sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
4737257890d159720a0534bea18ad6e93a028b4693bb03347d7276792aeccd31 | Python | 2,316 | 61 | import numpy as np
from sklearn.decomposition import PCA
class DynamicStatePCA():
"""
This is the state function used per default. For better performance, replace with your own state function
"""
def __init__(self,state_dim,data_length=360,bin_size=18):
"""
You can give the object param... |
38a0c2817673ad70e3b5ff74ca1ea7b43d13916398cd18b01445897db7cd652f | Python | 2,317 | 68 | import cedalion.typing as cdt
from cedalion.dataclasses.geometry import PointType
import matplotlib.pyplot as p
def plot_montage3D(
amp: cdt.NDTimeSeries,
geo3d: cdt.LabeledPoints,
landmarks: list[str] | None = None
):
"""Plots a 3D visualization of a montage.
Args:
amp: Time series dat... |
f3a259e9f770b6153f359bac4ddc1d65a809dc9bd7b34840ceb0004b31987838 | Python | 2,318 | 66 | import numpy as np
import pandas as pd
import pyBigWig
import errno
import os
from pathlib import Path
from typing import Tuple, Dict
def assure_folders(folders):
for folder in folders:
Path(folder).mkdir(parents=True, exist_ok=True)
print(f'Using folders at {[os.path.abspath(f) for f in folders]}')
... |
a48f663e5ee003d71d28c1aae93303ab2febebaed24fa9469e9fc071a1b6af74 | Python | 2,319 | 72 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Scientific Reports reproducibility runner.
Inputs (either option):
A) Raw ADNI file:
- ADNIMERGE.csv (place beside this folder or in data/raw/)
-> enables reconstruction of the n=411 baseline cohort tables (Table 1; Supp Table S2)
B) Analysis-ready file:
- da... |
8d18df31b2bae3c3ec0e272c9f7bc7a4067499ce7a5e034d8c0eeee20a85bf7b | Python | 2,320 | 85 | import numpy as np
import tifffile as tf
# import matplotlib.pyplot as plt
import cv2 as cv
import geopandas as gpd
from utils.contourtools import *
from utils.func import *
from utils.img2df import img2df as img2df
def get_program_parameters():
epilogue = """
create a dataframe of pixel sizes and z levels a... |
96098449fe1eb24f9822a294a8680821514752a735f55457865aafedd232d472 | Python | 2,321 | 93 | import itertools
import numpy as np
from lmfit import Parameters
from dp5.nmr_processing.proton.pearson7 import p7sim, p7plot
from dp5.nmr_processing.helper_functions import lorentzian
def simulate_regions(params, peak_regions, grouped_peaks, y_data, xppm):
sim_regions = np.empty(len(peak_regions), dtype=object... |
124ffb03b72d9bf581fb7d8d78f6ce0db4392c3319040982bc380f29b21439c8 | Python | 2,322 | 75 | import pytest
import pandas as pd
import pandas._testing as tm
@pytest.mark.parametrize(
"values, dtype",
[
([], "object"),
([1, 2, 3], "int64"),
([1.0, 2.0, 3.0], "float64"),
(["a", "b", "c"], "object"),
(["a", "b", "c"], "string"),
([1, 2, 3], "datetime64[ns]... |
89155c49f9beedab301cc479935826d09e305546f9cadfc6502cbd466f4d8caa | Python | 2,322 | 72 | """
Related Figures:
"""
import numpy as np
import scipy
import scipy.io
from scipy.fftpack import fft
def get_fft(sequence,sf,zeros_fill=None):
'''
频率图绘制
输入为一维numpy数组（时序），
采样频率（sampling frequency），
输出为原信号图和对应的信号频率图
'''
N=sequence.reshape(-1).shape[0]
if zeros_fill==None:
... |
09a49071de096461c1bee15bf64dc1463b1e17b01d3d31e5ae456c1bf7b10a41 | Python | 2,323 | 79 | '''
Related Figures:2a,4,s1
'''
import scipy
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.patches import Circle
def zplane(z, p, fig=None, ax=None):
if fig==None or ax==None:
fig, ax = plt.subplots(figsize=(4, 4),dpi=300)
circle = Circle(xy = (0.0, 0.0), radius = 1, alpha = 0.9, f... |
16bda4173d09e248529f193c1b972635e2620ceb0afa784c26edfea2773a1f23 | Python | 2,323 | 68 | import torch
from torch import nn
from braincog.base.encoder import encoder
from braincog.base.node import LIFNode
class CNNQnet(nn.Module):
def __init__(self, input_dim, output_dim):
super(CNNQnet, self).__init__()
self.cnn = nn.Sequential(
nn.Conv2d(in_channels=input_dim, o... |
d1daee586bd83030cd31f3685b86919fae28a609ca4009a74b98c23034079181 | Python | 2,323 | 71 | """ Binned dendritic events with respect to rhythmic bursts
Author: Drew B. Headley
"""
import numpy as np
import pandas as pd
from .load_dendevt_csv import load_dendevt_csv
from .load_spike_h5 import load_spike_h5
from .seg_dendevt import seg_dendevt
from .ser_seg_dendevt import ser_seg_dendevt
from .bin_rhym_dendevt... |
fee73a8986bda46f013ccce6b795b6293cb72b53d4aaf34353126d2c57ad4ee3 | Python | 2,323 | 63 | from __future__ import annotations
from typing import TYPE_CHECKING
from micromanager_gui import MicroManagerGUI
from micromanager_gui._menubar._menubar import DOCKWIDGETS, WIDGETS
from micromanager_gui._widgets._viewers import MDAViewer
if TYPE_CHECKING:
from pymmcore_plus import CMMCorePlus
from pytestqt.q... |
4de2d41335fea7183ec6819e58e3bae2f86638d02cc42a6b77bd2e522cdfff19 | Python | 2,325 | 81 | from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
from matplotlib import pyplot as plt
from .utils._checks import check_type
from .utils._docs import fill_doc
if TYPE_CHECKING:
import numpy as np
from numpy.typing import NDArray
@fill_doc
class Viewer:
"""Viewer of... |
1e7b62bde1bc7899b007cfc3de8e5c05746e18a9c2d1cbd6c60f743168758547 | Python | 2,327 | 85 | #
