sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
769ce7dc5b836dbd9695c33bf3028310a87dcda40b4aeb2ebf89f43687c82598 | Python | 1,794 | 53 | import json
import os
import numpy as np
import pytest
from oneqmc import convert_geo
INPUT_FILES = {
"yaml": "../data/cyclobutadiene/square.yaml",
"xyz": "test_square.xyz",
"json": "test_square.json",
}
@pytest.mark.parametrize("from_fmt,to_fmt", [["yaml", "xyz"], ["yaml", "json"], ["json", "xyz"]])
d... |
dbf47281ee7f70dbc1578964ee252b3b2dda4e97547055b44e70ffaa13ca7919 | Python | 1,796 | 52 | # 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 glob
import argparse
from utils.dedup import deup
import sys
WORKDIR_ROOT = os.environ.get('WORKDIR_ROOT', None)
if WORKD... |
628c063affadc3b22890ad2db42dde72d519eb073f143c5243e518dcff4a3cd9 | Python | 1,797 | 57 | import subprocess
from anarci import anarci
def get_seq(pdb_chain):
command="grep -A1 %s data/databases/pdb_seqres.txt" % (pdb_chain)
output = subprocess.getoutput(command)
return output.split("\n")[1]
def parse_anarci(in_seq):
try:
command="ANARCI --scheme aho -i %s" % in_seq
outpu... |
961ce77d00dd0b72f106873bc74a609e113d66fc17f095db82d951c4f51f534d | Python | 1,797 | 46 | import matplotlib.pyplot as plt
import loompy
from .colors import colorize
def embedded_velocity(ds: loompy.LoomConnection, out_file: str = None) -> None:
plt.figure(figsize=(12, 12))
if "UMAPVelocity" in ds.ca:
plt.subplot(221)
xy = ds.ca.UMAP
uv = ds.ca.UMAPVelocity
plt.scatter(xy[:, 0], xy[:, 1], c=col... |
c9b459cd0e5a172be07e430ef971237d8329aabf688875dcc51916abd8fb8b07 | Python | 1,798 | 53 | # @license
# Copyright 2020 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... |
147d286b6a2ef2857e5140f20f1460e4f5a0d22908872bc86ff02453e09d71db | Python | 1,800 | 55 | import os
import urllib2
from os.path import join, basename, dirname, exists
current_dir = dirname(__file__)
processed_dir = 'processed'
data_dir = 'external_validation'
processed_dir = join(current_dir, processed_dir)
data_dir = join(current_dir, data_dir)
if not exists(data_dir):
os.makedirs(data_dir)
def d... |
82d7d7f4f61091b7b04cd593defa6bc384475c64f5eb68c85a0184f2c8a6d338 | Python | 1,801 | 56 | # @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... |
12efc1bade39612f2ad527497f0a0beeeb6484318c712ef4d2069c23ce8d2134 | Python | 1,802 | 68 | from pathlib import Path
import click
import xarray as xr
def status_dataset(dataset: str) -> None:
click.secho(f'\n{str(dataset)}', bold=True)
dataset_path = Path(dataset)
if not dataset_path.exists():
click.secho('Dataset does not exist!', fg='red')
return
try:
chunking =... |
e654a0bf36ce2c691ab0711e8065f64887e0789dfa58809ddd67e71f95a68bf6 | Python | 1,802 | 57 | import torch
import torch.nn as nn
import torch.nn.functional as F
class Swish(nn.Module): #
@staticmethod
def forward(x):
return x * torch.sigmoid(x)
class Hardswish(nn.Module): # export-friendly version of nn.Hardswish()
@staticmethod
def forward(x):
# return x * F.hardsigmoid(x) ... |
edfc9110d65057f921dc97089508b0ace0f5c4ef3d38a57efe0b2365f882aef5 | Python | 1,802 | 58 | import matplotlib.pyplot as plt
import glob, os
import pandas as pd
import seaborn as sns
fig, ax = plt.subplots()
# Define the folder path containing the text files
folder_path = '/content/drive/MyDrive/red_blue/0.66_n/'
noiselist = []
noiseA =[]
val = []
# Iterate through all files in the folder
for fi... |
4ba405574a16330995c5c307ce6c1b7182b8f916b81764bf92d9e1607992ca81 | Python | 1,804 | 58 | import torch
import numpy as np
def fori_loop(lower, upper, body_fun, init_val, att, mutation, target):
val = init_val
for i in range(lower, upper):
val, att, mutation, target = body_fun(i, val, att, mutation, target)
return val
def fori_loop_reinforce_learn(lower, upper, body_fun, init_val, att... |
d7da431c6678d874f4ecc4ede18f512c2e91f08d8f57e5d02250a8f590926487 | Python | 1,804 | 59 | # This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
import shutil
import sys
import tempfile
import unittest
from typing import Optional
from unittest.mock import MagicMock
class TestFileIO(unittest.TestCase):
_tmpdir: Optional[st... |
f8f10343191427bb679eea4841e60661c280c4d304677941871f778fd4005bbb | Python | 1,805 | 71 | import torch
from torch.utils.data import Dataset, Subset
import pandas as pd
import numpy as np
from typing import Union
from pathlib import Path
from rinalmo.data.alphabet import Alphabet
