sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
c87b0cd61464488cbc21439b1609ccb585e784ea5dc130839c0b81f8a80aac79 | Python | 3,202 | 109 | """
Shared helper functions for evaluator-related tests
(MACE, MSLL, etc.).
These utilities are plain functions rather than pytest
fixtures so that individual tests can control their
parameters directly.
"""
import numpy as np
from pcntoolkit.dataio.norm_data import NormData
# Predefined batch-effect configurations... |
e158b3e1f72c4dd2c34ba9a274be93e5b709b69fb291201d7391918edb4c070c | Python | 3,202 | 121 | # ---
# jupyter:
# jupytext:
# text_representation:
# extension: .py
# format_name: percent
# format_version: '1.3'
# jupytext_version: 1.15.2
# kernelspec:
# display_name: .venv
# language: python
# name: python3
# ---
# %%
# %load_ext autoreload
from pathlib import Path
im... |
b136b2ac02bb6ae8a10714fd30923b6462dffb62eb23c946731ec29b6075bf48 | Python | 3,205 | 101 | __all__ = ["MgfReader"]
import os
import re
from typing import Optional, Union, cast
import numpy as np
from .abs import MassSpectrumReaderBase
from .spec import MassSpectrum
class MgfReader(MassSpectrumReaderBase):
def __init__(self, file):
if isinstance(file, str):
file = open(file, 'r')
... |
a24f6f8a3e1cc64b48bbf466f7037bbac74ead792218ffd8c4e133bbb659f55b | Python | 3,206 | 85 | import yaml
import os
import datetime
import getpass
import itertools
from argparse import ArgumentParser
import numpy as np
class Config:
def __parse_args(self):
parser = ArgumentParser()
parser.add_argument('parameters', metavar='param', type=str, nargs='*',
help='para... |
411808be75378aa7ab1d20433db7a81a613de16a4ce04e91f218226208ad10a3 | Python | 3,210 | 83 | #%%
# -*- coding: utf-8 -*-
import numpy as np
import sys,os
sys.path.append('./')
from utils.model import *
from utils.cal_param import *
from utils.move_detector import main
from utils.unet import *
from env_config import *
#=========================set values below==========================
# Load models
input_sh... |
a58d83a167e5588959e5c861bfb2ff585a0fb4dfd6cc21fc6db2ec0328832fa6 | Python | 3,212 | 63 | import pandas as pd
import mne
import numpy as np
class Epoch(object):
def __init__(self, data):
"""
Creates an 'Epoch' class that applies epoching and averaging functions on the contiuous data via its sub-functions.
Functions applied on a given class instance will adjust in-place
... |
ca027a4d1d46a1bac50177d6ca07645573934e3deb9e48cdddbb2f334ff03b54 | Python | 3,212 | 100 | import sys
import types
import pytest
from pandas.compat._optional import (
VERSIONS,
import_optional_dependency,
)
import pandas._testing as tm
def test_import_optional():
match = "Import .*notapackage.*pip.*conda.*notapackage"
with pytest.raises(ImportError, match=match) as exc_info:
impo... |
0c44f57c8afa26af7fce13eb50d1ca98d996d92bc530719af7979219e289e284 | Python | 3,214 | 90 | '''
Created 2016/2017
@author: arco
'''
from __future__ import absolute_import
import numpy as np
import pandas as pd
from six import BytesIO
import sumatra
from model_data_base.utils import silence_stdout
from .cell_parser import CellParser
def convert_hoc_array_to_np_array(hoc_array):
'''converts hoc array to ... |
a0becc4db5d24fd67bb95bab26caad7ec83d98c400b01d52ee840476a14be564 | Python | 3,214 | 93 | # emacs: -*- mode: python-mode; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*-
# ex: set sts=4 ts=4 sw=4 et:
"""
.. _annotations_cogat:
===================
The Cognitive Atlas
===================
We can download the Cognitive Atlas and extract CogAt terms from text.
"""
import os
import matplotlib.pyp... |
0467355430808f6f562e71215e62af3f32556fe6aa845bcca4748b7abb95cd64 | Python | 3,215 | 113 | # -*- coding: utf-8 -*-
"""
Created on Mon May 22 13:28:48 2023
@author: Jonas Hartmann @ Mayor lab @ UCL CDB
@descript: Potential functions E_pot=f(dist, ...) for use in understanding
and specifying simple_cell_sim models.
"""
# Imports
import numpy as np
def pot_Hooke(dist, dist0, k):
"""Hoo... |
b09179f000cd3abfeb1b5d703ff7edfa093ce9c2d5379831b5ad5b8852a0a3d1 | Python | 3,218 | 84 | # -*- coding: utf-8 -*-
"""
Created on Thu Jul 18 16:39:53 2019
@author: Wladek
"""
import scipy.stats as st
import os
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from figure_properties import *
def set_axis(ax, x, y, letter=None):
ax.text(x,
y,
... |
c9121ebcd0f26a7dba55eee0ed8f49d066106b1cf0459220b79bfa0b8379e392 | Python | 3,218 | 84 | import time
import pandas as pd
from utils import print_from_history, series_to_matrix
from copy import deepcopy
import warnings
from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier
from sklearn.linear_model import SGDClassifier, LogisticRegression
import numpy as np
from evaluators.calculate... |
74f9952f8959d4fe86620a4b7cf961d0b931f5b63bfed00377e59c56befc5525 | Python | 3,219 | 98 | import numpy as np
from scipy.stats import norm
from scipy import interpolate
from statsmodels.distributions.empirical_distribution import ECDF
def estimate_params(values):
"""
Estimate parameters of a gaussian distribution from values.
