sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
0e9a3a007dbbf2426dd1beaad2d1c5d3cbc2a433a5c6f4774eb30c39f0e98590 | Python | 6,731 | 173 | """3-state learning-curve comparison: n=93 → n=143 → n=193.
For each pool we report 5-fold CV metrics on:
(i) the full pool (with strain if present)
(ii) the non-strain subset (the fair, basis-suitable comparison)
This is the canonical AL learning curve for the perovskite OCE workflow.
"""
from __future__ import... |
2225a46398607167b004af54723428427092bc4e9b8f72ba929728fb15ea338f | Python | 6,732 | 199 | from pathlib import Path
from typing import List
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from sklearn.metrics import auc, roc_curve
from BLPlot.plotter import (
Plotter,
get_algo_ids,
iter_datasets_with_runs,
load_dataset_metric,
make_box_figure,
)
def _make_roc... |
1f0d09d1ade99d8528a8bd0a857c8a7a3728ad46f7a309b75396181d142d6d92 | Python | 6,736 | 168 | # 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... |
7b6bbe92066d804fa5d58a468f033225da0aacfebe59f279f02cc92b16489110 | Python | 6,736 | 150 | from typing import Callable, List, Optional
import numpy as np
import torch
import tqdm
from pytorch_grad_cam.ablation_layer import AblationLayer
from pytorch_grad_cam.base_cam import BaseCAM
from pytorch_grad_cam.utils.find_layers import replace_layer_recursive
""" Implementation of AblationCAM
https://openaccess.t... |
58cc327382e6d9e92ef543df7ceee20478b52855a9f75cba8c512d6206db161e | Python | 6,738 | 178 | from __future__ import print_function
from keras import activations, initializers, constraints
from keras import regularizers
from keras.engine import Layer
import keras.backend as K
import keras
class GraphLayer(keras.layers.Layer):
def __init__(self,
step_num=1,
activation=... |
847eb3210239890f34c8e36446a9bfc371ba48ce67eda87e36a8936c6da07a94 | Python | 6,738 | 189 | """Atomic orbital eigenenergy table built from xtb single-atom calculations.
Each element gets a list of (shell_label, eigenenergy_eV, occupation) tuples,
grouped by shell (s, p, d) — orbitals with identical eigenenergies are
collapsed into a single shell entry.
"""
from __future__ import annotations
import json
impo... |
519d6a3dc219b46009b9dff0f98fc4fc53a2add5c14f3eec201fb6e7f21a973a | Python | 6,741 | 261 | import numpy as np
import pandas as pd
import pytest
from joblib.externals.loky import get_reusable_executor
from pgmpy.causal_discovery import TAN
from pgmpy.example_models import load_model
from pgmpy.factors.discrete import TabularCPD
from pgmpy.models import DiscreteBayesianNetwork
from pgmpy.sampling import Bayes... |
9b87403a2c85a9ada2b343bff8d9933005c509361e169204548baad250bff88c | Python | 6,741 | 215 | #!/usr/bin/env python3
"""
Used for EMA tracking a given pytorch module. The user is responsible for calling step()
and setting the appropriate decay
"""
import copy
from dataclasses import dataclass, field
import logging
import torch
from omegaconf import II
from fairseq.dataclass import FairseqDataclass
try:
... |
95905e2e5eaecfa5ebe796afa5aa67b366f187b2dbc293fbcf6be477a032e40e | Python | 6,743 | 192 | from typing import Callable
import torch
from nnunetv2.utilities.ddp_allgather import AllGatherGrad
from torch import nn
class SoftDiceLoss(nn.Module):
def __init__(self, apply_nonlin: Callable = None, batch_dice: bool = False, do_bg: bool = True, smooth: float = 1.,
ddp: bool = True, clip_tp: f... |
eaea71bf194c63464c8e9dc5507fbfd4a2da8782a52a452ec455b49b7bb05195 | Python | 6,747 | 146 | '''
Compute the heatmap based on layer cell bins and their ABreelin occupancy over time
This code generates Figure 4 in the main manuscript
'''
import os
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
from matplotlib import gridspec
#Experimentally observed Lateromedial reeli... |
67061bfe13fd7bca549bc38498bcfccb8941ac5cfb67785cbdfb1f268a5746e9 | Python | 6,753 | 235 | #!/usr/bin/env python3
"""Base class for undirected graphical models in pgmpy."""
import itertools
import networkx as nx
class UndirectedGraph(nx.Graph):
"""Base class for all the Undirected Graphical models.
