sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
29966f8a84826eed71a50fa44bc71c601971bc697e5faabab094b599a18e6225 | Python | 18,130 | 451 | """Per-seed ev_lca ceiling resolver for v7+ tax-scope filtering.
Replaces the old ``--tax_scope inner_narrowest`` / ``AUTO_SCOPE_CLADES``
logic with an ``ev_lca ≤ ceiling`` gate applied per speciation event.
Two built-in auto modes are provided:
- ``auto`` (default): Eukaryota ceiling for all eukaryotes;
Prokaryot... |
86d42baf13531f1310d7631c51e891b852d4dbbcb61ba92b060346220774e8b9 | Python | 18,146 | 459 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jun 2 15:28:30 2023
@author: george
"""
from qtpy.QtCore import *
from qtpy.QtGui import *
from qtpy.QtWidgets import *
import numpy as np
import pandas as pd
import pyqtgraph as pg
import os
# import pyqtgraph modules for dockable windows
from pyqtg... |
c86b174b7faad7740d6d4cc020a58b60337585d69b2eec243f063f637bdeaa7a | Python | 18,157 | 448 | import functools
import glob
import random
import SimpleITK as sitk
import numpy as np
import os
import typing
import copy
import SimpleITK as sitk
import numpy as np
import scipy.ndimage.morphology as morph
import torch
import torch.cuda
import torch.nn.functional as F
from torch.utils.data import Dataset
from tqdm ... |
af52d0fd78c1abec2ebc1c89bdf3e9f7a564cb02012948dd68b9be0bca109723 | Python | 18,198 | 380 | """Unit tests for the channel-centric NWB metadata form widget.
``MetadataSelector`` is a Panel widget, but it is fully driveable in-process: its
values can be set in Python and its button callbacks fired synchronously
(``button.clicks += 1``), so the form logic is tested directly without a browser.
"""
import pytest... |
885cfc788f3178c9af10d7f4623a7d1770a34b2d3458bf5a910cf8ae64cc09b9 | Python | 18,227 | 439 | import torch
from torch import nn, einsum, broadcast_tensors
import torch.nn.functional as F
from einops import rearrange, repeat
from einops.layers.torch import Rearrange
# types
from typing import Optional, List, Union
# pytorch geometric
try:
import torch_geometric
from torch_geometric.nn import Message... |
a9f33114bb54ea8532cb954a2bdfb8d8107dd308cf90bd592af7e6863f201b64 | Python | 18,228 | 413 | # pytest unit tests for spinalcordtoolbox.deepseg
import json
import os
import shlex
import shutil
from pathlib import Path
from unittest import mock
import pytest
import warnings
import numpy as np
from torch.serialization import SourceChangeWarning
import spinalcordtoolbox as sct
from spinalcordtoolbox.image impor... |
ebdf7c157905c7d7020e0477ee6a6abe59da172274997350934a5a35bd182f52 | Python | 18,234 | 522 | # Copyright (c) OpenMMLab. All rights reserved.
from typing import Tuple, Union
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmengine.model import BaseModule
from mmengine.runner import CheckpointLoader
from torch import Tensor
from mmseg.registry import MODE... |
a3b5cb5cfd166ff8d34a13453ac9452eb4638ddc55a09c9a15adc2f43b3d85e4 | Python | 18,251 | 470 | from operator import index
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style('ticks')
sns.set_context('paper')
from RiboGraphViz import RGV
from RiboGraphViz import LoopExtruder, StackExtruder
from sklearn.model_selection import cross_val_score, cross_val_predi... |
9b5058735c1bfbe300b94648f7f521d8e8d153855c960108eaf1f00b59c8fd96 | Python | 18,254 | 380 | # -*- coding: utf-8 -*-
from collections import defaultdict, namedtuple
from datetime import datetime, timedelta
from functools import partial
import json
from networkx import connected_components
import pytz
from typing import Any, DefaultDict, Dict, Iterable, List, Optional, Tuple
from django.db.models import Count... |
b881355dffdf836237bda02aae633b00239e250a2b6cc7629d9cc6a1b02ca6f7 | Python | 18,263 | 449 | # !/usr/bin/env python
# -*- coding: utf-8 -*-
import pandas as pd
import json
import argparse
import torch
import os
import logging
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
from pytorch_lightning.utilities import rank_zero_info
from sacrebleu.metrics import BLEU
from fengshen.utils.utils import ch... |
43103bc9878e03ecfcb133044f5885246e1dd79c215f946af2a720dafdda0fd0 | Python | 18,289 | 487 | ##################################################################
# Test TrimNN on independent simulated data for subgraph matching
# Reproducibility for Figure.2E
##################################################################
import torch
import os
import numpy as np
import dgl
import logging
import da... |
aee0c5a8f59dbd5dd6f34f73593490f1c295347a311c3ad4dfafe7ff521c6916 | Python | 18,292 | 595 | from medperf.exceptions import CommunicationRetrievalError
import pytest
import requests
from unittest.mock import ANY, call
from medperf import config
from medperf.enums import Status
from medperf.comms.rest import REST
from medperf.tests.mocks import MockResponse
url = "https://mock.url"
full_url = REST.parse_url(u... |
10668835f7b3c5797a83f46499fb991123d8e620bf65a1ea92e6865f0384ee00 | Python | 18,293 | 516 | from torch import nn
import torch
from torch_geometric.nn import global_max_pool, global_mean_pool
