sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
8c726e04471ab137e6e8fdd50e321ce804eaa268a3d3102f224b76d27eb8d4d7 | Python | 4,728 | 127 | import subprocess
from pathlib import Path
import nibabel as nib
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from nilearn import plotting
from nilearn.image import mean_img
# Define the directory containing the derivatives
base_dir = Path('/data/elevchenko/MovieProject2/')
deriv_dir = base_d... |
8fed69f6fe99faa5aa49569af9ff3b53973804ae59a9de158e5a4f00305df53d | Python | 4,729 | 134 | #!/usr/bin/env python3
"""
Make a 2-way Venn diagram comparing fusion transcripts between
SFARI (Xu and Rynard et al.) and Patowary et al. datasets.
Transcripts are compared by intron chain:
multi-exon : 'chrom:strand:e1end-e2start,e2end-e3start,...'
mono-exon : 'chrom:strand:start-end:mono'
Only transcripts wit... |
0e689cf26ba8e59cdccb351c073cac57a7377a8b74dd75684ff9f15ea392b06a | Python | 4,731 | 100 | # 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... |
9dc4d4cd45a5183d58e36f3b7dd670f43ce225c874a73a0d150d5e8bfb412156 | Python | 4,733 | 152 | import json
import os
import pkgutil
import re
import yaml
from stripedhyena.utils import dotdict
from stripedhyena.model import StripedHyena
from .tokenizer import CharLevelTokenizer
MODEL_NAMES = [
'evo-1.5-8k-base',
'evo-1-8k-base',
'evo-1-131k-base',
'evo-1-8k-crispr',
'evo-1-8k-transposon',... |
ef24ad00b3bfe1a393c873f0848f1de78924fad43945d216f38dc3f9f2c3ff23 | Python | 4,733 | 135 | # coding=utf-8
PROJECT_PATH =r"D:\FangX24\code\LO-Det-main\mnt\Datasets\NWPU/"
DATA_PATH = r"D:\FangX24\code\LO-Det-main\mnt\Datasets\NWPU/"
DATA = {"CLASSES":['airplane', 'ship','storage tank','baseball diamond', 'tennis court', 'basketball court', 'ground track field', 'harbor', 'bridge', 'vehicle'],
"NUM"... |
98fbe0df1896827a6b668770f6847ea52456aa103c3f94ab6bd42facac8068ab | Python | 4,738 | 143 | # 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 dataclasses import dataclass, field
from typing import Dict, List, Optional
import torch
from fairseq.dataclass import Fa... |
00a0121c262a2201944caa0ecaf9ac6f2cc47a43254c388405c72a0c8f89c9d9 | Python | 4,740 | 148 | """The package config `brenda_references` ships, and the host that is not.
`config.py` reads `config.toml` at import and the package's `__init__` reaches
it, so a tree without that file cannot execute `import brenda_references` at
all. It was invisible to git for years because `.gitignore` hid the
machine-local root `... |
204d855b446e01ae6ee6499da0106514093c0e5a2ed97c5ab755b889fcd8bef0 | Python | 4,740 | 141 | #!/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 os
import re
import shutil
import sys
pt_regexp = re.compile(r"checkpoint(\d+|_\d+_\d+|_[a-z]+... |
a95309dccbde799119356c3d694b27c1421fd83a19aa939fcaab25128f468c7d | Python | 4,740 | 137 | #!/usr/bin/env python
# ENCODE DCC compare signal to roadmap wrapper
# Author: Daniel Kim, Jin Lee (leepc12@gmail.com)
import warnings
from matplotlib import pyplot as plt
import sys
import os
import argparse
from encode_lib_common import (
strip_ext_bigwig, ls_l, log, mkdir_p)
import numpy as np
import pandas as... |
61f29266634948c4ee84b6db83b16b7d6096b33ea65412641014247835fee077 | Python | 4,741 | 159 | from __future__ import annotations
from typing import TYPE_CHECKING
from typing import Any
from typing import Protocol
if TYPE_CHECKING:
from collections.abc import Callable
from contextlib import AbstractContextManager
from pathlib import Path
from cleo.io.inputs.argument import Argument
from c... |
1491a3a457c36b412bf0ac77dbf01780ca1b59c331934cad9b9deeaeaa8e85cf | Python | 4,744 | 125 | # 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
import torch.nn.functional as F
from fairseq import utils
from fairseq.incremental_decoding_utils import with_incremental_state
... |
2a269c4f942b5024413a9db4d6bd654ddb9116c9201b38134e6c14579b211e9b | Python | 4,744 | 141 | # 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.
# The code in this file is adapted from the BeiT implementation which can be found here:
# https://github.com/microsoft/unilm/tree/master/beit... |
bf7325ece3f85a00257d300e5cd2f5f7994ea7ed838ea0e73575e371bc584b20 | Python | 4,744 | 122 | '''Code Tests'''
# Authors: Ryan Thorpe <ryvthorpe@gmail.com>
# Darcy Diesburg <darcy.diesburg@gmail.com>
import os.path as op
import numpy as np
from scipy.io import loadmat
import SpectralEvents.spectralevents as se
def test_event_comparison():
'''Test if the output from MATLAB and Python event det... |
f785317659ff19572a6a162d0f63779e3f48a7287926c39ec38c193c06466161 | Python | 4,746 | 109 | from copy import deepcopy
import numpy as np
def merge(dict1, dict2):
keys = np.unique(list(dict1.keys()) + list(dict2.keys()))
keys = np.unique(keys)
res = {}
for k in keys:
all_configs = []
if dict1.get(k) is not None:
all_configs += list(dict1[k])
if dict2.get(k)... |
d250b2cda961fa8971a875eb58ed994e7f6ee3cdac6249b0d21a4d4d7480d08e | Python | 4,749 | 124 | # Copyright 2020 The Google Research Authors.
