sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
7cb02f8d7fe572129f1ae9d77ae5faa7d23a1e5a6b1d43fdb716875482121435 | Python | 3,212 | 117 | # Node-group asset "TEM Rotation" (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_CHECKING
... |
d238b359c08930444c853ff80183825589bd120ab6861cb63ff8fbec328e13e8 | Python | 3,213 | 70 | import argparse
from matplotlib import pyplot as plt
import pandas as pd
import pytorch_lightning as L
import seaborn as sns
import sys
# local imports
sys.path.append("..")
from shapelearningtheory.datasets.multi_shape_dataset import *
from helpers import train_and_validate, unpack_results, \
create_save_path, get... |
83a919c6b76249ee0ca0b69c2b1b4bb542e0b097e39721a6337bd5b77ddc64ad | Python | 3,214 | 134 | import os
from logging import root
import numpy as np
from topaz.utils.data.loader import (ImageDirectoryLoader, ImageTree,
LabeledImageCropDataset,
LabeledRegionsDataset,
SegmentedImageDataset, load_image,
... |
9497e9d9aa488404adccd78d6726f4a14f95a6a272db6e20df374f580dbc54aa | Python | 3,214 | 77 | # By Shuran Liu, 2023
import numpy as np
import torch
def interval_confidence(mu_list, b_list, epsilon, num_dropout_ensembles=1):
mu = np.mean(mu_list,axis=0)
mu_stack = np.tile(mu, (num_dropout_ensembles, 1, 1))
mu_stack = np.stack(mu_stack, axis=0)
left = laplace_cdf(mu_stack - epsilon, mu_list, b_li... |
dda22ccb581b39d264ebd26a15b2b9bb5ee7da181a0e1f87d699802ef482be60 | Python | 3,216 | 92 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge,... |
cb4bebd8870c9982de0d8bd9b65f49ff554c6f1be2b3d8587ad4293348a76890 | Python | 3,217 | 112 | from typing import Callable, Protocol, runtime_checkable
import torch
from torch import Tensor
from torch.nn import Conv1d as _Conv1d
from torch.nn import Module
def _create_weight_for_conversion_as_twos_complement(bits: int) -> Tensor:
return torch.tensor(
[[-(2 ** (bits - 1))]] + [[2**i] for i in rever... |
0421ce8485810464e2e33a88ff39a3e7814e5d7c2204bae0d908174f61c12d11 | Python | 3,218 | 82 | """Portable session recordings and offline replay, requiring no model load."""
from __future__ import annotations
import json
import math
from copy import deepcopy
from datetime import datetime, timezone
from pathlib import Path
from typing import Any
FORMAT = "liquidaion-observatory-v1"
def _validate_finite(value:... |
f7ae33067a923a019006e09c17b6bf9679686497098f66a725294f69602e59b3 | Python | 3,218 | 98 | # 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... |
5f7de54cc30a73df20467e90755eee0c1ba2d36cda8ff4ea7e23383addfef333 | Python | 3,219 | 99 | """Tests for conformer generation.
Author: Seth Axen
E-mail: seth.axen@gmail.com
"""
import os
DATA_DIR = os.path.join(os.path.dirname(__file__), "data")
SDF_FILE_COMPRESSED = os.path.join(DATA_DIR, "ritalin_nonplanar.sdf.bz2")
SDF_FILE_UNCOMPRESSED = os.path.join(DATA_DIR, "ritalin_nonplanar.sdf")
class TestConfor... |
ddc5d051b1058c40fc3837d537a0620e090f82d9daee2d24302122f753180378 | Python | 3,219 | 127 | from __future__ import division
# coding: utf-8
# In[2]:
# In[1]:
from builtins import range
#from past.utils import old_div
from operator import floordiv as old_div
import numpy as np
import scipy
from scipy import ndimage
import math
import cv2
import copy
from cvc import cvc
import sys
import os
# In[ ]:
... |
1060ca4b453af562d5d36f2a59c3674e78bc02372c17176ef3341b7d61cd210c | Python | 3,220 | 99 | import os
import requests
import hashlib
from tqdm import tqdm
def check_sha1(filename, sha1_hash):
"""Check whether the sha1 hash of the file content matches the expected hash.
Parameters
----------
filename : str
Path to the file.
