sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
9c131f82603b84b6b260352c377d2c5798cb6a267b523570700f370ec2c0446f | Python | 3,433 | 114 | # built-in dependencies
from typing import Tuple, Any
# 3rd party
import numpy as np
from numpy.typing import NDArray
import cv2
def normalize_input(img: NDArray[Any], normalization: str = "base") -> NDArray[Any]:
"""Normalize input image.
Args:
img (numpy array): the input image.
normalizat... |
ec222381db9599af8235f4bb2b4bae14d3c8fd3b86231c0e549fdb5ae33bb06b | Python | 3,433 | 90 | #!/usr/bin/env python
# coding: utf-8
# author: Maruthi Mutnuri (maruthi2008@gmail.com)
# loading libraries
import pandas as pd
import numpy as np
# loading database file
INTERVENTIONS_s = pd.read_pickle('/project/M-ABeICU176709/ABeICU/data/INTERVENTIONS.pickle', compression = 'zip')
# selecting columns
INTERVENTION... |
3d40bd3d5d2e0b34715f23e6dd7844ba7208adcbb5540dba0a054fc66f44b168 | Python | 3,434 | 92 | import unittest
from collections import namedtuple
import torch
try:
import numpy as np
except ImportError:
np = None
from rising.loading.collate import numpy_collate
class TestCollate(unittest.TestCase):
@unittest.skipIf(np is None, "numpy is not available")
def test_numpy_collate_int(self):
... |
5d3751a0675b149ce90f66e291da12bfe7d49d501e51124fb11b7f13b0ddd7a5 | Python | 3,435 | 97 | import pytest
import torch
@pytest.mark.parametrize("first_batch_size,second_batch_size", [(2, 4), (4, 2), (2, 2)])
def test_batch_size_mismatch(first_batch_size, second_batch_size):
from copy import copy
import sinabs.layers as sl
# Setting the spike_threshold larger than the number of timestamps, such... |
80342be8ee56a26fe66bf4c2a6263b0f32eb476da08cbb688fd95521a2929d12 | Python | 3,435 | 76 | # Copyright 2021 Division of Medical Image Computing, German Cancer Research Center (DKFZ)
# and Applied Computer Vision Lab, Helmholtz Imaging Platform
#
# 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 L... |
c5405d56e775a97f40cfa5ef92ec66e823ba2a4f710c1d5ccd0e4f5ba81b27e4 | Python | 3,436 | 104 | from typing import Any, Optional
import numpy as np
import torch
from torch.nn import functional as F
class TransformerBase(torch.nn.Module):
"""Abstract class for transformers."""
@staticmethod
def __top_k_logits(logits: torch.Tensor, k: int) -> torch.Tensor:
"""From https://github.com/karpathy... |
d09a81a42ffef210045f44832281530ced0bc1c374eb91e9c605b63ab20e970e | Python | 3,436 | 143 | from . import np, ut, pd
def save_samap(sm,fn):
import dill
if len(fn.split('.pkl')) == 1:
fn = fn + '.pkl'
sm.path_to_file = fn
#TODO: Clean this up...
try:
del sm.sam1.SamGui
except:
pass
try:
del sm.sam2.SamGui
except:
pass
try:
... |
54361caf752d117f70d6d6f822a442d432774fcc52979f68b5d987aaaacf5de5 | Python | 3,437 | 97 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
98f1aba15c161cc10dcf9becaef6ebfb6524a396b55378eeff96755d9d8df197 | Python | 3,437 | 90 | import torch
import torch.nn as nn
class Reg(nn.Module):
"""
Regularization module for graph-based smoothness regularization.
Args:
net (nn.Module): The neural network model.
group_size (int, optional): The number of inner parameters to group together. Defaults to 4.
"""
def __ini... |
cd1158a1a3bb9d46d001da0298fe684eb65392560abe22198c6b240d81b9472b | Python | 3,437 | 101 | """Compute statistical description of datasets."""
import multiprocessing
from concurrent.futures import ThreadPoolExecutor
from typing import Any, Tuple
import numpy as np
import pandas as pd
from tqdm import tqdm
from visions import VisionsTypeset
from data_profiling.config import Settings
from data_profiling.model... |
ce3e80e46731d429e9c484d3248376291ff5fefe88bf317ee89044058f4ee76f | Python | 3,437 | 128 | """
Useful functions for preprocessing.