Each node in the graph can represent either a random variable, `Factor`,
or a cluster of rando... |
dc728c850afdcf7741ecf50638300bd7fce972528521e5ca632752f540b5b227 | Python | 6,756 | 224 | # build large-scale data in scBank format from a group of AnnData objects
# %%
import gc
import json
from pathlib import Path
import argparse
import shutil
import traceback
from typing import Dict, List, Optional
import warnings
import numpy as np
import os
import scanpy as sc
import sys
sys.path.insert(0, "../../")... |
5db5b6f33dbc3a90294a6bca1a89e66f379eab7283f15aff2d832df7e3fda1e5 | Python | 6,757 | 182 | from torch.utils.data import DataLoader, TensorDataset
from sklearn import preprocessing
from sklearn.model_selection import train_test_split
import pandas as pd
import numpy as np
import torch
class BINNDataLoader:
"""
A utility class for aligning data to the BINN network, preparing train/validation splits,
... |
67113df1ec5314a8dedefd4abd73cfeceb4d704311930e30fe3a86193ab63d75 | Python | 6,757 | 193 |
import os
import pathlib
import omegaconf
import wandb
from pytorch_lightning import Trainer
from pytorch_lightning.callbacks import (
EarlyStopping,
LearningRateMonitor,
ModelCheckpoint,
)
from datasets.data_module import DataModule, Infos
from diffusion_model import FullDenoisingDiffusion
from utils.dat... |
50f06b13e8894f624eacbb1d9a052f03365ee6cfc7a6422115d76f7ce66d7a94 | Python | 6,758 | 155 | import os, sys
import matplotlib.pyplot as plt
from itertools import chain, product
import numpy as np
import torch
import torchvision
from LibKIME.LibGeneral import (MakeFolder,
StartTimer,
StopTimer,
Save_dict2j... |
57d9912a842fafd9d3db9b6c07f131b625a12dbafca15978b6b59e68d69b1533 | Python | 6,759 | 215 | """
Multi-GPU Training Example for Garfield Model
This script demonstrates how to train the Garfield model using multiple GPUs
with PyTorch DistributedDataParallel (DDP) following PyTorch Geometric patterns.
Usage:
python train_multi_gpu.py
Requirements:
- Multiple CUDA-capable GPUs
- PyTorch with CUDA s... |
112071a4b6f4b87c6e4e34061496c583d6fa5c2c887592e9ca4aeab8cf4afeed | Python | 6,760 | 217 | # @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... |
688193d0713979c70d328529e40a52d1b8042e169c1d5dd8b97064eea58aaf1c | Python | 6,760 | 165 | import glob
import os
import time
import numpy as np
import argparse
from datetime import date
from os.path import join
import pandas as pd
from joblib import Parallel, delayed
import nibabel as nib
from nilearn import image, masking
from nilearn.glm.first_level import FirstLevelModel
def prepare_data(subj, configs):... |
252e8c333bcc3f5e944bce4fb41e98b27546861c5f7580cc0397cb9fb2c9cdc1 | Python | 6,761 | 156 | """
Set up the VCF prediction pipeline
"""
import zarr
import tskit
import os
import yaml
import numpy as np
from pysam import FastaFile
from numcodecs import Blosc
from math import ceil
import ts_simulators
vcz = zarr.open(snakemake.input.vcz)
n_variants = vcz.variant_position.size
n_samples = vcz.sample_id.size
n... |
e245d5a553caeddce495db04b3ccc8c6c5c374737bc4d19b85af5b08667ac4ba | Python | 6,763 | 176 | #!/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 argparse
import collections
import os
import re
import torch
from fairseq.file_io import PathManager
def ave... |
5513e4a6ec5630cb148d0d64078997676816bbfae75b6395dbeb157c010b982a | Python | 6,764 | 218 | # -*- coding: utf-8 -*-
# This file is part of Eigen, a lightweight C++ template library
# for linear algebra.
#
# Copyright (C) 2009 Benjamin Schindler <bschindler@inf.ethz.ch>
#
# Eigen is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published... |
8ab206ea9b80f7edb52ad581b81b0b664922680fb1304a0da6c22fe97a63bf77 | Python | 6,765 | 172 | # @license
# Copyright 2026 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... |
aae838e08303f0bbe67797840b66e031ed05c09a40ce1097c94d28dcc6c30994 | Python | 6,770 | 151 | import torch
import numpy as np
import torch.nn.functional as F
import torch.nn as nn
from utils import *
from self_calibration import *
from torch.fft import fftshift, ifftshift, ifft2, fft2
from fft_conv_pytorch import fft_conv, FFTConv2d
dtype = torch.float32
class forward_model_wf(nn.Module):
def __init__(sel... |
269ac4996857a573a27a76b1b6a06d7b388b8a60f5145ad91e5bac09417c361d | Python | 6,773 | 208 | import random
import unittest
import numpy as np
import pandas as pd
from tqdm.auto import tqdm
from pgmpy.models import LinearGaussianBayesianNetwork
from pgmpy.utils import (
discretize,
get_example_model,
preprocess_data,
)
from pgmpy.utils.mathext import sample_discrete
class TestDiscretization(unit... |
32389a47d296e035febe40a200832b999d74784bebf3df4a4be43fa971657ce9 | Python | 6,774 | 95 | MOUSE_EXL = {
# 0:HK06, 3:HK03, 6:194, 21:146, 29:114, 30:111, 35:095, 39:083, 54:038, 57:029
'609882': [59, [0, 3, 6, 21, 29, 30, 35, 39, 54, 57]],
# 12:463, 20:493, 21:496, 33:538, 34:541, 39:557, 41:563, 57:HK07, 58:HK08
'609889': [58, [12, 20, 21, 33, 34, 39, 41, 57, 58]],
# 6:956, 7:959, 8:962... |
3c4cd7dc850cd1badcc7bcc8fb10b6adaf31f6795d785b8914ceecf31073bbdf | Python | 6,774 | 179 | from __future__ import annotations
import warnings
from time import sleep
from typing import Optional
import numpy as np
import torch
import torch.distributed as dist
from batchgenerators.utilities.file_and_folder_operations import join, maybe_mkdir_p
from nnunetv2.configuration import default_num_processes
from nn... |
9283a76caf1a99721f81cc1942d63e8f3fa5b055f244ed9d23d81aa9559e2955 | Python | 6,774 | 139 | #!/usr/bin/env python3
"""A variância do seletor exige DUAS condições. Este script mede a segunda.
