sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
cc6751b13b072bb2316fa1eb3d95a94838526e1506a96b874908c8bd2c013272 | Python | 5,276 | 151 | import numpy as np
import pandas as pd
from scipy import stats
from sklearn.cross_decomposition import CCA
from pgmpy.utils import preprocess_data
from ._base import BaseCITest, _CITestResult, _ResidualMixin
class WilksLambda(_ResidualMixin, BaseCITest):
r"""
Wilks' Lambda CI test for mixed data [1].
T... |
93be6bad66cbb0e42fc4222d9515fb618c85ac46cbd11807c42c6bc94d351b3b | Python | 5,277 | 140 | # 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
from typing import List, Dict, Tuple
import panda... |
af86ead7a1399d02b987f5d12ec59caa7a9b941fc841fc9024357c8ed8917cb7 | Python | 5,278 | 132 | """Functions dealing with ``tensorboard``"""
from __future__ import annotations
from pathlib import Path
import pandas as pd
from tensorboard.backend.event_processing.event_accumulator import (
EventAccumulator,
)
from torch.utils.tensorboard import SummaryWriter
from ..common.typing import PathLike
def get_s... |
1969ab5034ebcb699eaa6ca42bcf549bc9bfd58f3e4107dd6789bfffe2037a6f | Python | 5,279 | 163 | import torch
import numpy as np
from celltype_ibl.utils.ibl_data_util import encode_ibl_training_data
from sklearn.metrics import balanced_accuracy_score, f1_score
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from sklearn.preprocessing import StandardScaler
fr... |
d1be8b7a69c3926b6e5643b96c4ca99fbdd409c162ce147ada53aadd6bc1cd65 | Python | 5,279 | 155 | import re
from pathlib import Path
from typing import Dict, List
import pandas as pd
from BLEval.evaluator import Evaluator
from BLEval.data import EvaluationData
def _parse_cpu_time(time_file: Path) -> float:
"""
Parse CPU time from a single GNU ``time -v`` output file.
CPU time is defined as the sum ... |
5ac9c5184a52b7508784bb640745b4e49d33c0463c8d2839466813d515df5a5d | Python | 5,285 | 151 | # Authors: Christian O'Reilly <christian.oreilly@sc.edu>
# Scott Huberty <seh33@uw.edu>
# Tyler Collins <collins.tyler.k@gmail.com>
#
# License: MIT
"""Helper functions for extending mne_bids functionality."""
from mne_bids import BIDSPath, write_raw_bids
# TODO: Add parameters and return.
def get... |
69b29daf304d097027829bb96332bd9d3b084168f6be1aa937d0de4c41f85014 | Python | 5,285 | 144 | #
# Copyright 2017 National Technology & Engineering Solutions of Sandia, LLC
# (NTESS). Under the terms of Contract DE-NA0003525 with NTESS, the U.S. Government
# retains certain rights in this software.
#
# See LICENSE for full license details
#
from __future__ import annotations
from dataclasses import dataclass
... |
5439924fc6c80d688056bc83a89428ca2ce7428423e6c56c0bab730f0239035c | Python | 5,287 | 131 | # -*- coding: utf-8 -*-
"""
.. _tutorial03_ref:
Tutorial 3: Types of Input Data
===============================
This tutorial covers what types of data can be passed to the `data` parameter
of the :func:`~brainspace.plotting.Plot.add_layer` method of
:class:`~brainspace.plotting.Plot`.
`data` accepts four different... |
9124dd488fcc30605b817d0b66f55c51bd3f0ea64644b8adb1712006e799d431 | Python | 5,289 | 139 | from ... import options as opts
from ... import types
from ...charts.chart import Chart
from ...globals import ChartType
class Custom(Chart):
"""
<<< Custom >>>
Custom series allows you to customize the rendering of graphical elements
in the series. This enables the extension of different charts.
... |
1b6b38d699ba22afe3786dc49c81b33975ccde6db80fffb49bff83b2f7f869d0 | Python | 5,290 | 152 | #!/usr/bin/env python3
"""G3 — latent interpolation between cell types.
Pick a pair of cell types (`--type-a`, `--type-b`), compute the per-class mean
posterior means μ_A, μ_B, and decode along z_α = (1−α)·μ_A + α·μ_B for
α ∈ [0, 1]. For each α, report:
- L2 distance of each decoded modality to the endpoint-decod... |
f99328ed6a17fa488eb281b4df9024bfb735993b2647385f240c04d835a7d5d8 | Python | 5,290 | 166 | import numpy as np
import pandas as pd
import pytest
from skbase.utils.dependencies import _check_soft_dependencies, _safe_import
from pgmpy import config
from pgmpy.factors.continuous import LinearGaussianCPD
from pgmpy.factors.hybrid import FunctionalCPD
from pgmpy.models.LinearGaussianBayesianNetwork import LinearG... |
f548c55936c08b6eb2c9a9d2d4bdcf65ea8d9c453ce5c2e6b0b314597b95e2af | Python | 5,293 | 136 | from __future__ import annotations
from inspect import signature
from typing import TYPE_CHECKING
import torch
if TYPE_CHECKING:
from collections.abc import Callable, Iterator
from typing import Any
from torch import Tensor
from scvi.module.base import LossOutput
def compute_elbo(
module: Cal... |
9a6ae06b22812f2c8fed8dc049778d194efa35eee561e7c0e3e9b2dff301eacd | Python | 5,295 | 132 | """ASE Calculator wrapping a fitted OCE model.
