sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
86483428af7e77e6c4f532b12f5615fb4ef2a04e9db6fadf9f3cd5eddced5b21 | Python | 11,634 | 332 | """Mendelian randomization for ``ov.genetics`` — TwoSampleMR backend.
Wraps the standalone :mod:`pytwosamplemr` package. :func:`mendelian_randomization`
is a single dispatcher over the full library of two-sample MR
estimators (IVW, MR-Egger, weighted median, mode-based, maximum
likelihood, dIVW, contamination mixture,... |
a024854370945466376b4c5449ae7948d679bba813423b67dd58ded4a925b499 | Python | 11,635 | 320 | import vamb
import numpy as np
import os
import itertools
from typing import NewType, Union, Optional
from collections.abc import Sequence, Mapping, Iterable
from pathlib import Path
import argparse
import json
ContigId = NewType("ContigId", int)
BinId = NewType("BinId", int)
def main(
# Path to output cluster... |
a861802877dce4e391b9f9c1e8250e4f73bec3c2b138dda2c28d44f7a8165b32 | Python | 11,637 | 356 | """
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.
Custom Wigner D computation kernels for l=1, 2, 3, 4.
This module contains specialized, optimized kernels for computing Wigner D
matrices for ... |
520697d78722b6138a872e300b6716083efb832b71e5b2b11add9c9cd42a8cfd | Python | 11,638 | 302 | #!/usr/bin/env python
#
# This script is used to generate a figure showing the correspondence between spinal levels and vertebrae levels.
# The script also computes a distance from the PMJ to the middle of each spinal level. Results are saved to
# a CSV file.
#
# Usage:
# python generate_figure_rootlets_vertebrae_s... |
e3d6950450998369c85efbfcf582136aa189d9d1d4f7a1fd8aef1b50a2136089 | Python | 11,643 | 283 | import pdb
import torch
import torch.nn as nn
from STPN.Scripts.STPLayers import (
FastWeights,
STPNr,
STPNF, STPNBase,
HebbFF
)
from torch import Tensor, no_grad
from STPN.Scripts import utils
"""
Networks for Maze are descirbed in Maze/Scripts/maze_nets.py , instead of here
"""
class SimpleNetSTP... |
06714172db27a7b6fbc5eaa6475b9bebec7600a4227a722695ea2b08e98ea785 | Python | 11,659 | 381 | #
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
import enum
import os.path
import shutil
from library import *
from gemm_operation import *
from conv2d_operation import *
from conv3d_operation import *
##################################################################... |
0d54df99ee4d41e3e40ac7d7cfcd39f641ab813c2b29bfa3c2d444f5dccd43d6 | Python | 11,659 | 313 | """
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 os
import typing
from pathlib import Path
from typing import Any, Literal
import torch
from fa... |
4dd60cd6ce75047a5c7fc8b06f644a2da5070bc5cbca3c95ef3f5e472473692d | Python | 11,660 | 309 | import numpy as np
from numba import jit
import pandas as pd
from math import factorial
from scipy import signal
def nanzscore(array, axis=0):
return (array - np.nanmean(array, axis=axis))/np.nanstd(array, axis=axis)
@jit(nopython=True)
def get_ROI_coords_3D_planewise(stack, rois: np.ndarray):
""" A functio... |
088a041c029d681891b2574cdfb223c4a4cc05196c0407504a114ee327ceb580 | Python | 11,661 | 377 | """Unit tests for the GPU profiler manager.
All GPU and dynolog dependencies are mocked out.
This test just verifies that commands are launched correctly and that
validations are correctly performed.
"""
import asyncio
import sys
from pathlib import Path
from unittest.mock import AsyncMock, MagicMock
import pytest
... |
4bea2da210cd9a2fc5527d8eb328804139eff3521657cbba17d909ea7641cdb5 | Python | 11,661 | 330 | """
Custom Norm operators to enable sync BN, regular BN and for weight initialization
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from network.nn.mynn import Upsample, Norm2d
class ChannelReasonModule(nn.Module):
"""
Spatial CGNL block with dot production kernel for image classfica... |
9cb95d7d9488caf56bca77618511acc174902e804bd10493f2568e54dd245cfb | Python | 11,664 | 295 | ####################################################################################################
# Copyright (c) 2025, Open Brain Institute
# Author(s): Marwan Abdellah <marwan.abdellah@openbraininstitute.org>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is ... |
88d92528f779abd9e72af70e5666f8a87bbef6df1beaa7d0390e0f791b057fc2 | Python | 11,665 | 280 | # Copyright (c) 2017-present, Facebook, 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 or agreed... |
6175bbc8aea9f14abda1986be4deefe22e4c8dfb61a23919ff5b147eb7c58347 | Python | 11,669 | 323 | #!/usr/bin/python3
# System imports
import os
import re
import numpy
import seaborn
import pandas
import argparse
import matplotlib
import matplotlib.pyplot as pyplot
import matplotlib.font_manager as font_manager
import matplotlib.ticker
import colorsys
from matplotlib.ticker import PercentFormatter
from PIL import I... |
696191d58cc0f70428c0d64d4f87246f10d87fb79342292e06e681a9f71c28dd | Python | 11,675 | 309 | """
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.
