sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
80ba258912d40c56d1e4275b22eb0bd714b08a38247702de645e00ceb0b7d71f | Python | 10,537 | 397 | import os
import sys
import warnings
import torch
import pickle
import numpy as np
from itertools import product
from scipy.stats import sem
from torch.nn.functional import smooth_l1_loss
from copy import deepcopy
from scipy.linalg import qr
eps = np.finfo(np.float32).eps.item()
def is_even(number):
if number %... |
331d6b434b8ef370a603ad35893009afc84402417078c4f63b5707d4ae1dfd8e | Python | 10,545 | 239 | import os
import numpy as np
import pandas as pd
import scipy.sparse as sparse
from lib5c.util.system import check_outdir
from lib5c.util.statistics import adjust_pvalues
from hic3defdr.util.printing import eprint
from hic3defdr.util.clusters import load_clusters
from hic3defdr.util.simulation import simulate
from h... |
37d7a19c064b410cda63bad5a7cbce3c8d7f88c5d8d16bd889437087267f6f7f | Python | 10,552 | 291 | """
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: Inference-performance regression check — measures throughput
(atoms/sec) on a bulk-MgO supercell for each pretrained
mo... |
f8709b40d33fcd94638d894648c797933155eec46fa1319cce65c9bbbb8c1448 | Python | 10,558 | 293 | """
Adapter for AnnData-stateful functions.
Handles tools that require ``adata_id`` and typically mutate the dataset
in place. Records state changes (produced keys) after execution.
"""
from __future__ import annotations
import json
import tempfile
from typing import Any, Dict, List, Optional, Set
from .base impor... |
11f02913a901eebcd40cf4ced5b89b3e20cb0bb771c3f5839d72e65904b38a64 | Python | 10,565 | 213 | #!/usr/bin/env python3
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from t5x import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pipelines.spectrogr... |
2d761b727874f5e42e7edcc688126c007dbb624de9a4f39b796e19fd8c1cb7fa | Python | 10,570 | 244 | from __future__ import annotations
import warnings
from typing import TYPE_CHECKING
from datetime import datetime
from packaging.version import Version
from scanpy import settings
from ._compat import old_positionals
from ._scale import raise_not_implemented_error_if_backed_type
from ._neighbors import _choose_repre... |
5c520d66fa3230c70bd875e47c02a67f2a7b273c9d8b4f4a445c5ddf22dfe1e4 | Python | 10,573 | 274 | import os
import pickle
import pandas as pd
import numpy as np
import nibabel as nib
import pcntoolkit as ptk
from pcntoolkit.dataio.fileio import load as ptkload
from pcntoolkit.dataio.fileio import save as ptksave
from pcntoolkit.dataio.fileio import save_nifti, load_nifti
from pcntoolkit.normative import predict, e... |
996449ee17f9b841a32b2ffdd8f17103892a663c521c0f22dc517d4a5a961a27 | Python | 10,575 | 245 | # import sys