# This file is part of gunicorn released under the MIT license.
# See the NOTICE for more information.
import errno
import os
import tempfile
class Pidfile:
"""\
Manage a PID file. If a specific name is provided
it and '"%s.oldpid" % name' will be used. Otherwise
we create a temp file using os.mkst... |
591e62060648e92a18d517fc5fc3786bd53c46d3f5e2e167224c0bd7f0eb6db7 | Python | 2,327 | 43 | #This code contrains portions originating from neka-nat and is licensed under the MIT License. See: https://github.com/neka-nat/distributed_rl
#Code, Functions and structures were adopted from the original repository. Modified code is marked with [+].
import argparse
import gym
import torch
import visdom
from distri... |
9c47b6af31dc66992b354039836b86dde86d0a96da1c5a4372095777146f392c | Python | 2,327 | 77 | """
Script to run a short training session of reversal learning task from O'Doherty lab
Imports from config.py, initPract.py, runBandit.py
Adapted for IBC by:
Himanshu Aggarwal
himanshu.aggarwal@inria.fr
January 2021
"""
import os
import sys
from psychopy import visual, gui, data, core, event, logging, info
from psyc... |
c517fb1308339e61eeb1c90141c70cbc4c71a1d9c5d700b1cc17ab1c134f34a9 | Python | 2,328 | 82 |
# This code is written for readability rather than efficiency.
#
# - It is aimed to give a set of logical steps explaining how to run the analysis
# in the manner we ran it for this study.
#
import pandas as pd
import numpy as np
from scipy.spatial.distance import cdist
# Load data
df = pd.read_csv("your_file.c... |
30a44b145ce04da6ac0eec5e4ae94616c169205ee980eaf9dc6368b850e374c5 | Python | 2,329 | 74 | """contains code for the generation of legacy class bins and calculating
distances between all records in a given bin"""
# TODO: duplicate code with a lot of other edge generation
# from python
import logging
# from dependencies
import tqdm
# from other modules
import big_scape.data as bs_data
import big_scape.gen... |
90961f24ff7ce32dcc305035b74b5f07d668d1f6d6b81b096abb0379dad5868b | Python | 2,330 | 63 | from fenics import *
import numpy as np
from biotbiot.utils import load_data, load_mesh, meshFunction_to_DG, update_material_params
import sys
from biotbiot.utils import von_mises_projector
import yaml
if __name__ == '__main__':
sim_name = sys.argv[1]
mesh_name = sys.argv[2]
with open(f"config_files/{mes... |
c890552626b5f0bfdf2db34c3fe2e2ff7671af44f9c44d0f224101c2c1695dda | Python | 2,330 | 98 | #!/usr/bin/env python3
import pandas as pd
import numpy as np
import os.path as osp
import re
import datetime
from scipy.io import mmread
import argparse as arp
tag = str(datetime.datetime.now())
tag = re.sub('-| |:|\\.','',tag)
prs = arp.ArgumentParser()
prs.add_argument('-cp','--count_paths',
t... |
641ee7aea3d91f18c14b80e96db9fd1f4828a61d8de3200f4a7dce1f5e9da05b | Python | 2,331 | 67 | import matplotlib.pyplot as plt
import os
import random
import numpy as np
import torch
def seed_all(seed_val):
random.seed(seed_val)
os.environ["PYTHONHASHSEED"] = str(seed_val)
np.random.default_rng(seed_val)
torch.manual_seed(seed_val)
if torch.cuda.is_available():
... |
eae9c5b85f52ea11b91432438e2a9b2a0deb2fc22dcc9407c18f6f31d8eee3ed | Python | 2,331 | 75 | """
Tests for subclasses of NDArrayBackedExtensionArray
"""
import numpy as np
from pandas import (
CategoricalIndex,
date_range,
)
from pandas.core.arrays import (
Categorical,
DatetimeArray,
NumpyExtensionArray,
TimedeltaArray,
)
class TestEmpty:
def test_empty_categorical(self):
... |
bb985285dbe35dc69469a676c0f8f7875bc23858593a4ae7b495f046e49781b7 | Python | 2,334 | 59 | # License: GNU Affero General Public License v3 or later
# A copy of GNU AGPL v3 should have been included in this software package in LICENSE.txt.
""" The classification section of the smCOG module. Categorises gene function
according to a curated set of HMM profiles.
