sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
638fa883626291e16e395d2c564753b4751ca39ab9a0c2d259e76eb074bb1658 | Python | 2,648 | 67 | # Copyright 2018, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the f... |
ce34768d9babdb49fc7a01ef0eee5d7d99c94567db50e399bbe7284c820ad452 | Python | 2,648 | 69 | import unittest
import tempfile
import os
import shutil
from flask import Flask
from cellxgene_gateway import flask_util
from cellxgene_gateway.cache_entry import CacheEntry, CacheEntryStatus
from cellxgene_gateway.cache_key import CacheKey
from cellxgene_gateway.items.item import ItemType
from cellxgene_gateway.items... |
d0d2527a011dd0095800763e4478d77e92013e5160106d18761542230c8c6243 | Python | 2,648 | 82 | """Rung-4 summary facade (weightsfree memo D12 / face 2 / item 17).
A read-only facade may auto-select the exact structure-only option state
ONLY for an all-meta model plus an unambiguous input plan; it stamps the
SAME marker, admission record, and evidence envelope as the explicit power
path, with the auto-set visibl... |
0a77d05faa00cef04086c068cf9bc1635d2fb2e2d4fc456af4990fca652645cb | Python | 2,649 | 44 | from .activations import *
from .adaptive_avgmax_pool import \
adaptive_avgmax_pool2d, select_adaptive_pool2d, AdaptiveAvgMaxPool2d, SelectAdaptivePool2d
from .blur_pool import BlurPool2d
from .classifier import ClassifierHead, create_classifier
from .cond_conv2d import CondConv2d, get_condconv_initializer
from .co... |
77057e07652a7cdddd3d15dbc0de835185d0749c4681fe1b6545a5cb7c43977a | Python | 2,649 | 58 | """Implementation of StepAPICompatibility wrapper class for transforming envs between new and old step API."""
import gym
from gym.logger import deprecation
from gym.utils.step_api_compatibility import (
convert_to_done_step_api,
convert_to_terminated_truncated_step_api,
)
class StepAPICompatibility(gym.Wrapp... |
e1d1a8278b823ca54c5e01a41fcbe4001fe57da3ab07f0b50966f3abc4c65b11 | Python | 2,649 | 94 | import attr
from modular_splicing.utils.construct import construct
@attr.s
class ExperimentalSetting:
feature_map = attr.ib()
start_end = attr.ib()
feature_powers = attr.ib()
def query(self, probability_by_feature, combinator_spec):
"""
Produce a single probability from the probabili... |
8661d1094a5d7cb752ed10e446dab64bd88c8ce3ca9d165daeec908b5a8840c5 | Python | 2,650 | 89 | import numpy as np
import scanpy
from anndata import AnnData
from scipy.sparse import spmatrix
def log1p(
adata: AnnData | np.ndarray | spmatrix,
copy: bool = False,
chunked: bool = False,
chunk_size: int | None = None,
base: float | None = None,
) -> AnnData | None:
"""\
Wrap function of ... |
c0b0e29de5eb781c9e0d330928b27cc7cf46710a102056a4e88314b3e48aa6e6 | Python | 2,650 | 70 | """``tl.validate(scope="forward")`` settles ``False`` on a metadata-invariant failure (W051-HONESTY L9).
Before: stale-parent models returned ``False`` while the worker-thread escape
model RAISED ``MetadataInvariantError`` through the same door, so callers
branching on the documented bool missed the second failure cla... |
e60e01b39eb189913e71f70414e87228d0f7a09675d4ae31b60201e2585c6b76 | Python | 2,651 | 102 | """
Gregory Way 2018
PanCancer Classifier
scripts/compression.py
Perform a series of compression algorithms on the PanCanAtlas RNAseq data. The
compressed features (z) are input as features for gene alteration predictions.
Usage:
Run in command line
python scripts/compression.py
Output:
Compressed gene expr... |
bbd11e66047faf4741718012cc25a1efd81e9c613c6d212cfc79fa8593f41245 | Python | 2,653 | 84 | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
from torchvision import transforms
from easydict import EasyDict as edict
def padding(array, whole_dim):
# pad square array
array_size = array.shape[-1]
pad_size1 = (... |
f0052cb60060276fd3e5d2d48bdb420fa00ebf179c62c9ecb30f2acb8bad8562 | Python | 2,653 | 70 | from .constants import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, DEFAULT_CROP_PCT
def update_cfg(cfg, udict):
cfg.unfreeze()
cfg.update(udict)
cfg.freeze()
# pylint: disable=dangerous-default-value
def resolve_data_config(cfg, default_cfg={}, model=None, use_test_size=False):
default_cfg = default_... |
2328d6c69d06e626e4d87f55e5fe0ca17af1e6f9ecd7746a99cfde60820a0c59 | Python | 2,654 | 42 | import argparse
import os
import warnings
from scripts.slice_selection import train
from settings import CUDA_VISIBLE_DEVICES
os.environ['CUDA_VISIBLE_DEVICES'] = CUDA_VISIBLE_DEVICES
os.environ["TF_CPP_MIN_LOG_LEVEL"] = '3'
warnings.filterwarnings("ignore")
if __name__ == '__main__':
parser = argparse.Argu... |
ca40275e86a8bffece1e44d7397b5a184774d6b1d3ce1fb20b366e4a2299e75c | Python | 2,654 | 92 | """Screenshots for quick guide import ts (not working automatically)"""
import pathlib
import shutil
import sys
import tempfile
import matplotlib.pylab as plt
import numpy as np
import pandas
import seaborn as sns
from PyQt5 import QtCore
from PyQt5.QtWidgets import QApplication
from pyjibe.head.main import PyJibe
d... |
ec60ac58980c43dfc36711f862a6fcd59597873a7b93361567e7d31bbbfe10d6 | Python | 2,654 | 70 | """Download validation must remain active under optimized Python."""