Exposes ``energy`` and ``forces`` so an OCE model can drive
``ase.optimize`` (geometry relaxation) and ``ase.md`` (molecular
dynamics) without changes to the wider ASE ecosystem.
Usage
-----
>>> from oce.atomic_table import load_table
>>> from oce.fit import build_design... |
9fff8c207d2c0f372df09e51031135c5e421afe0561dc47583d62b5885b53b5c | Python | 5,298 | 147 | """
For the tractogram of a bundle creates two masks: One for startpoints and one for endpoints.
Approach:
Use DBscan clustering for dividing all endpoints into start and ending. Uses only a subset of all points
because of runtime.
Then train random forest on those 2 clusters and use random forest to divide all points... |
30c916565529851f483bbed5842c5ffbae3d04b3623d16eec1a0afe622cfcff1 | Python | 5,299 | 154 |
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import os # Add this line to import the os module
def adc_to_current_acs712_20a(adc_value):
voltage = (adc_value / 1023) * 5 # Convert ADC to voltage
current = (voltage - 2.5) / 0.100 # 100mV/A for ACS712 20A
r... |
fc53091bbf514769c1479263c40c97e05e0c02d27bc399ee62173dcf29016af5 | Python | 5,301 | 178 | # -*- coding: utf-8 -*-
"""
Created on Sat Jul 27 11:34:21 2019
@author: 俊男
"""
# In[] Warning setting
import warnings
warnings.filterwarnings('ignore') # "error", "ignore", "always", "default", "module" or "once"
# In[] Root of Mean Square Error (RMSE)
from sklearn.metrics import mean_squared_error
import numpy as... |
658028a94707deaa7bc741e43f799c0092bc6e28a94c200a6af914b601ec5d39 | Python | 5,302 | 142 | """Property-based tests for the relation-loss weighting helpers.
`test_base.py` pins `balanced_class_weights` and `focal_cross_entropy` at a
couple of hand-picked batches. What they actually claim are properties over any
batch — finite when a class is absent, `gamma == 0` reproducing plain
cross-entropy exactly, the w... |
a5d9283934bd148bbd830ac8a3e171ebb85eef3b0d5a49266fc715a90e8abe32 | Python | 5,303 | 145 | import numpy as np
import pandas as pd
from scipy import stats
from sklearn.cross_decomposition import CCA
from pgmpy.utils import preprocess_data
from ._base import BaseCITest, _CITestResult, _ResidualMixin
class PillaiTrace(_ResidualMixin, BaseCITest):
r"""
Pillai's trace test for conditional independence... |
41401c227f0264c1676243d75b44589db4435bff44e55cc6c60d61d6e3d96b13 | Python | 5,306 | 169 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Function
#######################################################
# AITL Classes & Functions #
#######################################################
class FX(nn.Module):
def __init__(self, dro... |
a36d24f32c2cdd2e37b9c9dcd6b87704c0da53b433313c4a5220633fcd48f60d | Python | 5,308 | 94 | '''
Pure-python implementation of UCSC "liftover" genome coordinate conversion.
Main class, which is actually a convenience wrapper around chainfile.py's LiftOverChainFile
Copyright 2013, Konstantin Tretyakov.
http://kt.era.ee/
Licensed under MIT license.
'''
import os.path
import gzip
from .chainfile import open_li... |
a0037a50ce3c10903770302133ff830c579973bffadcc77ebd6e1b6a0d8e2d95 | Python | 5,311 | 168 | from __future__ import annotations
from types import SimpleNamespace
import pytest
from matplotlib.colors import to_rgba
from matplotlib.figure import Figure
from PySide6.QtWidgets import QApplication, QDialog, QLabel, QWidget
from src.features.behaviour_alignment.data_processing_widget import (
DataProcessingSi... |
f2cbfdc3341a876eb6657f705c4070a3f16c2a80eb93aee189c188286ee86dbd | Python | 5,311 | 152 | # 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 collections import OrderedDict
from typing import Callable, Dict, List
import numpy as np
from . import FairseqDataset
def uniform_sa... |
b07927b43f44afbfd61761c2cc69f1b68c4fbdeddb992db03ff0c73052518cd4 | Python | 5,312 | 132 | #!/usr/bin/env python
#
# Copyright 2008, 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... |
373f4c8c3a524e61e50ef88157fbe7e5b67302aa56636ffc8f93c541c63b5382 | Python | 5,313 | 132 | """tests for vak.learncurve.frame_classification module"""
import pytest
import vak.config
import vak.common.constants
import vak.learncurve
import vak.common.paths
def assert_learncurve_output_matches_expected(cfg, model_name, results_path):
assert results_path.joinpath("learning_curve.csv").exists()
for t... |
65be35dfbe74a2788a9b85ce5ca34c0788daa87f2c9dbbf53f8ad9577122e0fc | Python | 5,314 | 136 | import numpy as np
from celltype_ibl.utils.c4_data_utils import get_c4_labeled_dataset
from celltype_ibl.models.bimodal_embedding_main import concatenate_dataset
from celltype_ibl.models.linear_classifier import cross_validate
from sklearn.model_selection import RepeatedStratifiedKFold
import celltype_ibl.models.mlp_cl... |
