sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
0bd8faaee920408d67fc97902e8646b8375f530cc25d287221d3d3a7a79d6cc4 | Python | 3,064 | 102 | import logging
import os.path
from typing import List, Optional
from pip._internal.cli.spinners import open_spinner
from pip._internal.utils.setuptools_build import make_setuptools_bdist_wheel_args
from pip._internal.utils.subprocess import call_subprocess, format_command_args
logger = logging.getLogger(__name__)
d... |
146d826cc92dd3c24899747217c2797a2d5b55033ac61b0d1cb62907459e3300 | Python | 3,064 | 86 | """The Laplacian solver's output field: float32, and axis solves are independent.
Two changes are pinned here:
1. The returned deformation field is float32 (the solve itself stays float64),
matching the sibling sliceToSlice3DLaplacian. It holds per-voxel displacements
in VOXELS, so float32's ~7 significan... |
3fec2c5d9e1747ce9740f1435a967ec3ed39e27b9352d8caeef5bab721fa3919 | Python | 3,064 | 119 | """
Dynamic of the buffer
Shows how the buffer gets values closer to the median when time increases
"""
import time
from pathlib import Path
import numpy as np
import ray
from median.distributions import Distribution
from median.median import run_new_median_full
from median.utils.utils import pretty_time
def gener... |
60466194b53c7e1721c2346c68164b5edbed1ad42a435e970db04f951d3e4b33 | Python | 3,064 | 96 | from __future__ import division
from functools import partial
import logging
import numpy as np
import pandas as pd
"""
Created on Mon Aug 20 20:30:31 2018
@author: Hannah Choi
"""
"""
This code contains functions needed for mapping TC clusters to FF/FB by
maximizing the global hierarchy score of the ... |
62584b4d1976a07040baa85cfb398bed4492ebb4cf5951c89a3780407ade6534 | Python | 3,064 | 84 | import itertools
import os
import shutil
import sys
from typing import List, Optional
from pip._internal.cli.main import main
from pip._internal.utils.compat import WINDOWS
_EXECUTABLE_NAMES = [
"pip",
f"pip{sys.version_info.major}",
f"pip{sys.version_info.major}.{sys.version_info.minor}",
]
if WINDOWS:
... |
76f9b3100df12adb7321259ea5617df1dee3d1705d9a5666d47b19ef396d642e | Python | 3,064 | 79 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
89f46f37cd171f02625afbd1ad2c0245529397b9738bf1a64b7888d6e1a3825b | Python | 3,064 | 100 | import argparse
import collections
from typing import Any
class dotdict(dict):
"""
From user derek73 at
https://stackoverflow.com/questions/2352181/how-to-use-a-dot-to-access-members-of-dictionary
and user Trevor Gross in the comments.
dot.notation access to dictionary attributes.
"""
... |
c860b1b1fbb8eae304587b437f33ba8b3cecfe601690b6bf802f714a1257916c | Python | 3,064 | 113 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
e66332eaa9a86842362f84438f25af233625de2ab40a0c6f76c4958412ceb2c2 | Python | 3,064 | 73 | import numpy as np
def list_of_dicts_to_dataframe(lst_results, st_key):
# expects lists of results, returns a long-form dataframe of one
# extra result keys are retained in the dataframe
import pandas as pd
dfs = []
for result in lst_results:
df = pd.DataFrame(result[st_key])
... |
20a373512a77eb48135c7422c33afda4e29c86065c4b10e0815ad36e6fca1f70 | Python | 3,065 | 89 |
'''
Part of the code modified from
https://github.com/andabi/music-source-separation
'''
import librosa
import numpy as np
from config import SE_Config
import soundfile as sf
from mir_eval.separation import bss_eval_sources
def to_spec_torchaudio(audio, config):
return
def get_chunks(spec, dur = 64, height = ... |
63d70ec28a1960663a719e9506f951d74a37c8a1ed64755e09a7891127eadbd3 | Python | 3,065 | 109 | """Converts an MNE Epochs object to a Signal object."""
import os
import sys
from pathlib import Path
cd_path = Path(__file__).absolute().parent.parent
sys.path.append(os.path.join(cd_path, "coherence"))
from coh_handle_files import generate_sessionwise_fpath
from coh_handle_files import load_file
from coh_loading i... |
7f5201c0486826a1369a23a37bb05f78754b553d3f6d41ff695f1ca0a067fc6b | Python | 3,065 | 101 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from __future__ import print_function
from HDPGPHSMM_segmentaion import GPSegmentation
import time
import matplotlib.pyplot as plt
import os
import numpy as np
import pandas as pd
import glob
def learn( savedir, dim, gamma, eta, initial_class, avelen, max... |
91fc4665bbbed5b9d8b58e06434670a3de79054fdaa06f98dc9fe8c2acf4681e | Python | 3,065 | 103 | # Import libraries
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import Dataset, DataLoader
import torch.nn.functional as F
import matplotlib.pyplot as plt
import os
import pickle
import numpy as np
from sklearn import metrics
from sklearn.model_... |
188973b56b6d4a3640f5db6e71de3288897a4c89e4eedd8bdd9b10d19f91d1df | Python | 3,066 | 84 | """The standalone TIFF read helpers must default to NO reorientation (opt-in).
