sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
780a1d959dc0ac7d242432a8fe73f26a8e06bad05094da4506dbd70a336b5b8b | Python | 8,430 | 185 | #!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import welch
import matplotlib
matplotlib.rcParams['path.simplify'] = True
matplotlib.rcParams['path.simplify_threshold'] = 1.0
matplotlib.rcParams['agg.path.chunksize'] = 10000
# import matplotlib.style as mplstyle
# mplstyle.... |
5bd0302c4cd4cd2c3b7e8b1d01eb49d546475d06897678f5543ea2e0172aae84 | Python | 8,431 | 243 | """Shared benchmark utilities: attention_ref, cuDNN helpers, flops calculation."""
import math
import torch
try:
import cudnn
except ImportError:
cudnn = None
# ── FLOPS calculation ────────────────────────────────────────────────────────
def flops(
batch,
nheads,
seqlen_q,
seqlen_k,
h... |
0f94f07a9adb0c51b4953db059aae7d9f47fa0cd40286085cec7ca1cc23e9757 | Python | 8,433 | 237 | """Interactive plotting functions for aggregated UMI counts.
"""
from typing import List, Optional, Tuple, Union
import anndata
import cv2
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import plotly.graph_objects as go
from anndata import AnnData
from matplotlib.axes import Axes
from matp... |
46c4e7ee9319394d52dd5d947ae36496f1fa9f189b66c016f1a54c516c9c7e2e | Python | 8,433 | 201 | """Anti-recurrence tests for the shared preview-backend finalizer (cert10).
Covers two bugs in ``torchlens/backends/_finalize.py::finalize_single_pass_trace``:
FIX 1 (BLOCKER): ``Op._tracing_finished`` was never flipped to ``True`` for any
preview (non-torch) backend. Only the trace-level flag was set. Every
finalize... |
320d3c5653c23836420c6cbf6e2436ee0b9a5560a6be4a0e4263d9950e379501 | Python | 8,434 | 201 | import numpy as np
def detect_synaptic_contacts(axonal_points, target_neurons_dict, annotation_volume=None, id2acr=None, threshold=5.0, probability_factor=0.1):
"""
Determine potential synaptic contacts between axonal arborization and dendritic arbors of multiple target neurons.
Parameters:
- axon... |
e5c7b9522ec87f74ed7d1ce76026ed58d712401089ed1d55a91e50dcff0c3db0 | Python | 8,434 | 211 | """W051 (AUD-CODE 2.17): the Python / NumPy GLOBAL-engine state surface is witnessed.
The seed-replayable global engines were witnessed only by a before/after state snapshot
at the capture boundary, so an owner-thread ``getstate -> draw -> setstate`` (or a
``seed``/``set_state`` from a pre-window value) left the compa... |
bae1612a8b6c928400d2e646c8350b759231d33672d8a934da300ae90452ad8e | Python | 8,435 | 177 | #!/usr/bin/python3
##########################################################################
## ##
## Copyright (c) 2019 Philipp Lösel. All rights reserved. ##
## ##
#... |
f05213bb275e08d354bf9750eb3a37aeb8fc713a8beee7edcdd3078d11af9d60 | Python | 8,436 | 295 | import pytest
from werkzeug.exceptions import Forbidden
from werkzeug.exceptions import HTTPException
from werkzeug.exceptions import InternalServerError
from werkzeug.exceptions import NotFound
import flask
def test_error_handler_no_match(app, client):
class CustomException(Exception):
pass
@app.er... |
b4b71d37d70fc222adb98bc084c0a76e63f8d568ed07c06f3a2019d66a97ada6 | Python | 8,440 | 246 | """Tests for seqpro.rag.reverse_complement (flat-buffer ragged kernel)."""
from __future__ import annotations
import numpy as np
import pytest
import seqpro as sp
from seqpro.rag import Ragged, lengths_to_offsets
from seqpro.rag._ops import reverse_complement
# ------------------------------------------------------... |
4ac87b705a9533e7b23391b4a948b03ccebca1315b6aa7a09dce6a63f636b0d3 | Python | 8,441 | 276 | """
Methods for importing data in lab-specific formats
"""
from __future__ import annotations
from typing import Any, Dict, Tuple, Callable, List
import glob
import os
from ... import vprint
from ..process.import_aux import (
PER_PARAMETER_TXT_SUFFIXES,
constrain_selected_tracks,
convert_spine_files_to_p... |
727d4b1ffc7fe05cd7faedd0fc73da8f95ea57df543ea623bc2fdc16eb0c5177 | Python | 8,441 | 218 | # coding: utf-8
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License... |
c2e228d53783e4d4753645b760fbf0ff28ba849ec42dda7fa8c829fc215fc27b | Python | 8,441 | 174 | from . import InvertibleModule
import torch
import torch.nn.functional as F
class GaussianMixtureModel(InvertibleModule):
'''An invertible Gaussian mixture model. The weights, means, covariance
parameterization and component index must be supplied as conditional inputs
to the module and can come from an ... |
1e0057f22607f5d4782e9ce810404b3b4b8d8e8f52c46f1c00bcb9a87f59e6e1 | Python | 8,443 | 219 | import argparse
import json
import sys
from pathlib import Path
def _parser():
"""The parser of the ``pyrosm`` command's arguments (see :func:`main`)."""
parser = argparse.ArgumentParser(
prog="pyrosm",
description="Run or check a pyrosm recipe, find the extracts of an area, describe "
... |
41878cd8e73bd2ab5e093cf27c81eaace14393d6a7b9c6d1506dffc8747c0a34 | Python | 8,444 | 209 | """Shared building blocks for the built-in quantization modes.