from Bio import SeqIO
class SpliceSiteDataset(Dataset):
def __init__(
self,
ss_csv: Union[str, Path],
... |
dd163b2d9fed188e8fa80bb85fcd5e65b7884aa74b2351f99dcaa60f85f1842b | Python | 1,809 | 73 | #%%
from ambiguous.dataset.dataset import DatasetTriplet
from torch.utils.data import DataLoader
import matplotlib.pyplot as plt
#%%
# Manually load dataset
import numpy as np
idx=2000
set_type='train'
img_size=28
image = np.load(f'/Users/guillaumeetter/Documents/datasets/amnistV2/{set_type}/{idx}_image.npy')
labe... |
4a5d2ddb436e17feafd86f448ba274a85965663f532b531223c6c34dfcb60576 | Python | 1,811 | 76 | import argparse
import os
import csv
import numpy as np
from process_pretrain_data import get_kmer_sentence
def Process(args):
SCAN_LIST = [int(500/(args.slide-1))*i for i in range(args.slide)]
old_file = open(args.file_path, "r", encoding="utf-8-sig")
old_lines = list(csv.reader(old_file, delimiter="... |
e49ddc39e9cc0a780fb78e7d68ad8e5737bdd6d649f45e570fc70e8fdf91294e | Python | 1,811 | 48 | from nipype.interfaces.base import BaseInterface, BaseInterfaceInputSpec, traits, File, TraitedSpec
from traits.api import List
# this VIF interface code was developed based on a draft from ChatGPT
class VIFCalculationInputSpec(BaseInterfaceInputSpec):
design_matrix = File(exists=True, desc='Path to design matrix ... |
e95de45e2d9ff44da817efcb7a3bef66a86c0cd9030b8e2f934533dd0cf03fcf | Python | 1,811 | 89 | """
NeuroVFM: Vision Foundation Model for Medical Imaging
A comprehensive framework for self-supervised pretraining and supervised fine-tuning
of vision transformers on 3D medical imaging data (MRI, CT).
"""
__version__ = "0.1.0"
# Data loading and preprocessing
from .data import (
DatasetMetadata,
CacheMana... |
4b213e36146a18ed5e6f987072243bd78e2d9758b40b0fda8a1b5d88edf1b6a1 | Python | 1,812 | 63 | import argparse
import neuroglancer
import neuroglancer.cli
import numpy as np
def add_example_layers(state):
a = np.zeros((3, 100, 100, 100), dtype=np.uint8)
ix, iy, iz = np.meshgrid(
*[np.linspace(0, 1, n) for n in a.shape[1:]], indexing="ij"
)
a[0, :, :, :] = np.abs(np.sin(4 * (ix + iy))) ... |
e1c29bac8e1c04e82bf13c5ba7b1602b5ffda53a92b05c53bce2077ca05b1c46 | Python | 1,813 | 46 | from typing import Any
from collections import defaultdict
import numpy as np
class DatasetSplitter:
"""Handles dataset splitting while keeping time series grouped together."""
def __init__(
self, data: list[dict[str, Any]], val_split: float, test_split: float, random_seed: int = 42
):
s... |
b3cec17c4c1f7e2cb6ae51492f845381845fe5d200afe53ff99820dc65eb3b25 | Python | 1,815 | 57 | #!/usr/bin/env python
from __future__ import print_function
from collections import OrderedDict
import re
regexes = {
"qbic-pipelines/rnadeseq": ["v_pipeline.txt", r"(\S+)"],
"Nextflow": ["v_nextflow.txt", r"(\S+)"],
"RColorBrewer": ["v_rcolorbrewer.txt", r"(\S+)"],
"reshape2": ["v_reshape2.txt", r"(\S... |
f318b1a2c575ee9dd6fa45dd61e03d6dc93af6d83a0c5018c917bac6ca90a894 | Python | 1,815 | 52 | import pytest
from pgmpy.example_models import load_model
from pgmpy.metrics import StructureScore
@pytest.fixture
def alarm_and_data():
alarm = load_model("bnlearn/alarm")
data = alarm.simulate(int(1e4), show_progress=False)
alarm_no_cpd = alarm.copy()
alarm_no_cpd.cpds = []
return alarm, data... |
e1c836c84feeef6c7a60e92a71f021843aa570badbfb69c758bedfbf9bd04dd5 | Python | 1,816 | 46 | import numpy as np
import numpy.testing as np_test
import pytest
from pgmpy.factors.discrete import NoisyORCPD, TabularCPD
from pgmpy.inference import VariableElimination
from pgmpy.models import DiscreteBayesianNetwork
def test_class_init():
cpd = NoisyORCPD(variable="Y", prob_values=[0.7, 0.6, 0.8], evidence=[... |
15ac9f817b8d31d43bdf59ea29f2974e944aae93e50c2f9bb7d10e39e48ecbe2 | Python | 1,818 | 61 | #
# Copyright 2017-2023 Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000 with
# Sandia Corporation, the U.S. Government retains certain rights in this software.
#
# See LICENSE for full license details
#
from __future__ import absolute_import
from __future__ import print_function
import pkg_resources... |
353d0e76deeebb8e87abd12c1d7a84e3d93054801c7fea7846c0883e1dc22a99 | Python | 1,818 | 52 | """Regression test: FasterRCNNBoxScoreTarget must not hardcode cuda/mps.
Mirrors the fix for SemanticSegmentationTarget (#546). The target must
inherit the device of the model outputs instead of assuming cuda/mps.
