sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
2f8e7e1ef70f5ca099c7da28619784061c9f9328db29ec7a49f8c7e3a03b5208 | Python | 869 | 22 | import pytest
from pgmpy.models import DiscreteBayesianNetwork
from pgmpy.structure_score import K2
class TestK2:
def test_score(self, small_df, small_df_models):
m1, m2 = small_df_models
scorer = K2(small_df)
assert scorer.score(m1) == pytest.approx(-10.73813429536977)
assert sco... |
6c20538112be2805d007f8bd5b9a78e5312a7256c6e86881665c9ef276bcd9df | Python | 869 | 31 | import pytest
from hashlib import md5
from time import localtime
from vak.common.constants import RESULTS_DIR_PREFIX
@pytest.fixture
def previous_run_path_factory(generated_test_data_root):
def _previous_run_path(model):
learncurve_results_root = generated_test_data_root.joinpath(
f"results... |
00707aba5a8e58333681aa338be355ff11d86baa20555f5b69d455c80315d87b | Python | 872 | 31 | from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser
from params import train, explain
modules = ['train', 'explain']
__version__ = "1.0.0"
def main():
parser = ArgumentParser(prog='pglcn',
formatter_class=ArgumentDefaultsHelpFormatter)
parser.add_argument('-v', '--... |
7e814129042d5bf578b99feaaf977ca4593e145d7634c62f503972eef8c99fb0 | Python | 872 | 27 | # 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 math
import torch
from torch.nn.modules.loss import _Loss
class HeadSelectionLoss(_Loss):
def __init__(self, args):
sup... |
860f59d9b316e3ca4968b11dc5f418867619117246a3e7bcbb2b9337d343c2be | Python | 872 | 34 | from pgmpy.datasets._base import BaseDataset
class Superconductivity(BaseDataset):
"""
References
----------
- :footcite:t:`uci_superconductivity`
"""
_tags = {
"name": "superconductivity",
"n_variables": 82,
"n_samples": 21263,
"has_ground_truth": False,
... |
97ad93d016347f970ee473dad3ab39b9bd3349123aa0204d5f87e2d24e2701bc | Python | 872 | 37 | from __future__ import annotations
from typing import TYPE_CHECKING
from tomlkit.toml_file import TOMLFile as BaseTOMLFile
if TYPE_CHECKING:
from pathlib import Path
from tomlkit.toml_document import TOMLDocument
class TOMLFile(BaseTOMLFile):
def __init__(self, path: Path) -> None:
super().__... |
13210297b96d5e33de1bee71d01551b025a600ff36a4a400bc49b1474c3b362d | Python | 873 | 22 | # 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 torch
src_ckpt = "/checkpoint/wnhsu/w2v/archived/hubert_base_ls960_it2.pt"
ref_ckpt = "/checkpoint/wnhsu/w2v/hubert_icassp_oss_v3/iter... |
a783833ba8dec9ecda3f99e132a43453fe82ad7d8868df3da81891d96d285522 | Python | 873 | 22 | import pytest
from pgmpy.models import DiscreteBayesianNetwork
from pgmpy.structure_score import AIC
class TestAIC:
def test_score(self, small_df, small_df_models):
m1, m2 = small_df_models
scorer = AIC(small_df)
assert scorer.score(m1) == pytest.approx(-15.205379370888767)
assert... |
d3c052c17cb91716fc73639453a824dd9b6d4ace720a3a4982748973b2832164 | Python | 873 | 22 | import pytest
from pgmpy.models import DiscreteBayesianNetwork
from pgmpy.structure_score import BIC
class TestBIC:
def test_score(self, small_df, small_df_models):
m1, m2 = small_df_models
scorer = BIC(small_df)
assert scorer.score(m1) == pytest.approx(-10.698440814229318)
assert... |
0876e69e118884c6d3dc164199c465ed42a11585f8a10e01668298ff867ceda5 | Python | 875 | 39 | # ------------------------------------------------------------
# Get Python package versions for reporting summary
# ------------------------------------------------------------
import sys
import importlib.metadata as metadata
import pandas as pd
packages = [
"numpy",
"pandas",
"scipy",
"scikit-learn"... |
d173fa68ddf9758445cbe51a3d5d4c5b2fede86733d012f8b6611917a5320dbc | Python | 875 | 35 | from __future__ import annotations
import pytest
from cleo.commands.command import Command
from cleo.exceptions import CleoLogicError
from poetry.console.command_loader import CommandLoader
class _DummyCommand(Command):
name = "dummy"
class _OtherCommand(Command):
name = "other"
def test_register_facto... |
ef9e63f00816f4ec6f68778e77732b6e57e6f16857a1bd8997ee3f94bbe08779 | Python | 875 | 29 | # 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 unittest
from tests.speech import TestFairseqSpeech
class TestXMTransformer(TestFairseqSpeech):
def setUp(self):
self.set... |
453a8146fad9cad30636553a1960dda6d64a5388accf7db5048f38e854698324 | Python | 877 | 36 | from pathlib import Path
import os
cwd = Path(".").resolve()
print("running 'check_installation.py' from:", cwd)
# Old versions of numpy/torch can prevent loading the .so files
import torch
print("torch:", torch.__version__)
import numpy
print("numpy:", numpy.__version__)
import fairseq
print("Fairseq installed a... |
b9c5e6b05c86cc734857f0f106ad09d69df218580f7d82b7dbd372f5e6639477 | Python | 877 | 37 | from __future__ import annotations
from typing import TYPE_CHECKING
from typing import ClassVar
from cleo.helpers import argument
from poetry.console.commands.command import Command
if TYPE_CHECKING:
from cleo.io.inputs.argument import Argument
class EnvUseCommand(Command):
name = "env use"
descripti... |
98afabedd16cb480de36500a1c6e660bedc3cda7071e594410a9b24cb7df785e | Python | 878 | 26 | """Regression test for `entity_stats`'s dict/list entity-shape branching."""