"""
__date__ = "August 2019 - October 2020"
import numpy as np
import warnings
from scipy.signal import stft
from scipy.interpolate import interp2d
EPSILON = 1e-12
def get_spec(t1, t2, audio, p, fs=32000, target_freqs=None, target_times=None, \
fill_value=-1/EPSILON, max... |
ed43e09ea5e060fcd45b3e3f6fe29ff2e91120c223dad8d688e6a8dae3d7eec6 | Python | 3,437 | 80 | import os, logging, datetime
from misc.abb_med_disease import gen_abb_med_disease
from misc.save_files import read_DocTermDict, read_w2v_model
def load_models(config: dict, year_list: list, med: bool, abb: bool, disease: bool):
logger = logging.getLogger(config["System"]["logging"]["logger_name"])
target_d... |
3fc7e9f764a73933351af02255a46efe886f804f2fe66cb706a6427527489eda | Python | 3,439 | 155 | # Ultralytics YOLO 🚀, GPL-3.0 license
"""
Base callbacks
"""
# Trainer callbacks ----------------------------------------------------------------------------------------------------
def on_pretrain_routine_start(trainer):
pass
def on_pretrain_routine_end(trainer):
pass
def on_train_start(trainer):
pa... |
e94ba2d2f1798d5bbc262960e13d33df11318ea05f1b8b4e6eb7ea109bff43d9 | Python | 3,442 | 92 | import numpy as np
# Just an iterator class
class SpikingDatasetIterator:
def __init__(self, dataset):
self._dataset = dataset
self._index = 0
def __next__(self):
if self._index >= self._dataset.shape[0]:
raise StopIteration
else:
sample = (self._datase... |
8ffb1d7ae84e30ed820bb4b1a3603728954285166994affb0a8c927e19cc12e3 | Python | 3,443 | 84 | #Patches
import rasterio
import numpy as np
def crop(bounds, sensor_path=None, savedir = None, basename = None, rasterio_src=None, as_numpy=False):
"""Given a 4 pointed bounding box, crop sensor data"""
left, bottom, right, top = bounds
if rasterio_src is None:
src = rasterio.open(sensor_path)
... |
999deec05509d025d25f62347f91cc2c3426e910dc525f24e3bbb8cb8c4c0413 | Python | 3,443 | 105 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
Modified from https://github.com/pytorch/vision/blob/main/torchvision/ops/stochastic_depth.py
"""
from __future__ import annotations
import t... |
f3bcac38309d4c446961f1fe10384494e532080bbccfafb12100aa2fbdf82b08 | Python | 3,443 | 95 | # Copyright 2023 The HuggingFace 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
#
# Unless required by applicabl... |
12dd66fb010d8cbedd4efd05ec197ac455d5654ad05d046bfb5bf6d9978896f7 | Python | 3,446 | 86 | import os
import subprocess
from ci.ray_ci.container import (
# _AZURE_REGISTRY_NAME and _DOCKER_AZURE_REGISTRY imports temporarily
# commented out: Azure image push is disabled due to CI issues.
# _AZURE_REGISTRY_NAME,
# _DOCKER_AZURE_REGISTRY,
_DOCKER_ECR_REPO,
_DOCKER_GCP_REGISTRY,
)
from ci... |
5df7df7826a98ba4685f0b75298e1b538e76bc234afc53d536068459b2085265 | Python | 3,446 | 106 | import copy as cp
import logging
import multiprocessing as mp
import functools
from typing import Dict, Any, Tuple, List, Set, Optional, Type
from argschema import ArgSchemaParser
from neuron_morphology.feature_extractor._schemas import (
InputParameters, OutputParameters)
from neuron_morphology.feature_extracto... |
474c22439384cc9a9d0840dceca6d3b47baab403e7a828ea84d74a1b39b9783e | Python | 3,447 | 92 | import os
import pandas as pd
import numpy as np
import pcntoolkit as ptk
from pcntoolkit.util.utils import create_design_matrix
from pcntoolkit.dataio.fileio import save as ptksave
from pcntoolkit.dataio.fileio import load as ptkload
# globals
root_dir = '/project_cephfs/3022017.02/projects/hansav/Run8_f/'
data_dir ... |
686c065145f0ab5b979e56cc89e8344ecee227c21811cbdfcdbfbebbede57131 | Python | 3,447 | 129 | import shutil
import sys
from pathlib import Path
import pytest
try:
from pyspark import SparkConf, SparkContext
from pyspark.sql import SparkSession
has_spark = True
except ImportError:
has_spark = False
from data_profiling.config import Settings
from data_profiling.model.summarizer import Profilin... |
dd4defc5fe0d98f2cc494660bdafb2d236f18c38f3ba874f2d8ff6a38cb11d4b | Python | 3,448 | 117 | import os
import pytest
import ray
import ray.cluster_utils
from ray.exceptions import CrossLanguageError, RayActorError
# plus.so / counter.so are staged next to this file via the bazel
# target's `data` attr; resolve them absolutely so the worker finds them
# regardless of its cwd.
_CODE_SEARCH_DIR = os.path.dirna... |
99fa116d64c96e0d61d5c464d45009bcb094880a051a0a1a20e0ea0f8e1eb14c | Python | 3,449 | 111 | import unittest
from spinnaker2 import mapper, snn, hardware
class TestMapping(unittest.TestCase):
def test_add(self):
m = mapper.Mapping()
p1 = snn.Population(20, "lif", params=None)
pe_0_0_0 = hardware.PE(0,0,0)
pe_0_0_1 = hardware.PE(0,0,1)
p1_1 = mapper.PopulationSli... |
a7c623d74cc995f55c93386f622a9650ca13721cfd83d3d3fad2004805b83e52 | Python | 3,450 | 82 | import numpy as np
from typing import List, Tuple, Dict, Optional, Union
from whitenoise import RandomNoiseFrameGenerator
from lib.data_utils.sta_metadata import RGB_CONVERSION
class WhiteNoiseSynchroSection:
def __init__(self,
frame_gen: RandomNoiseFrameGenerator,
trigger_times... |
98b0370c6c615c07271b5674eb4f4e6c0bae93ad4677dfcaf68fc723e6734d48 | Python | 3,451 | 100 | '''
simple_viewer.py
A simple viewer to demonstrate the image capture capabilities of an Azure
Kinect device using the Python API. This is not the fastest way to display
a sequence of images; this is only meant to show how to capture frames
in a sequence.