# sys.path.append('..')
import pandas as pd
import torch
import json
import toml
import argparse
import sys
import os
import monai
import nibabel as nib
from data.dataset_csv import CSVDataset
from adrd.model import ADRDModel
from tqdm import tqdm
from collections import defaultdict
from icecream import i... |
c2ad2d3bd6da9a26222a3404f8fd6e9570185f5218badbea1898191249b096c8 | Python | 10,587 | 266 | """
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 argparse
import os
import pickle
import omegaconf
import torch
from fairchem.core.scripts.migr... |
98d0dbd1cd7aa133b3a2d6ca9e2c8f7fd5859eea5a7ce2e6350c64db384f0640 | Python | 10,609 | 225 | import os
import pyvips
import sklearn
import torch
import numpy as np
import datetime
import cv2
import sklearn.metrics
from timeit import default_timer as timer
import json
import matplotlib
matplotlib.use('Agg')
from matplotlib import pyplot as plt
import glob
from torchsummary import summary
impo... |
175a45aaa4b71692fb4a27cd326eb1a0d2ab4c44f9584900dae4933f1516cf79 | Python | 10,610 | 230 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Dec 6 16:08:47 2021
@author: sam
"""
import math
import numpy as np
import h5py
import matplotlib.pyplot as plt
import scipy
import tensorflow as tf
from tensorflow.python.framework import ops
import pickle
import keras
from keras import layers
from ke... |
c55f575b5dbf3b1efee0b2b8689cedeba10d2c72e987b3768d2d819bb9db502f | Python | 10,619 | 316 | # 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, sof... |
0e01e9e7d2838b3f3365756b999dabe4565a8393385860a79213186389b59d24 | Python | 10,622 | 276 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# -------------------------------------------------------------------------
# Created By : Kangjoo Lee (kangjoo.lee@yale.edu)
# Last Updated: 08/06/2024
# -------------------------------------------------------------------------
# ========================================... |
98cb995b38dec8661afba4e7df618befaa2ce884e8e5d9b30850887be5c2797d | Python | 10,623 | 258 | """
Implementation borrowed from transformers package and extended to support multiple prediction heads:
https://github.com/huggingface/transformers/blob/master/src/transformers/models/bert/modeling_bert.py
"""
from typing import Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import BCEWithLog... |
1f9172501185cd0ec32a52b5d5d1ab843289f4bc9c874499174741b38c0f0609 | Python | 10,625 | 278 | # %%
import ast
import inspect
import os
from pathlib import Path
from typing import Optional
import pytorch_lightning as pl
import typer
import torch
from typer_config import conf_callback_factory
from typing import Union, List
from typing_extensions import Annotated
from .utils.dataloader import MultiEpochsDataLoad... |
77a96af0949ecec479e61381b4d482b606eae50f1bb436c2a036c83ed4390c53 | Python | 10,627 | 292 | # 3rd party dependencies
import cv2
import numpy as np
# project dependencies
from deepface import DeepFace
from deepface.commons.logger import Logger
logger = Logger()
detectors = ["opencv", "retinaface"]
def test_standard_analyze():
img = "dataset/img4.jpg"
demography_objs = DeepFace.analyze(img, silent... |
9c93de4f90e586d66b70580ed4e1cf7f11428f19d8edfceeaefa4a59972e2e7a | Python | 10,633 | 345 | """
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.
"""
"""The script used to perform inference for HER"""
from __future__ import annotations
import argparse
import os
import warnings
warnings... |
72135dff344b630d20945209620bd29b15132dbf0bfe61d09a3d4d7518c91404 | Python | 10,634 | 270 | #!/usr/bin/env python
"""
Complete demo pipeline for processing two photon calcium imaging data using the
CaImAn batch algorithm. The processing pipeline included motion correction,
source extraction and deconvolution. The demo shows how to construct the
params, MotionCorrect and cnmf objects and call the relevant fun... |
8d9a1a7a1ea5e1f3f5914e9a5bc498b2355dadd46a1eb4f1a37ba01422faf81d | Python | 10,634 | 251 | """
This script is used to run inference on a single subject using a nnUNetV2 model.
Note: conda environment with nnUNetV2 is required to run this script.