import pathlib
from tinydb import TinyDB
from tinydb.storages import JSONStorage
from scripts.statistics import entity_stats
TESTDB_PATH = pathlib.Path(__file__).parent / "test_files/testdb.json"
def test_entity_stats_reads_dict_and_list... |
077c25967da0f276fa7003675c2ea925b3a52ef51a5cdf3cbb8516efffbbb12a | Python | 879 | 27 | """Simulation Lightning datamodule wiring (registered via ``datasets.plugins``)."""
from __future__ import annotations
import os
from typing import Any
from omegaconf import DictConfig
from datasets.Simulation import ImagePatchDataset
def setup_simulation_datamodule(dm: Any, cfg: DictConfig, stage: An... |
e8d2f2c52a0319bf4f38d4c79f70b59d2cc387c9499eda922b2bfb0b77fd1889 | Python | 880 | 34 | from pgmpy.datasets._base import BaseDataset
class YachtHydrodynamics(BaseDataset):
"""
References
----------
- :footcite:t:`uci_yacht_hydrodynamics`
"""
_tags = {
"name": "yacht_hydrodynamics",
"n_variables": 7,
"n_samples": 308,
"has_ground_truth": False,
... |
7d96830a4c9ff0e01c333c1ad005fceafd569f469fa0823116b020a82d0f3946 | Python | 881 | 25 | # Authors: Christian O'Reilly <christian.oreilly@sc.edu>
# Scott Huberty <seh33@uw.edu>
# License: MIT
"""Tests for topo_viz.py."""
import mne
from pylossless.dash.mne_visualizer import MNEVisualizer
# chromedriver: https://chromedriver.storage.googleapis.com/
# index.html?path=114.0.5735.90/... |
875fa105527a64bfdd331d89ef1c384230e540320a4c3d766046f3c6aa9edb94 | Python | 881 | 35 | from pgmpy.datasets._base import BaseDataset
class AngristKrueger(BaseDataset):
"""
References
----------
- :footcite:t:`angrist_krueger_1991`
- :footcite:t:`angrist_krueger_qob_dataset`
"""
_tags = {
"name": "angrist_krueger_qob",
"n_variables": 5,
"n_samples": 32... |
35a2363827506b30ee9b6bd6427979d55dca22ac79551eb2386ad635af5f7344 | Python | 882 | 31 | import torch
import torch.nn as nn
class RadialFunction(nn.Module):
'''
Contruct a radial function (linear layers + layer normalization + SiLU) given a list of channels
'''
def __init__(self, channels_list):
super().__init__()
modules = []
input_channels = channels_list[0]
... |
4c000bd13e3408a405d3afce0f75b0454bed0637ce260490c3b940309a7393bf | Python | 883 | 39 | #!/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
def main():
anat = "${anatInputNii}"
nu = "${nuInputNii}"
atlas = "${atlasInputNii}"
dsts = []
for niigz in [anat, nu, atlas]:
nii =... |
fec55489f3c3ad5053275eae3b7a298ac9e34e0f66855c9a7821eb28a439477c | Python | 884 | 29 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
from tractseg.data import dataset_specific_utils
from tractseg.experiments.dm_reg import Config as DmRegConfig
class Config(DmRegConfig):
EXP_NAME = os.path.basename(__file__).split(".")[0]
DATASET = "HCP_all"
DATASET_FOLDER = "HCP_preproc_all"
... |
bd6e0067b210d30cd9ace7a4646eb1f233f92464a8e689b15fc07ee60f8d0c46 | Python | 888 | 31 | # 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 torch
class ScalarBias(torch.autograd.Function):
"""
Adds a vector of scalars, used in self-attention mechanism to allow
... |
fa25e2d8bbbdb835f469375d5a46d2bf53c432528196d2210c05228150d0bc70 | Python | 888 | 28 | # @license
# Copyright 2019 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... |
7f6f28dfd6d15318e850f866222a656f0f9e206dcbd36eeffa29bb936aa1a33a | Python | 890 | 31 | """Script for verifying the status of documents marked as not pmc_open."""