Structure Conversion, Manipulation, and Validation Utilities for FastCSP
"""
from __future__ import annotations
import hashlib
from collectio... |
4e48b30818a371e67fea8556ff72e0139feb9801fa4c66e522128440fd1a3a4e | Python | 11,681 | 334 | # 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 logging
import torch
import torch.nn as nn
import torch.nn.functional as F
from unicore import utils
from unicore.models import BaseUnicoreModel, register_mo... |
9392be84df91aa822fd846ad70b5c9b387923c62ce80820df20544799d70ba47 | Python | 11,682 | 334 | import argparse
import logging
import os
import platform
import signal
import sys
import traceback
from typing import Optional, Set
import ray
import ray._private.ray_constants as ray_constants
import ray.dashboard.consts as dashboard_consts
import ray.dashboard.head as dashboard_head
import ray.dashboard.utils as das... |
20dcb5126335170b8e541e077af1492cc6a8ebb8d5098976bec51dfa4ad2384e | Python | 11,687 | 271 | """Weighted Gene Co-expression Network Analysis registry shim.
The full implementation lives in :mod:`omicverse.external.PyWGCNA` (vendored
from the upstream PyWGCNA package). The registry scanner intentionally
ignores everything under ``external/`` to keep third-party code out of the
public API surface, so a class re... |
155b2bd9cc1fedc84bebf4324c413c601442773e7d088d6d0f3d75013302d0ca | Python | 11,689 | 362 | # AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/00_core.ipynb.
# %% auto 0
__all__ = ['logger', 'formatter', 'console_handler', 'scannot', 'preprocess_data', 'annotate_level1', 'annotate_level2',
'get_latent_representation', 'save_results', 'annotate_levels', 'annotate_deeper_levels', 'annotate_level',
... |
c29ec01a111067a6b80098d84aa0942e03922ffa85a8088266a1393501cc61ce | Python | 11,690 | 251 | import torch
from torch import nn
eps = 1e-8
class IRCN(nn.Module):
def __init__(self, channel):
super().__init__()
self.gammaRow = torch.nn.Parameter(torch.ones((1, channel, 1, 1)))
self.betaRow = torch.nn.Parameter(torch.zeros((1, channel, 1, 1)))
self.gammaCol = ... |
3f9ec97e108e41a484d1e49a85a954b6a9efe67b7acc2ca11aaf5888f3fd35fb | Python | 11,691 | 334 | import json
import random
import math
from random import sample
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import cm
from matplotlib.colors import Normalize
from typing import List, Dict, Set, Tuple
from scipy.stats import gaussian_kde
class Experiment:
def __init__(self, ... |
8805dae37d93b5423e0cd3f18ba67deb7bd68c9504cae3295add79df3d8fbb9a | Python | 11,699 | 253 | import argparse
import pickle
from typing import List, Iterator
import numpy as np
import torch
import lib.data_utils.data_util as du
import lib.data_utils.dynamic_data_util as ddu
import lib.dataset_config_parser.dataset_config_parser as dcp
from denoise_inverse_alg.hqs_alg import HQS_ParameterizedSolveFn, BatchPara... |
d3b1c48e28351b4a48cb5eb0ca37c356f2b210c2d59f8c057bd979ee71142e00 | Python | 11,700 | 358 | # Copyright 2021 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, sof... |
674fd7ae66c0b308cf6b3d1f06df4c6dc4c4338fcbd44d9d8cc62a2b29f8f747 | Python | 11,702 | 313 | """
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.
Tests: CPU-only tests for the calculate runners (ElasticityRunner,
SinglePointRunner, RelaxationRunner) and their checkpoint /
... |
9f95b2851ea072234b5dbdc571c82097b5063b7b023d36e44b2365b96126b123 | Python | 11,707 | 310 | """
This script makes a visual comparison of the validation pseudo dice across epochs for multiple nnUNet training logs.
The script reads the log files, extracts the epoch number and validation pseudo dice, and plots them.
NOTE: This script is a modified version of
https://github.com/ivadomed/utilities/blob/main/train... |
f992f6a6d368f5174474f40e0b73ec070a83d207c172b2bf680c483ab4bb84d1 | Python | 11,708 | 321 | # -*- coding: utf-8 -*-
"""
Project: CrowdingNumerosityGit
Creator: Miao
Create time: 2021-04-05 23:17
IDE: PyCharm
Introduction:
"""
from math import atan2, pi
from matplotlib import pyplot as plt
from matplotlib.patches import Ellipse
from scipy.spatial import distance
def drawEllipse_full(e_posi, extra_posi, ka,... |
6ad6a9cf7ad37ea8283e9316be2b1cd1d03969c6d10c7d2cb6791ce43dcb5f1d | Python | 11,713 | 330 | """Tests for the decision tree modularization"""
import glob
import json
import os
import os.path as op
import pandas as pd
import pytest
from tedana.selection import component_selector
THIS_DIR = os.path.dirname(os.path.abspath(__file__))
# ----------------------------------------------------------------------
# F... |
a4a0d2dbe996fa4d7c2d3f9e4899dbc32794a030fc4b10423ea81c2f702de150 | Python | 11,717 | 297 | import torch
import random
from sklearn.metrics import accuracy_score, roc_auc_score, confusion_matrix, auc, precision_recall_curve, precision_score
import matplotlib.pyplot as plt
from torch.utils.data import DataLoader, Dataset
import calibration as cal
import logging
import yaml
import os
import pandas as pd
import ... |
58572d5d941796be501f7bf36365e6f8a7a49dea7f2800035b73a1431614c1fc | Python | 11,718 | 249 | """Keep the ``doc_api`` conditional-testing rule in sync with the API-page set.