Companion to test_tiff_load_no_auto_orient.py (which covers load_volume). Here we
cover read_tif_section / read_multipage_tif / load_tiff_volume - the primitives
used by cell-counting, nii-creation, OME-Zarr, and the NG viewer.
"""
... |
a0a7291448026e28cb28bf49caa0f965b1167c82f2334c77693e8fbdd5088b3f | Python | 3,067 | 62 | import json
import os
import unittest
from hed.tools.bids.bids_file import BidsFile
class Test(unittest.TestCase):
@classmethod
def setUpClass(cls):
events_file = "../../data/bids_tests/eeg_ds003645s_hed/sub-002/eeg/sub-002_task-FacePerception_run-1_events.tsv"
sidecar_file = "../../data/bids... |
e9fca7f82f2b20fcb286b16d37d995b77504d3103c085613f0f648a204eae82a | Python | 3,067 | 80 | import numpy as np
from scipy.stats import ortho_group
def simulate_csd(n_domains,
n_per_domain,
p,
k,
corr_noise=True,
noise_scale=1.,
corr_top=1.,
diag=None):
"""Simulate data from the CSD ('com... |
7ff70edf18342dbed6052433f2ef6b0e1f9e51f996392e32fc6fd226cf814a32 | Python | 3,068 | 84 | import numpy
import pickle
import struct
import sys
t_start = float(sys.argv[1])
t_end = float(sys.argv[2])
f = open('heart_remeshed_3D.ensi.case', 'r')
line = f.readline()
while line != 'TIME\n':
line = f.readline()
line = f.readline()
time_set = line.split()[-1]
line = f.readline()
number_of_steps = float(line.s... |
b67253d671fc918d820bfe1b69e34755a1c66e5a5e22fa2898e977d06e3ea98a | Python | 3,068 | 77 | import os
import unittest
from hed.models.definition_entry import DefinitionEntry
from hed.models.hed_string import HedString
from hed.schema import load_schema_version
class Test(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.base_data_dir = os.path.join(os.path.dirname(os.path.realpath(_... |
c6aaec3dd4aaedd17c99ccb877e397bfd52753358efd78ca76c81d02f8ea5336 | Python | 3,068 | 92 | """Originally by @rhizhiy
https://github.com/bayesian-optimization/BayesianOptimization/issues/347#issuecomment-1273465096
"""
import time
from typing import Callable
import matplotlib.pyplot as plt
import numpy as np
from bayes_opt import BayesianOptimization
from bayes_opt import acquisition
from scipy.optimize impo... |
282ea5ff55ef650aae4450c73a64060adba7df0d37d8ef567f44eee88930aa20 | Python | 3,069 | 86 | # MEGIT model inference related functions
# Refer to OptiFlex package (https://github.com/saptera/OptiFlex) for more information
import os
import numpy as np
import cv2 as cv
import h5py as h5
import keras
from ..utils import prog_print
"""Constant list:
default_model: MEGIT default pose estimation mod... |
56bff5c1eb89bc01e2d6883accf4a3b8f423ffb25182cb53457e05cacc20377e | Python | 3,069 | 85 | """
Created on 25/05/2020
:author: Chinchien Lin
:summary: Adds padding to the files contained in source field of the configuration field.
Then save in the destination folder
"""
import os
import sys
import numpy as np
from src.commands.abstract_preprocessing_command import AbstractPreprocess... |
616b8c0a86eb88eb4423c1e88d9207b9fd47ce0cb78ca1e5ab49df1e2f9bf580 | Python | 3,069 | 103 | # Import libraries
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import Dataset, DataLoader
import torch.nn.functional as F
import matplotlib.pyplot as plt
import os
import pickle
import numpy as np
from sklearn import metrics
from sklearn.model_... |
d16f44b9c9b49f489f5609c8c3063583dd504875a9d2e62fef10d16b0eb13154 | Python | 3,069 | 92 | import os
from argparse import FileType, ArgumentParser
import numpy as np
import pandas as pd
from Bio.PDB import PDBParser, MMCIFParser
from Bio.Seq import Seq
from Bio.SeqRecord import SeqRecord
from tqdm import tqdm
from Bio import SeqIO
parser = ArgumentParser()
parser.add_argument('--out_file', type=str, defaul... |
45ec3e427841bea9e6414b472f88bf2c076379d47ac014d611e648cbbce3a630 | Python | 3,070 | 92 | import torch
import torch.nn as nn
from elasticai.creator.nn.integer.MPQ.encoderlayer import EncoderLayer
from elasticai.creator.nn.integer.MPQ.sequential import Sequential
from elasticai.creator.nn.integer.vhdl_test_automation.file_save_utils import (
save_quant_data,
)
class Encoder(nn.Module):
def __init_... |
ee1cf0cc9f7423218e82144bd6034804129ffdb0e69e78efa925d0c92875bb59 | Python | 3,070 | 91 | # Node group "Ease Switch" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# Shared by several assets, which import it; not an asset itself.