from torch.nn import Module, Linear, Softmax, BCEWithLogitsLoss, ModuleList
#from torch.nn import Module, Linear, MSELoss, ModuleList
from torch.nn.functional import relu
from torch import sigmoid
from torch.utils.data im... |
f78c57797fa3b579aa85a231e46c0bcb265d3b3bd3fc3e3a2ea8d3fe7b6d4476 | Python | 18,300 | 519 | from rest_framework import status
from medperf.tests import MedPerfTest
from parameterized import parameterized, parameterized_class
class ModelBenchmarksTest(MedPerfTest):
def generic_setup(self):
# setup users
model_owner = "model_owner"
bmk_owner = "bmk_owner"
bmk_prep_mlcube_... |
78768180ada7c172d76d918f6ebba9577591c74b3e0680824d51362f7d72c4d9 | Python | 18,301 | 447 | # Thomas Lavigne
# 18-09-2024
#
#------------------------------------------------------------#
# Libraries #
#------------------------------------------------------------#
#
# Functions created alongside the theory
try:
from porous_fenicsx import constitutive_laws, variational_for... |
dc5bb6d32e4aabba149d6d0d28177747b864cce5561e59d1adb4fceefc2adf42 | Python | 18,305 | 350 | from typing import Type
import pytest
import pytest_mock
from CybORG.Shared.Enums import ProcessName
from CybORG.Shared.Session import Session
from CybORG.Simulator.Actions.AbstractActions.DegradeServices import DegradeServices
from CybORG.Simulator.Actions.AbstractActions.DiscoverDeception import DiscoverDeception
fro... |
55a87a8fcfb5e0be204099cfe7ea0879fd636e32ae9952b12f59146ee3877c81 | Python | 18,307 | 447 | # Thomas Lavigne
# 18-09-2024
#
#------------------------------------------------------------#
# Libraries #
#------------------------------------------------------------#
#
# Functions created alongside the theory
try:
from porous_fenicsx import constitutive_laws, variational_for... |
21c090c2912ff286391ad243a68224e0b2af1dc8afd6465e65afa9ce56a7b61e | Python | 18,334 | 549 | from numpy import float32
import torch
import torchvision
from torch import Tensor, dropout, nn
import torch.nn.functional as F
import math
import torchinfo
from torchvision.models.feature_extraction import get_graph_node_names
from torchvision.models.feature_extraction import create_feature_extractor
import torchvisio... |
41f5bd974c1990b26822113314ba6227a56b46a92562207c973c38b37ac28148 | Python | 18,348 | 460 | from PyQt5.QtWidgets import (QDialog, QVBoxLayout, QHBoxLayout, QLabel, QPushButton,
QListWidget, QFileDialog, QLineEdit, QGroupBox, QMessageBox,
QListWidgetItem, QAbstractItemView, QProgressBar, QCheckBox,
QFrame, QApplication)
fro... |
3a41ca5ec277a9a099d5fe5909c556592ebed341a43c71f3fa38d38407f60762 | Python | 18,356 | 485 | # Copyright DST Group. Licensed under the MIT license.
"""
This module contains functions for parsing a YAML scenario config file
"""
import os
import yaml
from copy import deepcopy
from prettytable import PrettyTable
from CybORG.Shared.State.Credentials import AccessLevel, Credentials
from CybORG.Shared.State.Servic... |
5f74023587334f85b0f06ff089d6bc71e34e0dbe44bfa3f71371a086842c3442 | Python | 18,369 | 467 | #!/usr/bin/env python
#
# Check the installation and environment variables of the toolbox and its dependencies.
#
# Copyright (c) 2013 Polytechnique Montreal <www.neuro.polymtl.ca>
# License: see the file LICENSE
# TODO: if fail, run with log and display message to send to sourceforge.
# TODO: check chmod of binaries
... |
68ca13d8f6d80779629a6e5aa63a07b4bee5818322cf8b15bec42f30b29d021b | Python | 18,416 | 443 | """BART Style dataset. Modified from fairseq."""
import numpy as np
import torch
import math
import re
from fengshen.data.megatron_dataloader.dataset_utils import (
get_samples_mapping
)
class BartDataset(torch.utils.data.Dataset):
def __init__(self, name, indexed_dataset, data_prefix,
num_... |
15f486f22b1c50ac5097383d23a96af2f6bf825428d4771ad1b7e71172e564c4 | Python | 18,453 | 480 | import copy
import gzip
import json
import logging
import os
import re
import sys
from collections import namedtuple
from logging.handlers import RotatingFileHandler
from pathlib import Path
from time import gmtime
import curies
import psutil
import yaml
from bmt import Toolkit
from humanfriendly import format_size
i... |
b175c95e815c747cdc9194059466813dd3766e9479150e63a00591b992091df0 | Python | 18,454 | 518 | """
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 math import pi as PI
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from torch_geometric.nn import M... |
8aacac767dd7bea42e2c08f339ef3d972d08f3ce2379ebe43db9f7803ec3b642 | Python | 18,458 | 494 | import math
import numpy as np
import numpy.typing as npt
import random
import scipy.interpolate
from dtaidistance import dtw_barycenter
from typing import List, Dict, Any, Optional, Tuple, Union
# make TensorLike more flexible
from tsgm.types import Tensor as TensorLike
import logging
AugmentationOutput = Union[Te... |
66df266dbe14412305ae3398f0ec1bb21b303a93216b102d767e6c4ee5d4c3d7 | Python | 18,461 | 454 | # Copyright (c) Meta Platforms, Inc. and 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.