import subprocess
import sys
import textwrap
import pytest
@pytest.mark.parametrize("optimized", [False, True], ids=["regular", "optimized"])
@pytest.mark.parametrize("existing_output", [False, True], ids=["invalid", "existing"])
def test_download... |
89b834a6bc3e9d42871a460f275ed459bc163fd72b405c9e26646b6c4527edc1 | Python | 2,655 | 93 | import functools
import numpy as np
import os
from ..psams import PSAM
from .data_directory import DATA_DIRECTORY
MOTIFS_DIRECTORY = os.path.join(DATA_DIRECTORY, "motifs")
SPLICE_MOTIFS_DIRECTORY = os.path.join(DATA_DIRECTORY, "splice_point_motifs")
@functools.lru_cache(None)
def read_rbns_motifs(
directory=MO... |
0089b5998c60c871c04004aed92baef22f9f51219f501609f950ecaa6d5ac8af | Python | 2,657 | 69 | import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import os
import seaborn as sns
from tracking.timeSeries import createMaskTimeSeries
from .PlotUtils import plotLeafTimeSeries
from .FimgHandling import normalizeImg
import gc
def create_time_series(tray,resul... |
f0728aef8eb033197f9e9f2d1cb074032c57c26910b948c3a1468734b7f7e1b0 | Python | 2,657 | 89 | """extract dynamic content
"""
import os.path
import json
import time
import shutil
from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from selenium.webdriver import Firefox as Browser
from selenium.webdriver.firefox.options import Options
#from selenium.webdriver.chrome.options import... |
0023d9068a0a4e4c998cbf724b5ed1b2397e6a2d26340e6106542df8c3f66f4c | Python | 2,658 | 100 | import torch
import os
import logging
from transformers import AutoTokenizer, AutoModelForMaskedLM, logging
from tf_bind_transformer.cache_utils import cache_fn, run_once
logging.set_verbosity_error()
def exists(val):
return val is not None
def map_values(fn, dictionary):
return {k: fn(v) for k, v in diction... |
95d7a0dfc102ca70ffcef13a1edf5d2d6bbcfc6aabfe96b4e184c265a3442d33 | Python | 2,659 | 112 | """Functions dealing with correlation.
This file is a part of BdPy.
"""
__all__ = ['corrcoef', 'corrmat']
import numpy as np
from numpy.matlib import repmat
def corrcoef(x: np.ndarray, y: np.ndarray, var: str = 'row') -> np.ndarray:
"""Return correlation coefficients between `x` and `y`.
Parameters
-... |
cb85348cbefa96a0defd4ca8e43ce10a11ce33f2737e9a9b5024b49371c1c1d8 | Python | 2,659 | 82 | import os
import numpy as np
import pickle as pkl
from os.path import join as pjoin
from scipy.spatial.distance import cdist
from magicbox.io.io import CiftiReader
from cxy_visual_dev.lib.predefine import proj_dir,\
get_rois, mmp_map_file, Hemi2stru, mmp_name2label
anal_dir = pjoin(proj_dir, 'analysis')
work_dir =... |
116b7e34fd97a975649dc940ebfd27ace4e52f8495fcd099839b2297229dc329 | Python | 2,660 | 78 | import logging
import sys
from .hpc import LsfWrapper, PbsWrapper, SgeWrapper, SlurmWrapper
logger = logging.getLogger(__name__)
def make_caper_run_command_for_hpc_submit():
"""Makes `caper run ...` command from `caper hpc submit` command by simply
replacing `caper hpc submit` with `caper run`.
This als... |
40313cfcfa692f392dadec42da709b2902779012edb3280b2c33d34ac73da728 | Python | 2,660 | 66 | import unittest
from unittest.mock import patch
from carbontracker.components.cpu.generic import GenericCPU
class TestGenericCPU(unittest.TestCase):
def setUp(self):
self.generic_cpu = GenericCPU(pids=[], devices_by_pid=False)
self.cpu_power_data = self.generic_cpu.load_cpu_power_data()
sel... |
894a7fc08946c706ed83c39d0ae7e5eeed6264d57665e324bfe826c0c2aac831 | Python | 2,660 | 157 | """
Cyclical color scales are appropriate for continuous data that has a natural cyclical \
structure, such as temporal data (hour of day, day of week, day of year, seasons) or
complex numbers or other phase data.
"""
from ._swatches import _swatches, _swatches_continuous, _swatches_cyclical
def swatches(template=No... |
29eb015218b3b0ab52476672d6b0c1fc17d5c49b1216b58b42b39d4c2d329ad0 | Python | 2,661 | 81 | import argparse
import textwrap
from promptsource.templates import TemplateCollection, INCLUDED_USERS
from promptsource.utils import get_dataset
parser = argparse.ArgumentParser(description="Process some integers.")
parser.add_argument("dataset_path", type=str, help="path to dataset name")
args = parser.parse_args(... |
882adb87b5eb633e0584a6e13327226578f734aae1c6e2e9d6746d2af08846be | Python | 2,661 | 60 | """
evoked_basic plugin - analysis algorithms to analyzed evoked recordings
The module can be imported independently of the base UI system.