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenerated ... |
ad97ada90245c3e716608094727bbc7d1c12ff055466ca10d38d2a7d3b740792 | Python | 3,071 | 98 | # Node-group asset "Offset Color Attribute" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenerated from it on the next dump.
from typing import TYPE... |
42c2747f2d7d955349107237dc0123fdf23d9ff15f64314ea20bc19e4da8cdd5 | Python | 3,072 | 102 | """
Created on 04/06/2020
:author: Chinchien Lin
:summary: Extract mask images from the source field in the configuration file.
Then, save the extracted masks in the directory specified in the destination field.
"""
import os
import sys
import numpy as np
from PIL import Image
from src.command... |
54c447571dd924e0a556faa84bbe5dcaa186d3156c159d31147a3c37f730dec7 | Python | 3,072 | 80 | """Regression guards for review fixes to CCF section-browse mode."""
import os
os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")
import numpy as np
import pytest
pytest.importorskip("PySide6")
import nibabel as nib
import tifffile
from PySide6.QtWidgets import QApplication
from regtools.ccf_boundary_... |
8e0d402e881c60653de93412f62b0197a742aefc39cb9fbe04ffcafae164ffcb | Python | 3,072 | 91 | """
pygments.regexopt
~~~~~~~~~~~~~~~~~
An algorithm that generates optimized regexes for matching long lists of
literal strings.
:copyright: Copyright 2006-2023 by the Pygments team, see AUTHORS.
:license: BSD, see LICENSE for details.
"""
import re
from re import escape
from os.path import ... |
31eabd70567e30c056ad1192102ad0268de3e0a1c3a2ca9708d27b00854db459 | Python | 3,073 | 100 | # Node-group asset "Between Integer" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenerated from it on the next dump.
from typing import TYPE_CHECKI... |
7a9653d86e9f89057a9741fefb17e6dbfb3c10ecfd1fdc6fd9c790a00c97d99e | Python | 3,073 | 103 | import os
from distutils import log
import itertools
flatten = itertools.chain.from_iterable
class Installer:
nspkg_ext = '-nspkg.pth'
def install_namespaces(self):
nsp = self._get_all_ns_packages()
if not nsp:
return
filename = self._get_nspkg_file()
self.output... |
8a1d91098a11ce4c2b6a8419aa3762ab168fa04b48626e21a671fb98986c31e8 | Python | 3,074 | 72 | #! /usr/bin/env python
# ==============================================================================
# Copyright (c) 2021, Ko Sugawara
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Re... |
9220cb0fb50a2db84bb4aee20c444908c7962f8755b243cb38a62b1bdadd6764 | Python | 3,074 | 81 | #! /usr/bin/env python
from lab.parser import Parser
parser = Parser()
parser.add_pattern('ms_final_size', 'Final transition system size: (\d+)', required=False, type=int)
parser.add_pattern('ms_construction_time', 'Done initializing merge-and-shrink heuristic \[(.+)s\]', required=False, type=float)
parser.add_patter... |
93816c335370e63f272f742335b987739570463c439e8896d519b7f5a31361bd | Python | 3,074 | 104 | #! /usr/bin/env python3
# FutureWarnings from import corrupting fspoll output/parse
# alternatively, could eg prefix each 'real' output line with
# a sentinel or keyword
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
import sys
import os
import string
import re
import glob
#import nump... |
e33ee4b2371540a7041d3ac62ef9614b1292897bdc3b9ee457ebc5ee9de8ba1f | Python | 3,074 | 95 | import random
import string
import sys
import unittest
import neurolib.optimize.exploration.explorationUtils as eu
import numpy as np
import pytest
from neurolib.models.aln import ALNModel
from neurolib.optimize.exploration import BoxSearch
from neurolib.utils.loadData import Dataset
from neurolib.utils.parameterSpace... |
e9d7a63903ffbc65db92c4e3b5341d896f3b1b360113dbc3bd035bc5bc19ab28 | Python | 3,074 | 83 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
20d43a285bb057eabe0aa52a44a11fb27877fb2b54a25a31cc12bbdc158bcfa0 | Python | 3,075 | 64 | #!/usr/bin/env python
## this script creates dataframes from the full similarity matrices for each movie and parcel
## and saves them to a new CSV file
## The dataframes contain the correlation values for each pair of subjects.
import pandas as pd
from pathlib import Path
# Define the range for nodes
num_nodes = 210 ... |
2cf663e07d5949b0d01e8c5c03cbcc6dfe8d783659400ebf3153aa3be5040408 | Python | 3,075 | 96 | import torch
from torch import nn
from typing import Dict, Optional
__all__ = ["RadialLayer",
"EmbeddingLayer",
"CutoffLayer",
"TensorActivateLayer",
]
class EmbeddingLayer(nn.Module):
def __init__(self) -> None:
super().__init__()
def forward(self,
... |
48034084f677b3f908c3266289c10b393b6a9724b46c5ac28618dab3b0f524d9 | Python | 3,075 | 101 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from __future__ import print_function
from HDPGPHSMM_segmentaion import GPSegmentation
import time
import matplotlib.pyplot as plt
import os
import numpy as np
import pandas as pd
import glob
def learn( savedir, dim, gamma, eta, initial_class, avelen, max... |
fedb8333f40c5c34b13932fd66b382d70b48b258f85ff3fe51efb3e0719b4731 | Python | 3,075 | 87 | """
ALGORITHM FUNCTIONS
These functions implement the necessary calculations of the AARE and thd values.