943702f22a9df48533853459a67ee15df024d463effec8a5e32db7df81e8c228 | Python | 5,314 | 141 | # -*- coding: utf-8 -*-
# Title : model_entry.py
# Created by: julse@qq.com
# Created on: 2022/7/13 18:56
# des : 模型首行转换一次维度
from tkinter import Variable
import torch
import torchsummary
from torch import nn, Tensor
from model._0713 import mingpt
from model._0713.resnet import BasicBlock
class WrapLayers(nn.Se... |
d7f0dc92d3797f243da5c3a19bc3360c0d4095623f2485a57855c441bd596513 | Python | 5,314 | 142 | from __future__ import annotations
import numpy as np
import pandas as pd
from st_risk.models.base import BaseSpatialModelOutput
def _as_2d_array(values: np.ndarray | pd.DataFrame | pd.Series) -> np.ndarray:
if isinstance(values, (pd.DataFrame, pd.Series)):
array = values.to_numpy(dtype=float)
else:... |
228c6d7c7910d36321f7e2534ec4a4c15f257345a878db5397b63c4509775598 | Python | 5,316 | 197 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Finds yellow dots on PNGs"""
import os
from glob import glob
from typing import Optional, Generator
from pprint import pprint
import numpy as np
import matplotlib
matplotlib.use("QtAgg")
import matplotlib.pyplot as plt # noqa E402
from matplotlib.axes import Axes #... |
dbc073db78b417953621e34c8d85143133d7f3415da66c83ef2ec55065ad3a4c | Python | 5,316 | 123 | import numpy as np
import pandas as pd
from pathlib import Path
# Define paths
base_dir = Path('/egor2/egor/MovieProject2')
task_name = 'somatotopy'
output_per_subject_csv = base_dir / "bids_data/derivatives/group_analysis/somatotopy" / f"{task_name}_per_subject_motion.csv"
output_mean_csv = base_dir / "bids_data/deri... |
1b8c0d671f1bc2b76ab9cf4be9c9673d1ec7e7a366b22d3c826f95b70faf9716 | Python | 5,318 | 172 | from tqdm import tqdm
from typing import Tuple
from pathlib import Path
from pytorch_lightning import seed_everything
from utils.tokenization import Vocab
from model import MSATransformer
from dataclasses import dataclass
from hydra.core.config_store import ConfigStore
from dataset import RNADataset, RandomCropDataset
... |
053f506d8e48f7c27d0e3298249440cb560ebcc003b329f89108c8f464f802aa | Python | 5,319 | 168 | import os
import tempfile
import unittest
from unittest.mock import MagicMock, patch
from PIL import Image
from simulation_encoder.loaders.arcade_loader import ARCADELoader
def _write_images(directory, filenames):
"""Save real 10×10 greyscale PNGs to directory."""
for filename in filenames:
Image.ne... |
9a04f149cad31e76351c65fa5de2bc29d79796aba99a39cc9d5ae77dfa7b26e4 | Python | 5,319 | 155 | from math import ceil, floor
import numpy as np
import pytest
import scvi
from scvi.dataloaders import BatchDistributedSampler
from tests.data.utils import generic_setup_adata_manager
@pytest.mark.parametrize("batch_size", [128])
@pytest.mark.parametrize("n_batches", [2])
def test_batchdistributedsampler_init(
... |
fa0d855c6f23e55995f32c4bc145174004eb0610f947b8107c957cf433f4a6fb | Python | 5,320 | 160 | from collections.abc import Sequence
from pathlib import Path
import numpy as np
import pandas as pd
import torch
import torch.nn.functional as F
from jaxtyping import Bool, Float, Int, Num
from numpy.lib.stride_tricks import sliding_window_view
from torch import Tensor
def max_smooth(
arr: Num[np.ndarray, "batc... |
9e42dd2bcb2f2ae6ee2fcedcbd059055561a4336b4df3c911e7712b0567a41f0 | Python | 5,321 | 129 | """Supplemental Figure 5 — full cross-species method comparison (Lisberger → Hull).
Bar chart of KNN balanced accuracy for Lisberger (macaque) → Hull (mouse)
transfer, all methods including pretraining variants. Mirrors the main
Figure 5 panel B and adds HIPPIE WF+3D ACG with and without pretraining.
Evaluation rest... |
f913791f5551b27c07261a211c8b354e066340f86813ec8d6b43f831875bf714 | Python | 5,324 | 174 | """
Custom PyTorch Lightning callbacks for Garfield model training.
This module provides custom callbacks including a notebook-style progress bar
that mimics the original Garfield trainer logging format.
"""
import sys
from typing import Any, Dict, Optional
import pytorch_lightning as pl
from pytorch_lightning.callbac... |
116ba5a43fd901bf8d4e98d3866d8487551ed6f391ff826df755faac8b6c0882 | Python | 5,326 | 128 | # scSGL - a python package for fene regulatory network inference using graph signal processing based
# signed graph learning
# Copyright (C) 2021 Abdullah Karaaslanli <evdilak@gmail.com>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as pu... |
b34047c50742940f0a50e40fa4e64d6a827a18439c31a817c46302e417d1ebdb | Python | 5,326 | 113 | #!/usr/bin/env python3
"""Figuras 1 e 3 do manuscrito das perovskitas (a 2 é `fig_mecanismo.py`).
Fig. 1 — paridade do modelo completo, cor por haleto, com o viés dos iodetos
visível na própria figura em vez de só na Tabela IV.