SimplyFire - Customizable analysis of electrophysiology data
Copyright (C) 2022 Megumi Mori
This program comes with ABSOLUTELY NO WARRANTY
This program is free software: you can ... |
13dd37ddbb65db4b51bac795f59bdda7120072a8ceca8585a11731a7dbb3ca0b | Python | 2,662 | 79 | from __future__ import annotations
import pytest
from pytest_celery import CeleryBrokerCluster, CeleryTestSetup, RabbitMQTestBroker
from tenacity import retry, stop_after_attempt, wait_fixed
from celery import Celery
HEARTBEAT = 10
# gets the connection status from the rabbitmq side.
def list_connections(broker: R... |
35d252135aa2ffba477480868286d52222f9f3b2b57928f7e14c736c0265e23e | Python | 2,662 | 75 | """
Print every channel exposed by the Windows Energy Meter Interface (EMI), and
the power each of them reports, to diagnose CPU power measurements.
Usage:
python examples/emi_channels.py [duration_in_seconds]
"""
import sys
import time
from codecarbon.core import windows_emi
def main(duration: float = 5.0) ->... |
523d18b8bf9b9c2a0a09cae2be80f3407f65856fc9e2e7f1113c52b42b1ae701 | Python | 2,662 | 65 | from __future__ import division
import argparse, time, logging, os, math, tqdm, cv2
import numpy as np
import mxnet as mx
from mxnet import gluon, nd, image
from mxnet.gluon.data.vision import transforms
import matplotlib.pyplot as plt
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv import data
f... |
c4afab8f18214559c39d09836fef2b43eef2e36f3853792ee069e68bac7a3c89 | Python | 2,662 | 75 | # pylint: disable=keyword-arg-before-vararg
"""Mixup detection dataset wrapper."""
from __future__ import absolute_import
import numpy as np
import mxnet as mx
from mxnet.gluon.data import Dataset
class MixupDetection(Dataset):
"""Detection dataset wrapper that performs mixup for normal dataset.
Parameters
... |
bbc8cd6cb7cf3b356e3b3b5f1b40fd275a4e685b6f9b14ed42a3708a960ce239 | Python | 2,663 | 67 | from typing import Generator
import pandas as pd
from mirp.settings.feature_parameters import FeatureExtractionSettingsClass
from mirp._features.base_feature import Feature
from mirp._features.morph_3d_features import generate_morph_3d_features
from mirp._features.local_intensity_features import generate_local_intens... |
c0ddf8291c697c0549370d84cae68c3bc9aebda6e72957872d57a3b96b3dd433 | Python | 2,663 | 106 | """Trial scheduler class."""
import numpy as np
class BaseSchedule:
"""Base schedule.
Args:
n: int, number of conditions to schedule
"""
def __init__(self, n) -> None:
self.n = n
self.total_count = 0 # total count
self.count = 0 # count within a condition
s... |
d5393c21f248689fbc8d03d6f960115ce2b8adaba173306a735decb8c0530f7a | Python | 2,663 | 63 | # -*- coding: utf-8 -*-
"""
Created on Mon Feb 6 13:21:43 2023
@author: Caterina Brighi
"""
#%% Import functions
import os
import shutil
#%% Set Working directory
data_supradir = 'Path to data directory' #Set working directory
subjs_path = [ f.path for f in os.scandir(data_supradir) if f... |
2a193d088090a577832845ce58799ae5447226206d1aacb9b1239a992d717fb0 | Python | 2,664 | 81 | """Celery Application."""
from celery import _state
from celery._state import app_or_default, disable_trace, enable_trace, pop_current_task, push_current_task
from celery.local import Proxy
from .base import Celery
from .utils import AppPickler
__all__ = (
'Celery', 'AppPickler', 'app_or_default', 'default_app',
... |
89bb7aff6a736000f4ea64f0c04910b9735a2a191f3754897ea63fbc2a4f0df5 | Python | 2,664 | 68 | # -*- coding: utf-8 -*-
"""
Created on Mon Feb 6 21:01:02 2023
@author: Caterina Brighi
"""
#%% Import functions
import SimpleITK as sitk
import numpy as np
import os
from ImageAnalysisFunctions import *
#%% Set Working directory
data_supradir = 'Path to data directory' #Set working direc... |
0a5e1b4346983f7efaba440f685025be79628ea7efbe56a2cc06c3661ef72cc0 | Python | 2,666 | 88 | # -*- coding: utf-8 -*-
# @Author : Yue Liu
# @Email : yueliu19990731@163.com
# @Time : 2021/11/25 11:11
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from sklearn.manifold import TSNE
def t_sne(embeds, labels, sample_num=2000, show_fig=True):
"""
visualize embedding by t-SNE... |
17474962f0140b435eea98003cac0f1929c2e2c22a7dc17cded7a4f0ec44aeb2 | Python | 2,666 | 92 | """
ANCOVA
======
Example 1
---------
Based on [1]_, `Exercises
<http://www.bio.ic.ac.uk/research/crawley/statistics/exercises/R6Ancova.pdf>`_
(page 8).