sha1_hash : str
Expected sha1 hash in hexadecimal... |
23fa1601a7c03cb981e13d64a1c07e5929a22bf80b6509b51420c56a45820711 | Python | 3,220 | 101 | from hed.schema import from_string
library_schema_start = """HED library="testcomparison" version="1.1.0" withStandard="8.3.0" unmerged="true"
'''Prologue'''
!# start schema
"""
library_schema_end = """
!# end hed
"""
default_end_lines = """
!# end schema
"""
required_non_tag = [
"'''Unit classes'''",
... |
35870cf362798d96bf201521f5f52575c602b210ded4be2bc263c8ca0d24466b | Python | 3,220 | 87 | import gzip
import shutil
from pathlib import Path
import pytest
from nodebpy.nodes.geometry import RealizeInstances
import molecularnodes as mn
from molecularnodes.nodes.geometry import EnsembleInstance
from .constants import data_dir
from .utils import round_significant
cellpack_dir = data_dir / "cellpack/petworld"
... |
3a8999bcd10facb3bffb45ef4cf03b38525eb3a3706d66ec72afe111bf5b74eb | Python | 3,220 | 51 | """MF_AUDIT.py 2026-09-30. Pre-registration: 04-NOTES/PREREG-2026-09-30q-MF-AUDIT.md
The parameter-free rate theory of MEANFIELD.py on the whole brain (Shiu et al.'s file): does it reproduce the spiking
BRAIN_AUDIT (13 senses x 4 sign sets)? usage: python MF_AUDIT.py"""
import sys, os, time, hashlib
sys.path.insert(0... |
8a6651fd419a022fbd1f559e0c035b8486a20f297fded57eeee70896e17e19ec | Python | 3,220 | 128 | from __future__ import print_function
import glob
import os
import sys
from skimage.transform import resize
from skimage.io import imsave
import numpy as np
from keras.models import Model
from keras.layers import Input, concatenate, Conv1D, MaxPooling1D, Conv2DTranspose,Lambda
from keras.optimizers import Adam
from ker... |
78bcb5f99d3f8fea4efd1ca15fbfac8086cc390391af1690c8b6c15d2b171711 | Python | 3,221 | 88 | from torch.optim.optimizer import Optimizer, required
import torch
class SGLD(Optimizer):
"""
RMSprop preconditioned SGLD using pytorch rmsprop implementation.
"""
def __init__(self, model, params, lr=required, norm_sigma=0, alpha=0.99, eps=1e-8, centered=False, addnoise=True, Exp=None):
wei... |
f48d794b6061d36851ad7fb2ae1a75cb046d1ed8f9099c2a22562c39f661bf07 | Python | 3,221 | 93 | import os.path
from src import settings
import src.data.handler as data_handler
import torch
import itertools
import numpy as np
def sigmoid(z):
return (1 / (np.exp(-z))) - 1
def calc_weigths(fmri_data, min_weight=0.0, max_weight=2.0):
weight = sigmoid(np.abs(fmri_data)) # calc 0 based sigmoid
weight... |
42467c217aac6788b70d36ed2f9b2e2d86aa4cfc5a5edb174bc37faa473ecd42 | Python | 3,222 | 96 | """Perform and save time frequency analysis of given files."""
from __future__ import annotations
from pathlib import Path
from typing import Annotated, Literal
import numpy as np
import pte
from pytask import Product
import motor_intention.project_constants as constants
STIM = ("Off", "On")
OUT_DIRS = {stim: const... |
48413f688cef06fd00c92167599ed75cc8322d9735e533968d34c98f1e62370d | Python | 3,222 | 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... |
a42778dac112523fdef5c25b09b401377bb6e577310c6cd32180777afaf5d2b0 | Python | 3,223 | 61 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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
#
# ht... |
b90378a89fe5e40465bdb18542d4ecd32cd3bf1e07e557ea849e5f01060d86bd | Python | 3,223 | 81 | """Shared random-weight tiny-transformer fixtures: software tests, not scientific evidence."""
from types import SimpleNamespace
import pytest
import torch
from transformers import Qwen3Config, Qwen3ForCausalLM
from liquidaion_fly.observatory_engine import ObservatoryConfig, ObservatoryEngine
QWEN_REVISION = "c1899d... |
c596968f1b3028fa471c96dc40091070d22cbd27066d7992618e0562c062a3cd | Python | 3,223 | 103 | import h5py
import numpy as np
import torch
from torch.utils.data import DataLoader, TensorDataset
import torch.nn as nn
import torch.optim as optim
import torch
import torch.nn.functional as F
from torch.optim import Adam
# I copy Variational_autoencoder_train.py to this, and save the model as MoS2_model.pth for cle... |
3bb863db8b549863a45826dc483ccd47834e936c1ffbfc725f8eee86d7d10ba5 | Python | 3,224 | 88 | #! /usr/bin/env python3
import os
import subprocess
import logging
import APT_interface
class cd :
"""Context manager for changing the current working directory, and automagically changing back when done"""
def __init__(self, path):
self.path = path
def __enter__(self):
self.old_path = ... |
993996a4097d7978694f80f236ebf3173176c6e0c4078ebfba8f26eeadc1a100 | Python | 3,224 | 92 | """
Functions computing similarity & dissimilarity between spike trains
@author Iris Yoon
iris.hr.yoon@gmail.com
"""
import math
import numpy as np
import random
from itertools import combinations
from scipy.signal import correlate
# compute distance between neurons from raster
def pair_similarity(raster, neuro... |
eefa5f5444112dc254a6daf2a67cca2736132e0520e36f742b19848523d5f620 | Python | 3,224 | 82 | from pathlib import Path
def load_deepmd(fdict_or_fpath, type_map=None, pbc=True, shuffle=True, seed=0):
"""This is loader for deepmd input data. It takes a dict of key and file path or a directory path which contains the data files. If `type_map` is provided, it will be used to convert the type id to atomic num... |