For details how to install nnUNetV2, see:
https://github.com/ivadomed/utilities/blob/main/quick_start_guides/nnU-Net_quick_start_guide.md#installation
Author: Jan ... |
02e4e25e45354d27d2bff7b41244316fb0a6cc42bd7294f867f0b00bd3d4aea2 | Python | 10,635 | 278 | #
# 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... |
bd468d90e3c81d3ac0eac94ee0736c8aad7ec4cf6964d62f31cb0ebec938eb08 | Python | 10,635 | 270 | ####################################################################################################
# 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... |
afed04b1d702bcfa5a2b8ea8fe24aef45e360735a46408f17d95c4ac96011e05 | Python | 10,640 | 324 | #from subprocess import Popen, PIPE
from math import *
#import random
import numpy as np
#from copy import deepcopy
##from types import IntType, ListType, TupleType, StringTypes
#import itertools
import time
#import math
#import argparse
import subprocess
#from load_model import loaded_model
from keras.utils import pad... |
3a9e4bbce6963e38a944bda3f8a87a172def6055c798b7f8a2c7b680a2f5870b | Python | 10,641 | 236 | import torch
import torch.nn as nn
import numpy as np
import scanpy as sc
import anndata as ad
from torch.optim.lr_scheduler import _LRScheduler, ReduceLROnPlateau
from tqdm import tqdm
from copy import deepcopy
from ..utils.eval import downstream_eval, aggregate_eval_results, imputation_eval
from ..utils.data import X... |
fa7e2f5d811eb2cb7980a813d09af89bc1aa586f3be75cf8d1f5332fc1c2e238 | Python | 10,643 | 283 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# -------------------------------------------------------------------------
# Created By : Kangjoo Lee (kangjoo.lee@yale.edu)
# Last Updated: 08/06/2024
# -------------------------------------------------------------------------
# ========================================... |
eddfa9531435b4f5a784a04766980a9e4678cc48663040f348ce6b86534f498e | Python | 10,645 | 281 | # -*- coding: utf-8 -*-
"""
Created on Sun Jun 16 12:04:00 2019
@author: ju-bar
Calculation of 2-dimensional apertures
This code is part of the 'emilys' repository
https://github.com/ju-bar/emilys
published under the GNU General Publishing License, version 3
"""
# %%
from numba import njit, float64 # include compila... |
6ee2b044ed1563843e1fe4efdc0c397be483e07454f9265ba9b50c02b4932cfa | Python | 10,647 | 271 | from matplotlib import pyplot as plt
import numpy as np
import matplotlib.gridspec as gridspec/home/otprat/Documents/Neuroscience/Master/2017/MasterLab/Repos/luminance_analysis
from pylab import *
from scipy import optimize
from pyprind import prog_percent
import numba
from numba import jit
import random
from luminanc... |
4f5c614e72c8b9677fffef6d2800ce1393d3f6883bb7ebd729481f426e4c7fc0 | Python | 10,650 | 298 | r"""Metabolite-Set Enrichment Analysis (MSEA).
Two enrichment flavours, both keyed off KEGG-compound pathway membership:
1. **ORA** (over-representation analysis) — classic Fisher's-exact on
a pre-selected hit list vs the background universe. Fast, no
ranking needed.
2. **GSEA-style** — full ranked-list enrichm... |
e1c7980c5cdf62b21735244c5ebdc3dcf0c73bda9143dc05dac0e707ddf9cffd | Python | 10,650 | 340 | import yaml
from pathlib import Path
from nyumets.transforms.utils import patch_batch, spatial_augment_batch
from monai.inferers import SimpleInferer, SlidingWindowInferer
from nyumets.transforms.utils import (
post_processing_transforms,
cc_processing_transforms,
longitudinal_transforms,
)
from nyumets.m... |
5bf1fd8b6798a63e6845ed0018cb2d54a14bdcb4c1432c70b58c7645d67c6135 | Python | 10,652 | 214 | import pathlib
path = pathlib.Path.cwd()
if path.stem == 'tmb_survival':
cwd = path
else:
cwd = list(path.parents)[::-1][path.parts.index('tmb_survival')]
import sys
sys.path.append(str(cwd))
import pandas as pd
import numpy as np
import pyranges as pr
from tqdm import tqdm
import json
import pickle
import sub... |
040079c9fe184188685c0688eb2833390e9b55d7744d5e37dba721091b036565 | Python | 10,654 | 299 | """
The intention of this script is to easily sync a given MiSeq run path from the sequencer into the :doc:`NGSData <../ngsdata>` structure
You need to ensure that the run directory for the run you want to sync is available and that you know the path to it.
Accessing MiSeq Data
====================
The MiSeq stores ... |
9b72a39087da37b59b3775f0b222d2f27ce6fcc119244600a00f4fb649c7c091 | Python | 10,654 | 274 | """Pure-torch GPU t-SNE — no ``torchdr`` dependency.