The helpers here are pure code motion: each one emits exactly the op
sequence its call sites emitted inline, so modes that adopt them keep
producing identical traced programs.
"""
from keras.src import ops
from keras.src.backend.common import standardize_... |
7ee0189a772b4501895b54457a797fa019011cfbeb53f05b51c2bc4b452e6b12 | Python | 8,444 | 213 | from typing import Dict, List, Optional, Tuple, Union
from PIL.Image import Image
from torch import Tensor
from lightly.transforms.gaussian_blur import GaussianBlur
from lightly.transforms.multi_view_transform import MultiViewTransform
from lightly.transforms.rotation import random_rotation_transform
from lightly.tra... |
b97cf001e55ad0db814b47ca69e81fa97310c443f1cc66c3b0dd7d54fd10027f | Python | 8,444 | 235 | # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
"""Tools for generating Reports.
This is adapted from fMRIPost-AROMA.
"""
import stat
from pathlib import Path
from bids.layout import Query
from nireports.assembler.report import Report
from xcp_d impo... |
2ebc8f5265074461a0ec3254b22bea3b7b8797a28dab27945429ff747c0b8856 | Python | 8,445 | 263 | """
K-Folding script
author: obanmarcos
"""
import os
import os, sys
from config import *
sys.path.append(where_am_i())
import lightning as pl
import argparse
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from utilities import dataloading_utilities as dlutils
from utilities.folders import *
... |
8f477d44bf8097f0584181150c777afa9a3e72b00396cc5e6b69fdffb16a8f75 | Python | 8,445 | 235 | """Narrow ownership seam between ``Trace`` and sparse runnable internals."""
from __future__ import annotations
from collections.abc import Mapping, MutableMapping
from dataclasses import dataclass, field, replace
from typing import TYPE_CHECKING, Any, Protocol
import torch
if TYPE_CHECKING:
from .runnable impo... |
967a5b86867946055d4bcb0a75402d0e2523c1cc6d037f9988b61ea6ea4df783 | Python | 8,445 | 219 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Nov 5 16:22:54 2021
@author: fcheng
"""
import glob
import os
import numpy as np
import pandas as pd
from eval.image_process import img_process
from eval.identify_line_orientation import principalOrient_Radon_var
# save dirs
save_dir = "./results... |
fab53917ba4bde49ed3aef01a4705036fa74ece446dc84e7279d4dade8235627 | Python | 8,445 | 186 | # Copyright (c) ByteDance, 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.
# Main
import datetime
import math
import sys
import time
from functools import partial
from typing import List
import to... |
55e047b38777a374f1990140900a6ca616288150794e22b7a9ec9ea674b2911e | Python | 8,446 | 180 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import itertools
from pathlib import Path
from typing import Any
import torch
from ultralytics.data import build_yolo_dataset
from ultralytics.engine.trainer import BaseTrainer
from ultralytics.models.yolo.detect ... |
7085391b73d586fa4cdf5d0f3478b4a665b2735f3352f5265c78214a3b6c88ef | Python | 8,447 | 202 | from model import common
import torch
import torch.nn as nn
import torch.nn.functional as F
from thop import profile
from util.tools import extract_image_patches,\
reduce_mean, reduce_sum, same_padding, reverse_patches
from util.position import PositionEmbeddingLearned, PositionEmbeddingSine
import pdb
import math
... |
614a047f7d230f4cbdce66edf9ab2134c6262fffdf7c56e744182e07a48a6927 | Python | 8,448 | 205 | # FIXME: check the rpc-interface.js version and warn if incompatible
# support python 2.7+ and 3
from src.cfg import *
def JS(s):
print("Javascript injection requested (copy this to browser console if needed):")
print(s)
# The RPC Interface talks to a web-based app, hosted at `remoteUrl`
# The communication is m... |
55669fdbe879e42c598af035730c25d421a513553590d2a40aa5acf5a91aa3e8 | Python | 8,449 | 194 | try:
import unittest
from spitfire import BetaPDF, DoubleDeltaPDF, DeltaPDF, apply_mixing_model, PDFSpec, Library, Dimension, compute_pdf_max_integration_errors
import numpy as np
from pytabprops import LagrangeInterpolant1D
from scipy.interpolate import interp1d
from numpy.testing import assert... |
c2f77f45ef1cd84837ae557b1ec58e48f8f5d7a99e4865f7dff43a708f0d6268 | Python | 8,451 | 265 | """Tests for repr of all objects"""
import inspect
import os
import re
import warnings
from contextlib import contextmanager
from unittest.mock import patch
import numpy as np
import pytest
import pynapple as nap
from pynapple.core.metadata_class import _Metadata
@contextmanager
def mock_terminal_size(size):
c... |
6c365d69b2059ca5cc2e47713a88d2122ad93b71a1fb4e3862e893f18bf65227 | Python | 8,453 | 226 | """Tests for the TorchLens doctor utility."""