"""
from typing import Dict, List
from anti... |
53b0528e5b149e33fb98d81e1bcd5833300e417c6960df0e957f6270f7ddfc69 | Python | 2,336 | 64 | import csv
from pathlib import Path
from typing import Tuple
import numpy as np
from app.dataflow.qqueue import QQueue
from app.process.queue_process import QueueProcess
import logging
from util.trace import Trace
logger = logging.getLogger("grimace_box."+__name__)
class GrimaceResultWriter(QueueProcess):
@T... |
5e69e673904dc9a14595c30784f2335dfd7a1135c57d6f06e2122e957d8bb131 | Python | 2,336 | 76 | import glob
import os
import hydra
import lightning as L
import torch_geometric.loader as geom_loader
from lightning.pytorch.callbacks import ModelCheckpoint
from models import AMRNodeDualGNN
from utils import create_graph_dataset
@hydra.main(version_base=None, config_path="../conf", config_name="config")
def main(... |
d2a7301bc62675c70fdf1a3a1a3ce14c554f0fc7a563529de8bf97a8c2b6cee2 | Python | 2,336 | 92 | import pandas as pd
import pytest
from arcos4py.tools import estimate_eps
@pytest.fixture
def test_data():
data = {'t': [1, 1, 2, 2, 3, 3], 'x': [0, 1, 2, 3, 4, 5], 'y': [1, 2, 3, 4, 5, 6]}
return pd.DataFrame(data)
def test_estimate_eps(test_data):
# Test kneepoint method
eps = estimate_eps(
... |
6a6b189812601640416caf67d0a8485fd0719d9e7f9b85d4c54fd1beae464a9f | Python | 2,337 | 58 | import os
import shutil
from collections import defaultdict
from tqdm import tqdm
def organize_and_check_dataset(source_dir):
# 获取所有文件
files = os.listdir(source_dir)
# 用字典存储每个受试者的模态文件
subject_files = defaultdict(dict)
# 解析文件名并按受试者分组
print("正在分析文件...")
for file in fil... |
922979379d648614227d5f5acfec768a332bdf01ad75d2ab539a006ebd1bd61b | Python | 2,339 | 81 | """
Tests that work on both the Python and C engines but do not have a
specific classification into the other test modules.
"""
from io import StringIO
import pytest
import pandas._testing as tm
depr_msg = "The 'verbose' keyword in pd.read_csv is deprecated"
def test_verbose_read(all_parsers, capsys):
parser =... |
ff5a2acfe18ffdf161ae100539692ca0a7ed0cfc8e667e49d1cac1ba6169eb38 | Python | 2,339 | 67 | import numpy as np
import torch
from ase.units import Bohr, Hartree, mol, kcal
from torch_geometric.data import Data, InMemoryDataset
from tqdm import trange
from torch_geometric.data import DataLoader
class Chignolin(InMemoryDataset):
self_energies = {
1: -0.496665677271,
6: -37.8289474402,
... |
26dffdf1e4bb0718f4ed942950813d3f78c42918eb7ad8621794c1896c73e01a | Python | 2,340 | 73 | from snakemake.script import snakemake
import pandas as pd
import numpy as np
from sklearn.metrics import mean_squared_error, mean_absolute_error
ap_templates = pd.read_pickle(snakemake.input.ap_templates)
track_of_interest = snakemake.params.track_of_interest
# compute similarity between spike templates:
# compares... |
cda150dc68c36af36552c5117f4689c30cee737aa0994ca872c6ca5d2a5aa438 | Python | 2,342 | 82 | """
Vectorizing function execution, a lot of functions in YASS need to be executed
on different inputs over and over again, to simplify that workflow, some
utility functions are provided. Implementation is naive now (for loop) but
parallel execution will be implemented soon
"""
from copy import copy
from functools impo... |
f90fe8ece926893d729656fcc5f648c9623bf0cc5f87a451ffd705850c2654e4 | Python | 2,342 | 66 | #!/usr/bin/env python3
"""Fast ROCm/RCCL pre-flight health check for distributed CI shards.
Some gfx950 runner pods come up with a container that cannot read part of the
KFD/HSA topology -- RCCL fails every collective init with
"ncclUnhandledCudaError: Call to CUDA function failed / Could not read node #N"
(N is a fix... |
94a2c30ea652754eece8fc876ebcb091a0899cc2784ca4a9851aa69e8ec171b5 | Python | 2,344 | 67 | import numpy as np
import pytest
from pandas.core.dtypes.dtypes import PeriodDtype
import pandas as pd
import pandas._testing as tm
from pandas.core.arrays import period_array
@pytest.mark.parametrize("dtype", [int, np.int32, np.int64, "uint32", "uint64"])
def test_astype_int(dtype):
# We choose to ignore the s... |
1cea96495bbcd0f63ecda72b80c7f33c5d173ea102db804d4b0e8b9afc37d958 | Python | 2,346 | 76 | """
Tests which scan for certain occurrences in the code, they may not find
all of these occurrences but should catch almost all.
"""
import pytest
from pathlib import Path
import ast
import tokenize
import numpy
class ParseCall(ast.NodeVisitor):
def __init__(self):
self.ls = []
def visit_Attribute(s... |
8976fe49b7a3e0c05f07ffdc4777fddcb1993e45ee812e93012d27a9dadfcb53 | Python | 2,346 | 56 | from stimulus_generation import stimulus_generator, multiband_generator
data_path = 'Path/to/your/data' # update this to the path where your speech signals are
books = ['Polarnacht_female', 'Polarnacht_male', 'Darum_female', 'Darum_male'] # folder names that contain .wav files
harms_male = [[6, 15], [8, 18]] # [n1, n2... |
ca0e8476035ace56797315893538409f5051092b0b6e21ab395cc3c742446280 | Python | 2,346 | 55 | from pathlib import Path
import numpy as np
import torch
import argus
from src.indexes import IndexesGenerator
from src.inputs import get_inputs_processor
from src.argus_models import MouseModel
from src import constants
def get_blend_weights(name: str, size: int):
if name == "ones":
return np.ones(siz... |
80838bcbca2b6ad7f96bc71a230120f81aba6debd31edf2a5b772f7b536878c1 | Python | 2,348 | 82 | import pandas
class FeatureDataset(object):
"""
Dataset of protein mutations and associated structural- and chemical-features for simple machine learning.
Args:
dataframe (pandas.DataFrame)
protein (str, optional): protein name
gene (str, optional): gene name
species (str,... |
578b53dae336ff5b42b337758ca4b2f18da5f62047360e0c40906716c95ccbb1 | Python | 2,349 | 72 | """
Challenge Suite Problem 12: variational circuit to MPS overlap optimization.