8fd80f599ce4578a9be018292a339c69a72dc7e9774e1520ae75b7b1fa8d3487 | Python | 3,225 | 99 | from pathlib import Path
import tempfile
from unittest.mock import MagicMock
import pytest
import numpy as np
import pandas as pd
from scipy import sparse
import nibabel
import nilearn
from nilearn.datasets import _testing
from nilearn.datasets._testing import request_mocker # noqa: F401
def make_fake_img():
r... |
e9d702a6b31e1ea8108ddbaacaf9a83935fa3f2afb832d6d6bb2c5b288832b92 | Python | 3,225 | 102 | # 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... |
fbdcc10405d4ed7e5cf83c0a2ed30aa4ce690404df17897c87a029a03665406b | Python | 3,225 | 88 | import os.path
import zipfile
from ckg.graphdb_builder import mapping as mp, builder_utils
from collections import defaultdict
import pandas as pd
###############################
# Exposome Explorer #
###############################
def parser(databases_directory, download=True):
directory = os.path.join... |
9b1ce1d3bba6657dc30eae8bd3dba0581136b6152b90dbc0ace19187c407c749 | Python | 3,226 | 65 | #!/usr/bin/env python
import os
import pandas as pd
import matplotlib.pyplot as plt
from nltools.data import Brain_Data
from nltools.mask import expand_mask, roi_to_brain
from nltools.stats import threshold
from nilearn import plotting as nplot
## location of main project directory on HPC
proj_path = '/project/30111... |
c109e960d36a0f27a2b6034e75add2d0e1222f32ee493f2ea3cf7cc0e1237454 | Python | 3,226 | 78 | import os
import numpy as np
import SimpleITK as sitk
from tqdm import tqdm
from .sitk_tile import sitkTile
from yacs.config import CfgNode
from tiffile import imread, imsave
def computeTform(cfg: CfgNode):
'''
Compute a transformation map for the anchoring
channel
'''
# basic settings
m_trans... |
c90563ca1585854a7327a3383bf142d3cbf8de197b1a4ac262efd867a98418c7 | Python | 3,227 | 96 |
"""
MoCHI misc module
"""
import sys
from numbers import Number
from collections import deque
from collections.abc import Set, Mapping
from matplotlib import pyplot as plt
import numpy as np
import itertools
def getsize(
obj_0):
"""
Recursively iterate to sum size of object & members.
:param obj_0: ... |
718c9c0a5881575b20ec1dc5b2d7cc754f8643885f3b3bf864a465894dcd59d5 | Python | 3,228 | 75 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
class FCLayer(nn.Module):
def __init__(self, in_size, out_size=1):
super(FCLayer, self).__init__()
self.fc = nn.Sequential(nn.Linear(in_size, out_size))
def forward(self, feats):
x = s... |
e1501f3fbe89d563e4ea31f9b1b297cc003be4e9414bde2077211cd76cda9667 | Python | 3,228 | 111 | import torch
from diff_frech_mean.frechetmean.utils import (EPS, arcosh, arsinh, artanh, cosh, divsinh,
sinh, sinhdiv, tanh)
from .manifold import Manifold
class Lorentz(Manifold):
def __init__(self, K=-1.0):
super(Lorentz, self).__init__()
assert K < 0
if... |
66c6143a1152230f1d74dc16ce28276cdef3b0c317594079d45dbe77a527473a | Python | 3,229 | 75 | """Read metadata provided as a dataframe.
This module provides functions for reading metadata
"""
import pandas as pd
import xarray as xr
def add_metadata(epoch_data: xr.Dataset,
df: pd.DataFrame,
recording_id: str = 'recording',
epoch_id: str = 'epoch'
... |
a34f8f158b460820bef0a75b907a68cea8e7f3e9abb077179833921d831c653b | Python | 3,229 | 80 | """Analysis parameters
----------------------
A dictionary with parameters defining the network analysis.
"""
import numpy as np
ana_dict = {
# dtypes for reading ASCII files from NEST, file extension: .dat
'read_nest_ascii_dtypes': {
'spike_recorder': {'names': ('nodeid', 'time_ms'),
... |
1fb9219e226282590d6ebdc521404ff858e41e058f0ddd0849abd3d2d33879bf | Python | 3,230 | 84 | from elasticai.creator.file_generation.savable import Path
from elasticai.creator.file_generation.template import (
InProjectTemplate,
module_to_package,
)
from elasticai.creator.vhdl.auto_wire_protocols.port_definitions import create_port
from elasticai.creator.vhdl.code_generation.addressable import calculate... |
649e7076dba4df9ea2de2a61de8ab6633b4aa129d4aa4887fb6e0aec1d6cb061 | Python | 3,230 | 92 | #!/usr/bin/env python
"""
Creates a PDF figure from hexbin histogram data calculated by ex_Hexbin app (BioShell example)
USAGE:
./make_plots.py data_hex [x_min x_max [y_min y_max]]
"""
import math, re, sys, matplotlib
import matplotlib.pyplot as plt
from matplotlib.collections import PolyCollection
import mat... |
ed878830bd43a4d5df401870c269ecbbe6a88c65b5b4d9531defb3786d1a8b2e | Python | 3,230 | 97 | import sys,argparse
from pybioshell.core.data.io import find_pdb, read_scorefile
from os.path import expanduser, join
home_dir = expanduser("~")
# It is assumed VisuaLife library is installed in your $HOME/src.git/visualife/src/ directory
sys.path.append(join(home_dir, "src.git/visualife/src/"))
from core.Plot impo... |
ba6465aae78ed71cf9708d68163a84890f7a02fbd66d113fc8208bb6f21f1ea2 | Python | 3,231 | 43 | """MEASURE_NEXT.py 2026-10-01. Descriptive (no test, no pre-registration): which antennal-lobe local-neuron types should a
laboratory stain next? Types without a laboratory transmitter label, ranked by output synapses, with the published sign, the
classifier's call and the margin left before the balance line (PHASE_MAP... |
ca31a19a1d320457e1455cfa7a2769ec61ba5f5c4b72e09d7b78bf825b6ac1a3 | Python | 3,231 | 80 | '''
Description:
Pre-processing of Waddington-OT/Schiebinger2019 (SC) data.
