sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
ed75cd13bed4ff38d68b383f5ba0b279bc1c9271d702a7750a63d4f3b30b18b4 | Python | 3,381 | 97 | # 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 typing import Dict
from fairseq.data.monolingual_dataset import MonolingualDataset
from . import Fairse... |
02df8f93be911ac2a948a7890e026af8089801f63f153a93f125b4554a2d5a8c | Python | 3,385 | 70 | import torch
from torch._dynamo import OptimizedModule
from torch.nn.parallel import DistributedDataParallel as DDP
import torch.distributed as dist
def load_pretrained_weights(network, fname, verbose=False):
"""
Transfers all weights between matching keys in state_dicts. matching is done by name and we only ... |
1c625c6e9ef2993d5c6bfa73ef7317efc8fd2b60d5f6bb4d06318003bb74d76a | Python | 3,386 | 103 | #!/usr/bin/env python
# ENCODE DCC spp call peak wrapper
# Author: Jin Lee (leepc12@gmail.com)
import sys
import os
import argparse
from encode_lib_common import (
assert_file_not_empty, human_readable_number, log,
ls_l, mkdir_p, rm_f, run_shell_cmd, strip_ext_ta)
def parse_arguments():
parser = argpars... |
62b03ea317bfe63f33812a3cfed44f9cc3271a233022e6549055437fa8f9caa9 | Python | 3,387 | 104 | # 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... |
e7f721b1b607fb37f2511bf7e233c9b6df6329d23e05a7b1f1861410bea22967 | Python | 3,387 | 107 | # 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 subprocess
import threading
from pathlib import Path
import numpy as np
import torch
def fasta_file_path(prefix_path):
... |
36059dd05453ca9f5e3a61a0bb828609c73ae7f90a5c746d5348d8e8a3e0e3df | Python | 3,388 | 64 | # ##############################################################################
# GPLv3 LICENSE INFO #
# #
# Copyright (C) 2020 Mario S. Valdés-Tresanco and Mario E. Valdés-Tresanco ... |
babc5234099e47334172c3ff3664acb7426e7b2d88b25306a91b36ea1317fa9e | Python | 3,388 | 115 | import pytest
import torch
from gpn.scoring import (
log_likelihood_ratio,
nucleotide_probabilities,
require_reference_matches,
validate_centered_window_size,
validate_snv_batch,
)
def test_nucleotide_probabilities_normalize_final_axis():
logits = torch.tensor(
[
[0.0, 0.0... |
6322745bc100c60c0cb8e9b8a2c096027d7fe5a6a1a0ed7105a07c211d4481a9 | Python | 3,391 | 62 | import numpy as np
import torch
from torch import distributed as dist
from nnunetv2.training.nnUNetTrainer.nnUNetTrainer import nnUNetTrainer
class nnUNetTrainer_probabilisticOversampling(nnUNetTrainer):
"""
sampling of foreground happens randomly and not for the last 33% of samples in a batch
since most... |
bcdf0fe0032b149adaaa22e418817d114b4b3ff08089eee8a6497bd0b8fdd278 | Python | 3,391 | 71 | import numpy as np
import pandas as pd
import copy
from Net import omics_net
from SparseCoding import dropout_mask, fixed_s_mask, sparse_func
from Survival_CostFunc_CIndex import R_set, neg_par_log_likelihood, c_index
import torch
import torch.nn as nn
import torch.optim as optim
def eval_omics_net(x_tr, a... |
8721b4b2cfa6b8c88b1bf38ed8755e044fc84a1b4a1333305c080b4aa4bd7455 | Python | 3,394 | 93 | """Schema validation tests against the toy dataset.
These tests exercise the canonical CSV layout HIPPIE consumes:
waveforms.csv (N x T) -- trough-centered spike templates
isi_dist.csv (N x ~100) -- 1 ms bins, 0..100 ms
acg.csv (N x ~201) -- 1 ms bins, -100..+100 ms (optional)
labels.csv (N ... |
8e4caf109626e57507e717646dff2d26330d0b2ff62f172776a552e8a9d7e3db | Python | 3,395 | 100 | # coding=utf-8
# Copyright 2020 The Fairseq Authors 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
#
# Unles... |
9f15b2c0b0da35a5d16213f8bdea234ad3a01553867df6714f9742ed80f54bb8 | Python | 3,395 | 77 | #!/usr/bin/env python3
"""Exercise expected CLI failures and diagnostic-bundle policy."""
from __future__ import annotations
import argparse
import json
import subprocess
from pathlib import Path
try:
from .common import DEFAULT_EXAMPLES, DEFAULT_RESULTS_ROOT, copy_examples, entrypoint_command, environment_for, ... |
3b089086fa258d8db08a56580bb702c95269dd10eb72018b32379e8b87fb2ae5 | Python | 3,396 | 101 | # coding=utf-8
# Copyright 2020 The Fairseq Authors 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
#
# Unles... |
e8ccd4a7a4eb4d41ca79bfc2f3c059404c67565a3b180f1ffab23b26b76036b7 | Python | 3,396 | 75 | #!/usr/bin/env python
# PYTHON_ARGCOMPLETE_OK
"""Estimate the noise standard deviation of the Gaussian noise in the original complex image domain.