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# Adapted from https://github.com/yang-song/score_sde_pytorch which is released under Apache license.
# Key changes:
# - Introduced batch_idx argument to work with graph-like data (e.g. molecules)
# ... |
36d4973fe8d453c364d4ff33ef8d41e8d5402655271f574e0a9e1bb3cdec9963 | Python | 4,753 | 113 | '''
This script optimizes logistic nonlinearities for a variety of Gaussian distributions and plots the optimal parameters.
Author: Jonathan Gant
Date: 29.08.2024
Optimized for performance
'''
import numpy as np
from joblib import Parallel, delayed
from tqdm import tqdm
from scipy.stats import norm
import os
import sy... |
120fa652eb3c52fdbd81bce9151e9429ea45915a1ae0db56125e80b8dc272c09 | Python | 4,754 | 127 | import os
from abc import ABC
import vtk, qt, ctk, slicer
from slicer.ScriptedLoadableModule import *
from slicer.util import VTKObservationMixin
#
# NetstimPreferences
#
class NetstimPreferences(ScriptedLoadableModule):
"""Uses ScriptedLoadableModule base class, available at:
https://github.com/Slicer/Slicer/blo... |
41d7292aa491825eae44a759acf70337697df553a6f87d8b1e53cfa9efe1f6f6 | Python | 4,754 | 87 | import torch
import numpy as np
import torch.nn.functional as Func
from .light import Light
from scipy.special import j1 # J1: First-order Bessel function of the first kind
class Dun_propagator_1D:
# This function must be carefully used to satisfy input_pitch <= wavelength/(2*NA) gurantee the accuracy, where NA i... |
675f0825690a701dccea2d22a531e3769965381e68ef7ab735b967c9fa0d563c | Python | 4,754 | 150 | import os
import zipfile
from functools import lru_cache
from pathlib import Path
from typing import Callable, Dict, Iterable, Literal, Optional
import omegaconf
import pandas as pd
import torch
import wget
from graphein.protein.tensor.data import Protein
from loguru import logger as log
from sklearn.preprocessing imp... |
1d12cd80aba80a9cee91ba0e0273089c382a0a9675f1bd835a6778a32fb5b245 | Python | 4,755 | 116 | import os
from torch.utils.data import Dataset
from pycocotools.coco import COCO
import config.cfg_lodet as cfg
from utils.utils_coco import *
class COCODataset(Dataset):
"""
COCO dataset class.
"""
def __init__(self, data_dir='COCO', json_file='instances_train2017.json',
name='train2... |
1c64117678841fd9a7181906480bd0cecf9018b713a044a39a1e84d32d4f296d | Python | 4,759 | 142 | import logging
from typing import List
import numpy as np
import scipy.io
# set up logger
logging.basicConfig(
level=logging.INFO, format="%(asctime)-15s %(levelname)s:%(message)s"
)
logger = logging.getLogger(__name__)
def collapse_and_trim_neighborhoods(
nb_list, keep_fraction=0.95, keep_limit=None, target... |
d62faad073ef898d15c202e5ca205c2f2087cbf597abea81d8aae25215e6c97c | Python | 4,759 | 116 | from ... import options as opts
from ... import types
from ...charts.chart import Chart
from ...globals import ChartType
class Tree(Chart):
"""
<<< Tree diagrams >>>
Tree diagrams are used primarily to visualize tree data structures,
which are special hierarchical types with unique root no... |
6752ff9fa6b77690bec0bb03a2368b64e1729dc17c6ffbcf9d805e6b5149430e | Python | 4,760 | 151 | #!/usr/bin/env python
# Author_and_contribution: Niklas Mueller-Boetticher; created template
# Author_and_contribution: Jieran Sun; Implemented quality control code
import argparse
# TODO adjust description
parser = argparse.ArgumentParser(description="quality control (gene/cell filtering) using scanpy")
parser.add... |
f44d6f89a6d0261f5f7f15df36885aa921eb8f19840006650492f7ebcf52e3a2 | Python | 4,761 | 128 | import torch
def to_device(tensor, device):
"""
Moves the tensor to the specified device if the tensor is not None.
"""
return tensor.to(device) if tensor is not None else None
def apply_mask(tensor, mask, mask_dim=-1):
"""
Applies a mask to a tensor by broadcasting the mask along the last d... |
5c2e18c48f647139e8645453cc50e16ce94ec22b36247527a406963feeffa165 | Python | 4,763 | 116 | import os
from torch.utils.data import Dataset
from pycocotools.coco import COCO
import config.cfg_npmmrdet_dior as cfg
from utils.utils_coco import *
class COCODataset(Dataset):
"""
COCO dataset class.
