sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
19f62dcf3e2769a62891f519b5209b2d586acdf8a252ce6dd554c588a0e0b7b4 | Python | 6,135 | 169 | # Copyright 2018-2020 Xanadu Quantum Technologies Inc.
# 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... |
9e557a3b629ff4b62195d3b9733f049dac430f7d44e2c5b7fe9ff9b67fd030f8 | Python | 6,135 | 145 | from src.workflow import WorkflowRepresentation, WorkFlowSpecs, WorkflowResults, WorkflowBuilder
from src.test_config import pipe_config, model_config
from sklearn.pipeline import Pipeline
from sklearn.dummy import DummyRegressor
import pandas as pd
from pathlib import Path
import tempfile
import yaml
import pytest
... |
cccdf8f9796c2c05ea90fecae4a0daff4e814aff6f11ae0f323084ccb29a0b2c | Python | 6,136 | 176 | from typing import Any
from src import config_handler
import pandas as pd
from pathlib import Path
from src.paths import Paths
LOCATION = Path(__file__).parent
VALIDATION_FILE = Path(LOCATION,'resources','FreeSurferColorLut.txt')
def read_rois(roi_file,validate=True):
""" Read the roi file and return a dictionar... |
bcac090aa5b894eb95f3416d039e178a746d2b8d9356a0daf4d9f48f61c883fd | Python | 6,137 | 180 | from datetime import datetime
import numpy as np
import torch
import os
import time
import sys
from sklearn.metrics import roc_auc_score
from glob import glob
class AverageMeter(object):
def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0
self.sum = 0
... |
6c51befd05069be8d4a372713a40677fd2fdc78604c9556a955244a0613e0474 | Python | 6,140 | 171 | import torch
import wandb
import numpy as np
from tqdm import tqdm
from matplotlib import pyplot as plt
from typing import Optional
from twoandahalfdimensions.utils.config import DataViewAxis, Config
def train_step(data, label, model, opt, loss_fn, settings, do_step=True):
data = data.to(**settings)
pred, at... |
0be5b356d82857cb16108bb760436d9822e7b8bdfd93ef008c946726f5d6b88e | Python | 6,141 | 178 | import numpy as np
import torch
def scale(x, scaler):
"""
Scales the input data using the provided scaler.
"""
# Apply the scaling transformation to the NumPy array
x_scaled = scaler.transform(x)
return x_scaled
def scale_with_gold_standard(x, column_means, column_stds):
"""
Scales ... |
f6f3c8a3451476105a01b01555256ad0ef60d69a03f360e5e87f5dcf6d93f7d2 | Python | 6,141 | 178 | """Helper functions for saving stimulus features."""
import numpy as np
import os
from hard_coded_things import featuresets_dict
from features import Features
from textgrid import TextGrid
def get_feature(featureset, features_object):
model_function, model_kwargs = featureset[0]
modeldata = getattr(features_... |
ba60a649127f19f624206dd75f17f434351c741338baedbdfc912c3939720fab | Python | 6,146 | 146 | import torch
import numpy
import matplotlib.pyplot as plt
import bionetwork
import pandas
import seaborn as sns
def generatePerturbe(Yin, refFullRaw, level):
nrKO = Yin.shape[1]
inputKO = Yin.repeat(nrKO, 1)
perturb = numpy.eye(nrKO)
numpy.fill_diagonal(perturb, refFullRaw.flatten() * level)
inputK... |
b1d7b04b9e0025b51a131e9f98486f71ae84314d5b737dadc5cf9ea37bf4b7b2 | Python | 6,147 | 193 | from datetime import timedelta
import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
class TestIntervalArithmetic:
def test_interval_add(self, closed):
interval = pd.Interval(0, 1, closed=closed)
expected = pd.Interval(1, 2, closed=closed)
result = interval +... |
73ddbc481854581fb1026da05090e8bb5191eec09f4e082da67e2f83c98f4527 | Python | 6,148 | 174 | #! /usr/bin/env python