"""
import numpy as np
import torch
from pytorch_grad_cam.utils.model_targets import FasterRCNNBoxScoreT... |
f1951715722aaf417f6e212f14f6208790b916e6529deec191f7c31da4d5a8d2 | Python | 1,818 | 50 | import torch
from torch.nn import ModuleDict
from scvi.module.base._decorators import auto_move_data
from scvi.nn import Embedding
class EmbeddingModuleMixin:
"""Mixin class for initializing and using embeddings in a module."""
@property
def embeddings_dict(self) -> ModuleDict:
"""Dictionary of ... |
f8543f3a2562531c40fa88b3823cd0e593c65b6c25bb754141af3f8dcb22770f | Python | 1,818 | 55 | """Data modules for PyTorch Lightning."""
from argparse import Namespace
from typing import Optional
import torch
import pytorch_lightning as pl
from sklearn.model_selection import train_test_split
from calm.alphabet import Alphabet
from calm.dataset import SequenceDataset
from calm.pipeline import (
Pipeline,
... |
8e3ff85cbc9350ad2266ae22a570c2747183bf4856fdb7783fb7a18385505e87 | Python | 1,819 | 64 | """Shared path resolution for app-owned config and state files."""
from __future__ import annotations
import os
import sys
from pathlib import Path
APP_NAME = "NeuroSyncApp"
CONFIG_DIR_ENV_VAR = "NEUROSYNCAPP_CONFIG_DIR"
def repo_root() -> Path:
"""Return the repository root."""
return Path(__file__).resol... |
8ebafc6b3efb70302e21e0f2419cdea8274940318242b681f46aa5676723d5f7 | Python | 1,820 | 60 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (c) 2016-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
#
# To run the integration tests you must first fetch all the required test d... |
b957d21ee285c9103e960f3fb667e5b23fe30388e0f5efe9cb3d400b1b4cc395 | Python | 1,820 | 57 | """
Training dependency probe: used by ``main.py`` and :mod:`dlbase.train` before Hydra runs.
Import this submodule directly (``from dlbase.runtime_check import ...``); package
:mod:`dlbase` does not eagerly import PyTorch (see :mod:`dlbase` lazy exports).
"""
from __future__ import annotations
import sys
... |
4a93652817daafc8bbda99a33fae9214ebfa8b3fed97aab3217c286f5922f773 | Python | 1,822 | 54 | # 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... |
de7e6e1a50e8d62710d14e7d6aba81ecde82447d9889266af7dfb7e234553c42 | Python | 1,822 | 59 | import jax
import jax.numpy as jnp
from folx.ad import is_tree_complex
from .api import Array, ExtraArgs, FwdLaplArgs, MergeFn
from .utils import get_reduced_jacobians, trace_jac_jacT
def complex_abs_jac_hessian_jac(
args: FwdLaplArgs,
extra_args: ExtraArgs,
merge: MergeFn,
materialize_idx: Array | ... |
469248040358814289faa83d74db6c5566af7b0f4316394a919c5366e78e6237 | Python | 1,823 | 51 | #!/usr/bin/env python
##################### Imports ##################################
import argparse
import pandas as pd
import re
import numpy as np
parser = argparse.ArgumentParser()
parser.add_argument("--caller",help = "Precise the peak caller used to produce the files Genrich or Macs2", required = True)
parser... |
fe129fce1f0e80f035ccb65ea54edc2cb0844fd46d4c869a2c5a7fcf21974c72 | Python | 1,824 | 42 | import os
import numpy as np
import os.path as op
from glob import glob
from scipy.io import loadmat
base_dir = '/media/lukas/goliath/MVCA/ID1000'
raw_dir = op.join(base_dir, 'raw')
scan_infos = sorted(glob(op.join(raw_dir, 'ID*', '*DTI32', 'ScanInfo.mat')))
for scan_info in scan_infos:
print(scan_info)
si =... |
b71845968713e1fbde732cd867f6744b065f80cea6328c1fb36ff980204a7cc7 | Python | 1,825 | 45 | import numpy as np
from scipy import stats
import cv2 as cv
img = cv.imread('D:/Dataprocess/DATA/20240425/Timewindow_averaged/Electrical_tw/serial45_tw/averaged_tw19.png',flags=-1)
cv.imwrite('D:/Dataprocess/DATA/20240425/Timewindow_averaged/Electrical_tw/serial45_tw/average_tw20.png',img)
# filename = 'D:/... |
d096f9601bfb6e16bac25160f2a39f8840dadfcd7615be96e5c2f53a59f2fca8 | Python | 1,825 | 53 | # 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
import torch
from tqdm import tqdm
from fairseq import utils
from fairseq.tasks.text_to_speech import batch_mel_cepstral_dis... |
e9a39ca36ac6ca57e4046a4afd9d494ea6023d4c9bcd0f15ae14b28433350bc0 | Python | 1,825 | 65 | from __future__ import annotations
import hashlib
import io
from contextlib import suppress
from typing import TYPE_CHECKING
from typing import NamedTuple
if TYPE_CHECKING:
from pathlib import Path
class Hexdigest(NamedTuple):
md5: str | None
sha256: str | None
blake2_256: str | None
class HashM... |
9dea0bd5c9301bca0126c416c72d760e7991d075b7d364d12cf64712f4309ad7 | Python | 1,828 | 49 | # -*- coding: utf-8 -*-
"""
@author: Jack Zhang
"""
from fish_single_layer_manual import volpy_process_session
work_dir_trial_1 = '/data/zebrafish/230820/Fish2_1/stitched/aligned_layers'
work_dir_trial_2 = '/data/zebrafish/230820/Fish2_2/stitched/aligned_layers'
data_name_all = [
... |
202ef14fa70aa203ca1a0c7fda661259e40b984c0c6fedc9d75f69b4bdf0c646 | Python | 1,831 | 51 | #!/usr/bin/env python3
import sys, requests, time, re
from collections import Counter
API = "https://www.peptideatlas.org/api/promast/v1/map"
def read_fasta_peptides(path):
pep = []
with open(path) as fh:
seq = []
for line in fh:
if line.startswith(">"):
if seq:
... |
d1211217af214e12697353991416e1031761e3d740fabff3076a2181149dc384 | Python | 1,831 | 53 | # 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
import torch
from tqdm import tqdm
from fairseq import utils
from fairseq.tasks.text_to_speech import batch_mel_cepstral_dis... |
17ee5b31c6f0a71a79d39ddf85fd8dcbb1b6cdb9e8067c5bb6efe4bf947e24d1 | Python | 1,832 | 69 | # 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 torchaudio
import argparse
import json
import pathlib
def get_args():
parser = argparse.ArgumentParser(
"Assuring genera... |
33a0621e84f83595fe527540d61230d00257816e4b028d270fffeff77a97a95f | Python | 1,833 | 61 | """
Setup script for RAG-GNN package.
