sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
69799572fcf74c3233a813e501794fc88fa6c0661f0721cd27a2f83b8ab78d0b | Python | 2,596 | 77 | import torch.nn as nn
from ..builder import ALGORITHMS, build_backbone, build_head, build_neck
from .base import BaseModel
@ALGORITHMS.register_module()
class FPSiam(BaseModel):
"""FPSiam.
Implementation of `Self-supervised representation learning using feature pyramid siamese networks for colorectal polyp ... |
beaab7ec35196c0b9e267e73877948c60df2c5abd1963cd378f12d8a3f7e040a | Python | 2,596 | 67 | # pylint: disable=arguments-differ,line-too-long,missing-docstring,missing-module-docstring
from functools import partial
import mxnet as mx
from mxnet.gluon.nn import HybridBlock
__all__ = ['DropBlock', 'set_drop_prob', 'DropBlockScheduler']
class DropBlock(HybridBlock):
def __init__(self, drop_prob, block_size,... |
7107aa7eab118dc18e2af76b2d54a9eb5ddd828762ed983c1004bbcb04267cf1 | Python | 2,597 | 90 | import os
import torch
from modular_splicing.legacy.remapping_pickle import load_with_remapping_pickle
def load_model(folder, step=None, **kwargs):
"""
Load a model from the given path. Uses `load_with_remapping_pickle` to load the model
to allow for backwards compatibility.
Has different behav... |
71dd46c5556f5df1dac63e3ff7af877f0f2a788506d4edd0aad51ff810461b97 | Python | 2,597 | 84 | # 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.
from typing import List
import torch
import torch.nn.functional as F
from timm.models.resnet import ResNet
# hack: injec... |
a8626ca1ec6ba27de287170ca2c53e5a355e799893178ea5e74a92461c01218d | Python | 2,597 | 67 | from __future__ import division
import unittest
import numpy as np
from wyrm.types import Data
from wyrm.processing import append_epo
from wyrm.processing import swapaxes
class TestAppendEpo(unittest.TestCase):
def setUp(self):
ones = np.ones((10, 5))
# cnt with 1, 2, 3
cnt = np.append... |
0d4d3483c0e8a4524f460e92d39943386035dd6c3f5aebebf2c9c295f6cfd3fb | Python | 2,599 | 83 | # ---
# jupyter:
# jupytext:
# text_representation:
# extension: .py
# format_name: sphinx
# format_version: '1.1'
# jupytext_version: 1.10.2
# kernelspec:
# display_name: Python 3
# language: python
# name: python3
# ---
"""
.. _exa-customizing-plots:
Customizing plots
===... |
15bb837c6a98402662e47d3db3fce3137d1b17134a6f44934eda0c352b054977 | Python | 2,599 | 75 | import logging
from .wdl_parser import WDLParser
logger = logging.getLogger(__name__)
class CaperWDLParser(WDLParser):
"""WDL parser for Caper."""
RE_WDL_COMMENT_DOCKER = r'^\s*\#\s*CAPER\s+docker\s(.+)'
RE_WDL_COMMENT_SINGULARITY = r'^\s*\#\s*CAPER\s+singularity\s(.+)'
WDL_WORKFLOW_META_DOCKER_KEY... |
0f08e5fc346277fe65a4824fa2b90c0a48adb90b5ecda441d3e2991b199d5388 | Python | 2,600 | 82 | # This example requires the following dependencies to be installed:
# pip install lightly
# Note: The model and training settings do not follow the reference settings
# from the paper. The settings are chosen such that the example can easily be
# run on a small dataset with a single GPU.
import pytorch_lightning as p... |
2ebea623b3ea2b3bbdce86a0317d959c4bc53c98419648a477fdb0e62a20cf93 | Python | 2,600 | 71 | import numpy as np
import scanpy
from anndata import AnnData
def normalize_total(
adata: AnnData,
target_sum: float | None = None,
exclude_highly_expressed: bool = False,
max_fraction: float = 0.05,
key_added: str | None = None,
layer: str | None = None,
inplace: bool = True,
) -> dict[str... |
89fc97369df996c3f5139d2cc7cdc850c35374c3fb993d39cf7745f38d3e9449 | Python | 2,600 | 81 | """The modern-spelling quickstart gate: zero warnings, in a fresh process.
Quickstart memo B1: the block a newcomer actually types (modern spellings
only -- ``tl.trace`` + ``summary()`` + indexed reads, eval-mode torchvision
resnet18) must emit ZERO warnings. Historically the only spellings that
controlled render outp... |
7da617c6811f10964ddcd2b71aff864d6f31c889367ce29774e98347e9e4e82f | Python | 2,601 | 79 | import os
import re
import sys
import sysconfig
try:
from Cython.Distutils import build_ext
except ImportError:
from setuptools.command.build_ext import build_ext
from setuptools.extension import Extension
def is_pip_install():
if "_" in os.environ and os.environ["_"].endswith("pip"):
return Tru... |
ddc8def878c392ee0c1e62b130d91001b852f87a70f7cbc293a4f61014ee0e9a | Python | 2,601 | 68 | import json
import os
import numpy as np
from matplotlib import pyplot as plt
from angorapy.common.const import PATH_TO_EXPERIMENTS, QUALITATIVE_COLOR_PALETTE
experiment_ids = ['1674074113967956', '1674074113731734', '1673350499432390']
names = ["1", "2", "3"]
reward_developments = {}
reward_bands = {}
cosucc_devel... |
caf188c101f44347798630c5e750e02d4df8910ebb12a523849e7f00d9203abf | Python | 2,602 | 71 | #!/usr/bin/env python
import os
import torch
import argparse
import numpy as np
from models import InferSent
if __name__ == '__main__':
parser = argparse.ArgumentParser(
prog='extract-features',
description='Extract features from pretrained InferSent model')
parser.add_argument('-g', '--w2v_... |
2dcf2e0a54e75f0758fab86868fa98773c2dc0fe86cf9379f3e2760b4dd9a986 | Python | 2,604 | 93 | import csv
import time
import math
import numpy as np
import warnings
from rdkit import Chem
from rdkit import DataStructs
from sklearn.model_selection import KFold, StratifiedKFold
import torch
import torch.nn as nn
import torch.nn.utils.rnn as rnn_utils
def read_sequence_file(filename, unique=True, add_end_tokens=F... |
5354890ca0ecadf8c289e0dc9ab05bb892f95181812e710c4c53f3a9d5759ce4 | Python | 2,604 | 80 | """
This example demonstrates how to use the CodeCarbon library to track the carbon emissions of a transformer model.