##############################################################################
## DendroPy Phylogenetic Computing Library.
##
## Copyright 2010-2015 Jeet Sukumaran and Mark T. Holder.
## All rights reserved.
##
## See "LICENSE.rst" for terms and conditions of usage.
##
## If you use this wo... |
9ee0cba14e6a7c20fb9207503a045cbb4b7b265c2391cbd33aff28113668fa40 | Python | 6,149 | 219 | # -*- coding: utf-8 -*-
"""
Created on Sun May 1 17:33:44 2022
@author: jeanbaptiste
"""
import os
import json
import pycromanager_tessie as pmt
from pycromanager_tessie.acquisitions import experiment
# Start platform:
platform = pmt.microscope.platform.Platform(load_synchronizer=True)
# Set LED ring
platform.neop... |
413d78be826190d57df1478fffcc393b03fc587e17420b04dcad386703f2aa0b | Python | 6,154 | 136 | """
Rerun single cells in BGLibPy (for extra reporting and access to parameters to be modified)
authors: András Ecker, Sirio Bolaños Puchet; last update: 01.2023
"""
import os
import gc
import time
import logging
import numpy as np
import pandas as pd
import bglibpy
from assemblyfire.config import Config
import asse... |
06ab96798a8d7382036bba936b548c9d3d0a92ec5474764356b17d22d786b3e0 | Python | 6,159 | 185 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
def test_drop(idx):
dropped = idx.drop([("foo", "two"), ("qux", "one")])
index = pd.MultiIndex.from_tuples([("foo", "two"), ("qux", "one")])
dropped2 = idx.drop(index)
expected = idx[[0, 2, 3, 5]]
tm.assert_index_... |
ab04a5b1236b150ec6380501a6727c376844875c82d0b75cf0027b6d397ec176 | Python | 6,159 | 168 | # -------------------------------------------------------------------------------------------------------------------------------------
# Following code curated for GCPNet (https://github.com/BioinfoMachineLearning/GCPNet):
# ----------------------------------------------------------------------------------------------... |
7eec79082cf83ade7045b354e40dbd615891a4d6fd8c61c41c98b25f36ab55bd | Python | 6,160 | 189 | # coding: utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
def initialize_weights(m):
if isinstance(m, nn.Conv2d):
nn.init.kaiming_normal_(m.weight.data, mode='fan_out')
elif isinstance(m, nn.BatchNorm2d):
m.weight.data.fill_(1)
m.bias.data.zero_()
elif isi... |
1054e41fc6213c7dd2cc23c3690db666251cd4921b96e3ec4748ad341056154c | Python | 6,161 | 201 | # Copyright 2024 Xanadu Quantum Technologies Inc.
# 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 agre... |
2d8d31bbebdc544525c5bbe6e9a6a4c2dc9f7dbbec1ef8d87e49f46a48378918 | Python | 6,163 | 145 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@author: mbejtka
"""
import numpy as np
import h5py as h5
import matplotlib.pyplot as plt
from Fig2_traub_data_kcsd_column_figure import (prepare_electrodes, prepare_pots, do_kcsd)
import kCSD2D_reconstruction_from_npx as npx
from scipy.signal import filtfilt, butter
... |
3f1e7f81840f9a41a19d64ed9150b82d9fe6aa80214117628ef2fdfe5f479d9b | Python | 6,166 | 182 | __all__ = ["GlycoPeptideData", "GlycoPeptideDataConverter", "GlycoPeptideDataBatch"]
from typing import List, NamedTuple, Optional, Sequence, Union
import dgl
import torch
import torch.nn.functional as F
from torch.nn.utils.rnn import pad_sequence
from ....chem.gpep.glycans import (
GlycanNode,
Monosaccharid... |
939f565bd735092da3c00bf4631a033486e2afd838c5085da7546dd0d1009e7c | Python | 6,167 | 197 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
def test_to_numpy(idx):
result = idx.to_numpy()
exp = idx.values
tm.assert_numpy_array_equal(result, exp)
def test_array_interface(idx):
# https://github.com/pandas-dev/pandas/pull/60046
result = np.asarray(idx)
... |
a92c6da7a4705438e0040ef65ae613619caf3eefbebe9ccad3638d472b4c5da9 | Python | 6,168 | 164 | """ Onmt NMT Model base class definition """
import torch.nn as nn
class BaseModel(nn.Module):
"""
Core trainable object in OpenNMT. Implements a trainable interface
for a simple, generic encoder / decoder or decoder only model.
"""
def __init__(self, encoder, decoder):
super(BaseModel, s... |
96dd9602ed6e0b9a5e6170cd499caf7421768ee33171d15c76b4df0dcb7f59d4 | Python | 6,171 | 205 | # -*- coding: utf-8 -*-
#
# Configuration file for the Sphinx documentation builder.
#
# This file does only contain a selection of the most common options. For a
# full list see the documentation:
# http://www.sphinx-doc.org/en/master/config
# -- Path setup ------------------------------------------------------------... |
817d08a82960941f0f4256cbf681838aa091c2e1f7d9f9b7b7e44563fa2b68ca | Python | 6,172 | 171 | import importlib
import operator
import numpy as np
import pytest
from pandas.compat._optional import VERSIONS
import pandas as pd
import pandas._testing as tm
from pandas.core.computation import (
check,
expr,
expressions,
)
from pandas.core.computation.engines import ENGINES
from pandas.util.version im... |
4e35306a2a3aa058864ce1f2648f022a7969456fb50f1cb685339bf882ac2b53 | Python | 6,174 | 125 | """Prepare the real OrganAge example from the CC0 PRIDE deposit PAD000022.
Run from the repository root:
uv run --with openpyxl python tutorials/data/prepare_pad000022.py \
--source-dir /tmp/pad000022 --output-dir hf_static_data/repo
"""
import argparse
import hashlib
import json
from pathlib import Path
... |
16368ac8de653ae7ce857fa18597a5c9b40aae16fe002d591089cecc8a61edba | Python | 6,175 | 188 | # Copyright 2026 Xanadu Quantum Technologies Inc.