args:
values: values to estimate parameters from
returns:
... |
86e63921e6d232c37aaf4ae63795e36f2ac82cf61f66536c8015a563b8cfa03e | Python | 3,219 | 94 | import torch.nn as nn
import torch.nn.functional as F
from torch.utils.checkpoint import checkpoint
from sequence_models.convolutional import MaskedConv2d, ByteNet2d, ConditionedByteNetDecoder, MaskedConv1d, ByteNet
from sequence_models.layers import PositionFeedForward
class ByteNetStructureModel(nn.Module):
""... |
971609b15d63a5f8729f7954997fdee564cdaf66287cfae0a1694766fc78ed73 | Python | 3,221 | 113 | import re
import pytest
from pandas.core.indexes.frozen import FrozenList
@pytest.fixture
def lst():
return [1, 2, 3, 4, 5]
@pytest.fixture
def container(lst):
return FrozenList(lst)
@pytest.fixture
def unicode_container():
return FrozenList(["\u05d0", "\u05d1", "c"])
class TestFrozenList:
def... |
c86c876e4e5386e618bf303afc6bf1e8722b72e420fb95205d308bf32aa6a7c9 | Python | 3,221 | 81 | import gymnasium as gym
import numpy as np
from pettingzoo.sisl import multiwalker_v9
class MultiWalker(gym.Env):
def __init__(self, name="multiwalker", **kwargs):
gym.Env.__init__(self)
self.name = name
self.env = multiwalker_v9.parallel_env()
self.use_central_value = kwargs.pop('... |
2f471f1882d08d1cc983f78d4d52305b88e8d21b84831c280d7dc6bbaceb3b33 | Python | 3,223 | 125 |
import os
import torch
import pickle
import matplotlib.pyplot as plt
import matplotlib as mpl
load_dir = '/Users/elizabethnewman/Desktop/tnn_results/cifar10/tensor/'
subdir_names = []
for subdir_name in os.listdir(load_dir):
if subdir_name == '.DS_Store':
continue
subdir_names.append(subdir_name)
... |
63d413a9dc2302440135e689dbbe57ad0b3b1e0aeb18efe6b587857ca85375de | Python | 3,224 | 90 | from pathlib import Path
from unittest.mock import ANY, Mock
import pytest
import pyaging.data as public_data
import pyaging.data._data as data_module
@pytest.mark.parametrize(
("data_type", "filename"),
[
("GSE130735", "GSE130735_subset.pkl"),
("GSE193140", "GSE193140.pkl"),
("GSE13... |
bc3f32401fccd7fd9212f0dc2e5e18ca7fe0acdd6cf6ab9ec55506266726c475 | Python | 3,224 | 95 | #!/usr/bin/env python
#
# Copy manually corrected labels (segmentations, vertebral labeling, etc.) from the preprocessed dataset to the
# git-annex BIDS dataset's derivatives folder
#
# For full help, please run: python copy_files_to_derivatives.py -h
#
# Example:
# python copy_files_to_derivatives.py
# -pa... |
473e921d31d368b59902c4554e1799fdd7454c06437e7432b004cc8c90fce438 | Python | 3,225 | 76 | """Spoiled gradient echo signal model."""
import torch
from mrpro.operators.SignalModel import SignalModel
from mrpro.utils.reshape import unsqueeze_right
class SpoiledGRE(SignalModel[torch.Tensor, torch.Tensor, torch.Tensor]):
"""Spoiled gradient echo signal model."""
def __init__(
self, flip_angl... |
15219263dc38804147311fb3f69c5b74977459801a9ed72bce9782df0d204259 | Python | 3,227 | 94 | from dateutil.tz import tzlocal
import numpy as np
import pytest
from pandas.compat import WASM
import pandas.util._test_decorators as td
import pandas as pd
import pandas._testing as tm
class TestNormalize:
def test_normalize(self):
rng = pd.date_range("1/1/2000 9:30", periods=10, freq="D")
re... |
4c83a2da394b63dc9c293afd8ba65416b1956b8ed30b0d3ec9167fd39e30dc67 | Python | 3,227 | 97 | try:
if INIT:
print("Initialized.")
except:
import matplotlib.pyplot as plt
import numpy as np
from scipy.signal import find_peaks
import pandas as pd
INIT=True
def figGen(name="DATA.csv",i=0,T=False):
df = pd.read_csv(name,header=0)
stngExc = df['stngExc'].to_numpy()
stngExcStd... |
1d555e97a2f20e8d94d5c1473e8165a203ed8575fe449e1808ffe59d3458fcfd | Python | 3,229 | 98 | import sys
import re
import pdb
import random
DOCSTART = "0001:(U !ARTICLE)"
LOGFILE = open("numberededitabletrees2conll.log","w+")
class CorefTracker:
def __init__(self):
self.wordlist = [] #e.g., [('word1','0101'),('word2','0102'),...]
