56 | import math
import torch
from pfrl.testing import torch_assert_allclose
from pfrl.utils.mode_of_distribution import mode_of_distribution
def test_transform():
base_dist = torch.distributions.Normal(loc=2, scale=1)
dist = torch.distributions.TransformedDistribution(
base_dist, [torch.distributions.tr... |
1d25525897743a240e528c86a200e05daaccf27118154eacbd4beff3b1a5cbfd | Python | 1,782 | 60 | import os
import numpy as np
import torch
from tqdm import trange
from solver import Solver
torch.set_default_tensor_type(torch.cuda.FloatTensor
if torch.cuda.is_available()
else torch.FloatTensor)
os.makedirs('results', exist_ok=True)
... |
0f39696b7ab73a946ef0292154fd87b04ee8e95c77951d8cd4942881242fc072 | Python | 1,783 | 59 | import os
import torch
def save_checkpoint(path, epoch, model, optimizer, params=None):
"""
Save a PyTorch checkpoint.
Args:
path (str): path where the checkpoint will be saved.
epoch (int): current epoch.
model (torch.nn.Module): model whose parameters will be saved.
opti... |
7241b95083cc3c9e36ab187aed818fc9afe023a5d73840c80cf7fab9368cad6c | Python | 1,783 | 53 | """Maximum intensity projection over one dimension for a window."""
import os
import numpy as np
from nibabel import load, Nifti1Image, save
nii = load('/Users/sebastiandresbach/data/neurovascularCouplingVASO/Nifti/derivatives/sub-06/ses-04/anat/megre/11_T2star/sub-06_ses-T2s_part-mag_MEGRE_crop_ups2X_prepped_avg_com... |
849701035146e49d518d5221ecf35fb0cd42e0753d71f394758ce405029af60b | Python | 1,784 | 44 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
8e61937bd7215129353fbf75ebf013f3571ba240a432b846a61845734c2d2822 | Python | 1,784 | 56 | #!/usr/bin/python
# -*- encoding: utf-8 -*-
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
class MixSoftmaxCrossEntropyLoss(nn.CrossEntropyLoss):
def __init__(self, ignore_index=-1, **kwargs):
super(MixSoftmaxCrossEntropyLoss, self).__init__()
self.ignore_... |
cfce00aabacee4d3f3646aefcc7b5006d3ffeea13bf6f4d125442f721248404a | Python | 1,785 | 63 | import numpy as np
from keras.models import Sequential
from keras.layers import LSTM, Dense
import matplotlib.pyplot as plt
from matplotlib.ticker import FormatStrFormatter, MaxNLocator
import time
plt.rc('font',size=15)
start = time.time()
x = np.load('data.npy')
data = np.zeros((10000,1))
data[:,0] = x[0,... |
ebbe2bee59d949a13341a2cba218423afdddf65751723f59f91fdee343af7a37 | Python | 1,785 | 69 | # Copyright 2023 Google 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, ... |
564893f4ad5cf8d1e6739f6025217cdda6e628333f909c1d048b38265f9e5161 | Python | 1,786 | 56 | import argparse
import functools as ft
import swap_errors.analysis as swan
def create_parser():
parser = argparse.ArgumentParser(description="fit several autoencoders")
parser.add_argument(
"data_file",
type=str,
)
parser.add_argument(
"-o",
"--output_folder",
... |
633a721f3fa8196346f7291a054b4733fde1a6e238671dee19b5f7bfd3afe2ef | Python | 1,786 | 46 | import torch
from ..distances import CosineSimilarity
from ..utils import common_functions as c_f
from ..losses.generic_pair_loss import GenericPairLoss
class NTXentLoss(GenericPairLoss):
def __init__(self, temperature=0.07, **kwargs):
super().__init__(mat_based_loss=False, **kwargs)