The solution contracts a DMRG-MPS target bra directly with a trainable circuit
ket and differentiates the scalar overlap loss with respect to circuit angles.
"""
import numpy as np
import optax
import tensorcircuit as tc
K = tc.set_bac... |
eb19f39984a29bfca680ec30b5f24200191dacaf6180f4890f5351cabd3691d2 | Python | 2,350 | 74 | import unittest
from kernprof import ContextualProfile
def f(x):
""" A function. """
y = x + 10
return y
def g(x):
""" A generator. """
y = yield x + 10
yield y + 20
class TestKernprof(unittest.TestCase):
def test_enable_disable(self):
profile = ContextualProfile()
se... |
4e61cdb02c71be9f8a0cb0f949a4e6784b96243cd44b9d44834e2e4967adf4f8 | Python | 2,351 | 69 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
@pytest.mark.parametrize(
"to_concat_dtypes, result_dtype",
[
(["Int64", "Int64"], "Int64"),
(["UInt64", "UInt64"], "UInt64"),
(["Int8", "Int8"], "Int8"),
(["Int8", "Int16"], "Int16"),
([... |
629e976f62f462db5b862a6238cdd17012711cbd0e4e601c5022bcee5e5ff3f5 | Python | 2,351 | 70 | import os
import numpy as np
import pandas as pd
import torch
from torch.utils.data import Dataset, DataLoader
from sklearn.preprocessing import StandardScaler
import warnings
warnings.filterwarnings('ignore')
class Dataset_PEMS(Dataset):
def __init__(self, root_path, flag='train', size=None, scale=True):
... |
4fd07f56b75c16a28b1f6eb8265af15f0f8f5c25089a6dd5eade2f501d41673a | Python | 2,352 | 77 | """Frequency-related signal processing methods."""
import numpy as np
import scipy.signal
import xarray as xr
import cedalion.typing as cdt
from cedalion import Quantity, units
from cedalion.validators import check_dimensionality
import cedalion.dataclasses as cdc
@cdc.validate_schemas
def sampling_rate(timeseries: ... |
5f8a75a584f0f9d8fa3ad17ae05d4fcd13a4f9eed541fc09d65b7a94aea14aeb | Python | 2,352 | 53 | import logging
import torch
def init_edge_rot_mat(edge_distance_vec):
edge_vec_0 = edge_distance_vec
edge_vec_0_distance = torch.sqrt(torch.sum(edge_vec_0**2, dim=1))
# Make sure the atoms are far enough apart
# assert torch.min(edge_vec_0_distance) < 0.0001
if torch.min(edge_vec_0_di... |
3128e8e54eca2eeaae82712d5110bcce7a65748dfe70b21f5d094884dbd02c8e | Python | 2,354 | 73 | import pytest
from pandas import (
Interval,
Timedelta,
Timestamp,
)
class TestContains:
def test_contains(self):
interval = Interval(0, 1)
assert 0.5 in interval
assert 1 in interval
assert 0 not in interval
interval_both = Interval(0, 1, "both")
asse... |
67afa178adf1d395169294ae5680b2ce38dc5b3203d8a137e6a97ed495a56cac | Python | 2,357 | 51 | from pathlib import Path
from typing import Optional, List
import typer
from rich.console import Console
from .align_tilt_series import align_single_tilt_series
from .._cli import cli
from .._job_utils import write_global_output
from ..._metadata_models.relion.tilt_series_set import RlnTiltSeriesSet
from ..._utils.re... |
161da3e8e6cf85b29963b3bab3d748be22fe58477170b9299728b32aafcebfa6 | Python | 2,358 | 86 | import torch
from torch_geometric.data import Batch, Data
from torch_geometric.loader import DataLoader
from graphs import graph2dataset
from utils import set_seed
def collate_graphs(samples):
samples = [s for s in samples
if s is not None and hasattr(s, 'y')]
if len(samples) == 0:
... |
37b793e58181ef2b41507029e1056460536573078f83096930136fe5bfd7044c | Python | 2,358 | 72 | # -*- coding: utf-8 -*-
"""
Created on Thu Apr 17 15:12:02 2025
@author: 24233
"""
import numpy as np
import scipy.signal as signal
from scipy.io import savemat
from array import array
def ESA(raw_signal):
b, a = signal.butter(1, 300, btype='highpass',fs=30000)
filted_signal_1 = signal.lfilter(b, a, raw_si... |
01d805154c998f0f0ce275ef8750f5ddcc5463c2264b94adf6338b86f57da188 | Python | 2,359 | 79 | """
helper functions for conversions
"""
from typing import Any, Tuple, List
import numpy as np
from .. import gates
Tensor = Any
def get_ps(qo: Any, n: int) -> Tuple[Tensor, Tensor]:
"""
Get Pauli string array and weights array for a qubit Hamiltonian
as a sum of Pauli strings defined in openfermion ... |
88c000ed68a56f5a1f83562ea0b05e831a8f30f0cb359bc3af18916b0514baea | Python | 2,359 | 80 | # YOLOv5 🚀 by Ultralytics, GPL-3.0 license
"""
utils/initialization
"""
import contextlib
import platform
import threading
def emojis(str=''):
# Return platform-dependent emoji-safe version of string
return str.encode().decode('ascii', 'ignore') if platform.system() == 'Windows' else str
cl... |
cda060a5f3cd466c551b776850895b6488b207df7432c5e2c0369bad28fd1e74 | Python | 2,360 | 62 | """
ISO_C_BINDING maps for f2py2e.
Only required declarations/macros/functions will be used.
Copyright 1999 -- 2011 Pearu Peterson all rights reserved.
Copyright 2011 -- present NumPy Developers.
Permission to use, modify, and distribute this software is given under the
terms of the NumPy License.