"""
from setuptools import setup, find_packages
with open("README.md", "r", encoding="utf-8") as fh:
long_description = fh.read()
setup(
name="rag-gnn",
version="0.2.0",
author="Hasi Hays",
author_email="hasih@uark.edu",
description="Retrieval-Augmented G... |
abd3267516b3fba406218fe578d1f39f9e528e4ca4a1c78ab78313f4025a313e | Python | 1,834 | 51 | # 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 fairseq.optim import LegacyFairseqOptimizer, register_optimizer
@register_optimizer("lamb")
class FairseqLAMB(LegacyFairseqOptimizer):
... |
de6cc95a739dca1a016c6a7c6fdf067cf18ead0754726bd765bb0376b828982e | Python | 1,834 | 56 | """Config validation and pipeline-label helpers."""
import pytest
from crossda.config import (
Config,
normalize_pipeline_labels,
resolve_pipeline_spec,
)
def test_default_config_constructs():
cfg = Config()
assert cfg.method_mode in ("smoke", "mini", "svm_radial_add", "fair", "practical")
a... |
c15af4f6c86d67c000c7e02dbcaf5b9c82e3a26aa990cdd287be168fcbfb7239 | Python | 1,835 | 47 | # 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.optim
from . import LegacyFairseqOptimizer, register_optimizer
@register_optimizer("adadelta")
class Adadelta(LegacyFairseqOpt... |
60ea364183e960be22392238068b97b3d9c518130b68880f3c263b376354e163 | Python | 1,840 | 87 | """
@file logger.py
@author Simon Yu
@date 01/25/2023
@brief Logging functions.
"""
import header
import type
def log_trace(*args, **kwargs):
if header.log_level >= type.LogLevel.trace:
print("[TRACE]: ", end = "")
print(*args, **kwargs)
return
def log_debug(*args, **kwargs):
if hea... |
7f759c6b324363738ee15856e89654d90e7b9ab2729c78c228eaf7a8736866d8 | Python | 1,842 | 52 | """Train/val/test sample ids from ``encoded_data.csv`` ``split`` column."""
from pathlib import Path
import pandas as pd
def train_val_test_ids_from_encoded_csv(
data: str | Path | pd.DataFrame,
) -> tuple[list[str], list[str], list[str]]:
"""
Return sorted unique ``sample_id`` lists for each split in t... |
7ebd4e4c1d8e54ffb039645b9e487a6232c1ba5bf814de1b59b90b2ebc8f21f2 | Python | 1,844 | 63 | import torch.nn as nn
class EncoderDecoder(nn.Module):
def __init__(self):
super(EncoderDecoder, self).__init__()
self.encoder = nn.Sequential(
#Conv1d(in_channels, out_channels, kernel_size,)
nn.Conv1d(4, 6, 200, stride=1, padding=1),
nn.ReLU(),
nn.... |
8194cbdae717e225f8002b61d352f9f3bed69f27a92809b2ae62165a297bab73 | Python | 1,844 | 48 | """Tests for ``aestetik.dataloader.CustomDataset``.
Covers issue #7 (positional indexing) by exercising __getitem__ both
with string obs_names and with a non-contiguous train_size split.
"""
import numpy as np
from aestetik.dataloader import CustomDataset
def _attach_grid_and_clusters(adata, n_t=3, n_m=3):
rng ... |
b1b04434847fec5adf1ce906a09d7dd1e406e20f6e9a803d77a56c4b63757615 | Python | 1,844 | 49 | import jax
import jax.numpy as jnp
from ...geom import masked_pairwise_self_distance
from ...types import ElectronConfiguration
def masked_jastrow_factor(
electrons: ElectronConfiguration,
spins: jax.Array,
alphas: jax.Array,
) -> jax.Array:
r"""Compute Jastrow factor that uses a double exponential.