We will use the model from https://huggingface.co/HuggingFaceTB/SmolLM2-360M-Instruct
It's a small language model that fit on small GPU.
- 360M model took 1 GB on disk, less than 2 GB in VRAM.
- 1.7B ... |
fe25c9d3cd4db9052063da41cd86c1cb1f020f8069675c54f8b5e57a370d9e7d | Python | 2,604 | 60 | from __future__ import division
import argparse, time, logging, os, math, tqdm, cv2
import numpy as np
import mxnet as mx
from mxnet import gluon, nd, image
from mxnet.gluon.data.vision import transforms
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv import data
from gluoncv.data import mscoco
fr... |
a80cd424e65aceb2d59072f4162376c36cffe43305d07b7eb88ee6fff15b7590 | Python | 2,606 | 93 | import csv
import time
import math
import numpy as np
import warnings
from rdkit import Chem
from rdkit import DataStructs
from sklearn.model_selection import KFold, StratifiedKFold
import torch
import torch.nn as nn
import torch.nn.utils.rnn as rnn_utils
def read_sequence_file(filename, unique=True, add_end_tokens=F... |
ccbc8b838e1ab2671a90aacd918cfa5994f388426f786c485b23148138cb2f18 | Python | 2,606 | 87 | """
The data splitting script for pretraining.
"""
import os
from argparse import ArgumentParser
import csv
import shutil
import numpy as np
import grover.util.utils as fea_utils
parser = ArgumentParser()
parser.add_argument("--data_path", default="../drug_data/grover_data/delaneyfreesolvlipo.csv")
parser.add_argum... |
4bd07558e7399470a34e3fccf89f997f1d3c5b2017201e7e93d42e3e6de67670 | Python | 2,607 | 64 | # -*- coding: utf-8 -*-
# Copyright (c) 2016-2018 Braintech Sp. z o.o. [Ltd.] <http://www.braintech.pl>
# All rights reserved.
"""Wii Read Manager."""
from __future__ import print_function, division
from .. import read_manager
import numpy as np
from . import wii_utils
class WBBReadManager(read_manager.ReadManager):... |
7d5a7191044aaa84d814cedbd373c54ffbf37469ee64b425059a2c887e48b076 | Python | 2,607 | 78 | import random
import numpy as np
import copy
from scipy.spatial.transform import Rotation
predefined_rotation_arrays = np.array([
[ # identity
[1,0,0],
[0,1,0],
[0,0,1]
],
[ # counterclockwise 90
[0,0,1],
[0,1.,0],
[-1,0,0]
],
[
[0,0,-1],
... |
f6132525954dfc5110dd462b4f6d8f34afb1bd6d92e6ae883b37ddd3e77df39e | Python | 2,607 | 54 | import os, pydicom
import numpy as np
from operator import itemgetter
def load_stack(srcdir):
# Debug for CHUSJ mice:
# srcdir='/mnt/data/DATA_Micro-CT_CR_CHUSJ/SPINE/DICOM/2M/2M-25J-1'
# Assuming that slices are taken along the anteroposterior axis.
# Doubt may remain on whether rows/columns corresp... |
2bd0d29683d1d30d99ebc88cc92e3c99adbf7759b9bfc55dc0abfa990648ff9f | Python | 2,608 | 70 | """The ``celery purge`` program, used to delete messages from queues."""
import click
from celery.bin.base import COMMA_SEPARATED_LIST, CeleryCommand, CeleryOption, handle_preload_options
from celery.utils import text
@click.command(cls=CeleryCommand, context_settings={
'allow_extra_args': True
})
@click.option(... |
5b73fce2a29d8508620591756106c69deb19e54295e23a3dc2f4ecb0a9e7e2e6 | Python | 2,608 | 61 | """grind-r3 T-CACHES: the framework-filename verdict cache must be bounded.
``_FRAMEWORK_FILENAME_VERDICTS`` is a process-global keyed by ``co_filename``.
