sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
86ab4def8348054ceea6d2558b239417c64bd97e910c3285f8a512cb9fd67263 | Python | 2,223 | 89 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import shutil
from glob import glob
from vlpp.utils import gzipd, run_shell, run_matlab, TPL_PATH
PARTICIPANT = "${participant}"
def seg_spm12(img, spmDir):
for d in ["mask", "transform"]:
os.mkdir(d)
tags = {
"anat": gzipd(img),
... |
a3c287e15eab358d38ddce999f855268bbc013e897e9ebe0639cfe21be1f4162 | Python | 2,225 | 70 | from torch import nn
import torch.nn.functional as F
'''
https://blog.csdn.net/yiran103/article/details/100063021
'''
class BlazeBlock(nn.Module):
def __init__(self, inp, oup1, oup2=None, stride=1, kernel_size=5):
super(BlazeBlock, self).__init__()
self.stride = stride
assert stride in [1,... |
dfa1f98abbdce3fbd5681f184dcdbad3df02abeb067810822d6defe00b2dc133 | Python | 2,225 | 63 | import logging
from pathlib import Path
from .. import common, config
from .. import predict as predict_module
from ..common.logging import config_logging_for_cli, log_version
logger = logging.getLogger(__name__)
def predict(toml_path):
"""make predictions on dataset with trained model specified in config.toml ... |
0ebfd80053341917620e7c07debbf8e897f9f4fddbec34c9af8178736e9bc3a7 | Python | 2,226 | 79 | # Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
# author: adefossez
import math
import torch as th
from torch.nn import functional as F
def sinc(t):
"""sinc.
:... |
7ca4395bfebb5c0d0f4b0a38b08ccc6ffbddca03e8794ff099b76e0ebf7c8f13 | Python | 2,227 | 73 | import jax
import jax.numpy as jnp
import numpy as np
from folx import ForwardLaplacianOperator
jax.config.update('jax_enable_x64', True)
def brute_force_laplacian(fn):
def laplacian(x):
H = jax.hessian(fn)(x)
f = jax.grad(fn)(x)
return jnp.trace(H), f
return laplacian
def test_de... |
0a84bdc91d20a8e5f687a4e634948bade59304f77a3588e987687d2039408a47 | Python | 2,228 | 82 | """ Utility functions to manipulate image data. """
import cv2
import numpy as np
import dask.array as da
def normalize(image: np.ndarray) -> np.ndarray:
"""
Normalize an image to the range [0, 1].
Parameters:
image (np.ndarray): The input image.
Returns:
np.ndarray: The normalized image.
"""
retur... |
364631a1faa11ae55d05567396806fcc63758222f486c7a641b1ead3193c44e7 | Python | 2,229 | 79 | import os
from copy import deepcopy
from os.path import dirname
import numpy as np
base_dirname = dirname(dirname(__file__))
filename = os.path.basename(__file__)
task = 'classification_binary'
selected_genes = 'tcga_prostate_expressed_genes_and_cancer_genes.csv'
data_base = {'id': 'ALL', 'type': 'prostate_paper',
... |
ba4983630490dfb3187a8e077fed8b327102e79b09e157e34f3466e2fa2c9f70 | Python | 2,229 | 78 | """`d3text.excepthook`: the context an exception carries must reach the user.
`add_note` is where this package puts the line that names the file or the
setting a third-party exception could not name itself. stackprinter's hook
renders only the traceback, so on the console -- the one path those notes were
written for -... |
e97ecc828a2fca105c2a04f848dbf20fbc1a052f2a7104c481dd5d968c3e3128 | Python | 2,231 | 53 | ## Wrapper for crystalgrw.cli.evaluate.main ##
import argparse
import torch
import torch.multiprocessing as mp
from crystalgrw.cli.evaluate import run_eval
def main(rank, world_size, cfg):
run_eval(rank, world_size, cfg)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(... |
c1009119d0b1253b4ce5b7363101ad9ccf94e59d2ef41230dbed8f46528b7675 | Python | 2,236 | 73 | #!/usr/bin/env python
# Author_and_contribution: Niklas Mueller-Boetticher; created template
# Author_and_contribution: Thomas Chartrand; created script
import argparse
parser = argparse.ArgumentParser(description="Calculate Matthew's correlation coefficient (scikit-learn)")
parser.add_argument(
"-l", "--labels... |
6453f34411e55fd85b92f9e3153625773738cf16433c4589d0e517c0f0335b56 | Python | 2,238 | 76 | import gradio as gr
import os
from utils.foldseek_util import get_struc_seq
ROOT_DIR = __file__.rsplit("/", 3)[0]
####################################################
# gradio blocks #
####################################################
def upload_pdb_button(visible: bool = True... |
fba1a086e23a8b4da6bc2ca948a4e8996878791dabd39f84f84598e343d0d433 | Python | 2,238 | 100 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Project information -----------------------------------------------------
# https://www.sphinx-doc.org/en/master... |
05f47cd2523fba9028a9bdf745c39c3a41d0aca86d4d0c1e692628ab8d68e54b | Python | 2,240 | 66 | #
# Copyright 2017-2023 Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000 with
# Sandia Corporation, the U.S. Government retains certain rights in this software.
#
# See LICENSE for full license details
#
from ..idevice import EmptyDevice
from ...backend import ComputeBackend
xp = ComputeBackend()
c... |
5420f16d5f55e822003eee066c0d8b84d43850c2974cdae968863046d82df854 | Python | 2,240 | 65 | from ... import options as opts
from ... import types
from ...charts.chart import Chart
from ...globals import ChartType
class Liquid(Chart):
"""
<<< Liquid >>>
The liquid chart is mainly used to highlight the percentage of data.