CONTEXTO. A dispersão do RMSE sob permutação das linhas de treino foi medida em dez
casos (perovskitas e QMOF) e não escala com a largura da base nem com o regime
p > n -- as duas hipóteses caíram. O que os logs mostram ... |
bfb55648ac422a8a4a3dd5fa45f90b85834a60e77724297d80f158da6935e20a | Python | 6,774 | 201 | from __future__ import annotations
import warnings
import torch
import torch.nn.functional as F
from torch.distributions import Gamma, constraints
from torch.distributions.utils import (
broadcast_all,
lazy_property,
logits_to_probs,
probs_to_logits,
)
from scvi import settings
from ._constraints im... |
128e8cce9801f52cf62fe77f5bb03f4d9b00167696887acbba8a46e5cc7b49ed | Python | 6,780 | 184 | # 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 .. import tasks
from .. import models
from .. import losses
from ..datasets import MMDataset
from .. import processors
cla... |
6f4a365cad3c234655ab8d55630ae05c1d885528e5f893b95a6d99a455737299 | Python | 6,781 | 175 | #!/usr/bin/env python3
# Florian Bénitière 16/03/2025
# This script processes VEP outputs per chromosome, extracts necessary columns
# and merges them into a PySpark DataFrame before saving the output as a Parquet file.
import os
import sys
import pandas as pd
import subprocess
import psutil # System and process ut... |
89e862f71a4fa80792b73d8792d27c563f9ae4de587aca7f8d9a1c1061ece84a | Python | 6,786 | 173 | """
Usage:
This scripts it to evaluate the classification accuracy/error rate from the embedding extracted
by gen_audio_embedding.py
Example (LID classification)
PYTHONPATH='.' python examples/wav2vec/eval_speaker_clf_task.py \
--data /fsx/androstj/exps/lid_voxlingua/infer/atj_xlsr2_100pct... |
9e1c4eb8ac873613b58793978e719fcfa465a8343225401892bb9de7fd4221bf | Python | 6,786 | 199 | # pgmpy/tests/test_base/test_mixin_roles.py
import pytest
from pgmpy.base import DAG
@pytest.fixture
def basic_dag():
G = DAG(ebunch=[("X", "Y"), ("Z", "Y")])
G.add_node("U")
return G
def test_with_role_single_variable(basic_dag):
basic_dag.with_role(role="exposures", variables="X", inplace=True)
... |
19a0b12a0a8d64425d2cd072f8076a513f4b3bee8ad88e17cc761601efba51eb | Python | 6,789 | 151 | import pandas as pd
import numpy as np
from preprocessor.utils.preprocess_axial import get_segment_iax, update_root_node
class AxialCurrentPreprocessor:
"""
Initializes the AxialCurrentPreprocessor class.
Initializes two primary DataFrames:
- axial_current: Stores calculated axial currents with a Mu... |
612e867dad4685449ff86268dcdffc97f932cf6304073fdbdfb6b14fa4c78ed4 | Python | 6,789 | 200 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from abc import ABC, abstractmethod
from math import pi
from typing import Optional, Tuple
import pytest
import torch
from mattergen.common.data.chemgraph import ChemGraph
from mattergen.common.diffusion.corruption import (
LatticeVPSDE,
... |
2cf949e6067f88384b46c836c8a5f028f22149bfcdae625b04fde38344ed26d6 | Python | 6,790 | 174 | import torch
import torch.nn as nn
import torch.nn.functional as F
import matplotlib.pyplot as plt
import numpy as np
import random
from dataclasses import dataclass
def noising(
data, xnoiselevel, ynoiselevel, threshold=0, noise_region='above', plot=True
):
x, y = data
x = x.numpy()
y = y.nump... |
4a5b698167679f1fde01e6f0c1e1cea149d7c909918d8c9b53d547cfb9b40297 | Python | 6,792 | 154 | #!/usr/bin/env python3
# MIT License
#
# Copyright 2020 Broad Institute
#
# 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 rights
# to use... |
2e87fc5ae6df986e92a390476be6cd52a1f89ff95ddd3d26c0ae6fea8f2568df | Python | 6,795 | 216 | from __future__ import annotations
import logging
from typing import TYPE_CHECKING
import numpy as np
from scvi import REGISTRY_KEYS
from scvi.data import AnnDataManager
from scvi.data.fields import (
CategoricalJointObsField,
CategoricalObsField,
LayerField,
NumericalJointObsField,
)
from scvi.modul... |
e531d0c18bd09f83cb57f0ea588bc1b4dc076186b082ac6ace4d9478bc0788aa | Python | 6,795 | 210 | # 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 importlib
from collections.abc import Collection
from dataclasses import dataclass, field
from typing import List
import torch
from fa... |
c515abded3f8d7e8fe3849b6f3f141996bec7632180d98070919ed48fbbe3432 | Python | 6,796 | 184 | #!/usr/bin/env python3
"""Run the Evo 2 Gene Completion benchmark (% amino-acid recovery).