self.chains = {} #e.g., {'0102':['0102','0112',...],...}
... |
4f65243ae740935f227136a0d52f1fe0c3a220541f39bf01584876b97092d572 | Python | 3,229 | 92 | import pytest
import pandas._testing as tm
class TestDataFrameTake:
def test_take_slices_not_supported(self, float_frame):
# GH#51539
df = float_frame
slc = slice(0, 4, 1)
with pytest.raises(TypeError, match="slice"):
df.take(slc, axis=0)
with pytest.raises(Ty... |
f64aa4da92ea9356b1102b5aefc17f25f8bda1163fd6e70eb1057ceb1cf5e5c1 | Python | 3,229 | 89 | import pandas as pd
from matplotlib import pyplot as plt
import os
import numpy as np
import scipy as sc
import pylab as pl
import seaborn as sns
from matplotlib.lines import Line2D
def plot_quartet_identical(data_file):
data_frame = pd.read_table(data_file)
fig = pl.figure(figsize=(5, 2))
ax = fig.add... |
3b911781ceb5fcd68de11db308f2c5625aa028eb36c9d1b05df0541cc52648ac | Python | 3,230 | 93 | import os
from typing import Optional, Union, cast
import numpy as np
import pandas as pd
from ...util.config import Configurable
from .rtlib import RetentionTimeLibraryBase
COLUMN_RUN_NAME = "run_name"
COLUMN_RT = "retention_time"
COLUMN_SCORE = "score"
class NonRedundantRetentionTimeConsensus(Configurable):
... |
a8bbd7f8c37564fcc769798bb4cf2a3778026204930d833767a329f94aa5ce83 | Python | 3,231 | 87 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
@pytest.mark.parametrize("func", ["ffill", "bfill"])
def test_groupby_column_index_name_lost_fill_funcs(func):
# GH: 29764 groupby loses index sometimes
df = pd.DataFrame(
[[1, 1.0, -1.0], [1, np.nan, np.nan], [1, 2.0, ... |
26cdb534ba1437e2c7ef228b7e4675ef03b7078b25f60fbfd1deccca405d5f08 | Python | 3,232 | 137 | # JN 2015-01-13
# refactoring artifact calculation
"""
this module contains functions that identify
artifact clusters based on the spike wave forms
"""
from __future__ import print_function, division, absolute_import
import logging
import numpy as np
from .. import options, artifact_criteria
logger = logging.getLogg... |
3602d24402165b5d70cddd9b1b8e41ff3737c4f4cf54301b3a5996f569c0bb32 | Python | 3,232 | 68 | import os
import caffe
import argparse
import numpy as np
import scipy.misc
from PIL import Image
from util import segrun, fast_hist, get_scores
from cityscapes import cityscapes
parser = argparse.ArgumentParser()
parser.add_argument("--cityscapes_dir", type=str, required=True, help="Path to the original cityscapes da... |
ca6a9660b49582265714c8853fcb55a7ed11f8fb82877188ac720dcaeaa43bf2 | Python | 3,232 | 87 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
@pytest.mark.parametrize("func", ["ffill", "bfill"])
def test_groupby_column_index_name_lost_fill_funcs(func):
# GH: 29764 groupby loses index sometimes
df = pd.DataFrame(
[[1, 1.0, -1.0], [1, np.nan, np.nan], [1, 2.0, ... |
357784e70efb8ca5aec5f0baad8efb5eaf68cee7ef8713bdf8b62351683eac2c | Python | 3,234 | 69 | # 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... |
2ed9d96292a42d66d48ad6d73f1a8dd833a21cde037ae25cde9a9dcf340dcdc8 | Python | 3,237 | 170 | # Copyright 2018-2026 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 ... |
30b07a66bc2d345d6df284cb858b730065411982140f7041cf5c66e493164b59 | Python | 3,237 | 112 | import torch
import torch.nn as nn
from roost.cgcnn.model import DescriptorNetwork
from roost.core import BaseModelClass
from roost.segments import MeanPooling
class CrystalGraphPreNet(BaseModelClass):
"""
Create a crystal graph convolutional neural network for predicting total
material properties.
... |
be7dd5606165d0518fe5b1222087489887e8a172542cec49a308118dc1862743 | Python | 3,237 | 114 | from typing import Tuple, List, Dict
import numpy as np
from ...image import Stack
from . import motion_estimation
from . import iqa
from ...utils import DeviceType
def compute_metric(
stacks: List[Stack],
metric: str,
batch_size: int,
augmentation: bool,
device: DeviceType,
) -> Tuple[List[float]... |
bd7cc969cb5660dffdf1ecc83e6091ff5c5acba357fd0b7b340c7e46eded0e6c | Python | 3,239 | 88 | import sys
import argparse
import numpy as np
import pandas as pd
import configparser
def compute_splitID(y, split_fields):
"""
Map tuples in columns designated by **split_fields** into integer ID to use for data partitioning.
:param y: ``pandas`` ``DataFrame``; response data.
:param split_fields: ``l... |
a02dd553a34cdf7348cf531cc92803c084c816fa12c178efb75ad4ce04fb27a1 | Python | 3,240 | 108 | """CSV-upload datasource driver.
Reads a CSV that the user uploaded via ``POST /data-sources``. The
``config`` carries the object-storage URI (``file://`` or ``s3://``);
the driver pulls bytes through ``ObjectStore``.