from __future__ import annotations
import importlib.metadata
import pytest
from packaging.requirements import Requirement
import torchlens as tl
from torchlens import _state
from torchlens.backends.tf._tf_compat import get_tf_capability_snapshot
from torchlens.backends.... |
5134019ffeb658cb0c7e4b4d55d5a86055fab86c7d20e832a22ff022d55c3c71 | Python | 8,455 | 135 | ##########################################################################
## ##
## Copyright (c) 2019 Philipp Lösel. All rights reserved. ##
## ##
## This file is par... |
610c49ef8ea512bbe5a5cba6bf120016760e8dde44837d35fa14b63f00542dd9 | Python | 8,455 | 239 | import logging
from pathlib import Path, PosixPath
from collections import defaultdict
import tqdm
from ..dataset import GluonCVMotionDataset, get_vis_thumb_location
from ..utils.ingestion_utils import get_chunked_id_map
_log = logging.getLogger()
_log.setLevel(logging.DEBUG)
def get_data_gen(image_files=None):
... |
3a6fa87a6454f7944d5de6214755825b2d36747081acb71b04378aac56dad932 | Python | 8,456 | 213 | import numpy as np
import matplotlib.pyplot as plt
import argparse
from sklearn.metrics import confusion_matrix, balanced_accuracy_score, precision_recall_fscore_support
from sklearn.metrics import roc_auc_score
import itertools
from matplotlib import colorbar
import json
from pathlib import Path
import pandas as pd
fr... |
041c9ec559bc9707213e9388397287dd813b18e200cd3fd756c326bffa15415d | Python | 8,457 | 258 | import math
from typing import List, Callable, Union
from sklearn.metrics import accuracy_score, mean_squared_error, roc_auc_score, mean_absolute_error, r2_score, \
precision_recall_curve, auc, recall_score, precision_score, confusion_matrix, matthews_corrcoef, \
balanced_accuracy_score, f1_score
from scipy.st... |
415fd020a00594fd7ac5fffc9475dd3b57497020210514328712737126ce1c06 | Python | 8,458 | 192 | """This module processes the result of running probabilistic 20/20 by
converting lists into a formatted dataframe."""
import prob2020.python.utils as utils
import prob2020.python.p_value as mypval
import numpy as np
import pandas as pd
def handle_tsg_results(permutation_result):
"""Handles result from TSG results.... |
7a31c6bd524ec630c36bab9a65f71ad8803a6ce7bd6008aee7aaaaf268515780 | Python | 8,458 | 206 | from __future__ import annotations
from collections.abc import Callable
from PySide6 import QtCore
from PySide6 import QtGui
from PySide6 import QtWidgets
from .. import _ai_models
from .. import _automation
from .._utils import new_icon
from ._info_button import InfoButton
from ._integer_slider import IntegerSlider... |
461c1e74faef1d7217aa049ea8b914264dadf51d4b1d2a10d3e2f4f2a80b61b9 | Python | 8,460 | 241 | model = dict(
type='FasterRCNN',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=0,
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
style='pytorch',
init_cfg=dict(type='Pretra... |
84a979ce9bfabfa1f4f9398b499db92de0292e8d8a1a372520e54a0c3a5adc72 | Python | 8,461 | 217 | # -*- coding: utf-8 -*-
"""
General framework regrouping various compression methods to be performed on the data.
===================================================
A Compressor instanciation requires:
- n_components_list: list regrouping the number of components to keep for each model
representations dimensio... |
d5edcfea8fbbdf7309ebcdf1bf97b9de6c64b8004739c1d8034f610131c2a894 | Python | 8,462 | 244 | #!/usr/bin/env python
'''Train a random forest on model performance from an sql database and then
run a genetic algorithm to propose new, better models to run.
'''
import sys, re, MySQLdb, argparse, os, json, subprocess
import pandas as pd
import makemodel
import numpy as np
from MySQLdb.cursors import DictCursor
... |
350676fc5595ed6bf4b60faa5f838759540cc2ce3f9d953cdcb1ff76009f169c | Python | 8,463 | 192 | ###################################################
### This code simulates vesicle motility and ###
### presynapse capture during axonal motion. ###
### ###
### This is the subroutine that generates a ###
### single SV track following parameters given ###
##... |
698893ebf0086a0a448b2213261e51dc3b97bb1b7495d82ca8a92d686d15aa52 | Python | 8,465 | 197 | import torch
from torch import nn
import torch.nn.functional as F
import numpy as np
from ovseg.training.loss_functions import cross_entropy, dice_loss
from ovseg.training.loss_functions import __dict__ as loss_functions_dict
def to_one_hot_encoding(yb, n_ch):
yb = yb.long()
yb_oh = torch.cat([(yb == c) for c... |
f6673d7d231c3d5a45e952ee6d425c3e1fdcf6a77dc9215d6bb4fd74deee8f66 | Python | 8,465 | 226 | '''
Performs PLS on brain activation and behavioural data in the OCDbaseline
project.