"""
def __init__(
self,
init_opts: ... |
88d6837eb0b83ded1b972033e1ea8eb97208d73ce6b8acb42fd041d176cb7efc | Python | 2,241 | 63 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
TODO (huxu): a general fairseq criterion for all your pre-defined losses.
"""
from fairseq.criterions import FairseqCriterion, register_c... |
c9bb4373d2b9fd6070fedf730eb4db50895f47ad0c6d641af85f2d188ef098d9 | Python | 2,241 | 71 | from argschema import ArgSchemaParser
import os
import logging
import subprocess
import time
import shutil
import numpy as np
import io, json, os
from .create_settings_json import create_settings_json
from ...common.utils import get_repo_commit_date_and_hash
def run_npx_extractor(args):
print('ecephys spike so... |
f6fe7befbf0ed64a678adc10b636d5f3f3254ad0710157260b3014eaa20f1ea2 | Python | 2,241 | 68 | """Implementation of utilities to load a pretrained Enformer model in Trix."""
from typing import Callable, Tuple
import haiku as hk
import jax.numpy as jnp
from nucleotide_transformer.enformer.features import FEATURES
from nucleotide_transformer.enformer.heads import UNetHead
from nucleotide_transformer.enformer.mo... |
5d0788ae33d7f06521359c638d68bfd1eefda48d3465d168a7c0cd8cedd70cf6 | Python | 2,242 | 63 | import jax.numpy as jnp
import pytest
from oneqmc.types import Nuclei
from oneqmc.wf.orbformer.orbitals import generate_spd_orbitals
@pytest.mark.parametrize(
"nuclei,max_charge,max_orbitals,expected",
[
( # H2
Nuclei(jnp.array([[0.0, 0.0, 0.0], [0.0, 0.0, 1.0]]), jnp.array([1.0, 1.0]), ... |
6719cf28b26ba5a42a5c419d90f4e4dce6716d10db9e756addea82189a05d02f | Python | 2,242 | 73 | import cv2
import time
import glob
import numpy as np
import cmapy
import time
import cv2
from PIL import Image
from msi_visual.normalization import spatial_total_ion_count, total_ion_count, median_ion
from sklearn.metrics.pairwise import pairwise_distances
import numpy as np
def core_sets(data, Np):
... |
174403a6db90cc18a5a179e55fae1fa838549d5a2626cde71b038baed604c1d7 | Python | 2,244 | 73 | import numpy as np
import argparse
from celltype_ibl.models import mlp_classifier as mlp_probe
from celltype_ibl.utils.ultra_data_util import get_ultra_wvf_acg_pairs
from celltype_ibl.params.config import ULTRA_DATA_PATH
import os
import re
def extract_seed_and_epoch(checkpoint_path):
# Use regular expressions to... |
8909500d6dd8e677ecee5f5c591a45c57433932bc38b6eaf494d8cfa23c3a29f | Python | 2,245 | 61 | #
# Copyright 2017-2023 Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000 with
# Sandia Corporation, the U.S. Government retains certain rights in this software.
#
# See LICENSE for full license details
#
from .idac import IDAC
from .quantizer_dac import QuantizerDAC, SignMagnitudeDAC
class DAC(IDAC)... |
1d31fca84fd531a7a5073f45f78abe92d5718d09e021a762ef823e6a9cef6a5d | Python | 2,247 | 72 | """Bidirectional GRU on counts matrix."""
import warnings
import torch
import medaka.architectures.base_classes as base_classes
class GRUModel(base_classes.CountsMatrixModel):
"""Implementation of bidirectional GRU model in pytorch."""
def __init__(
self,
num_features=10,
num_class... |
97c9497f1055e393be35a7272ced59bfb7155b8a9421ea71be920f81000976da | Python | 2,247 | 70 | from argschema import ArgSchemaParser
import os
import logging
import time
import numpy as np
import pandas as pd
from ...common.utils import load_kilosort_data
from .extract_waveforms import extract_waveforms, writeDataAsNpy
from .waveform_metrics import calculate_waveform_metrics
def calculate_mean_waveforms(args... |
dffff59263a9600c65bc327feb9a09755c91fe397dbc5f9625ed05d59906e10d | Python | 2,247 | 79 | import os
from copy import deepcopy
from os.path import dirname
import numpy as np
base_dirname = dirname(dirname(__file__))
print(base_dirname)
filename = os.path.basename(__file__)
task = 'classification_binary'
selected_genes = 'tcga_prostate_expressed_genes_and_cancer_genes.csv'
data_base = {'id': 'ALL', 'type':... |
e0fee1478fd7a3076b0032487719a0ec3e99e9021f08bd227ab3b34257884b49 | Python | 2,247 | 79 | import torch
import wandb
from utils.data.dataholder import DataHolder
from utils.data.misc import to_batch
def training_step_func(self, data: DataHolder, i: int) -> torch.Tensor:
"""
Training step: based on node-level conditional point cloud diffusion model
Parameters:
- data: input data batch
... |
fc4ce7e088b0d261fea7d2b478cd181dac97b27b929226ec670b0e9ae58eebec | Python | 2,251 | 79 | import os
C4_COLORS = {
"PkC_ss": [28, 120, 181],
"PkC_cs": [0, 0, 0],
"MLI": [224, 85, 159],
"MFB": [214, 37, 41],
"GrC": [143, 103, 169],
"GoC": [56, 174, 62],
"laser": [96, 201, 223],
"drug": [239, 126, 34],
"background": [244, 242, 241],
"MLI_A": [224, 85, 150],
"MLI_B":... |
0ad1781aaa2ff69b6146bb6bce04e493d17dbc7ecc560a0907b59c38b64f43ca | Python | 2,252 | 54 | """Shared pytest fixtures for the pgmpy test suite.