"""
def __init__(self, data_dir='COCO', json_file='instances_train2017.json',
name... |
3eec4717ffaf38a18cea6cc8ac560ff50ec511366458bf20fa7fd8c7a26195d8 | Python | 4,764 | 142 | import logging
import os
import re
from typing import List
import numpy as np
import yaml
import loompy
class Annotation:
unknown_tags: set = set()
def __init__(self, category: str, filename: str) -> None:
with open(filename) as f:
doc = next(yaml.load_all(f, Loader=yaml.SafeLoader))
if "name" in doc:
... |
eda1ce51a6ae052dafe438d41abfcd3fbea0251945b4b9c860a0206986dd71c0 | Python | 4,766 | 128 | from typing import Union
import numpy as np
import pandas as pd
from scipy.optimize import minimize
from uncertainties import ufloat
from ..log import MetricLogStream
HARTREE_TO_KCAL = 627.509608031
def relative_energy(E, loc=None):
if loc is None:
return E - E.mean(-1, keepdims=True)
elif loc == "... |
62cd730b8af40e6803153b06d8d12beeb38e21ca831f16ac5793eb4f51f8f28a | Python | 4,767 | 146 | import numpy as np
import pandas as pd
import pytest
from pgmpy.factors import FactorDict
from pgmpy.factors.discrete import DiscreteFactor
@pytest.fixture
def phi1():
return DiscreteFactor(["x1", "x2", "x3"], [2, 2, 2], range(8))
@pytest.fixture
def phi2():
return DiscreteFactor(["x4", "x5", "x6"], [2, 2,... |
92fde8bbee887fde51ba5437458395bdaf35210c59adf05769dee302404d7ced | Python | 4,767 | 135 | """
Implement unsupervised metric for decoding hyperparameter selection:
$$ alpha * LM_PPL + ViterbitUER(%) * 100 $$
"""
import argparse
import logging
import math
import sys
import kenlm
import editdistance
from g2p_en import G2p
logging.root.setLevel(logging.INFO)
logging.basicConfig(stream=sys.stdout, level=lo... |
bf78aa7af5fa375b3141eca3826efae6178f99d63855c548afe482f74565a9dd | Python | 4,767 | 150 | import numpy as np
import pandas as pd
from scipy import stats
from ._base import _CITestResult
from .pearsonr import Pearsonr
class PearsonrEquivalence(Pearsonr):
r"""
Pearson equivalence test [1] for conditional independence on continuous data.
This test first computes the partial correlation coeffici... |
7b005ecf1ccf638ded7688afba3d498e3b4fdd7e1943d10a285f26e2a3bc4aaf | Python | 4,768 | 143 | from __future__ import annotations
import os
import sys
import textwrap
from pathlib import Path
from typing import TYPE_CHECKING
import findpython
import packaging.version
import pytest
from poetry.core.constraints.version import Version
from poetry.utils.env.python import Python
if TYPE_CHECKING:
from unit... |
9958467f372d9adfa1c57e3825aa45cbdeeb0e6af10e84ea6fc766ab3152bc13 | Python | 4,768 | 145 | import sys
import tsfdata
import sqlite3
import numpy as np
from PIL import Image
import cv2
import tqdm
from bisect import bisect_left, bisect_right
from typing import Optional
import os
import math
import os
from multiprocessing import Pool
import argparse
def get_args():
parser = argparse.Argu... |
61c82c744347ed6e9f686877c884d7674fb4c48fe80daf71b4dee6058f099890 | Python | 4,770 | 176 | # 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.
# author: adefossez
import functools
import logging
from contextlib import contextmanager
import inspect
import time
logge... |
624ceb395232f2f8fd46d4c87e1f1335987ca9cbc555314cc5ceab92ab37de4c | Python | 4,771 | 149 | from npyx.c4.dataset_init import (
N_CHANNELS,
WAVEFORM_SAMPLES,
extract_and_check,
get_paths_from_dir,
prepare_classification_dataset,
)
from torch.utils.data import Dataset
import npyx
import torch
import numpy as np
import os
import pandas as pd
from celltype_ibl.params.config import DATASETS_DIR... |
817696908c5913317309a61097f3bb9570e8d9edf66e86488afc53221e979e21 | Python | 4,771 | 140 | import numpy as np
def gaussian_2d(positions: np.ndarray, center, sigma: float) -> np.ndarray:
"""
Inputs:
positions: N x 2
center: [center_x, center_y]
sigma: spread of gaussian
"""
sigma_sq = sigma**2
return (
1.0
/ (2.0 * np.pi * sigma_sq)
* np.ex... |
e92038d7c27d7397858f1861973dc9b061d8ac6e39ad40d47990eb54ba479ce7 | Python | 4,771 | 141 | import os
import zarr
import torch
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from math import ceil
from torch import Tensor
from torch.utils.data import DataLoader
from lightning import LightningModule, Trainer
from sbi.inference import DirectPosterior
from sbi.utils import BoxUniform
i... |
241cb58614e0e24241bb5f77e9cba7200d03a5016603225d86e13919d1e2df3c | Python | 4,772 | 70 | """Validate and copy the official TCIA single-series archive without rewriting DICOM.