Due to the relatively small sample size (N=~90) the data input into the PLSC
undergoes dimensionality reduction (PCA). However, the number of components
to use is abitrary. We've chosen four per side, resulting in slighty
more than 1... |
93e5f6ce28631dbd6bb294f8e23281f57190e1e8419dfc29372c16e895c00abc | Python | 8,466 | 221 | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
"""Helper functions for multigrid training."""
import numpy as np
import slowfast.utils.logging as logging
logger = logging.get_logger(__name__)
class MultigridSchedule:
"""
This class defines multigrid training ... |
0150e55775798cbcd1df851da7797b3da59cfbf50c64f095447590b4dd055c22 | Python | 8,472 | 265 | """
Todo:
* @Xiaojieqiu: update with Google style documentation, function typings, tests
"""
import math
from typing import List, Optional, Tuple, Union
import anndata
import numpy as np
import pandas as pd
import shapely
import shapely.geometry as geometry
from sklearn.decomposition import PCA
from ..configurati... |
a5ae797d68655ec9dcbb89c77794e84c29773ab8b8acf628624b08895eb68fdc | Python | 8,472 | 282 | """R23 runnable regressions for torch structseq outputs and unary invert."""
from __future__ import annotations
import dataclasses
from pathlib import Path
from typing import Any
import pytest
import torch
from torch import nn
import torchlens as tl
from torchlens.errors import PathDivergenceError
from torchlens.op... |
b398af20972e13ca0589fe67dc0042f2095174f161fb1cb0b17deddf106e4e4c | Python | 8,473 | 252 | """
Crawler modules generating forward peristaltic motion.
Provides the crawler interface and its alternative waveform implementations,
which differ in how the stride cycle shapes the instantaneous forward
velocity: a constant stride, a Gaussian or square velocity profile, or an
explicit phase-dependent one.
"""
from... |
bebbcee1c78b564da874f1ca60fbb25b56835505e2041780341d260f71274ea0 | Python | 8,473 | 227 | #!/usr/bin/env python3
"""
File: overlap_pic_interactions_with_ct_interactions.py
Created: 2021/12/13
Last Changed: 2022/02/10
Author: M.Vochteloo
Copyright (C) 2020 University Medical Center Groningen.
A copy of the BSD 3-Clause "New" or "Revised" License can be found in the
LICENSE file in the r... |
d5edd6d1ed0b217489ec0b1a46f4ceca4df1eeacb4d385471a4dd7aed5fae641 | Python | 8,473 | 216 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import numpy as np
import tensorflow as tf
import pandas as pd
import argparse
import os
import sys
import pwd
import pdb
import csv
import re
import math
import time
de... |
762f40ec456325e5566c6a39655782377661c9a8de60c046d71b4fbdf87e57e7 | Python | 8,474 | 249 | # -*- coding: utf-8 -*-
"""
Created on Tue Mar 3 10:56:35 2020
@author: KEPetousakis
"""
import os.path
import numpy as np
import matplotlib.pyplot as plt
import Code_General_utility_spikes_pickling as util
import warnings
from copy import deepcopy as dcp
import Code_General_Nassi_functions as nf
impo... |
1cfd0e62c00a31775e725bc2f290e542266f74d3d45228e0361d9dd9ab0a116c | Python | 8,475 | 216 | """Galaxy file source plugin for Aspera ascp transfers.
This plugin provides download-only functionality using the Aspera ascp command-line tool.
It is designed as a configured plugin (not stock) requiring explicit configuration with
embedded SSH keys.
Architecture:
- ascp.py (this file): Galaxy plugin configuration ... |
fac640b491cdccfa17fc66718b65c275f12e7ec2f15d2211163b643bd7b4fdb7 | Python | 8,475 | 217 | # LICENSE
#
# _This file is Copyright 2018 by the Image Processing and Analysis Group (BioImage Suite Team). Dept. of Radiology & Biomedical Imaging, Yale School of Medicine._
#
# BioImage Suite Web is licensed under the Apache License, Version 2.0 (the "License");
#
# - you may not use this software except in compl... |
9168b9309273bbcbe31f12795e597c233592999ab092675a355b3a191ce57cc8 | Python | 8,476 | 292 | import torch
import torch.nn as nn
import torch.nn.functional as F
__all__ = ['forward_hook', 'Clone', 'Add', 'Cat', 'ReLU', 'GELU', 'Dropout', 'BatchNorm2d', 'Linear', 'MaxPool2d',
'AdaptiveAvgPool2d', 'AvgPool2d', 'Conv2d', 'Sequential', 'safe_divide', 'einsum', 'Softmax', 'IndexSelect',
'Layer... |
9b851a1658b826c8b5d6acf1a28c2761e740dca7d161bd7248cff4330a217dff | Python | 8,476 | 184 | # Copyright (c) 2025, Jay Shah, Ganesh Bikshandi, Ying Zhang, Vijay Thakkar, Pradeep Ramani, Tri Dao.
from typing import Tuple, Optional
from dataclasses import dataclass
import cutlass
import cutlass.cute as cute
from cutlass import Int32, const_expr
from flash_attn.cute.seqlen_info import SeqlenInfoQK, SeqlenInfoQK... |
4ca557088f3056c5c8721f3fa04c8220f148bae11c1b897516f2b53cd5a7b79b | Python | 8,477 | 213 | #!/usr/bin/env python3
"""Diagnostic M — Tier 3.1: state-axis projection features.