Example models and datasets are normally fetched from Hugging Face through ``pgmpy.utils.hf_hub.read_hf_file``. To keep
the test suite self-contained and free of network access, the autouse fixture below redirects that single byte-fetch
seam to local fixture files co... |
0b2c838b2ce494f2f300cd39393d8eb3597a8fd63c484b6b47c5bf9981cd17df | Python | 2,252 | 65 | from os.path import join
import matplotlib.patches as mpatches
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
from scipy.optimize import curve_fit
from config_path import PROSTATE_DATA_PATH
from setup import saving_dir
def sigmoid(x, L, k, x0):
b = 0.
y = L / (1 + np.exp(-k * (x... |
495e5b0b16d0a461c986edc896e659d55ba4024015baeac3cafbfd8f5a2ec67a | Python | 2,253 | 81 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
from fairseq import options
from examples.noisychannel import rerank_options, rerank_utils
def score_lm(args):
using_nbest =... |
b134144c1497488746d7d4a08ec47f3206378c06880e742a11638a0f211022ab | Python | 2,253 | 77 | import time
import RPi.GPIO as GPIO
class mainprogram:
#Main while loop condition
keepalive = True
#DEFINE NUMBER OF BUTTONS AND ORDER IN ARRAY
buttonarray = ['movefast','moveslow','buttontohome','relativeALL','relativeAP','relativeMV','relativeDV','buttonaction','miscbuttonC','miscbuttonD','miscbutto... |
7c4cf2cd950c7f443b64f577b57aafc927af801bb0fe8188e9fc33e17227e0b1 | Python | 2,254 | 32 | """Utilities for machine learning on genomics data.
See README for a brief description of the programs,
See the documentation (which you can build) for a specification,
and see doc/demos/osknExample.ipynb for a demonstration notebook.
"""
# Version specification:
# Versions are named as [major].[minor].[patch]
# A m... |
771a60ee033eb0fb48037fc82684b2b7f2ac6936da65201dade68a7545bcd055 | Python | 2,255 | 58 | #!/usr/bin/env python3
"""Preprocess Simulation raw data only (no training loop)."""
from __future__ import annotations
import argparse
import os
import sys
from pathlib import Path
from hydra import compose, initialize_config_dir
from omegaconf import OmegaConf
ROOT = Path(__file__).resolve().parents[... |
51e2c14270b5bb7ab74ae381fa80619544b403b320644c7d033337805de76429 | Python | 2,257 | 77 | from collections import namedtuple
from math import ceil
from typing import Optional
import jax
import jax.numpy as jnp
__all__ = ()
EWMState = namedtuple("EWMState", "step params buffer mean var sqerr", defaults=6 * [None]) # type: ignore
def init_ewm(
max_alpha: float = 0.999,
decay_alpha: float = 10.0,... |
d35edd67706448d49c79ddce2f9255652b2457914ac22bad7a7042468eb01e21 | Python | 2,257 | 65 | __author__ = 'Robbert Harms'
__date__ = '2017-06-19'
__maintainer__ = 'Robbert Harms'
__email__ = 'robbert@xkls.nl'
__licence__ = 'LGPL v3'
class PlottingFrame:
def __init__(self, controller, plotting_info_viewer=None):
super().__init__()
self._controller = controller
self._plotting_info_... |
8cc59e445d6bacedad317cbce859e5e426720394f7f4b3a04d0564c6275504da | Python | 2,259 | 61 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from typing import Dict, Optional
import torch
import torch.nn as nn
import torch.nn.functional as F
from fairseq import utils
from torch imp... |
17c1786a87e0c4a069893bccb643a811cc2647dc78b1b7c4a68ba107807dd014 | Python | 2,260 | 71 | #!/usr/bin/env python3
# -*- encoding: utf8 -*-
import argparse
import itertools
import os
import re
import sys
from pathlib import Path
import whisper
from tqdm import tqdm
parser = argparse.ArgumentParser()
parser.add_argument("--wavs", type=str)
parser.add_argument("--lids", type=str)
parser.add_argument("--dst"... |
74b98fe8d4482a06bc124240d9b8b9aa5ef6010d704279da5214f24c94cac0d4 | Python | 2,260 | 85 | #!/usr/bin/env -S uv run --script
# /// script
# requires-python = ">=3.11"
# dependencies = [
# "ngff-zarr[tensorstore]",
# "numpy",
# "tensorstore",
# ]
# ///
import os
import pathlib
import shutil
import zipfile
import ngff_zarr as nz
import numpy as np
import tensorstore as ts
THIS_DIR = os.path.absp... |
977249c954ea03650094b1bda3dc05a03cbdcf553b01838b5796ff090906b857 | Python | 2,260 | 77 | import itertools