NO WARRANTY IS EXPR... |
d194de3084c7acb5c62cee4129f6671e16353f70c5090877e78fb1f7dffaa15f | Python | 2,360 | 87 | """
A simple script to benchmark the approximation power of the MPS simulator.
"""
import tensorcircuit as tc
tc.set_backend("tensorflow")
tc.set_dtype("complex128")
def tfi_energy(c, n, j=1.0, h=-1.0):
e = 0.0
for i in range(n):
e += h * c.expectation((tc.gates.x(), [i]))
for i in range(n - 1):... |
5c757472a254923aea151e22e962a3a333b16ab83107858d1fbe92a6f29688da | Python | 2,362 | 37 | r"""
This module is a collection of builder functions used during training and inference for building Python object from configuration files
"""
import pkg_resources
from itertools import product
import numpy as np
DEFAULT_PRETRAINED_MODELS = ['HCT116_RNA002', 'arabidopsis_RNA002', 'HEK293T_RNA004']
DEFAULT_PRETRAINE... |
94799c114cbd891c1e52ece51b56d6f4fb5e53e09db7a17d64b7cc8ac3671e7b | Python | 2,365 | 63 | import numpy as np
import torch
from ase.units import C, _eps0, kJ, mol, nm, pi
from torch_scatter import scatter_add
from AIMD.protein import Protein
class MMNonBondedCalculator:
r"""
MMNonBondedCalculator is a non-bonded calculator based on MM calculations.
"""
def __init__(self, device="cpu") -> ... |
59de1b42e6d9752cbaf8fcab45036e307b67d959258caf6e3d93d596ed9c9b1d | Python | 2,367 | 91 | import sys
from typing import TYPE_CHECKING, Optional, Union, Literal
from .jupyter import JupyterMixin
from .segment import Segment
from .style import Style
from ._emoji_codes import EMOJI
from ._emoji_replace import _emoji_replace
if TYPE_CHECKING:
from .console import Console, ConsoleOptions, RenderResult
E... |
b06bb95ccfbf54236987225c639542a100a6cb9320b4bebf8439eca9fda3feba | Python | 2,367 | 74 | import sys
import subprocess
import textwrap
from importlib import reload
import pickle
import pytest
import numpy.exceptions as ex
from numpy.testing import (
assert_raises,
assert_warns,
assert_,
assert_equal,
IS_WASM,
)
def test_numpy_reloading():
# gh-7844. Also check that relevant globa... |
7d37646d969c2baaaeb5293ac2dac55499d95db13cb7c33246e40f239cb9ba12 | Python | 2,368 | 58 | import pandas as pd
import numpy as np
import pytest
import os
import shutil
from m6anet.utils.dataprep_utils import parallel_index, parallel_preprocess_tx
def test_parallel_index(dataprep_args, tmp_path, eventalign_index):
eventalign_filepath = dataprep_args['eventalign']
chunk_size = dataprep_args['chunk_si... |
7ff6e06f22ac41cf8129dac84e90db5e172c0385fbf2984962213e17210f8ad1 | Python | 2,372 | 77 | import ctypes
import os
import sys
from pathlib import Path
def get_gomp_thread():
"""
Retrieves the maximum number of OpenMP threads after loading the `libgomp.so.1` library
and the `libtorch_cpu.so` library. It then queries the
maximum number of threads available for OpenMP parallel regions using th... |
cf383040621dd8ff115208a64ac9bbb8c0986fad713de9eb3ff37491c654f31e | Python | 2,374 | 80 | import pytest
import numpy as np
from numpy.testing import assert_raises_regex
import numpy.lib._utils_impl as _utils_impl
from io import StringIO
def test_assert_raises_regex_context_manager():
with assert_raises_regex(ValueError, 'no deprecation warning'):
raise ValueError('no deprecation warning')
... |
b15d1b1296fe668b3d77c0b56c34114fdb835172b83df62bf8c4518064c3238c | Python | 2,375 | 79 | import numpy as np
from rdkit import Chem
import os
import sys
import tempfile
import shutil
from torch_geometric.data import Batch, Data, Dataset # , InMemoryDataset
from torch.utils.data import DataLoader
import logging
import warnings
import pickle
from ase.db import connect
import torch
from tqdm import tqdm
impor... |
d4c81712d7ef20ffa1a679edb32e22c2909630a3eced1b670ff2125f518e371c | Python | 2,375 | 80 | """
process.run tests, checking that the pipeline finishes without errors for
some configurations
"""
import os
import yass
from yass import preprocess
from yass import detect
from yass import cluster
def test_cluster_nnet(path_to_config, make_tmp_folder):
yass.set_config(path_to_config, make_tmp_folder)
(s... |
934b9f743a1305814be2512c42c2037175f5a2dcfcaa4df26f41e65e28518c90 | Python | 2,377 | 79 | """
Script to run IBC implementation of reversal learning task from O'Doherty lab.
Imports from config.py, initTask.py, runBandit.py
Adapted for IBC by:
Himanshu Aggarwal
himanshu.aggarwal@inria.fr
January 2021
"""
import os
from psychopy import visual, gui, data, core, event, logging, info
from psychopy.constants im... |
c34f10325cc79135da83daad98afbb7f205716663db9455c6c128ad3cee96ce9 | Python | 2,377 | 69 | # Copyright (c) 2023 ETH Zurich.