# Adapted from https://github.com/facebookresearch/segment-anything/blob/main/segment_anything/automatic_mask_generator.py... |
93fed31e4deec4a30c6a7109336072ee04beb0b19faaab56e150876885944cbe | Python | 18,470 | 436 | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import torch.nn as nn
import torch.utils.checkpoint as cp
from mmcv.cnn import ConvModule, build_activation_layer, build_norm_layer
from mmengine.model import BaseModule
from mmengine.utils.dl_utils.parrots_wrapper import _BatchNorm
from mmseg.registry i... |
e4d720f20b2ef62016eac1b1177f76f99a24c8957bed202257ceec6224d5f71e | Python | 18,474 | 447 | # -*- coding: utf-8 -*-
import atexit
import logging
import json
import ujson
import os
import shutil
from typing import List
from pathlib import Path
from catmaid import history, spatial
from django.apps import AppConfig
from django.conf import settings
from django.core.checks import Warning, register
from django.c... |
1ba6d862577a9a1f28ca2267651084f8f73a0179a027e03d1bb414e59872ee50 | Python | 18,487 | 428 | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from utils import fftshift, ifftshift
class FreeSpaceProp(nn.Module):
def __init__(self,
wlength_vc,
ridx_air,
total_x_num, total_y_num,
dx, dy,
... |
bacd42337873e2704d52d90fe4cad894bcfb6872355a7977fa8c74b87bc6d3ed | Python | 18,492 | 462 | """
Author : Alexis Lebrun (PhD student)
School : Université Laval (Qc, Canada)
This module provides different tools to visualize vibrational spectra quickly.
"""
import matplotlib.pyplot as plt
import numpy as np
from boxsers._boxsers_utils import _lightdark_switch
def random_plot(wn, sp, random_spectra, y_space=0... |
6e156dff125453fb95f48ceec69ddaebce3ef9dc436155c206e270f986cef274 | Python | 18,497 | 450 | import copy
import datetime
import functools
import logging
import random
from collections.abc import Callable, Mapping, MutableMapping, MutableSequence
from typing import cast
from uuid import UUID
from cwl_utils.types import CWLObjectType
from mypy_extensions import mypyc_attr
from ruamel.yaml.comments import Commen... |
3541bb33763bd7fb68a0a5771fda2a16df093024e43a3c525d44d38bdf9d85d9 | Python | 18,501 | 522 | """Adapt independent TDF2 reading results to MassCube's ``MSData`` model.
This module adds no dependency beyond MassCube itself. MassCube already
depends on NumPy, and the binary reader in :mod:`._tdf` uses only the
Python standard library plus the system ``libzstd`` runtime.
Mapping from timsTOF's four-dimensional ... |
fa9ccc641c20b5bf34f62ad4281f0a2f9062e307199b797b5e398c4db31a5e56 | Python | 18,501 | 393 | # -*- coding: utf-8 -*-
"""Locally-connected layers.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from .. import backend as K
from .. import activations
from .. import initializers
from .. import regularizers
from .. import constraints
from ..engine.b... |
7750565a7ef9e0d02394ca2cd744b3ce5b366562be62ada6d3180bfb008c5d32 | Python | 18,509 | 409 | import os, copy, torch, random, time, datetime
import numpy as np
import pandas as pd
from torch import nn
import torch.nn.functional as F
from torch.utils.data import Dataset
from torch.utils.data import DataLoader
from sklearn import metrics
from sklearn.preprocessing import MinMaxScaler
from sklearn.model_selection ... |
5589b55dc143023b195e1abcbc3d63c885e55fadd04dbfdbf9faa0a6700019e2 | Python | 18,514 | 463 | from myphdlib.interface.session import SessionBase
from myphdlib.pipeline.events import EventsProcessingMixin
from myphdlib.pipeline.saccades import SaccadesProcessingMixin
from myphdlib.general.labjack import filterPulsesFromPhotologicDevice
from myphdlib.pipeline.prediction import PredictionProcessingMixin
from myphd... |
468bdbdf7e126b50a45314301640ef00b08da6803883cec6952fcc6b21708be3 | Python | 18,518 | 428 | #
# report_tables.py
#
# As part of the `reports/` cleanup, this PR will create a bunch of new tables
# in `reports/tables` which:
# 1. Will be included in the Babel publication, and
# 2. Will be included in the GitHub repository in the `releases/` directory by version number, so that we can
# compare between ... |
7cb938d4122c35d20f68fba952ebb171810965caeac3543a04c26c1feb22c790 | Python | 18,532 | 450 | import argparse
import csv
import glob
import hashlib
import multiprocessing
import os
import random
import time
import numpy as np
from tqdm import tqdm
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import DataLoader, Dataset, Subset
import libro... |
d4ca39bf23d55bc39a4df0e7801723acb700a62f0c1a95df1f92697d10d5c294 | Python | 18,532 | 450 | import argparse