import joblib
import numpy as np
import pandas as pd
import os
import unittest
from numpy import testing
from sklearn import datasets, preprocessing
#from matplotlib import pyplot
from mentor import _cluster as cluster
from mentor import _datasets as datasets
from mentor import _metrics as metrics
fr... |
3ee56b5dc267d0e244fdc540de1de483e4aaa1ad08c1fa227c13e945100e7207 | Python | 2,262 | 66 | from ... import options as opts
from ... import types
from ...charts.basic_charts.geo import GeoChartBase
from ...commons.utils import OrderedSet, JsCode
from ...exceptions import NonexistentCoordinatesException
from ...globals import ChartType
class LMap(GeoChartBase):
"""
<<< LMap(leaflet) coordinate system... |
709c619e15ab154f4504e490a0c860d291ca38ed7719583faa0d56812a054b1f | Python | 2,262 | 65 | from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import roc_auc_score
import numpy as np
import pandas as pd
from tqdm import tqdm
import warnings
warnings.filterwarnings('ignore')
from .encode_structure import *
from .model import *
from .utils import *
import pickle
def get_contact_data(da... |
268fe01459dc29d13a0b8f391abedfe7841bb93fd3d82934d236e3fa3b17fd7a | Python | 2,264 | 57 | # @license
# Copyright 2021 Google 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 agreed to in... |
d0d038d81819fec71414bfdfe0533a0b257b427507889e7c4049a31f6e8f60c9 | Python | 2,264 | 82 | #!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Implement unsupervised metric for decoding hyperparameter selection:
$$ alpha * LM_PPL + ViterbitUER(%) * 10... |
e3745374b508d248f155879182105abcfabcfe752ce42897c532c68492ca048c | Python | 2,265 | 68 | from torch.utils.data import DataLoader
import lightning.pytorch as pl
from typing import Union, Optional
from pathlib import Path
from rinalmo.data.alphabet import Alphabet
from rinalmo.data.downstream.ribosome_loading.dataset import RibosomeLoadingDataset
from rinalmo.utils.download import download_ribosome_loadin... |
d0915ae1b78d0db68f30cc3f336b24de28ff0a7a6b6bc2b111ea2a51734522ad | Python | 2,267 | 57 | import torch
import torch.nn as nn
import torch.nn.functional as F
from core.modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d
class Decoder(nn.Module):
def __init__(self, num_classes, backbone, BatchNorm):
super(Decoder, self).__init__()
if backbone == 'resnet' or backbone == 'drn'... |
0573efa2caea1a24fd584a9368fb9f480734e84eef5e60e7c059a45fbe77bdeb | Python | 2,268 | 81 | # -*- coding: utf-8 -*-
import os
from glob import glob
from .utils import run_shell, gzipd, run_matlab, TPL_PATH
def applyWarpImageMultiTransform(_input, ref, mat, output=None):
if not output:
output = "tmp.nii.gz"
cmd = "WarpImageMultiTransform 3 {0} {1} {2} -R {3} --use-BSpline"
run_shell(cmd... |
5e3b287d103c3f2da94d8cab00893365f78ff97d3b5687d89401002ea263f7f0 | Python | 2,268 | 64 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import csv
from pathlib import Path
def main(args):
"""
`uid syn ref text`
"""
in_root = Path(args.generation_root).resolve... |
724f0bb92ffb7629c3e45a56a7aea4e0d4ef7d299634ddf7b3d018acc3acbbe0 | Python | 2,268 | 70 | """Save and load behaviour settings between a DataFrame and JSON."""
import json
import logging
import os
from typing import Any
import pandas as pd
logger = logging.getLogger(__name__)
def save_behaviour_static_inputs(dataframe: pd.DataFrame, filename: str | os.PathLike[str]) -> None:
"""Save behaviour settin... |
b027e15d0f3b7f9a633fe7e978e3e9e136caba336fd9c17e47bb3f0019d650f1 | Python | 2,268 | 93 | import argparse
from pathlib import Path
import anndata
import scanpy as sc
from anndata import AnnData
import novae
MIN_CELLS = 50
DELAUNAY_RADIUS = 100
def preprocess(adata: AnnData, compute_umap: bool = False):
sc.pp.filter_genes(adata, min_cells=MIN_CELLS)
adata.layers["counts"] = adata.X.copy()
sc... |
a2a15e1e8e3854947b1ab9c45783ec5f7e492e24f88132a5c10e11432d7f54a5 | Python | 2,269 | 68 | """
Run before training: dataset task gate, model task×dataset gate, and a forward shape dry-run.
Standalone package: Simulation + unet + dynamic_segmentation_CID only.
