sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
16ae17b5ab5da791d364bd4eb83bdbf0f55ebe304222256bab46102a44142767 | Python | 2,492 | 74 | """"""
"""
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... |
6acb20ccd30587106ed2a316a87f7d4dc02b89e7a4e9fe574592ee76febea4c9 | Python | 2,492 | 67 | import numpy as np
import scipy.signal
def getPowerSpectrum(activity, dt, maxfr=70, spectrum_windowsize=1.0, normalize=False):
"""Returns a power spectrum using Welch's method.
:param activity: One-dimensional timeseries
:type activity: np.ndarray
:param dt: Simulation time step
:type dt: float
... |
eb728c9bb82a2110cb9b79613aa2e75d5084b9bf5ccae6b126951b31b216790b | Python | 2,492 | 91 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 30 10:37:41 2023
@author: emma
code for fitting PCA model to velocity fields of specific brain regions (for disease and bias effects)
"""
# python imports
import os
import glob
import sys
import random
import tensorflow as tf
import numpy as np
... |
238806dca98472bbfc97e75bf6433d80abca1c864e11595bb3ade3c4f5151a9e | Python | 2,493 | 78 | """"""
"""
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... |
e7d825cd0fbd9fd4638901f8de43d9401add3ea12bd914db27d44a2ce3d39c4c | Python | 2,494 | 66 | # coding=utf-8
# Copyright 2018 The Microsoft Research Asia LayoutLM Team 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
#
# Unles... |
8e7f0642983167d0f4924eb07829d5058cf3b871d127961558e875b37c7cb17b | Python | 2,495 | 69 | from OnlineDetectors.online_nab_detector import OnlineAnomalyDetector
import numpy as np
class KnncadDetector(OnlineAnomalyDetector):
def __init__(self, *args, **kwargs):
super(KnncadDetector, self).__init__(*args, **kwargs)
self.buf = []
self.training = []
self.calibration = []... |
b048e182f632aef0aae2230a2d46a7151d43acf2f62a7c7045a22706e4ed40d8 | Python | 2,495 | 77 | from collections.abc import Callable
from typing import Any, Optional, Protocol
import torch
from .linear import Linear
from .math_operations import Add, MatMul, Mul, Quantize
class MathOperations(Quantize, Add, MatMul, Mul, Protocol): ...
class LSTMCell(torch.nn.Module):
def __init__(
self,
i... |
2bca7ddfe6a8c225c36ebb88b1f1107038c80c508e0c1f12011d46750dae6e95 | Python | 2,496 | 77 | from unittest import TestCase
from unittest.mock import MagicMock, patch
import numpy as np
import pandas as pd
from numpy.testing import assert_equal
from tgan.research import evaluation
class TestEvaluation(TestCase):
def test__proc_data_continous_column(self):
"""_proc_data adds a dimension in colum... |
e05134a1f3263e3fcebf712470d845283389f7785d4c89e882edc71bd8542a14 | Python | 2,496 | 93 | # 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... |
729f535adb96bbfdfdffd1fd8834a3438cff13c5e5994f368f3e49ae1bde39af | Python | 2,497 | 118 | #!/usr/bin/env python
# coding: utf-8
# ### Threshold CCLE CNV log-ratios into binary gain/loss calls
# In[1]:
import os
import sys
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pancancer_evaluation.config as cfg
# In[2]:
if os.path.isfile(cfg.ccle_cnv_rat... |
a98d9891acee446d6f74435e7a49bf01a6a4a34c4b3960d8092bb6fb0d9e55e3 | Python | 2,497 | 73 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import pandas as pd
from sklearn import preprocessing, metrics
import scipy
"""
evaluation.py provides evaluation functions that takes in predictions and output gene-wise correlation, peak-w... |
df57bbc3b975c87b90d2867861207a1d2c5debaa0e8038218b4afa3324f492e4 | Python | 2,497 | 83 | # Node-group asset "Image ID" (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
from... |
1e29acb46ba59f94ff704289cc38f2de2b35497d6bb37a25403949e5a8e34527 | Python | 2,498 | 74 | # 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... |
1ec4fe56b6077fe0fc81ee2de1680689ba52a62a71a4a622a5b1010da371dcc6 | Python | 2,498 | 79 | import numpy as np
def gini_index(X, y):
"""
This function implements the gini index feature selection.