Implements Van der Maaten & Hinton's t-SNE KL objective directly:
Q_{ij} = (1 + ‖y_i − y_j‖²)^-1 / Z, Z = Σ_{k≠l} W_{kl}
C = Σ_{ij} P_{ij} · log(P_{ij} / Q_{ij})
What makes this fit on a GPU in a few seconds at 94k cells is:
* ``Z`` is estimat... |
d45975158f205aecf648165aaf070fa700369df8b3fadfcf405e2ac1d4991cff | Python | 10,670 | 365 | # -*- coding: utf-8 -*-
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
#
# import os
# import sys
# sys.path.insert(0, os.path.a... |
6d929a2cbc4d253d32ba007b5962b9f7f46aedde8cefc06942af6272dca20dde | Python | 10,671 | 320 | import asyncio
import sys
import time
import pytest
from ray._common.test_utils import async_wait_for_condition, wait_for_condition
class TestWaitForCondition:
"""Tests for the synchronous wait_for_condition function."""
def test_immediate_true_condition(self):
"""Test that function returns immedia... |
cffbc035379232238829afb301be408e14cb627cea5873eea5504ac3ef37dbd1 | Python | 10,673 | 293 | # Modified from https://github.com/dbolya/tide
# This work is licensed under MIT license.
import os
from collections import OrderedDict
import cv2
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from .datasets import get_tide_path
from .errors impo... |
d22a9349731403ffc61f25dfec2ad8ac183509b1673a245a6149ece965a3bab0 | Python | 10,678 | 344 | import logging
import zipfile
from dataclasses import dataclass
from pathlib import Path
from typing import Callable, Dict, List, Optional, Tuple, Union
import numpy as np
import torch
from PIL import Image
import flyvis
from flyvis.utils.dataset_utils import download_url_to_file
from .rendering.utils import split
... |
22bd9069f38066b58d12264b900d95d41f06b0768ba2c38a95fe60566a581d08 | Python | 10,679 | 293 | import logging
from abc import ABC, abstractmethod
from typing import List, Optional, Tuple
from ray.autoscaler.v2.instance_manager.common import InstanceUtil
from ray.autoscaler.v2.instance_manager.instance_storage import InstanceStorage
from ray.core.generated.instance_manager_pb2 import (
GetInstanceManagerStat... |
f73ebb07d00188ca74c71f45bf181980e402d7fb05b1feb7315e86ee1ab930a0 | Python | 10,683 | 211 | import glob
import json
import matplotlib.pyplot as plt
import numpy as np
from datetime import datetime
from matplotlib.backends.backend_pdf import PdfPages
def convert_to_timestamp(t):
return datetime.strptime(t, '%Y-%m-%dT%H:%M:%SZ').timestamp()
def plot_brainage_convergence(files, metric="mae", show_globa... |
afe33ac2d8c661b019abd7746537fd4db4c04e10c44c10b93dacf26397322c85 | Python | 10,684 | 356 | """
Data structure validators for AnnData objects.
This module provides validators that check for the presence and validity
of required data structures in AnnData objects.
"""
from typing import List, Optional
import numpy as np
from anndata import AnnData
from .data_structures import (
ObsCheckResult,
ObsmC... |
c00bf388ab8f1dcdc1c783670f6abb305dd0e0f4864f12ea04cac04431a6663b | Python | 10,684 | 306 | CODE_DIR = '/home/kelarion/github/'
SAVE_DIR = '/mnt/c/Users/mmall/Documents/uni/columbia/assignment_errors/'
REMOTE_SYNC_SERVER = 'ma3811@motion.rcs.columbia.edu' #must have ssh keys set up
REMOTE_CODE = '/burg/home/ma3811/assignment_errors/'
REMOTE_RESULTS = '/burg/theory/users/ma3811/assignment_errors/'
# REMOTE_SY... |
87e7e9473d687566b59677d8188885f80178af1171135cd8ac1b490f3115fc2d | Python | 10,690 | 275 | import torch
import torch.nn.functional as F
import numpy as np
from torch import Tensor
from typing import Optional
from torch import nn
from ..utils import create_norm
from .transformer import AbstractTrasnformerLayer
class CosformerAttention(nn.Module):
"""
cosformer attention in "cosFormer: Rethinking Sof... |
4e22155d55e26b52947cc096d24a01b5c6379bb9703e62c621c705b9a57b74f7 | Python | 10,699 | 227 | ########################################################
######### Philipp R. Steen #########
######### Jungmann Lab #########
######### Max Planck Institute of Biochemistry #########
######### Ludwig Maximilian University #########
######### 2024 ... |
53d8f1d0ff113a204c81197aa057c45e3ee0743111f1d59a695f9ecd1ff82819 | Python | 10,700 | 304 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Created on Wed Feb 24 18:39:45 2016
@author: Andrea Giovannucci
For explanation consult at https://github.com/agiovann/Constrained_NMF/releases/download/v0.4-alpha/Patch_demo.zip
and https://github.com/agiovann/Constrained_NMF
"""
from __future__ import print_funct... |
2adcb05b647fa55440dc89ea0144d87bc154bfcfcd1de0b54ed920113145fe8e | Python | 10,702 | 278 | """Programmatic entry point for the vendored CAMEX pipeline.