"""
from __future__ import annotations
from typing import Union
import torch
from omegaconf import DictConfig
from models.build import ... |
c480a70ffb70ced3a9623e5728b33f76f7e2c41869342f57933ca450f5b511e8 | Python | 2,271 | 48 | import pandas as pd
from preprocessor.MembraneCurrentPreprocessor import MembraneCurrentPreprocessor
from preprocessor.AxialCurrentPreprocessor import AxialCurrentPreprocessor
class Preprocessor:
"""
Represents a class responsible for preprocessing simulation data to prepare
and transform current data (me... |
2363af683f41201cde86d78c8038134c150de762495bf7acd085163a9803d6d4 | Python | 2,273 | 55 | import os
import threading
from configparser import ConfigParser
from . import credentials_provider
from .futures import run_on_new_thread
class BossCredentialsProvider(credentials_provider.CredentialsProvider):
def __init__(self):
super().__init__()
self._lock = threading.Lock()
self._cr... |
e0d54e5f3e2b2566caabe42b434ad3d413639c3a00d51c6b57518fa74704ec27 | Python | 2,275 | 73 | from __future__ import annotations
from collections.abc import Iterator
from dataclasses import dataclass
from importlib import import_module
@dataclass(frozen=True)
class AppDefinition:
app_id: str
label: str
module_path: str | None
class_name: str | None
qt_supported: bool = False
descripti... |
5cead3508445e508599dc8cd6c3468f1a1f7c56ccc5300b50b03203726db9f7d | Python | 2,276 | 83 | from __future__ import annotations
from typing import TYPE_CHECKING
from typing import Any
import pytest
from poetry.publishing.hash_manager import HashManager
if TYPE_CHECKING:
from pathlib import Path
from pytest_mock import MockerFixture
from tests.types import FixtureDirGetter
@pytest.fixture
d... |
7f9626178f674ead0aa7a72281900b03e93abd9aa40f7eca48461e1130b02590 | Python | 2,276 | 66 | #!/usr/bin/env python
"""
This script will query a SMRTLink instance based on a provided set
of credentials, and pull a variety of run metrics for longitudinal
tracking. Notably, if an output file of the same name exists, it
will filter results by existing metrics to enable it to run quickly
as new runs are introduced... |
5c4dfd626ec078946258570c53caa63cab02dd442a7086ed36cb7f9821b4a101 | Python | 2,277 | 62 | """Tests for vak.predict.predict module."""
from unittest import mock
import pytest
import vak.cli.predict
import vak.config
import vak.common.constants
import vak.common.paths
@pytest.mark.parametrize(
"audio_format, spect_format, annot_format, model_name, predict_function_to_mock",
[
("cbin", None,... |
8a2db7e5439ec485d9b0ae56456e3d064be51dbc812a74078055b79584c4faae | Python | 2,277 | 65 | import numpy as np
import pytest
import torch
import scvi.external.velovi._module as velovi_module_module
from scvi.data import synthetic_iid
from scvi.external.velovi import VELOVI
from scvi.external.velovi._module import VELOVAE
@pytest.mark.optional
def test_velovi():
n_latent = 5
adata = synthetic_iid()
... |
20b8761a006b72640cbf3d20f703c1cc842c3891b52a5983fe60144774abb873 | Python | 2,279 | 67 | # Copyright 2018 Google Inc. All Rights Reserved.
#
# 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 a... |
a1e064629813d00c3f84074ac3b5c0a11c46b69ede0ecc9041d328cbdf68d30f | Python | 2,280 | 77 | import pandas as pd
from pgmpy.base import DAG
from pgmpy.datasets._base import BaseSimulatedDataset
from pgmpy.models import LinearGaussianBayesianNetwork
class LinearGaussianSCM(BaseSimulatedDataset):
"""
Simulates a dataset from a random Linear Gaussian SCM.
The random graph and its Gaussian paramete... |
7359cd003126bd30f516e267717b295a407f5f2b2c905d59f6296cc503c09a65 | Python | 2,281 | 78 | # @license
# Copyright 2017 Google 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 agreed to in... |
00c07c86463faec14b481203c9a630320388f7e3d33b7bda1b05ca3570315f38 | Python | 2,283 | 63 | # This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
import shutil
import tempfile
import unittest
from typing import Optional
class TestFileChunker(unittest.TestCase):
_tmpdir: Optional[str] = None
_tmpfile: Optional[str] = Non... |
88579fb7a638b639d7b2b617eaf1a7c477bcacd0dc13dcec34cde57874e6dfac | Python | 2,283 | 71 | #!/usr/bin/env python
import sys
import os
import numpy
if "DEBUG" in sys.argv:
sys.path.insert(0, "..")
sys.path.insert(0, "../../")
sys.path.insert(0, ".")
sys.argv.remove("DEBUG")
import unittest
from metax.DataSet import DataSet
from metax.DataSet import DataSetFileUtilities
from metax.DataSet im... |
1c18e15730f36196d044944ae351e9e9bbb295d704230dd414943b7334c7b399 | Python | 2,284 | 75 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import contextlib
import logging
import numpy as np
from fairseq.data.data_utils import numpy_seed
from . import BaseWrapperDataset
logger... |
74347da7855e81c5a2632890bf9047f3abd4b37a65e093daf04dccd2580ea36a | Python | 2,285 | 85 | from __future__ import annotations
import pytest
from poetry.utils import patterns
@pytest.mark.parametrize(
["filename", "expected"],
[
(
"markdown_captions-2-py3-none-any.whl",
{
"namever": "markdown_captions-2",
"name": "markdown_captions",
... |
9f0e41a72a15a7c9007a4b06a40455eb35b6e4956a793612fa9fdb7f5110e0f7 | Python | 2,287 | 71 | import os.path as op
from fetpype.pipelines.full_pipeline import (
create_full_pipeline,
create_rec_pipeline,
create_seg_pipeline,
create_surf_pipeline,
)
from fetpype.workflows.utils import (
init_and_load_cfg,
)
import pytest
import itertools
# 1. initialize will add config_path the config search... |
a919c59ab6a625521bc00a1ef58d6ff41fa63e002ccbd2a94d7b86a931a3f01b | Python | 2,287 | 85 | from screeninfo import get_monitors
import tkinter as tk
def center_window_on_screen(window):
"""
Center a Tkinter window on the screen.
Parameters:
- window (tk.Tk|tk.Toplevel): The window to center.