Input
----------
X: {numpy array}, shape (n_samples, n_features)
input data
y: {numpy array}, shape (n_samples,)
input class labels
Output
----------
gini: {num... |
69a66f27b88630d88927a508bead70ccefa6d72129eaa1e142b1d38aca9888dd | Python | 2,498 | 94 | #!/usr/bin/env python3
import os
import pandas as pd
# ------------------------------------------------------------------
# paths
# ------------------------------------------------------------------
proj_path = '/project/3011157.03/Simon/proj_2022_CABB_movie'
# location of R output files
r_path = os.path.join(
pr... |
99d197f305f00d62419cd8fd3927772157b644eb22b86279f1f2614a5ec8419a | Python | 2,498 | 76 | from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
if TYPE_CHECKING:
import pandas as pd
def extractor(
data,
cell_type,
*,
condition_key,
cell_type_key,
ctrl_key,
stim_key,
):
"""Returns a list of `data` files while filtering for a specific `... |
b3d2478ee1ce555a126254160ed41d9b00a018b4f04f751aa83473f53f4e62cc | Python | 2,498 | 84 | # Node group "Index to Factor" (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 regenera... |
db36ef20489ef9b7cc641f36b4ee45a76cd514f7fcef24d94d0992acac4dc252 | Python | 2,498 | 68 | from pykdtree.kdtree import KDTree
import numpy as np
# input:
# pre_points: pre neuron 3d points, shape (npoint, ndim)
# post_points: post neuron 3d points, shape (npoint, ndim)
# nsyn: synapse number
# thresh: distance threshold
# output:
# pre_id: an array, pre neuron 3d point id where synapse on
# post_id: an arra... |
0aecf6b52e2a71e5df5aa08bdceb02afa32a4053aeeaa373f496cebbbbfa6f73 | Python | 2,499 | 71 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed May 3 17:31:13 2023
@author: felipe
"""
#Load KuramotoNetworksPackage repository
import sys
import os
sys.path.append(os.path.abspath('../../'))
import analysis.frequency as frequency
import analysis.synchronization as synchronization
import numpy as ... |
603a4c1abc2e93fefff2f6e69a0472bab8507452d428392267d01601ce43e7c6 | Python | 2,499 | 99 | from typing import Union
import matplotlib.pyplot as plt
import numpy as np
import torch
from matplotlib import colors
from pylab import cm
from .utils import _plot_to_image
def plot_3d_tensor(tensor: torch.Tensor,
color: Union[colors.Colormap, str] = 'hsv'):
r'''
Visualize a 3-D matrices... |
60f653a6989074418de205a2fb9494c48c23415463bc9dc3ddd3b87d9e1b65e1 | Python | 2,499 | 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... |
7bf9ba4195730d74bddb688b8e0ef122d8a40b3ee6dca325c01fd845ac3c34c1 | Python | 2,499 | 80 | import gc
import main_config as conf
import online_buffer as obuff
from OnlineDetectors.online_nab_detector import OnlineAnomalyDetector
from OnlineDetectors.AnDePeD.ReRe import ReRe
class ANDEPEDDetector(OnlineAnomalyDetector):
def __init__(self, buffer_size: int, algorithm: str, *args, **kwargs):
supe... |
850cfb4e03ce3a07d454197b48482169302a53b781c712f6883046f71aa8c186 | Python | 2,499 | 73 | import os
import tiffile
import h5py
import matplotlib.pyplot as plt
import numpy as np
import cv2
from PIL import Image, ImageOps
from tiffile import imsave
from skimage.measure import label
from skimage.color import label2rgb
#output_dir = '/mp/nas3/Margaret_mouse/'
def retrieve_output(output_dir):
'''
arg... |
004e58fc9f5fba034ddafdc51eef934d9b8761aff42c4fef4142c53306ea631b | Python | 2,500 | 80 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys
import os
import numpy
import nest
def dict_of_numpyarray_to_dict_of_list(d):
'''
Convert dictionary containing numpy arrays to dictionary containing lists
'''
for key,value in d.items():
if isinstance(value,dict): # if value == dict
... |
08b94d8323e246671a565dddb9e12b109b760e8f6b1abfe0adf6968ed150911d | Python | 2,500 | 61 | # Copyright 2019 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
#
# http://w... |
138183b7b45c7707dcf58276f917dea60384d4edf0ea05f52ccfdce0b2f42219 | Python | 2,500 | 115 | #!/usr/bin/env python2.7
from __future__ import print_function
from pddlstream.algorithms.focused import solve_focused
from pddlstream.algorithms.incremental import solve_incremental
from pddlstream.language.constants import PDDLProblem, Or, print_solution
DOMAIN_PDDL = """
(define (domain debug)
(:requirements :... |
4ef794f31fd936a39765e965c2220ab97f36a45e15658ee198cea903e300a660 | Python | 2,500 | 64 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from common_setup import IssueConfig, IssueExperiment, is_test_run
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue684-base", "issue684-v1"]
CONFIGS = [
IssueConfig(
... |
09133906c2c2a55d0633eb9c2c0693c836aec95dad997852c2559e210042701b | Python | 2,501 | 80 | # Wrapper class for sesread.WCP and sesread.EDR to be used with Pyclamp
# Gary Bhumbra
import os
import numpy as np