For each gene in a panel the model is prompted with the start of the gene and
asked to complete it; the generated protein is recovered and compared to the
reference over the non-prompt region. See README.md for the methodology.
... |
c2596d515bb1b39b2e181d147a068dd5ee3e2904e4d5c010b94d200d1f1d8100 | Python | 6,800 | 181 | # coding=utf-8
# Copyright 2018 T5 Authors and 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
#
# Unless required by... |
fa0a6464ec38823323ae8a5ba538e36fa55f11b469d311400317878f83f39c09 | Python | 6,800 | 231 | """Matplotlib figure builders for raw-photometry analysis results."""
from __future__ import annotations
import numpy as np
import pandas as pd
from matplotlib.figure import Figure
from src.dfer.df_common import read_analysis_output
def _graph_time_values(axis) -> np.ndarray | None:
values: list[float] = []
... |
7f27dfb36966084044bdf70566886a1c6109cd87f154d2dd29c99de32650c982 | Python | 6,801 | 182 | # coding=utf-8
# Copyright 2018 T5 Authors and 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
#
# Unless required by... |
50f6febb2db918bb0279b34ac009571e41026bcb101c826182582f562e56032a | Python | 6,802 | 183 | import torch
from torch import nn
import torch.nn.functional as F
class ResizeConv1d(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, scale_factor, mode="nearest"):
super().__init__()
self.scale_factor = scale_factor
self.mode = mode
self.conv = nn.Conv1d(in_c... |
3753ea5826a004490f898a4192eb240f6a984bb3db6cf2c3807328da79b47ba1 | Python | 6,811 | 161 | import datetime
import logging
from copy import deepcopy
from os import makedirs
from os.path import join, exists
from posixpath import abspath
import numpy as np
import pandas as pd
import yaml
from sklearn.model_selection import StratifiedKFold
from data.data_access import Data
from model.model_factory import get_m... |
a78975f3221bc355295ee0098d2ccd752d4e10b44691514420297a6e6c3c393c | Python | 6,813 | 168 | """Compare 1F+2F (baseline) vs +CT2F on perovskite SIESTA pool (n=193).
Specifically targets the strain regime where 1F+2F got ρ=0.29 due to
topology-only blindness. CT2F is geometric-distance-binned and should
break this degeneracy.
"""
from __future__ import annotations
import json, re, sys
from collections import... |
f539e4dbc11880452ad6bb143267e69481ca3ba60143c14d696427fc024daa78 | Python | 6,816 | 207 | # Copyright (C) 2025 ETH Zurich, Moritz Thürlemann, and other AMP contributors
import time
import torch
import yaml
from datastructures.Graphs import Graph
from utilities.Utilities import (
scalar_product,
ff_module,
build_Rx2,
cdist,
pdist_sq_unsafe,
)
def load_parameters(filename: str):
fi... |
6f45c019df1a1b2ef6818f6f3d4c16672886dd2d5bfd7e79bd0d6a20631df645 | Python | 6,818 | 182 | #!/usr/bin/env python
"""Run `train` and keep the per-epoch timings it logs, as JSON.
`training/epoch_seconds` and `training/batches_per_second` are computed once an
epoch and handed to `tracking.log_metrics`, which is a no-op unless
`MLFLOW_TRACKING_URI` names a server — so a machine with no tracking server
runs the ... |
62268e1999a22e68f96324c470f3f87ebcd87d007a6811dc0e77c16796548586 | Python | 6,819 | 177 | import pytest
from pgmpy.base import ADMG, DAG, PDAG
from pgmpy.identification import BaseFormulaIdentification, BaseGraphicalIdentification
from pgmpy.identification.probability_expression import ProbabilityExpressionTree, ProbabilityNode
@pytest.fixture
def cg():
edges = [("U", "X"), ("X", "M"), ("M", "Y"), ("... |
2e378a9e52c15e2172dde57a3dd9967447309245045b66a3e7a1250e53891eda | Python | 6,822 | 255 | import pynwb
from contextlib import contextmanager
from datetime import datetime
from dateutil.tz import tzlocal
from uuid import uuid4
import numpy as np
@contextmanager
def open_nwbfile_local(file_path: str):
"""
Context manager to open and close a local NWB file.
Parameters
----------
file_pat... |
6b435c5babe90c1da7b62fce0eb0b1488ac4c624bceea3613128bd9bb06a4e82 | Python | 6,825 | 215 | # 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 copy import deepcopy
from dataclasses import dataclass
from typing import Optional
import torch
from fairseq.models.ema... |
2739beeba4db5cfadc17ff326e7b1981745264a959c8cb09b6be8fb44c020f92 | Python | 6,826 | 241 | # 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 os.path as op
import re
from tabulate import tabulate
from collections import Counter
def comp_purity(p_xy, axis):... |
84ad51c6475a173c646e8ff7ddc9f43da8a104f87784afee1889db25feaf1ad0 | Python | 6,827 | 176 | # -*- coding: utf-8 -*-
"""
Statistical comparison of the architectures.