"""
window.update_idletasks() # Update "idle" tasks to get updated dimensions
x, y = w... |
80168784e22232598c06d7ad459aa44c1cf326c1ac4bf8a90e7e5e9ef5c6315e | Python | 2,288 | 70 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import logging
from pathlib import Path
from collections import defaultdict
import pandas as pd
from torchaudio.datasets impo... |
e2259b3bd5b19d9235a786e8e3fa94e7dde0251ac82d0fccfd01893c976bbfc2 | Python | 2,289 | 73 | #!/usr/bin/env python
# Copyright 2015 Google Inc. All Rights Reserved.
#
# 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 ... |
50d3824b1927ddc1f8860ad075faeb63bd97f859ce3369eefefab168679e4b81 | Python | 2,290 | 59 | import igraph as ig
import leidenalg
import numpy as np
from scipy.sparse.csgraph import connected_components
from scipy.stats import mode
from sklearn.neighbors import NearestNeighbors
from sklearn.preprocessing import LabelEncoder
import loompy
class PolishedSurprise:
def __init__(self, min_cells: int = 20, graph... |
2d3b47a8aefa5b89dd76c3057dd9d690b81ce734f388c20380abde44601fa553 | Python | 2,291 | 65 | from collections.abc import Hashable
import numpy as np
from pgmpy.structure_score.log_likelihood_gauss import LogLikelihoodGauss
class BICGauss(LogLikelihoodGauss):
r"""
BIC structure score for Gaussian Bayesian networks.
This score penalizes the Gaussian log-likelihood to discourage overfitting. The ... |
4519dbe77d8b2588672434cac42ca256932c1d714ed3ada3bbed6d27764f3e75 | Python | 2,291 | 57 | from typing import Sequence
import jax
import numpy as np
from ..molecule import Molecule
from .analysis import ScoreMatchingDensityModel, get_dft_grid
from .operators import AutoDiffDerivativeOperator, NumericallyStableKSPotentialOperator
def create_npz_density_file(
density_model: ScoreMatchingDensityModel,
... |
9c489c67ff733b1a9f09c7a2ec484fb17151e243810f34df0e8c09cacc51e11f | Python | 2,291 | 74 | from collections import OrderedDict
import torch
import spacestream.models as models
def get_slowfast_model(arch_name, trained, **kwargs):
"""
Inputs:
arch_name : (string) name of deep net architecture.
trained : (boolean) whether or not to load a pretrained model.
Outputs:
mo... |
7147ef15f5d03779b7c7dfd1f43ffb2adfd888bfb257a4a2436de2c5c7e4b902 | Python | 2,292 | 67 | import glob
import os
from PyQt5.QtCore import QObject, pyqtSignal
from mdt.gui.utils import UpdateDescriptor
__author__ = 'Robbert Harms'
__date__ = "2015-08-20"
__maintainer__ = "Robbert Harms"
__email__ = "robbert@xkls.nl"
class SharedState(QObject):
state_updated_signal = pyqtSignal(str)
def __init__(... |
9b2013b58bb678e12dd567b140af3e4ebaf50301dc01506466f614e6b81352ff | Python | 2,292 | 87 | from __future__ import annotations
from typing import TYPE_CHECKING
from typing import Any
import pytest
from poetry.core.packages.package import Package
from poetry.__version__ import __version__
from poetry.factory import Factory
from poetry.repositories import RepositoryPool
from poetry.utils.env import EnvManag... |
12dcb8461fe1a604a9b56d8cd7c8659a9e4f0d08c55f9757ef9f8352f9b828d9 | Python | 2,293 | 69 | """A paper curated under several BRENDA references is split as one paper."""
import importlib.util
import pathlib
from brenda_references.sampling import SPLITS, entity_holdout_splits
_SCRIPT = (
pathlib.Path(__file__).resolve().parents[2] / "scripts/generate_splits.py"
)
def _load_generator():
"""The gener... |
b1294c6d2c8aaf58a8457c70350c0c15ee51d63f9159c0a2cf97c9a8ee6b04d8 | Python | 2,294 | 79 | import numpy as np
from scipy.stats import entropy
import matplotlib
import pandas as pd
from scipy.stats import gaussian_kde
min_n = 100
max_n = 0
def get_model_bit_scores(model_name, min_n, max_n):
all_seq_score_list = []
f = open("./outputs/" + model_name, 'r')
for line in f:
line ... |
4c0512813547b69069bd4f56ce783683a571a564bb32db27a0e0b22ac0abd667 | Python | 2,295 | 82 | import gzip
import io
import pandas
from .. import Utilities
def try_parse(string, fail=None):
try:
return float(string)
except Exception:
return fail;
def skip_na(key, value):
skip = (not value or value == "NA")
return skip
def skip_non_rsid_value(key, value):
return not "rs" in... |
9c78116f13907423e71c135db8ae46955261f3aeb4b2b3e49734e1e8dee6004e | Python | 2,296 | 105 | """Functions for surface creation."""
# Author: Oualid Benkarim <oualid.benkarim@mcgill.ca>
# License: BSD 3 clause
from vtk import (vtkTriangleFilter,
vtkVertexGlyphFilter)
from .mesh_elements import get_edges
from ..vtk_interface.wrappers import BSPolyData
from ..vtk_interface.decorators import w... |
641979551ce17642ad05cfbc449f248e2ce34857bace0e1f066c1ef6a81c3c96 | Python | 2,297 | 62 | """Tests for ``aestetik.utils.utils_transcriptomics``."""
from __future__ import annotations
import anndata
import pytest
from aestetik.utils.utils_transcriptomics import preprocess_adata
# preprocess_adata uses scanpy's seurat_v3 HVG flavor, which calls
# `from skmisc.loess import loess`. We need scikit-misc to (a)... |
0bda4ec9a0d0b9a1ce0f107f51e6840b6741ab01714ff2222e9d336ad8fc45c8 | Python | 2,298 | 68 | from collections.abc import Hashable
import numpy as np
from pgmpy.structure_score.log_likelihood_cond_gauss import LogLikelihoodCondGauss
class BICCondGauss(LogLikelihoodCondGauss):
r"""
BIC structure score for Bayesian networks with mixed discrete and continuous variables.