Fig. 3 — curva de aprendizado das três referências (1F, Magpie, wave15), que
... |
5b38d8bee16ea10b4e0ae1258d77dcede065b2a7c9bd93215377edb93731e69f | Python | 5,329 | 187 | from typing import Optional, NamedTuple, Dict
import numpy as np
from .typed import PathLike
from .constants import IUPAC_CODES
from scipy.spatial.distance import squareform, pdist
import contextlib
from collections import defaultdict
class PDB_SPEC(object):
__slots__ = ()
ID = slice(0, 6)
RESIDUE = slice... |
b764dded3d4ac2feab3c3a427b813b8f394d243fe138a868fc3dff2b5651d67c | Python | 5,329 | 144 | # coding=utf-8
# Copyright 2019-present CNRS, Facebook Inc. and the HuggingFace Inc. team.
#
# 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
#... |
196eb03c8706027a6dcd918b6cf030388201df0b1f9f4d89039694522d4493de | Python | 5,330 | 158 | import numpy as np
from scipy.spatial.distance import pdist, squareform
import scipy.sparse as sps
def distcorr(X, Y):
""" Compute the distance correlation function
>>> a = [1,2,3,4,5]
>>> b = np.array([1,2,9,4,4])
>>> np.allclose(distcorr(a, b), 0.762676242417)
True
"""
def allsame(x):
... |
ce7372a7586a04748a2d02706b0fe5d3e2bfd8ce87da5bb9e51c67b7d3fff670 | Python | 5,330 | 145 | # coding=utf-8
# Copyright 2019-present CNRS, Facebook Inc. and the HuggingFace Inc. team.
#
# 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
#... |
94b0163540d910ca4c2b91fd9d75f7455dff72cee9c906c6bad9613d0953db90 | Python | 5,331 | 152 | """Function that generates new inferences from trained models in the frame classification family."""
from __future__ import annotations
import logging
import os
import pathlib
import lightning
import torch.utils.data
from .. import datapipes, models
from ..common import validators
from ..datapipes.parametric_umap i... |
0164db4c80cdfc52c8bc91c34cd7482c86e31f9485d66d6e21f2c099f267830c | Python | 5,334 | 133 | #
# 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 .iadc import IADC
from .iadc import get_digit
from simulator.backend import ComputeB... |
52203905c5d2632351a59978ff80efc908c4af17506df5babded5f8df9149ee9 | Python | 5,335 | 145 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# Copyright (c) 2018-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
import argparse
from utils import *
import sys
parser = argp... |
ec0429433cdb973e4c017cbf28ff75b26631f7e7272b9bbe5becedf0f7d506a3 | Python | 5,335 | 146 | import torch
import torch.nn as nn
import torch.nn.functional as F
from core.update import BasicUpdateBlock, SmallUpdateBlock
from core.extractor import BasicEncoder, SmallEncoder, twins_svt_large
from core.corr import CorrBlock
from core.utils.utils import coords_grid, upflow8
try:
autocast = torch.cuda... |
5155d02f969aa5e3470b4648da801800bb5f08411fa6116a8719763b07c9de23 | Python | 5,336 | 105 | import os
import numpy as np
import subprocess
from subprocess import Popen
from meld_classifier.tools_commands_prints import get_m
from meld_classifier.paths import FS_SUBJECTS_PATH
#Function to register individual cortical surface to fsaverage_sym
def xhemi_register(subject_id, verbose=False):
subjects_di... |
a3591817f59627847ebcd852e3ae061dfd5243c8211bfd119416184fc2ccda56 | Python | 5,336 | 148 | # 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 os
from omegaconf import OmegaConf
from mmpt.utils import recursive_config, overwrite_dir
from mmpt_cli.localjob impor... |
920a248de398f25b82362c89eaa35ba2c8fd77f0201d79d2bf3f8526dc25c701 | Python | 5,337 | 138 | import argparse
import os
from tqdm import tqdm
import numpy as np
import editdistance
from multiprocessing import Pool
from functools import partial
cer_langs = [x.strip() for x in open("cer_langs.txt", "r").readlines()]
def compute(w, feats, ref_lid, nbest_lid, ref_asr, nbest_asr, n=10, exclude=None):
assert le... |
96fac685e89203e9f6c058f12e2bba5dc9d78c6fffafe608a56185e44a32855a | Python | 5,338 | 173 | import numpy as np
from scipy.ndimage import gaussian_filter
from torchvision import transforms
from scipy.ndimage import zoom
class gaussian_smoothing(object):
"""
Smooths an autocorrelogram (acg) using a Gaussian filter.
"""
def __init__(self, sigma: int = 2):
self.sigma = sigma
def __... |
62e5397078837df20777818051120800af348b55c49881ab582ccaa2d469c72a | Python | 5,343 | 141 | from itertools import combinations
import pandas as pd
from sklearn.metrics import f1_score
from pgmpy.base import DAG
from pgmpy.ci_tests import get_ci_test
from pgmpy.metrics import BaseUnsupervisedMetric
class CorrelationScore(BaseUnsupervisedMetric):
"""
Score to compute how well the model structure rep... |
d074076a7ff37f6a96160714b92dc10bf7d81f3c94c1304b703ba0e4ec99c0fd | Python | 5,343 | 148 | """
This module contains generic trainer functionalities, added as a Mixin to
the Trainer module.