The ``doc_api`` tag in ``.buildkite/test.rules.txt`` selects the API-consistency
CI checks ("doc: check API annotations" and "doc: check API doc consistency" in
``.buildkite/doc.rayci.yml``). It covers two populations: the API reference
pa... |
4e2e7a7810f042708f3d4367cd1242d0d2414acdaca785e374c629bbd09a1c54 | Python | 11,724 | 226 | from time import time
from batchgenerators.augmentations.crop_and_pad_augmentations import crop
from batchgenerators.dataloading.multi_threaded_augmenter import MultiThreadedAugmenter
from batchgenerators.examples.brats2017.config import brats_preprocessed_folder, num_threads_for_brats_example
from batchgenerators.tran... |
57f6528942e4e3e13b6b52b9f379759859d6fd93010af7a250abe298d76a19ac | Python | 11,728 | 314 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.optim import Adam
import math
import numpy as np
from utils import *
from lookahead import Lookahead
class SelfAttention(nn.Module):
def __init__(self, hid_dim, n_heads, dropout, device):
super().__init__()
self.hid_d... |
e54992e926b6f51ea2aaefda09aad00e2af758476ce782156957b2deb7273362 | Python | 11,728 | 345 | import json
from datetime import datetime
from pathlib import Path
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import pandas as pd
import torch
from fastai.vision.learner import load_learner
from sklearn.model_selection import StratifiedKFold, train_test_split
from sklearn.preprocessing ... |
0c2f571d431dd760f481e1744b5e21dc8bd45f6a68ec5f0f6a65c8bdb111d178 | Python | 11,731 | 304 | from batchgenerators.utilities.file_and_folder_operations import join
from typing import Any
from pathlib import Path
import shutil
import os
try:
import wandb
except ImportError:
wandb = None
def get_cluster_job_id():
job_id = None
if "LSB_JOBID" in os.environ:
job_id = os.environ["LSB_JOBID... |
6e0e2029cb88b9a4caf9f4c052028bfb5ff05e31028ebd395f92b73e78f0324b | Python | 11,731 | 283 | import os
import numpy as np
import pandas as pd
import pickle
from tqdm import tqdm
from .batch import make_batch_masks
class Buckets:
def __init__(self, buckets, masks=None, seed=0):
"""
A class containing multiple set of multiple features
Parameters
----------
buckets: l... |
06e2fb90212bcc960c4d61337c9cf8c8866e408560800301d36961437c7b53ca | Python | 11,732 | 329 | import torch
import copy
#from timm.scheduler.cosine_lr import CosineLRScheduler
#from timm.scheduler.multistep_lr import MultiStepLRScheduler
import inspect
import math
from bisect import bisect
#import torch.optim.lr_scheduler as lr_scheduler
def multiply(obj, num):
if isinstance(obj, list):
for i in ra... |
1785062aca64ae37299262505814330e5f6e70fd637d8cfc4e43f87d8b712479 | Python | 11,733 | 293 | import numpy as np
import rlexp.utils as utils
import exputils as eu
import exputils.data.logging as log
import torch
from ..approximation import NEC, ExperienceReplay
class NECAgent:
@staticmethod
def default_config():
return eu.AttrDict(
initial_epsilon = 1,
final_epsilon = ... |
cd9737107715089edec5b960981ce2a8ca868467a5be8feb4cf78946c57c6123 | Python | 11,736 | 259 | # Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
"""Client and server classes corresponding to protobuf-defined services."""
import grpc
import user_defined_protos_pb2 as user__defined__protos__pb2
class UserDefinedServiceStub(object):
"""Missing associated documentation comment in .proto fi... |
21aa9fab89fef51f0944ed503ec37f35912a018ca1db7163c7f647cef70dff45 | Python | 11,737 | 284 | # 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... |
a413d8b35ede53f9e251f577da3aa932c3895803a553f5569414fddad933c2b5 | Python | 11,742 | 245 | """Real public immune-repertoire (AIRR) datasets for the ``ov.airr`` tutorials.