The ``secret_value`` arg is unused (CSV uploads have no credentials),
kept in the signature for prot... |
0dca7c11f070bc3ae826ce0dc5c2a518da9b9b5cd0638ae16160426b81e151b9 | Python | 3,241 | 77 | # 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... |
960f1aa40712141184867ef7e0be6a69dcfc47bf4a5cc4572d4e07b5fb651fab | Python | 3,241 | 83 | import os, tempfile, shutil, pathlib
from tqdm import tqdm
from urllib.request import urlopen
_DOWNLOADS_URL = 'https://www.kilosort.org/downloads'
_DOWNLOADS_DIR_ENV = os.environ.get("KILOSORT_LOCAL_DOWNLOADS_PATH")
_DOWNLOADS_DIR_DEFAULT = pathlib.Path.home().joinpath('.kilosort')
DOWNLOADS_DIR = pathlib.Path(_DOWNL... |
f9d6ff71b36f5876019739fece5705cea827f46e340908113bb962c8578db686 | Python | 3,241 | 85 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 30 22:05:33 2022
@author: ecastrow
"""
import sqlalchemy as db
import pandas as pd
# Default setup to load a database
engine = db.create_engine('sqlite:////data2/eduardo/code'
'/xls_preprocessing/app/xls.db')
connection... |
0c2ea4365e32d0c19cd4bcb1139cb015a9c6f89ac6680abaa6809a584372939d | Python | 3,242 | 117 | import argparse
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as stats
import scipy.signal as signal
import sys
script_path = sys.argv[0][:sys.argv[0].rfind('/')]
sys.path.append(script_path+'/../..')
import charact_utils as utils
import plot_utils as pu
def plot(time,data... |
3c8cfe14fa5d2da91f008190c9b4539ae57d423dece16e3161ea8d7e26e5d484 | Python | 3,242 | 91 | import numpy as np
import torch.utils.data as tdata
import torch
import pandas as pd
from sklearn.decomposition import NMF
import warnings
def warn(*args, **kwargs):
pass
warnings.warn = warn
def randrows(A, size):
return A[np.random.randint(A.shape[0], size=size), :]
class RamanSpectraSeqDataset(tdata.... |
a0168100ec5989c1a7ab0c97722993ff4a0a266101c2fb16d095942ae1c21776 | Python | 3,242 | 97 | import gymnasium
import matplotlib.pyplot as plt
import numpy as np
import flappy_bird_gymnasium
from flappy_bird_gymnasium.envs.utils import MODEL_PATH
from flappy_bird_gymnasium.tests.dueling import DuelingDQN
from flappy_bird_gymnasium.tests.dueling_v2 import DuelingDQN as DuelingDQN_v2
from flappy_bird_gymnasium.t... |
daf74f9b5008543449ab0a41576248e30821ad042dd68231715964d7ff79d3a1 | Python | 3,242 | 105 | """Project CRUD (nested under a workspace)."""
from __future__ import annotations
from typing import Annotated
from fastapi import APIRouter, Depends, HTTPException, status
from sqlalchemy import select
from sqlalchemy.orm import Session
from pycaret_server.api.schemas import ProjectCreate, ProjectResponse
from pyc... |
26be883b75ef2fdd55c9052fa02aa4b0e1cdf24e2c50a32bc97370ccce4edebc | Python | 3,243 | 103 | # 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... |
d8d17a0ed09f078649ded87e9b647a8f2e06ec2fe354ecc9bffe73524ed49e15 | Python | 3,244 | 88 | import esm
from typing import Sequence, Tuple, List, Union
import torch
RawMSA = Sequence[Tuple[str, str]]
def rawbatchlen(raw_batch: str):
count = 0
counting = True
for ch in raw_batch:
if ch == "<":
counting = False
if ch == ">":
counting = True
... |
62e3e5725245307b37286ea4803b408e4a057cdc28ec242ab4cd99883c1b56bc | Python | 3,245 | 105 | """
This code incorporates modifications to software originally developed by the Turaga Lab, available at https://github.com/TuragaLab/DECODE.
The original work is licensed under the GNU General Public License version 3.0 (GPL-3.0).
We have adapted and extended this code under the same GPL-3.0 license.
"""
import t... |
e659611f9de7dccb783716537c135f90b36855ecda416e0b449637e14d7153f7 | Python | 3,246 | 107 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jul 5 11:47:43 2023
@author: cbclab
"""
from numpy import genfromtxt
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.style as style
import seaborn as sns
from scipy import stats
import pandas as pd
from matplotlib.ticker import F... |
c485918ad73e1ae5744a9a2b8c9a4bf4d92a45a7271d905654f2b057ad4e7234 | Python | 3,250 | 79 | from wordfreq import tokenize, word_frequency
import pytest
def test_tokens():
# Let's test on some Chinese text that has unusual combinations of
# syllables, because it is about an American vice-president.
#
# (He was the Chinese Wikipedia's featured article of the day when I
# wrote this test.)
... |
a2938be214748f2af59f09d81995e7839f05ab934534165f50f92504df8c1792 | Python | 3,251 | 105 | import numpy as np
import pygame
from flappy_bird_gymnasium.envs.constants import (
BASE_HEIGHT,
BASE_WIDTH,
PIPE_HEIGHT,
PIPE_WIDTH,
PLAYER_HEIGHT,
PLAYER_ROT_THR,
PLAYER_WIDTH,
)
class LIDAR:
def __init__(self, max_distance):
self._max_distance = max_distance
self.co... |
aea2ab81d244f6616d878792a99a3654473a65d57d54995aa9f08ad7e1833865 | Python | 3,252 | 85 | """
@author: Hongao ZHU
@description:
extract the human response data from the .mat files and rearrange them in .csv format
this program averages the voxel responses for the 12 rois relavant to language
@example usage:
cd ~/zhu.3986
python3 scripts/transform_mat.py -I /fs/project/schuler.77/corpora/or... |
fcf842bb42804c659e5e00606a963b50d78fb8507658a08a66352811da237e1a | Python | 3,252 | 135 | """Utility methods to print system info for debugging.