For each subject's 5D vector, project onto three pre-specified axes from
Paper 5's canonical z-space:
proj_cambridge: projection onto Cambridge propofol BL→Mod direction
proj_sleep: projection onto Sleep W→N3 direction
proj_d... |
08df09975a37b049e9a644fc41a34eea4751ee6541cf5609172d6481180742c5 | Python | 8,478 | 208 | import re
from pydantic import (
BaseModel,
ConfigDict,
model_validator,
RootModel,
ValidationError,
)
from typing_extensions import Self
from galaxy.exceptions import RequestParameterInvalidException
from galaxy.tool_util_models.parameter_validators import AnySafeValidatorModel
from galaxy.tool_u... |
633df11c9d445bd359cd324331f7add6dc29b2de439dcfb7ab07f4c49364d67e | Python | 8,478 | 235 | """Convolutional Occupancy Networks (ConvONet).
Peng, Niemeyer, Mescheder, Pollefeys & Geiger, ECCV 2020.
Paper: https://arxiv.org/abs/2003.04618
Source: https://github.com/autonomousvision/convolutional_occupancy_networks
ConvONet extends occupancy networks with *spatially structured* latent
representations. The ke... |
32b0686f91bc4e0d29133b55e401417429e675da6ad456c92438621e745c57a8 | Python | 8,479 | 266 | import sys, os
from tifffile import imread, imwrite
from biomedisa.features.biomedisa_helper import *
from biomedisa.interpolation import smart_interpolation
import numpy as np
#from asd import ASSD
def Dice(ground_truth, result):
dice = 2 * np.logical_and(ground_truth==result, (ground_truth+result)>0).sum() / \
... |
4ebf266e9c268cbb4583d6b4b3673575dbdfae6a722799cd0aa83f90774c036e | Python | 8,479 | 228 | #!/usr/bin/env python
'''Checks an sql database to determine what jobs to run next for
hyperparameter optimization.
Works incrementally by taking a prioritized order for evaluating
parameters. It is assumed the database is already populated with at least
one good model. The best model is identified according to som... |
639cc258da69b688fdf3c7b2ec68db184325feb8eda8760b047907fc0da420da | Python | 8,479 | 210 | #!/usr/bin/env python3
"""Diagnostic L — Tier 2.2: connectivity features (iPLV + dPLI)."""
from __future__ import annotations
import os, sys, json, time
from collections import Counter
import numpy as np
HERE = os.path.dirname(os.path.abspath(__file__))
OUT_DIR = os.path.join(os.path.dirname(HERE), "outputs")
TOOL_AUD... |
ac1bdee9da00907c691d1c820552f12590de9cab1e041fabb3e0146fcd55e9ea | Python | 8,479 | 144 | import argparse
import os
from util import util
import torch
import models
import data
class BaseOptions():
"""This class defines options used during both training and test time.
It also implements several helper functions such as parsing, printing, and saving the options.
It also gathers additional opti... |
3a47cc57a1aea162c8f405dd81bc0b89fb9e348b31aa691b40d191b37fb02d0e | Python | 8,480 | 219 | import logging
from typing import (
Any,
NamedTuple,
)
from galaxy.exceptions import RequestParameterInvalidException
from galaxy.files.models import (
BaseFileSourceConfiguration,
BaseFileSourceTemplateConfiguration,
FilesSourceRuntimeContext,
RemoteDirectory,
RemoteFile,
)
from galaxy.fil... |
78ad1c9cd96a15ce1e9b9cb0ef390781b615ba290d870ae4d5858fa2e8f30dd2 | Python | 8,482 | 219 | '''
K-Folding script
author: obanmarcos
'''
import os
import os, sys
from config import *
sys.path.append(where_am_i())
import pytorch_lightning as pl
import argparse
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from utilities import dataloading_utilities as dlutils
from utilities.folders i... |
b0d60935a5ef5eb69f694358c63b39e3473042b1ed305bf634c5147c8c2152c3 | Python | 8,484 | 229 | """Instrumented consumer ledger for the producer migration (P0, four sources).