# 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 agre... |
2686aa4b108a7aab39db581c731a8ac7502d57515dd34a8b0cd74dfd9d5e8e5f | Python | 6,177 | 180 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
from pandas.tests.base.common import allow_na_ops
def test_unique(index_or_series_obj):
obj = index_or_series_obj
obj = np.repeat(obj, range(1, len(obj) + 1))
result = obj.unique()
# dict.fromkeys preserves the order
... |
ecad109933d8d0e81087aecd04b232bb2ede361f71185fd290119a75df400a0a | Python | 6,177 | 176 | import reverb
import tensorflow as tf
from rl_toolkit.networks.models import DuelingDQN
from rl_toolkit.utils import VariableContainer
from ...core.process import Process
class Server(Process):
"""
Learner
=================
Attributes:
env_name (str): the name of environment
port (i... |
73a82721f26c64ba036a997cb2826bdde3b4991c87d35d2d3eed4620cd0b093e | Python | 6,178 | 151 | import numpy as np
class Chromatogram():
"""
Representation of a chromatographic peak
Contains the related peak object, the size and margin of the chromatogram and its dataframe as a numpy array.
"""
def __init__(self, peak, size, margin, dataframe):
self.peak = peak
self.size = ... |
487801fa6ebf72fb66944c008b528c4b386d9654cac1d024e30e14d60cc2a4f9 | Python | 6,180 | 198 | __all__ = ["NGlycan"]
import functools
from typing import Optional, Tuple
from .glycans import GlycanNode
NGlycanCore5 = Tuple[GlycanNode, GlycanNode, GlycanNode, GlycanNode, GlycanNode]
NGlycanBranches = Tuple[GlycanNode, ...]
SYMBOL_HEX = "H"
SYMBOL_HEXNAC = "N"
SYMBOL_FUC = "F"
SYMBOLS_BISECTING = ("N", "X")
... |
c3e4b4bcc374460cb46e52909de5fb7a8e811972b5b27beec86562a53f23b889 | Python | 6,180 | 140 | """Correctness tests for the GAE implementations (PyTorch loop and Triton kernel).
The Triton tests require CUDA and an importable triton; they are skipped
otherwise (e.g. on CPU-only CI). The PyTorch-path tests always run.
"""
import os
import subprocess
import sys
import pytest
import torch
from rl_games.triton_c... |
22ec187313be8f49e1f341b893956b07e7616ef132a0f6ba084d6e1a1d9f3da4 | Python | 6,181 | 140 | """DataFrame preprocessing must preserve sample identity and original values."""
import warnings
import numpy as np
import pandas as pd
import pytest
from pyaging.preprocess import df_to_adata, epicv2_probe_aggregation
def test_dataframe_stays_on_host_when_cupy_is_available(monkeypatch):
from types import Simp... |
ea5cfa9ed12cd0292f44b254f8727cfcb2c891b8081d6822cc93f98d5e04f70f | Python | 6,181 | 145 | """Defines DataSequence object."""
import numpy as np
import itertools as itools
from interpdata import sincinterp2D, gabor_xfm2D, lanczosinterp2D
class DataSequence(object):
"""DataSequence class provides a nice interface for handling data that is both continuous
and discretely chunked. For example, semanti... |
148cbea60149601c3cef7681a82cb56394297f84f813a0e874f0d5850663557a | Python | 6,182 | 194 | #!/usr/bin/env python3
# -*- encoding: utf-8
# JN 2014-08-30
# convert ncs files to edf files
# this converter does as of now (2014-08-31)
# not follow all EDF+ rules, but is compatible with
# EDF. In particular, no time channel is kept here
# further work is required
from __future__ import print_function, division
i... |
252d9f7dcf577bae443e122585d9fbeb9f9f686166d27a9e62713edcd859f8f2 | Python | 6,182 | 178 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Oct 5 11:09:36 2023
@author: jinani
This code is a working example of estimating the receptive fields
of a V1 neuron recorded in cats for the fist pass-without any cropping.
First part of the code loads the cell responses for natural images and
ca... |
a81d1362067dd5b558444d2aa7acc4ffddf4b9fd9eec7a8632722bc85091aa3f | Python | 6,184 | 193 | from __future__ import annotations
import datetime as dt
from typing import (
TYPE_CHECKING,
Any,
cast,
)
import numpy as np
from pandas.core.dtypes.dtypes import register_extension_dtype
from pandas.api.extensions import (
ExtensionArray,
ExtensionDtype,
)
from pandas.api.types import pandas_dt... |
2cf332fc5489b2a9905f998ab464d2e1d3ce8e42f5a2c5572ae9561d91381d75 | Python | 6,185 | 215 | import os
import pathlib
import random
import sys
import unittest
import anndata as an
import numpy as np
import pandas as pd
import torch
from torch.utils.data import *
random.seed(42)
from os.path import abspath, dirname, join
sys.path.append(join(dirname(abspath(__file__)), "..", "src"))
from data import *
from ... |
fe386395f244ff1ab19268cb0e98f2a0bfb69497f5c2d5421426886c39de242d | Python | 6,186 | 159 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Project information -----------------------------------------------------
# https://www.sphinx-doc.org/en/master... |
59b46f9a11a10ed925dbc7b856207dc2e12b259ac69e22f59b7a752b0f9cb8b6 | Python | 6,192 | 226 | import pandas as pd
import numpy as np
import itertools
import random
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.preprocessing import MinMaxScaler
from sklearn.metrics import mean_squared_error
from sklearn.metrics import mean_absolute_error
from... |
38b47c837a9f3331df40a029dcb0a35325714c8b2aab6ce43b2604ceca4be730 | Python | 6,193 | 188 | import numpy as np
import torch
import torch.nn.functional as F
import sys
from scipy.interpolate import LinearNDInterpolator, NearestNDInterpolator
from scipy.spatial.qhull import QhullError
class DataInterpolation:
def __init__(self, device, num_channels, nx, ny, nz):
self.__ny = ny
self._fac_... |
b3ad39953d432f5f7da71cc151fb3816d169afb78c22f81e13209ca00f01d576 | Python | 6,196 | 207 | # coding: utf-8
"""
class for channel table
"""
# JN 2014-12-16
from __future__ import division, print_function, absolute_import
import logging
logger = logging.getLogger(__name__)
from PyQt5.QtCore import Qt, QAbstractTableModel, QModelIndex, QVariant
NCOLS = 16
OBJECT, FNAME, POS_SP, NEG_SP, SORTED_SES, EXTR,\
S... |
7365ac60421a6aeb7836807c2a7577d9eaf97895d7d27f43d2d6c86135ae6dc3 | Python | 6,200 | 131 | import pandas as pd
import numpy as np
import scipy as sp
from tqdm import tnrange, tqdm_notebook
def label_trials(log_df, conds):
whisker = log_df['block_type'] == 'Whisker'
visual = log_df['block_type'] == 'Visual'
correct = log_df['correct'] == 1
lick = log_df['response'] != 0
lick_right = log_df['... |
ab4c6b8d9fa720409ad03a097bcbd84651366105f22a740ff4a7bcdd46009272 | Python | 6,200 | 135 | """Cardiac MR Fingerprinting signal model (EPG)."""