"""
import inspect
import os
import dill
import pickle
from copy import deepcopy
from typing import Optional, Union
import numpy as np
import torch
import scanpy as sc
from anndata import AnnData, concat
class BaseMixin... |
e8d63e3a1b2d47e3dc7600cdd06a41b6574448065c738595eee0eb17bab5c20a | Python | 5,343 | 164 | #!/usr/bin/env python
#
# Raspberry Pi Rotary Encoder Class
# $Id: rotary_class.py,v 1.3 2021/04/20 12:23:04 bob Exp $
#
# Author : Bob Rathbone
# Site : http://www.bobrathbone.com
#
# This class uses standard rotary encoder with push switch
#
# Some modification to made by Kirk Mulatz - to adapt it for use in this sce... |
6f35004af167d042e4b50e3d60417ae9bb7f1aecabd5cc4a00912afb363ac0b2 | Python | 5,345 | 172 | """
nfTranslator.py
Functions for translating NF (No Frontal) cap Source and Detector values
to regular cap configurations.
"""
import pandas as pd
import random
from typing import Tuple, Optional
# Define the tile mappings
nfSourceTile = {
1: [1, 2, 3], 2: [4, 5, 6], 3: [7, 8, 9],
4: [34, 35, 36], 5: [31,... |
f5bba9a4bfed04fbbdcb48593ee219f5637147bc91b3ab3596be88dc4d3902d5 | Python | 5,345 | 138 | #!/usr/bin/env python3
"""
Author: Ken Chen
Email: chenkenbio@gmail.com
Date: 2022-11-24
"""
import os
import sys
import json
import pickle
import gzip
from glob import glob
import argparse
from tqdm import tqdm
import numpy as np
import pandas as pd
from importlib import reload
from collections import defaultdict, Or... |
01b8c8e46a694ae80926cac0e72e769655dc25648d6f66f61265809da4ff5de1 | Python | 5,346 | 151 | import numpy as np
import pytest
import scipy.sparse as sp
from scvi.data import synthetic_iid
from scvi.external import JointEmbeddingSCVI
CCO_METRICS = {"cco_loss", "cco_invariance", "cco_redundancy", "variance_loss"}
N_LATENT = 5
def _get_adata(sparse: bool = False):
adata = synthetic_iid()
if sparse:
... |
4b811b7da7d6c87811ef605ca0d5246868ca350799183661bd7658e9295fb544 | Python | 5,347 | 148 | import numpy as np
import scipy.stats
'''
MIT License
Copyright (c) 2021 Nikita Kazeev
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the right... |
ef06a12438a6571e833e9b64172a69cd742bcfeba7043e6d5409917b347d7868 | Python | 5,347 | 168 | # 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 ctypes
import math
import sys
from dataclasses import dataclass, field
import torch
from fairseq.dataclass import FairseqDataclass
fro... |
4951199f91e80c60215b1dc32e5714db7a03695d346a85f71f642f759db37011 | Python | 5,348 | 123 | """Compute SIESTA-PBE decomposition energy for the 18 F-free endmembers
and recompute cross-correlation against Mannodi PBE / HSE06 decomp.
E_decomp(ABX3) = E_coh(ABX3) - E_coh(AX) - E_coh(BX2)
with each E_coh in eV per formula unit (each primitive cell here is 1 f.u.).
"""
from __future__ import annotations
import ... |
8ac9df8c43dafc32d675b72742b6894737de1e581e89301c619aa327f0353a5f | Python | 5,348 | 170 | import os
import json
from simulation_encoder.loaders.loader import Loader
from simulation_encoder.loaders.arcade_loader import ARCADELoader
from simulation_encoder.loaders.gastruloid_loader import GastruloidLoader
from simulation_encoder.loaders.alphanumeric_loader import AlphanumericLoader
from simulation_encoder.loa... |
020d4efe8907d06e9e224d9d880a51bb2e0c81cd9b8b6dcdc476b95a6ade605e | Python | 5,349 | 186 | import glob
import pdb
import random
import numpy as np
import pandas as pd
import h5py
import os
from sklearn.model_selection import StratifiedKFold
def read_csv(path):
# load sequences
df = pd.read_csv(path, sep='\t', header=None)
df = df.loc[df[0]!="Type"]
Type = 0
loc = 1
Seq = 2
... |
268aadd11eb5b6afc269b6bb60181a2b6e1de9a8a031234a48be1af156b1fa5d | Python | 5,349 | 133 | import torch
import torchvision.transforms as transforms
from torch.utils.data import DataLoader, Subset
from pipelines.dataloader import JacquardDataset
from modules.vgg16_baseline_longer import VGG16Baseline
from grasping_pvgg16_longer_bb import PVGG16SeparateHP as PVGG16
import toml
from modules.loss_functions impor... |
1b14fb6cd3153cbf33137ebee5bc340f9333bc488535374000f867a85b7c42d5 | Python | 5,350 | 146 | # coding=utf-8
import cv2
import random
import numpy as np
class HSV(object):
def __init__(self, hgain=0.5, sgain=0.5, vgain=0.5, p=0.5):
self.hgain = hgain
self.sgain = sgain
self.vgain = vgain
self.p = p
def __call__(self, img, bboxes):
if random.random() < self.p:
... |
cac8f2efec1bae3ded7bc334df5ab5d17ee24aab60c80bee7aca9246b3ac67ee | Python | 5,350 | 137 | # Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
from typing import List, Dict, Any... |
a7ebf2ba4f7630852fe090b600a18c43000d9cf7aae44d7722ef4eeab482af55 | Python | 5,352 | 150 | """Figure 3 — HIPPIE-bimodal and PhysMAP confusion matrices on A1 and S1.