"""
import numpy as np
# calculating AARE_t
def aare(self, time, predicted):
# calculating aare
sum_ = 0.0
for y in range(self.window_beginning, time + 1, 1):
# calculating coefficient for a... |
8e243ea7ebaeeed3e6e4bb5fc39d97322a5cb86803d27334fcef208a15e5d75d | Python | 3,076 | 98 | # This code calculates the intermediate scattering funtion ISF
#from the cage relative displacements for a dense colloidal suspension.
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.spatial import KDTree
import time
# load data
af = '60'
dia_big=3.34
path = '/media/hdd2/P2-Entr... |
7e968679d0103419a9be9daa6b8817bf5b08f761453e9f590c0ddd908e6a703c | Python | 3,077 | 64 | """code for automating data uploads via rclone"""
import subprocess as sp
import os
from pathlib import Path, PurePosixPath
import logging
logger = logging.getLogger(__name__)
class Uploader:
def __init__(self, local_project_dir, cloud_data_dir=None, video_framerate=30):
logger.debug('Beginning Uploader i... |
f4a01c2669a25bf64e642600ba156cc88510f8f93e71e0ae3df24cc55dfc9d73 | Python | 3,077 | 76 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
0ca235260ef10aeffc9d561c7c59243f77cac618f52b6ab6d5f8682bd034f605 | Python | 3,078 | 88 | #!/usr/bin/env python
#================================================================
# Copyright (C) 2023 Yufeng Liu (Braintell, Southeast University). All rights reserved.
#
# Filename : calc_glob_features.py
# Author : Yufeng Liu
# Date : 2023-01-24
# Description :
#
#============... |
7f861c5ff49df6111215defb6d09afd625232c0d7013a24e4e010615a87eb725 | Python | 3,078 | 107 | from .laplacian import solveLaplacianFromCorrespondences
# Configuration and diagnostics
from .config import (
HAS_ANTS,
DEFAULT_REGISTRATION_METHOD,
check_ants_environment,
estimate_registration_memory,
)
# Image I/O and axis alignment
from .io_utils import (
extractMetadata,
ext... |
9e80c8854d1c59cde3d877415984f56776aaaeeaa8b9bfbceb5bf2a15605995a | Python | 3,078 | 68 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Jan 21 11:22:56 2023
This script computes the lists of subjects to include and exclude based on the different exclusion criteria :
X is a threshold used in erratic answers
- more than X% of erratic answers (answers against the prior and the likel... |
c816c2dd37f9cdd57c0a8b33989b13286f85644cb677052369277438b99c5834 | Python | 3,078 | 79 | """Pure data types for the CCF boundary editor.
Extracted from ``contour_edit.py`` so the dataclasses live separately from
the deformation-application algorithm. Anything that *describes* an edit
goes here; anything that *applies* an edit stays in ``contour_edit.py``.
These types are deliberately framework-free... |
00e81f87e6b4cf38463a52305602abe380e4409d0ca28c2665c018cd7152a297 | Python | 3,079 | 93 | import pytorch_lightning as pl
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from models.common import create_decoder, create_encoder
class BetaVAE(pl.LightningModule):
def __init__(self, height, width, input_channels, latent_dim, beta=1.0):
super().__init... |
0bb1edae0102bca5137d511afa9a6a6ca7f20bd812c894bc2180a04d607e83be | Python | 3,079 | 81 | import ast
import csv
import os
import sys
from pickle import dump
import numpy as np
from tfsnippet.utils import makedirs
output_folder = 'processed'
makedirs(output_folder, exist_ok=True)
def load_and_save(category, filename, dataset, dataset_folder):
temp = np.genfromtxt(os.path.join(dataset_folder, category... |
0ccc378c8c88a03a5af21233e77bae83f63d5ffe26fd3269e5f45ad6b88d4d30 | Python | 3,079 | 103 | # Import libraries
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import Dataset, DataLoader
import torch.nn.functional as F
import matplotlib.pyplot as plt
import os
import pickle
import numpy as np
from sklearn import metrics
from sklearn.model_... |
4cff813707420024870065c532fabb1f9ebc73e866803a0c703096702e65e4f8 | Python | 3,079 | 90 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
7d13eb327ee5c7d817fb6a78c6c7ab7744138af72562640b9eb1132445320956 | Python | 3,079 | 65 | #!/usr/bin/env python
## this script creates dataframes from the similarity matrices
## (upper triangle) for each movie and parcel
## and saves them to a new CSV file
## The dataframes contain the correlation values for each pair of subjects.
import pandas as pd
from pathlib import Path
# Define the range for nodes
... |
ae0870adb5c6c75cb0cfda393e204bb1949c126d14485a1a7561dd34521c5be8 | Python | 3,079 | 86 | """
RERE ALGORITHM FUNCTIONS
These functions implement the necessary calculations of the AARE and thd values.