Usage: python lite-web/scripts/prepare-pancreas-ct-demo.py downloaded.zip
Requires pydicom and numpy (inspection only). No credentials or network access.
"""
import hashlib
import io
import json
from pathlib import Path
import shutil... |
3ffd7e90465d94309de32f0c75c96bb151913b57693fc99814745205ffbd93e0 | Python | 4,775 | 97 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'UI/ShatterValveTestUI.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.se... |
e02434924fd808ed0e7c8b747b0ea9dece2bb7d0ac0a080065109dc776ba4785 | Python | 4,775 | 131 | # 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 fairseq import utils
from fairseq.logging import metrics
from fairseq.criterions import register_criterion
from .label_smoo... |
be7ffea9bdcc4b2546e664881d8b63f8ef0db2fee871a19ad1dfa0d3c60314a7 | Python | 4,776 | 163 | from functools import partial
import numpy as np
import pytest
from scvi.data import synthetic_iid
from scvi.model import SCVI
from scvi.model.base._de_core import _prepare_obs
from scvi.model.base._differential import (
DifferentialComputation,
estimate_delta,
estimate_pseudocounts_offset,
)
def test_f... |
519ca21be7364e6750ff2ef36309090e8120bc738b928f88fc09eb1761958852 | Python | 4,777 | 133 | import argparse
import csv
from pathlib import Path
from importlib import resources
from typing import List, Optional, Union
import numpy as np
import torch
import torch.nn.functional as F
from evo2 import Evo2
def read_prompts(input_file):
"""Read prompts from input file or built-in test data.
Args:
... |
532b53a855da6079277aee5bc172c7fbee4bf2cbe62b8bae83c44f68dd2156fe | Python | 4,778 | 136 | """
Unit tests for src/math_ops/time_converters.py.
NOTE — known bug in current code:
CONVERSION_FACTORS = {"minutes": 1, "seconds": 60, "hours": 1/60}
with formula: value * CF[from_unit] / CF[to_unit]
This gives the wrong direction for convert_time, e.g.:
convert_time(60, "seconds", "minutes") → 3600 (sho... |
43f18c01e2e50b4b3a9558e2bef6d8dbc9cbb6a93178a161cc6ed1973f888841 | Python | 4,779 | 124 | """Get GO IDs from command-line arguments or from an ASCII file."""
from __future__ import print_function
__copyright__ = "Copyright (C) 2016-2019, DV Klopfenstein, H Tang. All rights reserved."
__author__ = "DV Klopfenstein"
import os
import re
from goatools.gosubdag.go_tasks import get_go2obj_unique
from goatools.... |
5c7f7051bb98089f456c095708f4f954dcd97aa6561b028b877ec4be753ef8f1 | Python | 4,779 | 152 | from __future__ import annotations
import functools
import logging
import os
import sys
import threading
import time
from concurrent.futures import wait
from concurrent.futures.thread import ThreadPoolExecutor
from typing import TYPE_CHECKING
import pytest
from poetry.utils.threading import AtomicCachedProperty
fro... |
d0a790414c91cdfb96ef15fd0a910f4876778a00c92c80ed0aa8706a0bd6c971 | Python | 4,781 | 167 | import sys
ROOT_DIR = __file__.rsplit("/", 3)[0]
if ROOT_DIR not in sys.path:
sys.path.append(ROOT_DIR)
import uvicorn
import os
import requests
import json
from utils.server_tool import get_ip, check_port
from fastapi import FastAPI
app = FastAPI()
BACKEND_DIR = f"{ROOT_DIR}/demo/backend"
# Map the function ... |
32c2a8aec2684c6cb8d28c3a44d86c074310477d23972f7afedb45bf9bdf9258 | Python | 4,782 | 133 | import cv2
import numpy as np
import string
def get_optimal_font_scale(text, width, height, fontFace, thickness, margin=0.9):
"""
Find the largest font scale such that the text (in a single line) fits
inside the rectangle [0, width] x [0, height], given a margin.
This function does a simple binary sea... |
7de71e5670e54e28ead4a2ac5567855a06dc078e53f337773ec2e4407f2b4d69 | Python | 4,782 | 103 | import logging
import warnings
from typing import List
import numpy as np
import scipy.sparse as sparse
from numba.core.errors import NumbaPendingDeprecationWarning, NumbaPerformanceWarning
from pynndescent import NNDescent
from scipy.sparse import SparseEfficiencyWarning
import loompy
from cytograph.decomposition im... |
45155086f217dd1c54f6a1df28665597d65ab40102eb8b1113b3f74060eaf619 | Python | 4,785 | 157 | from functools import partial
from typing import Literal
import jax
from folx import register_function
from .custom_gradients import mhsa_backward, mhsa_forward, mhsea_backward, mhsea_forward
from .forward_laplacian import mhsa_forward_laplacian, mhsea_forward_laplacian
from .mhsa import mhsa
from .mhsea import mhse... |
0620999623e44b691fa36c522f265cefa41cbe99c5642d31deaf6d06af1eabcc | Python | 4,786 | 105 | import os
import sys
from typing import Iterable, Tuple
import pytest
# Force headless offscreen rendering for Qt on macOS CI environments
if sys.platform == 'darwin':
os.environ['QT_QPA_PLATFORM'] = 'offscreen'
def pytest_configure(config):
os.environ['QT_DEBUG_PLUGINS'] = '1'
def pytest_runtest_logstart... |
ff47c1dc9e19ebcebe051232086d8077a78d6fd2d89680cd24b7245d17c71696 | Python | 4,787 | 123 | """
MAP Pipeline — Merge & Adapt Pipeline (supervised selection)
1) Score each feature × DA × classifier by cross-session CV
2) Merge ALL training sessions, apply best DA, train classifier
3) Return DA accuracy and no-DA baseline
"""
from __future__ import annotations
import logging
from typing import Any, Dic... |
2f3051f37218cc939501370cc1671b14ba91bfe1adcb25b7e9ecf496501f568a | Python | 4,788 | 144 | """`Trainer.fit` against a real model's `run_epoch`, not a stub.