# All rights reserved.
#
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
#
# main author: Nils Blach
from __future__ import annotations
from typing import List
from escargot.operations.operations import Operation... |
f2c33758c4ee6e2d5c05bd9cfe53e45a937427c74c02aae029160b2e2d5d0952 | Python | 2,377 | 79 | from __future__ import annotations
import logging
import sys
import typing as t
from werkzeug.local import LocalProxy
from .globals import request
if t.TYPE_CHECKING: # pragma: no cover
from .sansio.app import App
@LocalProxy
def wsgi_errors_stream() -> t.TextIO:
"""Find the most appropriate error stream... |
cf3ed47002069ccdef050ad326cc9bdd52903eb3ee3e17ff3ccf72bff46c01cc | Python | 2,379 | 80 | from math import comb
import pandas as pd
import sys
import numpy as np
sys.path.append("../")
language = None # pd.read_csv("somePath/LANGUAGE_run1_TAB.txt", sep='\t')
procedures = language["Procedure[Block]"].to_numpy()
responseOnsets = language["ResponsePeriod.OnsetTime"].to_numpy()
presentMathStart = language["P... |
9dae20aa18463a87ddf210b7c36111289336e53abd3b7b7f7de20546fa782088 | Python | 2,381 | 73 | # -*- coding: utf-8 -*-
"""
Wrapper functions for directly calling R functions in Python.
This is kept seperate from stats_utils because it requires an R installtion
to even load; without it, Python will crash. To install R: download it from
https://cran.r-project.org. After installation, make sure R is in you... |
4dec75e2205047b5fffd06c64bfb039aeaedff230c5b45c4b80ccce635da81dc | Python | 2,382 | 87 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Aug 17 16:54:12 2019
@author: wanxiang.shen@u.nus.edu
@usecase: calculate varies distances
"""
from molmap.utils.distances import named_distances
from molmap.utils.multiproc import MultiProcessUnorderedBarRun
import numpy as np
from tqdm import tqdm
... |
34a1f1a37bddd79b5ea3c9214c303aed66834beeef5a1894e6fd7c6a64cb88b6 | Python | 2,383 | 75 | """contains code for the generation of antiSMASH class bins and calculating
distances between all records in a given bin"""
# TODO: duplicate code with a lot of other edge generation
# from python
import logging
# from dependencies
import tqdm
# from other modules
import big_scape.data as bs_data
import big_scape.... |
c6278c4dbb40439808a75b888f206cd112418af2155b154b73f08a2f2002fce2 | Python | 2,383 | 51 | def remove_quotes(s):
if s and s[0] in ("'", '"') and s[0] == s[-1]:
return s[1:-1]
return s
def process_knowledge_ids(knowledge_ids):
knowledge_ids = knowledge_ids[knowledge_ids.find("(")+1:knowledge_ids.find(")")]
knowledge_ids = [remove_quotes(elem.strip()) for elem in knowledge_ids.split(",... |
c9a774121664a0f51a3aae79f092b82c61c129ca63d949893c29f06c4e682d97 | Python | 2,383 | 92 | import os
import sys
thisfile = os.path.abspath(__file__)
modulepath = os.path.dirname(os.path.dirname(thisfile))
sys.path.insert(0, modulepath)
import numpy as np
import tensornetwork as tn
from tensorcircuit import simplify
def test_infer_shape():
a = tn.Node(np.ones([2, 3, 5]))
b = tn.Node(np.ones([3, 5,... |
92b4f9c6acf886674392c21f29578608663b8ec88e5da47fb0c51910b550c1d0 | Python | 2,384 | 66 | from __future__ import annotations
from typing import cast
from pymmcore_plus import CMMCorePlus, DeviceType
from pymmcore_widgets import ShuttersWidget
from qtpy.QtCore import Qt
from qtpy.QtWidgets import QToolBar, QWidget, QWidgetAction
class _ShuttersToolbar(QToolBar):
"""A QToolBar for the loased Shutters.... |
ab1a3f8bfb45a7c0558005ad06d12593fe250bb51b77bd83376c7aa2ac2f2d6f | Python | 2,384 | 65 | import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import ImageGrid
import sys
import numpy as np
import k3d
from matplotlib.colors import LinearSegmentedColormap
import yaml
if __name__ == "__main__":
sim_name = sys.argv[1]
mesh_name = sys.argv[2]
plot_name = sys.argv[3]
if len(sys.argv) ==5... |
c21278c6a3deb753df7d539c47a5bfd8d17cc91e0b2c3877a592eb2a4974461e | Python | 2,384 | 75 | from ._backend import Backend
from numpy.distutils.core import setup, Extension
from numpy.distutils.system_info import get_info
from numpy.distutils.misc_util import dict_append
from numpy.exceptions import VisibleDeprecationWarning
import os
import sys
import shutil
import warnings
class DistutilsBackend(Backend):... |
675896359e9d7727236cbe721ce2520155566b21135e173f477c992276ef7771 | Python | 2,387 | 50 | # An old version of OpenAI Gym's multi_discrete.py. (Was getting affected by Gym updates)
# (https://github.com/openai/gym/blob/1fb81d4e3fb780ccf77fec731287ba07da35eb84/gym/spaces/multi_discrete.py)
import numpy as np
import gym
class MultiDiscrete(gym.Space):
"""
- The multi-discrete action space consists ... |
87f314678e466d990ff2deeeaa4b84da95fe3094fb8ddc3f9b1b97f6ba2e3fbb | Python | 2,388 | 80 | import torch.nn as nn
from .interaction_block import *
from .residual_stack import *
"""
Basic building block of the neural network which refines atomic features in an iterative way
"""
class ModularBlock(nn.Module):
def __init__(
self,
order,
num_features,
num_basis_functions,
... |
2aedb42d8596d61af2707f20b2517ca0dc1732ff3c4666890bbc746b918f6d8c | Python | 2,389 | 81 | """
Tests for DataFrame cumulative operations
See also
--------
tests.series.test_cumulative
"""
import numpy as np
import pytest
from pandas import (
DataFrame,
Series,
)
import pandas._testing as tm
class TestDataFrameCumulativeOps:
# ------------------------------------------------------------------... |
24dc8bb085a2a06d2c330f52760c6f0c68038f22c51306fc328644bbf921bd98 | Python | 2,390 | 87 | from typing import TYPE_CHECKING, Any, List, Optional, Sequence