The statistical unit is the participant: the cross-validation accuracies of a
participant are averaged into a single value before any test, so correlated
folds are never treated as independent observations. Each condition is analysed
separately; ... |
fd01df1121e3500da93fdb3b97adf7a5efb0535ba21540fff160537e6bd8e44d | Python | 6,831 | 170 | # 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 logging
from typing import Dict, List, Optional
from pathlib import Path
import torch.nn as nn
from torch import Tensor
from fairseq im... |
7bf54d67b42370537a8c11263764728afd61ea06e46d2e02e347b44d0edb29d3 | Python | 6,832 | 215 | """End-to-end integration tests modelled after the getting-started
notebooks, using the small simulated dataset ``test_data/A.h5ad``
(1000 spots, ``X_pca`` + ``image`` obsm pre-computed, ``ground_truth``
labels available).
These tests exercise the sklearn-style public API exactly the way the
notebooks do. Marked ``slo... |
501622e5edfd9b1cd19ac2b7cfbc0bc0a2e62deb41078ea69c43e671a9b234b1 | Python | 6,834 | 194 | from utility import *
import pandas as pd
from scipy.stats import zscore
import numpy as np
import os
"""
Author: Yuan Zhang
Date: 2026-04-13
This script performs receptor-based regression analysis using
the Mode 2 GMV weight map extracted from the joint CCA model
(math + reading combined model).
Specifically:
- l... |
56bfebb8c4e533df28ffaf369610b690becdb0448ddbde9913d164a39ee9c679 | Python | 6,838 | 224 | """
Compute linear CKA between MB18 task representations on NSD stimuli.
Uses the MB18 selected units (chosen_indices) and streams through images to
avoid storing full feature matrices.
"""
import argparse
from pathlib import Path
import numpy as np
import torch
from spacestream.core.feature_extractor import get_feat... |
5ea48f5857e3af9d2bc1b819d1668f2ec5f71a5afab172f03ca3bc9ef82e18fe | Python | 6,845 | 203 | """Tests fix_taxonomy reclassifying other_organisms into bacteria/strains."""
import copy
import logging
import pytest
import functools
from scripts import fix_taxonomy
from brenda_references.docdb import BrendaDocDB
from typing import Any
import pathlib
TESTDB_DIR = pathlib.Path(__file__).parent / "test_files"
TEST... |
fb28057e7e50f4cc75520bd02606b60d677b71aa9303c6768baf0ed5007f046b | Python | 6,851 | 143 | import os
import pandas as pd
from BLRun.runner import Runner
class SINGERunner(Runner):
"""Concrete runner for the SINGE GRN inference algorithm."""
def generateInputs(self):
'''
Function to generate desired inputs for SINGE.
If the folder/files under self.input_dir exist,
t... |
b86bcad9e6b6fb6fe6524eaf98ce5ef2f85c9325cfff30a176e3e24bb8d4f42a | Python | 6,856 | 159 | #!/usr/bin/env python3
"""
Author: Ken Chen
Email: chenkenbio@gmail.com
Date: 2022-11-24
"""
import json
import sys
import gzip
import numpy as np
from tqdm import tqdm
import torch
from torch import Tensor
from torch.utils.data import DataLoader, Dataset, Subset
import h5py
from transformers import AutoTokenizer
from... |
cef58813c9b3308733fd0b079a1f3a8366b2e996dec25457eb1233209228e4aa | Python | 6,860 | 137 | import os
import unittest
from collections import namedtuple
from medaka.common import Region
from medaka.labels import TruthAlignment
__truth_bam__ = os.path.join(os.path.dirname(__file__), 'data', 'truth_to_ref.bam')
__ref_fasta__ = os.path.join(os.path.dirname(__file__), 'data', 'draft_ref.fasta')
__ref_name__ = '... |
9c3590aed993f8b1893ab93023b3cad156a7178652aab2920515b658c3f1cde2 | Python | 6,861 | 175 | from md.Simulator import Simulator
import openmm as mm
from openmm import unit as u
from openff.toolkit import Molecule
import argparse
import os
import numpy as np
def current_cv(simulator, pullingForce):
cv1_value, cv2_value = pullingForce.getCollectiveVariableValues(simulator.simulation.context)
current_cv_... |
8ef35a106c54100523b6b2d1d8fc3dea48fe702fde450591e23202ae66fe1ea4 | Python | 6,865 | 173 | import unittest
import numpy as np
from pgmpy.factors.discrete import DiscreteFactor
from pgmpy.models import JunctionTree
from pgmpy.tests import help_functions as hf
class TestJunctionTreeCreation(unittest.TestCase):
def setUp(self):
self.graph = JunctionTree()
def test_add_single_no... |
3ead5d8a6bc424fe94c71e78d22201c692fc09141a0c87d88c9140552ca66146 | Python | 6,866 | 223 | # 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.
def gen_forward():
kernels = [3, 5, 7, 15, 31, 63, 127, 255]
blocks = [32, 64, 128, 256]
head = """
/**
* Copyright (c) Facebo... |
19eb1f6eaaebb32625459710cd996dfd12ffe14004d580d4508e1a15f8d77592 | Python | 6,868 | 126 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'UI/SchedGenUI.ui'
#
# Created by: PyQt5 UI code generator 5.5.1
#
# WARNING! All changes made in this file will be lost!
from pyqtgraph import PlotWidget
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_MainWindow(object):
def setu... |
3b9940fb9f419dc31ad725e97d910fa05996506398de86b6855857e67a9bce5d | Python | 6,869 | 217 | """Parametric UMAP model, as described in [1]_.