The result is a single floating point number with the noise std. for every voxel. It uses the estimation routines
from the components folders for the estimation. The estima... |
0c3aee4114d11f6752166783f0e006e24e71fc808b28aa36b5d6d94ee7c2bb1a | Python | 3,399 | 63 | import unittest
from pathlib import Path
from tangle_tracer.annot_conversion.WSIAnnotation import WSIAnnotation, load_annot
from tangle_tracer.annot_conversion.ROIAnnotation import ROIAnnotation
# from tangle_tracer.annot_conversion import point_to_mask as p2m
import zarr
class WSIAnnotationTestCase(unittest.TestCase... |
b44f25a08aa510b98d521462fa30da016eac89ff2cd5ada9f4c6cde36c3291be | Python | 3,400 | 70 | import numpy as np
import pandas as pd
import copy
from Net import omics_net
from SparseCoding import dropout_mask, fixed_s_mask, sparse_func
from Survival_CostFunc_CIndex import R_set, neg_par_log_likelihood, c_index
import torch
import torch.nn as nn
import torch.optim as optim
def train_omics_net(x_tr, ... |
122ca57b85b28ab714e2f3d86b0fde3ca01879f728ad53f8f4f445b9279149e9 | Python | 3,401 | 95 | '''
Functions for computing correcting fluorescence signals for changes in
baseline activity.
Authors:
- Scott C Lowe
'''
import numpy as np
import scipy.signal
def findBaselineF0(rawF, fs, axis=0, keepdims=False):
"""Find the baseline for a fluorescence imaging trace line.
The baseline, F0, is the 5th... |
a5247ee10131823ff9ad9e679a5c96fb14e60ed091aa770b391cdc47cc20d599 | Python | 3,402 | 124 | #### ::: DNABERT-viz SNP analysis ::: ####
import os
import sys
sys.path.append('../motif')
import pandas as pd
import numpy as np
import argparse
#import motif_utils as utils
def kmer2seq(kmers):
"""
Convert kmers to original sequence
Arguments:
kmers -- str, kmers separated by space.
R... |
23a6b56efad4b9c32c4a13eb1d042c3b8664ec16ba32a6c696329f64888c1d2d | Python | 3,403 | 97 | # 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
from dataclasses import dataclass, field
import torch
import torch.nn.functional as F
from fairseq import utils
from fairseq.log... |
d2e1ab166beaced8fcd8e5c40ab99c216067fa158cfbabd524573f6fdcdbed28 | Python | 3,404 | 107 | #!/usr/bin/env python
# ENCODE DCC FRiP wrapper
# Author: Jin Lee (leepc12@gmail.com)
import sys
import os
import argparse
from encode_common import *
def parse_arguments():
parser = argparse.ArgumentParser(prog='ENCODE DCC FRiP.',
description='')
parser.add_argument('... |
e6e8e9119ff4cd70d3a30552c739016843613b37502ecd815edc869efd492a62 | Python | 3,404 | 115 | import re
from ..datasets import EXTRA, FILENAMES
class JsCode:
def __init__(self, js_code: str):
self.js_code = "--x_x--0_0--" + js_code + "--x_x--0_0--"
def replace(self, pattern: str, repl: str):
self.js_code = re.sub(pattern, repl, self.js_code)
return self
class OrderedSet:
... |
0fb272a074559849f5cb5f548bdec3366738b036972d54cdc27e39087c8b964c | Python | 3,405 | 111 | #!/usr/bin/env python
import argparse
import pathlib
import h5py
import hdf5plugin
import numpy as np
import transformers
from d3text import corpus, utils
from jaxtyping import Float
from torch import Tensor
from tqdm import tqdm
def read_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(
p... |
8f7fad27f9e2018f530f8493589c088ec81aed3b27b6cf123f8936672a4c6e0e | Python | 3,405 | 78 | #!/usr/bin/env python
# PYTHON_ARGCOMPLETE_OK
"""Create a single slice mask that only includes the voxels in the selected slice."""
import argparse
import os
import mdt
from argcomplete.completers import FilesCompleter
import textwrap
from mdt.lib.nifti import load_nifti
import mdt.utils
from mdt.lib.shell_utils import... |
15fcd76d9beda9530dacf0bcb21b7c4894cbb5f1e8aa0b716b6652b5032c9b66 | Python | 3,408 | 78 | """Common checks in test data."""