"""
import numpy as np
# calculating AARE_t
def aare(self, time, predicted):
# calculating aare
sum_ = 0.0
for y in range(self.window_beginning, time + 1, 1):
# calculating coefficient f... |
2cbdecfafa1eebbe2f7c998afae8fc90a5cb315c53770ffe14e482527ec97230 | Python | 3,081 | 125 | from numpy import *
from pylab import *
nu = ['7','10','20','40','60','80']
norders = ['3','5','7']
tf = zeros((6,3))
ts = zeros((6,3))
np = zeros((6,3))
tq = zeros((6,3))
mf = zeros((6,3))
errs = zeros((6,3))
for inu in range(6):
for ino in range(3):
fname = 'data_nov15_2021/diary_ik1_np'+str(nu[i... |
3e000a81e33db85b9ef27925ce6210ecae4a0cc6548a8229229c3887cf03fb1e | Python | 3,081 | 112 | #!/usr/bin/env python2.7
from __future__ import print_function
import argparse
from pddlstream.algorithms.focused import solve_focused
from pddlstream.algorithms.incremental import solve_incremental
from pddlstream.language.constants import PDDLProblem, Or, Exists, print_solution
from pddlstream.language.stream impo... |
749e1ec9a94531ef80ad12030915ffb3af8c54db4e5c1301a595afdc1ea210e0 | Python | 3,081 | 46 | # C. Cocuzza, 2021
# Function to identify outlier participants in category selectivity (MAF project).
# Using a very conservative number of deviations above or below the median: 5
# See here for more: Leys, C., Ley, C., Klein, O., Bernard, P., & Licata, L. (2013). Detecting outliers: Do not use standard deviation arou... |
b5a3f647b9b8f0677217d2c4af30d6067cdd5651db47f379058ab311bc0dc3ed | Python | 3,081 | 102 | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from mmcv.cnn import constant_init, kaiming_init
from mmcv.utils.parrots_wrapper import _BatchNorm
def default_init_weights(module, scale=1):
"""Initialize network weights.
Args:
modules (nn.Module): Modules to be initialized.
... |
f4952d7c59d45583f7585953386bdc278bbd31afdcb3bf30412ab6edb5e1799f | Python | 3,081 | 77 | # import libraries
import numpy as np
from scipy.stats import multivariate_normal
import matplotlib.pyplot as plt
import sys
import os
# import modules within repository
sys.path.append('C:\\Users\\dreww\\Desktop\\hyperbolic-learning\\utils') # path to utils folder
from utils import *
#-------------------------------... |
09325393fe3a6a156640f2c99ce17a5d7e4d27b9ee1439f756d18a1de2172612 | Python | 3,082 | 89 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
plt.style.use('seaborn')
# %matplotlib inline
import networkx as nx
import sys
import os
# import modules within repository
my_path = r'C:\Users\Cole S Baker\Desktop\Thesis\Thesis\hgcn\hyperbolic-learning-master\utils' # path... |
53a4926c5b53b305e1801f84feb3c66b673671075b791b7070b8d2f806bab506 | Python | 3,082 | 110 | from __future__ import division
import logging
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
"""
Created on Fri Aug 09 16:19:11 2019
@author: Hannah Choi
"""
"""
This code takes previously generated hierachy scores & global hierarchy score data from the "Results" folder, and make figures.
""... |
671e541da36e219f40d0efa22c2c072cc794639f42b551483df93595c998960c | Python | 3,082 | 71 | import sys
from os.path import join, dirname, realpath
current_dir = dirname(realpath(__file__))
sys.path.insert(0, dirname(current_dir))
import os
import imp
import logging
import random
import timeit
import datetime
import numpy as np
import tensorflow as tf
from utils.logs import set_logging, DebugFolder
from config... |
96f01370c08e5699aebd7bd96e38142ac838eed2cdf3004c6a71e52dc6f4db34 | Python | 3,082 | 96 | """Plotting parameters
----------------------
A dictionary with parameters defining the plotting.
"""
import numpy as np
# conversion factor from cm to inch
cm2inch = 1. / 2.54
# used by plotting.py
rcParams = {
# dpi for typical journal printing
'figure.dpi': 300,
# line width
'lines.linewidth': 1.... |
e58bf4acf93074b62055763566c42287c4d5e0ef722c257c97e079e83bb4650e | Python | 3,082 | 93 | # Node group ".MN_init_tmp_attributes" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# Shared by several assets, which import it; not an asset itself.