from collections.abc import Sequence
import torch
from mrpro.operators.models.EPG import DelayBlock, EPGSequence, FispBlock, InversionBlock, Parameters, T2PrepBlock
from mrpro.operators.SignalModel import SignalModel
class CardiacFingerprinting(SignalModel[torch.... |
034272820a5e1f496fb5638f177fad52236e563cc28c2a64cea84cc119ccead2 | Python | 6,201 | 179 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 3 00:51:46 2023
@author: s205272
"""
import numpy as np
def normalize_mi_ma(x, mi, ma, clip=False, eps=1e-20, dtype=np.float32):
if dtype is not None:
x = x.astype(dtype,copy=False)
mi = dtype(mi) if np.isscalar(mi) else mi... |
923d0027880965a935988d32df441f039f37ba060c31dcb18f21211b693980d8 | Python | 6,201 | 140 | import numpy as np
import pytest
from pandas.errors import Pandas4Warning
from pandas.core.dtypes.dtypes import CategoricalDtype
import pandas as pd
import pandas._testing as tm
class TestCategoricalDtypes:
def test_categories_match_up_to_permutation(self):
# test dtype comparisons between cats
... |
debf900a24e3084525eec01779eebcdd57eb458187ece0684a487da3de2c3858 | Python | 6,201 | 163 | # -*- coding: utf-8 -*-
"""
Created on Mon Jul 11 11:26:07 2022
@author: fm02
epoching is adapted from setareh10/semnet-project/sn_epoching.py
"""
import sys
import numpy as np
import pandas as pd
import os
import mne
from importlib import reload
path = "/home/fm02/Decoding_SDLD/SourceSpaceDecoding_SDvsLD"
os.chdir... |
3bbf2c847bd98ef3934d5f6e8426dafb5471967264572458708411839d61206f | Python | 6,203 | 194 |
#### create branch- and depth-specific pcfg
import re, sys, os
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..', 'resource-gcg', 'scripts'))
import model
MAX_ITER = 20
#### 0) read model from stdin
mCr = model.Model('Cr')
mCC = model.CondModel('CC')
mCu = model.CondModel('Cu')
mX = model.CondM... |
4423cb7d26191469e06a3d70836c8099071564adce47ac90e3fe1f1a67981ee2 | Python | 6,203 | 166 | import torch
import numpy
import matplotlib.pyplot as plt
import time
import bionetwork
import plotting
import pandas
from scipy.stats import pearsonr
import seaborn as sns
from scipy.stats import pearsonr
import saveSimulations
#Load network
networkList, nodeNames, modeOfAction = bionetwork.loadNetwork('data/KEGGnet-... |
5cd3c10bfbdf368238f8450ab766a0df8b2eac6f25199ad34fd4db8c23ded79d | Python | 6,203 | 187 | # -*- coding: utf-8 -*-
import torch
import random
import inspect
import numpy as np
from itertools import islice, repeat
import os
def check_path(path, exist_ok=False, log=print):
"""Check if `path` exists, makedirs if not else warning/IOError."""