Each loader downloads a dataset asset from the ``omicverse-data`` GitHub
release (``airr-v1``) on first use, caches it under ``dir``, and returns
it ready for the ``ov.airr`` adaptive-immune-receptor-repertoire workflow
(clonotype calling,... |
f0de4ed44238af736be4cc245075c36265f0d3e6d23c3b7f59bbdf6f57902f29 | Python | 11,742 | 276 | import glob
import os
from itertools import chain
import h5py
import numpy as np
import pytorch3dunet.augment.transforms as transforms
from pytorch3dunet.datasets.utils import get_slice_builder, ConfigDataset, calculate_stats
from pytorch3dunet.unet3d.utils import get_logger
logger = get_logger('HDF5Dataset')
clas... |
0e507163fb3cf5e41b20f25a3ce7c21da6430b6a076a8cf9f8b6b5d712f50aef | Python | 11,744 | 354 | import argparse, os, sys, glob
import cv2
import torch
import numpy as np
from omegaconf import OmegaConf
from PIL import Image
from tqdm import tqdm, trange
from imwatermark import WatermarkEncoder
from itertools import islice
from einops import rearrange
from torchvision.utils import make_grid
import time
from pytorc... |
b04a6d214f50482a330206b443666ab7bdd9f9240ec62e1bcdbbaf3c1bae8dbb | Python | 11,744 | 351 | import itertools
import numpy as np
import torch
from torch import nn
def is_recurrent(layer):
"""Return True iff a given layer is recurrent and supported by PFRL.
Args:
layer (callable): Any callable object.
Returns:
bool: True iff a given layer is recurrent and supported by PFRL.
... |
4e8f01393e7cf82e7e1d560c680c86c54995a2c5fa66fddadd4b19282240a9fb | Python | 11,747 | 338 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""Run every example script in this folder and record what happened.
Each ``NN_*.py`` file is executed, in numeric order, with the Python
... |
3531023b435520c116189a83b855c41be2792b74ec65d0c4ac8e43f101034440 | Python | 11,748 | 365 | import datetime
import os
import warnings
from functools import partial, wraps
from typing import Callable, Sequence, Set
from urllib.parse import urlparse
import filetype
import pandas as pd
import visions
from multimethod import multimethod
from pandas.api import types as pdt
from visions.backends.pandas... |
9933991f1efcbba109b26e8138fe2e3d1ce3f35a552da04d9cf677133d81ede2 | Python | 11,758 | 250 | from argparse import ArgumentParser
import os
import os.path
import skimage
import pathlib
import numpy as np
import scipy as sp
import scipy.signal
import pandas as pd
import tqdm
import cv2
import src.data
import src.metrics
import sak
if __name__ == '__main__':
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ LOAD INPUTS ~... |
4bba48e2d5767008e96b498df7250baa7b976a3f525481859cb3216d1f4161ad | Python | 11,766 | 293 | import os
import torch
import torch.nn as nn
import torch.backends.cudnn as cudnn
import torch.utils.data as Data
import random
import numpy as np
import pandas as pd
from collections import defaultdict
import warnings
warnings.filterwarnings('ignore')
import numpy as np
import random
import torch
from tqdm.auto impor... |
56a880e6a190f7d5ece5aa1b876287e12e5c11b4eac251a8542a4dba47e8f4f9 | Python | 11,766 | 290 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# -------------------------------------------------------------------------
# Created By : Kangjoo Lee (kangjoo.lee@yale.edu)
# Last Updated: 08/06/2024
# -------------------------------------------------------------------------
# ========================================... |
aa242d943cfef6a3f4b19065ffd860b86c17333101de4deef36e558fc405d325 | Python | 11,768 | 370 | """
Utility functions for plotting in Palantir
"""
from typing import Optional, Union, Dict, List, Tuple, Any, Callable
import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.colors import Normalize
from matplotlib.axes import Axes
from mpl_toolkits.axes_grid1 import m... |
9dae94b83ebbe3ffff6fe2daddaf480bff4d183ab6fcdc76c844d89c1de462cf | Python | 11,773 | 343 | import pdb,sys,os
import anndata
import scanpy as sc
import argparse
import copy
import numpy as np
import faiss
import scipy
from sklearn.decomposition import PCA
### evaluation functions
def faiss_knn(query:np.array, x:np.array, n_neighbors:int=1) -> np.array:
n_samples = x.shape[0]
n_features = x... |
3af6dc7f0154f843fdf3c23a869330bc4ac6316e6e13c7fbd6fd6d07939e3ae0 | Python | 11,775 | 273 | import requests
from .__config import base_url
from .__aux_funcs import process_response
def fetch_clinical_data(attribute_ids, entity_study_ids, clinical_data_type="SAMPLE", projection="SUMMARY", ret_format="WIDE"):