This score penalizes the co... |
7946b33562040236dc8d69ccb25cfbbb75236522b4bc9f37e78c4d938ad28113 | Python | 2,298 | 70 | #%%
import os
import subprocess
from tqdm import tqdm
from concurrent.futures import ProcessPoolExecutor, ThreadPoolExecutor, as_completed
NUM_WORKERS = 14
DATA_DIR = "/home/thulasiseetha/research/dataset/curated/ChordomaMR/data/"
# Skull stripping, Tissue segmentation and radiomics feature extraction
def execute_co... |
35841f4f4ce1807cf9565dd5b895d768ba86f7663f50e8589a68c8570fb43b5f | Python | 2,301 | 86 | from typing import Sequence, TypeVar
import jax
import jax.numpy as jnp
import jax.tree_util as jtu
from jaxtyping import Array, ArrayLike, PyTree
T = TypeVar('T', bound=PyTree[ArrayLike])
def _is_leaf_pytree(x) -> bool:
return jtu.treedef_is_leaf(jtu.tree_structure(x))
def tree_scale(tree: T, x: ArrayLike) -... |
ff3ac1160aaa489c1cd9453d3687fb2c92ad00f85799456baafb8efb9af50e80 | Python | 2,302 | 69 | import unittest
import jax
import jax.numpy as jnp
from folx import batched_vmap
class BatchedVmapTest(unittest.TestCase):
def test_single_argument(self):
def fn(x):
return jnp.sin(x).sum()
x = jax.random.normal(jax.random.PRNGKey(42), (10, 3))
y = jax.vmap(fn)(x)
f... |
47fcbf9026e191b871914d95f194eabe3cd8ef06de4eab2290736c2c18c689a2 | Python | 2,303 | 54 | import re
from pathlib import Path
import qdarkstyle
from rnalysis.exceptions import InvalidTypeError, InvalidValueError
from rnalysis.utils import settings
FONTPLACEHOLDER = '$FONTPLACEHOLDER'
FONTSIZEPLACEHOLDER = '$FONTSIZEPLACEHOLDER'
PATHPLACEHOLDER = '$PATHPLACEHOLDER'
STYLESHEETS = {'base': None, 'light': qda... |
377e15389fb5a9e345e5b6109edcb0241c59bbcc5c0dc9a07401f7ce49a991ff | Python | 2,304 | 69 | # @license
# Copyright 2017 Google 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 agreed to in... |
aed8244e98b2fad384c038c0cba120741b6249f26a4b431dd48acd51f86e2ce6 | Python | 2,304 | 60 | from typing import Callable, List, Optional, Tuple
from pytorch_grad_cam.base_cam import BaseCAM
from pytorch_grad_cam.utils.model_targets import ClassifierOutputTarget
import torch
import numpy as np
"""
Weights the activation maps using the gradient and Hessian-Vector product.
This method (https://arxiv.org/abs/2501... |
6398ab051271994f9a3a3bccb8c0faca02ba56943ed145108ee3f56522fbde23 | Python | 2,306 | 68 | """Converts a Neuroglancer state to display a cross-section cube."""
import argparse
import neuroglancer
import neuroglancer.cli
import neuroglancer.coordinate_space
if __name__ == "__main__":
ap = argparse.ArgumentParser()
ap.add_argument(
"--cube-size",
type=neuroglancer.coordinate_space.pa... |
c90b011a7e00250e9f147a1192f30e7916cf3ce00c2d897af6c253936fa51166 | Python | 2,307 | 87 | import numpy as np
# Colours and types
Types = np.array(["T4", "T5"])
Type_colours = np.array(["#17becf", "#ff7f0e"])
Subtypes = np.array(["T4a", "T4b", "T4c", "T4d", "T5a", "T5b", "T5c", "T5d"])
Subtype_colours = np.array(
[
"#1f77b4",
"#9edae5",
"#98df8a",
"#bcbd22",
"#d6... |
cdd9240882c58e1746c495317b427fec5b411a80f8410fe67dce5dbfba64c02d | Python | 2,309 | 57 | import torch.nn as nn
import torch
'''
https://github.com/qiulinzhang/SPConv.pytorch
'''
class SPConv_3x3(nn.Module):
def __init__(self, inplanes, outplanes, stride=1, ratio=0.5, reduction=16):
super(SPConv_3x3, self).__init__()
self.inplanes_3x3 = int(inplanes*ratio)
self.inplanes_1x1 = in... |
5b028a25c5a64620198032738068cdb66950393caf9e6e998082b19b6de1d3b0 | Python | 2,311 | 75 | import vtk, qt, slicer
from math import sqrt, cos, sin
from .CircleEffect import AbstractCircleEffect
class AbstractDrawEffect(AbstractCircleEffect):
def __init__(self, sliceWidget):
# keep a flag since events such as sliceNode modified
# may come during superclass construction, which will
# invoke o... |
7dd49eee8b8f29f684f27b00d5bb502a47c4df3ddfc51dbf525a16ef8d982cea | Python | 2,311 | 74 | import networkx as nx
import numpy as np
import pytest
from pgmpy.base import DAG
from pgmpy.example_models import load_model
from pgmpy.metrics import FisherC
SEED = 42
N_SAMPLES = 1_000
EDGE_PROB = 0.1 # probability of an edge in the lower triangle
def _random_dag_with_same_nodes(model, rng, edge_prob: float = E... |
716651fda59d17c465c6efa6bdf09ae12864d4b372c1a6c61119c3318a71f991 | Python | 2,312 | 88 | import numpy as np
# Colours and types
Types = np.array(["T4", "T5"])
Type_colours = np.array(["#17becf", "#ff7f0e"])
Subtypes = np.array(["T4a", "T4b", "T4c", "T4d", "T5a", "T5b", "T5c", "T5d"])
Subtype_colours = np.array(
[
"#1f77b4",
"#9edae5",
"#98df8a",
"#bcbd22",
"#d6... |
db2b8cb203da624597716c21042cecf9240a3578c289383f9c5117ed1ae100e3 | Python | 2,312 | 63 | #!/usr/bin/env python
"""Regenerate `data/bacteria.txt` from ncbitax's bacterial species/genus index.