import asyncio
from aiotinydb import AIOTinyDB
from tinydb.middlewares import CachingMiddleware
from tinydb.storages import JSONStorage
from tqdm import tqdm
from brenda_references.config import config
from apiadapters.ncbi import AsyncNCBIAd... |
ba256828fb127f1b2d073ad9678e7c0778998acaef2b16c0fc7125888c9a09b3 | Python | 890 | 17 | __author__ = "alvaro barbeira"
from .. import Exceptions
from ..misc import KeyedDataSource
def gtex_snp(gtex_snp_file, gtex_release_version):
if not gtex_release_version:
gtex_snp = KeyedDataSource.load_data(gtex_snp_file, "VariantID", "RS_ID_dbSNP142_CHG37p13", numeric=False)
elif gtex_release_versi... |
6bb9adc59f3fc9110f19d7dcb4940f1ed6eaf29aeeb30a85409115394b3bbb81 | Python | 893 | 44 | from __future__ import annotations
from typing import TYPE_CHECKING
import pytest
if TYPE_CHECKING:
from pathlib import Path
from cleo.testers.command_tester import CommandTester
from poetry.utils.cache import FileCache
from tests.types import CommandTesterFactory
@pytest.fixture
def tester(comm... |
13d7c09fba4606bac79cb1f3fc2342f94a18b24515412432321689786b192167 | Python | 896 | 34 | import gl
gl.resetdefaults()
kframesperrotation = 180
gl.meshcolor(210, 148, 148)
gl.meshload('BrainMesh_ICBM152.lh.mz3')
gl.edgeload('LPBA40.edge')
gl.clipazimuthelevation(0.3, 0, 130)
gl.nodesize(6, 1)
gl.edgesize(3,1)
gl.nodehemisphere(-1)
gl.azimuthelevation(250, 35)
gl.edgecolor('actc',1)
gl.nodecolor('red',1)
gl.... |
8bac7748573c9e69054b287d52d2958f289eb9728e67e5b179dfa3cb68164e55 | Python | 897 | 34 | from __future__ import annotations
from typing import TYPE_CHECKING
from poetry.packages.dependency_package import DependencyPackage
if TYPE_CHECKING:
from collections.abc import Iterable
from poetry.core.packages.dependency import Dependency
from poetry.core.packages.package import Package
class Pac... |
9a2839b142f61c46b40f1b8900b6ed814a57fcede5b65dfdf4c5824f92aec441 | Python | 898 | 29 | import numpy as np
from pytorch_grad_cam.base_cam import BaseCAM
from pytorch_grad_cam.utils.svd_on_activations import get_2d_projection
class GradCAMElementWise(BaseCAM):
def __init__(self, model, target_layers,
reshape_transform=None):
super(
GradCAMElementWise,
... |
7f5a3a3787983eb4d23144559d6618a169d3d6fa75228cacbae2888d9cc5e0fd | Python | 899 | 32 | """
Simulate tree sequences
"""
import os
import zarr
import yaml
import numpy as np
import ts_simulators
indices = yaml.safe_load(open(snakemake.input.yaml))["indices"]
output_dir = os.path.dirname(snakemake.input.yaml)
config = snakemake.params.simulator_config
model = config["class_name"]
simulator = getattr(ts_... |
51e53b32fa01f821e98948a73eb39926d6bf5ba95bdee7378445dc4d380d9e52 | Python | 900 | 29 | from . import fixtures
# keep this import here, we need it for fixtures
from .fixtures import *
def by_slow_marker(item):
return 1 if item.get_closest_marker('slow') is None else 0
def pytest_addoption(parser):
parser.addoption('--dtype', action="store", default="float32")
parser.addoption('--slow-last... |
d9a4be7cc0d31959f48deb7675565f342349f8e8f3e0596f858eb562e0d90c4c | Python | 900 | 24 | import jax
import jax.numpy as jnp
from .loss import ClipMaskFunction
from .types import Energy, Mask
class MedianAbsDeviationClipAndMask(ClipMaskFunction):
def __init__(self, width, exclude_width=jnp.inf, balance_grad=False):
self.width = width
self.exclude_width = exclude_width
self.bal... |
bb28df4e0feea6e827edced2f385aba468193b9b1fcbd50253cff6a3c999ba9d | Python | 901 | 26 | import streamlit as st
from st_pages import add_page_title, get_nav_from_toml
st.image("logo.png")
main_page = st.Page("pages/help.py", title="Main")
extract_page = st.Page("pages/extract.py", title="Import MSI data", icon='🔍')
viewer_page = st.Page("pages/viewer.py", title="Viewer", icon='🔍')
pipeline_page... |
cfd0915945ee64739c9fd6ab764de7ea29ecc25a0618934185c4f46c2b913927 | Python | 901 | 24 | # Copyright 2022 InstaDeep Ltd
#
# Licensed under the Creative Commons BY-NC-SA 4.0 License (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://creativecommons.org/licenses/by-nc-sa/4.0/
#
# Unless required by applicable law or a... |
d322ee9b0c7b9dc790a65b7c18869346d2ea4c6d1910dfeaec15e22c4f3af37b | Python | 901 | 28 | import hashlib
from pathlib import Path
from typing import Union
def calculate_checksum(filename: Union[str, Path]):
assert Path(filename).exists(), f"file '{filename}' does not exist!"
with open(filename, 'rb') as file_to_check:
# read contents of the file
data = file_to_check.read()
... |
bbbcb5ad4f9b64d5c1ae959d3c5de4a4e2189cb6de3e15c0bbce17c76e161278 | Python | 902 | 30 | from .. import Exceptions
class ExpressionManager(object):
def expression_for_gene(self, gene): raise Exceptions.ReportableException("Unimplemented expression_for_gene")
def get_genes(self): raise Exceptions.ReportableException("Unimplemented get_genes")
def enter(self): pass
def exit(self): pass
clas... |
762c5765576a0cfa42f65aa3ca92f3cdb9d4be6bbef57b21d2b6914b2b0d5283 | Python | 903 | 31 | import numpy as np
import torch
from .._constants import Nums
@torch.no_grad()
def spectral_stats(z: np.ndarray) -> tuple[float, float, np.ndarray]:
"""Compute spectral statistics on a batch of embeddings.
Args:
z: A batch of embeddings of size `(B, O)`.