`test_trainer.py` drives a model defining its own `run_epoch`, so a reverted
three-argument signature would pass that whole file. This puts one real
`BrendaClassificationModel` batch through `fit`, on a tiny injected BERT and a
tiny on-disk encodings fil... |
bad2f8129997dfd1b4f0ca26d6e8de2b41aba7f725336aae8df3c1ede64de8e0 | Python | 4,788 | 139 | import sys
from os import makedirs
from os.path import dirname, realpath, exists
current_dir = dirname(dirname(realpath(__file__)))
sys.path.insert(0, dirname(current_dir))
import pandas as pd
import os
from config_path import *
from data_extraction_utils import get_node_importance, get_link_weights_df_, \
get_dat... |
f6b208e8b742bd77efa9a0e04d56ef6c4fde72db7253d0f3da67d6fd08337f2d | Python | 4,789 | 122 | import torch
import torch.distributed as torch_dist
import graphein
import lovely_tensors as lt
from typing import Literal, Optional, Union
from loguru import logger as log
from omegaconf import DictConfig
from proteinworkshop.models.base import BenchMarkModel
from proteinworkshop.types import EncoderOutput, ModelOutp... |
8741aa7e6ab408218a7bf5629a38f5ac8de3f127b710569eb72b4917ebbb873c | Python | 4,792 | 144 | from celltype_ibl.models.WvfAug import get_wf_transform
from celltype_ibl.models.AcgAug import get_acg_transform
from celltype_ibl.params.config import DATASETS_DIRECTORY
from torch.utils.data import Dataset
import npyx
import torch
import numpy as np
import os
import pandas as pd
class EmbeddingDataset(Dataset):
... |
fc2238a286e78c9ff7c1b15ee5244b760a6c0c7c958a5b33fa39e0b3256352aa | Python | 4,792 | 127 | import contextlib
import tempfile
import unittest
from io import StringIO
import numpy as np
from tests.utils import create_dummy_data, preprocess_lm_data, train_language_model
try:
from pyarrow import plasma
from fairseq.data.plasma_utils import PlasmaStore, PlasmaView
PYARROW_AVAILABLE = True
except ... |
2ad6dc54cf839d7e524597d80f3e796853a88b2d11edfb624749e4d1b5905f1d | Python | 4,793 | 185 | """
This is a module that contains the exceptions thrown by gmx_MMPBSA
"""
# ##############################################################################
# GPLv3 LICENSE INFO #
# #
#... |
6fc0a66303323cb8fd9f21e36885fdfc388f84f519bede54a32755553b32c2c3 | Python | 4,793 | 105 | #!/usr/bin/env python3
"""Build multi-dataset training spec and combined eval directory for CVAE-only experiments.
Run after downloading all datasets. Does three things:
1. Writes datasets_train.json (training spec consumed by train_hippie.py).
2. Writes source_id.csv and super_regions.csv into each individual dat... |
430cef2cd5348d0c21b3d335627749aebcca5e9130da2bff40b24d5595f73996 | Python | 4,794 | 109 | from __future__ import annotations
import logging
from typing import TYPE_CHECKING
from scvi.external.drvi._generative_mixin import GenerativeMixin
from scvi.external.drvi._interpretability_mixin import InterpretabilityMixin
from scvi.external.drvi._module import DRVIModule
from scvi.external.drvi._trainingplan impor... |
64c4c0b72e1a19d209fadaf880720a66f4b0b827b96935ac9d9c117c645ec47e | Python | 4,795 | 136 | import cv2
import numpy as np
import pytest
import torch
import torchvision
from pytorch_grad_cam import (
EigenCAM,
GradCAM,
GradCAMPlusPlus,
LayerCAM,
ScoreCAM,
SESS,
XGradCAM,
)
from pytorch_grad_cam.sess import sliding_window
from pytorch_grad_cam.utils.image import preprocess_image
fro... |
732207fc9a482b5853434da7d2cc1aebe4f78747953b8738e122020ea94f797a | Python | 4,796 | 131 | # 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.
"""
This module contains collection of classes which implement
collate functionalities for various tasks.