Code adapted from implementation by @elyxlz
https://github.com/elyxlz/umap_pytorch
with changes made by Tim Sainburg:
https://github.com/lmcinnes/umap/issues/580#issuecomment-1368649550.
"""
from __future__ import annotations
import pathlib
from typing import Callable,... |
b79a57f52ab3739b2750461708fa662594f283d788f18237e23d916791559a69 | Python | 6,870 | 201 | from pathlib import Path
from typing import List
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from sklearn.metrics import auc, precision_recall_curve
from BLPlot.plotter import (
Plotter,
get_algo_ids,
iter_datasets_with_runs,
load_dataset_metric,
make_box_figure,
... |
129cee2cc0d343559ca1579057b32788ac32582d40afc1f104db176b0a36206a | Python | 6,872 | 176 | # source: https://github.com/IndigoAI/SemanticSegmentation/blob/master/HRNet/OCR.py
import torch
import torch.nn as nn
import torch._utils
import torch.nn.functional as F
from OCRForClothes.HRNet.batchnorm import SynchronizedBatchNorm2d
BatchNorm2d = SynchronizedBatchNorm2d
import warnings
warnings.filterwarnings("ign... |
809f0e701fe6c6a42e481102032d7e15ee36a0485df47d27f66bdeda1e1aca14 | Python | 6,872 | 219 | """
Graph Neural Network encoder module.
Implements GCN-style message passing for network topology encoding.
"""
import numpy as np
from typing import Optional, List, Literal
from .utils import normalize_adjacency
class GNNEncoder:
"""
Graph Neural Network encoder using spectral convolutions.
Implement... |
2dc9eb5b591d88a84e748a76457d64d1f83f37e3e19ff310625b45d322533250 | Python | 6,873 | 203 | """
Regression utils adapted
(credit to Yamins lab: https://github.com/neuroailab/)
"""
import numpy as np
import scipy.stats as stats
from sklearn.model_selection import GridSearchCV
from spacestream.utils.general_utils import featurewise_norm, rsquared
# very trimmed down get_splits function
def get_splits(
d... |
54ce6415c7af073b01094a26c1900121816319b2321a340612cf862c5503ffe1 | Python | 6,874 | 169 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
"""
This is an integeratation test of reverse sampling. For a known data distribution that
is Gaussian, we substitute the known ground truth score for an approximate model
prediction and reverse sample to check we retrieve correct moments of the ... |
50b753e5e399fcfcbb9a8295688c639113e5ab50e703bc9fb076dc3476305ae9 | Python | 6,878 | 141 | #!/usr/bin/env python
# PYTHON_ARGCOMPLETE_OK
"""Fits a batch profile to a set of data.
This script can be used to fit multiple models to multiple datasets. It needs a batch profile with information
about the subjects. If no batch profile is given, this routine will try to auto-detect a good batch profile.
The most g... |
087ca0900d4ef281e9af8a97709d8a4d8c8e46352594883a6014eaaef36fb1bf | Python | 6,882 | 206 | # Copyright 2020 The Lucent Authors. 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 ... |
9834ef3b3c1453de6f0121ca98c3cac9e44b9a56986fac919a54a498f749ac33 | Python | 6,882 | 137 | """Execute the upload cell with Colab mocked; no network or training dependencies."""
import ast
import contextlib
import io
import json
from pathlib import Path
import sys
import tempfile
import types
import unittest
from unittest.mock import Mock, patch
import zipfile
ROOT = Path(__file__).resolve().parents[1]
def... |
5cd7e3763ac4aba405d59ac7e8c635776d2342b1ca1c43958bc47abb5aed6da6 | Python | 6,884 | 219 | import logging
import warnings
from collections.abc import Iterable as IterableClass
import anndata
import numpy as np
import pandas as pd
from scvi import settings
from scvi.data._constants import _ADATA_MINIFY_TYPE_UNS_KEY, ADATA_MINIFY_TYPE
from scvi.utils import track
from ._differential import DifferentialCompu... |
131463a1ff12f0c53b14ae976ccf57d2b12988e3c8c1f32de52499c237768d64 | Python | 6,890 | 131 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'UI/CorrUI.ui'
#
# Created by: PyQt5 UI code generator 5.5.1
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_Form(object):
def setupUi(self, Form):
Form.setObjectName(... |
cee0e899ac59c37bd8d529916f77ed8b6e34f86eb47a1e09b89a34a1bd072006 | Python | 6,890 | 186 | import os
import readline
import numpy as np
import pandas as pd
from scipy.stats import chi2
def set_confounds_type(confounds):
if pd.isna(confounds):
return 'None'
else:
return 'all'
def set_confounds_type_detail(confounds):
if pd.isna(confounds):
return 'None'
else:
... |
04a84ae159c40d6ef1e373ad548f9a02c058c6aa43ee4215e958a124bf23bdaf | Python | 6,893 | 191 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Transforms data, for subsequent classification"""
from pathlib import Path
from typing import List, Optional
import numpy as np
import pandas as pd
from utils.models import Cell
def get_features_one_cell(cell: Cell, features: List[str]) -> np.ndarray:
"""Gets f... |
38ff1e65b9883fa7c5bd4dc3f320c8dfe35296c08a9bd4f48a671189b922d617 | Python | 6,893 | 222 | from typing import Optional, Any
import torch
from torch import nn
from torch.utils.data import DataLoader
from simulation_encoder.logger import ExperimentLogger
DEBUG = False
class BaseCNN(nn.Module):
"""
Base convolutional neural network class.