Sources (design-of-record section 7):
1. Static AST scan — every ``<expr>.<field>`` and ``getattr(<expr>, "<field>"
[, default])`` site over ``torchlens/`` where ``<field>`` is an OpEvent
field name. Over-approximates by name (conser... |
37eedb8fb86d2b2389114c69057e98ebdab89088ce0618ebe53073359845a4c5 | Python | 8,490 | 254 |
import numpy as np
import scipy.stats as stats
from sklearn.cross_decomposition import CCA
from natsort import natsorted
# My modules
import data
import image
# Get correlation between two one-dimensional variables
# Can be either Pearson's r or Spearman's r
# Do this instead of np.corrcoef to get stats and eliminat... |
da8ebedda2b5dcaa99527da51a3dd54ba34d378aac90c1ee623a3dabd07cad33 | Python | 8,490 | 208 | #!/usr/bin/env python
"""
# Author: ChangXu
# Created Time : Mon 23 Apr
# File Name: cal_graph.py
# Description:`
"""
import os,sys
import numpy as np
import torch
from scipy import stats
import scipy.sparse as sp
from scipy.spatial import distance
from torch_sparse import SparseTensor
import networkx... |
578a96791adcdbe6364f89c3604747d46480b8236c93fe9b97630f11495a1fb3 | Python | 8,491 | 156 | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import numpy as np
class Fingerprint(nn.Module):
def __init__(self, radius, T, input_feature_dim, input_bond_dim,\
fingerprint_dim, output_units_num, p_dropout):
super(Fingerprint, self).__init__()
... |
67087a9bce2ed20172877853a384fd750064ac5b2590cc7a255002f28958c840 | Python | 8,492 | 194 | import numpy as np
class SequenceTools(object):
dna2gray_ = {'c': (0, 0), 't': (1, 0), 'g': (1, 1), 'a': (0, 1)}
gray2dna_ = {(0, 0): 'c', (1, 0): 't', (1, 1): 'g', (0, 1): 'a'}
codon2protein_ = {'ttt': 'f', 'ttc': 'f', 'tta': 'l', 'ttg': 'l', 'tct': 's', 'tcc': 's', 'tca': 's',
'tc... |
9cb8cf501070ed14d3c7a3b8449679780306823246f1b7a20db9055c36692ee3 | Python | 8,493 | 260 | import os
import socket
import atexit
import re
import functools
from setuptools.extern.six.moves import urllib, http_client, map, filter
from pkg_resources import ResolutionError, ExtractionError
try:
import ssl
except ImportError:
ssl = None
__all__ = [
'VerifyingHTTPSHandler', 'find_ca_bundle', 'is_a... |
fc34f17f774373af202ef61d07e19ce39e4a41d791f12c6bfe71c617cf067aa4 | Python | 8,494 | 195 | """
File: cmd_line_arguments.py
Created: 2020/11/16
Last Changed: 2023/08/21
Author: M.Vochteloo
Copyright (C) 2020 University Medical Center Groningen.
A copy of the BSD 3-Clause "New" or "Revised" License can be found in the
LICENSE file in the root directory of this source tree.
"""
# Standard ... |
7934a661a408a20ee8d62441b517eeff2ab55970fee91d60f59a2b40fd3a0fe5 | Python | 8,495 | 262 | """Module for regression functions."""
import functools
import numpy as np
from sklearn.metrics import r2_score
from sklearn.svm import SVR as sklearnSVR
from sklearn.utils.extmath import softmax
from .utils.kernel import kernel
from .classification import MDM, _check_metric
from .utils.mean import mean_covariance
... |
64a7926f70c8de74aef3293be04f034a6b82a269c1bda2530da32844dd9a3ddb | Python | 8,497 | 230 | # coding=utf-8
# Copyright 2024 The Google Research Authors.
#
# 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 applicab... |
7dd12df6131c747aa87bfb78c7172867cccd4186048d6d980138c04d378a66c6 | Python | 8,499 | 289 | from functools import partial
import math
from array_api_compat import array_namespace as get_namespace, device
from array_api_extra import create_diagonal
import numpy as np
import pytest
from pytest import approx
from scipy.linalg import eigvalsh
from conftest import assert_array_almost_equal
from pyriemann.geometr... |
d2c0065d6460fdac96dbf0a8da26dc405ecb7cae92f1b27766d4c6a7cf750033 | Python | 8,499 | 255 | """
stim_plots.py
This script contains functions for plotting stimulus comparison analyses.
Authors: Colleen Gillon
Date: January, 2021
Note: this code uses python 3.7.
"""
import numpy as np
from util import logger_util, plot_util
from sess_util import sess_plot_util
from analysis import misc_analys
from plot_fc... |
0b427a75ba33e5655640895a67655a1643bfd4b7e862e6c2009d231c0ba8dff8 | Python | 8,500 | 239 | import itertools
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
import statsmodels.api as sm
from matplotlib import colors
from tqdm import tqdm
from angorapy import register_model
from angorapy.agent import PPOAgent
from dexterity.model import build_fpn_models, build_fpn... |
14a840dc12db8e250d646c9884495523d9a92b65323165e8935597e9e3c60730 | Python | 8,500 | 252 | import os
import sys
import logging
from pathlib import Path
from typing import Dict, List, Tuple
from multiprocessing import Pool
import pickle
import numpy as np
import pandas as pd
from scipy.sparse import csr_matrix
import snapatac2 as sa2
import anndata
# import scanpy as sc
import pyprojroot
import pyreadr
p... |
cb246a86d89a778f889b155e66a982dee0b9c266a0050bdfb01499dd5c726735 | Python | 8,500 | 151 | import argparse
import os
from util import util
import torch
import models
import data
class BaseOptions():
def __init__(self):
self.initialized = False
def initialize(self, parser):
"""This class defines options used during both training and test time.