from pyclamp.dsp.sesread import WCP, EDR
from pyclamp.dsp.channel import chWave
class SES (WCP): # WCP inherits from EDR
edr = None
wcp = None
IntData = None
ADCData = None
def __init__(self... |
1b430008897f871eb765355798118a09a2a19c8baaff4bd41809329176d2c40f | Python | 2,501 | 71 | """
Created on Tue May 2 17:32:22 2023
@author: trianaa1
This script visualize the FD for all the MRI tasks
"""
import os
import pandas as pd
import matplotlib.pyplot as plt
################################ Modify these #################################
path = "/m/cs/scratch/networks-pm/pm_preprocessed"
tasks = ['... |
4fded502ea3af55a9777305698d5dd21552990cbb33cf1db33bdd991ccc8ae8e | Python | 2,501 | 81 | from __future__ import annotations
import os
import tempfile
import time
from typing import NoReturn
import optuna
from optuna.trial import TrialState
from optuna_dashboard import ChoiceWidget
from optuna_dashboard import register_objective_form_widgets
from optuna_dashboard import save_note
from optuna_dashboard.art... |
6c86e70892afde50581a00929582cc113b6ff8c35d138334718fc3e58fbbf4b7 | Python | 2,501 | 99 | import torch.nn as nn
import torch
from bio_attention.attention import TransformerEncoder
from bio_attention.embed import ContinuousEmbedding
class MLP(nn.Module):
def __init__(
self,
n_inputs=6000,
n_outputs=512,
layer_dims=[512, 512, 512],
layer_or_batchnorm="layer",
... |
a264c5f5ab1a027b0ce322d8f78791ffd7604514a6d651d4b335f6d03d726024 | Python | 2,501 | 96 | import sys
from typing import TYPE_CHECKING, Optional, Union
from .jupyter import JupyterMixin
from .segment import Segment
from .style import Style
from ._emoji_codes import EMOJI
from ._emoji_replace import _emoji_replace
if sys.version_info >= (3, 8):
from typing import Literal
else:
from pip._vendor.typin... |
aadcbdd6bc77c774815b2fe9a58b77b2245a16215fa1a05d71e4d833c73739b4 | Python | 2,501 | 49 | import pathlib
import os
alphaSeedsDir = r'C:\Users\ICN_guest\Charité - Universitätsmedizin Berlin\Interventional Cognitive Neuromodulation - PROJECT ECoG Atlas Connectomics\data\original_data\seeds\alpha_seeds'
alphaSmapDir = r'C:\Users\ICN_guest\Charité - Universitätsmedizin Berlin\Interventional Cognitive Neuromodu... |
fedac3a61e615a881ddb1b67ec5ebd1c28aa68afee041846f4c2b3f9cfb220fa | Python | 2,501 | 92 | """
Run an encoding model of our behavioral dimensions on the BOLD 5000 imagenet data.
This script uses fracrional ridge regression for obtaining regularized and more stable
dimension tuning maps.
"""
from os.path import join as pjoin
import os
import argparse
import numpy as np
from scipy.stats import zscore
from di... |
565de3686bb7272a20b4cd43af4d29d739f87afff9ca4f9b9ae49d6034293f28 | Python | 2,502 | 125 | from wonambi.viz import Viz3
from wonambi.attr import Surf, Channels
from .paths import (surf_path,
chan_path,
VIZ_PATH,
)
def test_plot3d_surf():
surf = Surf(surf_path)
v = Viz3()
v.add_surf(surf)
v.save(VIZ_PATH / 'viz3_01_surf.png')
... |
f4ba2d904df48b6c70f1cfff1577ae4b6d3358dc2ab49eb7b9c39c6beff6a334 | Python | 2,502 | 71 | import math
import numpy as np
import pytest
import sympy as sym
import smart
def test_Parameter_initialization(parameter_kwargs_k3f):
"""Test that we can initialize k3f SpeciesContainer"""
k3f = smart.model_assembly.Parameter(**parameter_kwargs_k3f)
assert k3f.name == parameter_kwargs_k3f["name"]
a... |
1692b2f8f59310e7d353965c3e0600c1801ba5f2362add3226e7609a117b4005 | Python | 2,503 | 66 | """
Interaction tests for MediaInfoEntity against the simulated Wikibase instance.
"""
import pytest
from wikibaseintegrator import WikibaseIntegrator
wbi = WikibaseIntegrator()
@pytest.fixture
def mediainfo_budapest(wikibase):
return wikibase.add_fixture('mediainfo_M75908279')
class TestGet:
... |
34d99d0fd1c8fb94390550219a7e2502abaf832422bd967b9f45d025d68d0071 | Python | 2,503 | 82 | # 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... |
6e90b0257c81dd2a3cff7daf8ec4ca38324096955dd34a55e4ff515320190745 | Python | 2,503 | 104 | # 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... |
7409ca4b356df21fd221b0edd9aa52d7fa52bf6097d6bab204f46f6f6d761235 | Python | 2,503 | 65 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from common_setup import IssueConfig, IssueExperiment, is_test_run, get_repo_base
from relativescatter import RelativeScatterPlotReport
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REPO = g... |
b064404e8e488ff9c2186657bef1a199d9a2e27fb66f4323eb448716ec8dd358 | Python | 2,503 | 65 | import torch.utils.data
from torch.utils.data.dataloader import default_collate
from batch import BatchSubstructContext, BatchMasking, BatchAE
class DataLoaderSubstructContext(torch.utils.data.DataLoader):
r"""Data loader which merges data objects from a
:class:`torch_geometric.data.dataset` to a mini-batch.