"""
Fetch clinical data by patient IDs or sample IDs (all studies) from cBioPortal. \n
:pa... |
061b50694e19622babe05c922475e5a0a87d43ca4a6ff4de24f11c3f033edb8e | Python | 11,781 | 243 | import sys
import numpy as np
from threshold_frame import threshold_frame
from scipy.spatial.distance import pdist, squareform
from scipy.cluster.hierarchy import fcluster, linkage
from scipy import sparse
import multiprocessing as mp
sys.path.insert(1, '../SUNS2') # the path containing "suns" folder
from suns.PostPro... |
6eb3d03817f7eb337eeb16a0e9eb8986b977fd0423622f4256bd68a2a29fa918 | Python | 11,787 | 323 | # Copyright 2021 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, sof... |
f44a2e92daedf28bc294c2d2328191df7793f12315a3d2c84c9390688aea57d8 | Python | 11,787 | 359 | # --------------------------------------------------------
# Swin Transformer
# Copyright (c) 2021 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ze Liu
# --------------------------------------------------------'
import os
import torch
import yaml
from yacs.config import CfgNode as C... |
62da22c05f95ed5f678afa83fd0a78746f9b8e0df04ad466a9cdb994bd9e7895 | Python | 11,790 | 315 | import collections
import copy
from logging import getLogger
import numpy as np
import torch
from torch import nn
from torch.nn import functional as F
from pfrl.agent import AttributeSavingMixin, BatchAgent
from pfrl.replay_buffer import ReplayUpdater, batch_experiences
from pfrl.utils.batch_states import batch_state... |
c3cc215d2e43dd4ccffd2211eb018004e4f14aaaf4c6a28cfd439b379a7ca521 | Python | 11,793 | 371 | r"""
Align metrics
"""
from typing import List, Optional, Union
from collections import Counter
import numpy as np
import pandas as pd
from scipy.spatial.distance import euclidean
from scipy import sparse
import torch
import torch.nn.functional as F
import torch_geometric as pyg
from anndata import AnnData
from .mode... |
6875c24baa732a4de5bb18dcf6268049d53191e80f146e98c5b8ca71f9429802 | Python | 11,795 | 262 | import os, sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import torch
import torch.nn as nn
# from TEST_dataset import *
from splam_dataset_Chromsome import *
from SPLAM import *
# from splam_utils import *
import matplotlib.pyplot as plt; plt.rcdefaults()
import numpy as np
from tqd... |
9bbc95af49b0a1e4e29684292b87bf187980a705e67381c5ba2c8516c405bc61 | Python | 11,795 | 294 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 19 11:52:05 2022
@author: sam
"""
import keras
from keras import backend as K
from dualChannelRNN import rnnCell_dualNet_ as rnnCell_
import tensorflow as tf
import numpy as np
class zeroConstraint(keras.constraints.Constraint):
"""Constrains w... |
a880d8ca2f7c6fdd9b697c669db8682e93b5da889246b08b8935d83dfb485cdc | Python | 11,806 | 267 | # Definition of several convolutional modules
# Normal convolution, Residual, ResNeXt, Inception, Amoeba...
# From [this link](https://towardsdatascience.com/history-of-convolutional-blocks-in-simple-code-96a7ddceac0c).
import numpy as np
import keras
import keras.layers
import keras.backend
import keras.backend as K
... |
be58214b60c0f4f7a5eda45792ccdc235b9bf95263ad140ec7cf3837d86c4861 | Python | 11,807 | 325 | # Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under th... |
19130d726a7e25e1fd7ff367c668c69faa7c05b1563290f7e40b0bed9a73a852 | Python | 11,809 | 392 | """Visualization functions for metabolism scores."""
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
from typing import Optional, Union, List
import anndata
import logging
logger = logging.getLogger(__name__)
def _zissou1_cmap():
colors = ["#3B9AB2", "#... |
0be2e751e0bb69784fc12a2c9dcd0c157ab6ba10abb217e127953678c162e7ed | Python | 11,810 | 337 | # coding=utf-8
# Copyright 2023 HuggingFace 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 or ag... |
cae6d7f341fbfa3613a0876eead25fe20447cb5125dbf9540769859daedb65eb | Python | 11,810 | 400 |
# coding: utf-8
# # Table of Contents
#
# 1. [Import & Set Up](#import_everything)
# 2. [Load in data](#load_files)
# 3. [Within Pair Correlation](#within_pair_correlation)
# 3. [Center of Mass](#c_o_m)
# 1. [distance apart](#distance_apart)
# 2. [error by overlap](#error_by_overlap)
# # Import Stuff
# <a i... |
480fcf58e22bed579de9b6c7c740f1a4d3070c4fc5d9348f175a97f30b3a08f6 | Python | 11,817 | 292 | from typing import Optional
class NullMetric:
"""Mock metric class to be used in case of prometheus_client import error."""