Requirements:
Users should install the following python packa... |
e8dd654c722a36c7683df7c187b2dc72e93cb4548876fd54c85d2698612d3e2c | Python | 3,452 | 97 | #! /usr/bin/env python
import sys
import re
import numpy as np
import os
import iced
from iced.io import loadtxt, load_counts, savetxt
from scipy import sparse
def load_bed(filename):
'''
Load a BED file using numpy
Parameters
----------
filename : str,
path to the file to load. The file ... |
0b362f9330e16e852cd1cd8838b4ec7c4eb9549ec544999e941abc29a0359115 | Python | 3,453 | 110 | from typing import Annotated, Any, Callable, Iterable, Literal
import numpy as np
from numpy.typing import NDArray
from sklearn.base import BaseEstimator
from sklearn.metrics import get_scorer
from sklearn.model_selection import (
BaseCrossValidator,
cross_val_score,
train_test_split,
)
from siapy.core im... |
26b95dc8e89e34bdbaa1884079f13a00cd2718941e1cd4573e07250a285afd53 | Python | 3,453 | 100 | import numpy as np
import wfdb
from scipy import signal as sgn
import torch
from src.dataset.utils import compute_weights, remove_baseline_filter
BASELINE_FILTER_400 = remove_baseline_filter(400)
def map_ptb_to_swedish(traces, new_length=4096):
# we have the leads in the following order:
# DI, DII, DIII, AV... |
68335c4e9bd105e4642a7e26ed5eed75c94638164285c28800f9d16efd532b17 | Python | 3,453 | 61 | # -*- coding: utf-8 -*-
import sys
import numpy
import mozaik
from parameters import ParameterSet
from mozaik.models import Model
from mozaik.connectors.meta_connectors import GaborConnector
from mozaik.connectors.modular import ModularSamplingProbabilisticConnector
from mozaik import load_component
from mozaik.space i... |
07d322429b15583e1f4ee27ed46506e46b3ababd91214e74cf32bd41c36dd625 | Python | 3,454 | 98 | import numpy as np
import pyvista as pv
from lib.surface import find_boundary_vertices, read_surface_from_gifti, write_label_gii
from lib.utils import setup_logger
# Setup logger
log_file = snakemake.log[0] if snakemake.log else None
logger = setup_logger(log_file)
logger.info("Loading surface from GIFTI...")
surface... |
04732db3f894b1042d7f2f8498599ccddebdae511801179f496d5ae58997350d | Python | 3,455 | 92 | import os
import pandas as pd
import numpy as np
import pcntoolkit as ptk
from pcntoolkit.util.utils import create_design_matrix
from pcntoolkit.dataio.fileio import save as ptksave
from pcntoolkit.dataio.fileio import load as ptkload
# globals
root_dir = '/project_cephfs/3022017.02/projects/hansav/Run8_fs/'
data_dir... |
a0ff2e9f81b90f5617afede34f2c23d2cec3d910f15997984d8956c7dc642c80 | Python | 3,455 | 106 | r"""``ov.epi.datasets`` — fetch-on-demand example epigenomics datasets.
Convenience wrappers over epione's pooch registry
(:func:`epione.utils.register_datasets`). Each fetcher downloads (once,
then caches under epione's pooch cache) a small public dataset suitable
for running an ``ov.epi`` tutorial end-to-end, mirror... |
3408a3ad6af439cc5af7afb5d68835d25f66c5919e703237a216fdc1c27f47ea | Python | 3,457 | 103 |
import os
import glob
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
SUBS = ['sub-05', 'sub-06', 'sub-07', 'sub-08', 'sub-09']
ROOT = '/Users/sebastiandresbach/data/neurovascularCouplingVASO/Nifti'
# ======================================================================... |
515266b946ce415521c877163821c86618069667e2cfc44ea9618356481bed8e | Python | 3,457 | 92 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
5ae7e19d6f01e6a31393aa8836ced09c0be8871a96b9714f94bdff8df4dddecf | Python | 3,457 | 90 | import os
import sys
from typing import List
from unittest import mock
import pytest
from ci.ray_ci.anyscale_docker_container import AnyscaleDockerContainer
from ci.ray_ci.container import (
# _DOCKER_AZURE_REGISTRY import temporarily commented out: Azure image
# push is disabled due to CI issues.
# _DOCK... |
821b83848e5ba90164042085900d09c7797f3df31746b0c9c12b30346d3c77ab | Python | 3,458 | 100 | import numpy as np
from hic3defdr.util.progress import tqdm_maybe as tqdm
try:
from sklearn.metrics import roc_curve, confusion_matrix
sklearn_avail = True
except ImportError:
sklearn_avail = False
roc_curve = None
confusion_matrix = None
def make_y_true(row, col, clusters, labels):
"""
... |
445826a700ed12bbcde69bbf0dc42991944ef236e292aae4da7fa50a3d87bc83 | Python | 3,459 | 88 | import sys
import json
import copy
import argparse
import subprocess
from lop.utils.miscellaneous import *
def main(arguments):
parser = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('-c', help="Path of the file contai... |
a919d1013cbb4cc0f9cb000e402089dc72b89b8030ebdd9e174b7f23bcdd611e | Python | 3,459 | 95 | import time
from dataclasses import dataclass
from typing import Callable, FrozenSet, List, Optional
from .base_autoscaling_coordinator import (
AutoscalingCoordinator,
LabelSelector,
NodeResources,
ResourceDict,
ResourceRequestPriority,
ResourceRequestStrategy,
ResourceType,
)
class Fake... |
e4d2489f97630e3446734cb96ead56fa19c6491bbbc5ae210e05d57a1168f5c4 | Python | 3,459 | 90 | import os
import sys
project_root = '/ccb/cybertron/khchao/splam-analysis-results/'
input_file_dir = f'{project_root}train/results/RefSeq_ALTS/BAM_REF_Intersection/'
output_dir = f'{project_root}train/results/RefSeq_ALTS/INPUTS/'
def main():
SEQ_LEN = sys.argv[1]
HALF_SEQ_LEN = int(SEQ_LEN) // 2
QUATER_S... |
d1a4abd16726c962f9144a8bdbc144f93314f7a390ca377b9976cd3ca414178f | Python | 3,460 | 98 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
This submodule contains the scripts that the we used to run VASP.