if os.path.exists(path):
if exist_ok:
lo... |
6f38445d71449f892c3b03f8ba7e06ff31fb35300ba16d7fceedeaaffa183906 | Python | 6,203 | 222 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
adapted from https://github.com/FNNDSC/pl-fetal-brain-assessment/blob/main/fetal_brain_assessment/resnet_architecture.py
"""
INPUT_SHAPE = (217, 178, 60)
# Identity Block for ResNet
def id_block(X, f):
from keras.layers import (
Conv3D,
BatchNo... |
d7be1711660cbdfb8dd6f70b3342973adea6fbccf21810dbd511a069cb33da21 | Python | 6,203 | 198 | """Module for parallel processing of pdb files into structural info"""
from argparse import ArgumentParser
import logging
import os
import sys
from time import time
from typing import Tuple
import h5py
from hdf5plugin import LZ4
import numpy as np
from progress.bar import Bar
from pyrosetta.rosetta.core.pose import P... |
8dc8add21555e756fc4bf3ddf6886a208d2461876eb1a59fe8de043a3aa64aed | Python | 6,204 | 187 | from __future__ import absolute_import
from __future__ import print_function
import tarfile
import os
import sys
import shutil
import hashlib
from six.moves.urllib.request import urlopen
from six.moves.urllib.error import URLError, HTTPError
import requests
from generic_utils import Progbar
from modac_utils import g... |
1f1c3349800c35a52dda44bbd470daa558bfa5f22c3a3ffe061e95b7064e138a | Python | 6,206 | 142 | #!/usr/bin/env python
"""
Given:
1. single cell UMI, BC file (ccs -> umi, bc)
2. collapse group.txt (ccs -> pbid)
3. SQANTI classification (pbid -> transcript, isoform, category)
4. optional ontarget file (pbid -> ontarget or not)
Output a collated infor file that is:
<ccs>, <pbid>, <transcript>, <ge... |
f07939f4c9934f4bdeacca09f77b4f4763a7c7f8c66df32e63455374dee2edb2 | Python | 6,206 | 109 | # 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... |
b0379fb8c9caf5b1aaecdd061f267771f804160d25f1d6a1250ace57a339ea29 | Python | 6,208 | 193 | import requests
from PIL import Image
from neuronbridge.model import *
class Client:
def __init__(self, data_bucket="janelia-neuronbridge-data-prod", version="current"):
"""
Client constructor.
When the client is created, it retrieves the configuration for the specified version.
... |
76d90e98b30e252a0753ee6a93da193b22d7fe38fabb3a1f4aa7f81e104cc71c | Python | 6,210 | 179 | """
Create seaborn plot for discriminator predictions on real data
Author: Rebecca Riley
Date: 03/15/2023
"""
import math
import matplotlib.pyplot as plt
import numpy as np
import sys
sys.path.insert(1, "../")
from discriminator import OnePopModel
from generator import Generator
from global_vars impor... |
6c41b22e5a74105debb61477fe75c402c66155d764f8f540f40c5e17600bd0f2 | Python | 6,211 | 202 | """
Tests for the Skew and Kurt evaluation metrics.
Verifies that:
- Skewness and excess kurtosis are near 0 for
standard-normal z-scores.
- Skewness is positive for right-skewed z-scores.
- Excess kurtosis is positive for heavy-tailed z-scores.
- Both metrics handle NaN and Inf values gracefully.
"""
import numpy ... |
5bf63421f50efeb09c43736f2d33c120d41187ac6b4c334057b6fac0b8765382 | Python | 6,212 | 150 | from initialization.config import *
import numpy as np
import pandas as pd
from typing import Optional, List
from sklearn.preprocessing import MinMaxScaler, StandardScaler
def scale_features(
df: pd.DataFrame,
factors: List[str],
method: str = SCALING_METHOD,
average_time_windows: bool = AVERAGE_TIM... |
48a1432136cae0284c9677281c0c221a5a9be159b6a637f711972121ec623ca1 | Python | 6,213 | 149 | # Copyright 2018-2025 Xanadu Quantum Technologies Inc.
# 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... |
8adb24149695759235722ae2d10d5c77270ea34f43c04f2f640588e440a99163 | Python | 6,215 | 137 | from botocore.client import Config
import ibm_boto3
from io import StringIO
import types
import os
import pandas as pd
from sqlalchemy import create_engine
import sqlalchemy.orm as orm
import sys
import json
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(os.path.abspath(os.... |
628d95360846c9ef35e8d5817f7270b37934e4a01f21d611bdd50bf7148ad4f1 | Python | 6,218 | 147 | '''
Contains the clutter class
'''
import warnings
warnings.filterwarnings("ignore")
import os
from utils_mod import shlex_cmd
class Clutter:
'''
A class that contains all of the paramters for a single clutter image
'''
def __init__(self, clutter_sample, composition_type='occlusion'):
'''
... |
8117198fb06631dac21926f10e21c61910d8a1096e7ed6f19042f400632d482c | Python | 6,218 | 151 | """Tests for filters."""
import pytest
import torch
from einops import repeat
from mrpro.utils.filters import filter_separable, gaussian_filter, uniform_filter
@pytest.fixture
def data():
"""Create a simple 3D tensor with a single voxel set to 1.0."""
data = torch.zeros(1, 1, 5, 5, 5)
data[..., 2, 2, 2] ... |
f28f9e5d59f75e02e754a091fe53520f79683fce171d3e8642cec700b791ddfa | Python | 6,218 | 168 | """Public caller regressions run in subprocesses to bound native hangs."""
import os
from pathlib import Path
import signal
import subprocess
import sys
import pytest
SCRIPT = r'''
import numpy as np
import sys
import threading
import logging
from concurrent.futures import ThreadPoolExecutor
import MACS3.Signal.Call... |
c69d7e5ba06f710fbb0afd363e383cac397efac1c49b276ab3d35539cc430b7f | Python | 6,221 | 161 | """Session 22 — god-class drain, first pass: persistence verbs.