self.tempera... |
ecefae5d0120dd2ac770c8e9d853011d20d77917124f3092c38bb1f333a4a93d | Python | 1,786 | 60 | import logging
from pprint import pprint
import pandas as pd
import yaml
import pytest
from click.testing import CliRunner
from pathlib import Path
from deeprvat.deeprvat.config import cli as config_cli
from deeprvat.deeprvat.config import create_main_config, load_yaml
script_dir = Path(__file__).resolve().parent
tes... |
73160c12f5980791ebe112fcbb0a8dceceaf885c80cfe6527be4a57de15f24bb | Python | 1,787 | 58 | import numpy as np
import matplotlib.pyplot as plt
from math import sqrt
import matplotlib as mpl
def generate_parameter_sensitivity_plot(
final_performances=None,
param_axis_1=[],
colors=None,
yticks=[],
xticks=[],
labels=None,
xlabel='',
ylabel='',
):
... |
9eab0f9d36ebac96d6df8e29e4450eb9e1297868a3ca3ca24ce1f7fa29856b53 | Python | 1,787 | 53 | # Copyright 2023 Google 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, ... |
e08209a5674654d4b9392f46869b6e605b2b00f9cb629f687f55f030f9f0abb5 | Python | 1,787 | 64 | import pdb
import numpy as np
import torch
import torch.optim as optim
class Optimizer():
def __init__(
self,
model: torch.nn.Module,
args: dict,
) -> None:
self.model = model
self.args = args
if self.args['weight_decay'] is None:
self.optimi... |
4434f4813bbadbd29ae0d6bc7ad2cc1c87a997ca966704e4d528e1426039f800 | Python | 1,788 | 56 | import pytest
import os
import boto3
import zipfile
from moto import mock_aws
import unittest
from neuron_morphology.pipeline.post_data_to_s3 import post_object_to_s3, zip_files
path_to_current_file = os.path.realpath(__file__)
current_directory = os.path.split(path_to_current_file)[0]
file_name1 = "test_post_data_t... |
e6bde3e6e384c85033e9b9c59a426d9f65a570a0aca268dfac187143246342b0 | Python | 1,788 | 45 | """Lightweight CLI output helpers for cluster launcher context notes.
These functions produce informational output that disambiguates head-node
commands from local-machine commands. They have NO dependency on the ``ray``
C++ runtime and accept ``cli_logger`` / ``cf`` as explicit parameters so they
can be tested in is... |
00fa1751b48d2bb6fc7101b286463e8c502ed1e51c5ec83c364aec761a570dc6 | Python | 1,790 | 63 | import time
import tensorflow as tf
class PerformanceProfiler(tf.keras.callbacks.Callback):
def __init__(self):
super(PerformanceProfiler, self).__init__()
self.epochs_wall_clock_time_sec = list()
self.batches_wall_clock_time_sec = list()
self._epoch_start_wt = None
self.... |
5cbf55d0287a6b7398983ac47ec4cb29e96f0d5b56d3edeb1b2c50c65fe378a9 | Python | 1,791 | 68 | import cc3d
from tqdm import tqdm
import scipy.ndimage.measurements
import numpy as np
import time
import fastremap
def cc3d_test_multilabel(labels):
labels, remap = fastremap.renumber(labels)
res = cc3d.connected_components(labels)
N = np.max(labels)
for segid in tqdm(range(1, N+1)):
extracted = (res == s... |
03d707cf26776a5e80579cd5d142190f7319b38380f5090558554f7efbb5324b | Python | 1,792 | 61 | import numpy as np
import scipy.sparse as sparse
from hic3defdr.util.clusters import find_clusters
def threshold_and_cluster(qvalues, row, col, fdr):
"""
Thresholds pixels by comparing their q-values to a target FDR and clusters
the significant and insignificant pixels.