Collaters should know wh... |
e5b7f154c96d42b84ccff8ed2d6098e23920fead05903747e32143f7836dcc98 | Python | 4,796 | 117 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... |
d96a4508f197c063cdc5a4153e981e8fe2201a68b0c853675f510c5033866690 | Python | 4,797 | 118 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... |
f4f828261fe4b7072339a113d4fcd50aee829e9aba546d3744369e45bd35cc5d | Python | 4,797 | 112 | import torch
import torch_geometric.nn as gnn
from Bio.PDB import PDBParser
import numpy as np
from torch_geometric.utils import remove_isolated_nodes
from matplotlib import pyplot as plt
import warnings
warnings.filterwarnings('ignore')
from .utils import *
class Node():
def __init__(self,coord,chain,indx,re... |
1e9d7f084683ea79d93a702094c2f8d33818e30ce54953a28e5fb4be56176ca6 | Python | 4,798 | 149 | import itertools
import joblib
import numpy as np
import os
import unittest
from numpy import testing
from sklearn import datasets, preprocessing
#from matplotlib import pyplot
from mentor import _cluster as cluster
from mentor import _datasets as datasets
from mentor import _metrics as metrics
from mentor import _rw... |
44396eb1a646de038c733567c14648a184351f802bd8b924344b9c3762900262 | Python | 4,798 | 136 | import pandas as pd
import numpy as np
import ast
import re
from scipy.stats import norm
from pathlib import Path
def calculate_rates(tono_responses, times):
hit_count = 0
false_alarm_count = 0
# values from the experiment (257(?) sequences in total)
num_signals = 12
num_noises = 244
# Dict... |
bd6246b27abb0cdda60fc5d4c1747b0d95ee949b3c3085a25245c50068793e5c | Python | 4,799 | 137 | # 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 lightconv_cuda
import torch
import torch.nn.functional as F
from fairseq import utils
from fairseq.incremental_decoding_utils import wi... |
501dc2f334bdd5b487d14d89716f103460ff1134b277af92ecad8d829ed61669 | Python | 4,803 | 154 | #!/usr/bin/env python3
# Copyright (c) 2018-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import io
import numpy as np
import collections
def load_vectors(fname, maxload=200000, norm=True, cente... |
6f8fe8f7a4a26e677a593a8384553d034b9d441e29552bd518bf7b75a0ce84f7 | Python | 4,805 | 110 | """Sorts GO IDs or user-provided sections containing GO IDs."""
__copyright__ = "Copyright (C) 2016-2019, DV Klopfenstein, H Tang, All rights reserved."
__author__ = "DV Klopfenstein"
import collections as cx
class SorterGoIds(object):
"""Sorts grouped GO IDs.
* Get a 2-D sorted list:
goids... |
7905776fe4aa594c69323d4e149cf4f1f284e93e8b6c1c12f8239f4e2db80722 | Python | 4,805 | 150 | from __future__ import annotations
from subprocess import CalledProcessError
import pytest
from poetry.console.exceptions import ConsoleMessage
from poetry.console.exceptions import PoetryRuntimeError
@pytest.mark.parametrize(
("reason", "messages", "exit_code", "expected_reason"),
[
("Error occurr... |
9dfbc4dbe720308da2588ad846e7ac45d694964a5e50685c32ece05cc446404b | Python | 4,805 | 96 | import sys
import os
import argparse
from parcellate.cfg import get_cfg
from parcellate.util import get_path
base = """#!/bin/bash
#
#SBATCH --job-name=%s
#SBATCH --output="%s-%%N-%%j.out"
#SBATCH --requeue
#SBATCH --time=%d:00:00
#SBATCH --mem=%dgb
#SBATCH --ntasks=%d
"""
if __name__ == '__main__':
argparser... |
2d208c2cceeb1bbba7237450af97be783128316617400beb043627fd9552fe29 | Python | 4,808 | 100 | import sys
import json
from msi_visual.normalization import total_ion_count, spatial_total_ion_count
from msi_visual.supervised.annotations import get_img, get_visualization, get_dataset
from xgboost import XGBClassifier
import joblib
from sklearn.model_selection import train_test_split
from sklearn.metrics impo... |
6a848f67a8a6adcfef3e86c74f2a133b8475f4efec8ccbc0126ec30ba3acb8bd | Python | 4,809 | 129 | """What an evaluation reports about the documents it actually scored.
`dataset/test_documents` is logged at setup from the split frame; the scores
are computed over whatever the encodings file backs. These pin the counts that
state the difference, over a split holding one pmid the HDF5 does not and drawn
the way `eval... |
89023950722846e6c0e3c6011148f13d99c890a4d08bf6baf9d6df2458d36986 | Python | 4,809 | 100 | # 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... |
884901da5fa64a44008bd4060838a30fb0c81d0b96d50b4834b9796aa883ab60 | Python | 4,810 | 128 | import streamlit as st
import glob
import os
import json
import sys
import numpy as np
import joblib
from collections import defaultdict
from pathlib import Path
from argparse import Namespace
from PIL import Image
from msi_visual.normalization import spatial_total_ion_count, total_ion_count, median_ion
fro... |
86c1cf0b8b4eb3f9da8ee12ec5263028afb474e63659e0303fd16999245ea99c | Python | 4,811 | 143 | #!/usr/bin/env python
# ENCODE DCC GC bias wrapper
# Author: Daniel Kim, Jin Lee (leepc12@gmail.com)
import warnings
from matplotlib import pyplot as plt
import sys
import os
import argparse
from encode_lib_common import (
strip_ext_bam, ls_l, log, logging, rm_f)
from encode_lib_genomic import (
remove_read_g... |
ae497b649756d3d71150b6cfbdba485615ba38d7889279645203c4d83cedc780 | Python | 4,813 | 149 | """Configurational CE example: H/F decoration of benzene.