Parameters
----------
logger : Logger, optional... |
7649ccc66070d73344ffdb6884f4d7d4e6cf7c1c5330c57c41bbd9de1112578d | Python | 6,893 | 221 | from __future__ import annotations
import warnings
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from collections.abc import Callable
from typing import Literal
import numpy as np
import torch
from torch.nn import (
Linear,
Module,
Parameter,
)
from scvi import settings
from scvi.distributi... |
7cd6b1356c01d926f11b97a0bb0a4a2efbc716e0ed844efcbab79a44cdeb0979 | Python | 6,894 | 226 | from __future__ import annotations
from copy import deepcopy
from dataclasses import dataclass
from importlib import resources
from itertools import count
from typing import Any, ClassVar
import jax
import jax.numpy as jnp
import numpy as np
import qcelemental as qcel
import yaml
from .types import Embeddings, Molec... |
d48c2f013a4792262604960434cb9a5b2cd773127ace9b9b87782b6e2b4955a6 | Python | 6,896 | 217 | # 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... |
63983782d22e38217c610c1e6c47d0a1db7f5ba752cdb8dd46d95a4a0bdfb179 | Python | 6,898 | 122 | import logging
import re
import os
import pandas
import numpy
from . import GWAS
from .. import Exceptions
from .. import Constants
from .. import Utilities as BUtilities
def add_gwas_arguments_to_parser(parser):
parser.add_argument("--snp_column", help="Name of -snp column- in GWAS input file", default="SNP")
... |
6d2a70a69c9d7974e272ee39696fa909b4cc15aa1dba3938a22202b8bb1ee096 | Python | 6,899 | 193 | import random
import unittest
from pyecharts import options as opts
from pyecharts.charts import Bar, Bar3D, Timeline
from pyecharts.commons.utils import JsCode
from pyecharts.faker import Faker
def get_bar_3d_chart(i: int):
data = [(i, j, random.randint(0, 12)) for i in range(6) for j in range(24)]
c = (
... |
239a97b701c568672991145cee4953265dbc98b60ffd4dd104b818dc67fbdfe4 | Python | 6,910 | 205 | import logging
import os
from functools import partial
from typing import Dict, NamedTuple, Optional, Sequence
import jax
import jax.numpy as jnp
from tqdm import trange
from oneqmc.density_models.analysis import ScoreMatchingDensityModel
from oneqmc.density_models.base import (
DensityFittingBatchFactory,
De... |
599048a8b00f5b0d68a6adf9709df12ebda84dda4fee37f2cfe71c5d4e3c8e60 | Python | 6,913 | 201 | from pathlib import Path
import numpy as np
from math import ceil
from fairseq.data.audio import rand_uniform
from fairseq.data.audio.waveform_transforms import (
AudioWaveformTransform,
register_audio_waveform_transform,
)
SNR_MIN = 5.0
SNR_MAX = 15.0
RATE = 0.25
NOISE_RATE = 1.0
NOISE_LEN_MEAN = 0.2
NOISE_... |
09926fc47c977383963d68f0082f6e62dc3f58c1d70e4c9abd744b1567a53911 | Python | 6,916 | 189 | import pytest
import torch
import numpy as np
import pandas as pd
import torch.nn as nn
from binn.analysis.explainer import BINNExplainer
from binn import BINNTrainer
class DummyModel(nn.Module):
"""
A dummy model to mimic a trained BINN.
It needs the following attributes:
- device (a string, e.g., ... |
ca33b919b80d375b59ecd4c7ef723450ed2e5de538bcb8f36bdaf787b97cbde6 | Python | 6,916 | 181 | from __future__ import annotations
import json
import logging
from pathlib import Path
import lightning as L
import numpy as np
import pandas as pd
import torch
import torch.nn.functional as F
from anndata import AnnData
from fast_array_utils.conv import to_dense
from sklearn.decomposition import PCA
from sklearn.nei... |
18a101532d1a8d0dc22777c04f8c19ff1d0bbe9ec91b8ed70440e3d177b43823 | Python | 6,917 | 204 | import numpy as np
from itertools import product
import matplotlib.pyplot as plt
from collections import Counter
from scipy.stats import permutation_test, ks_2samp
class ConfusionVarianceMatrix:
def __init__(self, cm_array, display_labels=None):
self.cm_array = cm_array
self.display_labels = displ... |
610b4f4221c49d126a58ff968ac5e5302cda7a13c165a6a97ea67705c72d5270 | Python | 6,917 | 203 | """
Copyright (c) Facebook, Inc. and its affiliates.