Parameters
----------
... |
4e5f3d12ae566e28d4ae54505d47750727987690d5f317d87d2539be21103ff4 | Python | 1,792 | 60 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
import pandas as pd
from behaviopy.plotting import qualitative_times
from behaviopy.utils import full_subsets
from os import path
import matplotlib.pyplot as plt
data_dir = path.abspath(path.expanduser('~/ni_data/ofM... |
6457523827314befd1452c8b4330c447a3916b452a0b8c0f5cd0e8d664e465e0 | Python | 1,792 | 60 | import json
import os
import click
from ci.ray_ci.bisect.bisector import Bisector
from ci.ray_ci.bisect.generic_validator import GenericValidator
from ci.ray_ci.bisect.macos_validator import MacOSValidator
from ci.ray_ci.utils import ci_init, logger
from ray_release.test import (
Test,
TestType,
)
from ray_r... |
96c942cf19d1d446eb5a88c69a00f17fa0a7beef0b9d29d8aa9084cdec9577df | Python | 1,792 | 41 | import torch
import torch.nn as nn
class LSTM(nn.Module):
def __init__(self, input_size, hidden_size, output_size, num_layers=1):
super(LSTM, self).__init__()
self.input_size = input_size
self.output_size = output_size
self.hidden_size = hidden_size
self.num_layers = num_la... |
dd95620004a5e9d1e54a65e705abcac8ca9ae7b8f0d5304fb335f1a0e6f1d3dc | Python | 1,792 | 59 | import itertools
import pytest
class TestAllCallbacks:
@pytest.fixture
def callbacks(self):
"""Return all callbacks"""
import skorch.callbacks
callbacks = []
for name in dir(skorch.callbacks):
attr = getattr(skorch.callbacks, name)
# pylint: disable=un... |
f44bedf7a80860f2e8f46567d3bb156539dbc30115946ed0f8a2002c91c8bb43 | Python | 1,793 | 77 |
import numpy as np
class Histogram:
def __init__(self, _min = 0, _max = 0.1, bins = 10000):
self.min = _min
self.max = _max
self.bins = bins
self.data = []
self.dx = (self.max - self.min) / self.bins
self.norm = 0
self.act_min = self.max
self.act_max... |
31417987cd40271b704e8a190d37ab906f3884af85e3be56d6ffc8e00499bd85 | Python | 1,794 | 57 | from typing import TYPE_CHECKING, List
import pyarrow
from packaging.version import parse as parse_version
if TYPE_CHECKING:
from ray.data._internal.planner.exchange.sort_task_spec import SortKey
pl = None
# Polars 0.16.8 introduced the `descending` parameter for the `sort` method,
# replacing `reverse`.
# See ... |
2ae200465d26e1091a1cd91853dc45e7ddb5dba2f9962c444f4b837bba56d35b | Python | 1,799 | 56 | from __future__ import annotations
"""
Minimal GitHub repository content extractor using PyGithub if available.
Collects README (if present) and basic repo metadata into markdown files.
"""
from typing import List, Tuple
def extract(repo_slug: str) -> List[Tuple[str, str]]:
"""Extracts README and metadata for ... |
cf2874860bff0f5ba8164bfe4ceb95ae0f0dd8e5274b39ed0fdf8a99011cdbba | Python | 1,799 | 24 | import matplotlib; matplotlib.use("Agg"); import matplotlib.pyplot as plt
from matplotlib.patches import FancyBboxPatch, FancyArrowPatch
plt.rcParams.update({"font.family":"DejaVu Serif"})
fig,ax=plt.subplots(figsize=(9,4.8)); ax.set_xlim(-0.4,10); ax.set_ylim(-1.3,4.6); ax.axis("off")
def box(x,y,w,h,t,c):
ax.add_... |
493ae78efd5e63e080bcd1aa430788620f4fc1727b843cd1050b92d3e15222bb | Python | 1,801 | 59 | import importlib
import os
import torch
import torch.nn as nn
from pytorch3dunet.datasets.utils import get_test_loaders
from pytorch3dunet.unet3d import utils
from pytorch3dunet.unet3d.config import load_config
from pytorch3dunet.unet3d.model import get_model
logger = utils.get_logger('UNet3DPredict')
def _get_pre... |