"""
# Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
from eelbrain import *
y = Var([2, 3, 3, 4,
3, 4, 5, 6,
1, 2, 1, 2,
1, 1, 2, ... |
bb122b487f7fd6530a79f92dd41230f983ba780d0a2677b08d60879f37fa8f37 | Python | 2,666 | 56 | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2017-05-17 09:49
from __future__ import unicode_literals
import biomedisa_app.models
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
depende... |
d2692a78eb862214c35fccbc2d7ee9fdf64b584542bb81f5be95a546cee294da | Python | 2,666 | 65 | """01. Predict with pre-trained SSD models
==========================================
This article shows how to play with pre-trained SSD models with only a few
lines of code.
First let's import some necessary libraries:
"""
from gluoncv import model_zoo, data, utils
from matplotlib import pyplot as plt
###########... |
1281f5c64c18362935626a34e16c2dbcc2eb796c29d469cfd493d0a5aa4efe93 | Python | 2,667 | 73 | """
Copyright (c) 2022 EPFL-BBP, All rights reserved.
THIS SOFTWARE IS PROVIDED BY THE BLUE BRAIN PROJECT ``AS IS''
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE BLUE BRAIN PROJE... |
22a6d7a209e474923b1852169749516dded8c9b3ac6bdb7ced0249da559fd822 | Python | 2,667 | 78 | from typing import Optional, Union
import numpy as np
from anndata import AnnData
from numpy.random.mtrand import RandomState
from .._compat import Literal
import scanpy
_InitPos = Literal["paga", "spectral", "random"]
def run_umap(
adata: AnnData,
min_dist: float = 0.5,
spread: float = 1.0,
n_comp... |
892e16d4178cbdb03f1bb659743cbb2e3a24231bc1d57cb88641c713a4c9c11e | Python | 2,667 | 87 | from math import sqrt
from model import common
import torch
from torch import nn
import torch.nn.functional as F
def make_model(args, parent=False):
return FSRCNN(args)
class FSRCNN(nn.Module):
"""
Args:
upscale_factor (int): Image magnification factor.
"""
# def __init__(self, upscale_f... |
a8880cb3783a6146a45cfdb1c24476cb10058446c1a25d1778e94af92453329e | Python | 2,667 | 96 | #!/usr/bin/env python
#=========================================================================
#
# Copyright NumFOCUS
#
# 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:/... |
24ac274a2335ac87e6b6334b3f2fae080a2a7bb132c8ef033d5f2f7ccde19bce | Python | 2,668 | 104 | import pandas as pd
import polars as pl
import polars.testing.parametric as plst
import pytest
import seqpro as sp
from hypothesis import given, settings
from polars.testing import assert_frame_equal
from pytest_cases import parametrize_with_cases
settings(deadline=500)
def bedlike_strategy():
return plst.datafr... |
55c8767c539dfa3ceb434cec23cae23eaecc9444c5923da8d45c1690715fa26b | Python | 2,668 | 81 | """Tests for Trace-level semantic facet finders."""
from __future__ import annotations
import pytest
import torch
from torch import nn
import torchlens as tl
from torchlens import trace as trace_fn
class DistilBertSdpaAttention(nn.Module):
"""Tiny DistilBERT-like attention block for recipe tests."""
def _... |
065da9db72a0c435d59c05feb21efa84dd5b8d636c32a13b67eac73995c7ee77 | Python | 2,669 | 90 | """DLRM: Deep Learning Recommendation Model.
Naumov et al., 2019, arXiv:1906.00091. DLRM processes dense features through a
bottom MLP, sparse categorical ids through embedding tables, forms explicit
pairwise dot-product feature interactions, and feeds those interactions to a top
MLP. This compact version keeps that... |
9392895717c50192f1966b95fdfb65193bd790e801e3e877b32752abe33d15fc | Python | 2,670 | 73 |
from typing import Dict
import torch
from rbm.custom_fn import one_hot
@torch.jit.script
def sample_hiddens(
chains : Dict[str, torch.Tensor],
params : Dict[str, torch.Tensor],
beta : float=1.
) -> Dict[str, torch.Tensor]:
"""Samples the hidden layer conditioned on the state of the visible layer.... |
99837f5a8f20cba8119df37579feef3ebc4d1892e3407395f08d437b88442b1c | Python | 2,670 | 93 | # randomamp.py
# Copyright (C) 2013 Bastian Venthur
#
# 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 2
# of the License, or (at your option) any later version.
#
# This program ... |
d8e1375bf972558dc990f267c3a594387b95c3e456da249aed43208c29c05ec4 | Python | 2,671 | 76 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
106e133c7723a494657a34eae8f9d3715f0d029dbcb4cd031c15c79c75380644 | Python | 2,672 | 77 | import os
import glob
import pickle
import pandas as pd
import numpy as np
import loompy as lp
from dask.diagnostics import ProgressBar
from arboreto.utils import load_tf_names
from ctxcore.rnkdb import FeatherRankingDatabase as RankingDatabase
from pyscenic.utils import modules_from_adjacencies, load_motifs
from py... |
654af3459712716ad6d980351904c817b821fc6972c61dcd59164f4b349907c0 | Python | 2,672 | 101 | """Run data commands in parallel."""