Generated-code, notebook, plugin, and long-running service workloads mint
fresh filenames without limit (grind-r2 b4-sol R39: 1,000 distinct compiled
filenames grew... |
b0e1e7fb4da044f4c6439b7ad1161ec4766fe2a52db6aaee8dc8a239ca48ce22 | Python | 2,608 | 81 | # ---
# jupyter:
# jupytext:
# text_representation:
# extension: .py
# format_name: sphinx
# format_version: '1.1'
# jupytext_version: 1.4.2
# kernelspec:
# display_name: Python 3
# language: python
# name: python3
# ---
"""
.. _exa-boxplot:
Boxplot
=======
Much of the fun... |
c0327da6c04411b5fbe6c0dc2e5f3019754d5de4409744ad9ca25430f64f26a0 | Python | 2,608 | 84 | import torch
__all__ = ["batch_trace", "batch_norm", "batch_diag", "batch_div"]
def batch_operation(operation, tensor_a, tensor_b=None):
"""
This function allows to extend tensor operations provided in pytorch to
batch tensors. As an input, it takes the pytorch operation and the tensors
on which th... |
50e3619cbc9f20ba3f21fcf851f24bcd873e6e2303f39d367ca77fda8f02dcdf | Python | 2,609 | 81 | import tensorflow as tf
# implementation from: https://github.com/sayakpaul/Adaptive-Gradient-Clipping/blob/main/agc.py # noqa
def compute_norm(x, axis, keepdims):
"""
Computes the euclidean norm of a tensor :math:`x`.
Args:
x: input tensor.
axis: which axis to compute norm across.
... |
185a021840b204efa7d482c5a3dc29f1f7192c419e2749dc0a1b130da15549da | Python | 2,612 | 48 | import torch.nn as nn
import torch.nn.functional as F
class LSTM_CNN_3_layers(nn.Module):
def __init__(self, seq_length, img_size,kernel_s_layer_1, kernel_s, max1, max2, max3,out_channels_1, out_channels_2, out_channels_final, LSTM_hidden, LSTM_layers, p=0.0):
super(LSTM_CNN_3_layers, self).__init__()... |
c5dfd8884a6f02579182e1a47689c1547a25ab743c8216350366bd4d23d2c3cf | Python | 2,612 | 66 | import pandas as pd
from pandas.core.frame import DataFrame
from sklearn.model_selection import train_test_split
from typing import List, Tuple
import utils
import numpy as np
def split_datasets(root_data_path: str, random_seed: int, train_fraction: float) -> None:
"""Performs random split of dataset and exports c... |
abbd298bfdd1ebe97a4af953291437378af0c0743817ab3221734c46e104ae60 | Python | 2,613 | 83 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sat Apr 4 18:44:27 2020
Find peaks and slopes from PSDs using fooof
@author: ml
"""
import mne
import numpy as np
import os
import sys
from fooof_parametrization import fooof_inparcel
BASE_PATH = os.path.dirname(os.path.dirname(os.path.abspath(__file__)... |
c2f93ffcf01f095cb8345ecb00e3a1ac53f8cfed4db4d0b6b8a40fd610f7cfe9 | Python | 2,614 | 84 | import pytest
import rpy2.robjects.packages_utils as p_u
def test_default_symbol_r2python():
test_values = (
('foo', 'foo'),
('foo.bar', 'foo_bar'),
('foo_bar', 'foo_bar')
)
for provided, expected in test_values:
assert expected == p_u.default_symbol_r2python(provided)
@p... |
2a660f01b10169a6c9bb258080bcec027df48d1ed9e69cff45ecc7fccc697267 | Python | 2,615 | 75 | import os
import numpy as np
import cv2
from operator import itemgetter
from sklearn.preprocessing import LabelEncoder
folder = next(os.walk('.'))[1]
for f in folder:
# Declarations
X = []
Y = []
folders = []
filenames = []
readMask = False
readImage = False
image = np.empty((1024, 102... |
9f6164565c115ff852eb57d8b779d2021d9ed95e827199ff75f6cf21dd690101 | Python | 2,615 | 82 | from __future__ import absolute_import
import logging
import os.path
import tempfile
from pip._internal.utils.misc import rmtree
logger = logging.getLogger(__name__)
class TempDirectory(object):
"""Helper class that owns and cleans up a temporary directory.
This class can be used as a context manager or a... |
ebd524da6253bdc5d73cd22410bc186161ac9f058e135ae9db9c7514b1160553 | Python | 2,616 | 104 | from sphinx_celery import conf
globals().update(conf.build_config(
'celery', __file__,
project='Celery',
version_dev='6.0',
version_stable='5.0',
canonical_url='https://docs.celeryq.dev',
webdomain='celeryproject.org',
github_project='celery/celery',
author='Ask Solem & contributors',
... |
deb6c740ea5d80cf2a3fd166b1f2fd7651d2a19d785a39421350475651069c8a | Python | 2,617 | 83 | """.. _lightly-timm-backbone-tutorial-8:
Tutorial 8: Using timm Models as Backbones
===========================================
You can use LightlySSL to pre-train any timm model using self-supervised learning since
most methods share a similar workflow. All methods have a base model (the backbone), which
can be any ... |
495b8ca2ed9cb542ef052a0770006e2f316d8666b0425111f7928233265281d2 | Python | 2,618 | 90 | import matplotlib as mpl
import numpy as np
from numpy.typing import NDArray
from scipy.optimize import curve_fit
from scipy.special import erf
from neurogym.utils.decorators import suppress_during_pytest
def probit(
x: NDArray[np.float64],
beta: float,
alpha: float,
) -> NDArray[np.float64]:
"""Cumu... |
ff21c54218c0c991f78aea7ce5319d8541cb3e8cd43981df8628ecf09a09d57b | Python | 2,619 | 91 | import pytest
from larvaworld.lib.reg.parDB import ParamRegistry
_VALID_CATEGORIES = {
"initial",
"angular",
"spatial",
"chunks",
"sim_pars",
"deb_pars",
}
@pytest.fixture(scope="module")
def pclass() -> ParamRegistry:
return ParamRegistry()
def test_build_populates_category_dict_for_a... |
4dda9c413732cc9a9b45f38b52d9b2f484e36a5c20eb16288f9075996c86cc58 | Python | 2,620 | 86 | #!/usr/bin/env python
# Created on: October 8, 2013
__author__ = "Sven Kreiss, Kyle Cranmer"
__version__ = "0.1"
import optparse
parser = optparse.OptionParser(version=__version__)
parser.add_option("-i", "--input", dest="input", default="output/atlas_counting/comb.root", help="Input root model.")