'''
import scanpy
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
# Change file directory to the raw SC data
days_df = pd.read_csv("./raw/cell_days.txt", index_col='id', sep='\t')
adata = scanpy.read_h5ad("./raw/Expr... |
e5f8e40cc54a182cdca8338a54b3bd8a0bda417ba9159e1bb68876f2f1c88a09 | Python | 3,231 | 76 | import nibabel as nib
import glob
import argparse
import matplotlib.cm as cm
import matplotlib.colors as mcolors
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import numpy as np
# Argument parsing
parser = argparse.ArgumentParser(description='Plot lesion frequency maps.')
parser.add_argument('--t... |
f0b0d14b7808fc1c1177b3c89befba9b5215c66ec610ab54c22f63e296b3dfce | Python | 3,231 | 114 | import h5py
import click
import numpy as np
import pandas as pd
@click.command()
@click.option('--score',
'score_file',
required=True,
type=click.Path(exists=True, readable=True),
help='Score h5 file sequences')
@click.option('--satmut',
'satmut_fi... |
27434c195b17ccd3f4d6d57d55c72e323b4989b8eb529e1584d53a719e11bf82 | Python | 3,232 | 88 | import sys
sys.path.append("../../../../pylib")
from pathlib import Path
import os
import numpy as np
import pickle
from scipy.spatial import distance_matrix
import matplotlib.pyplot as plt
from multiprocessing.pool import Pool
def get_matrix(pts):
pts = np.array(pts)
# make a grid, points in the grid and ne... |
425b21b31adf0b488c7dad6cd824770bd29976b50d7a44580cf38323b38f737c | Python | 3,232 | 75 | import sys
import gzip
chro_order=[]
for i in range(1,24):
chro_order.append('chr'+str(i))
chro_order.append('chrX')
chro_order.append('chrY')
chro_order.append('chrM')
chro_order='1 2 3 4 5 6 7 X 8 9 10 11 12 13 14 15 16 17 18 20 Y 19 22 21'.split()
fn1=sys.argv[1]
fn2=sys.argv[2]
sample_name1=fn1.split('_')[... |
e43fa89be10a36f664a89c50ade98307c9de4dd397151be343b17f8842cf1b0e | Python | 3,232 | 90 | """
Create saliency map of training samples to visualize what model looks for in input
"""
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection
import numpy as np
import torch
from src.model import ModelSpikeSorter
from src.data import MultiRecordingDataset
from src import plot, utils
MO... |
5ea2c9838292e9d39e2cbc3a3c129a0c9abb57e14e8b3fec3fb0f0e107ffbdab | Python | 3,233 | 101 | # Node-group asset "Fallback Matrix" (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... |
68c2b08477f6eedb923821ebfda0373436844441235cfea9f2dce426d055a5ee | Python | 3,234 | 115 | # ----------------------------------------------------------------------
# Copyright (C) 2014-2015, Numenta, Inc. Unless you have an agreement
# with Numenta, Inc., for a separate license for this software code, the
# following terms and conditions apply:
#
# This program is free software: you can redistribute it and/... |
01b73730b7a9892872b4b1f0fcf60e3d6a797e752fbbe77b83fb69b966e8bd4b | Python | 3,235 | 93 | import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
sns.set_theme(context="talk")
def xavier (Nout,Nin):
return np.random.rand(Nout,Nin) * np.sqrt(6/(Nout+Nin))
#Setting seed to produce the same figure as in the paper
np.random.seed(0)
#Setting network size
... |
8639b4514c5e203a2f7475218f1c78a7b5123732e8f08cb260dcf743d6e0f0a1 | Python | 3,236 | 102 | import os
import pandas as pd
from calvados.cfg import Config, Job, Components
import subprocess
import numpy as np
from argparse import ArgumentParser
from scipy.constants import Avogadro
def get_number_PEG_chains_wv(wv_fraction, mw_peg, volume_simulation_box):
""" wv_fraction: weight/volume fraction in g / 100 m... |
072f6399788d5f47781d7085e679896925125545bfb67dd9a5940360e2077c95 | Python | 3,237 | 83 | import os
import netCDF4
import numpy as np
from simtk import unit
DATA_DIR_PATH = os.path.join('..', 'SAMPLing', 'Data', 'BarostatData')
YANK_VOLUMES_DIR_PATH = os.path.join(DATA_DIR_PATH, 'YankVolumes')
EE_VOLUMES_DIR_PATH = os.path.join(DATA_DIR_PATH, 'EEVolumes')
# =============================================... |
6c77e34c1e4eb24506f9c48a64937e8473262c2f55a068c57cad0d74d208c127 | Python | 3,238 | 100 | """Module to reject bad channels and bad epochs.