Note that some of these scripts were taken and modified from
[GASpy](https:/... |
46aae557c7d9d2ae5c53a9dbf07c9c9b900bf363311d489304dc642eb48ca4f4 | Python | 3,461 | 96 | # built-in dependencies
import os
from typing import Any, List
# 3rd party dependencies
from numpy.typing import NDArray
# project dependencies
from deepface.models.Detector import Detector, FacialAreaRegion
class MediaPipeClient(Detector):
"""
MediaPipe from google.github.io/mediapipe/solution... |
a211106364e1e1167799065ec44715a9579a9c423cda784e2afb9acb4fdeb9dc | Python | 3,461 | 107 | import random
from imports import *
from fixtures import FIXDIR
#from .. import bam_to_qualdepth as btqd
from ngs_mapper import bam_to_qualdepth as btqd
def rand_info( ):
''' Generates random parse_pileup() info '''
depth = random.randint(0,1000)
quals = [random.randint(0,40) for i in range(depth)]
r... |
4a243be062923edad67a7942d65223b7728a97109893f6712240dca3b064bb7c | Python | 3,462 | 121 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
Clean records in VCF based on de novo filter results
"""
import argparse
import sys
from collections import defaultdict
import pysam
import svtk.utils as svu
from svtk.famfile import parse_famfile
def set_null(record, sample):
dat = record.samples[sample].item... |
3c7026c679ebbeb9e73a479ff5f5d811113bf2a47d9a9beddee8fea7c0bd627b | Python | 3,463 | 93 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
853c042636b44115223f2b57266f440310608ddcfdfb2bda70e839618ec8162a | Python | 3,463 | 129 | '''Some helper functions for PyTorch, including:
- get_mean_and_std: calculate the mean and std value of dataset.
- msr_init: net parameter initialization.
- progress_bar: progress bar mimic xlua.progress.
'''
import os
import sys
import time
import math
import torch
import torch.nn as nn
import torch.nn.i... |
f9ec33844bd23397e4c702e2ea33b538238401569201cc0461b29608a6bc1fcf | Python | 3,463 | 124 | import json
import logging
logger = logging.getLogger(__name__)
def _to_dict(value):
if isinstance(value, str) or isinstance(value, int) or isinstance(value, float):
return value
else:
return value.to_dict()
class BaseVocab(object):
def __init__(
self,
counter=None,
... |
ca74684bb036ef7f742002cfd5e4e14d403f675fa93ed96d8305a7572572d2f9 | Python | 3,464 | 103 | from abc import ABC, abstractmethod
from collections.abc import Callable
from functools import wraps
from typing import Any
from numpy.typing import NDArray
import numpy as np
import torch
class Imputer(ABC):
''' ... '''
def __init__(self,
modalities: dict[str, dict[str, Any]],
is_embedding: di... |
dc7f4f1ecd3582a6cfa02be23e7e2336c69f860a0cbb5f43033faf03660889fe | Python | 3,464 | 114 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
import numpy as np
from ase import Atoms
from ase.build import bulk, fcc111, molecule
from ase.build.su... |
7133874ffc5b44c469723db92082031dea2f79f519676dea01ba1218f79a5b5c | Python | 3,465 | 92 | import tensorflow as tf
from models.deep_learning.deep_learning_models import DLRegressor
from utils.constants import is_spline
class ConvLSTMRegressor(DLRegressor):
"""
This is a class implementing the ConvLSTM model for time series regression.
"""
def __init__(
self,
output_... |
79380f2160304f13f4ee04e8425b727e647fccce1a4dc1d1d58aec5d70111443 | Python | 3,465 | 93 | import os
import re
from os.path import join
from typing import Dict, List
import numpy as np
import pandas as pd
from numba import njit
from sklearn.metrics import classification_report
@njit
def correct_labels(y_true: np.ndarray, y_pred: np.ndarray, child_matrix: np.ndarray):
"""
Update predictions.