Concatenates predictions across all 5 folds (HIPPIE) or across folds stored in
one CSV (PhysMAP), then plots row-normalized confusion matrices.
Outputs:
figures/25_figure_3_confusion_matrices/<dataset>_<method>_cm.{svg,png}
figures/25_f... |
7969d8bf79b704d6d7a76c93d672eaaf6c2d7a6a78ecd10e65b25868527a0dd8 | Python | 5,353 | 154 | """Unit tests for the per-step weight update and its gradient telemetry.
Kept apart from the model tests: the accumulators these drive
belong to `BatchUpdate`, not to the model it steps.
"""
import pytest
import torch
from d3text.training.update import GRAD_CLIP_NORM, BatchUpdate
@pytest.fixture
def update():
m... |
0655fb6bfdf0f0193194caedcf140663cb359f2a89adb1ceeea35f12850f7221 | Python | 5,354 | 143 | import pyro
import torch
from scvi.module.base import (
PyroBaseModuleClass,
)
from scvi.train import PyroTrainingPlan
class DecipherTrainingPlan(PyroTrainingPlan):
"""Lightning module task to train the Decipher Pyro module.
Parameters
----------
pyro_module
An instance of :class:`~scvi.... |
7b1ea90dfe81777bf76c1427686bf098847f9ce7883bda675168b837bb85a6d8 | Python | 5,357 | 152 | import importlib
import os
import types
from unittest.mock import MagicMock
import pandas as pd
import pytest
from sklearn.utils.estimator_checks import parametrize_with_checks
from pgmpy.causal_discovery import LLMPairwise
@pytest.fixture
def data():
return pd.DataFrame({"Smoker": [0, 1, 1, 0], "Cancer": [0, 1... |
8e0a024f02f1e155bc207ce757ae8528331d601a39bfc28175f869fb6bd84c57 | Python | 5,357 | 166 | # Copyright 2021 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
8e67f5522c18a93d94e208a829457b024be837639f05ebd2eddd8fd2edd71a07 | Python | 5,359 | 126 | from __future__ import annotations
from attrs import asdict, define, field, validators
from .. import common
def is_valid_accelerator(instance, attribute, value):
"""Check if ``accelerator`` is valid"""
if value == "auto":
raise ValueError(
"Using the 'auto' value for the `lightning.pyto... |
7bdbff0ea5e6f047fb4cfd0ea8afe93574c9b8798cefcd0b4d86556c0fb5a720 | Python | 5,362 | 154 | import h5py
import numpy as np
import torch
import scipy.io as sio
from scipy.signal import find_peaks
from DeepMathedFilterModel import DeepMatchedDetector
def compute_metrics(detected_peaks, target_peaks, tolerance=20):
detected_peaks = sorted(detected_peaks)
target_peaks = sorted(target_peaks)
tp = 0
... |
699e5f158d91840b0d6837a87a177994ddbce79e9de861872bdc44513be8e86e | Python | 5,365 | 157 | import logging
import random
import numpy as np
import scanpy as sc
import torch
from sklearn.decomposition import PCA
from sklearn.preprocessing import LabelEncoder
from gsMap.config import FindLatentRepresentationsConfig
from gsMap.GNN.adjacency_matrix import construct_adjacency_matrix
from gsMap.GNN.train import M... |
e5ce69e1c6b751612ee5f415028872f614a6debf10e65638dd3f7b503a548909 | Python | 5,366 | 138 | from argschema import ArgSchemaParser
import os
import logging
import subprocess
import time
import shutil
import numpy as np
import matlab.engine
from scipy.signal import butter, filtfilt, medfilt
from . import matlab_file_generator
from ...common.utils import read_probe_json, get_repo_commit_date_and_hash, rms
d... |
0d64ecde93a6ef25fb33e67edadc285c753aeb23198be9d84b396396cc358b6e | Python | 5,367 | 149 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import tensorflow as tf
from sklearn.utils import shuffle
tf.logging.set_verbosity(tf.logging.INFO)
from tensorflow.examples.tutorials.mnist import input_data
DATA_DIR = './data/fashion'
... |
546fab3931d2ae7b6a0ee06ff64c6bcedf2d58b460e5aa90be623b0895befe43 | Python | 5,367 | 155 | import logging
import typing
import torch
import torch.nn as nn
import torch.nn.functional as F
from .modeling_utils import ProteinConfig
from .modeling_utils import ProteinModel
from .modeling_utils import ValuePredictionHead
from .modeling_utils import SequenceClassificationHead
from .modeling_utils import SequenceT... |
dea1abaf737d087edad09a94b114db238c80841ee5ddd7c056c60f04790da0c7 | Python | 5,370 | 153 | import json
from sklearn.metrics import accuracy_score, roc_auc_score, precision_score, recall_score, f1_score, confusion_matrix, roc_curve, auc
import matplotlib.pyplot as plt
import numpy as np
import json
import seaborn as sns
import pandas as pd
import os
import numpy as np
import json
def compute_eval_metrics(lab... |
4a4664e16141410da0fc924c411188eff1b5d5cff0c91530088a0bbb19728a35 | Python | 5,371 | 163 | """
Projection Heads and MLP Modules
Various projection heads for self-supervised learning and downstream tasks,
including DINO, iBOT, contrastive learning, and general-purpose MLPs.