The ``save_model`` / ``load_model`` / ``save_experiment`` / ``load_experiment``
verbs on ``Experiment`` no longer delegate to ``self._legacy``. They are now
thin wrappers around the stateless helpers in ``pycaret.persistence``. These
tests lock that contr... |
d0ca66a5a8f34b784681d5fb81d6a526acd68a1699cdc6f66ad9a02331751ffe | Python | 6,226 | 179 | ''' backcheck_publishedurl.py
This program will backcheck publishedURL to neuronMetadata
'''
import argparse
from operator import attrgetter
import sys
from colorama import Fore, Style
import jrc_common.jrc_common as JRC
# Database
MONGODB = 'neuronbridge'
DATABASE = {}
def terminate_program(msg=None):
''' ... |
3fdfbb0d805b1df384bbf667ede010442668b4fde0cb6cfae621074577e10ba2 | Python | 6,227 | 146 | import sys
import re
from storestate import Sign, StoreState, getUnkWord
import numpy
import scipy.sparse
import collections
import math
################################################################################
class IndexMap(dict):
def __missing__ ( this, key ):
this[key] = len(this)
return this[key... |
44f98c16943fa3e858d67c26cd9008634d16336256bf748dbda0dc8644c66b03 | Python | 6,227 | 103 | #!/opt/local/bin/python2.7
import os
from os import path
import argparse
import base.surfaces as surfaces
import logging
from base import loggingUtils
from base.kernelFunctions import *
from base.affineRegistration import *
def main():
parser = argparse.ArgumentParser(description='runs surface matching registra... |
315089cfe3102f3a9c8fb4be91eef0c070db1521270d31175268728feffd0c51 | Python | 6,228 | 134 | # License: see [LICENSE, LICENSES/legged_gym/LICENSE]
import os
from datetime import datetime
from typing import Tuple
import torch
import numpy as np
from rsl_rl.env import VecEnv
from rsl_rl.runners import OnPolicyRunner #, AMPOnPolicyRunner
from legged_gym import LEGGED_GYM_ROOT_DIR, LEGGED_GYM_ENVS_DIR
from .he... |
f773a52233c414e80f900924248dae43fbe5a8a552e006bee95ca9bbb1d36203 | Python | 6,228 | 215 | import h5py
import numpy as np
import xml.etree.ElementTree as etree
from typing import Dict, List, Optional, Sequence, Tuple
def load_file_T2(fname: str) -> Tuple:
"""
Load T2 fastmri file.
Parameters:
-----------
fname : str
Path to the h5 fastmri file.
Returns:
-------... |
9b461f150cb090b721906e05548f627ba7417dda0f9e9f40b65e86d07f978bde | Python | 6,233 | 165 | """Public API and CLI regressions for #801, part of #757."""
import gzip
from pathlib import Path
import struct
import subprocess
import sys
import pytest
from conftest import macs3_env, no_core_dumps
def run_probe(tmp_path, path, source):
script = tmp_path / "probe.py"
script.write_text('''
from pathlib i... |
c3cd3adc3e7ac0e6f6866093f7619da091d86ce996ebb69167e9dc7abcb8f617 | Python | 6,233 | 275 | import operator
import pytest
import pandas as pd
import pandas._testing as tm
@pytest.fixture
def dtype():
"""A fixture providing the ExtensionDtype to validate."""
raise NotImplementedError
@pytest.fixture
def data():
"""
Length-10 array for this type.
* data[0] and data[1] should both be n... |
52ff16b43052e4b8d657c9f803643bb4ee9cae37b3654a151174f6d37e523318 | Python | 6,234 | 167 | # Copyright 2018-2021 Xanadu Quantum Technologies Inc.
# 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... |
7f932c99323e76d020b69e9ce6d032d41c88a5d3de73c7d349d6a7e5ddc249d8 | Python | 6,244 | 139 | """Public compiled-track and CLI regressions for #802 (part of #757)."""
from pathlib import Path
import random
import pytest
from MACS3.Commands import callpeak_cmd, callvar_cmd
from MACS3.Signal import FixWidthTrack, PairedEndTrack
@pytest.mark.parametrize("command", [callpeak_cmd, callvar_cmd])
@pytest.mark.par... |
071a903583df09f26ba6fe3162aeed20e5a09bbef8ade91cf7a97f6820f8d0f8 | Python | 6,248 | 231 | """Plot module for gradec."""
import math
import os
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import colormaps
from neuromaps.datasets import fetch_civet, fetch_fsaverage, fetch_fslr
from surfplot import Plot
from surfplot.utils import threshold
from wordcloud import WordCloud
from gradec.fe... |
3f7b776a7b66702db884449d4026103bd7be3a35f2126fb765a5a1863bbc190b | Python | 6,249 | 206 | import os
import numpy as np
import matplotlib.pyplot as plt
from src.models import NeuralKalmanFilter, KalmanFilter
from src.utils import *
plt.style.use('ggplot')
device = "cpu"
print(device)
# hyper parameters
seq_len = 1000
inf_iters = 20
inf_lr = 0.1
learn_lr = 1e-5
# create the dataset of the tracking prob... |
889853dcb05ea03b14e1e4e38fe54bb265e6eb8d3d61f4c6be048321f742b906 | Python | 6,252 | 192 | # Copyright 2018-2023 Xanadu Quantum Technologies Inc.