It also implements several hel... |
a35b87d112787b1a4cf0513ebd31f098c7d14ddfd40bfe6a0216028eee247fc9 | Python | 8,504 | 220 | try:
from typing import Any, List, Literal, Tuple, Union
except ImportError:
from typing_extensions import Literal
from itertools import chain
from typing import List, Optional, Tuple, Union
import numpy as np
import pyvista as pv
from anndata import AnnData
from scipy.spatial import ConvexHull, Delaunay
fro... |
e22f6d93ecab49db8d90daf160f86927eb19d51ab160b3f1af280d368699ffff | Python | 8,505 | 266 | import os
from argparse import ArgumentParser
import torch
from pytorch_lightning import LightningModule, Trainer
from torch import nn
from pl_bolts.models.vision.image_gpt.gpt2 import GPT2
def _shape_input(x):
"""shape batch of images for input into GPT2 model."""
x = x.view(x.shape[0], -1) # flatten imag... |
1905dcf1c88630150f25454fca35a0fe809e7895945d23395490d9cc039e3059 | Python | 8,510 | 231 | """Feature processing logic for multimer data pipeline."""
from absl import logging
from typing import Iterable, MutableMapping, List
from helixfold.common import residue_constants
from helixfold.data import msa_pairing_a3m
from helixfold.data import pipeline_a3m
import numpy as np
REQUIRED_FEATURES = frozenset({
... |
31d4c6f0a5a344edda66a641ce11949fe5599dd91def0e812e2b22f816c924a3 | Python | 8,513 | 241 | model = dict(
type='FasterRCNN',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=0,
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
style='pytorch',
init_cfg=dict(type='Pretra... |
5029a37f55eeb9145533045822611f9dbfa9df628b5d3a83737005316f3a13f0 | Python | 8,513 | 241 | model = dict(
type='FasterRCNN',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=0,
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
style='pytorch',
init_cfg=dict(type='Pretra... |
c308398f3f48e9b5c3cd49fce58a7a545a60847988b05d22c850f667dc0f64f4 | Python | 8,513 | 241 | model = dict(
type='FasterRCNN',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=0,
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
style='pytorch',
init_cfg=dict(type='Pretra... |
1ad73b0ca0a6af34c53192d29e8485e07f0ea9ae51552880c78be84e82855c99 | Python | 8,515 | 355 | import sys
from importlib.util import find_spec
from unittest.mock import Mock
import pytest
from celery.local import PromiseProxy, Proxy, maybe_evaluate, try_import
class test_try_import:
def test_imports(self):
assert try_import(__name__)
def test_when_default(self):
default = object()
... |
32195c15e2240645392982b92c7208b848023e744b38c560120e9d3dc90dcdce | Python | 8,515 | 241 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Tickformatstop(_BaseTraceHierarchyType):
_parent_path_str = "carpet.baxis"
... |
6dd21c5b8600df6c13675222d4411967144732928d221b69032ce121ee9420fd | Python | 8,515 | 241 | model = dict(
type='FasterRCNN',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=0,
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
style='pytorch',
init_cfg=dict(type='Pretra... |
c96820c4d7407929f39b71da30ccfd97fca67980df41759353b81d212f5fe1e3 | Python | 8,515 | 241 | model = dict(
type='FasterRCNN',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=0,
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
style='pytorch',
init_cfg=dict(type='Pretra... |
e378d24d5da8df3574d133d8028cce1d388387860af654123d7b761c1eda02b8 | Python | 8,515 | 193 | """Written by @Jinerhal, adapted by @Xiaojieqiu.
"""
from typing import Tuple
import numpy as np
from anndata import AnnData
from ..configuration import SKM
from ..logging import logger_manager as lm
from .utils import *
@SKM.check_adata_is_type(SKM.ADATA_UMI_TYPE)
def digitize(
adata: AnnData,
ctrs: Tuple... |
f23e743963bb7efea577281a43814279ffc892c306a054f883f89fc133ace113 | Python | 8,515 | 241 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Tickformatstop(_BaseTraceHierarchyType):
_parent_path_str = "carpet.aaxis"
... |
1b755698f17d69d9be47959d6deec197d8ece21763f901d19717cfc2bb678035 | Python | 8,516 | 181 | #==============================================================================#
# Author: Dominik Müller #
# Copyright: 2024 IT-Infrastructure for Translational Medical Research, #
# University of Augsburg ... |
2db1d5670e859b1eff8488c01fc71a7e63f39e4a37597c604cb360216cbdb9d4 | Python | 8,517 | 196 | """Save-level payload policy: include-flag resolution + write-side coherence.