from __future__ import annotations
import argparse
import os
from os.path import dirname, join, splitext
from subprocess import DEVNULL, check_call
from typing import Callable, List
from joblib import Parallel, delayed
from tqdm import tqdm
def parse_arguments() -> argparse.Nam... |
cf47be7987c17a0506e636188692f3b30e700119135fd280608414f2d5743538 | Python | 2,672 | 94 | #!/usr/bin/env python
import argparse
import sys
import xml.sax as sax
import readfile
from rest_tool_functions import DictHandler
def getIDofLine(line):
arr = line.split(">")
if len(arr) > 1:
aid = arr[1].split("<")[0]
return aid
else:
return "-1"
# get xml of all aids with c... |
20ced63f5e469cf3caa1e9a09c2c33be8081e27d232dadd4f60c547473357724 | Python | 2,673 | 72 | '''
Copyright 2021 Twente Medical Systems international B.V., Oldenzaal The Netherlands
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 requir... |
59df7786777273f4ffc8efa6478727b465227622be9caad46a41fa71b8977b06 | Python | 2,673 | 86 | from collections import defaultdict
import numpy as np
from shelved.plot_base_importance import plot_base_importance, Motif
def load_from_paper():
from_paper = """
sequence: atggttgtactgatggcttgtttttcattttttttgtgctttttggtccatctattaa
red : --------*--**-------------*----------------------*---*---*
... |
820bcc953df6b63eac89c38cb64c3adce8686037b3727da3c27baea02395f26e | Python | 2,673 | 80 | """
Model download for sc_crop.
Models are cached in ~/.cache/sc_crop/<model_version>/. SHA256 is verified on every load.
The model version (_MODEL_TAG) is decoupled from the package version.
To reclaim disk space from old versions:
rm -rf ~/.cache/sc_crop/v0.0.9
"""
import hashlib
import urllib.request
from pat... |
01cd396ba6c4747444a8193837fd5a26c68de39c1c1e508359417eab02071b1c | Python | 2,674 | 84 | from collections import defaultdict
import h5py
import attr
import numpy as np
import tqdm.auto as tqdm
@attr.s
class SpliceAIDatafile:
"""
Represents a SpliceAI datafile, as created by `create_spliceai_datafile`.
"""
datafile = attr.ib()
names = attr.ib()
names_backmap = attr.ib()
chro... |
4a11b20183318d80fe01ee3912a31352ed52863e2080591730f6d42b9e73d984 | Python | 2,674 | 63 | # pylint: disable=arguments-differ,line-too-long,missing-docstring,missing-module-docstring
from mxnet.gluon import nn
from mxnet.gluon.nn import Conv2D, HybridBlock, BatchNorm, Activation
__all__ = ['SplitAttentionConv']
class SplitAttentionConv(HybridBlock):
# pylint: disable=keyword-arg-before-vararg
def ... |
50e563b353fc5541518a77f44e804d0bce49bf1eeb688af20862c4014f3ae984 | Python | 2,674 | 92 | """Screenshots for quick guide import ts (not working automatically)"""
import pathlib
import shutil
import sys
import tempfile
import matplotlib.pylab as plt
import numpy as np
import pandas
import seaborn as sns
from PyQt6 import QtCore
from PyQt6.QtWidgets import QApplication
from pyjibe.head.main import PyJibe
d... |
0b4db1d82f1ffff415240b1abf810973846a36034fef533394513c0b7e6844e2 | Python | 2,675 | 76 | """End-to-end dispatch-consumption conformance (sol probe, live runtime).
A capability flag flipped True with a bound-but-undispatched implementation
must refuse at ``tl.trace()``, never capture while silently ignoring the
requested option. The policy-level biconditional lives in
``test_capability_truth.py``; these te... |
ebf7aa4f30e6e9041d4f59aba8ca712918c51c4ca2a7385bb6151e971f56000a | Python | 2,675 | 87 | import json
import os
import pickle
import tempfile
import pandas as pd
from .leafcutter_data import load_all_leafcutter_data
from modular_splicing.data_pipeline.create_datafile import produce_datafiles
from modular_splicing.data_pipeline.create_dataset import produce_datasets_from_datafile
from .compute_psi import ... |
244d1922df606d72aded23846bf629d6d8eca61dfd409f68e9eb160bfab1e45f | Python | 2,676 | 97 | import pytest
from pyrosm import get_data
@pytest.fixture
def test_pbf():
pbf_path = get_data("test_pbf")
return pbf_path
@pytest.fixture
def helsinki_pbf():
pbf_path = get_data("helsinki_pbf")
return pbf_path
def test_parsing_landuse_with_defaults(test_pbf):
from pyrosm import OSM
from ge... |
420abfca21177d3cda12b26826ddcc729cbe8474c11d104a21ff54cf12ccc790 | Python | 2,676 | 80 | import torch
import matplotlib.pyplot as plt
import brainbox.physiology.rfs as rfs
def build_rfs(model, rf_len=5, t_len=100, noise_var=10, samples=200, batch_size=50, layer=1, device="cuda"):
def model_output(noise):
with torch.no_grad():
print(f"noise {noise.shape}")
print(model(... |
63bd44626cfc96026e2cf216b422ee2afb990dbe541d7239518afc205281e09a | Python | 2,676 | 94 | import torch
from torch import nn, optim
import cv2
import numpy
import torch.fft
from complexPyTorch.complexLayers import ComplexConvTranspose2d,ComplexConv2d
from complexPyTorch.complexFunctions import complex_relu
class CDown(nn.Module):
def __init__(self,
in_channels,
... |
6612cb7e3a4606547c17e5e9bd5c8ff0d9222d0cb31888e7154eaea6b0c3aa77 | Python | 2,676 | 90 | """
utility code without big impact of the main function of the actual model
"""
import torch
from matplotlib import pyplot as plt
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import torchvision
import numpy as np
import warnings
import seaborn as sns
warnings.filterwarnings(
action="ignore... |
e14bd936126cd11f32bafc61ceda11cfee5d33d99ed8ff86222f03d7186701c3 | Python | 2,676 | 85 | import logging
import yaml
import copy
import argparse
from bson.objectid import ObjectId
from pymatgen.core import Molecule
from atomate.qchem.fireworks.core import FrequencyFlatteningOptimizeFW
from atomate.common.powerups import add_tags
from fireworks import LaunchPad, Workflow
from instance_mongodb import ins... |
4204d76694aba4304a587f8d1a82d65d15d6a8f97be1f9d1dd94d460da04f26f | Python | 2,677 | 84 | import os
import sys
from typing import List
from pathlib import Path
import itertools
import numpy as np
import matplotlib.pyplot as plt
import snapatac2 as sa2
with open("../meta/mba.whole.sample.lst", 'r') as f:
samples = [ l.strip() for l in f.readlines()]
# * summarize doublet removal under bmat
bmat_dlt_di... |
b42c9f4ac2be76c22a1a23f295de292e55d3057c7f81d6cd5125e2a07c07d481 | Python | 2,677 | 64 | import os
from data.base_dataset import BaseDataset, get_params, get_transform
from data.image_folder import make_dataset
from PIL import Image
class AlignedDataset(BaseDataset):
"""A dataset class for paired image dataset.