# 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... |
42d24495d38499e3353426ca425894e81d691780cd45b9c28228590c636bc1aa | Python | 6,261 | 124 | # Copyright (c) 2018-2023, NVIDIA Corporation
# 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. Redistributions of source code must retain the above copyright notice, this
# list of condit... |
9dea04b837dbe66e11924750331c5490621ac1cf90d0a4a134fca805b35cf49d | Python | 6,262 | 210 | import math
import numbers
import random
import numpy as np
import torch
from PIL import Image, ImageFilter
from torchvision import transforms
class Compose(object):
def __init__(self, transforms):
self.transforms = transforms
def __call__(self, img, mask):
assert img.size == mask.size
... |
3d6e24814374c277d056c91799bc5ea6787f7e1c3f0208feaece26ce71ea019e | Python | 6,263 | 177 | import numpy as np
import pytest
from pandas._libs.tslibs import IncompatibleFrequency
import pandas as pd
import pandas._testing as tm
@pytest.fixture
def date_range_frame():
"""
Fixture for DataFrame of ints with date_range index
Columns are ['A', 'B'].
"""
N = 50
rng = pd.date_range("1/1... |
1c988b9f1732d67f6061e4203196ea153da2b99db9fae8b890622a617691790b | Python | 6,266 | 177 | from collections import defaultdict
import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
@pytest.mark.parametrize(
"data, categories",
[
(list("abcbca"), list("cab")),
(pd.interval_range(0, 3).repeat(3), pd.interval_range(0, 3)),
],
ids=["string", "interv... |
b57872509a27d1068e1122f4819c72182e122585569d73c21b8905c6ed26f589 | Python | 6,269 | 160 | import torch
import numpy
import matplotlib.pyplot as plt
import bionetwork
import pandas
from scipy.stats import pearsonr
import seaborn as sns
import copy
import matplotlib.patches as patches
from matplotlib import cm
from matplotlib.colors import ListedColormap
def loadModel(refModel, fileName):
#work around to... |
1c1b067c4fbf8b5e84d16f238ce075c7035054e1ab39c5526622ff9b65947191 | Python | 6,271 | 186 | import torch.nn as nn
import torch
import torch.nn.functional as F
import numpy as np
class MaskedCosineLoss(nn.Module):
"""Masked cosine loss between angles."""
def __init__(self):
super().__init__()
def forward(self, pred, tgt, mask):
mask = mask.bool()
p = torch.masked_select(... |
ffebd9df844e70791678fd0fe2bf6021c3e4fec1233c9e12ac69f2cdcccda92e | Python | 6,272 | 199 | # coding: utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
def initialize_weights(module):
if isinstance(module, nn.Conv2d):
nn.init.kaiming_normal_(module.weight.data, mode='fan_out')
elif isinstance(module, nn.BatchNorm2d):
module.weight.data.fill_(1)
module.... |
c8e6aba4f43de25ed667c80e4970793f3e2acef2b67cca6b02939ba228cd8f7a | Python | 6,274 | 210 | # Copyright 2018-2025 Xanadu Quantum Technologies Inc.
# 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... |
5ae55bbad9fadb7e15001c8f455333b195fa5a52b00aae265a654d5ff83e5271 | Python | 6,275 | 157 | import os, sys, re, torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import numpy as np
def read_dictionary(filename):
d = {}
with open(filename, 'r+') as f:
for line in f:
line = line.strip().split('\t')
d[line[1]] = int(line[0]... |
03e455bee4751fcd113770f97c2a078c13cfe78bcd1e0da817269f3fd37fea20 | Python | 6,280 | 174 | import numpy as np, matplotlib.pyplot as plt, sys
import pumpprobe as pp
from scipy.optimize import lsq_linear
plt.rc('xtick',labelsize=5)
plt.rc('ytick',labelsize=5)
unc31 = "--unc31" in sys.argv
add_s = "_unc31" if unc31 else ""
funa = pp.Funatlas(merge_bilateral=False,merge_dorsoventral=False,merge_numbered=False... |
e2a3d104a160ba09720421c56a177dfae631ec113703c5e671ed5228c4b8dd4f | Python | 6,282 | 175 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
from pandas.core.arrays import FloatingArray
@pytest.mark.parametrize("box", [True, False], ids=["series", "array"])
def test_to_numpy(box, using_nan_is_na):
con = pd.Series if box else pd.array
# default (with or without miss... |
6b8d5b5cf28a79940f337995930fab793f202b3f435b59fed2f1c89cc6a26ac3 | Python | 6,283 | 189 | import numpy as np
import scipy as sp
import scipy.interpolate as interp
try:
from vtk import vtkPolyDataReader, VTK_ERROR
gotVTK = True
except ImportError:
print('could not import VTK functions')
gotVTK = False
import os
# General surface class
class Grid:
def __init__(self, gridPoints=None):
... |
1eaf9dc4290810d839f2122c87a429fcb8d46e39c7a2116e1694d8e9fb04f0a6 | Python | 6,285 | 143 | import subprocess
from os import path as op
from importlib import reload
print(__doc__)
# wrapper to run python script via qsub. Python3
fname_wrap = op.join('/', 'home', 'fm02', 'Desktop', 'MEG_EOS_scripts',
'Python2SLURM.sh')
job_list = [
# # Neuromag Maxfilter
# {'N': 'SemCat_TimeG... |
b90028e863eaf71ccbbfca096bb060818aea750bba513e94a02bdfb2b5346bc4 | Python | 6,287 | 174 | import numpy as np