If... |
9c9ce1d515d08ecf5216c6fd83f724f60b62ce3a8cead2c4f04cc2bca074e8f6 | Python | 3,465 | 97 | import pandas as pd
import os
def get_hg38_chrom_size():
f_chrs = open("../hg38_chrom_size.tsv", "r")
lines = f_chrs.read().splitlines()
chrs = {}
for line in lines:
eles = line.split("\t")
chrs[eles[0]] = int(eles[1])
return chrs
def main():
THRESHOLD = "100"
SEQ_LEN="800"... |
3066212322d473dac00b447a952f567f077a2a32969aabd3a5727256b3d0baea | Python | 3,467 | 80 | # unet from mwr yuntao7.28 version
import tensorflow
from tensorflow.keras.layers import Dropout, Activation, BatchNormalization
from tensorflow.keras.layers import Add, Input, Conv2D, MaxPooling2D, UpSampling2D, Conv3D, MaxPooling3D, UpSampling3D
from tensorflow.keras.layers import Concatenate
from tensorflow.keras.mo... |
0f7747108d7b503a48f1187403ec466d9c55f76adb0aa85264b0dd9c644d52c7 | Python | 3,468 | 103 | # Copyright (c) DP Technology.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
from functools import lru_cache
from unicore.data import BaseWrapperDataset
class TTADataset(BaseWrapperDataset):
def __init__(self, datase... |
5159d4a652d2c21ceef35132c3d2fe5b8fca8c719fbda0be021705244fe3f1ee | Python | 3,468 | 103 | import asyncio
import logging
from aiohttp.web import Request, Response
import ray.dashboard.optional_utils as optional_utils
import ray.dashboard.utils as dashboard_utils
import ray.exceptions
from ray._raylet import NodeID
from ray.dashboard.modules.reporter.utils import HealthChecker
routes = optional_utils.Dashb... |
a0883987b7e908ff7824660471253df1ee84a32d45b45f4c4809b339da4d4622 | Python | 3,470 | 100 | PARAMS = {
"input_space_type": "mozaik.space.VisualSpace",
"input_space": {"update_interval": 7.0, "background_luminance": 45.0},
"visual_field": {
"centre": (0.0, 0.0),
"size": (7.0, 7.0),
},
"sheets": {
"retina_lgn": {
"component": "mozaik.models.vision.spatiote... |
096c369578a7214f8fccf0df94b057e05ad1bb47445630f0622f7ed2cc922aae | Python | 3,472 | 148 | """
Created on Tue Mar 21 14:35:00 2025
@author: ju-bar
Functions implementing interatomic potentials
This code is part of the 'emilys' repository
https://github.com/ju-bar/emilys
published under the GNU General Publishing License, version 3
Remarks: The notation is in so-called "metal" units, where
[charge... |
89304306efd0ee4443155c57c11512720f9d6ac9061a0af1bfa1db958d3651d1 | Python | 3,473 | 142 | """Common util functions (e.g. missing in Python)."""
import collections.abc
import contextlib
import os
import platform
import subprocess
import zipfile
from datetime import datetime, timedelta
# Image type detection
from pathlib import Path
from typing import Mapping
import pandas as pd
import requests
from data_... |
95f20992ec2039bcf972f794906fe733208c619809361c4eac811c2fc58b5ddb | Python | 3,474 | 181 | r"""
Set the color palette for plotting.
Reference
---------
https://github.com/scverse/scanpy/blob/master/scanpy/plotting/palettes.py
"""
from matplotlib import cm, colors
# Colorblindness adjusted vega_10
# See https://github.com/scverse/scanpy/issues/387
vega_10 = list(map(colors.to_hex, cm.tab10.colors))
vega_10... |
87fcf6fbd8fd9d1fd7c3d0113b97540e74545e7546130324c87f4bb776d11fbf | Python | 3,475 | 109 | from functools import partial
from warnings import warn
from typing import List, Optional, Set
import pandas as pd
import numpy as np
def _check_features(df,
features: List[str]) -> Set[str]:
valid_features = set(df.index) & set(features)
if len(features) != len(valid_features):
w... |
92e27efdcee178a8cc9893f7035ed4f963a370f636927f9fadca2062dfad20b0 | Python | 3,476 | 95 | import torch
import torch.nn as nn
import numpy as np
from torch.optim import AdamW
import torch.optim as optim
import itertools
from model.warplayer import warp
from torch.nn.parallel import DistributedDataParallel as DDP
from model.IFNet import *
from model.IFNet_m import *
import torch.nn.functional as F
from model.... |
94aa22659d0eb91a0ce69d33f50543ebdba7606c9e189fc33fafb4e84e73840c | Python | 3,476 | 90 | import sys, os
import argparse
import concurrent.futures as cf
import numpy as np
import pandas as pd
import torch
os.environ.setdefault('PROJECT_DIR', ".")