import csv
import glob
import hashlib
import multiprocessing
import os
import random
import time
import numpy as np
from tqdm import tqdm
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import DataLoader, Dataset, Subset
import libro... |
dad21d13627a5eb6c4ae2a2dbfb435c6d9f6524574f65e8c3e9edc90b157a119 | Python | 18,532 | 459 | """Handle BIDS specific operations"""
import hashlib
import os
import os.path as op
import logging
import re
from collections import OrderedDict
from datetime import datetime
import csv
from random import sample
from glob import glob
from .external.pydicom import dcm
from .parser import find_files
from .utils import... |
70f949f2a4ce8274837f448dffdbf2f3ac13326336c1f477c32b90ece22b052a | Python | 18,544 | 450 | import argparse
import csv
import glob
import hashlib
import multiprocessing
import os
import random
import time
import numpy as np
from tqdm import tqdm
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import DataLoader, Dataset, Subset
import libro... |
9e839d17665909996230c6e575c0d3848cecf3a06251e80cc57ab62fe4101aca | Python | 18,544 | 450 | import argparse
import csv
import glob
import hashlib
import multiprocessing
import os
import random
import time
import numpy as np
from tqdm import tqdm
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import DataLoader, Dataset, Subset
import libro... |
1a7f6991d9040db01665da85b84ce2f7a89cd0500b6013a39e24c81bef44f31a | Python | 18,550 | 549 | from rest_framework import status
from medperf.tests import MedPerfTest
from parameterized import parameterized, parameterized_class
class DatasetTest(MedPerfTest):
def generic_setup(self):
# setup users
data_owner = "data_owner"
bmk_owner = "bmk_owner"
bmk_prep_mlcube_owner = "b... |
605ef99023976937e399f981974aac834f841c0511ad0a0efb6b026d1e70fa0a | Python | 18,551 | 553 | #!/usr/bin/env python3
"""
CICADA smoothing-only downstream reclassification in Python.
Purpose
-------
Reconstruct CICADA's downstream automatic IC classification from the small,
language-neutral CSV outputs written by CICADA_2_AutoLabeling.m:
* feature_auto_vals.csv (feature_relative_table)
* IC_auto_checker.c... |
aa50e0a7e9e9ddf82fc041c74a12608b9b32d63a920ed8bc79c2e8c7b236d5a1 | Python | 18,554 | 363 | import json
import os
from collections import defaultdict
from src import util
from src.exporters.duckdb_exporters import log_duckdb_settings_on_error, setup_duckdb
from src.memory import log_memory_snapshot
logger = util.get_logger(__name__)
def check_for_identically_labeled_cliques(
parquet_root, duckdb_filen... |
3afb4f1e33cd2f0ab86a03f9076338d889166adc89d28c6c920c2db29d76fb03 | Python | 18,559 | 465 | """
Central place to store the config info
"""
import textwrap
from collections import OrderedDict
import numpy as np
# default values
default_out_dir_name = 'visualqc'
annot_vis_dir_name = 'annot_visualizations'
default_mri_name = 'orig.mgz' # brainmask would not help check expansion of surfaces into skull
default... |
3dd68f9d08072e5915d5580f87e9172ba06a0d4ad673d4481bc44f6d3e2dc7c1 | Python | 18,564 | 491 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Nov 29 11:35:15 2022
@author: schwab
"""
from scipy.spatial import KDTree
import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
import mrcfile
from ..utils.utils_new import field2bild
def get_ess_grid(grid, points, box... |
8478f286afb237c98341c6332f08b6f186fb38a9d9623f56c674967222fc0573 | Python | 18,571 | 567 | """Tests for Edit Lock REST API endpoints and WritableRoomDep enforcement."""
import asyncio
import json
import pytest
from helpers import MockSioServer, auth_header, create_test_room, create_test_user_in_db
from httpx import AsyncClient
from redis.asyncio import Redis
from sqlalchemy.ext.asyncio import AsyncSession
... |
2196e2c209398e2e334727752b42a3d69953c66ecb0eaf3f906f0e2634922207 | Python | 18,592 | 414 | import os
import tqdm
import torch
import numpy as np
import argparse
import json
import cv2
import scipy.io as sio
import matplotlib.colors as mcolors
import matplotlib.cm as cm
from scipy.interpolate import interp1d
from skimage import io
from nns.model import ISOSNet
from utils import fix_random_seeds
from tools.vis... |
d4af4442469beec9f0f7ba93bf248f9c85033ecd16374d22d03b5514a7da40e8 | Python | 18,594 | 512 | """Database access for v7+ integer-encoded databases.
v7 databases use integer protein IDs with delta-varint encoded BLOBs.
This module provides bulk query methods for high-throughput annotation.