"""
from logging import getLogger
lg = getLogger(__name__)
def rejectbadchan():
"""Class to reject bad channels.
"""
pass
def remove_artf_evts(times, annot, chan=None, name=None, min_dur=0.1):
"""Correct times to remove events marked 'Artefact'.
... |
7c59a2122995870b6ca7d2214b2901377801e34e5d670362da1af075840d3e86 | Python | 3,238 | 145 | import pickle
import scipy.io as sio
import matplotlib.pyplot as plt
import os
import pandas as pd
import json
def format_global(value):
if (value >= 0.8):
return "{}d".format ( round ( value, 1 ) )
elif (value < 0.8) and (value >= 1 / 24):
return "{}h".format ( round ( value * 24, 1 ) )
... |
6ee69ab8d144316eb420e46c22492dd221f4ec8b6906e5a295df1ff5716fa686 | Python | 3,239 | 72 | import urllib.request
import argparse
from tqdm import tqdm
import zipfile
import shutil
import os
class DownloadProgressBar(tqdm):
def update_to(self, b=1, bsize=1, tsize=None):
if tsize is not None:
self.total = tsize
self.update(b * bsize - self.n)
def download_url(url, output_pat... |
a7efd355532e24aa1733012b3a94a2772842a6dae9e5bd68f8baab9eac25ef52 | Python | 3,239 | 111 | '''MobileNet in PyTorch.
See the paper "MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications"
for more details.
'''
import torch
import torch.nn as nn
import torch.nn.functional as F
def conv_bn(inp, oup, stride):
return nn.Sequential(
nn.Conv3d(inp, oup, kernel_size=3, stri... |
aec7fd71f918cadba72d659b4d9898c11839b5a5adf44427019f5406dd9009e4 | Python | 3,239 | 102 | # -*- coding: utf-8 -*-
#
# Test spy.concat function
#
import pytest
import numpy as np
# Local imports
import syncopy as spy
from syncopy.shared.errors import SPYTypeError, SPYValueError
class TestConcat:
nTrials = 10
nSamples = 100
nChannels = 2
nFreq = 5
nTaper = 4
def test_ad_concat(s... |
bcca94c2cbde14c04ec296ed3807aa265fa10dab9b5f6fb3c0c04e3bfc78cceb | Python | 3,239 | 88 | #! /usr/bin/env python3
import os
import subprocess
import logging
import APT_interface
class cd :
"""Context manager for changing the current working directory, and automagically changing back when done"""
def __init__(self, path):
self.path = path
def __enter__(self):
self.old_path = ... |
20596ead6e2690288a8180faaf02eac2e8b36ea4c9e487117da8764aa5638a87 | Python | 3,240 | 114 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Initialize LDS model
Created on Thu Jun 13 2019
@author: jmagraner
"""
# %%
import autograd.numpy as np
import autograd.numpy.random as npr
def initparams_random(specs,*unused):
sc=0.01
ndim, tdim, mdim, cdim, cxdim = specs['data dims']
udim, ... |
d743740a37b86e2c34213a7cf92c14094bfb66059cb4f6ea083c26dad1c1a601 | Python | 3,240 | 77 | import argparse
from matplotlib import pyplot as plt
import pytorch_lightning as L
import seaborn as sns
import sys
# local imports
sys.path.append("..")
from shapelearningtheory.datasets import make_dataset
from shapelearningtheory.networks import make_vit_b_16
from helpers import format_table, train_and_validate, unp... |
4b1a69c80b374e22f9bfb2b1e4b214e8d00545c195e420157976eac9dfa2a87b | Python | 3,241 | 103 | """Utilities for k-point handling."""
from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
from pymatgen.io.ase import AseAtomsAdaptor
from pymatgen.io.vasp.inputs import Kpoints
from pymatgen.symmetry.bandstructure import HighSymmKpath
if TYPE_CHECKING:
from ase.atoms import A... |
abf3989afa380e2c63da35474e97cc247e084ac61dcea4243722bf4bb59bc365 | Python | 3,241 | 98 | # -*- coding: utf-8 -*-
"""Evaluate detected communities using NMI and element-centric similarity."""
import sys
import numpy as np
import pandas as pd
from scipy import sparse
from sklearn.metrics.cluster import normalized_mutual_info_score
if "snakemake" in sys.modules:
detected_group_file = snakemake.input["d... |
191dda77e23fc6ed348e29d3f41670fc828a0adf76de90a58869b287eca2d567 | Python | 3,242 | 97 | """Constructor for spin-echo sequence to measure global T2 relaxation."""
from math import pi
import numpy as np
import pypulseq as pp
from console.utilities.sequences.system_settings import raster
from console.utilities.sequences.system_settings import system as default_system
def constructor(
echo_time_range:... |
ce26cc560e51a4a6fe304f7fec4606e1933649fd3b347710cd9d7653ead8261a | Python | 3,242 | 112 | """
Script which takes one or more file paths and reports on their detected
encodings
Example::
% chardetect somefile someotherfile
somefile: windows-1252 with confidence 0.5
someotherfile: ascii with confidence 1.0
If no paths are provided, it takes its input from stdin.