# _build_group() is the source of truth: the docstring, __init__ and accessors are ... |
f5e5a33d493967e9d9cce993d7b01d975988791ca9091e0600bd8785d55b27d2 | Python | 3,082 | 85 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
6118771f0d15ed506b89be9ef8b68e8fb36bd58ac0638c4da58624557212b808 | Python | 3,083 | 90 | '''Preprocess events from the presentation logs to the BIDS events file for the
nback task.
Parameters
----------
path : str
path where the raw data is stored
savepath : str
BIDS folder
'''
import os, sys
import re
import pandas as pd
from glob import glob
path = '/m/cs/... |
a37f708ff15b46a9941fe5932947db82ce4115627e871a0db43a642511dd4046 | Python | 3,083 | 102 | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from mmcv.cnn import constant_init, kaiming_init
from mmcv.utils.parrots_wrapper import _BatchNorm
def default_init_weights(module, scale=1):
"""Initialize network weights.
Args:
modules (nn.Module): Modules to be initialized.
... |
4779395e26a6d940a9c669560868a9a657bef83c7fc994d747f37c19b24fd0db | Python | 3,084 | 86 | import cocotb
import pytest
from cocotb.triggers import Timer
import elasticai.creator_plugins.adders as adders
from elasticai.creator.arithmetic import int_arithmetic
from elasticai.creator.testing import CocotbTestFixture, eai_testbench
from elasticai.creator_plugins.multipliers.utils import (
generate_mult_test... |
2622d18a53a95fbdacc25a6bc1028e189a76bdd45c97e3314d339a85d92bda0f | Python | 3,085 | 72 | from typing import List
import torch
from tqdm import tqdm
import numpy as np
from chemprop.data import MoleculeDataLoader, MoleculeDataset, StandardScaler
from chemprop.models import MoleculeModel
def predict(model: MoleculeModel,
data_loader: MoleculeDataLoader,
data_right_loader: MoleculeD... |
50e0526af23a7d3448818528daedcd5108563482192c83b956e08a6fac71191d | Python | 3,085 | 96 | import os
import zipfile
import io
import numpy as np
from PIL import Image
from PIL import ImageFile
ImageFile.LOAD_TRUNCATED_IMAGES = True
def is_zip_path(img_or_path):
"""judge if this is a zip path"""
return '.zip@' in img_or_path
class ZipReader(object):
"""A class to read zipped files"""
zip_... |
e1cd003e4632b34e022a16ae33540c0b4e3486faf8591e570fc760b82434b282 | Python | 3,085 | 87 | import torch
import torch.nn as nn
import torch.nn.functional as F
from ..initializer import create_initializer
class Network(nn.Module):
def __init__(self, config):
super().__init__()
model_config = config.model.vgg
self.use_bn = model_config.use_bn
n_channels = model_config.n_c... |
2dcc27e1983be26adf7216ee249b83a6cccf9028af48443301818f0e1bfa8847 | Python | 3,086 | 94 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
60c26ced98197cd0fae4f44baa5181fda8297c65e57a6c7fe479b83ca9c1aa94 | Python | 3,086 | 103 | # Copyright 2016–2021 Julien Danjou
# Copyright 2016 Joshua Harlow
# Copyright 2013-2014 Ray Holder
#
# 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-... |
b24fb2027a5345b1a5f8dbcc1dcd2385a7772b16a633a3c7ec6f956b72ab9f97 | Python | 3,086 | 77 | """
Optuna example that optimizes a classifier configuration for cancer dataset
using XGBoost.
In this example, we optimize the validation accuracy of cancer detection
using XGBoost. We optimize both the choice of booster model and its
hyperparameters.
"""
import numpy as np
import optuna
import sklearn.datasets
im... |
e544449d81abae9d10bbbfb8b077e0db3002a611efd23d825abe153765df0cd6 | Python | 3,086 | 80 |
#import scanpy as sc
from sklearn.neighbors import NearestNeighbors
import anndata as ad
from scipy.sparse import csr_matrix
import numpy as np
import scanpy as sc
def UnfilteredAdataAdata(filteredPath, rawPath, outdir, nHKgenes=50, raw_to_filt_ratio=1, n_neighbors=20):
"""
RawFilt ratio is the number of raw cells... |
94ebf7933cabd0dd026d6b32975af0179beed34837ca72d7b7c0e31dffdee8af | Python | 3,087 | 86 | """Fixtures to test the spectrum devices without driver and cards."""
import ctypes
import importlib.util
from pathlib import Path
from types import ModuleType, SimpleNamespace
from unittest.mock import MagicMock, Mock
import pytest
import console.spcm_control.abstract_device as abstract_device
CARD_HANDLE = 1
def... |
0d278ed15115112fb901141df0f876581584319c9177db67019c87fd7daf395e | Python | 3,088 | 78 | # Copyright 2015 gRPC authors.