... |
49bde025dea1c328cc2c7231d031d104f7564a9cadd152baecd0b8594c6ca0f2 | Python | 2,504 | 61 | # -*- coding: utf-8 -*-
from pinn.models.AC import AC_dipole_model
from pinn.models.AC_AD import AC_AD_dipole_model
from pinn.models.AC_BC_R import AC_BC_R_dipole_model
from pinn.models.AD import AD_dipole_model
from pinn.models.AD_BC_R import AD_BC_R_dipole_model
from pinn.models.AD_OS import AD_OS_dipole_model
from ... |
577eb599de09af8c02de5529b1c4c041ca9e17f2f27d95d3c501e1d923b6f081 | Python | 2,504 | 73 | import torch
from .combined_scheduler import CombinedScheduler
from .components import (
ConstantScheduler,
CosineScheduler,
ExponentialScheduler,
LinearScheduler,
)
from .multistep_scheduler import MultistepScheduler
from .sgdr import SGDRScheduler
def _create_warmup(config, warmup_steps):
warmu... |
a6db532b5552f2232272f0c9330f4b0fea26b4239b63ce0a6fbea55dbe3b92a7 | Python | 2,504 | 99 | # Node-group asset "OKLab Offset LCh" (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... |
6ffa8fd83451b319c3b597dc03a4f7b64e6cdde5d66b75397d3f4327f45425b0 | Python | 2,505 | 70 | import scipy.stats
import autograd.numpy as np
from autograd.extend import defvjp, primitive
from autograd.numpy.numpy_vjps import unbroadcast_f
pdf = primitive(scipy.stats.multivariate_normal.pdf)
logpdf = primitive(scipy.stats.multivariate_normal.logpdf)
entropy = primitive(scipy.stats.multivariate_normal.entropy)
... |
8bf217950c5bfd127f94ec16ab756b8fb09440922311b41d74158ab121d52119 | Python | 2,505 | 41 | # -*- coding: utf-8 -*-
import argparse
from supar import TetraTaggingConstituencyParser
from supar.cmds.run import init
def main():
parser = argparse.ArgumentParser(description='Create Tetra-tagging Constituency Parser.')
parser.set_defaults(Parser=TetraTaggingConstituencyParser)
parser.add_argument('-... |
ca9b2e08db566d67fdd6edbb58ffbbcac0fb2e833a0fc0fd23b80f9643f72ef8 | Python | 2,505 | 72 | import matplotlib
matplotlib.use("Agg")
import torch
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
import yaml, io
with open("./config/DryBean_config.yaml", 'r') as stream:
config= yaml.safe_load(stream)
config["default_path"]= str(config["default_path"])
config["split"]= float(config... |
e731b5702ee6e1c6a3c9f6ef93ae6f15ecea295e429711acb3233215c9aca6ec | Python | 2,506 | 73 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 31 14:10:27 2023
@author: felipe
"""
import numpy as np
import matplotlib.pyplot as plt
#Load pre-calculated metrics
file=np.load('sd_T_matrix.npz')
var_tensor=file['var_tensor']
var_vector=file['var_vector']
sq_var_tensor=file['sq_var_tensor']
s... |
a374fba2ced3b4ad205e4ab69323dd316aefab338442cc7cdd74d2f59757e243 | Python | 2,507 | 61 | """A 2D custom annotation must be halved to match a halved 2D template.
Regression for the tilt-slice / custom-2D-atlas path: `_load_and_orient_2d`
halves the 2D template by `half_mode` but historically left the paired 2D
annotation full-size, so a non-'whole' half_mode silently skipped region
counting (grid mism... |
b9497f6d6b6af9f85a0c404c3930c179a395d61dd71edf5c928596f46429225a | Python | 2,507 | 67 | # Script to actually run CCA on the data
# Using the meet package https://github.com/neurophysics/meet.git to run the CCA
import numpy as np
from meet import spatfilt
import pandas as pd
def run_CCA_restingstate(window_times, epochs):
# Crop the epochs
window = epochs.time_as_index(window_times)
epo_cc... |
a20db3d50e53e6e7817a90e93badc867733bd3c4e1939e43c220c1b1787fef3a | Python | 2,508 | 75 | import os
import numpy as np
import deepdish
import argparse
import scipy.io as sio
import torch
from torch_geometric.data import InMemoryDataset,Data
from os.path import join, isfile
from os import listdir
import numpy as np
import os.path as osp
from networkx.convert_matrix import from_numpy_matrix
import networkx as... |
f5f4cb00f080c079815dd46feca654d7de234a036b45be96c7b448a0182a78a6 | Python | 2,508 | 89 | # coding: utf-8