"""
import argparse
import sy... |
da50bd404811da8ce2cf4271add33afc03f52b190062432edaf06da89b4b873e | Python | 3,242 | 102 | import pytest
from elasticai.creator.testing.cocotb_func import (
all_within_tolerance,
error_count_outside_tolerance,
is_mae_within_tolerance,
)
@pytest.mark.parametrize(
"result, expected, tol, passed",
[
([1, 2, 3], [1, 2, 3], 0, True),
([1, 2, 3], [0, 3, 4], 1, True),
... |
10a6cd2cb0b141de8aef16864f961aa4edff0cb40436de22544af9523e571cf7 | Python | 3,243 | 101 | #test that commands can be imported and arguments parsed
def test_main():
from topaz import main
try:
main.main()
except SystemExit:
#no commands are passed, so we call sys.exit
pass
def test_train():
from topaz.commands import train
parser = train.add_arguments()
args... |
f4ac88de15ae1699103f8445977ba288cbb12355ee55322b9bb5b252f0c158bc | Python | 3,243 | 77 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge,... |
0ebfbc4dd3d1645c61ac1d9b7ce014dd51b8dd81eae8d483d37abbf40098aa99 | Python | 3,244 | 83 | """Test Robust Reference."""
from unittest import mock
import mne
import numpy as np
import pytest
from pyprep.reference import Reference
@pytest.mark.usefixtures("raw", "montage")
def test_basic_input(raw, montage):
"""Test Reference output data type."""
ch_names = raw.info["ch_names"]
raw_tmp = raw.c... |
1f469f2565bb538ac39e8e96b273de1cda1469002c775278001d4d39cf13e45a | Python | 3,244 | 110 | from typing import Any
class MWApiError(Exception):
"""
Base class for MediaWiki API error handling
"""
error_dict: dict[str, Any]
code: str
info: str
messages: list[dict[str, Any]]
messages_names: list[str]
@property
def get_conflicting_entity_ids(self) -> list[... |
df4dac81c4e9a0b65d8e74bca9c3febc45b835f3b825fbdf5bff74a17920c760 | Python | 3,244 | 77 | # SPDX-FileCopyrightText: 2024 Blue Brain Project / EPFL
#
# SPDX-License-Identifier: AGPL-3.0-or-later
'''
Utitly functions in ordder to add activity based node property conn ConnetivityMatrix objects for BBP and MICrONS
Author(s): Daniela Egas S.
Last update: 02.2024
'''
# General
import numpy as np
import pand... |
5f0f41c7115839f8be814da1f9cba186320407d209e016120ef552f1d4e7ce4e | Python | 3,245 | 112 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Aug 11 10:45:28 2023
@author: felipe
#WC-Kuramoto
"""
import numpy as np
import matplotlib.pyplot as plt
from numba import jit,float64, vectorize
from numba.core.errors import NumbaPerformanceWarning
import warnings
warnings.simplefilter('ignore', ca... |
eac555671160b6dffea4488e659ed028f2daddbc29c902b6ea9f6d84861f37d6 | Python | 3,246 | 92 | """The 2D preview applies the enabled intensity preprocessing (what ANTs sees)."""
import os
import sys
PROJECT_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
if PROJECT_ROOT not in sys.path:
sys.path.insert(0, PROJECT_ROOT)
os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")
i... |
63a18e135093f1aa9fb7736fba495c61202a0da377c0885e7248aba02b49adb7 | Python | 3,247 | 121 | # 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... |
0d56eef98f7724482ea4d064b2255fb400c7609573eefb3f5188e9d88327b547 | Python | 3,248 | 96 | from __future__ import annotations
import re
from typing import Any
from wikibaseintegrator.models import Claim
from wikibaseintegrator.wbi_enums import WikibaseSnakType
class BaseDataType(Claim):
"""
The base class for all Wikibase data types, they inherit from it
"""
DTYPE = 'base-dat... |
88b4bb3c31ffc32ca2d9f50ed5ffd6c1e92cca26741eb581b2f3c6019b707475 | Python | 3,248 | 118 | """
Script for growing a binary segmentation the specified nm
Input: - Segmentation
- Distance to grow
Output: - Grown segmentation
"""
__author__ = 'Antonio Martinez-Sanchez'
# ################ Package import
import sys
import time
import getopt
import operator
import scipy as sp
impor... |
9b598c736aacc389a7f9eda685024cd29363fd9f5b3cfbedd1f42f85c731a549 | Python | 3,249 | 90 | # this set of functions primarily developed as utilities for the cryovesnet package
import numpy as np
import napari
import mrcfile
from .unetmic.unetmic import interactive
import sys
from pathlib import Path
def query_yes_no(question, default="yes"):
valid = {"yes": True, "y": True,
"no": False, "... |
714fbee15c51df37d788001e20e9d582d9c62863e0535f77f4d94d211cdb7a3f | Python | 3,250 | 122 | # Node-group asset "Flat Internal" (ShaderNodeTree), 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_CHECKING, ... |
96f08000e9ff29bebd8e3c79d491db2deffd39c5eb69c2a4be344fb6569e09f8 | Python | 3,250 | 39 | """FIG_TWO_WAYS.py 2026-10-08. Report figure F19 (two ways to fail), from REST_STATE (prereg 08e):
(a) the phase diagram — background drive b (x Hallem resting rates) against the excitatory share s of the local neurons'