#
# 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 writing... |
563006937832f52b343dfed02a30f17c7c25127fd09e8117864e90fb74c49278 | Python | 3,088 | 82 | import re
import math
from pddlstream.language.constants import AND, OR, OBJECT, TOTAL_COST, TOTAL_TIME, is_cost, get_prefix, \
CONNECTIVES, QUANTIFIERS
from pddlstream.language.conversion import pddl_from_object, is_atom, is_negated_atom, objects_from_evaluations
from pddlstream.language.object import Object, Opt... |
26ffb8af63c2ab1af2f0f154653360c454923530d2d385982d49a0cd219358aa | Python | 3,089 | 114 | # Node-group asset "MN Typed Bundles" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenerated from it on the next dump.
from typing import TYPE_CHECK... |
301324cccb0759fdcae7258808c5f1062dbff052d72132892316e8a3f11bd152 | Python | 3,089 | 87 | import numpy as np
from basicsr.archs.rrdbnet_arch import RRDBNet
from realesrgan.utils import RealESRGANer
def test_realesrganer():
# initialize with default model
restorer = RealESRGANer(
scale=4,
model_path='experiments/pretrained_models/RealESRGAN_x4plus.pth',
model=None,
... |
638e0c35ae76baaabee048aceaf2d727e8cc82bce06dae42c34d6a942bb25d42 | Python | 3,089 | 79 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# 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 applicab... |
8c856976e89047ef8b48f38c00ba56b73dadc11023b0db4b59ce55bb7acc2cce | Python | 3,089 | 64 | """Diagnostic pilot: the steering_dynamics_probe.py plugin outside the GUI, plus one legacy run.
The plugin's settings can be overridden from the command line (e.g. when the GPU only fits a
smaller model). Example:
CUBLAS_WORKSPACE_CONFIG=:4096:8 PYTHONPATH=src python scripts/steering_probe_pilot.py \\
--prof... |
923bda1e7e336b0370ef53fd500e8b050f58d78b75bca05ca2a253d1c9fe9dc8 | Python | 3,089 | 64 | from lavaset_new import LAVASET
import numpy as np
import pandas as pd
from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split
import time
import csv
import sys
import os
from sklearn.mode... |
c5368e974df95e429106a4936b3111ee3532aa8815825216ca9b8b69bf389163 | Python | 3,090 | 76 | import os
from typing import Dict, Iterator, List, Tuple, Union
import pandas as pd
from torcheeg.datasets.module.base_dataset import BaseDataset
from .base_model_selection import BaseModelSelection
from .utils import create_subset, read_indices, validate_partitions, write_partitions
class TrainValTestSplitCrossTria... |
9b8378df70907bd7132dc2c9da963d689e331fa0ce428e21557d54c914b0f083 | Python | 3,091 | 95 | import os
import pandas as pd
from ckg import ckg_utils
from ckg.graphdb_connector import connector
def read_knowledge_queries(dataset_type='proteomics'):
queries_dir = os.path.abspath(os.path.dirname(__file__))
query_file = dataset_type+"_knowledge_cypher.yml"
queries_file_path = os.path.join(queries_dir... |
6ff9eee7f7f71c2812769e52fda351050d4c4829b86630f079cd8e993462724c | Python | 3,092 | 104 | """
pygments.scanner
~~~~~~~~~~~~~~~~
This library implements a regex based scanner. Some languages
like Pascal are easy to parse but have some keywords that
depend on the context. Because of this it's impossible to lex
that just by using a regular expression lexer like the
`RegexLexer`.
... |
9ee3251d03c2d39b2d3815c8de6a728e400ef68e10517d61e16a21b1b93d07df | Python | 3,092 | 51 | """POST HOC (8 Oct 2026, after the TWIN tuning). The tuned twin fits Seki's fly worse (best r 0.55) than the plain model with
the laboratory prior did (r 0.741, REAL_SCAN_OFFICIAL). Which added mechanism costs the fit? Same code (TWIN.run), F4 signs,
Seki's 17 odours, 3 trials:
A plain model: no resting firing, no d... |
2b66d3ec5b4e2eb5df27fe5fe881e2a10573c6d45575e9b14837b2156eb88848 | Python | 3,093 | 104 | """"""
import cv2
from pupil_recording_interface.decorators import process
from pupil_recording_interface.process import BaseProcess
from pupil_recording_interface.externals.circle_detector import CircleTracker
@process("circle_detector")
class CircleDetector(BaseProcess):
""" Circle detector for the world video... |
e5de2da15424944785dccd19d0a354bbe57b4ea11c9d35cf85df8e823ebdf4e5 | Python | 3,093 | 119 | # Node-group asset "Force Brownian" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenerated from it on the next dump.
from typing import TYPE_CHECKIN... |
fee3a971686b3b7dbf2a95a91e8010503c7510d4471c6b3253ca6dfa01f8e254 | Python | 3,093 | 101 | """Core recipes for universal machine-learned interatomic potentials."""