parser.add_optio... |
83c843db878a864ccb5a84f1dcd5647834d029d72aaf6077f240903e8ffdf480 | Python | 2,620 | 72 | """Tests for specparam.algorthms.algorithm."""
from specparam.modes.modes import Modes
from specparam.algorithms.settings import SettingsDefinition
from specparam.algorithms.algorithm import *
###################################################################################################
########################... |
a50354f4606ab739a6ed0f7d6c418f634211241d6aa1318468483c64cf23bcd2 | Python | 2,620 | 67 | """
utility funcs to handle encapsulated objects
"""
import numpy as np
def handle_encapsulated_contour(outer_cont, inner_cont) -> np.ndarray:
"""
given an outer contour (potentially) containing included inner contours this
functions generates a contour representing the exact topology (outer contour
w... |
cb69e549aa393f2be74c9f376ac6d59368fcf4e6271a7d93ffbee49be081551d | Python | 2,620 | 76 | #!/usr/bin/env python
"""Convert GlimmerHMM GFF3 gene predictions into protein sequences.
This works with the GlimmerHMM GFF3 output format:
#gff-version 3
#sequence-region Contig5.15 1 47390
Contig5.15 GlimmerHMM mRNA 323 325 . + . ID=Contig5.15.path1.gene1;Name=Contig5.15.path... |
cc9191aab6b8307c5d5114050aac03d03c4bfd426d0f7bf0ba295bb2bdfb3629 | Python | 2,620 | 82 | from typing import Callable, Dict
import numpy as np
from hobj.types import ImageId
# %%
class RepresentationalModel:
"""
Class which maps images to feature vectors of shape (d,).
"""
def __init__(
self,
d: int,
image_to_features_func: Callable[[ImageId], np.ndarray],
):... |
30db1d769db7d9b9443bc220e68f5bd408193f0937114bc89798efc98abe9a6e | Python | 2,622 | 99 | import numpy as np
import pandas as pd
from tqdm.notebook import tqdm
from constants import DATA_SUBSETS, RANDOM_SEED, LABEL_FEATURE, ROGUE_WAVE_THRESHOLD
def read_files(infiles):
"""Read all parquet input files into a single pandas DataFrame."""
if isinstance(infiles, str):
infiles = [infiles]
... |
4e4137fc8a9fa14c289aed2c2b36f14d1c4ee41bc5cdf737d35f7fd3d143b617 | Python | 2,622 | 68 | from unittest import TestCase, main
from os.path import join, abspath, dirname
from deblur.workflow import _system_call, create_otu_table
from tempfile import mkdtemp
from shutil import rmtree
from biom import load_table
class TestScript(TestCase):
def setUp(self):
self.data_dir = join(dirname(abspath(__... |
a6f323561380a74d120c41d3cfc872e21ea9a38f25c69254c1271145f87dd1fd | Python | 2,622 | 66 | import time
from pytest_celery import RESULT_TIMEOUT, CeleryTestSetup
from t.smoke.tasks import add
def _wait_until(predicate, timeout=RESULT_TIMEOUT, interval=0.5):
deadline = time.monotonic() + timeout
result = predicate()
while not result and time.monotonic() < deadline:
time.sleep(interval)
... |
2f4221e412fdf0f738deaec050933736786d425c1fb057b6f26e775fd1134858 | Python | 2,623 | 77 | import collections
from cycler import cycler
import matplotlib.pylab as plt
from matplotlib.figure import Figure
from matplotlib.backends.backend_qt5agg import (
FigureCanvasQTAgg as FigureCanvas)
import numpy as np
from ..head import custom_widgets
class MPLPreproc:
def __init__(self):
"""Matplotli... |
76bad5ec18ce64c4c19447635b1a19a8a6f596ac383ec218cf25b77445918dbf | Python | 2,623 | 65 | from ovseg.model.SegmentationModelV2 import SegmentationModelV2
from ovseg.preprocessing.SegmentationPreprocessingV2 import SegmentationPreprocessingV2
from ovseg.model.SegmentationEnsembleV2 import SegmentationEnsembleV2
from ovseg.model.model_parameters_segmentation import get_model_params_3d_UNet
from ovseg.utils.io... |
f2d1a51d6198848b3915d117b2953d25194e59f5c349e55515e840d5f16c5bab | Python | 2,624 | 99 | from mongoengine import *
import datetime
class TaskModel(DynamicDocument):
id = SequenceField(primary_key=True)