adapted from :func:`sktime.show_versions`
adapted from :func:`sklearn.show_versions`
"""
__author__ = ["Nikhil Gupta"]
__all__ = ["show_versions"]
import logging
import platform
import sys
from typing import Optional
from pycaret.utils._dependencies import get_m... |
3454e1967763864897a44eedfd037159012e9c6eacba5fef4db26410a93fa488 | Python | 3,253 | 75 | import psycopg2
import pdb
from sqlalchemy import create_engine
import sqlalchemy.orm as orm
import os
import sys
import zipfile
import pandas as pd
import numpy as np
from tqdm import tqdm
import json
from io import BytesIO
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(os... |
91f0094ae5f319a16cc0954c0c158492950a9538530bbf689841629d692abbe9 | Python | 3,253 | 111 | import os
import csv
import glob
import random
import pandas as pd
def ID_shuffler(list1, list2):
temp = list(zip(list1, list2))
random.shuffle(temp)
res1, res2 = zip(*temp)
# res1 and res2 come out as tuples, and so must be converted to lists.
res1, res2 = list(res1), list(res... |
ff0ec9fc7a70f82889703caea6912d93b1023e0675fceae6687849e93b6044f6 | Python | 3,254 | 96 | import numpy as np
import pytest
import pandas.util._test_decorators as td
import pandas as pd
import pandas._testing as tm
from pandas.core.internals.blocks import NumpyBlock
class BaseCastingTests:
"""Casting to and from ExtensionDtypes"""
def test_astype_object_series(self, all_data):
ser = pd.S... |
4d0fa3fae91d936ae661c8169faf02ffda875913d4e80ff12306df49793e09ab | Python | 3,256 | 79 | # Ported from the Isaac Lab rl_games integration (isaaclab_rl); original DexPBT
# implementation from NVIDIA-Omniverse/IsaacGymEnvs (https://arxiv.org/abs/2305.12127).
# Copyright (c) 2022-2026, The Isaac Lab Project Developers.
# SPDX-License-Identifier: BSD-3-Clause
from dataclasses import dataclass, field, fields
... |
6712f19eda0889ec4b00aae445a5e671e9767a530504909dbcceef48084345af | Python | 3,256 | 84 | # 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... |
8571cafe948f08dbfcd7e475733226c7cea662d49abde8e0ac6e0ebf5eece39c | Python | 3,259 | 87 | import numpy as np
import matplotlib.pyplot as plt
import sys
import os
from kcsd import sKCSD
from kcsd import sKCSD_utils as utils
import kcsd.validation.plotting_functions as pl
import sKCSD_utils
n_src = 512
lambd = 1
R = 8e-6/2**.5
if __name__ == '__main__':
fname_base = "Figure_3"
tstop = 75
scaling_f... |
1f33c358e7cd8b019edee3905d17b028665fd555c27c4d142ee41ccb4c41d387 | Python | 3,260 | 75 | """Phase 1: jobs table — queueable unit-of-work for the worker pool.
Revision ID: a1b2c3d4e5f7
Revises: f0a1b2c3d4e5
Create Date: 2026-05-13 09:00:00.000000+00:00
Adds the ``jobs`` table that backs the executor backend toggle
(``RUNS_BACKEND=inprocess|redis``). With ``inprocess`` the in-process
``RunOrchestrator`` ke... |
2451c3826210640a5e8ba50434da1841ea22283ca1f61f6761c1a011bc6f9305 | Python | 3,262 | 102 | """Test MDCNN dataset."""
import io
import re
import urllib.request
import numpy as np
import pytest
import scipy.io
import torch
from mrpro.data import KData
from mrpro.phantoms.mdcnn import MDCNNDataset, download_mdcnn
from mrpro.utils import RandomGenerator
N_PHASES = 2
N_COILS = 3
N_K1 = 208
N_K0 = 416
N_K0_PADD... |
a057e93f33a258d27087ef2a0cc459334b36696b72a1e84dbc575d13e5eaa35f | Python | 3,263 | 103 |
from skimage import filters, morphology as morpho, measure, util
from matplotlib import pyplot
#from sklearn.neighbors import LocalOutlierFactor
from sklearn.ensemble import IsolationForest
from cine import Cine
import tube2
import align
import numpy as np
import glob
import pathlib
from multiprocessing import Process... |
e26aa0acebf1799b22a11c2fbdeffab2c1cfccd1b226f9e562fe14c3d33619a0 | Python | 3,265 | 91 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
class TestToNumpy:
def test_to_numpy(self):
df = pd.DataFrame({"A": [1, 2], "B": [3, 4.5]})
expected = np.array([[1, 3], [2, 4.5]])
result = df.to_numpy()
tm.assert_numpy_array_equal(result, expected... |
3add731d5663d0c782b56e34fad99730ee85c9efbfd1abc5d4c8e8d1bdc03925 | Python | 3,266 | 111 | import os
import csv
import glob
import random
import pandas as pd
def ID_shuffler(list1, list2):
temp = list(zip(list1, list2))
random.shuffle(temp)
res1, res2 = zip(*temp)