__copyright__ = "Copyright (C) 2010-2019, DV Klopfenstein, H Tang, All rights reserved."
__author__ = "DV Klopfenstein"
from goatools.gosubdag.gosubdag import GoSubDag
from goatools.gosubdag.plot.gosubdag_plot import GoSubDagPlot
class CheckGOs:
"""Check that the dicts of GO ID... |
50a34beb8b6cea5f1a54a325c281a9185d6734ca21985ac0b8c606e012fd928b | Python | 3,408 | 101 | from __future__ import annotations
from typing import TYPE_CHECKING
from typing import ClassVar
from cleo.helpers import argument
from poetry.console.commands.env_command import EnvCommand
from poetry.utils._compat import WINDOWS
if TYPE_CHECKING:
from cleo.io.inputs.argument import Argument
from poetry.co... |
8c2b58b3562ab0e7ea384e35668987bae342279940a755c6cc6846a9410ccaa2 | Python | 3,408 | 104 | #!/usr/bin/env python
# ENCODE DCC fastq merger wrapper
# Author: Jin Lee (leepc12@gmail.com)
import sys
import os
import argparse
from encode_lib_common import (
copy_f_to_f, log, ls_l, mkdir_p, read_tsv, run_shell_cmd,
strip_ext_fastq)
def parse_arguments(debug=False):
parser = argparse.ArgumentParser... |
a070878a313788cb129e8f60bd1668b72ad4aef6c6bf6e9ef73a1e9e1a987f23 | Python | 3,408 | 106 | # 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 pickle
import os
import argparse
import numpy as np
from torch.utils.data import Dataset, DataLoader
from mmpt.processors import PKLJS... |
d2d7a5fe264ea63f8582cdace95b497ceff3e94b3a6586576205d9875bcc0d83 | Python | 3,409 | 93 | # /usr/bin/env python
'''
Written by Kong Xiaolu and CBIG under MIT license:
https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
'''
import os
import numpy as np
import torch
import CBIG_pMFM_basic_functions as fc
def CBIG_mfm_validation_desikan_main(gpu_index=0, subject=1):
'''
This function is to va... |
e1cfcf5a4298e2e57daf57496f27445e7bf009d2b7da836d89fb2c61a06e1dce | Python | 3,409 | 73 | # Copyright 2021 HIP Applied Computer Vision Lab, Division of Medical Image Computing, German Cancer Research Center
# (DKFZ), Heidelberg, Germany
#
# 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... |
4c3c28dbd99c05ac1c7a6b954c1ca09edf927f482ded076111a0d6c84e896852 | Python | 3,410 | 89 | # 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 urllib.parse
import json
import pandas as pd
from tqdm import tqdm
# TODO: extending to other datasets.
supported_formats =... |
75d49273b3b984d9cd4cc3ab0f9ce29bab30ae8a3ae891bfade2f62fc33142bf | Python | 3,410 | 96 | import gzip
import logging
import io
import numpy
from .Genotype import GF
from .. import Utilities
from . import Helpers
def parse_gtex_variant(variant):
comps = variant.split("_")
return comps[0:4]
def gtex_geno_header(gtex_file):
with io.TextIOWrapper(gzip.open(gtex_file, "r"), newline="") as file:... |
cd459ccb9efa9414020d3582062b08383d63b8b37bf80dd1d3c9898abcc7f979 | Python | 3,412 | 130 | """fixture used to test DAS model"""
from __future__ import annotations
import numpy as np
import pytest
import torch
from .test_data import NETS_TEST_DATA_ROOT
DAS_TEST_DATA_ROOT = NETS_TEST_DATA_ROOT / "das"
DAS_BATCH_DATA_ROOT = DAS_TEST_DATA_ROOT / "batches"
AMP_TO_DB_IN_BATCHES = [
batch
for batch in... |
2087d5e3786ded8eeffc7020a4cffcf46e5c0b16080002c6c1c52c3b2b8fc6c4 | Python | 3,413 | 89 | import torch
from tqdm import tqdm
from transformers import EsmConfig, EsmForMaskedLM, EsmTokenizer
from torch.nn.functional import normalize
class StructureEncoder(torch.nn.Module):
def __init__(self, config_path: str, out_dim: int, gradient_checkpointing: bool = False):
"""
Args:
co... |
d261d5584e7da33d7fc65f4d4d3aa6d8a68103904bbfbc8cd99b22f1b5005de8 | Python | 3,413 | 98 | import numpy as np
from mdt import CompartmentTemplate, FreeParameterTemplate
from mdt.lib.post_processing import DTIMeasures
from mdt.model_building.parameter_functions.transformations import ScaleTransform
__author__ = 'Robbert Harms'
__date__ = "2015-06-21"
__maintainer__ = "Robbert Harms"
__email__ = "robbert@xkls... |
a9241dcb6a81b25ec7a47b1ce78dbaac70374f83e64496129c2880a0bb237695 | Python | 3,414 | 83 | from model.builders.prostate_models import build_pnet2_account_for
task = 'classification_binary'
# selected_genes = 'tcga_prostate_expressed_genes_and_cancer_genes.csv'
selected_genes = 'tcga_prostate_expressed_genes_and_cancer_genes_and_memebr_of_reactome.csv'
data_base = {'id': 'ALL', 'type': 'prostate_paper',
... |
0585f64dfdfe445b48229f233df60bf57e88366fcaf1d4ef8bf400688c7568fb | Python | 3,416 | 105 | import pandas as pd
from sklearn.gaussian_process import GaussianProcessClassifier
def _gaussian_process_classifier(
lfc_g1_g2: pd.Series,
lfc_n1_g2: pd.Series,
fdr_g1_n1: pd.Series,
lenght_scale_init: float = 10,
lenght_scale_bounds: tuple = (1e1, 1e2),
alpha_init: float = 0.1,
alpha_boun... |
554340359d85c0959215e0e7cd166b60a00114dcbba6016ea6563945274b8fa7 | Python | 3,416 | 88 | import torch
import torch.nn as nn
import torchvision.models as models
from . import DA_network
class Deeplabv3plusMobilenetFeatureExtractor(nn.Module):
def __init__(self, layers_to_extract):
super(Deeplabv3plusMobilenetFeatureExtractor, self).__init__()
self.deeplabv3plus_mobilenet = DA_network.mo... |
fa3b9f6cc6bae3baa48851b32dc2074a7632fc2c7758faa9fa1af2bfdfea48e4 | Python | 3,416 | 100 | import random
import numpy as np
import pandas as pd
import nibabel as nb
from scipy.stats import ttest_ind
import statsmodels.stats.multitest as multi
from matplotlib_surface_plotting import plot_surf
from meld_classifier.meld_cohort import MeldCohort, MeldSubject
# Load demographics
df = pd.read_csv('/home/meldstude... |
67180d30e70122827d7fd0d8d5571cf5a65b4ad9aafade87e35d083eb8297c3c | Python | 3,418 | 114 | from __future__ import annotations
import fnmatch
import pathlib
import re
def find_fname(fname: str, ext: str) -> str | None:
"""given a file extension, finds a filename with that extension within
another filename. Useful to find e.g. names of audio files in
names of spectrogram files.