synapses onto uPNs; each sign set marked fly-like (quiet rest and >= 40/50 channels), spread (quiet ... |
57763fc68ed73d454dfe55d534145094da04e3e48bdf74becc2b6383f6f043b0 | Python | 3,251 | 61 | def set_up_net_connection(self, connect_file):
self.input_synapse = [None, None, None, None]
circuit = pickle.load(open(connect_file, 'rb'))
for post_neuron in circuit.neurons: # for each post neuron
id_post_cell = post_neuron.index
if (id_post_cell > 0) and (str(id_post_cell) not in self.c... |
a20d9c36e4491dccf9ed7bbcca65cffc8fce0274edac81eb24e7c93ef7566d92 | Python | 3,251 | 74 | import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from skimage.transform import resize
import matplotlib
import numpy as np
import comparison_datasets
import torch
plt.rcParams.update({'font.size': 20})
color_map = matplotlib.colors.LinearSegmentedColormap.from_list("", ["blue", "white","red"])
... |
24ac5632714d865e3c8be62a2cb36128fd96e83c893608a09cc80da8e4e039a5 | Python | 3,252 | 102 | """
Filter rows in a STAR file by column
Input: - STAR file
- Column filter setings
Output: - A copy of input STAR file where some rows can be filtered
"""
__author__ = 'Antonio Martinez-Sanchez'
###### Global variables
import pyseg as ps
key_col, key_img = '_rlnClassNumber', '_rlnImag... |
841802655718ce7a164aac64222a4b1d600d6a8c47bdff77bdc5d2784deccade | Python | 3,252 | 82 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
import suites
from lab.reports import Attribute, gm
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
def main(revisions=None):
benchmarks_dir=os.path.expanduser('~/projects/downward/benchmarks')
... |
d9aabcfd0f9261d8fd2beeb8f0cbdaba7af8e7ead9fdd58182d7af162975cbcb | Python | 3,252 | 82 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
import suites
from lab.reports import Attribute, gm
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
def main(revisions=None):
benchmarks_dir=os.path.expanduser('~/projects/downward/benchmarks')
... |
ec416fbf27ed15e7e03f03f4fc0978db90891973a9a554af7230eacfe49b2d67 | Python | 3,252 | 91 | import numpy as np
from scipy.stats import gamma
def ridge_regress_deconvolution(BOLD: np.ndarray,
TR: float,
alpha: float = 0.005,
NT: int = 16,
xb: np.ndarray = None,
... |
052c449da7ac76be7ea483e634a1fa00230adf834f3b702a6f34aa70e32b2604 | Python | 3,253 | 114 | import sys
import random
import os
import argparse
import sys
import pwd
import time
import subprocess
import re
import shutil
from sklearn import metrics
import re
from sklearn.metrics import roc_curve,roc_auc_score
import numpy as np
import glob
import logging
import io
import tensorflow as tf
#from callbacks import... |
d5eadf45472e97a5dcc88aade7fe929f0317794618a1ea499a3b665efd3a0c9c | Python | 3,253 | 98 | """Plotting methods."""
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
from console.interfaces.unrolled_sequence import UnrolledSequence
def plot_unrolled_sequence(
sequence: UnrolledSequence,
time_range: tuple[float, float] = (0, -1),
) -> tuple[mpl.figure.Figure, np.ndarray]:
... |
e2e893ae70736a387e92c6f3297a95a4441a280b11bad3fb60c19d17c39d70e6 | Python | 3,253 | 108 | # 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... |
300e3424498e1e17b554d84483012b7dd31aa4b61d67f307960d2a2546c5fb2f | Python | 3,254 | 115 | # %%
import sys
import os
sys.path.append(os.path.abspath("../.."))
sys.path.append(os.path.abspath(".."))
sys.path.append(os.path.abspath("."))
# %%
import torch
import pandas as pd
import numpy as np
from pathlib import Path
import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns
from prosper_nn... |
43877ffbf63ff06c5a10e9e074144367e089e9b83add5040e2b40cd7eab783e5 | Python | 3,254 | 80 | #!/usr/bin/env python
from __future__ import print_function
import argparse
import os
import numpy as np
from examples.pybullet.utils.pybullet_tools.pr2_problems import create_floor, create_table
from examples.pybullet.utils.pybullet_tools.pr2_utils import get_top_grasps, get_side_grasps
from examples.pybullet.utils... |
8df5ad4b11689764fe45ad4bc86a2079327aa24d60d8e143f2cf809c30b2d1af | Python | 3,254 | 52 |
def extract_params_f(df, filter_by):
param_cols = None
if filter_by == 'BDLMapper' or filter_by == 'NeuMapper' or filter_by == 'EucNeuMapper':
df['K'] = df.apply(lambda x: int(x['Mapper'].split('_')[1]), axis=1)
df['R'] = df.apply(lambda x: int(x['Mapper'].split('_')[2]), axis=1)
df['G'... |
fd36ae0c18c13fc23c2c2dc701547be8cd81c6b6f31d86fc4c36ac75cf765dce | Python | 3,254 | 119 | """
Script for running object detection inference on a directory of images using
a pre-trained Tensorflow Hub detector and saving to CSV in either:
- Tensorflow Object Detection API format
- Open Images Kaggle Competition format
| Copyright 2017-2022, Voxel51, Inc.