... |
946b1e1c817a0e04952a216e785fdf6bcbed329076e8d6e5c380f3ecc7707168 | Python | 1,847 | 66 | """Utility functions for brenda_references"""
import string
import nltk
from aiotinydb.middleware import AIOMiddlewareMixin
from rapidfuzz import fuzz
from tinydb.middlewares import CachingMiddleware as SyncCachingMiddleware
class CachingMiddleware(SyncCachingMiddleware, AIOMiddlewareMixin):
"""Adding async pow... |
e200d1ee502716c6dd3dbffd7a0e46f15c237f053fb9bb349b119dbb45dce749 | Python | 1,848 | 48 | # 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 torch import nn
from fairseq.models.transformer import Linear
class StackedEmbedding(nn.Embedding):
"""Embedding modu... |
4d22782a4d5086a8d20fa4ccc77b9923087661a6b000d1a0790f5a94c7f5c591 | Python | 1,849 | 57 | import argparse
from tqdm import tqdm
from multiprocessing import Manager, Pool
from scipy.io.wavfile import read
from librosa.util import normalize
import numpy as np
import amfm_decompy.pYAAPT as pYAAPT
import amfm_decompy.basic_tools as basic
MAX_WAV_VALUE = 32768.0
parser = argparse.ArgumentParser(description=""... |
60a59e03951070108e0ce0c9ab8b4bb2e8f0713c849996125a74681d568b847d | Python | 1,850 | 58 | """Parsing and diffing two `evaluate` logs' class-metrics tables."""
import sys
from pathlib import Path
import pytest
sys.path.insert(
0, str(Path(__file__).resolve().parents[2] / "scripts/dec04_full")
)
from negative_ablation_compare import class_table, verdict # noqa: E402
REPORT = """
=== Entity CLASS metr... |
d341d0ecd1e90d3c91e670fbdcd23ec22e57c8fe67ee644f97d9445577ec4e3a | Python | 1,851 | 60 | import unittest
from unittest.mock import patch
from pyecharts import options as opts
from pyecharts.charts import Tree
TEST_DATA = [
{
"children": [
{"name": "B"},
{
"children": [{"children": [{"name": "I"}], "name": "E"}, {"name": "F"}],
"name": "C... |
9c9eb710438eb45aa99b2a1e049b55b261aa016794ac51ed7316ff07f7e7825b | Python | 1,852 | 36 | # Source code:
# https://github.com/zbmed-semtec/doc2vec-doc-relevance-training/blob/main/code/train_model/train.py
# This file includes the modifications to the source codes according to this project!
import os
import time
import logging
from gensim.models import Word2Vec
import utilities as utilities
def run(best_... |
a6138ba3486aee0edc94df620e8039b869fdf1ec67f92be45c7e38bd40f6cd3f | Python | 1,853 | 48 | import numpy as np
from Bio import SeqIO
from code.pre_processing.sequence_encode import one_hot_encode
from code.pre_processing.outer_concatenation import outer_concatenation, matrix_concatenation
from pathlib import Path
class DataProcess(object):
def __init__(self,
fasta_file,
... |
75f2c0661ac85456af867ccba53aac33bc1fddfb9a0bc3b5e6efe88e874403dc | Python | 1,854 | 44 | import subprocess
import os
def get_allowed_n_proc_DA():
"""
This function is used to set the number of processes used on different Systems. It is specific to our cluster
infrastructure at DKFZ. You can modify it to suit your needs. Everything is allowed.
IMPORTANT: if the environment variable nnUNet... |
13cab02343cc3c7a1cdac547b70fe7d9d12416c891f6d9e22a7d6c7a37a78c9a | Python | 1,856 | 47 | from typing import Optional
import requests
from batchgenerators.utilities.file_and_folder_operations import *
from time import time
from nnunetv2.model_sharing.model_import import install_model_from_zip_file
from nnunetv2.paths import nnUNet_results
from tqdm import tqdm
def download_and_install_from_url(url):
... |
20da5a929a17c76cb35d042126dc0a82e7973ff5e7ceb9def3363bf7f22ae244 | Python | 1,856 | 50 | import torch
import collections
from proteinworkshop.models.base import BenchMarkModel
from src.models.unsupervised_model import UnsupervisedModel
from src.models.contrastive_model import ContrastiveModel
from src.models.dual_model import DualModel
from loguru import logger as log
def load_model(cfg, batch):
log.i... |
acf2489c58122c7be45601f3c3bc777f2014c13070d4235cbed236dd9daec319 | Python | 1,856 | 45 | #
# 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
#
# """
# Cores used to simulate and model memristive crossbars and peripheral circuitry
# Algorith... |
ae818b8f04fec63bb56330f0aeee2015c910ed36ef67557d1742f46e8d36326c | Python | 1,856 | 43 | """How sensitive is the OCE 2F LCAO bonding eigenvalue to bond length?
The 2F figure value uses
h(r) = h0 · exp(-α (r - r0)), h0 = -8.0 eV, α = 1.5 Å⁻¹, r0 = 1.5 Å.
Plot λ⁻(r) over the typical C–C bond range.
"""
from __future__ import annotations
import sys
from pathlib import Path
ROOT = Path(__file__).resolve... |
caa6c74aa4eb13f4c6036768779f2566eb0774047d697eebee989099b3644f45 | Python | 1,856 | 59 | # Configuration file for the Sphinx documentation builder.