It assumes that the directory '/path/to/data/train' contains image pairs in the form ... |
1b138f6db6a9a8370237d0b1fb7986094c58e10d81f7932a2a423b5f23a8f571 | Python | 2,678 | 78 | #!/usr/bin/python
#-*-coding:utf-8-*-
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance wi... |
971885b241700ce1ed2d198f0fa8a44b215d6c3ef70b484395660bb0f64bebd3 | Python | 2,678 | 65 | '''Extracts the distributions associated with NeuroM module'''
import neurom as nm
from neurom import stats
import numpy as np
def transform_distr(opt_distr):
'''Transforms distributions'''
if opt_distr.type == 'norm':
return {"norm": {"mean": opt_distr.params[0],
"std": opt_... |
9a17fb78d7c8f9e70298edd8882ab85b8ba919a95db79863a5d426162b4afd0b | Python | 2,678 | 85 | import operator
import time
import pytest
from celery.utils.functional import noop
class test_thread_TaskPool:
def test_on_apply(self):
from celery.concurrency import thread
x = thread.TaskPool()
try:
x.on_apply(operator.add, (2, 2), {}, noop, noop)
finally:
... |
add699259a052a491ff71d6471c418222936c6cc80bd16964117962f8c32c663 | Python | 2,678 | 88 | from sklearn.preprocessing import StandardScaler
from sklearn.decomposition import PCA
import numpy as np
import pandas as pd
from scipy.io import loadmat, savemat
import unidecode
meg = loadmat('bids/derivatives/meg-derivatives/grand_ave/matrices/modality-picture.mat')
target_word_labels = [w.strip() for w in meg['... |
1f769b2271947c151b6c59ab58422c4218c17d5e88f97eb8c416c380a8386670 | Python | 2,679 | 87 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Import raw (MaxFiltered) MEG data to remove metadata then save in same format for
further BIDSifying.
@author: mikkel
For information about NatMEG-PD please refer to the data descriptor:
Vinding, M. C., Eriksson, A., Comarovschii, I., Waldthaler, J., Manting, C. L.,... |
5fabcb82f736be983f3bbe0a8dd164b66b4bb0dbe788980b1368d58c9211817a | Python | 2,679 | 75 | """
This script replicates the finding by David and Friston 2004 NeuroImage that the frequency of the Jansen-Rit model
can be tuned between delta and gamma frequencies by adapting the synaptic time constants.
"""
from pyrates import grid_search
import matplotlib.pyplot as plt
from seaborn import heatmap
from scipy.sig... |
9ca4c99801cd4aa737d20f79fcd3c3b6fab33f819681837404d874d79005cd83 | Python | 2,679 | 66 | # Adapted from https://github.com/pytorch/pytorch/blob/v2.7.0/torch/_library/triton.py
# The PyTorch implementation simply ignores the schema argument, we simply modify it to use schema.
from typing import Optional, Callable, Iterable, Union
from torch.library import custom_op, CustomOpDef
from torch._library.triton ... |
0b5bba9d25c019acd5526ae7aa630eaaa5ab8755f7f0238cc77e3996c393388a | Python | 2,680 | 72 | class BiomedisaParameter():
allaxis: bool = False
denoise: bool = False
nbrw: int = 10
sorw: int = 4000
smooth_active: bool = False
smooth: int = 100
clean_active: bool = False
clean: float = 0.1
fill_active: bool = False
fill: float = 0.9
ignore: str = 'none'
only: str =... |
828925b355f3d901943ea9bd58c476586d884363dbb63755a4950f37a6695559 | Python | 2,681 | 53 | # Adapted from https://github.com/mlcommons/training_results_v1.1/blob/main/NVIDIA/benchmarks/bert/implementations/pytorch/padding.py
import torch
import torch.nn.functional as F
from einops import rearrange
def unpad_input(hidden_states, attention_mask, unused_mask=None):
"""
Arguments:
hidden_state... |
be1717c02b0e6abd1c6033d9a3b205fee9510ec186bd9cde3c8792a5209580b9 | Python | 2,681 | 91 | #!/usr/bin/env python3
# coding: utf-8
"""
Created on July 10 2019
Authors:
Nathan De Lara <nathan.delara@telecom-paris.fr>
"""
from abc import ABC
from typing import Union
import numpy as np
from scipy import sparse
from scipy.sparse.linalg import svds
from sknetwork.base import Algorithm
class SVDSolver(Algorith... |
38a650b354e967fc64d25b4e55a638576e5fde3ac35806c7ddc3d18a8ede553a | Python | 2,682 | 61 | def motif_model_types():
from .learned_motif_model import (
LearnedMotifModel,
)
from .no_motif_model import NoMotifModel
from .parallel_motif_model import ParallelMotifModels
from .adjusted_motif_model import AdjustedMotifModel
from .reprocessed_motif_model.reprocessed_motifs import Rep... |
3a9ad02704702dadcb7bb83c71cc233d3c2a61857d5de9461940873074cdc8b6 | Python | 2,682 | 67 | from __future__ import annotations
import pytest
import torch
from lightly.utils import dependency
if not dependency.timm_vit_available():