Parameters
... |
b9043f8316b777a4c08a02c0a53da612e91f76cc0714cc01c427de1ac73d4a4e | Python | 3,419 | 87 | """Deprecated compatibility shims for :class:`pgmpy.causal_discovery.ChowLiu` / :class:`pgmpy.causal_discovery.TAN`."""
from pgmpy.causal_discovery import TAN as _TAN
from pgmpy.causal_discovery import ChowLiu as _ChowLiu
from pgmpy.estimators import StructureEstimator
from pgmpy.utils._warnings import _warn_external
... |
bb60316d016fc943bd79b3fae65d65e42000fc534cb6b04ff0f6383116a06554 | Python | 3,421 | 83 | from model.builders.prostate_models import build_pnet2_account_for
task = 'classification_binary'
# selected_genes = 'tcga_prostate_expressed_genes_and_cancer_genes.csv'
selected_genes = 'tcga_prostate_expressed_genes_and_cancer_genes_and_memebr_of_reactome.csv'
data_base = {'id': 'ALL', 'type': 'prostate_paper',
... |
31514b5bbe7baf765dbcbae530e785af84854a82f53f6a32b685775b561c15d2 | Python | 3,424 | 83 | from model.builders.prostate_models import build_pnet2_account_for
task = 'classification_binary'
# selected_genes = 'tcga_prostate_expressed_genes_and_cancer_genes.csv'
selected_genes = 'tcga_prostate_expressed_genes_and_cancer_genes_and_memebr_of_reactome.csv'
data_base = {'id': 'ALL', 'type': 'prostate_paper',
... |
ee8ba260b31eb9493fcc2934f161fbd85cd24ebb90f1e3a64df8d4e2dc742636 | Python | 3,425 | 93 | """Checkpoint loading for HIPPIE models."""
from __future__ import annotations
import torch
def infer_model_dims(state_dict: dict) -> tuple[int, int]:
"""Infer num_sources and num_classes from a checkpoint state dict."""
src_key = next(k for k in state_dict if "source_embed" in k and "weight" in k)
num_... |
4aa191f99b32518f4f51ad478c4f6c5393ef9e8193e26c28241347964950d384 | Python | 3,427 | 139 | """
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 torch import nn
from .base_layers import Dense
from crystalgrw.gnn.embeddings import MAX_ATOMIC_NUM
... |
dea8f8f302a19c59577621237caebb8fa05f4172ba42ff26b4dd688b025b999a | Python | 3,427 | 105 | """Unit tests for delaf.py."""
from __future__ import division
import unittest
import numpy as np
from .base_test import BaseTestCase
from .. import deltaf
class TestFindBaseline(BaseTestCase):
"""Test baseline functions."""
@unittest.expectedFailure
def test_trivial(self):
"""Test trivial inp... |
567d2b6b03fc91fe411b6985539c3295f8eb3aca22c37974058662c1cbd0922b | Python | 3,428 | 83 | from model.builders.prostate_models import build_pnet2_account_for
task = 'classification_binary'
# selected_genes = 'tcga_prostate_expressed_genes_and_cancer_genes.csv'
selected_genes = 'tcga_prostate_expressed_genes_and_cancer_genes_and_memebr_of_reactome.csv'
data_base = {'id': 'ALL', 'type': 'prostate_paper',
... |
dcae261dbd98023b7b7a4a78b4d27056f59c2f6339acf3aa7215f60220a362aa | Python | 3,429 | 100 | # 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
def calc_mean_invstddev(feature):
if len(feature.size()) != 2:
raise ValueError("We expect the input feature to be ... |
dfcbceab2206244779bd80b53501be0713a2979e45682d78617791c3bcf82d8e | Python | 3,429 | 102 | #!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import json
import os
import re
class InputExample:
def __init__(self, paragrap... |
7df77db5f7b31b1aeffd4ca39c09c6fb54efd0b8ce5df3129617bf5ac7317778 | Python | 3,430 | 87 | import multiprocessing
import shutil
from multiprocessing import Pool
from batchgenerators.utilities.file_and_folder_operations import *
from nnunetv2.dataset_conversion.generate_dataset_json import generate_dataset_json
from nnunetv2.paths import nnUNet_raw
from skimage import io
from acvl_utils.morphology.morpholog... |
a369cdbe6cdcb95c35064b85c446c1cd5ddc7e6891b096548d2cb5525fc35d07 | Python | 3,430 | 87 | import multiprocessing
import shutil
from multiprocessing import Pool
from batchgenerators.utilities.file_and_folder_operations import *
from nnunetv2.dataset_conversion.generate_dataset_json import generate_dataset_json
from nnunetv2.paths import nnUNet_raw
from skimage import io
from acvl_utils.morphology.morpholog... |
7b14699b73cac8b212a8a8dddd1ce14ae117283fc66ed6b9bb723639135937a2 | Python | 3,432 | 119 | #!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import absolute_import, division, print_function, unicode_literals
import argparse
i... |
b39babe3ea833f8df35010fae8361f2405c4f0b3582e190a8a22970b4bf6ac88 | Python | 3,436 | 94 | from __future__ import annotations
from typing import TYPE_CHECKING
from poetry.core.packages.package import Package
from poetry.installation.chooser import Chooser
if TYPE_CHECKING:
from poetry.repositories.repository_pool import RepositoryPool
from poetry.utils.env import MockEnv
def test_chooser_no_li... |
239f869c1db274cbd2233ba2c3c49967d5a908c734e681b7035db7e3901fbac0 | Python | 3,439 | 96 | from collections.abc import Mapping
from typing import NamedTuple, TypedDict
from jaxtyping import Float, Integer
from torch import Tensor
type BatchedLogits = Float[Tensor, "sequence logits"]
class BatchItem(TypedDict, total=False):
"""One document's inputs as consumed by the model methods.