"""
import array
import hashlib
import logging
import os
import sqlite3
import tempfile
from typing import Dict, Iterable,... |
e3ec0efb308a52e0d51d76c86e2213dae1fa1d3c21d2d3e69c4203b4df8bb6a5 | Python | 18,610 | 399 | import torch
import torch.utils.data
import configparser
import os
from glob import glob
import multiprocessing
from subprocess import call
import soundfile as sf
import numpy as np
import textgrid
from collections import Counter
import json
from tqdm import tqdm
import pandas as pd
import torch
import... |
e41161a7d4dc05c3ea895b281f4a531f55f93985563ec98529dfe1256a3d04c3 | Python | 18,639 | 539 | # dicom operations
import os
import os.path as op
import logging
from collections import OrderedDict
import tarfile
from .external.pydicom import dcm
from .utils import (
get_typed_attr,
load_json,
save_json,
SeqInfo,
set_readonly,
)
import warnings
with warnings.catch_warnings():
warnings.sim... |
6d6323b0786334922bd2d5ea7b0d88713f9275fe185b817bdffcd13317ca100c | Python | 18,650 | 310 | """ Questions are reproduced from the Qualtrics file https://osf.io/e3wkr """
import pandas as pd
import random
import numpy as np
import re
from tqdm import tqdm
import sys
from unsloth import FastLanguageModel
import transformers
import argparse
def randomized_choice_options(num_choices):
choice_options = list(m... |
7aa33367127098c1773316d08217ae1dde2b66e84eb8bdc43eda762a23112585 | Python | 18,659 | 455 | import os
import tempfile
import numpy as np
from . import error, run, Image, Overlay, Volume, Surface, Geometry, collect_output
class Freeview:
'''A visualization class that wraps a freeview command.
After configuring the wrapper, the freeview window can be opened with the show() method. Volumes and
su... |
8c2424c25216e66b4ce8d3d14a1713737231f05e7ea41815e2bac96fd3cb5bf8 | Python | 18,734 | 494 | # Standard Library Imports
import datetime
import os
import subprocess
from itertools import cycle
# Third Party Imports
import matplotlib.pyplot as plt
import MDAnalysis as md
import numpy as np
from matplotlib.lines import Line2D
from matplotlib.path import Path
from matplotlib.widgets import Lasso
from scipy.interp... |
c681e28a39e7eb475d4e27f63620874b245dc61c4810445ae104690702ea7cb7 | Python | 18,739 | 490 |
import copy
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch_geometric.nn import GCNConv, GATConv, global_mean_pool, global_max_pool, TAGConv
from torch_geometric.nn import global_add_pool, SAGPooling, ASAPooling, GATv2Conv
from torch_geometric.nn.aggr import Attentiona... |
ef6122d9263d42c278b3794f925d6ec35dbd5d7e5b878be5e770890f83506202 | Python | 18,750 | 399 | # Copyright The Lightning AI 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 law or agreed to in wri... |
f39b56ade93398ec71e91e49ba70a829ae14515564244ac0705e15e5c0c93621 | Python | 18,777 | 519 | import os,re
from rdkit import Chem
from rdkit.Chem.Draw import IPythonConsole
from rdkit.Chem import Draw
from rdkit.Chem import rdChemReactions
# from DrawSVG import DrawSVG
from IPython.display import SVG
IPythonConsole.ipython_useSVG = True
import pandas as pd
from rdkit import Chem
from rdkit.Chem.BRICS import F... |
7f4eda874409305be55d25e032d27f347a295c3765df0c641f0670383c3525e8 | Python | 18,778 | 457 | import shutil
from pathlib import Path
import h5py
import pytest
from guppy.testing.api import locate_run_folder, step1, step2, step3, step4
from guppy_test_data import STUBBED_TESTING_DATA
@pytest.mark.filterwarnings("ignore::UserWarning")
def test_mixed_modality(tmp_path):
"""
Integration test for auto mo... |
edb7114d9e74cc9141289991d692bff175fcffdbbde864a93e08450ad7f0a17e | Python | 18,788 | 483 | # 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... |
43f70d3166c3014a5a444e5d107a824e67710ad33ef829bda1179e01f4043657 | Python | 18,807 | 517 | """
This module provides classes for training neural network models for various synthetic functions.
It includes an abstract base class and specific implementations for different synthetic functions.
"""
from abc import ABC, abstractmethod
from dataclasses import dataclass, field
from enum import Enum, auto
from pathl... |
449aa64c48c12577e3fba696d91ffc69dd389d63bc3bbc5f426f8654458bbe9b | Python | 18,831 | 462 | import pytest
import numpy as np
import random
import networkx as nx
from pettingzoo.test import parallel_api_test
from gymnasium import spaces
from CybORG import CybORG
from CybORG.Simulator.Scenarios import EnterpriseScenarioGenerator
from CybORG.Simulator.Scenarios.EnterpriseScenarioGenerator import SUBNET
fro... |
e2d12d2d43dcad22dc56b17fbdb8587428705dd8e3478ea4fb98be4946ed9c6d | Python | 18,845 | 473 | import os
import numpy as np
import pandas as pd
from paq_utilities import *
from utilities import *
import matplotlib.pyplot as plt
import seaborn as sns
import tifffile as tf
from datetime import datetime
sns.set()
sns.set_style('white')
params = {'legend.fontsize': 'x-large',
'axes.labelsize': 'x-large',
... |
998ec3e6815433ea97cd63ed6bf0b3c14709bedd19c3bf7c10c260dab4320851 | Python | 18,859 | 585 | # 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.