"""
# Copyright (c) ByteDance, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found... |
b4bbe6d83d7f88137db0d57d43cf31e8237ad401e10c04849befe18ae5d3d95a | Python | 5,371 | 124 | import os
import pytorch_lightning as pl
from pytorch_lightning import Trainer
from pytorch_lightning.callbacks import ModelCheckpoint, EarlyStopping, TQDMProgressBar
from pytorch_lightning.loggers import WandbLogger
import wandb
from argparse import ArgumentParser
from nft_datasets import ROIDataModule
from modules i... |
c3ab28aa52b1a211b8a73f83856b82d87a4cc2a84e83b8751044ee943d1bd600 | Python | 5,371 | 161 | import math
from collections.abc import Callable
import torch
import torch.nn as nn
import torch.nn.functional as F
def last_adaptive_avg_pool2d_in_module(module: nn.Module) -> nn.AdaptiveAvgPool2d | None:
"""Return the last ``AdaptiveAvgPool2d`` in depth-first order (typically the final global pool)."""
las... |
a9d99bbf8352f955d005628b383fdd704bde7a8fcdba4561709fefd6d6035c7e | Python | 5,372 | 130 | # 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 __future__ import absolute_import, division, print_function, unicode_literals
import logging
import math
import torch
import torch.nn.f... |
68cbf2036dffe2d2d7d42ef100b2db3a6b9519cd008e7b700e75a1c1e859748e | Python | 5,374 | 159 | from utils.dataset import (
BaseWrapperDataset,
)
from typing import Collection
from utils.dataset import CollatableVocabDataset
from utils.align import MSA
from typing import Union
from Bio import SeqIO
from utils.typed import PathLike
from torch.utils.data import DataLoader
from typing import Optional
from utils.... |
ff7a900ca1e980e608f4feca98a8348e859384ba538ef8612120fe102c92bb25 | Python | 5,374 | 113 | import matplotlib
from batchgenerators.utilities.file_and_folder_operations import join
matplotlib.use('agg')
import seaborn as sns
import matplotlib.pyplot as plt
import wandb
class nnUNetLogger(object):
"""
This class is really trivial. Don't expect cool functionality here. This is my makeshift solution to ... |
63366ce5e1dbe10f20b66eb7ff1f65b52f5a985216d881ebf0339d9f751b1bc5 | Python | 5,375 | 143 | from collections.abc import Callable
import rich.table
from anndata import AnnData
from mudata import MuData
from scvi._types import AnnOrMuData
from ._base_field import AnnDataField, BaseAnnDataField
class BaseMuDataWrapperClass(BaseAnnDataField):
"""A wrapper class that adds MuData support for an AnnDataFiel... |
a289c1d4f751b3970e79101362a07297183f031d5f4497cfa2685fac74c6cfa1 | Python | 5,375 | 182 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import glob
import os
import re
import ast
import sys
from os.path import join
from pprint import pprint
import numpy as np
from tractseg.libs.system_config import SystemConfig as C
def create_experiment_f... |
01c48dfa31cbf4e6b48c3e8a5203bd07ad5ed3fe70af57c289371ffb48bbcb89 | Python | 5,376 | 134 | """
The confounds module contains code to handle and account for
confounds in pattern analyses.
"""
import numpy as np
from sklearn.base import BaseEstimator, TransformerMixin
class ConfoundRegressor(BaseEstimator, TransformerMixin):
""" Fits a confound onto each feature in X and returns their residuals."""
... |
18be68f99c9259b1256b6ea22052d60bde712ca3cbbe911d3585df409aab5262 | Python | 5,378 | 165 | #!/usr/bin/env python3
"""
Verify that every ExperimentConfigs preset matches its expected feature schema.
Runs both as a pytest module (`pytest tests/test_configs.py`) and as a
standalone script (`python tests/test_configs.py`).
"""
import os
import sys
import pytest
# Add hippie to path
code_dir = os.path.abspath... |
7d87a79aa3eb72b01f0aaa8ac2055b6141304e6c940c76df29ac2a6aa8cb2192 | Python | 5,379 | 144 | #!/usr/bin/env python
# ENCODE DCC cross-correlation analysis wrapper
# Author: Jin Lee (leepc12@gmail.com)
import sys
import os
import argparse
from encode_common_genomic import *
from encode_common_log_parser import parse_xcor_score
def parse_arguments():
parser = argparse.ArgumentParser(prog='ENCODE DCC cross... |
678586f5092fa65fef0c17a420a596f403f9466cdbd7475147efea1ff7325315 | Python | 5,381 | 151 | # Copyright (C) 2025 ETH Zurich, Moritz Thürlemann, and other AMP contributors
import os
import json
import logging
from typing import Dict, Iterable
from openmm.app import ForceField, PDBFile, Modeller, Simulation, CutoffNonPeriodic
import openmm as mm
from openmm import unit as u
import tqdm
import numpy as np
def ... |
f293b01c2c9019bb1a4263af367197df2341f0ab2a24737bb3dc3275b63e8acc | Python | 5,382 | 147 | """
This notebook loads in videos of natural scenes collected via the video collection protocol,
and computes the response of a set of Gabor filters.