Every field is... |
c0fcfbb8dc74721e8fc972762cb347493923f8adc53147f49564020c8758df0e | Python | 3,439 | 106 | #!/usr/bin/env python3
"""
Basic usage example for RAG-GNN.
This example demonstrates how to:
1. Create a simple network
2. Generate RAG-GNN embeddings
3. Evaluate embedding quality
"""
import numpy as np
import networkx as nx
from rag_gnn import RAGGNN, GNNEncoder
from rag_gnn.utils import compute_silhouette, evalua... |
0e08b73d5d6b244b408bd4143e36351af746f569b458e25443d5ae8b5bcbe23b | Python | 3,441 | 96 | # 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 unittest
from tempfile import TemporaryDirectory
from fairseq import options
from fairseq.binarizer import FileBinarizer, Vo... |
8898b45dd75ba3d7f2254aef92c9de4fc99c692f73a1fad00b5326723ecff36a | Python | 3,441 | 103 | import logging
import os
from anndata import AnnData, read_h5ad
from scvi.data._download import _pooch_retrieve_with_retries
from scvi.utils import dependencies
logger = logging.getLogger(__name__)
@dependencies("pooch")
def _load_retina(save_path: str = "data/") -> AnnData:
"""Loads retina dataset.
The d... |
7591cfc7fb26d3d9a8947f463e39ff0ff687800803c4150e3e6e009167784c8f | Python | 3,442 | 131 | import math
import torch
import torch.nn as nn
from torch.nn import init
class Input(nn.Module):
def __init__(self):
super(Input, self).__init__()
def forward(self, x):
return x
class ConvHole2D(nn.Conv2d):
def __init__(
self,
in_channels,
out_channels,
k... |
928bf4db43e7eabaab91236680f6d506b5daa67267995230596bf2fde051064c | Python | 3,443 | 85 | from src.utils import read_gtf
import polars as pl
from tqdm import tqdm
import numpy as np
import multiprocessing as mp
from src.utils import read_CAGE_peaks, read_polyA_peaks
#--------Read in datasets--------
cage_peak_obj = read_CAGE_peaks("data/refTSS_v3.3_human_coordinate.hg38.sorted.bed")
polya_peak_obj = read_p... |
51bd004c6fe768069c401757a55f2472834df2d7cbb0f6f947e4c58016df953e | Python | 3,444 | 77 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from pymatgen.core.structure import Structure
from pymatgen.entries.compatibility import Compatibility, MaterialsProject2020Compatibility
from mattergen.common.utils.globals import get_device
from mattergen.evaluation.metrics.evaluator import Me... |
1bbe7835f91f915888fdda5d9524d686494c47df6a51e78d5decaa1d4c2fd987 | Python | 3,445 | 118 | import anndata
import numpy as np
import pytest
from anndata import AnnData
from fast_array_utils import stats
from fast_array_utils.conv import to_dense
from scipy.sparse import csr_matrix
import novae
x_np = np.array([
[1, 0, 0, 3],
[0, 5, 6, 0],
[7, 0, -1, 0],
])
x_sparse = csr_matrix(x_np)
adata = A... |
ce0fdd9d5746996d5996837acffa36c4bfc680e1e5d150dfb8e41b026a4c4889 | Python | 3,445 | 69 | #!/usr/bin/env python3
"""A super simple program that displays a summary of your model and optionally saves an image.
.. warning::
This module is deprecated and will be removed in BPReveal 6.0.0.
To see a text description of your model, just do::
model = utils.loadModel(modelFname)
print(model... |
ebe52fb9de22db4a5cb4d6ca6f5fb2056f9fee61b31b37ca59ca7f7eda32de76 | Python | 3,445 | 126 | from typing import Optional, Dict
from torch import Tensor
import torch
def waitk_p_choose(
tgt_len: int,
src_len: int,
bsz: int,
waitk_lagging: int,
key_padding_mask: Optional[Tensor] = None,
incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]] = None
):
max_src_len = src_... |
30112490112299d65b0f566f789a16e3d3cf6ea649e97e7d29c78409521dbc3c | Python | 3,446 | 110 | from __future__ import annotations
import shutil
from typing import TYPE_CHECKING
from typing import ClassVar
from cleo.helpers import argument
from cleo.helpers import option
from poetry.core.constraints.version.version import Version
from poetry.core.version.exceptions import InvalidVersionError
from poetry.conso... |
a2d8180975b36ae6788230dae05b04a5ea2cdbad9f059f978637757fd49b310f | Python | 3,446 | 123 | """
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
import torch
import torch.nn as nn
from torch_geometric.nn import radius_graph
from ..common.utils import (
compute_neig... |
37c341dc41c11ebc5d8b0c3d3ab203ed80ca040861cf735d27c97c28f68a9c8f | Python | 3,451 | 94 | from __future__ import annotations
from functools import cache
from typing import TYPE_CHECKING
import torch
if TYPE_CHECKING:
from collections.abc import Callable
@cache
def _mps_supports(op: Callable[[torch.Tensor], torch.Tensor]) -> bool:
"""Whether ``op`` has an MPS kernel in the torch build in use.