from .base import IMCFileTreeItem, ModelBase
if TYPE_CHECKING:
from .channel import ChannelModel
from .imc_file import IMCFileModel
class IMCFileAcquisitionModel(ModelBase, IMCFileTreeItem):
imc_file_tree_is_checkable = True
def __init... |
09c00a0ec02841196b974775731c44c48c9eef0f0c6c238a09909f4703c40cec | Python | 2,391 | 78 | # coding: utf-8
from collections import defaultdict
import torch
from torch.optim import Optimizer
class Lookahead(Optimizer):
def __init__(self, optimizer, k=5, alpha=0.5):
self.optimizer = optimizer
self.k = k
self.alpha = alpha
self.param_groups = self.optimizer.param_groups
... |
322a98cc2207bcd6cc1fe2dd4582effb84f410803b8432ade462d1d084532dd2 | Python | 2,392 | 75 | import logging
import os
import tempfile
import shutil
import json
from subprocess import check_call, check_output
from tarfile import TarFile
from dateutil.zoneinfo import METADATA_FN, ZONEFILENAME
def rebuild(filename, tag=None, format="gz", zonegroups=[], metadata=None):
"""Rebuild the internal timezone info ... |
7e6faa36f586b66cacf63fa19d9af803abe46b7b407231b42e6df2c7cdaeb9cc | Python | 2,392 | 80 | """Measure entrainment of dendritic events by rhythmic signal
Author: Drew B. Headley
"""
import numpy as np
from .bin_serser import bin_serser
from .ppc import ppc2
def ent_rhym_dendevt(seg_df, rhym_ser):
"""
For each segment's dendritic event time series measure it entrainment
with PPC to a rhythmic seri... |
136a88f8860ed87209cacfee89a6400846888c435783ddfa4bdd99d4d5bbafce | Python | 2,396 | 81 | """ Creates binary time series of dendritic event occurrences
Author: Drew B. Headley
"""
import numpy as np
import sys
sys.path.append(".") # have to do this for relative imports to work consistently
from .ser_ss import ser_ss
from .ser_pt import ser_pt
def ser_seg_dendevt(seg_df, **kwargs):
"""
Takes a d... |
91baa83d067fada9868376a6ce0a02664eedf5d7d7e4ba15fe3787042429ce18 | Python | 2,396 | 64 | # License: GNU Affero General Public License v3 or later
# A copy of GNU AGPL v3 should have been included in this software package in LICENSE.txt.
"""Map Pfam domains to Gene Ontology terms"""
from typing import Any, Dict, List, Optional
from antismash.common import path
from antismash.common.secmet import Record
f... |
fb9b988435020f9e73bf923767c6951440737428525ad6cf3523f4e67a941220 | Python | 2,398 | 71 | from pandas import (
TimedeltaIndex,
timedelta_range,
)
import pandas._testing as tm
class TestTimedeltaIndexDelete:
def test_delete(self):
idx = timedelta_range(start="1 Days", periods=5, freq="D", name="idx")
# preserve freq
expected_0 = timedelta_range(start="2 Days", periods=4... |
088889583719f11ccb3e6055237c5aaa79f2f783eb87ee412cfe8b386aba77bf | Python | 2,399 | 55 |
import torch
from torch import nn
from braincog.base.node.node import IFNode
from braincog.base.learningrule.STDP import STDP,MutliInputSTDP
from braincog.base.connection.CustomLinear import CustomLinear
from collections import deque
from random import randint
class RSNN(nn.Module):
def __init__(s... |
5972e8ae29ab0be385c7b6d9a24724580919105b1dcd26331a1192a4a3ebc390 | Python | 2,400 | 73 | import numpy as np
import os
import parmap
import scipy.signal
def duplicate_l2(fname_templates, fname_spike_train, neigh_channels,
save_dir, n_spikes_big=100, min_ptp=2, units_in=None):
# output folder
if not os.path.exists(save_dir):
os.makedirs(save_dir)
templates = np.load(fn... |
fb45bf6bfba0269befa53bcaac1b84554df00d43176bf3728ffe1888a28b36c1 | Python | 2,401 | 48 | #!/usr/bin/env python3
"""R0 scaffold — selective access to Zenodo 17726565 (77 GB single archive).
Status: SCAFFOLD. R0 has NOT been run; nothing here produces citable output yet.
Strategy: the archive is one zip; we read its END-OF-CENTRAL-DIRECTORY via HTTP range
requests to enumerate members WITHOUT downloading 77... |
8e7a103b79ebc592d0dbc71621e1f2eab015319271e966fe2b08aa7cfcf4c33c | Python | 2,402 | 71 | from asv_runner.benchmarks.mark import skip_benchmark_if
from xgboost import XGBClassifier
from shap import Explanation
from shap.datasets import adult, imagenet50
from shap.explainers import PartitionExplainer
from shap.maskers import Image
try:
from tensorflow.keras.applications.resnet50 import ResNet50, prepro... |
cf14b8214fb22230c05301463101ba368e88b8529b380d99553b24697b538989 | Python | 2,402 | 73 | # %%
import pandas as pd
import numpy as np
from utils import index_structure
from plot_utils import divergent_green_orange
from surfplot import Plot
from brainspace.datasets import load_parcellation
from neuromaps.datasets import fetch_fslr
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
aeb24ef82e476a034a268e78da1df6781e53396543c62ac9bf5bb93d726487f2 | Python | 2,404 | 84 | import numpy as np
import pytest
from pandas import (
DataFrame,
MultiIndex,
Series,
concat,
)
import pandas._testing as tm
@pytest.mark.parametrize(
"args, kwargs, increment",
[((), {}, 0), ((), {"a": 1}, 1), ((2, 3), {}, 32), ((1,), {"c": 2}, 201)],
)
def test_agg_args(args, kwargs, increme... |
f57a5eae4edae3205340aa3c7e09378026b64b026bdf4987d896183185a0b966 | Python | 2,405 | 96 | from copy import (
copy,
deepcopy,
)
import pytest
from pandas import MultiIndex
import pandas._testing as tm
def assert_multiindex_copied(copy, original):
# Levels should be (at least, shallow copied)
tm.assert_copy(copy.levels, original.levels)
tm.assert_almost_equal(copy.codes, original.codes... |
c15c3e120daa6f2b4dec7ec3da791633302e46ac5bf8dfda5589a84f1107463a | Python | 2,406 | 48 | #!/usr/bin/env python
import os
import argparse
import warnings
from tqdm import tqdm
parser = argparse.ArgumentParser(description='Process data from openmx output.')