| `voxel51.com <https://voxel51.com/>`_
|
""... |
b432973615b4a5de1a392e2d6de595df3756f971d4480ff397d64111d062755e | Python | 3,255 | 124 | import sys, os
from pandas.io.parsers import read_csv
import numpy as np
import pandas as pd
from collections import Counter
try:
bedintronfile=sys.argv[1]
bedexonfile = sys.argv[2]
output = sys.argv[3]
except:
sys.exit("Please, provide input bed (1) intron and (2) exon files; (3) output file")
def ge... |
db0128e5adb1647ddf7dc67e1edac890839c0f0442a5490b072823e0f236ea21 | Python | 3,255 | 103 | """
Shared utility functions for schema tests.
Provides helper decorators and functions for creating temporary files and schema folders in tests.
"""
import functools
import os
import shutil
import tempfile
from hed import schema
def get_temp_filename(extension):
"""
Create a temporary filename with the gi... |
409ebad80fc432ede66f3f12fab7cd458c5112c2894fbe2418e8b6036ebcf0fc | Python | 3,256 | 96 | import torch
import torch.nn as nn
import math
class InstanceLoss(nn.Module):
def __init__(self, batch_size, temperature, device):
super(InstanceLoss, self).__init__()
self.batch_size = batch_size
self.temperature = temperature
self.device = device
self.mask = self.mask_co... |
69ed96f41aa4a38f387bf4abe5a0a869995b2f7c77f88fa319cb76591d2d7ef5 | Python | 3,256 | 92 | """"""
"""
Prosper_nn provides implementations for specialized time series forecasting
neural networks and related utility functions.
Copyright (C) 2022 Nico Beck, Julia Schemm, Henning Frechen, Jacob Fidorra,
Denni Schmidt, Sai Kiran Srivatsav Gollapalli
This file is part of Propser_nn.
Propser_nn is free softw... |
8e8adbb3e89f0444ce42277aa215fcfb999d710872c5e3f948a77eb0ae28fe27 | Python | 3,256 | 58 | """D02_RADIUS_X_SIZEMATCHED.py - written 2026-09-04. VERIFY V-62.
Does the optic/central gap still grow with the clustering radius after matching on
synapse count? Reads tmp/d02/radiussweep.parquet (build it with
D02_DECAY_AND_ORIENTATION.py sample, scan, radiussweep first).
Output: 06-OUTPUT/d02_radius_x_sizematch... |
b20307118171a7fd060652a1fd2558a57c4ab7836ba836baa5302c06881896e5 | Python | 3,256 | 91 | # coding=utf-8
# Copyright 2021 The Facebook Inc. and The HuggingFace Inc. 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/LI... |
5c9d8b3abc85a3186a28b4dfb88892acd6240db4ed383cd089072212c3eee824 | Python | 3,257 | 97 | import subprocess
import logging
import shutil
import re
import glob
import shlex
def find_files_with_string_in_name(directory_path, string_in_name):
# This pattern will match any files that include the specified string in their names
# '**' allows for searching recursively in all subdirectories
pattern = ... |
991fb3b284ded07622b68814e928901b3dda561824f0e8b7242f53cf145ea7bb | Python | 3,257 | 94 | import numpy as np
from bayes_opt import BayesianOptimization, acquisition
from sklearn.ensemble import GradientBoostingClassifier
from sklearn.datasets import load_digits
from sklearn.model_selection import KFold
from sklearn.metrics import log_loss
import matplotlib.pyplot as plt
N_FOLDS = 10
N_START = 2
N_ITER = 25... |
1af1e0e8f4aacddd01924d9b8f5d4eb55f5f3c0e508d9e4630bc63917069433c | Python | 3,259 | 89 | #! /usr/bin/env python3
import os
import subprocess
import logging
import APT_interface
class cd :
"""Context manager for changing the current working directory, and automagically changing back when done"""
def __init__(self, path):
self.path = path
def __enter__(self):
self.old_path = ... |
62c16334174d1aaf9ed3d48cfb93256e3d96a5a1648a77e4efcdc6919fe54cc8 | Python | 3,259 | 96 | from collections import defaultdict
from functools import lru_cache
from codex.utils.graph_algos import pathways
def sort_layers(node_layers, cons):
# layers: {i: [nodes in layer i]}
layers = defaultdict(list)
for node in node_layers:
layer = node_layers[node]
layers[layer].append(node)
... |
635bbc0bc8f76b22b13d235cf7d657e4905703abfc0d1e20551bfc1696bd6630 | Python | 3,259 | 107 | from vtk import vtkPolyData, vtkCellArray, vtkPoints, vtkPolygon
from vtk import vtkPLYWriter, vtkDecimatePro, vtkSmoothPolyDataFilter, vtkPolyDataNormals
import numpy as np
def ndarray2vtkMesh(inVertexArray, inFacesArray):
''' Code inspired by https://github.com/selaux/numpy2vtk '''
# Handle the points & ver... |
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