import pytest
from pandas._libs import index as libindex
import pandas as pd
import pandas._testing as tm
class TestGetSliceBounds:
@pytest.mark.parametrize("side, expected", [("left", 4), ("right", 5)])
def test_get_slice_bounds_within(self, side, expected):
index = pd.Index(list... |
3669f7db111958a410e3ecc9615d0ca6defcdb865379551376b02a59b8481379 | Python | 6,296 | 214 | #!/usr/bin/env python
from __future__ import print_function, division
import numpy as np
import pandas as pd
from rdkit import Chem
from rdkit import rdBase
from rdkit.Chem import AllChem
from rdkit import DataStructs
import rdkit.Chem.QED as QED
from MCMG_utils import scripts as sascorer
import pickle
# from chemprop... |
513004d7752d57e48cf63171144d3a0a15e5e31cef3dbf564c54d4ace4d19e01 | Python | 6,303 | 179 | from datetime import datetime
import zoneinfo
import pytest
from pandas.errors import NullFrequencyError
import pandas as pd
import pandas._testing as tm
class TestDatetimeIndexShift:
# -------------------------------------------------------------
# DatetimeIndex.shift is used in integer addition
def ... |
29029d983d70ffaf2a7bb91a1dfc61fcc8f8eb2269a85163eae3e21577f19813 | Python | 6,304 | 150 | import torch
import torch.nn as nn
import numpy as np
import rl_games.algos_torch.torch_ext as torch_ext
class GeneralizedMovingStats(nn.Module):
'''
Updates moving statistics with momentum
'''
def __init__(
self, insize, impl='mean_std', decay=0.99, max=1e5, eps=0.0, perclo=0.05,
perc... |
47bb1822e4aebbd4b416848bec53fc018601012800d1da90f8567df0fa0faa69 | Python | 6,306 | 186 | from __future__ import print_function, absolute_import, division
import json
import numpy as np
import os
from PIL import Image, ImageDraw
from collections import namedtuple
data_folder = 'semantic_segmentation_images_annotations/Images_and_Supervisely_Annotations/'
folder = 'json'
folder_masks_anatomy_inst = 'mask_an... |
9b9449e3e6c53f0fe6b4018e2eb2f15466f9a2c67e47c98b8ffc64a218281502 | Python | 6,307 | 159 | # this module creates objects of the different models
import tensorflow as tf
from tensorflow.keras import models
from tensorflow.keras import layers
from tensorflow.keras.applications import (
VGG16, VGG19, Xception, ResNet50, ResNet50V2, ResNet101,
ResNet101V2, ResNet152, ResNet152V2, EfficientNetB0,
Eff... |
6591247b0021bb7c70791e22bd6b7258314978f4a348dbcefc1daa65f25bd82c | Python | 6,314 | 150 | """Diagnosis normalization and longitudinal (temporal) label correction.
Ports the labeling logic from `Dataset_MRI.ipynb` / `Dataset_PET.ipynb`
(see `docs/legacy-notebooks-inventory.md`), preserving its scientifically
meaningful decisions:
- The demented/not-demented regex classification, including treating
"uncer... |
a065de43a2d0ea4fb9a4072b387ed52b5872b21aae65c261f9d2a597c7332a5b | Python | 6,316 | 182 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
def test_reindex(idx):
result, indexer = idx.reindex(list(idx[:4]))
assert isinstance(result, pd.MultiIndex)
assert result.names == ["first", "second"]
assert [level.name for level in result.levels] == ["first", "second... |
a448879edc625f6e219fa2e324cb3f9c7b34b05478064d564ae4b0eb8baa1e9b | Python | 6,316 | 190 | from __future__ import print_function, absolute_import, division
import json
import numpy as np
import os
from PIL import Image, ImageDraw
from collections import namedtuple
data_folder = 'semantic_segmentation_images_annotations/Images_and_Supervisely_Annotations/'
folder = 'json'
folder_masks_mix = 'mask_mix'
folder... |
eccf77a1e317d186a6793a95ba949ef5b48c976ed435d7c9c88ca5fdeea4b853 | Python | 6,317 | 119 | # 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... |
e6e2d83e0ed1384d615213a426d43556650048ad45556ad52e5d3a35f226d514 | Python | 6,318 | 162 | # Copyright 2026 Xanadu Quantum Technologies Inc.
# 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 agre... |
a96531cb54b3fdaf92fe668580163d9a9ac132c4d9a40f5b1784d8c9d0ff60b4 | Python | 6,322 | 196 | import importlib
import sys
import torch
import torch.nn as nn
import windseer.utils as utils
from .ModelBase import ModelBase
class ModelStacked(ModelBase):
'''
Experimental model consisting of multiple stacked models.
'''
def __init__(self, **kwargs):
super(ModelStacked, self).__init__()... |
7012094b810e27c9f4f8e69944cf5f8948ed570f8bf569de6a21af9a2c6f8b67 | Python | 6,323 | 173 | from datetime import datetime
import numpy as np
import pytest
from pandas.errors import OutOfBoundsDatetime
import pandas as pd
import pandas._testing as tm
class TestSeriesClip:
def test_clip(self, datetime_series):
val = datetime_series.median()
assert datetime_series.clip(lower=val).min() ... |
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