sys.path.append(os.environ['PROJECT_DIR'])
from src.models.model_whole import prepare_model, add_model_args
from src.models.components import MeanPooler, StartPool... |
78cd40d3ee2140ecb7de4fdc19a495a711ffa5be87655c14d54a95869920179b | Python | 3,477 | 99 | #
# CEBRA: Consistent EmBeddings of high-dimensional Recordings using Auxiliary variables
# © Mackenzie W. Mathis & Steffen Schneider (v0.4.0+)
# Source code:
# https://github.com/AdaptiveMotorControlLab/CEBRA
#
# Please see LICENSE.md for the full license document:
# https://github.com/AdaptiveMotorControlLab/CEBRA/bl... |
3e8fba4af3e50aee59c1a9574da7cabe8fba972bbb64aa7f44e8402476170e11 | Python | 3,478 | 105 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# -------------------------------------------------------------------------
# Created By : Kangjoo Lee (kangjoo.lee@yale.edu)
# Last Updated: 08/06/2024
# -------------------------------------------------------------------------
# =========================================... |
4a0a42b17b5e2fb73425dbc322268e391b7392f3e86b1b82d4c15cf445415e00 | Python | 3,478 | 104 | import os
from importlib.util import find_spec
from typing import List, Union
import torch
import ray
import ray._private.ray_constants as ray_constants
from ray._private.accelerators.npu import ASCEND_RT_VISIBLE_DEVICES_ENV_VAR
from ray.air._internal.device_manager.torch_device_manager import TorchDeviceManager
de... |
88fdbc50c996a6cbdd2f8ef3f48715820e12a9ab90e2d44ab1b117f9200dc051 | Python | 3,478 | 92 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
abd5ee2be17059b7c4e3425008fc2d0c75639381ff2a039ae7522a188128c12a | Python | 3,478 | 113 | import logging
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
from ray.data._internal.delegating_block_builder import DelegatingBlockBuilder
from ray.data._internal.util import _check_import
from ray.data.datasource.file_based_datasource import FileBasedDatasource
if TYPE_CHECKING:
impo... |
4d2406e3ace5588ec00451b72b5df193c005cdd4aaf8f058eb2113a0409bc7fe | Python | 3,479 | 89 | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
import matplotlib.pyplot as plt
import pdb
from numpy.fft import ifftshift
from torchvision.transforms import Resize
import fractions
import math
def fft_conv2d(img, psf):
img_fft = torch.fft.fft2(torch.fft.fftshift(i... |
d0c25bdbcf9fa86616a7d83946307bdc99a1c2f2c11de868acae4757b160a912 | Python | 3,481 | 104 | import nibabel as nib
import numpy as np
from lib.qc_srcsink import compute_qc
from lib.surface import (
assign_boundary_terminals,
read_surface_from_gifti,
write_label_gii,
)
from lib.utils import setup_logger
log_file = snakemake.log[0] if snakemake.log else None
logger = setup_logger(log_file)
nmin = ... |
38292c40069e757d4296f4f2ee0c718a0d41a3bb5b343eb766f0e4349955f450 | Python | 3,482 | 108 | import numpy as np
from numpy.linalg import inv
from sklearn.mixture import GaussianMixture
def construct_landscape(sc_object,thresh_cal_cov = 0.3, scale_axis = 1.0,
scale_land = 1.1, N_grid = 100, coord_key = 'X_umap'):
"""
Function to construct the landscape of the multi-stable attra... |
50238415164c84a0cbdcf3a0a6d9d1b98e1e260b4cb87f5c5ec11dae043e9b92 | Python | 3,482 | 75 |
# location for defining the Pytorch model architecture that will be read in during model training
import torch
import torch.nn as nn
import torch.nn.functional as F
# a version of the model for hyperparameter optimisation, that has the opportunity to change the model hyperparameters on init
class LSTM_Drop... |
135d65571c9c58586fc80189820c5fce8db1905c6cac7f7b2cd2bcc989f3e8b1 | Python | 3,483 | 96 | from typing import Dict
import numpy as np
import pandas as pd
import tensorflow as tf
from ml4ht.data.data_description import DataDescription
from data_descriptions.echo import VIEW_OPTION_KEY
class EcholabDataDescription(DataDescription):
# DataDescription for a wide file
def __init__(
self,... |
53128829de5c13ecc2644cafa95e897626845b62b9057bcf80fff024aab1f457 | Python | 3,485 | 118 | from scipy.io import loadmat
from scipy.special import erfcinv
import numpy as np
import pandas as pd
from scipy.stats import kruskal
from itertools import combinations
def star(p_val):
assert 0 <= p_val <= 1
if p_val >= 0.05:
return 'ns'
if p_val >= 0.01:
return '*'
if p_val >= 0.... |
0b70f9e876dd085ec1da548941d21b37a743666ef3e48a8829fe3cc869defdd7 | Python | 3,486 | 89 | """
Created on Sun May 30 19:40:39 2021
@author: trmabdelaal
"""
import scvelo as scv
import scanpy as sc
import numpy as np
import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt
from sklearn.metrics.cluster import contingency_matrix
import sys
sys.path.insert(1,'SIRV/')
from m... |
9b90e76beb4769c0a5d043fc3b3e8cb3a73d48888df996afe7561716ba367c23 | Python | 3,486 | 104 | # built-in dependencies
from typing import List, Union, cast
# 3rd party dependencies
import torch
from torch import nn, Tensor
# project dependencies
from deepface.commons import weight_utils
from deepface.models.facial_recognition.pytorch.TorchFacialRecognition import (
TorchFacialRecognition,
load_model_we... |
df3cc5f57f3c250750cb82bb9ad822f11bf7c3fbfce8a430574ebb28e5e32d22 | Python | 3,486 | 137 |
import numpy as np
import argparse
import pandas as pd
import math
import pdb
import Bio.Seq as bioseq
def oneHotFromSeq(inputStr, seqLength): #, seqOrient="+"):
# See if this is empty
# If so, return a zero'd vector
# pdb.set_trace()
if not ((isinstance(inputStr, str)) ):
return (np.zeros((4, seqLength)))
#... |
e73c06abb02c43ebcb463f22dcf5207497345b80e27b1741d158079688c2e806 | Python | 3,486 | 86 | import torch
import logging
from torch.utils.data import TensorDataset
from sklearn.model_selection import train_test_split
from sklearn.feature_extraction.text import TfidfVectorizer
from agent.data.entities.config import FC_CLASS_VALUES
from agent.classifiers.utils.class_mgmt import get_number_of_classes, get_numer... |
bf5efcd44cf720b2579736854de7cfd370c8ae5602aa59e97cbf5b3fe05f17b7 | Python | 3,487 | 108 | """Predefined units and system names."""