The previous `bacteria.txt` had no generation script anywhere in history and
had not moved since 2024-09-16; this replaces it wholesale with names drawn
from NCBI's own taxonomy dump (species + genus rank, division Ba... |
ec91e817bcd487893d5d6a23967429b7bbbf0604a645de1f66514a5b71b2abbb | Python | 2,313 | 66 | from collections.abc import Hashable
from pgmpy.structure_score.log_likelihood import LogLikelihood
class AIC(LogLikelihood):
r"""
AIC structure score for discrete Bayesian networks.
AIC balances discrete log-likelihood against model complexity using a sample-size independent penalty. The local
scor... |
49c2e227c879143ec37cc000c13958d90b777a5612d13d83fa57d5b615da7b83 | Python | 2,314 | 90 | import numpy as np
# Colours and types
Types = np.array(["T4", "T5"])
Type_colours = np.array(["#17becf", "#ff7f0e"])
Subtypes = np.array(["T4a", "T4b", "T4c", "T4d", "T5a", "T5b", "T5c", "T5d"])
Subtype_colours = np.array(
[
"#1f77b4",
"#9edae5",
"#98df8a",
"#bcbd22",
"#d6... |
9ae0d3cc20612536d81aa6ff95936d807afdcb4014267f799eae986cde4185af | Python | 2,314 | 90 | import numpy as np
# Colours and types
Types = np.array(["T4", "T5"])
Type_colours = np.array(["#17becf", "#ff7f0e"])
Subtypes = np.array(["T4a", "T4b", "T4c", "T4d", "T5a", "T5b", "T5c", "T5d"])
Subtype_colours = np.array(
[
"#1f77b4",
"#9edae5",
"#98df8a",
"#bcbd22",
"#d6... |
33c9b00ade8d10580ea596b109266baeff1f0fa98c1db7084bac8495865da2d5 | Python | 2,315 | 67 | from typing import Optional
import torch
__all__ = ["one_hot"]
# adapted from kornia, https://github.com/kornia/kornia/blob/master/kornia/utils/one_hot.py
def one_hot(
labels: torch.Tensor,
num_classes: int,
device: Optional[torch.device] = None,
dtype: Optional[torch.dtype] = None,
eps: float =... |
3436df2f2f5b496caed4f83cc4b98fb899c3ae63206fb2793c868398fa143ee4 | Python | 2,316 | 49 | """Run the unchanged Local SVG parser against repository fixtures and Lite output."""
import json
from pathlib import Path
import subprocess
import tempfile
import unittest
import cv2
import numpy as np
from generate_svg_parity_fixture import ROOT, local_harness
class LiteSvgParityTests(unittest.TestCase):
def t... |
5cb9765bef7d3e4f6f86cfcc6f30b2e346371c51c076239d3a89077248a3126d | Python | 2,317 | 66 | from ... import options as opts
from ... import types
from ...charts.chart import Chart3D
from ...globals import ChartType
from ...options import InitOpts, RenderOpts
class Lines3D(Chart3D):
"""
Lines 3D
"""
def __init__(
self,
init_opts: types.Init = InitOpts(),
render_opts: ... |
ae1b0b2370b3138410a9d2e7c44c9d73f2ea2d810c77db4c66a9de8bc7643de0 | Python | 2,317 | 68 | # _ _
# | | | |
# ___ __ _ __ _ ___| |_ ___ ___ | |___
# / __/ _` |/ _` / __| __/ _ \ / _ \| / __|
# | (_| (_| | (_| \__ \ || (_) | (_) | \__ \
# \___\__,_|\__,_|___/\__\___/ \___/|_|___/
'''
A Convergent Amino Acid Substitution identif... |
4993c11d9ed4ab71c37e0a03188916d91c052eed31d76b387e5c5fd98606e461 | Python | 2,318 | 64 | import jax
import jax.numpy as jnp
import numpy as np
from jax.experimental import enable_x64
from oneqmc.laplacian.folx_laplacian import ForwardLaplacianOperator
from oneqmc.physics import loop_laplacian
def test_dense_forward_laplacian():
key = jax.random.PRNGKey(42)
key, subkey = jax.random.split(key)
... |
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