"""Functions for reporting filesizes. Borrowed from https://github.com/PyFilesystem/pyfilesystem2
The functions declared in this module should cover the different
use cases needed to generate a string representation of a file size
using several different units. Since there are many standards regarding
... |
15bee27a6f97fc3c2c33ce73a5b8fbe65b36b7c6af9e91e2dd1a240c99ea4194 | Python | 2,509 | 66 | # coding: utf-8
import pandas as pd
roc = pd.read_csv('../data/roc_data.csv')
roc.head()
roc[fpr >=0.9]
mask = roc.loc[:,['fpr']] >= 0.9
roc[mask]
roc.loc[mask,:]
mask[0:5]
roc.loc[mask, [:]]
roc.loc[mask, :]
a = roc.loc[mask,:]
a.head()
roc.head()
mask = roc.loc[:,['fpr']] >= 0.9
roc.shape
roc.loc[mask, :].shape
... |
27b3cbc253c986cb8f625e4b64a3a2a03ba33078aa1668123c4b8b917f4cec0f | Python | 2,509 | 85 | import os
import csv
import pandas as pd
from typing import Dict
class MetaInfoIO:
r'''
Use with torcheeg.io.EEGSignalIO to store description information for EEG signals in the form of a table, so that the user can still analyze, insert, delete and modify the corresponding information after the generation i... |
9d1b72f832da23117ccf3fbfa5abfd4b1199e4a7577436ca56a8fc5c869e0487 | Python | 2,509 | 89 | # pylint: disable=invalid-name, missing-function-docstring, no-member
""" MeanLSTM model module """
from random import uniform, randint
import torch
from torch import nn
from omegaconf import OmegaConf, DictConfig
def get_model(cfg: DictConfig, model_cfg: DictConfig):
return MeanLSTM(model_cfg)
def default_HP... |
c7533b67e84b2abc05cf05c5416eb1902d382e0d30d383466f23685edc3df59c | Python | 2,509 | 74 | import nibabel as nib
import numpy as np
from ref_tumor_seg import calculate_distance_map
'''
Regions of Interests:
2 & 41: Left and Right Cerebral White Matter
16: Pons
10 & 49: Left and Right Thalamus
'''
def region_selection(subject):
tumor_MRI_hd = nib.load(subject.volume_MRI)
tum_flair = np.rint(tumor_... |
5cca4f569d532d6b98d52841480aac50cca914b7570487eaef852789c049bee3 | Python | 2,510 | 88 | # Node-group asset "Bond Count" (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
fr... |
66561d06661f0d35f82163b9d75b407f2b33a835b71715cc01633fdf8d5222a3 | Python | 2,510 | 83 | """EK 5-point velocity tests."""
from __future__ import annotations
import numpy as np
import pytest
from msfeature.velocity import ek_velocity, ek_velocity_2d
def test_constant_position_zero_velocity():
v = ek_velocity(np.full(20, 3.14), dt=1e-3)
assert np.all(v[2:-2] == 0.0)
assert np.all(np.isnan(v[... |
208fd642a5d6844b2e9efc92fab1c650e1d170a5b1386d0cf8cc3fa2d4c1ddf8 | Python | 2,511 | 63 | from ..region_1020 import (FRONTAL_REGION_LIST, GENERAL_REGION_LIST,
HEMISPHERE_REGION_LIST)
from ..standard_1005 import STANDARD_1005_CHANNEL_LOCATION_DICT
from ..utils import (format_adj_matrix_from_adj_list,
format_adj_matrix_from_standard,
format_... |
44fc20272625447e79cb01f34447498777245cf61096ef10512d39f41a0982d6 | Python | 2,512 | 45 |
import scanpy as sc
import pandas as pd
import matplotlib.pyplot as plt
# Data reading
input_file = "Dementia/Dementia_processed.h5ad"
adata = sc.read_h5ad(input_file)
# Add APOE contribution
adata.obs['APOEContr'] = 0.0
adata.obs['APOC1ContrDementia'] = 0.0
adata.obs['SPP1ContrDementia'] = 0.0
adata.obs['MCC'] = 0... |
c54ad3eec6732b36780f57c77f49ca1a4cb38199a335f3bce3a1fb1fd421a0f1 | Python | 2,513 | 99 | """
Inferring a function from a reproducing kernel Hilbert space (RKHS) by taking
gradients of eval with respect to the function-valued argument
"""
from itertools import chain
import autograd.numpy as np
import autograd.numpy.random as npr
from autograd import grad
from autograd.extend import Box, VSpace, defvjp, pr... |
69e96bb497de4a3f0acac4923610922cc3c30e97fd93ffc502dbfd97fb61dfd1 | Python | 2,516 | 57 | '''
Description:
Utility functions for figure plotting.