# Type of task: Importer, Exporter, Scanner, etc.
group = StringField(required=True)
name = StringField(required=True)
desciption = StringField()
status = StringField(default... |
358198694a243a39afb7075d78a17b152d96e09331a753046f72568ef6110e0c | Python | 2,625 | 76 | import matplotlib.pyplot as plt
import scipy as sp
import sklearn.decomposition as skld
from matplotlib import animation
from mpl_toolkits.mplot3d import Axes3D
def plot_results(self, results, action_data, fixed_point, title: str = "Results", dreiD: bool = False):
"""Plot results of analysis performed by chiefinve... |
848cf47787b469b72be454b59ab0f393a1601485a0fa7e9036624a816e6cd3ad | Python | 2,625 | 65 | # Copyright 2017 The TensorFlow Authors. 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
#
# Unless required by applica... |
8a5190ddc3a35fbd8a2d85ce40a2567a9e75b829d67cdebfd01073cf388a11b0 | Python | 2,625 | 85 | import copy
from typing import Any
import numpy as np
import pandas as pd
from mirp._images.generic_image import GenericImage
from mirp._imagefilters.generic import GenericFilter
from mirp._images.transformed_image import TransformedImage
from mirp.settings.generic import SettingsClass
class SquareRootTransformedIm... |
005bf0b5b93789fe1ed19d834882b0b8554706194c27b750642c7129896c94ac | Python | 2,626 | 86 | import sys
import copy
import argparse
import logging
import pathlib
import numpy as np
import joblib as jb
import mudcod.sutils as sutils
import mudcod.community_detection as community_detection
logging.captureWarnings(True)
parser = argparse.ArgumentParser(
description="Cell-type-specific subject split experime... |
03e369f3210bc62efeddcb1b67179bbef7c375b958fbde84d4ebf75ab9f39cd9 | Python | 2,626 | 88 | from .base import Renderer
class FakeRenderer(Renderer):
"""
Fake Renderer
This is a fake renderer which simply outputs a text tree representing the
elements found in the plot(s). This is used in the unit tests for the
package.
Below are the methods your renderer must implement. You are fre... |
af293ec22b22ef4e6388d9557947ca2b5b22305676b916e32829c69f6a11b556 | Python | 2,626 | 75 | # from schnetpack.md import neighborlist_md, calculators
from ase import io
# from ase.build import bulk
import time
from mace.calculators import MACECalculator
# import schnetpack as spk
# import random
# from ase.md.npt import NPT
from ase.md.langevin import Langevin
from ase.units import s
from ase import units
from... |
5ecb55f96882e475bc8acdf0df21428aab779eb3c8b6492ce1771d55e03f17ed | Python | 2,627 | 80 | import argparse
import numpy as np
import sys
def generate():
parser = argparse.ArgumentParser()
parser.add_argument('--vocab_file', default='vocab.txt', type=str)
parser.add_argument('--vectors_file', default='vectors.txt', type=str)
args = parser.parse_args()
with open(args.vocab_file, 'r') as f... |
aaea563c40b9da52c5be555c33b528dcb6c7af09628835069828076cf06c76f1 | Python | 2,627 | 89 | """Comprehensive predicate API contract tests for fastlog."""
from __future__ import annotations
from collections.abc import Generator
from typing import Any
import pytest
import torch
from torch import nn
import torchlens as tl
from torchlens.fastlog import CaptureSpec, PredicateError, RecordContext
class Predic... |
c09d936b483ceb25d39a91e300cab374dc6d85c3fbbc3861def64e4eab75d933 | Python | 2,627 | 69 | from pathlib import Path
import torch
import torch.nn.functional as F
from brainbox import trainer
from brainbox.physiology.neural import cc
from src import readout
class Trainer(trainer.Trainer):
def __init__(self, root, model, train_dataset, n_epochs, batch_size, lr, lam, shuffle=True, device="cuda", id=None... |
d562a5f689b892679cdc190b0cf3629f1ab3c0119bc0dc1a0cdeb00886f0e24b | Python | 2,627 | 108 | """
Useful constants
"""
from pyproj import CRS
UNIVERSAL_CRS = CRS.from_epsg(3857)
DEFAULT_CRS = CRS.from_epsg(4326)
UID = 'uid'
TID = 'tid'
LATITUDE = 'lat'
LONGITUDE = 'lng'
ORIGIN = 'origin'
DESTINATION = 'destination'
ORIGIN_LAT = 'origin_lat'
ORIGIN_LNG = 'origin_lng'
DESTINATION_LAT = 'destination_lat'
DESTINA... |
18fc1c5ac54d1e2386829c256fe03fe28035cd7029337697099737c7b2e51cd4 | Python | 2,629 | 97 | # %%
'''
Extracts regions based on Tian SC parc. Saves ROI masks and a list of centroids.
Looks at con_0006 ('threat reversal') and con_0007 ('safety reversal') specifically.
'''
from nilearn import plotting
from nilearn.image import new_img_like
from scipy.ndimage import center_of_mass
import nibabel as nib
import nu... |
48fd8a54969e45699079a0f5ee218fe3fcb8e79bcd3e238f54402c44ae0f368a | Python | 2,629 | 71 | from pydantic import AliasChoices, Field, model_validator
from pydantic_settings import BaseSettings, SettingsConfigDict
class Settings(BaseSettings):
model_config = SettingsConfigDict(env_prefix="", extra="ignore")
db_url: str = Field(
"postgresql://codecarbon-user:supersecret@localhost:5432/codecar... |
eedc65eb40f6dd57d086cb66631846543a5be16d3991ce9fcdeb75d4494767b8 | Python | 2,629 | 66 | import torch
from typing import Dict
def compute_gradient(
data: Dict[str, torch.Tensor],
chains: Dict[str, torch.Tensor],
centered: bool = True,
pseudocount: bool= False,
) -> Dict[str, torch.Tensor]:
"""Computes the gradient of the log-likelihood. By default implements the centered version of th... |
02f5f818fa087a9a4aff0a5bcfb543abf7119dd847f9768f591dacd75b7771ec | Python | 2,630 | 30 | # Read in the file
with open('index.html', 'r') as f:
data = f.read()
# data = data.replace('<h1>Index</h1>',
# '<h1>Index 🔍</h1>')
# data = data.replace('<a href="https://csinva.github.io/imodels/">Docs</a>',
# '<a href="https://github.com/csinva/imodels">Github</a>')
#... |
13e81d33085d6a401e262acb0301337ae85a53498d85b2445855d970789c376f | Python | 2,630 | 74 | # 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.