# -- Path setup --------------------------------------------------------------
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, u... |
6d7790f903ef70fb0ddc767db4970dfcb5959857226111bc9416b44b41b3321c | Python | 1,858 | 78 | import pathlib
from unittest import mock
import pytest
import vak
@pytest.fixture
def parser():
return vak.__main__.get_parser()
def test_parser_usage(parser,
capsys):
with pytest.raises(SystemExit):
parser.parse_args(args=[''])
captured = capsys.readouterr()
assert c... |
cf49a5a24a3ad2e2520b60406db7d5724824708009c6f0260c96b9ff09492dd1 | Python | 1,858 | 64 | from ._arraylike_field import (
CategoricalJointObsField,
CategoricalJointVarField,
MuDataCategoricalJointObsField,
MuDataCategoricalJointVarField,
MuDataNumericalJointObsField,
MuDataNumericalJointVarField,
MuDataObsmField,
MuDataVarmField,
NumericalJointObsField,
NumericalJoint... |
e1893e915314eb68f2d0d35f7a035cd58324a0cec0d2255932883015bc8be9ea | Python | 1,860 | 54 | """
Set up simulation design for training
"""
import os
import numpy as np
import zarr
import yaml
from math import ceil
from numcodecs import Blosc
zarr_path = snakemake.output.zarr
split_sizes = snakemake.params.split_sizes
split_names = snakemake.params.split_names
random_seed = snakemake.params.random_seed
n_sim... |
7f2609f9b7b3d053733b4257ac9a39e552f50e3782effd96a0ff0c44ef4959a0 | Python | 1,862 | 47 | # coding=utf-8
# Copyright 2020 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
#
# Unless required by applicable... |
4e1582384a8498fcfd98ef368fa6d17dad01691dc1a4b4afaac3bda9e5896cdb | Python | 1,864 | 49 | import novae
from novae._constants import Keys
from novae.utils import get_reference
def test_get_reference():
adatas = novae.toy_dataset()
novae.spatial_neighbors(adatas)
assert get_reference(adatas, "largest").n_obs == 1958
assert len(get_reference(adatas, "all")) == 3
assert get_reference(a... |
fbb8cf76481d4cd511edac4c2cf3754310329ff7225e3704501cfb8f147fb211 | Python | 1,864 | 54 | """Constants used by vaktestdata and scripts that rely on it."""
import json
import pathlib
from .config_metadata import ConfigMetadata
HERE = pathlib.Path(__file__).parent
TEST_DATA_ROOT = HERE / ".." / ".." / "data_for_tests"
CONFIG_METADATA_JSON_PATH = TEST_DATA_ROOT / "configs" / "configs.json"
with CONFIG_METADA... |
17c39da6e886e050fe40f974fab82a9adbf03f946e8c90ebeea0fb83eaefd83b | Python | 1,865 | 54 | # 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
import torch
from fairseq.data import MonolingualDataset
from fairseq.tasks.language_modeling import LanguageModelingConfig,... |
b831a2b52fa22e8d33fecbd69ec47a0db150b4aa7226e6793672f46e9524d36e | Python | 1,865 | 39 | # Copyright 2020 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 of the License at
#
# http://w... |
67ef3352694add9dbe96d18c6325137494fe4aceb86e84661a5ab678ea82bf0d | Python | 1,866 | 58 | # 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
import torch
from fairseq.data import LanguagePairDataset, TokenBlockDataset
from fairseq.data.concat_dataset import ConcatDa... |
8cfe2a58d8e622785befba316c52e660e204d078c030e14be05aad34f4932cb3 | Python | 1,866 | 71 | #!/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 re
from collections import OrderedDict
import torch
from fairseq.file_io import PathManager
... |
4edf05d3ea683e48e322b844de5d78d0dd988ae1148355ad97112adf0af324d2 | Python | 1,867 | 36 | import pandas as pd
import numpy as np
import sys
# python convert_cleansumstats_output_to_mixer_format.py /cluster/projects/p697/projects/SUMSTATv3/v3.1/STD_GRCh37/CTG_COG_2018.sumstats.gz CTG_COG_2018_mixer.sumstats.gz
if __name__ == "__main__":
fname = sys.argv[1]
fname_out = sys.argv[2]
print(f'process... |
76328bfc6cdf147feb946e9926b6d0958bdb9b2d5837109722249466ef903dd6 | Python | 1,868 | 49 |
class ReportableException(Exception):
"""Simple exeception with message"""
def __init__(self, msg):
self.msg = msg
class InvalidArguments(ReportableException):
"""Logical Error for unexpected arguments"""
def __init__(self, msg):
super(InvalidArguments, self).__init__("Invalid argument... |
856d482a7cf0ce16e663973b6014afc63801bcfac4658beeb36b261d5c12ad02 | Python | 1,868 | 63 | #!/usr/bin/env python
# Author_and_contribution: Niklas Mueller-Boetticher; created template
# Author_and_contribution: Kirti Biharie; implemented Davis-Bouldin score
import argparse
parser = argparse.ArgumentParser(description="Calculate Davies-Bouldin Score (scikit-learn)")
parser.add_argument(
"-l", "--label... |
8fc48d1e4e71f99ed48d7b75899149bbc9cc379ab3491ff6530954b5ae6df2a4 | Python | 1,868 | 44 | """Small lightweight utilities used frequently in GOATOOLS."""