Author:
Jiaqi Zhang <jiaqi_zhang2@brown.edu>
'''
import numpy as np
from umap import UMAP
from sklearn.decomposition import PCA
# ======================================
def computeVisEmbedding(true_data, model_pred_data, embed_name):
if embed_name =... |
b8b8cf085816f8fa742608fd50be9be3f793753568f821cd954096225187f7b2 | Python | 2,516 | 69 | """ Calculate the rates of phrases, syllables, words and phones for each stimulus. """
import numpy as np
import pandas as pd
import textgrid
from pathlib import Path
from helpers import load_config
from scipy.io import wavfile
if __name__ == '__main__':
config = load_config('speech_config.yaml')
# Create ou... |
22881834163bb66b1c7e6a98ab82c75d18c680ecbbfd176d2fc099a30be366e4 | Python | 2,517 | 79 | #
# 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,... |
439f6131caae0fee5315daff22c6378578492fbe26ad4cbd0efd30875c02f435 | Python | 2,517 | 74 | # from scripts import *
import argparse
from deepsramp.inference import inference_warpper
parse_dict = {
# 'preprocess': {
# 'help': 'prepropcess the data',
# 'func': preprocess_data,
# '--gtf': 'the path of GTF file',
# '--fasta': 'the path of the chromosome-level FASTA file that a... |
9b01057c69f371e29ffdc70f756de9900a207ffb8ac4a995133bc5fd23f704fb | Python | 2,517 | 70 | #!/usr/bin/env python
from __future__ import print_function
import argparse
from examples.continuous_tamp.primitives import get_pose_gen, distance_fn, inverse_kin, \
get_region_test, plan_motion, MOVE_COST
from examples.continuous_tamp.run import display_plan, initialize, create_problem, dump_pddlstream
from exa... |
8edf98d398ec23b6d62a8b7da5d137d14e4db4c9e7ea233591fc0851771c01f5 | Python | 2,518 | 98 | #!/usr/bin/env python
import pickle
import numpy as np
import syncopy as spy
import matplotlib.pyplot as plt
plt.rcParams['pdf.fonttype'] = 42
# Parameters
saveFig = 1 # 0:not savefigs 1: save figs
freq_range = [15, 90] # frequency range
fs = 1250 # sampling rate
areas = {
"V1L": ['V... |
32d6a75087b99aecad6794c6ae0cdf006fe74af9542699874881a0e5229dc25d | Python | 2,519 | 79 | #!/usr/bin/env python
import sys
import re
from datetime import datetime,timedelta
import argparse
parser = argparse.ArgumentParser(description='summary iostat log.')
parser.add_argument('log_file')
parser.add_argument('-s', '--start_time', help='start of effective time')
parser.add_argument('-e', '--end_time', help=... |
6b2291d404e30214490db49e6fcd427c2624981a9250dd4cc71e7bb13e8cfb2c | Python | 2,519 | 63 | # import numpy as np
#
# from imutils import rotate_bound
# from skimage import transform
# from scipy.ndimage.interpolation import map_coordinates
# from scipy.ndimage.filters import gaussian_filter
#
# # from constants import CANVAS_SIZE
#
#
# def elastic_transform(image, alpha=0, sigma=0, random_state=None):
# "... |
c4c78e0ad63901071ccc8beb03c2768388028f464c3d0ce1af39eebabee59907 | Python | 2,519 | 114 | from collections.abc import Callable
import torch.nn as nn
handlers: list[Callable[[nn.Module], dict]] = []
def _register(fn):
handlers.append(fn)
return fn
@_register
def conv1d(module: nn.Conv1d) -> dict:
return {
"in_channels": module.in_channels,
"out_channels": module.out_channels... |
0c9a4c623c5e60a29077035c30bdbf174bed021faa9ca4d87be0a94f141efb88 | Python | 2,520 | 80 | from typing import FrozenSet, Optional, Set
from pip._vendor.packaging.utils import canonicalize_name
from pip._internal.exceptions import CommandError
class FormatControl:
"""Helper for managing formats from which a package can be installed."""
__slots__ = ["no_binary", "only_binary"]
def __init__(
... |
7ea21eae60277f2f29041b6f0adc8fa2a3db7c06bb5d39dcc3349efa1826a2bb | Python | 2,520 | 58 | import pysam
import argparse
#chromosomal locations of gene in different annotations
#currently, Ensembl human annotation...
gapdh_location = {'grch37': ("12", 6643093, 6647481, '+'),
'grch38': ("12", 6533927, 6538374, '+'),
'hg19': ("chr12", 6643585, 6647537, '+'),}
def main(sam, genome):
"""Finds the st... |
905c44f78d9b0b5ddb3ae6189d7b0eab4068a8008f968a061baf50ea1657cf0f | Python | 2,520 | 65 | import sys, os
import numpy as np
import pandas as pd
import pickle
from scipy.io import loadmat, savemat
import concurrent.futures
sys.path.append('/m/cs/scratch/networks-pm/effects_externalfactors_on_functionalconnectivity/src/analysis')
from utils import get_behav_data_15days
#####################################... |
412278d5912ee07fc35701c7291098245b9bfaac7bd3a7c6adc5ce68b233095a | Python | 2,521 | 65 | import os
import argparse
def generate_slurm_script(input_dir, output_dir, output_filename):
# Ensure output directory exists
os.makedirs(output_dir, exist_ok=True)
# Find all .bam files in the input directory
bam_files = sorted([f for f in os.listdir(input_dir) if f.endswith('.bam')])
# Generate... |
607c42ddedd42b5ab1c01f509917c924214031614a4821e9c60681f604452fc9 | Python | 2,521 | 83 | #! /usr/bin/env python
# Time-stamp: <2021-03-23 22:02:10 christophe@pallier.org>
# License: Creative Commons Attribution-ShareAlike CC BY-SA
""" Implementation of Posner endogeneous attention cueing task (see https://en.wikipedia.org/wiki/Posner_cueing_task)
"""
import random
import numpy as np
from expyriment impor... |
6e71fb1af2403b55e0729a4a23ab6f0f06808a6856bf1b5e0e51bb708752ab04 | Python | 2,521 | 60 | """Re-order the smartphone files and name it following the pre-established criteria
This script will unify the different measurements splitted in several files
into one dataframe that includes all days. The dataframe is stored as a csv
file.