from openmm import unit
from openmmtools.constants import kB
### define units
distance_unit = unit.angstrom
time_unit = unit.femtoseconds
speed_unit = distance_unit / time_unit
# constants
stepsize = 1 * time_unit
collision_rate = 1 / unit.picosecond
temperature = 300 * unit... |
ea21ac08169f8e3850f5d405e988385c92525123be0383dfdb043f147e457cd5 | Python | 3,487 | 101 | """TLS utilities shared across Ray libraries (e.g. Serve)."""
import datetime
import os
import socket
from typing import Tuple
from ray._common.network_utils import (
get_localhost_ip,
node_ip_address_from_perspective,
)
def generate_self_signed_tls_certs() -> Tuple[str, str]:
"""Create self-signed key/... |
641b84a4e85009fb07297c757bcce0c8d97c962ab24f5b63f7e761b3643e4494 | Python | 3,488 | 85 | from abc import ABC, abstractmethod
from typing import Generic
import pyarrow as pa
from ray.data._internal.datasource_v2 import InputSplit
from ray.data._internal.datasource_v2.interfaces.reader import Reader
from ray.util.annotations import DeveloperAPI
@DeveloperAPI
class Scanner(ABC, Generic[InputSplit]):
"... |
a74253952ae63d5c6713bed3c0bca1842180aa670056f6393320b9ff1e3677ed | Python | 3,490 | 144 | import os
import sys
import time
import errno
import time
import timeit
import numpy as np
from numba import jit
import warnings
warnings.simplefilter("ignore")
@jit(nopython=False)
def VEP2Dmodel_sensor(params, constants, init_conditions, SC, Gain, dt, ts):
nt=ts.shape[0]
nn=SC.shape[0]
ns=Gain.sha... |
f46625665e9b2d8faa2e447fa93669523fb8606c1f03bb5d3bb6ed957cc42547 | Python | 3,490 | 90 | import torch.nn as nn
import torch
from torchvision import models
def create_conv2d_block(in_channels, kernel_size, n_filter, dilated_rate=1, batch_norm=True):
# padding formula https://discuss.pytorch.org/t/how-to-keep-the-shape-of-input-and-output-same-when-dilation-conv/14338
"""
o = output
p = pad... |
77508f7dd91b30d9bbdbb55c533faa499c97f4b24743b3640d9ce0223423114e | Python | 3,491 | 145 | import numpy as np
import sympy as sp
from goodness_of_fit import goodness_of_fit
def fitting_solving(data, tmp_min, tmp_max):
# Two types
sorts = ['concrete', 'football']
# The degree of polynomial fitting.
fitting_num = 5
R_thres = 0.98
with open('results_all', 'a') as datatmp:
... |
7cba2ac3676c788e0de9af4cdbf8763b6cde29d01fe8e7c0a15dc450f8a33d2d | Python | 3,492 | 102 | from __future__ import division
import scipy as s
import numpy as np
from .. import gpu_utils
from ..gp_utils import covar_to_corr
from .variational_nodes import *
from ..gp_utils import *
# TODO: for large number of groups avoid constructing Kmat if spectral decomp and only save x at the end (getParameters in SigmaN... |
345f8999a80e75fe850d62ee075b4ad3127ed72641ca7dcde4a425dca85d8fc3 | Python | 3,493 | 40 | # -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: i_input_file.proto
"""Generated protocol buffer code."""
from google.protobuf.internal import builder as _builder
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_... |
b191eacd742b0dd1366568f0af7387561a76408d717fe7bec78c796f3ccfea2d | Python | 3,494 | 129 | from abc import ABCMeta, abstractmethod
import torch
from pfrl.agents.dqn import DQN
from pfrl.utils.recurrent import pack_and_forward
class AbstractDPP(DQN, metaclass=ABCMeta):
"""Dynamic Policy Programming.
See: https://arxiv.org/abs/1004.2027.