__copyright__ = "Copyright (C) 2016-2018, DV Klopfenstein, H Tang, All rights reserved."
__author__ = "DV Klopfenstein"
def extract_kwargs(args, exp_keys, exp_elems):
"""Return user-specified keyword args in a dictionary and a set (for True/False ite... |
fad69747854874f5378420eb22f30575fb2925b46aadf7de14bc6046aa72f7c1 | Python | 1,868 | 58 | # 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 enum import Enum
class TextCompressionLevel(Enum):
none = 0
low = 1
high = 2
class TextCompressor(object):
def __init... |
af83e81e5433904477bf8d5ee20926cfd85861b3b41fa996b132bcfdb6e66672 | Python | 1,869 | 33 | import pytest
import torch
from scvi.model._utils import parse_device_args
@pytest.mark.skipif(not torch.backends.mps.is_available(), reason="requires an MPS device")
def test_auto_accelerator_falls_back_to_cpu_when_mps_available(monkeypatch):
# Regardless of whether this suite is itself running under SCVI_ALLOW... |
c6fbac1f92995d2c558f6a01d1ae1d93c4e1febbcdfc7211fbf76b527e4d2df9 | Python | 1,869 | 39 | """LOD/LOQ 95% CIs consistent with the paper's Table 3.
Same estimator as paper2/interpret_food.lod_table (LOD = 3.3*sigma/|S|), cluster-bootstrapped
over whole physical samples on the SAME hold-out predictions used for the published point values."""
import numpy as np, pandas as pd, os, sys
sys.stdout.reconfigure(enco... |
a929943403b7060aa9ae49ac63ba9f1f6dd17cbbbfe25a8df8e4022913a86c79 | Python | 1,871 | 59 | # 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.functional as F
logger = logging.getLogger(__name__)
def _cross_entropy_pytorch(logits, target... |
0810e630ecf8f459d53ad493073df1c1da734e46073b96edeb8b47e8d0f5405f | Python | 1,872 | 65 | # 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 torch
from tqdm import tqdm
from data_utils import load_audio_path
from fairseq.data.codedataset import get_f0_by_filename
d... |
5d40e985fc0f19bf37bf1b1dc51654ea776fd6278bbf00df47bf2ad9194b7043 | Python | 1,872 | 60 | # -*- coding: utf-8 -*-
"""
@Time:Created on 2019/4/30 16:10
@author: LiFan Chen
@Filename: word2vec.py
@Software: PyCharm
"""
from gensim.models import Word2Vec
import pandas as pd
import numpy as np
def seq_to_kmers(seq, k=3):
""" Divide a string into a list of kmers strings.
Parameters:
seq (strin... |
ff1c14b64942ad2298b7d47f381216eaa9abf2ef30cbc2b457bdef643a461515 | Python | 1,873 | 51 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Functions to resample an image. Intended to downsample images to ~512x512 px"""
from typing import Callable, List, Optional, Tuple
import numpy as np
from skimage.transform import rescale
from .types import MetaLike_ND2
def resample_image(
image: np.ndarray, me... |
c3c70a2a0599662bbfdf4523112bda620845f13f3b6919c37236add8ccc54312 | Python | 1,875 | 56 | #!/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.
"""
Helper script to pre-compute embeddings for a flashlight (previously called wav2letter++) dataset
"""
import argpa... |
e9f86bec54c6c707feb50b5b0b4be42d479ecf1d5e66e1d76a8144feba448cf9 | Python | 1,875 | 52 | """Shared fixtures: synthetic EEG sessions so tests need no real data."""
from __future__ import annotations
import numpy as np
import pytest
def make_synthetic_sessions(n_sessions=5, n_trials=40, n_ch=22, n_times=256, seed=0):
"""Deterministic synthetic motor-imagery sessions.
Each session is a dict ``{"x... |
e061fea8334e94ffff31e969549abd48381b101ec20d8061080d9d816881622b | Python | 1,878 | 32 | import matplotlib.pyplot as plt
import numpy as np
plt.style.use(['science','nature'])
x_ax = np.load('new_inf_comp_x.npy')
y_base = np.load('new_inf_baseline_y.npy').reshape(-1,1)
y_sot = np.load('new_inf_sotmram_y.npy')
y_sotnorm = 100*y_sot/y_base
y_rram = np.load('new_inf_rram_y.npy')
y_rramnorm = 100*y_rram/y_ba... |
aab3ddfdb089dea5ad64763af74cf17fe348bd3b7706d320f2015fa9fd292b37 | Python | 1,879 | 55 | ## Wrapper for crystalgrw.cli.train.main ##
import time
import argparse
from omegaconf import DictConfig, OmegaConf
import torch
import torch.multiprocessing as mp
from crystalgrw.cli.train import run_train
def main(rank, world_size, cfg):
run_train(rank, world_size, cfg)
if __name__ == "__main__":
parse... |
1f5d83299c880d1d3a6b49049de2fac6fcfb05ba723cb08de51bafed35093bad | Python | 1,880 | 54 | """Shared helpers for the NONAN Python test suite.