# res1 and res2 come out as tuples, and so must be converted to lists.
res1, res2 = list(res1), list(res... |
517b788b954f2ca2d610bfb16b57784022ff55397479b5d6d580b336f5223fea | Python | 3,266 | 111 | import numpy as np
import re
import sys
import random
import cv2
def read_pfm(filename):
file = open(filename, 'rb')
color = None
width = None
height = None
scale = None
endian = None
header = file.readline().decode('utf-8').rstrip()
if header == 'PF':
color = True
elif he... |
7e04de074cd6945fbeb0f2fafd00e11cdd999c6933de48192a22e64f3fefb110 | Python | 3,266 | 167 | """
compat
======
Cross-compatible functions for different versions of Python.
Other items:
* platform checker
"""
from __future__ import annotations
import platform
import sys
from typing import TYPE_CHECKING
from pandas.compat._constants import (
CHAINED_WARNING_DISABLED,
IS64,
ISMUSL,
PY312,
... |
d78f2a7c2bb3e2350eefbb7b8b8797cd33c3bdc1858899bc33e94c643b7dca96 | Python | 3,267 | 86 | #!/usr/bin/env python3
"""
Description:
Parallel experiment simulation using Python multiprocessing.
Usage:
./simulate_exps_python.py -i <tx_counts> -m <tx2gene> -l <pheno> -n <num_experiments>
Author:
Beril Erdogdu
Date:
September 2025
"""
import os
import argparse
from multiprocessing import Pool, c... |
1124e0b9fe8ec3fc2a45063b03076b41a075d28dd790408a2f8cc62a4587fdcd | Python | 3,271 | 73 | #
# Linearity class for use in holographic neural networks.
#
# Layer takes inputs f_{i-1} of shape l x c(l,i-1) x m(l)
# and contracts it with weights W_{i} of shape c(l,i-1) x c(l,i).
# It returns the contracted product as output.
#
# In einstein notation, the equation for this layer is
#
# g^i_{l,c(l,i),m(l)} =... |
e612ea4e0643b2207dc7691b956c9cc7ba2497bb5f71cc8f922dd74568480ddc | Python | 3,271 | 100 | import pandas as pd
import itertools
from nltk.stem.isri import ISRIStemmer
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, confusion_matrix, roc_auc_... |
c418c5d9a38dd1658b10927df4212d06b979fcf1c6d973f6c5289e65aba937fb | Python | 3,273 | 102 | from sklearn.model_selection import KFold, RepeatedStratifiedKFold, GridSearchCV
class CVSpec():
"""
A class that stores the specifications for the CV process.
Attributes:
-----------
n_splits : int, optional
The number of folds to generate. Default is 5.
n_repeats : int, optional
... |
8daae99db219083485261f0df73ee1985008b56aa469cee295e17c7e4f095f8b | Python | 3,275 | 107 | from typing import Tuple
import numpy as np
import scipy.signal # type: ignore
from caiman.source_extraction.cnmf import deconvolution # type: ignore
def foopsi_all(intensities: np.ndarray) -> Tuple[np.ndarray, np.ndarray]:
"""Uses FOOPSI algrorithm from CAIMAN package to decompose calcium signal and estimate... |
d40b191115290b6d37ff61083f152bdcc465df500e5e349c7b18863bf352b734 | Python | 3,276 | 139 | # MOFTransformer version 2.2.0
import torch.nn as nn
from transformers.models.bert.modeling_bert import (
BertConfig,
BertPredictionHeadTransform,
)
class Pooler(nn.Module):
def __init__(self, hidden_size, index=0):
super().__init__()
self.dense = nn.Linear(hidden_size, hidden... |
3d2890194240469193ade3d9340b366fde451f630dbea757f86103727f9fa9e0 | Python | 3,277 | 109 | # PrairieLink
# Lloyd Russell 2017
import os
import numpy as np
import time
try:
# for Python2
import Tkinter as tk
import tkFileDialog as filedialog
except ImportError:
# for Python3
import tkinter as tk
from tkinter import filedialog
def ReadRawFile(movie_path=None, start=1,... |
3e62e0b4f600a8abc8e3ca75291eee6c6e750e75bac821ec58d7317ad098bb6c | Python | 3,278 | 93 | """Tests for MOLLI signal model."""
from collections.abc import Sequence
import pytest
import torch
from mrpro.operators.models import MOLLI
from mrpro.utils import RandomGenerator
from tests import autodiff_test
from tests.operators.models.conftest import SHAPE_VARIATIONS_SIGNAL_MODELS
@pytest.mark.parametrize(
... |
e5b3ef67d09939d98239d1a772e714e27c203c64bd63db2ace8979d9de7501ba | Python | 3,278 | 94 | import numpy as np
from collections import OrderedDict
from batchgenerators.utilities.file_and_folder_operations import *
from nnunet.paths import splitted_4d_output_dir
import SimpleITK as sitk
import shutil
def copy_nifti_modify_labels(in_file, out_file):