def set(self, *args, **kwargs):
pass
def observe(self, *args, **kwargs):
pass
def inc(self, *args, **kwargs):
pass
def labels(self, *args, **kwarg... |
faa3d7ab669742a1405e21805f0176ee2b83b37a89d311c3b824872946268396 | Python | 11,818 | 302 | """
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 contextlib
import uuid
from concurrent.futures import ThreadPoolExecutor
from functools import c... |
134a661ca3657faa65b87a0677b0771c86870facc7b1443f66aa895df894404e | Python | 11,824 | 321 | # 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... |
c37a01a8a1a6dfaa4f99d748ef6b46dce2d2ee656208dbd02a4a623da2394c2e | Python | 11,828 | 342 | from __future__ import annotations
import contextlib
import operator
import warnings
from functools import wraps
from typing import Iterable, List
import matplotlib.pyplot as plt
import numpy as np
import xarray as xr
def where_xarray(
dataset: xr.Dataset | xr.DataArray,
rtol: float = 1.0e-5,
atol: floa... |
3dfee9b4ce19f1d22d2870a4b2988ac49271834e4ebf23ed9a03f3a9fee8819e | Python | 11,830 | 376 | # These classes are the tensorflow counterparts of Minivision's Silent-Face-Anti-Spoofing
# Repo licensed under Apache License 2.0
# Ref: github.com/minivision-ai/Silent-Face-Anti-Spoofing/blob/master/src/model_lib/MiniFASNet.py
# built-in dependencies
from typing import Any, List, Tuple
# project dependencies
from d... |
6236960ed83e59f77be2d8d7e28dccd3d548ccc30c3bc612d9fe1ddd213f8b20 | Python | 11,830 | 207 | import nibabel as nb
import numpy as np
import pandas as pd
from nilearn.plotting import plot_roi
from nilearn.image import threshold_img, math_img, new_img_like
from matplotlib import cm
def interestingrois(model,pairoflabels,mistatlaslabel='../data_in/MIST_122.csv',doubledrois=['L_IPlob']):
labelinf = pd.read_c... |
b89bc4301087c35df454c00af5efd2fc77b7697cf32763ba03a0b10be3434551 | Python | 11,830 | 394 | r"""
Utility functions for data handling and analysis.
This module provides essential utility functions for data I/O, manipulation,
visualization, clustering, and various computational tasks across the omicverse
ecosystem. It serves as the foundation for many higher-level analysis functions.
Data I/O and manipulation... |
b23da948100fe4c6161971deeab2e23e09052cc72d5844de766cc1b72284ee85 | Python | 11,833 | 234 | # Ultralytics YOLO 🚀, GPL-3.0 license
"""
Common modules
"""
from copy import copy
from pathlib import Path
import cv2
import numpy as np
import pandas as pd
import requests
import torch
import torch.nn as nn
from PIL import Image, ImageOps
from torch.cuda import amp
from ultralytics.nn.autobackend import AutoBacke... |
a900f463fbeb874a39bc0e9c1a224e82d63be9419f8b464f04b5d647d3337dd1 | Python | 11,836 | 342 | """Contains custom skorch Dataset and ValidSplit."""
import warnings
from collections.abc import Mapping
from functools import partial
from numbers import Number
import numpy as np
from scipy import sparse
from sklearn.model_selection import ShuffleSplit
from sklearn.model_selection import StratifiedKFold
from sklearn... |
8d7ace1e87c4ed87e247956017dcc87d1d7c39bdc0ec21cd1d0cca4ec64cd90d | Python | 11,837 | 294 | import argparse
import pickle
from collections import namedtuple
from typing import List
import numpy as np
import torch
import tqdm
import lib.data_utils.data_util as du
import lib.data_utils.dynamic_data_util as ddu
import lib.dataset_config_parser.dataset_config_parser as dcp
from convex_optim_base.unconstrained_o... |
f8aedbce55818396edd82e0958ba9ada834314c38d65321f36b54acb0ab18b63 | Python | 11,841 | 324 | from __future__ import annotations
import warnings
from typing import TypeVar
import numpy as np
from numpy.typing import NDArray
from scipy import sparse
from .._optional import normalize_torch_device
SpBase = sparse.spmatrix | sparse.sparray # noqa: TID251
"""Only use when you directly convert it to a known subcl... |
6d2b542b0c4a0aa613f40315e2881a9b37c1d88a4bf0e83dd9a3b3893f6f1fd1 | Python | 11,843 | 278 | import logging
import pathlib
import re
import h5py
import numpy as np
import nir
PATH_TYPE = str | pathlib.Path
logger = logging.getLogger(__name__)
def read_cuba_lif(layer: h5py.Group, shape: tuple[int] | None = None) -> nir.NIRNode:
"""Reads a CUBA LIF layer from a h5py.Group.