import random
import numpy as np
import torch
from torch.utils.data.sampler import Sampler
def worker_init_fn(worker_id... |
3f3f88313763a0ddc3d382935ec51fe4d08e8f8b160ba4bb57700c7ab3af7af9 | Python | 2,630 | 71 | from numpy.testing import assert_array_equal
import numpy as np
import pytest
from pytest import approx
from pyriemann.utils.ajd import rjd, ajd_pham, uwedge
@pytest.mark.parametrize("ajd", [rjd, ajd_pham, uwedge])
@pytest.mark.parametrize("init", [True, False])
def test_ajd(ajd, init, get_covmats_params):
"""Te... |
52590085bb2c9c9ae477b62d15c44f431929b13decc28df2c0c5f3726b84383a | Python | 2,630 | 99 | """Double DQN."""
import argparse
from collections import OrderedDict
from typing import Tuple
from pytorch_lightning import Trainer
from torch import Tensor
from pl_bolts.losses.rl import double_dqn_loss
from pl_bolts.models.rl.dqn_model import DQN
class DoubleDQN(DQN):
"""Double Deep Q-network (DDQN) PyTorch ... |
8de0711c217e44bd02e025db48102ce10c193f091ed05952a23f9227362c41b0 | Python | 2,630 | 77 | #!/usr/bin/env python3
import argparse as ap
import numpy as np
import pandas as pd
import pickle
from tqdm import tqdm
# Parse arguments
parser = ap.ArgumentParser()
parser.add_argument("files", nargs="+", type=str)
parser.add_argument("-out", "--output", type=str)
args = parser.parse_args()
# Open first file to g... |
9fb2eb5192c84d152d30a82f1e48028dd56b9466ccf173bc9604783e612fdb7f | Python | 2,630 | 69 | import os
import json
import shutil
import glob
from tools.hash_value.morphology import make_morphology_hash_key_dict
'''
Code for transferring morphology files from BluePyOpt output to BasalGangliaData
and Snudda format
'''
def transfer_morphologies(source, destination, selected=False):
"""
:par... |
faa0358fab579e8b4170686f06b32c81b6d653f7d38b92b3f5b43c1f662059a0 | Python | 2,631 | 72 | import numpy as np
import sympy as sp
from scipy.integrate import odeint
from . MarkovModel import MarkovModel
from . MarkovChain import MarkovChain
from . common import *
from . settings import settings
class M10Model(MarkovModel):
"""
A four state Hodgkin-Huxley model with k=e^{av+b} parameters
"""
... |
5ec91c846f710813fa22772fc555d5a04a82c8f093cfa045bd303d359e69609f | Python | 2,632 | 82 | from typing import Literal
import numpy as np
import scanpy
from anndata import AnnData
from numpy.random.mtrand import RandomState
_InitPos = Literal["paga", "spectral", "random"]
def run_umap(
adata: AnnData,
min_dist: float = 0.5,
spread: float = 1.0,
n_components: int = 2,
maxiter: int | Non... |
7cced387b943e03615803710d2030b1520f30f8d9640631dcff0311cfc631ea3 | Python | 2,632 | 93 | from abc import ABC, abstractmethod
import attr
import torch
class LocalSplicepointModelResidualPropagator(ABC):
"""
Represents a technique for propagating the LSSI residual through a model.
"""
@abstractmethod
def propagate_residuals(self, output, splicepoint_results_residual):
"""
... |
91d34f84222b38eb586157d231efb3040fe522d4245e9762888730b7df50a457 | Python | 2,632 | 95 | import pytest
from pyrosm import get_data
@pytest.fixture
def test_pbf():
pbf_path = get_data("test_pbf")
return pbf_path
@pytest.fixture
def helsinki_pbf():
pbf_path = get_data("helsinki_pbf")
return pbf_path
def test_parsing_natural_with_defaults(test_pbf):
from pyrosm import OSM
from py... |
cefb01b9507f173510f5bcc1e633273e5c2dd35b850822d021b6c2a7d65ea373 | Python | 2,632 | 96 | #!/usr/bin/env python3
"""Resolve the next FA4 beta tag and optionally create + push it.
Usage:
python bump_beta_tag.py # dry-run by default
python bump_beta_tag.py --push # create and push the tag
"""
from __future__ import annotations
import argparse
import os
import re
import subprocess... |
3b1ac397632e2ae313bfc864e88f86ec6aebaa656a7098c0abf28986c630139b | Python | 2,633 | 78 | from collections import defaultdict
import itertools
import os
import warnings
import numpy as np
import torch
from permacache import permacache, stable_hash
from more_itertools import chunked
from modular_splicing.dataset.basic_dataset import basic_dataset
@permacache(
"analysis/extract_psams",
key_functi... |
5e4cca8f23980227b45508de66254d78f3d682a1813aecd4e41606df04867fc2 | Python | 2,633 | 79 | """
Video Utilities Module
This module provides utility functions for video file management including
file listing, video file indexing operations, and migration utilities
for directory structure updates.