Returns:
A tuple containing:
... |
c1ea11843c33baaf9d6b0185d20f08086e919c0099b503065f54cc3f93317073 | Python | 903 | 31 | """Script for verifying the status of documents marked as not pmc_open."""
import asyncio
from aiotinydb import AIOTinyDB
from aiotinydb.storage import AIOJSONStorage
from tqdm import tqdm
from brenda_references.config import config
from brenda_references.utils import CachingMiddleware
from apiadapters.ncbi import A... |
b62014021f93d6563ddb3e6512f93639fa7be9fa0e734320483942bad02bb22d | Python | 904 | 41 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
from vlpp.utils import filename2dict, add_suffix
from vlpp.operation import computeSuvr, ImgStatsFromAtlas
def main():
os.mkdir("pet")
os.mkdir("centiloid")
os.mkdir("stats")
pet4070 = "${pet4070}"
pet5070 = "${pet5070}" #centiloid
ma... |
94b010d3099c2fbe5189d7d5dde01555882a72128a376b4d2a5d27c6453ee71a | Python | 906 | 38 | from __future__ import annotations
from typing import TYPE_CHECKING
from poetry.installation.operations.operation import Operation
if TYPE_CHECKING:
from poetry.core.packages.package import Package
class Install(Operation):
def __init__(
self, package: Package, reason: str | None = None, priority:... |
f7363bce1b01e4be63b5b5ac215509ee67d5df9863ae0ac433bf2d4573228da0 | Python | 906 | 24 | from typing import List
import numpy as np
def collate_outputs(outputs: List[dict]):
"""
used to collate default train_step and validation_step outputs. If you want something different then you gotta
extend this
we expect outputs to be a list of dictionaries where each of the dict has the same set o... |
e2490901d38633f7d1907f003eff84e54880ba1eb79e72ca6435226bddc2d4ba | Python | 907 | 33 | # for backwards compatibility, this was moved to scvi.data
from scvi.data import AnnTorchDataset
from ._ann_dataloader import AnnDataLoader
from ._anncollection import CollectionAdapter
from ._concat_dataloader import ConcatDataLoader
from ._custom_dataloaders import (
AnnbatchDataModule,
MappedCollectionDataM... |
d3ed843ba02ecff001a483193bdedc6449c88c97beac3249970b3df0ab53c5a1 | Python | 909 | 30 | # 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 torch
from fairseq.data import encoders
def get_whole_word_mask(args, dictionary):
bpe = encoders.build_bpe(args)
if bpe is n... |
e07873660ba65c57491da0f7ab91a31a0549acb40b2555a66a98ff86b5b8e571 | Python | 909 | 28 | rec.begin(
{
"dimensions": {"x": [8e-9, "m"], "y": [8e-9, "m"], "z": [8e-9, "m"]},
"position": [3242.833251953125, 3334.499755859375, 4045.5],
"crossSectionScale": 1,
"projectionOrientation": [
0.23160003125667572,
0.20444951951503754,
-0.017615893... |
e8103eb05d383366cfc3e876f8e8c7f2405ac65943a062a0851b78baa600b21a | Python | 910 | 35 | # import from plugins/cluster_view_styling.py
"""Show how to customize the styling of the cluster view with CSS."""
from phy import IPlugin
from phy.cluster.supervisor import ClusterView
class colorSelectorPlugin(IPlugin):
def attach_to_controller(self, controller):
# We add a custom CSS style to the Clu... |
547ece721d45473b4b14c015922e6c3a0ce3d45c2144e8f93dd7654b2e108e17 | Python | 913 | 32 | import numpy as np
from pytorch_grad_cam.base_cam import BaseCAM
class GradCAM(BaseCAM):
def __init__(self, model, target_layers,
reshape_transform=None):
super(
GradCAM,
self).__init__(
model,
target_layers,
reshape_transform)
... |
c7c22fb37abe9a88a5e055bc52ef75f56fcf10998b0eb5aede0d53d292655171 | Python | 913 | 44 | """
@file type.py
@author Simon Yu
@date 02/06/2023
@brief Global types.
"""
import enum
class LogLevel(enum.Enum):
all = 6
trace = 5
debug = 4
info = 3
warn = 2
error = 1
fatal = 0
off = -1
def __ge__(self, other):
if self.__class__ is other.__class__:
re... |
ac6f9c60c28b520482b44099d4e6343f56ed026028305bf1be068d9d3153c4e0 | Python | 916 | 28 | import numpy as np
import glob
import sys
from sklearn.cluster import KMeans
from sklearn.neighbors import KNeighborsClassifier
import joblib
paths = glob.glob(sys.argv[1] + "/*h.npy")
groups = []
data = []
for path in paths:
h = np.load(path)
data.append(h)
data = np.float32(data)
Percentile R... |
723a4dad95ade765a794f1a1ebc370822f7eaee477249478eb2abc484e77c5af | Python | 917 | 23 | import tskit
import argparse
###############################################################################
# read parameters
###############################################################################
if __name__ == '__main__':
parser = argparse.ArgumentParser(description="")
parser.add_argument("-i", "--Input"... |
f738db9c0b67f5b8aeee22c297bd849c3e64fd000a05d70ac5dedad971f5faad | Python | 917 | 24 | """Guards on the ad-hoc scripts that read and write the data files."""
import pytest
from brenda_references import data_paths as package
from scripts import pull_data
def test_every_script_agrees_with_the_package_on_the_data_dir() -> None:
"""One home for the path, or a writer misses every reader.