The input should be done in the following order:
... |
f6cad62a5731d772cb04c545017fbb4e8833492a2c6677728ecf99f00d4d092e | Python | 2,521 | 80 | # -*- coding: utf-8 -*-
"""
Created on Fri Apr 30 19:41:08 2021
@author: divyoj
"""
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from matplotlib.animation import FuncAnimation
import numpy as np
import seaborn as sns
sns.set_style("ticks")
start=100;
stop=100;
step=10
def plots_at_rho(aL... |
091f3dc622566d3ac6da2106475a907e21640ae1b5eaaa69b6d488b122a6ef30 | Python | 2,522 | 55 | #!/usr/bin/env python
## this script visualizes the results of the anova movie comparison of the ISC values
## it reads in the results of the anova and visualizes the results on a glass brain
## it also writes the results to nifti files (if needed)
## import libraries
import os
import pandas as pd
import matplotlib.py... |
2df57668fe5e450e10c619cd518e4d152f3b6c084018f7a8eb7f43b06a7f1cc8 | Python | 2,522 | 78 | rest_api_version = 99
extensions = dict(
required_params=['training_frame', 'x'],
validate_required_params="",
set_required_params="""
parms$training_frame <- training_frame
if(!missing(x))
parms$ignored_columns <- .verify_datacols(training_frame, x)$cols_ignore
""",
with_model="""
model@model$aggreg... |
5626a1e999f923062ba7728096cf38ef66946d74bd88d7269d187264dda8d9a2 | Python | 2,522 | 89 | # 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... |
88a3edd903df2926984302f35d688121bcf68870eb51d73ee46942858bd447cb | Python | 2,522 | 75 | # 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... |
95d636a2eb5464d64849fb1eb70b064989d526998a1120470966785a972c38c4 | Python | 2,522 | 82 | """"""
"""
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... |
fb4f85f290b6d613e918b1e06a61352b80153fe6165c99f96a6ce74a9a8f8784 | Python | 2,522 | 75 | # Node group ".MN_constants_atom_name_peptide" (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 access... |
4055d3a69473c230b21f29b0e179f5a35434cb392957a94ab78cd82c0fac8c61 | Python | 2,523 | 77 | import argparse
from pathlib import Path
import multiprocessing as mp
import cv2
import pandas as pd
def is_bg(crop, box, acc):
x1, y1, x2, y2 = box
return (x2 - x1) * (y2 - y1) > 5000 or (acc < .5 and crop.std() < 30)
def filtered(args):
image_dir, annot_dir, output_dir, bg_dir = args
print(f... |
7f517e74a2672d865a899aed48571407d2773ac0cc4a3c049d6a405611f6c15f | Python | 2,523 | 72 | from collections import OrderedDict
from dictor import dictor
import copy
from srunner.scenarioconfigs.route_scenario_configuration import RouteScenarioConfiguration
from leaderboard.utils.route_parser import RouteParser
from leaderboard.utils.checkpoint_tools import fetch_dict, create_default_json_msg, save_dict
... |
bf4d298fb37a5cb8caa534a5322245dfff832eaab3dc07b0176df8062918e963 | Python | 2,523 | 78 | import numpy as np
import os
from wsilearn.compress.encoders import PytorchEncoderWrapper
from pathlib import Path
histossl_enc_pathes = [
"~/.cache/torch/hub/checkpoints/histossl_tenpercent_resnet18_state_dict.ckpt",
"~/.torch/models/histossl_tenpercent_resnet18_state_dict.ckpt... |
7af42d7356ec9b77678d51800f394123100525a8910dcbeafab9f8be4ebba5ba | Python | 2,524 | 106 | from __future__ import annotations
import pytest
prefect = pytest.importorskip("prefect")
from ase.build import bulk, molecule
from quacc import flow
from quacc.recipes.emt.core import relax_job, static_job
from quacc.recipes.emt.slabs import bulk_to_slabs_flow
def test_tutorial1a(tmp_path, monkeypatch):
monke... |
9af3e4ec53638c82ca44b21d33147b22f275ba080b802b33a3e2fdae37e98b43 | Python | 2,524 | 80 | """PEP 656 support.
This module implements logic to detect if the currently running Python is
linked against musl, and what musl version is used.