7ab942b8bf74e55d5904ad46d45a43a7cff7f0adce8502228284c6bf810ba11c | Python | 1,801 | 58 | import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple
_NAMESPACE_CACHE_SIZE = int(os.environ.get("LANCE_RAY_NAMESPACE_CACHE_SIZE", "16"))
def _has_namespace_params(
namespace_impl: Optional[str],
table_id: Optional[List[str]],
) -> bool:
return namespace_impl is not Non... |
aea219a5e7fe78d4eba07f8a5c9f08abfcba3ad235bcca943dd08af803ab9e3a | Python | 1,801 | 76 | import os
from datetime import datetime
from pathlib import Path
from importlib import resources
import dotenv
import torch
from pytz import timezone
from flyvis.version import __version__
device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
torch.set_default_device(device)
del torch
... |
95b099d9a9b1dae906d8980e70455d233197fdace1304951055ddacd04eb2478 | Python | 1,802 | 61 | import sys
from parameters import ParameterSet
from mozaik.models import Model
from mozaik.connectors.modular import ModularSamplingProbabilisticConnector
from mozaik import load_component
from mozaik.space import VisualRegion
import mozaik
class ModelMapDependentModularConnectorFunction(Model):
required_paramete... |
5d30f8df4ad682d6c5fffb67f62fc253e857544c20dd24d3d9cb1e19fac171f5 | Python | 1,803 | 82 | import numpy as np
def make_rendered(env, *render_args, **render_kwargs):
base_step = env.step
base_close = env.close
def step(action):
ret = base_step(action)
env.render(*render_args, **render_kwargs)
return ret
def close():
env.render(*render_args, close=True, **ren... |
73e536b26ec7c4f063ba456bb91ab4c495f236dd20b7b6cdd501ee0bcda8d80d | Python | 1,803 | 64 | # -*- coding: utf-8 -*-
"""
Created on Fri Feb 02 15:08:00 2024
@author: ju-bar
data alignment
This code is part of the 'emilys' repository
https://github.com/ju-bar/emilys
published under the GNU General Publishing License, version 3
"""
import numpy as np
def get_row_align(a, ref_row=0):
"""
Calculates s... |
ad1b64b5803a530da5605fc42e2d20daf95f1496e79a12fd5bc68d7388ea1b8e | Python | 1,803 | 45 | import numpy as np
import pickle
import pandas as pd
import sklearn.model_selection as md
import matplotlib.pyplot as plt
import os
import seaborn as sb
# Load and separate the dataset
with open('./model_optimisation/balanced_epochs.pickle', 'rb') as handle:
balanced = pickle.load(handle)
trainset = balanced[balan... |
6375ef11f3ef78b3ab082fd97e225c32b1651e5c4b5f72b7ee5ad7c84c32f05f | Python | 1,804 | 53 | # Copyright 2023 Google 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, ... |
855d07d4610d21d03259fae5bcafd86140661e84d75e1fd2b1a3e2b16ca7dff5 | Python | 1,804 | 62 | #!/usr/bin/env python
import sys
import os
import argparse
import gzip
import vamb
parser = argparse.ArgumentParser(
description="""Creates the input FASTA file for Vamb.
Input should be one or more FASTA files, each from a sample-specific assembly.
If keepnames is False, resulting FASTA can be binsplit with sepa... |
86f31ff39847ebcac1c0fb66d25d2680bb78c6fdf6883b138836b8d9cee30c65 | Python | 1,804 | 67 | import numpy as np
import torch
from accelerate import Accelerator
from sklearn.datasets import make_classification
from sklearn.model_selection import cross_validate
from torch import nn
from torch.distributed import TCPStore
from skorch import NeuralNetClassifier
from skorch.hf import AccelerateMixin
from skorch.his... |
25a93c40834e30971ffe5a01be185514fb34f83e6c5647f1c04bceb0c4dc3904 | Python | 1,805 | 63 | """
Documentation example and test for embedding model batch inference.