`pull_da... |
e118ac1eb48315c4741d610b74d48086ad7968e208722343bf64bc9b1bfce096 | Python | 918 | 27 | import unittest
from unittest.mock import patch
from pyecharts import options as opts
from pyecharts.charts import ThemeRiver
class TestThemeRiverChart(unittest.TestCase):
@patch("pyecharts.render.engine.write_utf8_html_file")
def test_themeriver_basefake_writer(self, fake_writer):
data = [... |
49f8c0ab679f14c761198945db1694ada6b6e56ff28ab48668a00d4b50a2ba46 | Python | 919 | 34 | from pathlib import Path
import pytest
REPO_ROOT = Path(__file__).parent.parent
SCRIPTS_DIR = REPO_ROOT / "scripts"
def pytest_addoption(parser):
parser.addoption(
"--pytorch",
action="store_true",
default=False,
help="Run tests that require PyTorch CNN training (slow on CPU, ski... |
aabcd42911438d06b19db1115b3f4ddc91c3c3d054dfc6ce170f362a26365aa5 | Python | 919 | 34 | """Common class for sequence datasets."""
from typing import Tuple
import torch
from Bio import SeqIO
from .sequence import (
Sequence,
CodonSequence,
AminoAcidSequence
)
class SequenceDataset(torch.utils.data.Dataset):
"""Common class for sequence datasets."""
def __init__(self, fasta_file: s... |
caff940c03c6b9036ee6bcb5429a04b599715776e5e2ebff81b6efbb93713f3a | Python | 920 | 23 | import time
import torch.utils.data as d
import torchvision
import torchvision.transforms as transforms
if __name__ == '__main__':
BATCH_SIZE = 100
transform = transforms.Compose([transforms.ToTensor(),
transforms.Normalize((0.5,), (0.5,))])
train_set = torchvision.datas... |
f967189bdf6d55fbc04c8c78930a45e3fdfbfbd9eb9f5df6e1a15623d1deee6f | Python | 920 | 28 | from src.dashboard.catalog import (
DEFAULT_APP_ID,
get_app_definition,
iter_app_definitions,
)
def test_feature_catalog_points_to_feature_entrypoints():
definitions = {definition.app_id: definition for definition in iter_app_definitions()}
assert DEFAULT_APP_ID == "raw_analysis"
assert defin... |
8fbe899687137095b2c4ddd12fc5fdde46ba7bb78771a71497d3943cc0373edf | Python | 924 | 29 | """Ownership boundaries for transient PyQt6 graphics items."""
from PyQt6 import sip
from PyQt6.QtCore import pyqtSignal
from PyQt6.QtWidgets import QGraphicsScene
def release_item(owner, name):
"""Forget first, then detach and destroy an exclusively held temporary item.
Scene ownership ends at removeItem()... |
9601fd7f2e9369fc1c7d3eca241c9d7fa6c8bc5f6e093e56c5da28211976cf2d | Python | 925 | 38 | from pgmpy.datasets._base import BaseDataset
class AppleWatchFitbit(BaseDataset):
"""
References
----------
- :footcite:t:`khan_2025`
"""
_tags = {
"name": "apple_watch_fitbit",
"n_variables": 18,
"n_samples": 6264,
"has_ground_truth": False,
"has_exper... |
a574f0127293f652027050baa6d2a2f29db3114c567aac5f63c592659d2259ac | Python | 925 | 30 | from typing import NamedTuple
class _SCVIVA_REGISTRY_KEYS_NT(NamedTuple):
SAMPLE_KEY: str = "sample"
Z1_MEAN_KEY: str = "latent_mean"
NICHE_INDEXES_KEY: str = "niche_indexes"
NICHE_DISTANCES_KEY: str = "niche_distances"
NICHE_COMPOSITION_KEY: str = "niche_composition"
Z1_MEAN_CT_KEY: str = "la... |
512fbae0751a31e314df18cc6bac9ebb63596c5368e3f7da8dac9f493003fcd7 | Python | 926 | 31 | """Basic plotting utilities for training curves."""
import os
import matplotlib.pyplot as plt
def plot_training_history(train_losses, val_losses, val_accuracies, out_dir):
os.makedirs(out_dir, exist_ok=True)
plt.figure(figsize=(8, 5))
plt.plot(train_losses, label="Training Loss")
plt.plot(val_losses... |
35acb495239bd9cd12404c97ee9e6b279661e21485d71c3fb9bbf38260c48189 | Python | 930 | 21 | """
Path management
"""
# Update with your path stem here!
path_stem = "/oak/stanford/groups/kalanit/biac2/kgs/projects/Dawn/streamlined/"
# This data path corresponds to the following project on OSF: https://osf.io/qy32x/files/osfstorage
DATA_PATH = path_stem + "data/"
RESULTS_PATH = path_stem + "results/"
# These f... |
43cfa76f224b7dfd0e6ad8bde92d815aef8f545b7383bb43c3e9cb4c4ca2cdea | Python | 930 | 33 | import numpy as np
from ._constants import Nums
class Settings:
# misc settings
auto_preprocessing: bool = True
disable_multimodal: bool = False
scale_to_microns: float = 1.0
def disable_lazy_loading(self):
"""Disable lazy loading of subgraphs in the NovaeDataset."""