Six aromatic carbons form a fixed hexagonal scaffold; each of the 6 ortho
positions is either H or F. This gives 2⁶ = 64 binary configurations σ.
By C6v symmetry there are 13 unique necklaces (orbits under D6h):
C6H6 (1)
C6H5F (1)
C6H4F2 — ortho, me... |
4718f05b30538042083944ef27dc56eae86b8d460d27e5374d0632d5bdb61111 | Python | 4,814 | 120 | #%%
import glob
import mne
import pandas as pd
import numpy as np
from fooof import FOOOF
from scipy.signal import welch
workingpath = 'D:\\aperiod\\'
segmentcode = [56, 63, 78]
segment = ['baseline', 'training', 'stress']
segmentlength = [5, 5, 5]
roi_channels = ['Fp1', 'Fp2', 'Fz', 'F4', 'F3', 'F8', 'F... |
8e7831208e82c79f3d2a55fa7a87c1965d5cf131a8b373f44416d3711d7de1c2 | Python | 4,822 | 106 | import numpy as np
from wholeslidedata.samplers.callbacks import BatchCallback
import time
from batchgenerators.transforms.abstract_transforms import AbstractTransform, Compose
from batchgenerators.transforms.color_transforms import BrightnessMultiplicativeTransform, \
ContrastAugmentationTransform, GammaTransform... |
a0b92904d0f91682a3387e077ebf363d26f2180f850e79f9add8338452a50b50 | Python | 4,823 | 88 | #!/usr/bin/env python3
"""Tabela FINAL do controle de SOC: 12 CsBX3, nosoc de work2/ e soc de work3/.
Por que tres rodadas (registrado para nao repetir):
work/ conjunto FR `standard`: SOC certo, mas valencia menor que a de producao e o
controle escalar falha (Ge 0,5-0,7 eV fora). Descartado.
work2/ co... |
3bcf1e01fb9393db937b56c78d81e2e74d733d0b9121002cf4f7613358e6834a | Python | 4,824 | 94 | """
Input: whitespace-delimited csv file with CHR, BP, A1, A2 and ID columns.
Output: tab-separated csv file with two columns ID and UID, where ID column is taken from the input file,
UID column is constructed as CHR:BP:AA1:AA2, where CHR and BP are from the input file, AA1 is min(A1, A2, A1_complementary, A2_compl... |
508f1a51a3dbe4ecc6607bc9385254048b9a1a95e810652d4aefc16a6767f9a8 | Python | 4,825 | 168 | from __future__ import annotations
from typing import TYPE_CHECKING
import pytest
from poetry.core.constraints.version import Version
from tests.console.commands.env.helpers import check_output_wrapper
if TYPE_CHECKING:
from pathlib import Path
from cleo.testers.command_tester import CommandTester
fr... |
0a991d4d31b0f927578b66db5068cc4bb51e31516b7c1609b9094d3d58c029ee | Python | 4,826 | 117 | # coding=utf-8
# Copyright 2019 Facebook AI Research and the HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 Licens... |
7b47bedb7c4b20068b3f32de7317432dffd0d8f1a1002700152f1e925ea895f4 | Python | 4,827 | 136 | # 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 numpy as np
from fairseq.data.data_utils_fast import batch_by_size_fn, batch_by_size_vec
class TestBatchBySize(unit... |
9852de04f8fb384726721d0be6b195c36da92ca2f2a1ee226d980df40b9b979e | Python | 4,827 | 118 | # coding=utf-8
# Copyright 2019 Facebook AI Research and the HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 Licens... |
f473a28a044d98cad1eba261b90f6b353be7ec61d4e584934c4def918bf6c870 | Python | 4,828 | 172 | # 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 itertools
import random
import torch
from torch.utils import benchmark
from fairseq.modules.multihead_attention import MultiheadAtten... |
8a517b3dd3c38b3631d5ddc270926a708e3c99596a18562818952b62a1ea03a0 | Python | 4,831 | 129 | #!/usr/bin/env python3
import subprocess
from pathlib import Path
import polars as pl
import argparse
def main():
parser = argparse.ArgumentParser(description='Filter the scans to detected peptides only, also generate corresponding Identification.csv file')
parser.add_argument('--mzXML_file', action='store', d... |
270f76c76042adf9360d843bd22dbb5a84e3d559391e09bc0fc9a358f769a632 | Python | 4,832 | 132 | import logging
from functools import partial
from typing import Literal
import jax
import jax.numpy as jnp
from jax.experimental import pallas as pl
from .utils import (
big_number,
compiler_params,
compute_q_and_kv_block_len,
create_grid,
get_mask_block_spec,
get_value_or_laplacian_block_spec... |
7739a3f0a24061579c5f9720d60163d7b67b09a246c802e217340e2f22a5c9fd | Python | 4,832 | 127 | # 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... |
260890b368da82fe1ce87da129857dc049bb486f0f198f05e04c92a0027d9e66 | Python | 4,833 | 146 | from __future__ import annotations
import re
from pathlib import Path
from typing import TYPE_CHECKING
import pytest
from poetry.core.constraints.version import parse_constraint
from poetry.installation.wheel_installer import WheelInstaller
from poetry.utils._compat import WINDOWS
from poetry.utils.env import Mock... |
1073f52b6902865697643588d48df1d898e3481ce17dd01607a2b06074fc6ad8 | Python | 4,838 | 122 | #!/usr/bin/env python3
"""Trains up a simple regression model to match a bias model to an experiment.