"""
import glob
import logging
import os
import subprocess
def list_local_video_files(rootdir, createMD5=False)... |
85c35e6114017b4a01f36365f6a723654b221ddbd528e0104666f0602af00bfe | Python | 2,633 | 74 | import numpy as np
import os
import cv2
import os.path as osp
def compute_mean_std(dataset_dir):
"""
计算给定数据集中所有图像的RGB通道的平均值和标准差
参数:
dataset_dir (str): 数据集路径，包含所有图像文件的目录
返回:
mean (np.ndarray): RGB通道的均值，形状为(3,)
std (np.ndarray): RGB通道的标准差，形状为(3,)
"""
# 初始化变量
pixel_n... |
30bdeb95b42600f1a17b01779c8a397565f16ebb27d4d211eeea4f767543f7a8 | Python | 2,634 | 74 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import print_function, division
import json
import argparse
from os import walk
from os import path as osp
from zipfile import ZipFile
from gluoncv.utils import download, makedirs
def parse_args():
parser = argparse.ArgumentParser(
description... |
5028eeb2ede96c28107d2b6f2fd4d4e311312503dd128a1db257a14f42b764f0 | Python | 2,634 | 103 | #!/usr/bin/env python3
# encoding: utf-8
import os, sys, re
import logging
import argparse
import gzip
from collections import defaultdict
def main():
parser = argparse.ArgumentParser(description="validate fastqs", formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument("--left_fq",... |
6035dc15df258f33a793d99c751f53de18c8799d8e391df89ba310fa8461d1ec | Python | 2,636 | 70 | from datetime import datetime
import warnings
import sklearn
import auggam.config as config
from datasets import load_from_disk
import auggam.linear
import auggam.data
import pandas as pd
from copy import deepcopy
from transformers import AutoTokenizer, AutoModelForSequenceClassification, AutoModel, AutoModelForCausalL... |
d29482fcd6b7b17e2286cddc30ca3cb64ab6afbda51bc97f80a62d4c6b4339a8 | Python | 2,636 | 69 | from src.keras_tuner_cv import *
from src.data_processing import *
import keras_tuner as kt
import pandas as pd
import numpy as np
import os
import click
import datetime
@click.command()
@click.option('--cuda_device', default='0', help='which GPU to use', show_default=True)
@click.option('--input_train', default='../... |
640bd6949735b4bdc6ccfdeb67d32be38d4f77aaa7652c8386bfa2ea03ba9736 | Python | 2,637 | 80 | # This example requires the following dependencies to be installed:
# pip install lightly
# Note: The model and training settings do not follow the reference settings
# from the paper. The settings are chosen such that the example can easily be
# run on a small dataset with a single GPU.
import pytorch_lightning as p... |
0865226feac5065a7fd4cbb5fd0d2a35f3cb8b87c9a389f506b66983a24030e2 | Python | 2,639 | 67 | ### Monte-Carlo routines for significance level estimation
import numpy as np
import sys
from .random_proc import ar1
from .fnutils import take
def mc_levels(transform_fn, size=(256,256),level=3, N = 1e3):
"""Return Monte-Carlo estimation of noise :math:`\\sigma`
Parameters:
- transform_fn: (`functio... |
5fc1197620852e4ca7233b7082a03e076ba7bd10e093373107b845c1fdeadea9 | Python | 2,639 | 82 | """grind-r5 b7 R24: the roster contradiction guard must survive ``python -O``.
The plain-callable branch of the ``get_ignored_functions`` vs
``get_testing_overrides`` contradiction check was a bare ``assert`` +
``continue``: under ``-O`` the assert stripped, and a (fault-injected) future
torch listing an overridable f... |
328c2d28d131f097c063bf22335a51a33ea0d68b52b3945892dbe6aa0d2ccd94 | Python | 2,640 | 73 | import os
import warnings
import h5py
import numpy as np
import pandas as pd
import scanpy as sc
from scbig import run_scbig, preprocess, setup_seed
warnings.filterwarnings('ignore')
for dataset in ['fetal_liver_atlas', 'Trachea']:
print('----------------real data: {} ----------------- '.format(dataset))
set... |
b790a9d36c88fe3fa93e62ecf54bbc24dff5a2ac61214110189040ca3cca3c07 | Python | 2,640 | 82 | """Composite datatype for the HDF5SummarizedExperiment R data object.
This datatype was created for use with the iSEE interactive tool.
"""
from galaxy.datatypes.data import Data
from galaxy.datatypes.metadata import MetadataElement
from galaxy.datatypes.protocols import (
HasExtraFilesAndMetadata,
HasMetadat... |
f9c1efa0205911f93a3d04d159e651f6adf63541505c42b54f16b97eb0e93886 | Python | 2,640 | 30 | # Read in the file
with open('index.html', 'r') as f:
data = f.read()
# data = data.replace('<h1>Index</h1>',
# '<h1>Index 🔍</h1>')
# data = data.replace('<a href="https://csinva.github.io/imodels/">Docs</a>',
# '<a href="https://github.com/csinva/imodels">Github</a>')
#... |
ff4da05ddc4cc28dacaa2bd5e084fb6a52c35a0cceae7446eaf2e7f2cf465990 | Python | 2,640 | 92 | # Author: Aqeel Anwar(ICSRL)
# Created: 7/30/2020, 1:44 PM
# Email: aqeel.anwar@gatech.edu
# Code resued from https://stackoverflow.com/questions/38511444/python-download-files-from-google-drive-using-url
# Make sure you run this from parent folder and not from utils folder i.e.
# python utils/fetch_dataset.py
import... |
2b65cb904dc166c38f27ad79b849f1ca88b3a98bf1e688341852bca4f5a58223 | Python | 2,641 | 88 | """Fuzzy Min-Max Neural Network, 1992, Patrick Simpson.
Paper: Simpson 1992, "Fuzzy min-max neural networks. I. Classification."
Hyperbox membership measures compare each feature to learned lower and upper
corners, then aggregate boxes by class.