Nums.LAZY_LO... |
51d4ed9ae31d668f11e466db41ff01b729dba7e40b55da0ec11bd7a486401fb2 | Python | 930 | 26 | from dipy.data import get_sphere
from dipy.reconst.shm import sh_to_sf
import numpy as np
def get_sf_range(data, sh_order, full_basis, sphere_name):
sphere = get_sphere(sphere_name)
sf = np.array([sh_to_sf(sh, sphere, sh_order, full_basis=full_basis)
for sh in data], dtype=np.float32)
v... |
c7c62a1a3eb2c26fc40625f78db490bd862cef8597e0bcc3880380c2c1501d50 | Python | 930 | 21 | _MAJOR = "2"
_MINOR = "2"
# On main and in a nightly release the patch should be one ahead of the last
# released build.
_PATCH = "2"
# This is mainly for nightly builds which have the suffix ".dev$DATE". See
# https://semver.org/#is-v123-a-semantic-version for the semantics.
_SUFFIX = ""
#_SUFFIX = "dev-2025-09-09"
V... |
9145570977e4988777e184ecbbbbc4b3cde15ffdaab348f1b8f55f4ab8555f0a | Python | 931 | 29 | import argparse
import math
from tqdm import tqdm
from Bio.SeqIO.FastaIO import Seq, SeqRecord
from tape.datasets import LMDBDataset
parser = argparse.ArgumentParser(description='Convert an lmdb file into a fasta file')
parser.add_argument('lmdbfile', type=str, help='The lmdb file to convert')
parser.add_argument('fas... |
a54367b354080bfe049f9dfb4aba3822a453d517702ec573c1471f0950cbd21c | Python | 931 | 34 | #!/usr/bin/env python3
#
# 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 sys
"""Reads in a fairseq output file, and verifies that the constraints
(C- lines) are present in the outpu... |
172ddedbe7107657872d1b3050f6f47526300bd4ead7ab413061c1ec6662faae | Python | 932 | 28 |
def normalize_deduplicate_and_order_strings(strings: list[str]) -> list[str]:
"""Normalize, deduplicate, and alphabetically order a list of strings."""
allowed_special_chars = "-'"
normalized_strings = [
clean_string(string, allowed_special_chars)
for string in strings
if string.s... |
34ab137e7c00c08ff0293deda09a57a9b3c0d9b74727aaf8504dfedfe6092cd1 | Python | 932 | 29 | """`rapidfuzz`'s upper bound must not silently harden into an exact pin.
`b6f6215` turned `rapidfuzz>=3.14.1,<4` into `rapidfuzz==3.14.1,<4` as a side
effect of an unrelated python-version change; nothing in that commit's
message mentioned rapidfuzz. An exact pin beside a `<4` upper bound is the
tell that survives suc... |
600da90f5779f1f333cfdd0fd4bb1dcda4c52d0c37f04f8e8ecf311fd01055d3 | Python | 932 | 34 | #!/usr/bin/env python
"""
# Author: Kui XU
# Created Time : Mon 3 Jul 2017 09:42:31 PM CST
# File Name: setup.py
# Description:
"""
from setuptools import setup, find_packages
with open('requirements.txt') as f:
requirements = f.read().splitlines()
setup(name='prismnet',
version='0.1.1',
description=... |
e9ed4c58f59719c17cb7b53a53d2827078ab6d4852d874453a9afca3762db1ab | Python | 933 | 30 | rec.begin(
{
"dimensions": {"x": [8e-9, "m"], "y": [8e-9, "m"], "z": [8e-9, "m"]},
"position": [3242.833251953125, 3334.499755859375, 4045.5],
"crossSectionScale": 1,
"projectionOrientation": [
0.23160003125667572,
0.20444951951503754,
-0.017615893... |
3b69ac12abb9d473ac91931f573bb43defe722bbdd6afc75d6ebea3f695c41be | Python | 938 | 28 | # utils/audio_utils.py
import numpy as np
def seconds_to_index(seconds, sample_rate):
"""Convert time in seconds to index based on the sample rate."""
index_size = int(seconds * sample_rate // 1000)
return index_size
def seconds_to_chunk_index(seconds, chunk_size, sample_rate):
"""Convert... |
57d64862e959e22f3e582048cf556381399fbcc50b8477c45e953cdaf0edfccf | Python | 939 | 36 | from __future__ import annotations
import argparse
import sys
from pathlib import Path
from st_risk.data.validate import validate_ready_directory
from st_risk.paths import project_root
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description="Validate a prepared ready-data directory.... |
7d21f43adef6d6a52dbe832fd0d22fce052bd83d1dacf5c13d4ebd68576670dd | Python | 939 | 40 | #!/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.
import argparse
import sys
from fairseq.data import Dictionary
def get_parser():
parser = argparse.ArgumentPa... |
2678ea86994ddbfa0f3b4cfe4e1699d41cfbeb582a02f48525c55304f8fe9f7c | Python | 940 | 36 | """Create individual experiment files for a parameter sweep."""
from itertools import product
from pathlib import Path
import yaml
def set_value(dct, keys, val):
for key in keys[:-1]:
if isinstance(dct, dict) and key in dct:
dct = dct[key]
else:
raise KeyError(f"{keys} do... |
f1c3c4ae2f704380d166dbad459df3f65cc5fa0a2d97ca58bb7817a2e6d6fbe6 | Python | 940 | 29 | """Utilities for grouper modules."""