# copied from fairseq/fairseq/data/indexed_dataset.py
# Removed IndexedRawTextDataset since it relied on Fairseq dictionary
# other slight mo... |
1297fcf6fe05c20a37f893f4c602b2140858a97634dab55ea427b09746b5c252 | Python | 18,863 | 550 | import torch
import torch.nn as nn
import numpy as np
import gym
import pickle5 as pickle
from ray.rllib.utils.annotations import override
from ray.rllib.models.torch.torch_modelv2 import TorchModelV2
from ray.rllib.utils.torch_ops import convert_to_torch_tensor
import torch.nn.functional as F
from typing import Dict
f... |
cdee3bc88a647d8a7d800dcc6c5c97ca7c03cf249f63116b3c744a562feb72e6 | Python | 18,884 | 463 | """Enables Docker software containers via the {u,}docker or podman runtimes."""
import csv
import datetime
import json
import math
import os
import shutil
import subprocess # nosec
import sys
import threading
from collections.abc import Callable, MutableMapping, MutableSequence
from io import StringIO # pylint: disa... |
51aaf7bfd3f78574012a5c8e57b09035ff03df34682989241219f5d06427ea60 | Python | 18,886 | 473 | ##################################################################
# Calculating ROC curve in TrimNN and CytoCommunity
# Reproducibility for Figure.3A
##################################################################
#TrimNN method
import pandas as pd
import numpy as np
from scipy.spatial import Delaunay
from itertoo... |
75eebcccb1053f24f33ff35c8108b3671af0c3816158773a12d6e51d92aad2eb | Python | 18,891 | 488 | import json
import logging
import os
import random
import tempfile
import uuid
from collections import namedtuple
import numpy as np
import pytest
import xgboost as xgb
from xgboost import testing as tm
from xgboost.callback import LearningRateScheduler
pytestmark = pytest.mark.skipif(**tm.no_spark())
from typing i... |
f00c2e35ccbe1d29d416e2374e5d98faff858dc8f1b40913ffca1ce44251b239 | Python | 18,913 | 388 | #!/usr/bin/env python
"""
MeteWIBELE workflow: MeteWIBELE characterization workflow
1) clustering into protein families
2) protein family annotation
3) domain/motif annotation
4) abundance annotation
5) integration
Copyright (c) 2019 Harvard School of Public Health
Permission is hereby granted, free of charge, to an... |
fed3c48ad85670557098db91e6d5f1ea9388b13e5360cf9d9808b831104a33f8 | Python | 18,924 | 493 | import os
import numpy as np
from rdkit import Chem
from rdkit.Chem import AllChem, rdFMCS, rdMolTransforms
from openbabel import openbabel as ob
from . import printit, config
# TODO check this function
# Default charge partially from Charmm36 forcefield
DEFAULT_PARTIAL_CHARGE = {
"H": 0.09, # <Atom name="HB1" ... |
ec711347b0a477cefdb154d31ab7f9df3ce531d22fad48200135c9573a9d199c | Python | 18,927 | 438 | # coding=utf-8
# This file is derived from the code at
# https://github.com/huggingface/transformers/blob/master/transformers/tokenization_bert.py
#
# Original copyright notice:
#
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the ... |
7665851370ef9e88479c0949d4254a69a93d3cc6aaa153094c75022569dae183 | Python | 18,948 | 562 | """
Modified from the original file to train the model for diastereomeric resolutions.