TODOs:
- what if the l... |
923e5753697f7cd9f62c4bad54e032cdb302a30f566ce3713ed05b9cc3feeefd | Python | 11,846 | 310 | #
# 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... |
a16f49221b6db611ca4173c2edd85453bbda44b086e7e8a9ddc80188fd7c884c | Python | 11,853 | 336 | import math
import numpy as np
import pytest
import torch
from torch import nn
import sinabs
import sinabs.layers as sl
from sinabs import SNNAnalyzer, SynOpCounter
from sinabs.layers import IAFSqueeze, NeuromorphicReLU
class Model(torch.nn.Sequential):
def __init__(self):
super().__init__(
... |
95147c94a3f754db9ae4c37137e55e3d568dd025549ba28a00120156236d0954 | Python | 11,856 | 324 | from PIL import Image
import numpy as np
from ctypes import *
import ctypes
import copy
import torch
import torch.nn as nn
import torch.nn.functional as F
import os
import cv2
import time
import pdb
import socket
import pickle
import scipy
import scipy.ndimage
import matplotlib.pyplot as plt
from datas... |
c3f38a6d8c043c01abbb262f3612fd293295c517a1e9c814de64ac677bde34ae | Python | 11,861 | 284 | # %%
import math
import os
import random
import shutil
from pathlib import Path
from typing import List, Optional
import torch
import typer
from typer_config import conf_callback_factory
from typing_extensions import Annotated
from .utils.load_function_args_from_yaml_config import (
load_function_args_from_yaml_c... |
c7c563336d5d2ca13b1fe82e45d860665699daf9ad7f6d838675673e2e866bf1 | Python | 11,873 | 342 | from typing import Optional, List
import numpy as np
import torch
import skimage
from monai.config.type_definitions import NdarrayOrTensor, NdarrayTensor
from monai.utils import optional_import
from monai.utils.type_conversion import convert_data_type, convert_to_dst_type
cp, has_cp = optional_import("cupy")
cp_ndarra... |
64783298231867d6901fc811166e02300f88aa638979609695e8e5cb9b321872 | Python | 11,877 | 307 | from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
if TYPE_CHECKING:
import torch
import ray
from ray.dag import (
ClassMethodNode,
DAGNode,
)
from ray.dag.constants import COLLECTIVE_OPERATION_KEY, IS_CLASS_METHOD_OUTPUT_KEY
from ray.experimental.channel import ChannelContext
from ... |
fd151a9121d78e31067af86d152695584f24958db91900e381a003c2437fcf26 | Python | 11,880 | 251 | # Ultralytics YOLO 🚀, GPL-3.0 license
import os
from pathlib import Path
import numpy as np
import torch
from ultralytics.yolo.data import build_dataloader
from ultralytics.yolo.data.dataloaders.v5loader import create_dataloader
from ultralytics.yolo.engine.validator import BaseValidator
from ultralytics.yolo.utils... |
f901e814e2f37659f67a0cbeae528948ee9f6a5378bfc7bd62472099fdac8fda | Python | 11,884 | 301 | # based on https://github.com/gzerveas/mvts_transformer
# with minor adjustments to fit the forecast project
from typing import Optional
import math
import torch
from torch import nn, Tensor
from torch.nn import functional as F # noqa
from torch.nn.modules import (
MultiheadAttention,
Linear,
Dropout,
... |
449f14050d33e5862edaa901b5b9ab2f26cd61141fe5c2b367348b68593dbc31 | Python | 11,888 | 335 | # -*- 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.
#... |
929f878e8fe79f075483d6ba5d2c4733d066c4cd1c6392a5b32beb78e5d0df82 | Python | 11,888 | 330 | from imports import *
from .fixtures import THIS, ungiz
class Base(BaseClass):
modulepath = 'ngs_mapper.bam'
@patch('ngs_mapper.bam.subprocess.Popen')
class TestUnitMergeBam(Base):
functionname = 'mergebams'
samtools_cmd = ['samtools','merge','merged.bam']
def test_input_files(self, popen_mock):
... |
bd5bd1c2892b727f3e54e71486518e3fb1c801127e710df4e7f1693ac28a70dc | Python | 11,890 | 318 | # Ultralytics YOLO 🚀, GPL-3.0 license
import copy
import cv2
import matplotlib.pyplot as plt
import numpy as np
from ultralytics.yolo.utils import LOGGER
class GMC:
def __init__(self, method='sparseOptFlow', downscale=2, verbose=None):
super().__init__()
self.method = method
self.dow... |
e5538498dd2ff0f7b93b421c0be320c27265fbd11c3d9ce78fea2dfdde17c8df | Python | 11,890 | 304 | import logging
from types import ModuleType
from typing import Any, Dict, List, Optional
from ray.autoscaler._private.command_runner import DockerCommandRunner, SSHCommandRunner
from ray.autoscaler.command_runner import CommandRunnerInterface
from ray.util.annotations import DeveloperAPI
logger = logging.getLogger(__... |
b66a8172b7462d66a9963509fdeceb7b68ff3b2f56600fd95587484f2fbff1a1 | Python | 11,893 | 265 | from django.db import models
from django.urls import reverse
CHECKWORTHY_CLASSIFICATION = [
('NF', 'Not factual'),
('FR', 'Factual and relevant'),
('FNR', 'Factual and non-relevant'),
('NA', 'Not applicable'),
('FRC', 'Factual, relevant but complex'),
('OOI', 'Out of news item'),
]
TRUTHFULNES... |
d46aea15093d7fc9d6adab57c5b8f9c6eda9db2f513c25089e925a29f3b7733a | Python | 11,895 | 243 | #!/usr/bin/env python
"""
Complete pipeline for motion correction, source extraction, and deconvolution
of one photon microendoscopic calcium imaging data using the CaImAn package.