__copyright__ = "Copyright (C) 2016-2017, DV Klopfenstein, H Tang, All rights reserved."
__author__ = "DV Klopfenstein"
import collections as cx
def get_hdridx_flds():
"""Return "hdr idx" named tuple fields used in Excel spreadsheets."""
return ["format_txt", "hdr_idx", ... |
686b0ef432d5bb27df04b1b2f2096bf3b11de3627c4302e5e952702e3fcfab2f | Python | 942 | 30 | from __future__ import annotations
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from poetry.core.packages.package import Package
from poetry.utils.env import Env
def format_build_wheel_log(package: Package, env: Env) -> str:
"""Format a log message indicating
that a wheel is being built for ... |
b39ad606d242753b9f61bac59d5cfdbbd59c9c7115da363452683af9676bf112 | Python | 942 | 34 | from __future__ import annotations
import pytest
from packaging.tags import Tag
from poetry.repositories.legacy_repository import LegacyRepository
from poetry.repositories.pypi_repository import PyPiRepository
from poetry.repositories.repository_pool import RepositoryPool
from poetry.utils.env import MockEnv
@pyte... |
b601decf2d370d9948b6d3027b69079fe193c53324a3e5697efe35152855a4ff | Python | 942 | 30 | import argparse
import webbrowser
import neuroglancer
import neuroglancer.cli
if __name__ == "__main__":
ap = argparse.ArgumentParser()
neuroglancer.cli.add_server_arguments(ap)
args = ap.parse_args()
neuroglancer.cli.handle_server_arguments(args)
viewer = neuroglancer.Viewer()
with viewer.tx... |
73cd5672064472496da808014c5c54849de5db37ae9c3b330e2b766894b2f008 | Python | 943 | 36 | from setuptools import find_packages, setup
setup(
name="spacestream",
version="1.0",
packages=find_packages(),
install_requires=[
"attrdict==2.0.1",
"deepdish==0.3.7",
"eagerpy==0.30.0",
"foolbox==3.3.4",
"geopandas==0.13.2",
"h5py==3.11.0",
"mat... |
614ab26f62b772a1c8ec8213cce1449bab0925f7056f9c1f8fb52600e8abcb33 | Python | 944 | 32 | #!/usr/bin/env python3
# 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 Union
from fairseq.data.dictionary import Dictionary
from .decoder_config import DecoderConfig, F... |
b5bfc9eb3e3f8858d892299e7da139d1134fdc63afe8f190ef80d685b0b30d15 | Python | 944 | 31 |
import loompy
import matplotlib.pyplot as plt
import numpy as np
from sklearn.metrics import balanced_accuracy_score
def decision_boundary(ds: loompy.LoomConnection, clf, transformed, y_true, score, out_file) -> None:
plt.figure(None, (10, 10))
plt.scatter(ds.ca.UMAP3D[:, 0], ds.ca.UMAP3D[:, 1], c='grey', alpha=... |
0d312a765ba62fd1880786e933ff0fa926ca7e5a807a0484dcad49189551ad0c | Python | 946 | 40 | from .check_functions import _check_1d_array_object, _check_length_equal
from .mathext import cartesian, sample_discrete
from .optimizer import optimize, pinverse
from .state_name import StateNameMixin
from .tabular import (
build_state_names,
collect_state_names,
encode_columns,
get_state_counts,
g... |
fb04639b7893ef817fdf0b96105fc76214bfed28189c45cd8537a01bdc84ed68 | Python | 946 | 30 | import numpy as np
import pytest
from pgmpy.factors.continuous import LinearGaussianCPD
def test_class_init():
beta = np.array([7, 13])
std = np.array([[4, 3], [3, 6]])
cpd1 = LinearGaussianCPD("Y", beta=beta, std=std, evidence=["X1", "X2"])
assert cpd1.variable == "Y"
assert cpd1.evidence == ["... |
743ba0d3300e65974ee3874af7ecc16b938265095d6ec7ddbceea9fafe54f219 | Python | 949 | 30 | from typing import Callable
import jax
import jax.numpy as jnp
SUPPORTED_FFN_ACTIVATIONS = ["gelu", "gelu-no-approx", "relu", "swish", "silu", "sin"]
def get_activation_fn(activation_name: str) -> Callable:
"""
Return activation fn given its name.
Args:
activation_name: Activation name.