Author: Jonathan Gant
Date: 04.08.2023
"""
# import statements
import numpy as np
from tqdm import tqdm
import cv2
import glob
import os
import h5py
from decord import... |
6c6cc559f6d91bab7e60e29a46051cc2e40c6d4a3e3768db685fd355be2a7397 | Python | 5,383 | 100 | #! /usr/bin/env python
import os
import logging
import traceback
from metax import __version__
from metax import Logging
from metax import Exceptions
from metax import Utilities
from metax.gwas import Utilities as GWASUtilities
from metax.cross_model import Utilities as CrossModelUtilities
from metax.cross_model impor... |
b682a2c0919423f299004279f5ced1cc8e70ee4f3231218c3d118dcb5274cf01 | Python | 5,386 | 141 | import math
from functools import partial
from typing import Optional
import haiku as hk
import jax
import jax.numpy as jnp
from .basic import Constructor, MultiDimLinear, PsiformerDense, param_free_ln
class MaskedMessagePassingLayer(hk.Module):
def __init__(
self,
message_dim: int,
num_... |
077d23f873995089e6bcd6baf3ed824d57b211a5dbaa335458655bf31ea12d67 | Python | 5,387 | 149 | #!/usr/bin/env python
# coding: utf-8
"""
Script that generates the "source" test data
used to test the implementation of the DAS model.
This script should be run in an environment
created by the 'das-test-data-env' files
in ``./tests/scripts/``.
"""
import pathlib
import urllib.request
import das.data
import das.io
... |
41fb6d1810a861707941d70ae238424eb0c22729bfebfa05d25811046f30416c | Python | 5,387 | 133 | import argparse
import pandas as pd
import numpy as np
from typing import List, Tuple
def read_file(tsv_file: str) -> Tuple[List, pd.DataFrame]:
"""
Reads the input 4-column cosine similarity existing pairs TSV file in a pandas dataframe, generates all the unique PMIDs
and returns the dataframe.
Parame... |
b493e2c5c505102a3c5a438a9540615a6cd13eed5f28394d1c11d77d08e2124f | Python | 5,387 | 171 | #!/usr/bin/env python
# ENCODE DCC MACS2 signal track wrapper
# Author: Jin Lee (leepc12@gmail.com)
import sys
import os
import argparse
from encode_lib_common import (
get_num_lines, log, ls_l, mkdir_p, rm_f, run_shell_cmd, strip_ext_ta)
def parse_arguments():
parser = argparse.ArgumentParser(prog='ENCODE ... |
5012e5380b20815fbe44c72f00779d183687d7789be172c3ccf9abd17d503842 | Python | 5,391 | 133 | # ##############################################################################
# GPLv3 LICENSE INFO #
# #
# Copyright (C) 2020 Mario S. Valdés-Tresanco and Mario E. Valdés-Tresanco ... |
d31d1db69e4bad6df31deec6cfea0635a5ba85e3eed1469cbc50465a150de329 | Python | 5,393 | 141 | """What `load_split`'s `limit` counts, and what it scales with it.
A short run is meant to be a scaled-down run, not a differently-composed
one: the noise pools are appended after the real documents, so a `limit`
that does not shrink them leaves a slice that is mostly synthetic and
converges on nothing the whole corpu... |
18d78b0e87d7a8a6f433ff73f3579b87cacd2e18fd889e99dc9c1d2a144c3255 | Python | 5,395 | 129 | import polars as pl
from src.utils import read_gtf
from src.single_cell import SingleCell
import seaborn as sns
import matplotlib.pyplot as plt
import seaborn as sns
# Load transcript annotations
lr_bulk = SingleCell("results/long_read/pbid_filtered.h5ad")
pbid_to_transcript = lr_bulk.var\
.filter(
pl.col(... |
45eba48f04ea38f892701aaa63957113a4ee99b14294cf0d7876fa18af11f454 | Python | 5,396 | 171 | # _ _
# | | | |
# ___ __ _ __ _ ___| |_ ___ ___ | |___
# / __/ _` |/ _` / __| __/ _ \ / _ \| / __|
# | (_| (_| | (_| \__ \ || (_) | (_) | \__ \
# \___\__,_|\__,_|___/\__\___/ \___/|_|___/
'''
A Convergent Amino Acid Substitution identif... |
14b896062e524ffd2f5ec5bff8781e76e084a08d800c92840ffa3b853697bb65 | Python | 5,397 | 157 | # 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 json
import os
import re
import sys
import torch
from examples.speech_recognition.data import AsrDataset
from examples.speech_recognit... |
c2240dee81e978c309fa77372ebacc1e6e83c5d67fac9c7d88b21caf1d3dbd2d | Python | 5,397 | 146 | import os, re, math, torch
import numpy as np
from pathlib import Path
from rdkit import Chem
from scipy.spatial import distance_matrix
from torch_geometric.data import Data
from tqdm import tqdm
from rdkit import RDLogger
from concurrent.futures import ProcessPoolExecutor, as_completed
import warnings
warnings.filter... |
868ec06901f3ab7ac9b91c7deb82119d252c1674d6df114265e27089751013db | Python | 5,399 | 150 | import keras.backend as K
import theano
from keras.layers import TimeDistributed, RepeatVector, Permute
from model.layers_custom import AttLayer
theano.config.openmp = False
from keras.layers.core import Flatten, Reshape, Lambda
from keras.layers import Dense, merge
def get_similarity(similarity, params=None):
... |
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