parser.add_argument('--input_dir', type=str, default='/home/lihe/hdd/materials_data/MoS2/md_openmx/configuration/', help='Every folder under input_dir ... |
93ae904ccb627461544f37a5239bc9d283e7c12a9468c11088e22d09e2d28098 | Python | 2,408 | 81 | import scipy
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import scanpy as sc
import decoupler as dc
import statsmodels.api as sm
from statsmodels.stats.multitest import multipletests
from patsy import dmatrices
cell_type = snakemake.params.cell_type
sample_key = snakema... |
db3012520c41ee5f2db46d9f2a30a9223b6dfd343b8f8349d8bf7117373250f5 | Python | 2,408 | 79 | import numpy as np
from pandas.core.dtypes.cast import can_hold_element
def test_can_hold_element_range(any_int_numpy_dtype):
# GH#44261
dtype = np.dtype(any_int_numpy_dtype)
arr = np.array([], dtype=dtype)
rng = range(2, 127)
assert can_hold_element(arr, rng)
# negatives -> can't be held b... |
c452a341406c5ebb29888b833d71d4cba0492ec5131c1c4c7055f9ea6d607eaf | Python | 2,412 | 55 | # Tests for FreeSASA class in ExternalCode.py
import pandas
import numpy
import pytest
import sbmlcore
def test_freesasa_rnap():
# b = {'segid': ['A', 'A', 'A'], 'mutation': ['M1D','R2K', 'A3V']}
b = {'segid': ['A', 'A', 'A', 'B', 'C', 'C'], 'mutation': ['I3D','S4K', 'Q5V', 'R6D', 'S450F', 'D435F']}
df = pa... |
cc1f9242f272764b3bb50d32230acfe860f77d035249a3e2abbcf0e321794f8d | Python | 2,412 | 68 | import contextlib
import os
import re
import ssl
import typing
# candidates based on https://github.com/tiran/certifi-system-store by Christian Heimes
_CA_FILE_CANDIDATES = [
# Alpine, Arch, Fedora 34-42, OpenWRT, RHEL 9-10, BSD
"/etc/ssl/cert.pem",
# Fedora 43+, RHEL 11+
"/etc/pki/ca-trust/extracted/p... |
efda860fc7b5f12adeda91225dffe4d5978b22effca5eae1506332a7cc911672 | Python | 2,414 | 78 | import os, sys, re
import argparse
from torch import nn, tensor
from .utils_ML import LayerNorm
from model.XMolNet import XMolNet
def FindModel(directory):
# Regular expression to match model files
model_pattern = re.compile(r'model_(\d+)\.chk')
# List files in the directory and filter those that matc... |
e2fb69218a80659adb2988b77e73fb97f667e3662705b3f097cf9e35f64e1c7a | Python | 2,415 | 66 | import pytest
from numpy import array
from . import util
@pytest.mark.slow
class TestReturnComplex(util.F2PyTest):
def check_function(self, t, tname):
if tname in ["t0", "t8", "s0", "s8"]:
err = 1e-5
else:
err = 0.0
assert abs(t(234j) - 234.0j) <= err
asser... |
ec5527db2323cf92eba243c70d4fabc21fc0543407d12472ced5917fa981d77d | Python | 2,415 | 64 | # License: GNU Affero General Public License v3 or later
# A copy of GNU AGPL v3 should have been included in this software package in LICENSE.txt.
""" The general clusterblast, comparing clusters to other antismash-predicted
clusters.
"""
import os
from typing import Dict
from antismash.config import ConfigType... |
7ded0a8cb0caad9415216964a879f996a05f0cd0a69680fcdf22a95f96c4c384 | Python | 2,416 | 80 | # -*- coding: utf-8 -*-
"""
Created on Tue Jul 19 10:44:19 2022
@author: lindseyb
"""
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import odeint
import pandas as pd
from scipy import stats
import matplotlib
matplotlib.rcParams['pdf.fonttype'] = 42
matplotlib.rcParams['ps.fonttype'] = 42
ma... |
ab459e5b4973c6290f4d9cc460722a494024c909776763a5d0083e41187f193f | Python | 2,416 | 55 | import multiprocessing
import jax
import jax.numpy as jnp
import jax.scipy.stats as stats
import blackjax
import jax.random as random
import pickle
from MCMC.HMC_utils import inference_loop, inference_loop_multiple_chains
from utils.utils import PyTree
def get_MCMC(step_size,num_integration_steps, MCMC = 'HMC'):
... |
6e46b5a0e0f6514813e3d625b667adf21e8bed6c1524498771069c83df68dc66 | Python | 2,419 | 72 | #!/usr/bin/env python
# Relatively generic setup.py that should be easily tailorable to
# other python modules. It gets most of the parameters from the
# packaged module itself, so this file shouldn't have to be changed
# much.
import os,sys,distutils
from distutils.core import setup
# patch distutils if it can't c... |
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