Design note -- why fixtures on disk instead of generating signals in each
language:
MATLAB and NumPy cannot draw the same random numbers. Any cross-language test
that generates its own series is comparing two different realisations and can
only ever check loose stati... |
878c2f7695afe45bf3826ea9ca6880ed5788f9e7f7b384c18dcdd652060a8ba0 | Python | 1,880 | 54 | import torch
import torch.nn.functional as F
from core.utils.utils import bilinear_sampler
class CorrBlock:
def __init__(self, fmap1, fmap2, num_levels=4, radius=4):
self.num_levels = num_levels
self.radius = radius
self.corr_pyramid = []
# all pairs correlation
corr = Cor... |
db80b6df8b3ebf7386c649e9e6c6f9042125feed530b787afcc272ce7995e0b2 | Python | 1,880 | 63 | try:
from torch_geometric.data import LightningDataset
except ImportError:
from torch_geometric.data.lightning import LightningDataset
from torch.utils.data import DataLoader
class AbstractDataModule(LightningDataset):
def __init__(self, cfg, train_dataset, val_dataset, test_dataset):
super().__in... |
dd7e501f3e6546a2c74059608a55d39469ad4ac9bc472843b20910e16533c7ed | Python | 1,880 | 44 | import numpy as np
import pandas as pd
import sklearn
# The function is modified from https://github.com/jianhuupenn/SpaGCN/blob/master/SpaGCN_package/SpaGCN/util.py
def refine(sample_id, pred, dis, shape="hexagon"):
refined_pred = []
pred = pd.DataFrame({"pred": pred}, index=sample_id)
dis_df = pd.DataFra... |
e45df65b750123400c9b681933a4d34ce987867fe6465ef799189ee158b774bc | Python | 1,880 | 60 | from src.utils import read_gtf
import polars as pl
riboseq = read_gtf("nextflow_results/V47/orfanage/UCSC_tracks/riboseq.gtf")
novel_CDS = read_gtf("nextflow_results/V47/orfanage/UCSC_tracks/novel_CDS.gtf")
classification = pl.read_parquet("nextflow_results/V47/final_classification.parquet")
peptides = read_gtf("ne... |
8fef77567e06a946b46845c5422be402d4d5e1481b935e0a939ecd0b65a37ad8 | Python | 1,881 | 57 | """Shared helpers for syncing example READMEs to docs/examples/."""
from __future__ import annotations
from pathlib import Path
EXCLUDE_DIR_NAMES = {
'API (copy)',
'__pycache__',
'.gmx_mmpbsa_temp',
}
EXCLUDE_FILE_SUFFIXES = (
'.log',
'.kate-swp',
)
SKIP_DOCS_RELATIVE = {
Path('gmx_MMPBSA_t... |
a10ca1270b5b9d5044f8b6638a98edfac9f30a82a90844af1253e6b6322a2ec4 | Python | 1,881 | 63 | #!/usr/bin/env python
# Author_and_contribution: Niklas Mueller-Boetticher; created template
# Author_and_contribution: Kirti Biharie; implemented Calinski-Harabasz score
import argparse
parser = argparse.ArgumentParser(description="Calculate Calinski-Harabasz Score (scikit-learn)")
parser.add_argument(
"-l", "... |
4bd9316568ec833e1dbf6d290b6166efc90247ec8f5fc6fe1892f9f7dcab0ae2 | Python | 1,883 | 46 | import matplotlib
matplotlib.use('TkAgg')
res = {"DTCR": {"PISTE": 0.9264718981831416, "TEIM": 0.9012353342571597, "ERGO": 0.934445901875,
"epiTCR": 0.8943023353125001, "NetTCR-2.0": 0.9247589841503963},
"DTCR-R": {"PISTE": 0.8829555691267463, "TEIM": 0.8658527947723582, "ERGO": 0.913677704... |
75991aca94292604ad7b41094cde5b7e3d60b15d8801b8c29c788b8e95fba932 | Python | 1,884 | 63 | """Lightning DataModule for NPZ patch folders (train/ / test/).
Supports datasets: WMB, CA1, Simulation via registry (``datasets.plugins``).
"""
from __future__ import annotations
import pytorch_lightning as pl
from omegaconf import DictConfig
from torch.utils.data import DataLoader
from dlbase.registry ... |
f14522bbda1ede3a477edc09dae8383f065e5a06a3c29e9f6453ece7202aa991 | Python | 1,884 | 49 | # 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 fairseq.models import FairseqDecoder, FairseqEncoder
# a container for different encoders with training samples from different modalit... |
2ee067f403ec84853842deb2723eab1efb84a2188ebd9069b004f3fbf3cb6b3a | Python | 1,886 | 68 | # 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 random
import numpy as np
import torch
from .shardedtensor import *
from .load_config import *
def set_seed(seed=43211):
random.s... |
49343d2b59600dbfc717ecccac610a83d3e630bf1875e10a37d9d98cd2bf60ad | Python | 1,886 | 63 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
from fairseq.data import BaseWrapperDataset, data_utils
class AddClassTargetDataset(BaseWrapperDataset):
def __init__(
... |
5cd6510a32ff6b0353849f4e6fe36c66f1efd7a3844200f5cc0135b788b51ee5 | Python | 1,889 | 67 | from __future__ import annotations
import json
import os
from pathlib import Path
from typing import TYPE_CHECKING
from typing import Any
from poetry.core.constraints.version import Version
if TYPE_CHECKING:
from collections.abc import Callable
VERSION_3_7_1 = Version.parse("3.7.1")
def build_venv(path: Pat... |
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