This reproduces the glue found in the upstream CAMEX analysis notebooks
(``analysis/1liver/Integrate_liver_across_4_species.ipynb`` and
``analysis/4cortex_annotation/integration_annotation_in_relatives_distant_species.ipynb``)::
from CAMEX.base import D... |
c1dee058e483fc734a215f7674b680bdd0b5bcc528a2208478596243bf5128ba | Python | 10,702 | 227 | from agent.classifiers.tr_ffnn_ensemble_classifier import tr_ffnn
from agent.classifiers.fd_naive_item_classifier import fd_naive_classifier
from agent.classifiers.data.tr_ffnn_dataset_mgmt import get_datasets as get_fc_tr_ffnn_datasets
from agent.classifiers.data.tr_ffnn_dataset_mgmt import annotate_dataset as annotat... |
81f811a903a924a0b891f310ceaab8725facc9c77cbabbd2f906da729cd75761 | Python | 10,709 | 281 | # ML4H is released under the following BSD 3-Clause License:
#
# Copyright (c) 2020, Broad Institute, Inc. and The General Hospital Corporation.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
#... |
02e494129c1cf5e28faa3b78a114beb16d3c91e73bd1d5a5a55c53094ec9977e | Python | 10,711 | 361 | import os
import sys
import pytest
import torch
import ray
import ray.cluster_utils
import ray.experimental.collective as collective
from ray.dag import InputNode
from ray.dag.output_node import MultiOutputNode
from ray.exceptions import RayChannelError, RayTaskError
from ray.experimental.channel.cpu_communicator imp... |
c00b0681cec52b2329b9192acd917533b951ec42707b0b4191ac401a1214dec1 | Python | 10,711 | 328 | import os
import random
import torch
import argparse
import numpy as np
import pandas as pd
from tqdm import tqdm
import torch.nn.functional as F
from torch_geometric.data import Data
from torch_geometric.nn import GCNConv, Linear
parser = argparse.ArgumentParser()
masks = ["true", 'false']
parser.add_argument('-k',... |
2b9963d8d79c9485b937b4904c14c8e733b37b7fc1003620004418a75102ef7a | Python | 10,713 | 281 | # ML4H is released under the following BSD 3-Clause License:
#
# Copyright (c) 2020, Broad Institute, Inc. and The General Hospital Corporation.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
#... |
ddb78d044b4eec7fac351b7bee754379e07d7d61c3e2763edd7afdc94d327f28 | Python | 10,714 | 287 | import numpy as np
from openmm import unit
import endstate_correction
import pathlib
from openmm.app import (
CharmmParameterSet,
CharmmPsfFile,
PDBFile,
CharmmCrdFile,
NoCutoff,
Simulation,
PME,
)
from openmm import LangevinIntegrator
from openmmml import MLPotential
import mdtraj as md
fro... |
d142fa9bde9a1451bd344beacba7f5e32e7137c039ec2b51f979f4071b481d7c | Python | 10,717 | 299 | # -*- 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.