... |
784ab4147d374b7f18f75a0aebb7ab1663ee08231c40e2b8d2ae3e529e5ed163 | Python | 3,451 | 103 | import os
import h5py
import numpy as np
from types import SimpleNamespace
from typing import Tuple
from voluseg._tools.constants import hdf
from voluseg._tools.evenly_parallelize import evenly_parallelize
def collect_blocks(
color_i: int,
parameters: dict,
) -> Tuple[np.ndarray, np.ndarray, np.ndarray, np.n... |
ed0a3d8f6cd787c3aba3d6e730b93212f21c1810b14e5c69a7f84581c720dbf0 | Python | 3,451 | 116 | import copy
import numpy as np
import pandas as pd
import pytest
import vak.common # for constants
import vak.common.files.spect
import vak.common.labels
@pytest.mark.parametrize(
'labelset, map_background',
[
(
set(list("abcde")),
True
),
(
set(l... |
6bd5f61cf9d85ab7a5007bdb7cd1af5a2cb918a87fc2a3c77aa0230b96e04e24 | Python | 3,452 | 112 | # -*- coding: utf-8 -*-
"""
@Time:Created on 2019/9/17 8:54
@author: LiFan Chen
@Filename: main.py
@Software: PyCharm
"""
import torch
import numpy as np
import random
import os
import time
from model import *
import timeit
def load_tensor(file_name, dtype):
return [dtype(d).to(device) for d in np.load(file_name ... |
0fd0bf2251ebf3fcc302fed8fae3a357fd9e22e0e4c5fa822e39bbf07ede5457 | Python | 3,453 | 68 | import pandas as pd
import numpy as np
from currentscape_calculator.partitioning_algorithm import partition_iax
class CurrentscapeCalculator:
"""
Represents a calculator for performing Currentscape analysis for input data.
This class is designed to calculate positive and negative membrane current componen... |
28b5f109a664f73f38bccb5fe8273cb3c4d3a0284aa69193c0bc3da7f5908d7c | Python | 3,457 | 102 | # @license
# Copyright 2025 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... |
fe625c8a62d5696aaa96f4248a1d56749d2ef41dc4595c2a4f590c70d09debaa | Python | 3,457 | 81 | """Guards for the packaging metadata.
The optional-dependencies file (``requirements_extra.txt``) must stay a *valid* pip requirements
file: Dependabot's dependency-graph parser reads every ``requirements*.txt`` in the repo, and a
custom grammar (the old ``pkg>=x: tag`` format) makes that job fail with an ``InvalidReq... |
03df163fb1759788ba4933049cb6e0c2bd93cd82459825a5533236be69fe2db2 | Python | 3,460 | 99 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# ----------------------------------------------------------------------------------------------------------------------
# Author: Lalith Kumar Shyam Sundar
# Institution: Medical University of Vienna
# Research Group: Quantitative Imaging and Medical Physics (QIMP) Team
... |
b0bbfea93ec84457946e2021310cb19e6297cac17c7d4448d7c64cfe8ab39bea | Python | 3,460 | 94 | import torch
import torch.nn as nn
import torch.nn.functional as F
from core.modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d
class _ASPPModule(nn.Module):
def __init__(self, inplanes, planes, kernel_size, padding, dilation, BatchNorm):
super(_ASPPModule, self).__init__()
self.atro... |
1766b09b5166096a5586fa0d00ec1069294200b447ed699e59ce83989fa2a701 | Python | 3,463 | 101 | #!/usr/bin/env python3
# This is used by the acceptance test script to test the GA.
import argparse
from bpreveal import gaOptimize
import pysam
import tqdm
from bpreveal import utils
from bpreveal.internal import disableTensorflowLogging
del disableTensorflowLogging
utils.setVerbosity("INFO")
def runGaOptimization(... |
ea099c980e375d7dcc97c67da3a2f5fed6a5c5235f0516d95d854d0253fcfc4f | Python | 3,465 | 113 | import pandas as pd
import pytest
from pgmpy.base import DAG, PDAG
from pgmpy.metrics import OrientationConfusionMatrix
# The models in true_dag and est_dag fixtures are taken from the paper: https://arxiv.org/pdf/2412.10039
@pytest.fixture
def true_dag():
return DAG(
[
("x1", "x2"),
... |
f41a41127dd329736e043eb3c60ca1637de26cff26f75214c0126ce351c4e749 | Python | 3,465 | 103 | # -*- coding: utf-8 -*-
# Copyright (C) 2023 Phillip Alday <me@phillipalday.com>
# License: BSD (3-clause)
"""BrainVision Writer tests."""
import os
from shutil import rmtree
import mne
from nose.tools import assert_equal, assert_raises
import numpy as np
from numpy.testing import assert_allclose, assert_array_equa... |
347164235330844d9112ce8315c4285532b3cf6963f4dafec61a563fe2d59eda | Python | 3,472 | 109 | # 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 math
import os
import subprocess
import sys
import tempfile
from collections import defaultdict
from itertools import c... |
eea3325e7a407eceddbe742e938d9a07f0e1b385ad1569544f96b2457fb9bdab | Python | 3,472 | 93 | """Registry for models.