Date: 2022-11-23 11:29:36
LastEditors: yuhhong
LastEditTime: 2022-12-12 12:57:28
"""
import argparse
from typing import Literal
import numpy as np
import pandas as pd
import pickle
import pathlib
from tqdm import tqdm
import yaml
i... |
bc1e2882cc87ac04bcccbd4efa2831c9bc10e8c65d053ec5ffb0f3ca23d05033 | Python | 18,948 | 361 | # 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... |
534edbf803b63fbee84653b0ed2ebd41415b33905e46d7e7ac5d5a28333664e5 | Python | 18,963 | 594 | import itertools
import typing
from typing import Any, Dict, List, Optional, Iterator, Tuple, Generator
from neo4j import GraphDatabase, Neo4jDriver
from neo4j.graph import Node, Relationship
from kgx.config import get_logger
from kgx.source.source import Source
from kgx.utils.kgx_utils import (
generate_uuid,
... |
27b583bb8e9a3b8347c57acc87cc68f7f351668b12a3ac66a9631946e3afb6bd | Python | 18,965 | 497 | ##
import sys
import os
import bz2
import gzip
import shutil
import errno
import struct
import tempfile
import time
from os.path import join as pjoin
from os.path import exists as pexists
from subprocess import Popen, PIPE, run, CalledProcessError
from .utils import colorify
from .emapperException import EmapperExcep... |
c0226c784c6af717d20465789f4b3a2d279713d252fca5d4b8d1b4cbe961ec1a | Python | 18,969 | 539 |
# This file helps to compute a version number in source trees obtained from
# git-archive tarball (such as those provided by githubs download-from-tag
# feature). Distribution tarballs (built by setup.py sdist) and build
# directories (produced by setup.py build) will contain a much shorter file
# that just contains t... |
55a47c4381c72fcafd2e25955ab73b1b4bbdbe980ed9695646937e6c5541523a | Python | 18,970 | 390 | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from dataclasses import dataclass
from diffusers.configuration_utils import ConfigMixin, register_to_config
from diffusers.models.modeling_utils import ModelMixin
from diffusers.models.embeddings import GaussianFourierProjection, Time... |
0db7131d9a4195cbd2cc4ae51c47f578fd47d382fe60dc44f88fab2154da8de4 | Python | 18,993 | 410 | # coding=utf-8
# Copyright 2022 IDEA-CCNL The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... |
1e05372c11b589fc1c2015b162bb46920ca0028b4d372e6bf96c1dbd5b6a0174 | Python | 19,006 | 507 | #!/usr/bin/env python
"""
MetaWIBELE: maaslin2_summary module
Summary association summary for protein families
Copyright (c) 2019 Harvard School of Public Health
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
... |
a7f112abaa36a105a857681ff06bda18aa2a696dc3216f4a2fc469b83d5a8cc5 | Python | 19,018 | 504 | """
Copyright (c) 2022 EPFL-BBP, All rights reserved.
THIS SOFTWARE IS PROVIDED BY THE BLUE BRAIN PROJECT ``AS IS''
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE BLUE BRAIN PROJE... |
b0cb1ed6baadb63488d2302702da6045e9257e36b7a880f7a1fe16bb953f4e0a | Python | 19,034 | 522 | import csv
import os
import tempfile
import warnings
import numpy as np
import pytest
import scipy.sparse
from hypothesis import given, settings, strategies
from scipy.sparse import csr_matrix, rand
import xgboost as xgb
from xgboost import testing as tm
from xgboost.core import DataSplitMode
from xgboost.testing.dat... |
b33f97425b754e4834ff330ed624417e6bc591ba26af6329e1980922026dc994 | Python | 19,039 | 631 | import os
import subprocess
from os import path
import numpy as np
def write_xyz(path, coords, atoms):
coords = np.asarray(coords).astype(str)
atoms = np.asarray(atoms).astype(str)
xyz_str = str(len(coords)) + "\n\n"
for i in range(len(coords)):
xyz_str += atoms[i] + " " + " ".join(coords[i]... |
d1879efc9a7d21b3d8e751b56cfbfb50aef2459a194597d02b10043227ce78d2 | Python | 19,068 | 485 | # coding=utf-8
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import copy
import logging
import math
from os.path import join as pjoin
import torch
import torch.nn as nn
import numpy as np
from torch.nn import CrossEntropyLoss, Dropout, Softmax, Linear, ... |
177f0b0cc513c6a7d58915b12c92543d01fcd0d91c86bf75fe88c47eb7e21cc0 | Python | 19,069 | 442 | import os,torch,json
import datetime, warnings
import tensorboardX
import numpy as np
import torch.nn as nn
from utils.config import opt
from TSAN.utils.discretize_age import discretize_age
from prediction_second_stage import test
from model import ScaleDense,Second_stage_ScaleDense
from model.ranking_loss imp... |
db7285d2a57e3d9056a23d149c0f68f9c162c221381fadf020cf6dbf00fc5031 | Python | 19,098 | 504 | import threading
import time
from importlib.metadata import version
import panel as pn
import pytest
from guppy.orchestration.home import build_homepage
from guppy.utils import progress
def poll_until_stopped(capture_periodic, timeout=3.0):
"""Drive the poll callback the way the IOLoop would, until it reports t... |
66676a2eced7fd1ca6bcb0db1df77466db41c4d4caeda8dd99212986996c935c | Python | 19,102 | 554 | """
Parse adapter specifications
"""
import re
import logging
from pathlib import Path
from typing import Optional, Any
from collections.abc import Iterable
from xopen import xopen
from dnaio.readers import FastaReader
from .adapters import (
Adapter,
FrontAdapter,
NonInternalFrontAdapter,
BackAdapter,... |
ae1d3e81758b1b2facd1904ad357f26189aa9fa348952728e5b8ec55fc02b4e2 | Python | 19,105 | 461 | # Copyright (c) OpenMMLab. All rights reserved.
from typing import List
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule, build_activation_layer, build_norm_layer
from mmcv.cnn.bricks.transformer import (FFN, MultiheadAttention,
... |
2edce425000fea601398def630160230065a1bebfec46ba60accfddcbd7ba917 | Python | 19,107 | 532 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.distributions import Normal
from TD3.TD3_GNN import GNN_Feature_Extractor
from torch_geometric.nn import GCNConv, global_mean_pool, global_add_pool
from torch_geometric.nn import global_mean_pool
import numpy as np
LOG_SIG_MAX = 2
LOG_SIG_MI... |
140d823953bc0390cf5f0225d17bb929f46738e3b8444a43c0aa4d003af68e2a | Python | 19,144 | 532 | """
Utility functions for manipulating neuprint-python output.