# use this for segmentation only!!!
# nnUNet wants ... |
5408a8c22c0efaeceb7c176fa9de32f26af446324fbdb6228781d6c8ecdcc7c9 | Python | 3,279 | 93 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon May 9 18:08:13 2022
@author: jinani
"""
# Import Required Libraries
from tensorflow import keras
from tensorflow.keras.layers import Conv2D, AveragePooling2D
from SysIden_AvgMethod_SupportFiles.k_layers import gaussian2dMapLayer, PowerLowNonLinearity
... |
ddb9dffbe26b69fe8ffeafc42d62e8e98e734e39b503b4044ab3c5ef24965f25 | Python | 3,279 | 86 | import dgl
import torch
import torch.nn as nn
import torch.nn.functional as F
from dgllife.model.readout import WeightedSumAndMax
class MultiHeadGATLayer(nn.Module):
def __init__(self, in_dim, hidden_dim, num_heads):
super(MultiHeadGATLayer, self).__init__()
self.heads = nn.ModuleList()
fo... |
adba3ac0faabe52bdfb4541ca288d9b69db15ada7d6d77b7861c98e3d29155ad | Python | 3,282 | 86 | import numpy as np
import pytest
from pandas.errors import Pandas4Warning
import pandas as pd
import pandas._testing as tm
class TestIndexConstructor:
# Tests for the Index constructor, specifically for cases that do
# not return a subclass
@pytest.mark.parametrize("value", [1, np.int64(1)])
def t... |
c0fe257ad695f03039273eab2cd413ad1ce97bace9128bc547a07ffb33b5051f | Python | 3,283 | 86 | from Environment import *
from Registration.VISoR_Brain.visor_sample import VISoRSample
VERSION = '0.9.6'
class VISoRBrain:
def __init__(self, path=None):
self.slices = {}
self._transforms = {}
self.transform_source = {}
self.atlas_transform = None
self.slice_spheres = {}
... |
456583d492861ed0ae1d168991a48e283edd260556f725b4147e384563617262 | Python | 3,286 | 103 | from torch.nn.modules.loss import _Loss
import torch.nn
import torch.nn.functional as F
from tnn.tensor_utils import modek_product
class tLoss(_Loss):
def __init__(self, size_average=None, reduce=None, reduction: str = 'mean') -> None:
super(tLoss, self).__init__(size_average, reduce, reduction)
class t... |
dde398a12d98265a1d5ecf8db2f11259a63e0bbbeb3da924dae70e5681893c98 | Python | 3,286 | 103 | r"""
General math utils.
"""
__all__ = ['lerp', 'normalize_tensor', 'append_value', 'append_zero', 'append_one', 'vector_cross_matrix',
'vector_cross_matrix_np', 'block_diagonal_matrix_np']
import numpy as np
import torch
from functools import partial
def lerp(a, b, t):
r"""
Linear interpol... |
07e69ca1c102d30db40651b2ac2e5e5f04e13bb9bfd924042f7789f2f267c1d7 | Python | 3,287 | 82 | # 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... |
7762070cea7d49a747d2063ed9d2f58e70b073083e67dd13f35792c73c42e136 | Python | 3,287 | 110 | """
datetimelke_accumulations.py is for accumulations of datetimelike extension arrays
"""
from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
from pandas._libs import iNaT
from pandas._libs.tslibs import OutOfBoundsTimedelta
from pandas.core.dtypes.missing import isna
if TYPE_C... |
42a63d88e71cd3ead1755e5a17ece0bf863cdf732f42e191046c8ee1314a8540 | Python | 3,289 | 123 | # -*- coding: utf-8 -*-
# JN 2014-09-25
# create h5 file containing histogram of firing channels
# in time bins
# this is used to exclude bins with too many channels firing
# as they are likely to be artifacts
from __future__ import print_function, division
import logging
import os
import numpy as np
import tables
imp... |
89070d1ff91b3282ade831fcf073e3d02c0f42ae8d103399d31ec5f32a9a0b01 | Python | 3,289 | 86 | import torch
from torch import nn
# Typing
from torch import Tensor
from typing import List, Optional, Tuple
def bessel(x: Tensor, start: float = 0.0, end: float = 1.0, num_basis: int = 8, eps: float = 1e-5) -> Tensor:
"""Expand scalar features into (radial) Bessel basis function values.
"""
x = x[..., N... |
aa0ea528b0ccaa910d6f89016725bf9931b97a76e24b94e2dccdfdd4673dfa41 | Python | 3,289 | 96 | #####################################################################################################################
# Date created : 10/21/2022
# Date modified: 10/21/2022
# Purpose : This program is to crate features from pdb, 25 features from dssp, 2 features from convex hull atoms volume and surface area, ... |
34ed31ed305b2905752c2d1e6e06c002e43bfaa98c31814bbdd4556228165d51 | Python | 3,290 | 74 | # 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... |
9cc7de095cba862b7b76945a245ce6b2925cc6effc8da1d71c83c91a7eafade9 | Python | 3,291 | 85 |
import pandas as pd
import numpy as np
import altair as alt
import scipy.stats as st
datasets = ["glauc_sec", "age", "amd_rob", "amd_rob_age", "glauc_rob", "tenano"]
bundles = ["UNC_L", "UNC_R", "CST_L", "CST_R", "L_OR", "R_OR"] #"fov_L", "fov_R", "mac_L", "mac_R", "periph_L", "periph_R"]
formal_b_names = {
"UNC... |
732de35f55a4765941dc6b7efedac36ae19f501e5749869a3c9f22b2e8dcb11d | Python | 3,292 | 84 | # Copyright 2021 DeepMind Technologies Limited
#
# 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 agr... |
b7325bddbcd79697723c5da8110ec9d53ca8dfbe55e5f19fd58f4a71d407b98f | Python | 3,292 | 105 | #!/usr/bin/env python
"""
If given 1 input argument (FILEN), lists all the sub-BRIKs in that file.