Makes it possible to register a model declared outside of ``vak``
with a decorator, so that the model can be used at runtime.
"""
from __future__ import annotations
from typing import TYPE_CHECKING, Any, Type
import lightning
if TYPE_CHECKING:
from .factory import ModelFactory
MODEL_FA... |
ace8dc92128fb198405a6ea43a950f27c54a74490979659fdea383c87698c6a4 | Python | 3,473 | 84 | from model.builders.prostate_models import build_pnet2_account_for
task = 'classification_binary'
# selected_genes = 'tcga_prostate_expressed_genes_and_cancer_genes.csv'
selected_genes = 'tcga_prostate_expressed_genes_and_cancer_genes_and_memebr_of_reactome.csv'
data_base = {'id': 'ALL', 'type': 'prostate_paper',
... |
0ff87cc9c236246b4a5c46c394c30dee9b7c6240fa1e9eff18b06bc181f9d107 | Python | 3,474 | 114 | """Implements models which run 1d convolutions along the read features."""
import enum
import torch
def make_1dconv_layers(
kernel_sizes, in_feat, channels, use_batch_norm, activation="ReLU"
):
"""Make the 1d conv blocks."""
if not isinstance(channels, list):
channels = [channels] * len(kernel_si... |
11a68a9cd04aeca94c27695edaf783e18d4793ecabed67e55d108f4a5826d863 | Python | 3,474 | 93 | import logging
import numpy as np
import pandas as pd
import warnings
from dynamicTreeCut import dynamicTreeCut
from dynamicTreeCut import R_func as dtc_utils
from scipy.cluster import hierarchy
from scipy.spatial import distance
from mentor import _metrics as metrics
from sklearn.base import BaseEstimator,ClusterMixin... |
93fd54fe115b189fa07a8bfc3f5e8884d9e1e1c84e445e705ffc089756647c8c | Python | 3,474 | 106 | """Retrieve PubMed abstracts and full text content when available.
Feed the document database with abstracts and full text retrieved from PubMed.
"""
import asyncio
import itertools
from collections.abc import Iterator, MutableMapping
from aiotinydb import AIOTinyDB
from aiotinydb.storage import AIOJSONStorage
from... |
c644a5050f9c2a24b358a016be0c89ccaa2eeee06fadfdedd4435896a121f1c2 | Python | 3,474 | 82 | import pandas as pd
from pgmpy.causal_discovery._base import BaseOrderDiscovery
class VarSort(BaseOrderDiscovery):
r"""Causal discovery by sorting marginal variances and regressing on predecessors.
Sort variables by increasing marginal variance to obtain an estimated causal order, exploiting the varsortabil... |
016581cbe9374e25cc879df0c14f9104bf7b9adee4cc01c83427141a7868d640 | Python | 3,476 | 92 | from copy import deepcopy
import numpy as np
from model.builders.prostate_models import build_pnet2
task = 'classification_binary'
selected_genes = 'tcga_prostate_expressed_genes_and_cancer_genes.csv'
data_base = {'id': 'ALL', 'type': 'prostate_paper',
'params': {
'data_type': ['mut_imp... |
be62da66c43e81b39eefb71e1c02cbb6450788e4a19225d3b94d67190f590549 | Python | 3,477 | 75 | import numpy
import numpy.testing
import pandas
import unittest
from metax.gwas import Utilities as GWASUtilities
#
from metax.Constants import SNP
from metax.Constants import EFFECT_ALLELE
from metax.Constants import NON_EFFECT_ALLELE
from metax.Constants import ZSCORE
from metax.Constants import CHROMOSOME
from meta... |
4f591603e7e6cb4444ca182731705e6b4e394afdd0bba7138a12865ee3c16328 | Python | 3,483 | 108 | from __future__ import annotations
from contextlib import contextmanager
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import TYPE_CHECKING
from poetry.utils.env.base_env import Env
from poetry.utils.env.env_manager import EnvManager
from poetry.utils.env.exceptions import EnvCommandErr... |
ca190be7a8a577bb36dae099ca6dd1fa48c940421aeab77b87d059f160660fe3 | Python | 3,483 | 115 | import logging
import os
from functools import partial
import jax
import jax.numpy as jnp
import numpy as np
__all__ = ()
log = logging.getLogger(__name__)
DEVICE_AXIS = "device_axis"
@jax.pmap
def broadcast_to_devices(pytree):
return pytree
def split_rng_key_to_devices(rng):
return broadcast_to_devices... |
d5f4d76da411c00ec1162a383de05b1e48cbf6d6e83d70f6174e2a375378a275 | Python | 3,484 | 127 | # 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 gc
import os
import random
import shutil
import numpy as np
import torch
import tqdm
from examples.textless_nlp.gslm.speech2unit.pretr... |
5c6f073b3450c5ea6c95003ed0460c30c81d2165c420c2149abb5f1dbe2b6bfd | Python | 3,487 | 88 | """
Logic to generate sobol samples for pTau,agg dynamics with A\betaReelin dynamics parameters fixed
"""