# We do not use pytest.importorskip on module level because it makes mypy unhappy.
pytest.skip("TIMM vision transformer is not available", allow_module_level=True)
from... |
fd94eca67d367d21ba46479c47c35ebf31649663bf85e7d2abbbdf72f90420ce | Python | 2,682 | 75 | """Captum ``layer()`` against the REAL captum package.
``tl.bridge.captum.layer`` shares Grad-CAM's resolver: an op label resolves to
the outermost module whose output its tensor is, and LayerGradCam on that
module is bit-identical to LayerGradCam on the module named directly.
"""
from __future__ import annotations
... |
bdf64d27c0b3d9adf3b6674ed7c56b5be4840167e562067574d93633fba7728f | Python | 2,683 | 88 | ## Read write encoder
import sys,os
from datetime import datetime,timezone,timedelta
import serial
import pyqtgraph as pg
from pyqtgraph.Qt import QtCore, QtGui
import numpy as np
import multiprocessing
from scipy.ndimage.filters import gaussian_filter1d
from tkinter import filedialog
import csv
port = 'COM13'
max_nu... |
be54fe7b1501eeb3e8f942173d3b58cf4e2fe16ebe574b9f334ed536803a23d3 | Python | 2,684 | 79 | """
A general test to try to find out if anything is wrong with the API.
"""
import os
import random
import tempfile
import time
import unittest
from _constants import DRAW_FRAMES, VIDEO
from ethoscope.core.monitor import Monitor
from ethoscope.drawers.drawers import DefaultDrawer
from ethoscope.hardware.input.camer... |
d0aacefb29dcc84d0e64fe982871a215bdc4960da62977b026eaa76cc59477e8 | Python | 2,684 | 78 | import gzip
import io
import os
from pathlib import Path
import pandas as pd
import wget
def get_download_path():
"""
Returns a path to download files to
If EUGENe is installed, returns the path specified in settings.dataset_dir
Otherwise, creates a directory called 'seqdatasets' in the current ... |
df327596502602b9f7a706588e16596f6dc4755428a0146ad259c69fe0257987 | Python | 2,685 | 85 | #!/usr/bin/env python
# -*- encoding: utf-8 -*-
from __future__ import absolute_import
from __future__ import print_function
import io
from os.path import dirname
from os.path import join
from os import path
from setuptools import find_packages
from setuptools import setup
import os
from Cython.Build import cythonize
... |
0c16b8d000d013b531454acfb1787666793f1bf802ad6e3a5c9a71ae1026b3be | Python | 2,687 | 73 | """Parameter converters.
Notes
-----
Parameter converters should have the following properties, depending on component:
- for 'aperiodic' parameters : callable, takes 'fit_value' & 'model' as inputs
- for 'peak' parameters : callable, takes 'fit_value' & 'model', 'peak_ind' as inputs
"""
import numpy as np
from spec... |
3d5d5af705dc0c3d274fc3d7fc1814577c6a098e108549755b5c243d81f55c15 | Python | 2,687 | 85 | from typing import Optional, Union
from anndata import AnnData
from matplotlib import pyplot as plt
from pathlib import Path
import os
from PIL import Image
Image.MAX_IMAGE_PIXELS = None
def image(
adata: AnnData,
imgpath: Union[Path, str],
library_id: str,
quality: str = "hires",
scale: float = ... |
70cb8a5b57bcee9776281d3556206281e15bbd424820c86818e7a66c4405b027 | Python | 2,687 | 90 | #!/usr/bin/env python
import argparse
import re
from Bio import SeqIO
from Bio.Alphabet import generic_dna
from Bio.Seq import Seq
from Bio.SeqUtils import nt_search
choices = [
"embl",
"fasta",
"fastq-sanger",
"fastq",
"fastq-solexa",
"fastq-illumina",
"genbank",
"gb",
]
def find_p... |
8e4d82792643597ab581df964d12958136291bdb6bce427c1f93cb48ab0644d0 | Python | 2,687 | 87 | """
using prody to extract the pocket
"""
import os, re
import prody as pr
from openbabel import openbabel as ob
#import subprocess
#os.environ["BABEL_LIBDIR"] = "/home/shenchao/.conda/envs/my2/lib/openbabel/3.1.0"
def write_file(output_file, outline):
buffer = open(output_file, 'w')
buffer.write(outline)
buffer.cl... |
5edbfd3f2e75944e3ab90db66f8e209f320639ebc28903bc1b2ade79eb246cf2 | Python | 2,688 | 85 | import os
from pathlib import Path
from anndata import AnnData
from matplotlib import pyplot as plt
from PIL import Image
Image.MAX_IMAGE_PIXELS = None
def image(
adata: AnnData,
imgpath: Path | str | None,
library_id: str,
quality: str = "hires",
scale: float = 1.0,
visium: bool = False,
... |
7f89e8c8a6445468ddaf8e3a8505c5c3e4a6db0e973dda552d488d8dfd279d49 | Python | 2,688 | 103 | #!/usr/bin/env python3