Copyright (c) Microsoft Corporation.
Licensed under the MIT License.
Adapted from https://github.com/FAIR-Chem/fairchem/blob/main/src/fairchem/core/models/gemnet/layers/atom_update_block.py.
"""
from typing import Tuple
import torch
from torch_scatter import scatte... |
04dce5f9a02633be0c3343fef1697d22516d95fb2d7960c8f083fe70d925f93a | Python | 6,920 | 194 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Reads nd2 images and extracts layers of interest"""
from pathlib import Path
from typing import Optional, Any
from xarray import DataArray, Coordinates
import imagej
import numpy as np
import scyjava
from scyjava import config, jimport, JavaMap, JavaList
config.ena... |
31b83e9645c08c4d287daa1d4d1a3d18ba4e5848b09fe718473589748a7fa575 | Python | 6,921 | 209 | """Compute and analyse the phase plane diagram (PPD)."""
# /usr/bin/env python3
import copy
import warnings
from typing import Optional
import numpy as np
import numpy.typing as npt
from scipy.integrate import trapezoid
from scipy.interpolate import CubicSpline, RegularGridInterpolator
from tqdm.contrib.itertools im... |
5365b564b0f1d164a3595a208cd5aba5a6e2e8db3eca81b00c38456c41ea656e | Python | 6,921 | 165 | """Gaussian Process surrogate model for Bayesian Optimization."""
import math
import numpy as np
import torch
class GPRegressor:
"""Gaussian Process regressor with ARD RBF/Matern kernels.
Optimizes log length scales, signal variance and noise by maximizing the
log marginal likelihood for the current BO ... |
231c80f6f675dd15996df1085bfa1d5e5c6117f61d57465446ee80393baf26ad | Python | 6,923 | 205 | # 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.abs
import csv
import logging
impor... |
90e2cec385b746c7820242bb61db6d7a60a3b7c9c996643b25559da134eba38b | Python | 6,923 | 146 | import os
import pandas as pd
import torch
import numpy as np
import transformers
from sklearn.model_selection import train_test_split
from torch.utils.data import Dataset
from transformers import AutoTokenizer,BertTokenizer, DistilBertTokenizer, ElectraTokenizer, \
BertForSequenceClassification, DistilBertForSeque... |
ba8de348af25b87ed2570bfcc3b511898afbd179e7a19588409c72c301e3adc3 | Python | 6,923 | 221 | #
# Modified by Peize Sun
# Contact: sunpeize@foxmail.com
#
# Copyright (c) https://github.com/FateScript/CenterNet-better
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
#
import math
import torch
import torch.nn as nn
import fvcore.nn.weight_init as weight_init
from detectron2.layers import Co... |
ba419d462e4a8ea6fc97790e3da52f69171e4e67bba1a363c313a9c76d91ea81 | Python | 6,925 | 190 | import torch
import torch.nn as nn
import math
from mamba_ssm import Mamba
class PositionalEmbedding(nn.Module):
def __init__(self, d_model, max_len=5000):
super(PositionalEmbedding, self).__init__()
# Compute the positional encodings once in log space.
pe = torch.zeros(max_len, d_model).fl... |
149c54ab0323ac5623c5dcc4e0c94d6b4ad8b5feb5b18fdb7c74ff9d4ac9b59a | Python | 6,928 | 180 | import os
import time
import requests
import numpy as np
from tractseg.libs.system_config import SystemConfig as C
def invert_x_and_y(affineMatrix):
"""
Change sign of x and y transformation (rotation, scaling and transformation)
IMPORTANT note: only done for diagonal elements (if we need rotation (no... |
8171959194239f841bdd5ed952b73d4d65913e7d40a0d8214fc18f57320bef32 | Python | 6,933 | 143 | #!/usr/bin/env python3
"""A variância do seletor exige DUAS condições. Este script mede a segunda.
CONTEXTO. A dispersão do RMSE sob permutação das linhas de treino foi medida em dez
casos (perovskitas e QMOF) e não escala com a largura da base nem com o regime
p > n -- as duas hipóteses caíram. O que os logs mostram ... |
54f2dabb3421ea6e6e506c138c75a07643bcbbefcd63169093f81e9a1bdc2547 | Python | 6,934 | 180 | # Source code: https://github.com/zbmed-semtec/medline-preprocessing/blob/main/code/Evaluation/calculate_gain.py
# This file includes the modifications to the source code according to this project
import os, sys
currentdir = os.path.dirname(os.path.realpath(__file__))
parentdir = os.path.dirname(currentdir)
sys.path.a... |
7f7980d600c06e537a3d0195e65f438c15c04270ba26790a4b431b4c032e78a4 | Python | 6,934 | 157 | from md.Simulator import Simulator
import openmm as mm
from openmm import unit as u
from openff.toolkit import Molecule
import argparse
import os
def submit_protein(name, checkpoint_folder, output_folder, idx, steps, force_constant, xi_0, start, number, seed):
base_folder = os.path.abspath(os.path.dirname(__file_... |
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