from SALib.analyze import sobol
from SALib.sample.sobol import sample
import numpy as np
from scipy.stats import qmc
np.random.seed(0) #This was not set for large simulation
def induction_linear(max_y... |
79819598cd1e366eaa8f2a4fee2d638b6ef0686e490402fae792ccce58d876c0 | Python | 3,487 | 103 | #!/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... |
93643a8b93caca6edea17fec6b8e14f7a520ead072c77926bc5412cb6a72e936 | Python | 3,487 | 103 | """
Utils
"""
import warnings
warnings.filterwarnings("ignore")
import pandas as pd
import numpy as np
import os
import requests
from tqdm import tqdm
import tarfile
def get_shapes_dict(dataset_path):
shapes_dict = {}
datasets_df = pd.read_csv(dataset_path)
sorted_dataset_names = sorted(datasets_df["nam... |
66eaffbbc7910fbf2996f881fca88176b78b3730b6e96734218d4495b20084e4 | Python | 3,490 | 98 | import os
import numpy as np
import json
from meld_classifier.meld_cohort import MeldCohort, MeldSubject
from meld_classifier.paths import CLIPPING_PARAMS_FILE
#Generate feature lists
ds_gmfrac_features_to_generate = []
ds_gmdist_features_to_generate = []
ds_wm_features_to_generate = []
hemispheres = ['lh', 'rh']
... |
8836a2e5e9a8f51a8f7bab76bc5d3a571a4059dd6cb1c19f46e61ef50de0a324 | Python | 3,491 | 118 | """
Copyright 2020 The Google Research Authors.
Copyright (c) Microsoft Corporation.
Licensed under the MIT License.
Based on code from https://github.com/yang-song/score_sde_pytorch/blob/main/sde_lib.py
which is released under Apache licence.
Abstract SDE classes, Reverse SDE, and VE/VP SDEs.
Key changes:
- Rename... |
13e2a5cb628805c1645a9b7cc0fad40422b123b2effcfe85be0bfc8047e57591 | Python | 3,492 | 70 | #!/usr/bin/env python3
"""figure1_workflow.py — workflow with the current two-gene Tier-1."""
import matplotlib.pyplot as plt
from matplotlib.patches import FancyBboxPatch, FancyArrowPatch
fig, ax = plt.subplots(figsize=(7.5, 10.5), dpi=300)
ax.set_xlim(0, 10); ax.set_ylim(0, 14); ax.axis('off')
CI="#E3F2FD"; CP="#FF... |
41c13457ecc7813539b983097738631574ee11c5f136fd80253fc79b451db8ca | Python | 3,492 | 156 | # flake8: noqa
from .charts_options import (
BarItem,
BarBackgroundStyleOpts,
BMapCopyrightTypeOpts,
BMapGeoLocationControlOpts,
BMapNavigationControlOpts,
BMapOverviewMapControlOpts,
BMapScaleControlOpts,
BMapTypeControlOpts,
BoxplotItem,
CandleStickItem,
Chord... |
5ec9c29d0563a45a988bfb82210e43a76b68b47a196eb77f8d63ab7504cbf894 | Python | 3,492 | 73 | import numpy as np
import torch
from torch.utils.data import DataLoader
import time
from pathlib import Path
from input_data_from_mesh import prep_input_data
from fit import fit, fit_with_early_stopping
from optim import *
from plotting import plot_field
def train_continue(disp_idx, field_comp, disp, pffmodel, matpro... |
98d29c99f478145c238afd328812ff0262edd986b613e7c1ac444baca863e4ac | Python | 3,494 | 122 | #!/usr/bin/env python
"""
Thin Slurm-facing entry script for cluster-based HbO power simulations.
Small test version:
- 3 x 5 = 15 block/subject grid cells
- reduced iterations
Choose the scenario by setting SCENARIO below.
Supported:
- "null_vs_null"
- "signal_vs_null"
- "signal_vs_signal"
"""
import sy... |
a8fee5b8a01523e3d35e3f8f1116c13470e97fabbff790364268d8b48fbde623 | Python | 3,495 | 97 | import vtk, qt, slicer
from math import sqrt, cos, sin
import numpy as np
from .CircleEffect import AbstractCircleEffect
class AbstractShrinkExpandEffect(AbstractCircleEffect):
def __init__(self, sliceWidget):
# keep a flag since events such as sliceNode modified
# may come during superclass constructio... |
123275502ec4a7bfee8f09d00d989447883ddeb0a3c9c56eac6fd88913b372fe | Python | 3,496 | 94 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from collections import defaultdict
from itertools import combinations
from typing import Any, Callable, Iterable, TypeVar
import numpy as np
from pymatgen.core import Structure
from pymatgen.core.lattice import Lattice
from pymatgen.entries.com... |
8aaf0e83b46c9de58759ef439eda368a142a9b582ce1f1d89edf1ad835f2c964 | Python | 3,501 | 106 | """A later batch item's store read overlaps an earlier item's replay.
`_resolve_layer_boundary_cached` submits every hit's `store.get` to a single
background thread before replaying any of them, so the thread can be reading
item `n + 1` while the trainable top layers replay item `n`'s prefix. A
version that reads and ... |
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