from __future__ import annotations
from typing import TYPE_CHECKING
from quacc import job
from quacc.recipes.mlp._base import pick_calculator
from quacc.runners.ase import Runner
from quacc.schemas.ase import Summarize
from quacc.utils.dicts im... |
a9819bf1025685cf5f64c79ad21780cb83e94e646c65ba94b1015d90e7376e8e | Python | 3,094 | 92 | import argparse
from cv2 import imread
import cv2
import matplotlib.pyplot as plt
import numpy as np
from constants import DEFAULT_CANVAS_SIZE
from src.preprocessing.helpers import cutdown, resize_padded
parser = argparse.ArgumentParser()
parser.add_argument('--image', type=str, required=False)
parser.add_argument('-... |
4f47f8073bde7fc6751e9e39563bbd10929e783add9c28abcf84c88e80f107ec | Python | 3,095 | 81 | '''
Original Author: Nate Zuniga
Modified by Yi Jie(Josh) Tseng on 11/1/2023
This script is to convert the PEAKS11 output to PEAKS10 format which is compatible to deuterater.
Requirement:
Make sure to have the features.csv, protein.csv and peptide.csv from PEAKS11 output
Usage:
python Files_to_Deut.py ... |
0477628aa5033e671a4283d3b14653f3eb1aa238138b24476be90887f6b3b769 | Python | 3,096 | 101 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from __future__ import print_function
from HDPGPHSMM_segmentaion import GPSegmentation
import time
import matplotlib.pyplot as plt
import os
import numpy as np
import pandas as pd
import glob
def learn( savedir, dim, gamma, eta, initial_class, avelen, max... |
7d9a5cfb765f6cb1a2e8550d90b6426821a6518461d67a0505022b6e81102aa7 | Python | 3,096 | 91 | """Loading the .mat files shipped with the repo.
The monkey sample is a Matlab v5 file containing a single struct `sess`
with fields:
EyeX (n_trials, n_samples) float64, degrees of arc
EyeY (n_trials, n_samples) float64, degrees of arc
trial_isface (n_trials... |
7b8f7402fd49c8b93b4b1275064533f995f239b64042ee2eb81897d33cd8567f | Python | 3,097 | 101 | import cocotb as ctb
import pytest
from cocotb.clock import Clock
from cocotb.triggers import RisingEdge
from cocotb.types import LogicArray, Range
from elasticai.creator.testing import eai_testbench
from .helpers import _reset_dut, _write_current_d_in
pytest_plugins = "elasticai.creator.testing.cocotb_pytest"
# Cl... |
e69eed5e290e090220ecedf4aafc47161ec806f7c96126e4195de19a5a5ddae5 | Python | 3,098 | 95 | """Plotting utilities."""
import numpy as np
from treem.io import SWC
def plot_tree(ax, tree, data, **kwargs):
"""Plots entire branch.
Args:
ax: matplotlib axes object.
tree (treem.Node): branch start node.
data (NumPy ndarray): raw data of morphology Morph.
kwargs: argument... |
f885b6c4556085e3a16108f9222c2516bc915a224b2ea6d47728ebd236294f1e | Python | 3,099 | 80 | #!/usr/bin/env python
"""
Code provided by Allen Institute
"""
import logging
import numpy as np
class Tile(object):
def __init__(self, index, image, is_missing, bounds, channel, size, margins, *args, **kwargs):
# identifier
self.index = index
# actual image data
... |
1705b5b48c5cc610dda10713b09b5759a289457e74d7b3fea82a0479a1ffdd84 | Python | 3,100 | 85 | from __future__ import annotations
import re
from typing import Any
from wikibaseintegrator.datatypes.basedatatype import BaseDataType
from wikibaseintegrator.wbi_config import config
from wikibaseintegrator.wbi_enums import WikibaseSnakType
class MonolingualText(BaseDataType):
"""
Implements th... |
6059bd850bf3e031426e365e153439ea14f3dc073e9830671e478d455bcc1cb6 | Python | 3,100 | 80 | from collections import defaultdict
from logging import getLogger
from typing import Any, DefaultDict
from pip._vendor.resolvelib.reporters import BaseReporter
from .base import Candidate, Requirement
logger = getLogger(__name__)
class PipReporter(BaseReporter):
def __init__(self) -> None:
self.reject_... |
69f2b842198eb5233c63e0c45ec533c5682d013b6a16456b417928e060d0f285 | Python | 3,100 | 95 | #!/usr/bin/env python
#================================================================
# Copyright (C) 2021 Yufeng Liu (Braintell, Southeast University). All rights reserved.
#
# Filename : image_io.py
# Author : Yufeng Liu
# Date : 2021-05-17
# Description :
#
#======================... |
8986af4c9e45cc2c2794f000ae3856141148b384bc14560f76711c22c0d32114 | Python | 3,100 | 80 | import numpy as np
import pytest
import nibabel as nib
def _write_mask(tmp_path, arr):
p = str(tmp_path / "edit_mask.nii.gz")
nib.save(nib.Nifti1Image(arr.astype(np.uint8), np.eye(4)), p)
return p
def test_apply_edit_zeros_template_and_annotation(tmp_path):
from regtools.registration.reg... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.