The demo demonstrates how to use the params, MotionCorrect and cnmf objects
for processing 1p microendoscopic data. The analysis pipeline ... |
6ef9dd12259852f5c627974593ee442e7cab5e7f047ac1529c69e3f12caaea38 | Python | 11,898 | 358 | from os.path import join
import argparse
from subprocess import Popen, PIPE
import pandas as pd
import numpy as np
import toml
from eval_simulation import eval_simulation
from util import EMB_DIR, OUT_DIR, \
PATH_TO_EXPORT, PATH_TO_GWAS, \
get_out, get_img_dir, get_emb, \
get_aggregate_fn
... |
29d68716dd38e7f78dbdaaf67d6e580d774d044ca100f95dfcbf9ec00802e836 | Python | 11,908 | 296 | ####################################################################################################
# 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... |
4c0d373d62f3a8104f54c1dec44d285bced8c0e2b5efec013c552995c9d4c4d1 | Python | 11,911 | 354 | import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from anndata import AnnData
from typing import Optional, List, Tuple, Dict
from scipy import stats
def shannon_diversity(
adata: AnnData,
groupby: str,
cell_type_key: str,
base: str = 'natural',
calculate_... |
d2d83c7592b623bb42af1935b0ddd2f8b0235750e7502beaf3294455bfeb779e | Python | 11,914 | 297 | #!/usr/bin/env python
# ================================
# @auther: Rongbin Zheng
# @email: Rongbin.Zheng@childrens.harvard.edu
# @date: Oct 2024
# ================================
import os,sys
import time
import pickle as pk
from datetime import datetime
import numpy as np
import pandas as pd
import traceback
from ... |
294d933b7badac16819ca12285b833fc9abe6d4ef1b6df83d31306a9cafc3820 | Python | 11,918 | 343 | """
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
from typing import Literal
import torch
from fairchem.core.common import gp_utils
def get_l_compone... |
a84fa3045af145f58107d60c059f3945cacc308192b691cbe4b4f1d690fd1a79 | Python | 11,921 | 261 | import numpy as np
import h5py
import pandas as pd
from src.dataset.batchdataloader import BatchDataloader, EvenSamplingBatchDataloader
from src.dataset.utils import compute_weights_bucketized, check_mutual_exclusive, classes_to_levels
def load_dset_electrolyte(
path_to_csv:str,
path_t... |
7eff344a7a0bd2b7237f37f2df4756aeccad5b9b8a051da77e8857207983669a | Python | 11,922 | 289 | import numpy as np
import os
import glob
import re
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
from scipy.stats import f_oneway, linregress, ttest_ind, ttest_rel
import pingouin as pg
# import statsmodels.api as sm
# from statsmodels.formula.api import ols
import warnings
warnings.filterw... |
ebd04895761c757782d2f14055de69bc7f2e960297dfee7ccd81a20675cf7412 | Python | 11,923 | 306 | # coding=utf-8
# Copyright 2023 HuggingFace 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 or ag... |
18eab9d2358a7c7c70dbc40ecda4c15f332ca1b366b6fa77cdb7bfae700185a5 | Python | 11,925 | 385 | import random
from typing import Optional
from unittest.mock import MagicMock
import pytest
import ray
from ray import train
from ray.data import DataIterator
from ray.data._internal.execution.interfaces.execution_options import (
ExecutionOptions,
)
from ray.tests.conftest import * # noqa
from ray.train import ... |
17ac1b3a2528bf6aea46d55222952a81f1290d6b1969f2d5c65f659fd5ddc210 | Python | 11,926 | 342 | """SubagentController — spawn and manage subagent conversations.
Extracted from ``smart_agent.py``. A subagent gets its own system prompt,
restricted tool set, independent message history, and — critically — an
isolated ``SubagentRuntime`` that prevents mutable-state leakage between
parent and child turns.
Isolation... |
1d6966053573c540612ee686b1f7094599bfafdbf85657a682d0568ea5bbb48a | Python | 11,931 | 315 | # VTK-specific tensormaps
import os
import h5py
import numpy as np
import vtk
import vtk.util.numpy_support
from ml4h.TensorMap import TensorMap, Interpretation
from ml4h.defines import MRI_SEGMENTED, MRI_LAX_SEGMENTED, MRI_FRAMES, MRI_PIXEL_WIDTH, MRI_PIXEL_HEIGHT, MRI_SLICE_THICKNESS, MRI_PATIENT_ORIENTATION, MRI_PAT... |
e4de6b5fd4038899a02b356ad59cf60a269ebc075e13d224885fa121ead62637 | Python | 11,933 | 260 | import os, logging
import pandas as pd
from misc.save_files import read_pickle, write_pickle,read_pandas_from_csv
from misc.abb_med_disease import gen_abb_med_disease
def generate_keyword_plotting_files(config: dict, df_publications: pd.DataFrame):
n_gram_list = [index for index in config["NLP"]["n_gram_list"]
... |
5bcc67066802ce721a65f4304d51170810bae038eb1279d7e3a32662fa97d9fc | Python | 11,936 | 361 | import asyncio
import dataclasses
import logging
import os
import re
import traceback
from dataclasses import dataclass
from typing import Any, AsyncIterator, Dict, List, Optional, Tuple, Union
from ray._raylet import RAY_INTERNAL_NAMESPACE_PREFIX, GcsClient
from ray.dashboard.modules.job.common import (
JOB_ID_ME... |
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