Ret... |
8d53863bdf191d9c2cb59bb0352bbda188265103a323598596bcc03e3097fc9e | Python | 949 | 26 | from torch.optim.lr_scheduler import _LRScheduler
class PolyLRScheduler(_LRScheduler):
def __init__(self, optimizer, initial_lr: float, max_steps: int, exponent: float = 0.9, current_step: int = None):
self.optimizer = optimizer
self.initial_lr = initial_lr
self.max_steps = max_steps
... |
9cae04072b964805b6ee9ccbc99ff9a5ab0763f18d68ccc21c12e40f7ac3d5fc | Python | 949 | 33 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from vlpp.utils import splitext_, run_shell, warn
def main():
img = "${img}"
_, ext = splitext_(img)
output = "${participant}_input${suffix.pet}"
if ext == ".mnc":
run_shell("mnc2nii -nii -short {0} petconvert.nii".format(img))
#run_shel... |
c2e4c7f4965d7115907b869069e53cb4a72a96e61b67f79d0708a96abf64e4d0 | Python | 950 | 35 | # 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 setuptools import setup
with open("fm/version.py") as infile:
exec(infile.read())
with open("README_backup.md") as f:
readme =... |
84e2fa3c81fb2dd4bc7dafda70895bb44d44d591bfb323c16c15ceb466bb1c65 | Python | 951 | 32 | import py3Dmol
import qcelemental as qcel
from ..convert_geo import xyz_string
from ..molecule import ANGSTROM, Molecule
from ..types import MolecularConfiguration
def mol_conf_to_xyz(mol_conf: MolecularConfiguration) -> str:
assert mol_conf.nuclei.charges.ndim == 1
mask = mol_conf.nuclei.mask
return xyz... |
af394f4252d59912e27724105cc251618a3b9b340218fcd085131820cf1aa82a | Python | 952 | 31 | import torch
import numpy as np
class Dataset(torch.utils.data.Dataset):
def __init__(self, count_matrix, gene_ids, vocab, pad_value, batch_ids=None):
self.count_matrix = count_matrix
self.gene_ids = gene_ids
self.batch_ids = batch_ids
self.vocab = vocab
self.pad_value = pa... |
0197ca5967ebb7fb11c50989ffd9d79a68b941f733da603fb1e0a8725e8b6e36 | Python | 953 | 41 | from __future__ import annotations
from typing import TYPE_CHECKING
from poetry.installation.operations.operation import Operation
if TYPE_CHECKING:
from poetry.core.packages.package import Package
class Uninstall(Operation):
def __init__(
self,
package: Package,
reason: str | None... |
1b1c9516b80f3a2e19d79691d54f0383681daceeaa47876f73bc1d7415acf30e | Python | 953 | 39 | from pgmpy.datasets._base import BaseDataset
class ResidentialBuilding(BaseDataset):
"""
References
----------
- :footcite:t:`uci_residential_building`
"""
_tags = {
"name": "residential_building",
"n_variables": 109,
"n_samples": 372,
"has_ground_truth": False... |
51a7236b5bd48e2af2ad33d1b6f0bde44396b22a17d27fa0417e29eb4bbe8483 | Python | 953 | 24 | import numpy as np
def _setup_vmin_vmax(data, vmin, vmax, norm=False):
"""Handle vmin and vmax parameters for visualizing topomaps.
This is a simplified copy of mne.viz.utils._setup_vmin_vmax.
https://github.com/mne-tools/mne-python/blob/main/mne/viz/utils.py
Notes
-----
For the normal use-c... |
5e5ff3237fd7679e07b919efcfc8f7583b68285c3ea3588bae7d148ddfc52e48 | Python | 953 | 27 | OrderList = ['1234', '1324', '2134', '2314', '3124', '3214']
OrderList = ['ABC', 'BAC', 'ACB', 'CAB', 'BCA', 'CBA']
for i in range(6):
for j in range(2):
with open('Training_dataset_R%s_weights_length.tab' % (i*2 + j +1), 'r') as fin:
lines = fin.readlines()
with open('Training_dataset_R%s_%s_weights_length.ta... |
638342c3bedbbb9b7fdcfb0fa6e7b29a89253ea6583189cee4ad543c81c1dda9 | Python | 953 | 28 | # 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 numpy as np
import torch
from . import BaseWrapperDataset
class PrependDataset(BaseWrapperDataset):
def __init__(self, dataset, ... |
ed7ed75ee5b5060d8ba7628a3d595332f428512e9429a550d12a7d7571e61991 | Python | 953 | 25 | # Compare Koopman spectra for REST: remote (S1) vs recent (S2) -- ASCII only
import os, numpy as np
EXP_REMOTE = r".\exp_remote_rest\K_weight.npy"
EXP_RECENT = r".\exp_recent_rest\K_weight.npy"
def eigs(p): return np.linalg.eigvals(np.load(p))
def summary(name, w, thr=0.95):
m = np.abs(w)
print("{}... |
913cb1ba000e4c463a77128c00d2e8b1646fddd5bb1efcf35604cfe454b4d0ce | Python | 954 | 27 | # 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 torch
from .task import Task
class MILNCETask(Task):
def reshape_subsample(self, sample):
if (
hasattr(self.... |
da6a606c98787965e6412565d0e483feadf2296e2e2a8993831fd54496d15e0e | Python | 954 | 36 | # 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 dataclasses import dataclass
from fairseq.dataclass import FairseqDataclass
from fairseq.scoring import BaseScorer, register_scorer
@... |
169ef9b9a2896899d6aa80e9eb61b3ee3c8cf719c42fe9ddd4db5a8f597d366f | Python | 955 | 37 | #!/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.
import os
import argparse
import sys
parser = argparse.ArgumentParser()
parser.add_argument("--tsv", required=True... |
f072e55cd11100fa4f789e984c330716cd7428c25df0ed59409413fa241f38b3 | Python | 956 | 33 | from ..misc import GWASAndModels
class GF(object):
RSID=0
CHROMOSOME=1
POSITION=2
REF_ALLELE=3
ALT_ALLELE=4
FREQUENCY=5
FIRST_DOSAGE=6
def force_mapped_metadata(generator, sep):
for line in generator:
varid = line[GF.RSID]
allele_0, allele_1 = line[GF.REF_ALLELE], line[... |
6ab2641b5d2ceeca4659977b69d88a88eb1a95153071771fcd34088d406f16fe | Python | 957 | 25 | # Compare Koopman spectra for ENCODING: remote (S1) vs recent (S2) -- ASCII only
import os, numpy as np
EXP_REMOTE = r".\exp_remote_enc\K_weight.npy"
EXP_RECENT = r".\exp_recent_enc\K_weight.npy"
def eigs(p): return np.linalg.eigvals(np.load(p))
def summary(name, w, thr=0.95):
m = np.abs(w)
print("... |
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