The transformation input file is a JSON file that names a solo model and gives
the experimental data that it should be fit to.
Note that it may occasionally be appropriate to chain several transformation
models togeth... |
dbd6178143b1e6984ab15f43d5bb262c287e389dbe784432c4759fff10ca0dda | Python | 4,840 | 115 | import numpy as np
import io_mesh as io
import subprocess
import argparse
import os
import copy
def calculate_area(surfname,fwhm, software="CIVET", subject="fsid",surf="pial",hemi="lh"):
"""calculate and smooth surface area using CIVET or freesurfer"""
tmpdir='/tmp/' + str(np.random.randint(1000))
os.mkdir... |
d136393ccefbf9c122fffabea74541f726f2ffb9c71921804e8ecfd57ea7a37c | Python | 4,841 | 139 | import numpy as np
import pandas as pd
import pytest
from scipy import stats
from sklearn.cross_decomposition import CCA
from pgmpy.ci_tests import RoysLargestRoot
from pgmpy.tests.test_ci_tests import _multivariate_fixtures
pillai_data = _multivariate_fixtures.pillai_data
skip_gh_actions = _multivariate_fixtures.ski... |
0f84c8925a83268d80d211956c8962548395062ee99012d61c00036bc377b602 | Python | 4,845 | 139 | import networkx as nx
import numpy as np
import pandas as pd
from pgmpy.base import DAG, PDAG
from pgmpy.metrics import BaseSupervisedMetric
class AdjacencyConfusionMatrix(BaseSupervisedMetric):
"""
Computes confusion matrix based metrics for comparing causal graph skeletons.
Treats edge presence/absenc... |
f4d4caec5af48916c8fa19e105dd038ad7e6b6aedd0eedb78578c736c1704042 | Python | 4,845 | 164 | import logging
import os
from pathlib import Path
import numpy as np
from skbase.utils.dependencies import _check_soft_dependencies
logger = logging.getLogger("pgmpy")
logger.addHandler(logging.NullHandler())
PGMPY_DATA_HOME = os.path.join(Path.home(), ".pgmpy")
class Config:
def __init__(self):
"""
... |
31fe228ce4f4ad38f73f2286043002ebf1d1f6546e07253609401e60d9319ace | Python | 4,847 | 141 | import SimpleITK as sitk
import matplotlib.pyplot as plt
import numpy as np
#
# Set of methods used for displaying the registration metric during the optimization.
#
# Callback invoked when the StartEvent happens, sets up our new data.
def start_plot():
global metric_values, multires_iterations, ax, f... |
9cbf47d2237bf05572eaf0f956b19808d054593f4a47b91eb6d3bae35317fdf3 | Python | 4,847 | 123 | import warnings
from itertools import cycle
from scvi import settings
from scvi.data import AnnDataManager
from scvi.dataloaders import ConcatDataLoader
class _ContrastiveIterator:
"""Iterator for background and target dataloader pair in contrastive analysis.
Each iteration of this iterator returns a dictio... |
f9520c1c427c41c1e6eaf797c866022f2efa0beb497d12bb7d102149f7f66fbb | Python | 4,847 | 141 | #!/usr/bin/env python3
"""A little script that removes unhelpful warnings from program outputs.
Can be used either in a pipe, as in ``cat log.out | filterProc``
or as a parent process as in ``filterProc trainSoloModel config.json``.
In the second case, this program will capture both stdout and stderr.
"""
import os
i... |
ba0cacbfe5088593b64b2f3dfd2b5942bf236a2b6c1fd8a1686df26ffc855ae0 | Python | 4,848 | 137 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Sep 7 16:44:30 2020
@author: bianca
----------------------------------------------
Decoding action predictions - Stimulus localiser
Stimulus: gratings from main experiment (8° diameter, with annulus of 0.5°),
static, duration 12s
Fixation: duration 12... |
d3900624db14e05e4bc60e863d1277d40ffb3b4fd72dfd2ae7654d2f1224672d | Python | 4,849 | 131 | import os
import numpy as np
import tifffile
import cv2
import skimage as ski
import matplotlib.pyplot as plt
from tqdm import tqdm
from segment_anything import sam_model_registry, SamAutomaticMaskGenerator
import colorcet as cc
from matplotlib.colors import LinearSegmentedColormap
import argparse
def setup_sam(dev... |
1f46368d917fc8c066e57d05e30b36c45d3e582bebb0ba7be233bf65da3291f9 | Python | 4,853 | 93 | #!/usr/bin/env python3
"""Literature-standard pseudobulk for Kaufmann GSE144744: SUM of RAW INTEGER UMI COUNTS per
biological sample x cell cluster (Crowell/muscat; Squair 2021).
The GEO matrix is deposited log-normalised, but the raw counts are exactly recoverable because
Seurat LogNormalize is invertible given each ... |
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