"""
import subprocess
import sys
subprocess.check_call([sys.executable, "-m", "pip", "install", "--upgrade", "ray[llm]"])
subprocess.check_call([sys.executable, "-m", "pip", "install", "numpy==1.26.4"])
def run_embedding_example():
# __emb... |
8711e10285c6f5ca1e4b1223b58472906e38346b30cf44939a54875da7e018ec | Python | 1,806 | 57 | """Script to validate a single network across all its checkpoints."""
import argparse
from flyvis import NetworkView
from flyvis.analysis.validation import validate_all_checkpoints
from flyvis.utils.config_utils import HybridArgumentParser
def main():
parser = HybridArgumentParser(
hybrid_args={
... |
b14b1b57b90178763274b5c7ae601a22aff99706b44ebdf91a7e1f1dd82d4246 | Python | 1,806 | 52 | # -*- coding: utf-8 -*-
import numpy as np
from vtkplotlib.plots.BasePlot import ConstructedPlot
class Polygon(ConstructedPlot):
"""Creates a filled polygon(s) with **vertices** as it's corners. For a 3
dimensional **vertices** array, each 2d array within **vertices** is a separate
polygon.
:param ... |
d9fa1c8c8e0a1cee5cb02ac78437587a9065171d9ab1e2960df06c81c7a3f1bb | Python | 1,806 | 50 | # @String(value="This script converts all .traces files in a directory into SWC. Conversion log will be shown in Console.", visibility="MESSAGE") msg
# @File(label="Directory of .traces files:", style="directory") input_dir
# @Boolean(label="Open Console", value=false) open_console
# @LogService log
# @StatusService st... |
daf664ac879ad99bd706f72742eec3bbf886ab3df1ec064015355ceaa56360e5 | Python | 1,806 | 42 | # Copyright 2021 Division of Medical Image Computing, German Cancer Research Center (DKFZ)
# and Applied Computer Vision Lab, Helmholtz Imaging Platform
#
# 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 L... |
86fcae8681c8905046c666238daf00d1af4920221a6a1cd6128181b6ebb3b977 | Python | 1,807 | 57 | import logging
class FileLogger:
def __init__(self, is_master=False, is_rank0=False, output_dir=None, logger_name='training'):
# only call by master
# checked outside the class
self.output_dir = output_dir
if is_rank0:
self.logger_name = logger_name
self.lo... |
1b4b01e861358be196aaa4a193286b6332318f0f4fea5bed02662c417fe3e587 | Python | 1,808 | 49 | #!/usr/bin/env python
from __future__ import print_function
import argparse
import glob
import sys
import numpy as np
import pysam
MISSING_QUAL_CHAR = '"' # got from calling 'samtools bam2fq' on bam w/o qualities
def parse_args():
parser = argparse.ArgumentParser("Produce FASTQ file from soft-clipped reads")
... |
47d35089a7eff7848efa9741a8252557c99f0d3a025a852c006d88d29b2b6f91 | Python | 1,808 | 69 | import os
import pickle
from typing import Tuple, Union
import numpy as np
import yaml
def load_yaml(path):
with open(path) as file:
content = yaml.load(file, Loader=yaml.FullLoader)
return content
def dump_config(args, path):
with open(os.path.join(path, "args.yaml"), "w") as outfile:
... |
8a8f5cdee04217648e17f6bc264688935f78134d68e93b0e74cb725c9ad9dbf4 | Python | 1,808 | 49 | from __future__ import annotations
import logging
from pathlib import Path
from ._config import GenerateLdscoreConfig
from ._style import Colors, EMOJI
logger = logging.getLogger(__name__)
def _ensure_symlink(link_path: Path, target_path: Path) -> None:
"""Create a symlink when missing and validate existing li... |
b322ed93a8c23d0464e3a945e91a718cf199277f4b714b278bc20ad57e9bd2cb | Python | 1,808 | 50 | # -*- coding: utf-8 -*-
"""
This script will calculate the Bayes Factor
for the null behavioural and RIFT restuls
from the perceptual_load project.
the input is the Pearson rs from MATLAB
the output is bayes factor.
@author: GhafariT
"""
import pingouin as pg
import numpy as np
import pandas as pd
imp... |
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