Lane A08 (WT1 A-IV items 19 + 22; weightsfree W3), split out of
``_io/bundle.py`` per the file-size ratchet's split-preferred rule. Owns the
per-level include-flag defaults/requirements tables, the explicit-conflict
refusals (``save_payload_... |
3b2454e5161734d15514e0a527d5db38db744384ef447552fafcfebc2a5572ca | Python | 8,517 | 241 | model = dict(
type='FasterRCNN',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=0,
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
style='pytorch',
init_cfg=dict(type='Pretra... |
4d97154acfbe74533b309523e8c0e8ab7a19540591f37b3e85acc4ec6c7f490c | Python | 8,517 | 190 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from copy import copy
from typing import Any
import torch
from ultralytics.data import ClassificationDataset, build_dataloader
from ultralytics.engine.trainer import BaseTrainer
from ultralytics.models import yolo... |
6e747062cf04eb42780d77a8830be0b0862361cbdd94b980b3eed9c7effc8e7b | Python | 8,518 | 241 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType
import copy as _copy
class Tickformatstop(_BaseLayoutHierarchyType):
_parent_path_str = "layout.xaxis"... |
c6a01d1d9bc5c7622f14da499f5567eff87f8638668ad7396961b3b715496f10 | Python | 8,518 | 241 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType
import copy as _copy
class Tickformatstop(_BaseLayoutHierarchyType):
_parent_path_str = "layout.yaxis"... |
ddbfca4301567f37a888f21953c62c7a12932a392b6659a167ea1f94da235b29 | Python | 8,520 | 264 | """Regression coverage for tensor replacement during active TorchLens captures.
These tests cover a reported bug where user replacement tensors lacked
TorchLens raw-label metadata and broke the next module boundary. The audited access sites
fall into two groups: output/module-exit paths now repair missing labels, whil... |
e3654efd1fdb2bc15856061b21ce3c8e49028e7e8611cda6b7e8d00c59ac749c | Python | 8,520 | 241 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Tickformatstop(_BaseTraceHierarchyType):
_parent_path_str = "cone.colorbar"
... |
946929f166bbeac8f20343964d7a334a4e176895dc14b1f4945f576c6a7b7c69 | Python | 8,521 | 200 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Automate the execution of peak calling on .bam files.
# Originally designed for ATAC-seq data, but will work with any directory of .bam files.
#
# By default, this runs both macs14 and macs2 for comparison.
#
#
# Copyright (c) 2014-2016 Nick Semenkovich <semenko@alum.mi... |
c485baaf58bc83750c8dce76ac888011eb8dd294971b1de5204a0504ab7abc73 | Python | 8,526 | 241 | model = dict(
type='FasterRCNN',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=0,
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
style='pytorch',
init_cfg=dict(type='Pretra... |
2a1f58ff9465a331d00dc4aed9ab73b44d203814e331d2cd65fd80c94e4f5321 | Python | 8,529 | 284 | """AcademiCodec SoundStream: convolutional encoder, RVQ, decoder audio codec.
Source: SoundStream (Zeghidour et al., 2021) and the AcademiCodec toolkit. The
architecture is an end-to-end neural audio codec with a fully convolutional
encoder/decoder and residual vector quantizer.
"""
from __future__ import annotations... |
ba61bcbc5c401b2a3b640ce70d2b8d9f35a029d624afdddfbc763cafc40437db | Python | 8,530 | 217 | """
Run ridge regression to learn mapping between brain response and feature vectors.
"""
import sys
sys.path.append('..')
import argparse
import subprocess
from scipy.io import loadmat
from brain_semspace_map import brain_semspace_map_loo
from pathlib import Path
from scipy.io import savemat
import numpy as np
print(... |
4da1a36172d47a15d877a3c265bdeae126f3c109c9d106b6b698e19e3b24ffbc | Python | 8,531 | 241 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Tickformatstop(_BaseTraceHierarchyType):
_parent_path_str = "mesh3d.colorbar"... |
b401d5bb280bd63c110da071efaf665eb5676b808710b07d30ae91ca6ebcea0c | Python | 8,531 | 241 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Tickformatstop(_BaseTraceHierarchyType):
_parent_path_str = "volume.colorbar"... |
64a041b5158b462e038e278c5a56c83337b7e2906c6795b5a77470f67a28a466 | Python | 8,532 | 244 | model = dict(
type='FasterRCNN',
backbone=dict(
type='ResNet',
depth=50,
num_stages=4,
out_indices=(0, 1, 2, 3),
frozen_stages=0,
norm_cfg=dict(type='SyncBN', requires_grad=True),
norm_eval=False,
style='pytorch',
init_cfg=None),
neck=d... |
776b4ecb59348a75945ffea90ed0f2080c8578c9e399c2501e74b16a2d576f0b | Python | 8,535 | 235 | from collections import defaultdict
from torch.utils import _pytree as torch_tree
def register_tree_node_class(cls):
torch_tree.register_pytree_node(
cls,
flatten_fn=lambda x: x.torchtree_flatten(),
unflatten_fn=cls.torchtree_unflatten,
serialized_type_name=f"{cls.__name__}",
... |
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