"""
@abstractmethod
def _l_operator(self, qout)... |
bb84a966f713006c0d1a678165db29cd275b6279b950c4b535340d28a178ab58 | Python | 3,496 | 105 | #!/usr/bin/env python
from __future__ import print_function
import argparse
import glob
import gzip
import math
import numpy as np
import sys
def parse_args():
parser = argparse.ArgumentParser("Makes plots and reports details of vcfeval output")
parser.add_argument('--input_bed', '-i', dest='input_bed', req... |
759c7082ad205da3e220757a6cc26f5f4d33993ce887b535ae18d423b4fcc051 | Python | 3,497 | 114 | # Copyright 2023 Google LLC
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
8c1d130a451e11526181524c46ef688dcb95b92bdf204ef57bf7bba8fa1e1044 | Python | 3,497 | 91 | import os
import sys
project_root = '/ccb/cybertron/khchao/splam-analysis-results/'
input_file_dir = f'{project_root}train/results/ALL_RefSeq/BAM_REF_Intersection/'
output_dir = f'{project_root}train/results/ALL_RefSeq/INPUTS/'
def main():
SEQ_LEN = sys.argv[1]
HALF_SEQ_LEN = int(SEQ_LEN) // 2
QUATER_SEQ... |
801998984dad46d5c08e07c4531b3016b60eda5f32a0d41c000145317b4a3932 | Python | 3,499 | 108 | #
# CEBRA: Consistent EmBeddings of high-dimensional Recordings using Auxiliary variables
# © Mackenzie W. Mathis & Steffen Schneider (v0.4.0+)
# Source code:
# https://github.com/AdaptiveMotorControlLab/CEBRA
#
# Please see LICENSE.md for the full license document:
# https://github.com/AdaptiveMotorControlLab/CEBRA/bl... |
7b4c08404bb13443c8042c3fa1e8ef3050cc0ec08a0beb0e316c14d3863c5da7 | Python | 3,500 | 96 | from typing import Any, List, Optional
import numpy as np
from pyspark.sql import DataFrame
from data_profiling.config import Settings
from data_profiling.visualisation.missing import (
plot_missing_bar,
plot_missing_heatmap,
plot_missing_matrix,
)
class MissingnoBarSparkPatch:
"""
Technical Deb... |
fbcd866830f0628e1351cf8408a4467c02922571d2b92474b462d7627663303f | Python | 3,500 | 92 | import os
import re
import json
import torch
project_root = '/ccb/cybertron/khchao/splam-analysis-results/'
output_dir = f'{project_root}train/results/ALL_RefSeq/REF_junctions/'
def chr_name_convert():
f_chrs = open(f'{project_root}/Dataset/Refseq_2_UCSU_chromosome_names.tsv', "r")
lines = f_chrs.read().sp... |
5b70896430a93a46af8fc87fe9adb8781f759b181a99f06e5b1b5ef40a1d88d9 | Python | 3,501 | 85 | import os
import json
import torch
import pandas as pd
from .data import prepare_test_loader
from .model import GeneformerMultiTask
def evaluate_test_dataset(model, device, test_loader, cell_id_mapping, config):
task_pred_labels = {task_name: [] for task_name in config["task_names"]}
task_pred_probs = {task_n... |
7b1c2b7f76b08c84fd42e673efeeaea2b13166a1731bc7886bd767b0bf5c462d | Python | 3,501 | 84 | import unittest
from neuron_morphology.morphology_builder import MorphologyBuilder
from neuron_morphology.feature_extractor.feature_extractor import FeatureExtractor
from neuron_morphology.feature_extractor.data import Data
from neuron_morphology.feature_extractor.marked_feature import (
specialize
)
from neuron_m... |
d529f9b51140e3cb192c22a584b56326888ed1d65f460863e40bfbc7b3c3967d | Python | 3,502 | 129 | from typing import Dict, Optional, List, Any
import logging
import copy as cp
import numpy as np
from scipy.interpolate import interp2d
import xarray as xr
from argschema.argschema_parser import ArgSchemaParser
from neuron_morphology.transforms.upright_angle._schemas import (
InputParameters, OutputParameters)
f... |
a5261f8c44ea709840c64df873c3e8e5ef1b2708af8ab8b3d2d5d90f90c8f0d0 | Python | 3,503 | 99 | # Ultralytics YOLO 🚀, GPL-3.0 license
import torch
import torch.nn as nn
import torch.nn.functional as F
from .metrics import bbox_iou
from .tal import bbox2dist
def wasserstein_loss(pred, target, eps=1e-7, mode='exp', gamma=1, constant=12.8):
center1 = (pred[:, :2] + pred[:, 2:]) / 2
center2 = (target[:,... |
190a604a1c9ff00766b3d8c1828521325400804fe21628bd2e25328ec012fd60 | Python | 3,505 | 113 | from pathlib import Path
from typing import Literal
import math
import pickle
import json
import matplotlib.pyplot as plt
import argparse
import logging
import pandas as pd
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.utils import ModelEma
from timm.loss import Label... |
4861612a4bdd35cc89ab78010bf16a387c897835d51f8d9f4bfe60a5143387c3 | Python | 3,505 | 112 | import tensorflow as tf
from tensorflow.keras import backend as K
import os, sys
import matplotlib.pyplot as plt
from utils import *
import gc
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import matplotlib.pyplot as plt; plt.rcdefaults()
from keras.models import load_model
from pkg_re... |
7a360152f4e209b1dd60fa9295607a26a00e2ca9dedb730b0245d67adc74f0ae | Python | 3,505 | 101 | import numpy as np
import scipy.sparse as sp
import torch
import torch.nn as nn
import torch.nn.functional as F
from ..utils import to_sparse_tensor
__all__ = [
'GCN',
'GraphConvolution',
]
def sparse_or_dense_dropout(x, p=0.5, training=True):
if isinstance(x, (torch.sparse.FloatTensor, torch.cuda.spars... |
93fb1a7ea17dbb306f644c9da61f8dc29b131427dbbd6a990954bad6fbb1b2de | Python | 3,507 | 97 |
def draw_colormap(position,
length,
radius,
material,
color_list,
resolution,
options):
# Add the maximum value string
maximum_value_string = create_text_object(text_string=bpy.context.scene.NMV_M... |
0fd97459fbb4cfe83b6cf21b098ac05702d4660c8823b7c0a4db44cf1e95a828 | Python | 3,508 | 90 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
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