'''Adds show_arrows command to pymol, which takes an xyz file'''
import sys
import os
from pymol import cmd, cgo, CmdException
from chempy import cpv
def draw_arrow(xyz1,xyz2, radius=0.5, gap=0.0, hlength=-1, hradius=-1,
color='blue red', name=''):
'''
Draw an arrow; borrows... |
ac01d7927c3f05abb4902b94b8b1d41a64d48adfe26e16826a7797b1d10f9156 | Python | 2,688 | 71 | #!/usr/bin/python
#from distutils.core import setup
from setuptools import setup
#import path
import subprocess
import versioneer
#here = path.abspath(path.dirname(__file__))
#version = '0.1.4'
def version_from_git():
try:
proc = subprocess.Popen(["git", "describe", "--tags"], stdout=subprocess.PIPE)
... |
d1cd154dfb02b354d1d3c5957ab5d6fd63a3136f6f808d9b1e187b796746113e | Python | 2,688 | 97 | # Copyright 2024 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agre... |
e3c855d041b4f062abd6e3425cce88a3e2c52fd07420f36342b7658179a5efe2 | Python | 2,689 | 97 | # randomamp.py
# Copyright (C) 2013 Bastian Venthur
#
# 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 2
# of the License, or (at your option) any later version.
#
# This program ... |
99b3bb7109f689077adf879357deff5cb4db7c8a848a6e58f384564be306ccb4 | Python | 2,691 | 77 | """
Gregory Way 2017
PanCancer NF1/RAS Classifier
scripts/within_tissue_analysis.py
Usage: Run in command line
python within_tissue_analysis.py
with the following required flags:
--genes comma separated string of HUGO gene symbols
and the following optional flags:
--diseases c... |
5131d425e170e47f7402ef86aa509af6c1bf72f8e62d15f78f338f44c5a5359f | Python | 2,692 | 115 | import numpy as np
import subprocess
from math import sqrt
from sklearn.metrics import average_precision_score
from scipy import stats
def get_aupr(Y, P, threshold=7.0):
# print(Y.shape,P.shape)
Y = np.where(Y >= 7.0, 1, 0)
P = np.where(P >= 7.0, 1, 0)
aupr = average_precision_score(Y, P)
... |
bcc7761dd9c0ec861cc6e1ebe8b8b4b4928661e2b1168ea2a4e219084d5212d0 | Python | 2,693 | 82 | """Tests for the xcp_d.cli.version module."""
from datetime import datetime, timezone
from packaging.version import Version
from xcp_d.cli import version
class _FakeResponse:
def __init__(self, tags, next_url=None, status_code=200):
self._tags = tags
self._next_url = next_url
self.statu... |
f7588a86ff7dffadfe3cc251b47a94e62f72005c9c9c363cba5cd8170c9d1058 | Python | 2,694 | 92 | """Tests that gym.spec works as expected."""
import re
import pytest
import gym
def test_spec():
spec = gym.spec("CartPole-v1")
assert spec.id == "CartPole-v1"
assert spec is gym.envs.registry["CartPole-v1"]
def test_spec_kwargs():
map_name_value = "8x8"
env = gym.make("FrozenLake-v1", map_na... |
f7927b399d7fda3522a29fc99b636d551d4ff1c6a3384a3c5e06e8ed95e04f0d | Python | 2,694 | 74 | from PyQt5 import QtCore
from .tracker_widget import TrackerControlWidget
class TrackerController(QtCore.QObject):
def __init__(self, tracker=None, parent=None):
super(TrackerController, self).__init__(parent)
self._tracker = tracker
self.tracker.tracker_controller = self
self.wi... |
2e8ff1967777587be8014ef971ef8463c51a27dfd6f1e634eb184a17e21231d0 | Python | 2,695 | 67 | """02. Predict with pre-trained Faster RCNN models
==============================================
This article shows how to play with pre-trained Faster RCNN model.
First let's import some necessary libraries:
"""
from matplotlib import pyplot as plt
import gluoncv
from gluoncv import model_zoo, data, utils
#######... |
cc8b72808f5c2ccad0a272e13ae6efa2b125539a9a66e9857e331eb61c78ac3c | Python | 2,695 | 62 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
""""tests for distances.py"""
import unittest
from sknetwork.data.test_graphs import *
from sknetwork.path.distances import get_distances
class TestDistances(unittest.TestCase):
def test_input(self):
adjacency = test_graph()
with self.assertRaises(V... |
f474b802b3ffac1342f3d5e90b323b02edddf71cc8fe7add2388350f11ed1a52 | Python | 2,695 | 92 | import numpy as np
from numpy.random import default_rng
import pathlib
from mpi4py import MPI
from causal_optoconnectics.tools import conditional_probability, joint_probability, roll_pad
from causal_optoconnectics.generator import (
construct_connectivity_filters,
construct_connectivity_matrix,
simulate,
... |
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