"""
import functools
import re
import subprocess
import sys
from typing import Iterator, NamedTuple, Optional
from ._elffile import ELFFile
class _MuslVersion(NamedTuple... |
a188740a07d84808398854b7c8ddde2957671615bb499ab8c888c586022ccf6a | Python | 2,524 | 65 | # Imports
from tqdm import tqdm
import numpy as np
import torch
import matplotlib.pyplot as plt
import sys
sys.path.append("/data/MEAprojects/DLSpikeSorter/src")
from model import ModelSpikeSorter
from meta import SI_MOUSE
RECORDING = np.load(SI_MOUSE[2] / "traces.npy", mmap_mode="r")
SAMP_FREQ = 30
MODEL = ModelSp... |
591dcdfeb5a4c4f26c836287a68bb5a75548e1791125ea375cbadd3d9ed41c36 | Python | 2,525 | 85 | # Plots neuron positions for Fig 3B
from os.path import join
from get_paths import *
import matplotlib.pyplot as plt
from colors_paultol import colors
import pickle
plt.rcParams["mathtext.default"] = "regular"
save_flag = 0
# Load data
fpath = join(dir_data, "data_network_locations.pickle")
with open(... |
5e250ff70c7c7f0a1fca82d939fd139ef1ba4c7f49a4bb3486babae908439e38 | Python | 2,527 | 86 | #
# Main package initializer
#
# Copyright © 2020-2025 Ernst Strüngmann Institute (ESI) for Neuroscience
# in Cooperation with Max Planck Society
# Copyright © 2026 Ernst Strüngmann Institute (ESI) of the Max Planck Society
#
# SPDX-License-Identifier: BSD-3-Clause
#
# Don't spam GIL warnings about msgpack not being t... |
c9f28b6418f21f443cd72e36d3cd3e567d9592650e22afd3082b3d57a09df8d4 | Python | 2,527 | 87 | # pylint: disable=invalid-name, missing-function-docstring, no-member
""" Transformer model module """
from random import uniform, randint
from torch import nn
from omegaconf import OmegaConf, DictConfig
def get_model(cfg: DictConfig, model_cfg: DictConfig):
return Transformer(model_cfg)
def default_HPs(cfg: ... |
6bdc1066a948b7f323e3e15c03cff0fa5aa25295b7011db6fc07a79ca0328e9e | Python | 2,528 | 65 | import numpy as np
import pandas as pd
import pytest
import scanpy as sc
import scipy.sparse as sp
from anndata import AnnData
import pertpy as pt
@pytest.fixture
def adata(rng):
labels = np.array(["control", "target1", "target2"]).repeat(30)
centers = {"control": 0.0, "target1": 5.0, "target2": -5.0}
X ... |
b46663ef8acb12350e62c3ca103c0fdc9f947731de42af03281400fe340970c2 | Python | 2,528 | 55 | # 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... |
9ddcb8098f372d7e0d051c32eda908f10055fc6e6fa2790ed8a1ff6b969fe713 | Python | 2,529 | 80 | #!/usr/bin/env python
# Written by Minh Nguyen and CBIG under MIT license:
# https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
from __future__ import print_function, division
import argparse
import pickle
import cbig.Nguyen2020.dataloader as dataloader
import cbig.Nguyen2020.misc as misc
def get_data(args,... |
6d27ba82ef448a945f862e77275928aacb3ab63e86313dc9d679f15ec94c08e7 | Python | 2,530 | 64 | # -*- coding: utf-8 -*-
"""ANI-1, A data set of 20 million calculated off-equilibrium conformations
for organic molecules. (https://doi.org/10.6084/m9.figshare.c.3846712.v1)
Please cite the original paper when using this dataset.
The dataset is splitted by molecules while loading,
meaninig the same molecule shows up... |
7766397eff05ef219b404e8e104d6e2764a7e1bb1f7bc6d78e0fe4cd5ca17426 | Python | 2,530 | 53 | """Taken from the libsonata lib."""
import h5py
import numpy as np
def write_element_report(filepath, units):
population_names = ["default", "default2"]
node_ids = np.arange(0, 3)
index_pointers = np.arange(0, 4)
element_ids = np.zeros(3)
times = (0.0, 1.0, 0.1)
data = [node_ids + j * 0.1 for... |
78e05992763ea1f66f499e14b32db3b2cbff21266b5bb150dbf1e0d95fda42fa | Python | 2,531 | 67 | ################################################################################
# Import, Set up MPI Variables, Load Necessary Files
################################################################################
import os
from os.path import join
import sys
import matplotlib
import matplotlib.pyplot as plt
from matp... |
bbb460f4ddbd329fed836dd98910550cf76dbe628008ba012e3b2667f27755c2 | Python | 2,531 | 100 | # %% Package Imports
import sys, os
sys.path.append(os.path.abspath(".."))
sys.path.append(os.path.abspath("."))
import torch
import torch.nn as nn
import torch.optim as optim
import prosper_nn.models.dhcnn as dhcnn
import prosper_nn.models.ensemble as ensemble
from prosper_nn.utils import visualize_forecasts
impor... |
e9cb635c018ed885db045646659f45033d25b9348b27021801b74fba0edc6b94 | Python | 2,531 | 105 | from __future__ import annotations
import csv
from pathlib import Path
from ..metadata.config import NomenclatureConfig
from ..metadata.files import NomenclatureScan
def save_nomenclature_csv(
output_dir: str | Path,
scan: NomenclatureScan,
config: NomenclatureConfig,
) -> Path:
"""
Save the c... |
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