If given 2 input arguments (FILEN, SUBBRIKNAME), returns the zero-indexed
BRIK number for that sub-brik.
e.g.
> greg% python /path/to/parse_3dinfo.py my_bucket+orig
Full_Fstat
cat2_conv_c1#0_Coef
cat2_conv_c1#... |
1c3039d38e2824fa46ec1f69cca350167275bd2bc5f6a176e4d9b707f3ee0511 | Python | 3,294 | 90 | from StimulationProcess.BasicStimulationProcess import BasicStimulationProcess
from psychopy import core, visual, event
import time
class FinishProcess(BasicStimulationProcess):
def __init__(self) -> None:
super().__init__()
def change(self):
if self.controller.endGame:
... |
fafaf024a89247846b1c700df80aab523775b3fdd87424adaf39595a42864f5b | Python | 3,296 | 63 | import pandas as pd
import os
import sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from app import create_app, db
from app.models import Subject, SourceDataset, Visit
from load_db.OASIS import get_oa... |
18c05ed78c77fba5e72a41d7a8f033d288110f6a6728ffd6bf75f720db5b0ad3 | Python | 3,298 | 77 | #%% Imports
from pathlib import Path
import os
import argparse
def get_subjects(data_dir: Path):
subjects = [subject.name for subject in data_dir.iterdir() if subject.is_dir()]
# remove fsaverage
subjects = [subject for subject in subjects if subject != 'fsaverage']
return subjects
def get_asegstats2t... |
83e2ddd4cae409f95bf873b7b9121b05ae695a0d1969492637aa9937849f0294 | Python | 3,298 | 94 | """Zero Operator."""
import torch
from mrpro.operators.LinearOperator import LinearOperator
class ZeroOp(LinearOperator):
"""A constant zero operator.
This operator always returns zero when applied to a tensor.
It is the neutral element of the addition of operators.
"""
def __init__(self, keep... |
92627927252964927a75e2acc759b643a027be99b72c43441a6e1c7900a49be3 | Python | 3,298 | 100 | import pandas as pd
import itertools
from nltk.stem.isri import ISRIStemmer
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, confusion_matrix, roc_auc_... |
f1249ba51e33acf8dac493027dc33a6c86d7e727400893b3f08d9abe470d3056 | Python | 3,300 | 102 | # Created by G. Peter Lepage (Cornell University) in 12/2013.
# Copyright (c) 2013-19 G. Peter Lepage.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# any... |
06711858d7b1158165567ce9405e9ba193de79689284db28af21e6a1bd13bfac | Python | 3,303 | 97 | import argparse
from datetime import datetime
import numpy as np
import os
import windseer.utils as utils
def make_openfoam_csv(
cosmo_data_file,
cosmo_terrain_file,
geotiff_file,
logfile,
csv_file,
resolution=64,
plot_figs=False,
rotate=None,
s... |
45bcc0ef81a071bc5bbbfc832d1c0848f7da235aa4b8cc5cf1a7fc4dc2bffccb | Python | 3,303 | 79 | """Tests for CardiacFingerprinting signal model."""
from collections.abc import Sequence
import pytest
import torch
from mrpro.operators.models.cMRF import CardiacFingerprinting
from mrpro.utils import RandomGenerator
from mrpro.utils.reshape import unsqueeze_right
from tests import autodiff_test
def test_cmrf_basi... |
d8885b8d64e780c4b6c936f70b82f18ff90d9d14c508dbab85883d2cba590c63 | Python | 3,303 | 71 | # -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import numpy as np
import json
import time
import openmc
from utils.mcsimulation_square import *
from env_config import *
#=========================set values below==========================
num_sources = 1 # the number of radiation sources to place.
a_num = 2 ... |
3bb24796e6d93867bdeef1adbdbb8bf2ec60f96ced3fd029088f1d8f46771732 | Python | 3,304 | 104 | """
Public API classes that store intermediate results useful for type-hinting.
"""
from typing import TYPE_CHECKING
from pandas._libs import NaTType
from pandas._libs.lib import NoDefault
from pandas._libs.missing import NAType
from pandas.core.col import Expression
from pandas.core.groupby import (
DataFrameGr... |
876cf418c53543bd7a7280e7d5879ad6f82dee07855b08ac6cb86fa4bd3d6801 | Python | 3,304 | 111 | import os
import csv
import glob
import random
import pandas as pd
def ID_shuffler(list1, list2):
temp = list(zip(list1, list2))
random.shuffle(temp)
res1, res2 = zip(*temp)
# res1 and res2 come out as tuples, and so must be converted to lists.
res1, res2 = list(res1), list(res... |
d02b55565017c604f6164d9252177ec0a5dc88007b3300b21a5ce08ad22a07ab | Python | 3,307 | 103 | import pytest
import pandas as pd
import pandas._testing as tm
from pandas.tseries.offsets import (
BaseOffset,
Day,
Hour,
MonthEnd,
)
class TestFreq:
@pytest.mark.parametrize("values", [["0 days", "2 days", "4 days"], []])
@pytest.mark.parametrize("freq", ["2D", Day(2), "48h", Hour(48)])
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.