"""
import re
import os
import sys
import inspect
import functools
import warnings
from textwrap import dedent
from collections.abc import Iterable, Iterator, Collection
import numpy as np
import pandas as pd
from requests import Session
import ujson
cla... |
ce2cf32bde4fbe36e3c92668e2536d7d4d9ff3c72ed871c835f6c778398b5406 | Python | 19,146 | 428 | # 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... |
07923a6dc0bb0f574456281758e19a390691c0c16ed6393b14988d7d5da85729 | Python | 19,189 | 551 | #!/usr/bin/env python
"""
MetaWIBELE: mspminer_protein_family module
Summary MSP annotation for each protein family
Copyright (c) 2019 Harvard School of Public Health
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to ... |
170b991ff618f3292d580ab533d03f273595c684b5509afc25b97e41ccfe657d | Python | 19,208 | 374 |
# -*- coding: utf-8 -*-
"""
Created on Mon May 6 22:24:37 2024
@author: guill
"""
import numpy as np
import external_functions as ef
from matplotlib import pyplot as plt
from Network_Class_Small import SpikingNetwork, WeightMatrix
from tqdm import tqdm
from scipy.io import savemat, loadmat
from Parameters_Small im... |
587adc3f92fbfbb423784ba908b6cc304d781b9527c36628608db50db7a156dc | Python | 19,235 | 387 | """Report on '' occurrences in NCBIGene gene_info.gz that could be *genuine* name components
(e.g. double-prime nomenclature) rather than issue-#744 pipe-split artifacts.
Classification of a '' occurrence:
- **open-marker artifact**: a pipe-fragment that STARTS with '' (e.g. ``''cytochrome P450``) --
the opening of... |
7aa2f74dcb0131f1304558688f74005f9be41963e30ad933d3fa0281a1003165 | Python | 19,242 | 581 | """
Steps of the read output pipeline
After all read modifications have been done, a read is written to at
most one output file. For this, a pipeline represented as a list of "steps"
(SingleEndSteps or PairedEndSteps) is used. Each pipeline step can consume
(discard) a read or pass it on to the next step.
Steps are a... |
bf5568a246ebf9b4b1ef259b4013c22bfe62ca3f1f477e5198ec68a26608804e | Python | 19,249 | 575 | from rest_framework import status
from medperf.tests import MedPerfTest
from parameterized import parameterized, parameterized_class
class ModelTest(MedPerfTest):
def generic_setup(self):
# setup users
model_owner = "model_owner"
bmk_owner = "bmk_owner"
bmk_prep_mlcube_owner = "b... |
35797b5f6d37ff8b0eb119bacad7012652f85b4546d780c8041a7c0ee56bc425 | Python | 19,252 | 474 | import matplotlib.pyplot as plt
import numpy as np
import torch
import torch.nn.functional as F
import scipy.ndimage as ndimage
class T2StarFit:
""" Computes the T2star maps with least_squares_fit.
Parameters
----------
dim : int, optional
The number of dimensions of the input image. Default ... |
a84da164a7d912dd8ef9a44e6a19a5ab64d3ac720372e60e25d121341c9e1a17 | Python | 19,265 | 549 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import pickle as pkl
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import pickle as pkl
pd.options.display.float_format = '{:,.2f}'.format
pd.options.display.width = 0
import sys
from datetime import date
import joblib... |
3437df38de0855d1d0742968722c458f7393858bfde70f6605d83cc2da5ec633 | Python | 19,295 | 609 | """Run simple cell optimisation"""
"""
Copyright (c) 2016-2020, EPFL/Blue Brain Project
This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
This library is free software; you can redistribute it and/or modify it under
the terms of the GNU Lesser General Public License version 3.0 as published
... |
c8d64e53da5728e5bc5cae3a22513bd6387155e210521c77b417f76573fc887e | Python | 19,307 | 473 | '''
Ingredient for building the VGAE model, which learns
a latent representation of the neuroimaging features.
License: BSD 3-Clause
Author: Hanna M. Tolle
'''
import sys
sys.path.append('../../')
from sacred import Ingredient
from .data_ingredient import data_ingredient
import torch
from torch_geometric.loader imp... |
32b2b1ea47296c09c467bd68451be6e83971b6361496c1a41fc51f923d1052cb | Python | 19,330 | 442 | import torch
import yaml
import argparse
import numpy as np
import gc
import matplotlib.pyplot as plt
from scipy.ndimage import binary_fill_holes
from dl_utils.config_utils import set_seed
from data.t2star_loader import *
from projects.moco_t2star.utils import *
from mr_utils.parameter_fitting import T2StarFit, CalcSus... |
0114485f07db506e335311e5561041b5842c19e013095ceb5dd5cf953c342cab | Python | 19,335 | 458 | # Thomas Lavigne
# 18-09-2024
#
#------------------------------------------------------------#
# Libraries #
#------------------------------------------------------------#
#
try:
from porous_fenicsx import constitutive_laws, variational_forms, functions
except:
print("Please run first `python3 -m p... |
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