"""
from __future__ import annotations
import torch
from torch import T... |
6fc912ec3aa977ea5d97317a4302a00877246ad53c90558435cf3bbc47999960 | Python | 2,641 | 68 | # Copyright 2019 Novartis Institutes for BioMedical Research Inc. Licensed
# under the Apache License, Version 2.0 (the "License"); you may not use
# this file except in compliance with the License. You may obtain a copy
# of the License at http://www.apache.org/licenses/LICENSE-2.0. Unless
# required by applicable law... |
d4174305da79b02e076a0d857ad87fde31a414c0d9dda0a90826c62a9d4c9f2e | Python | 2,641 | 73 | import numpy as np
import sympy as sp
from scipy.integrate import odeint
from markov_builder.example_models import construct_four_state_chain
from . MarkovModel import MarkovModel
from . import common
class BeattieModel(MarkovModel):
"""
A four state Hodgkin-Huxley model with k=e^{av+b} parameters
"""
... |
6f2db9244d9c5f19f8e64e6c427b866464813d8f8f3f131b6f5ed704b07eb4ea | Python | 2,642 | 67 | from typing import Dict, Any
from .atomistic import AtomicDimeNet
from .atomistic_nn_model import AtomisticNNModel
from bioconfpred.data.split import DataSplit
from bioconfpred.params import (LOG_DIRPATH,
DIMENET_CONFIG,
DIMENET_MODEL_NAME)
class DimeNetModel(AtomisticNNModel):... |
599facb857e88437879d22e588e38d2b8585b6553e48f78c4f9538941b93bf3a | Python | 2,643 | 43 | #==============================================================================#
# Author: Dominik Müller #
# Copyright: 2024 IT-Infrastructure for Translational Medical Research, #
# University of Augsburg ... |
5b68d2fa6bd72f5d799eab995348c03231b6206857c0250e5f5534fc19dbfd4a | Python | 2,643 | 99 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Nov 29 10:25:54 2018
@author: nfcontrol
"""
# import statements - all of these are packages within the rt environment
import time
from random import random as rand
import sys
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
im... |
4e7796dc68e484e2e33effb8d6ea5ee263fad42656ffce91d3c0e8bce258c6f7 | Python | 2,644 | 77 | # coding=utf-8
# Copyright 2025 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... |
bd2d6d5ecd6943733d50bdad1a17c2bad9e7b0804fa664d97b6a7ec8ae55135a | Python | 2,644 | 79 | from __future__ import print_function, unicode_literals, absolute_import, division
from six.moves import range, zip, map, reduce, filter
from ..utils import _raise, backend_channels_last
import numpy as np
from ..utils.tf import keras_import, BACKEND as K
def _mean_or_not(mean):
# return (lambda x: K.mean(x,ax... |
fd75229f1196972db82672234307c872cdaa815be06241f960f4d510b4a80b1c | Python | 2,644 | 91 | #!/usr/bin/env python
"""
Input: File with tab separated columns.
One column contains the id's of a collection of molecules
that should to be retrieved.
Output: Retrieved compounds
"""
import argparse
import sys
import cheminfolib
import psycopg2.extras
cheminfolib.pybel_stop_logging(... |
dd6dfae3ff10e1ad3a29e05ad635a2737f24cf3b4638339f569039da25ce784e | Python | 2,645 | 91 | import numpy as np
import matplotlib.pyplot as plt
from collections import defaultdict
from modular_splicing.utils.statistics import bootstrap
def plot_by_model_group(
vals,
names,
title,
ylabel,
*,
ax=None,
colors,
extra_zero_line=True,
error_bars=True,
):
"""
Run a plot... |
f349a7cac7eb8338fcd16eea927cb0e26e81034642f0d116711feae91a1166a0 | Python | 2,645 | 62 | # 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... |
5a6c7ee90db0dac8c1fd3736b70f599a77ba7551104f173b8263d6d7662a9241 | Python | 2,646 | 66 | """
Framework constants — single source of truth across the paper series.
Imported by:
- paper5_5d/pipelines/reprocess_car_local.py
- paper7_ad_cross_cohort/analyses/state_geometry.py
- paper4_empirical/code_package/eeg_phi_analysis_v3.py
- paper4_empirical/code_package/eeg_regional_analysis_v2.py
- paper4_e... |
08e155723e3d939543d8f6daf704c93d517c39720a6d81fa95e2c4e876f93234 | Python | 2,647 | 72 | """
This module define the EncoderModel
"""
import math
import torch.nn as nn
import torch
# Create pytorch Transformer model
class model_ENCODER(nn.Module): # pylint: disable=invalid-name,abstract-method
"""
This class was created a long time ago but we CANNOT change the content because
we load the pre... |
6b601253e67524bf5ef958d29b8d2159669693031417dc09b2e3cdd20aaa7992 | Python | 2,647 | 95 | import os
import psutil
import sys
import traceback
PROCESS = psutil.Process(os.getpid())
MEGA = 10 ** 6
MEGA_STR = ' ' * MEGA
def main():
try:
print_memory_usage()
#alloc_max_str()
alloc_max_array()
except MemoryError as error:
# Output expected MemoryErrors.
log_exce... |
2182c274bc8914dfa7760de72d5476d1bc9853666dde487899e00612a7a9ec87 | Python | 2,648 | 73 | import os
import pandas as pd
import numpy as np
from sklearn.ensemble import BaggingRegressor
from sklearn.ensemble import BaggingClassifier
from sklearn import linear_model
import sklearn
import pickle
def load_model(in_model_fp=r"./models/model_clinical.pkl"):
if not os.path.exists(in_model_fp):
print("... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.