#... |
e04b7b107f39189c9a24c6c90aab50191ba25bbb1fdf3b62f5404e1db4038c03 | Python | 10,719 | 289 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
"""
import argparse
from collections import defaultdict
import pysam
from svtk.genomeslink import GenomeSLINK, GSNode
import svtk.utils as svu
from statistics import median
import numpy as np
import datetime
class DiscPair(GSNode):
def __init__(self, chrA, po... |
98bb22dbc9ced736908590218b138f7c80b3c7c3681af96bd0dc55280f2d4151 | Python | 10,720 | 304 | from RNN_helpers.io import load_outputs, load_network_all
from RNN_helpers.analysis import binarize_inputs, binarize_outputs
import numpy as np
import math
import os
import json
from types import SimpleNamespace
import sys
import h5py
def loadNetwork(DIR, RUN, OutputOnly=True):
print("loading "+RUN)
# Loading ... |
b598e16d3090f492a7bc03b29e24eea1b5886ea26cbbc88a2185732a19f2b271 | Python | 10,720 | 324 | # built-in dependencies
from typing import List, Tuple, 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_m... |
46d9a69fe02b029eb48840f1cc35f6b0d398447e097cc1d39c2c9a837f5e1296 | Python | 10,721 | 327 | import os
import sys
import random
import torch
import argparse
import numpy as np
import pandas as pd
from tqdm import tqdm
import torch.nn.functional as F
from torch_geometric.data import Data
from torch_geometric.nn import PNAConv, Linear
parser = argparse.ArgumentParser()
masks = ["true", 'false']
parser.add_argu... |
fc7bbf47049fb0867aca34d3a53c450866e603322e08c9e55ea43ca7e9745e98 | Python | 10,721 | 176 | """
QUADRA_HC: total-body [18F]FDG-PET/CT of 48 healthy controls (test/retest), Medical University of Vienna.
Download the raw data (CC BY 4.0, no registration needed):
Zenodo record 16686025, version 1.1.1: https://zenodo.org/records/16686025
Single file QUADRA_HC.zip (20,184,928,484 bytes, md5 5b37cd936988a0... |
4e06f51a1f15b45d45aaaed3cbb62570690eac1782ff847ac950340e3e6c796e | Python | 10,724 | 266 |
# creates a 2-channel map (.csv) with random spatial segments
# e.g., python create_maps.py --help # help message
# e.g., python create_maps.py --out temp1.csv --seed 123 --w 50 --min_c1 0.2 --max_c1 3 --min_c2 4 --max_c2 40
# e.g., python create_maps.py --out temp1.csv --seed 123 --w 500 --png # output optional PN... |
cc68bc93d9e66c5e5b0500cd5ecae268dd4f720c3f3f9d5797c0dd0dd65aa78f | Python | 10,729 | 236 | from sklearn.model_selection import RepeatedKFold, RepeatedStratifiedKFold
from reval.relative_validation import RelativeValidation
from collections import namedtuple
from scipy import stats
import numpy as np
import math
import logging
import multiprocessing as mp
import itertools
import pandas as pd
logging.basicCon... |
d45bb1a7f8f002c3e479db75dffb8941bed349bca3ad60a90e2a924aa6a9734c | Python | 10,731 | 291 | # -*- 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.
#... |
5263ada3bcfd4a780c64cc1b2e3f85f82ac9c0239aa71086f8aa6edb1e010881 | Python | 10,733 | 329 | import gc
import numpy as np
import pandas as pd
import os
import seaborn as sns
import matplotlib.pyplot as plt
from collections import defaultdict
from functools import partial
import scipy as sp
from scipy.stats import f_oneway, linregress, ttest_ind
import warnings
warnings.filterwarnings("ignore")
# load in dire... |
8ccf5af4bbf0728252aa7f8dc5da9332044fd17bd6ae757ae2b9dcb05e0d2d89 | Python | 10,739 | 374 | import inspect
import os
import sys
import tempfile
import numpy as np
import pytest
import nir
from tests import mock_affine, mock_conv, mock_linear
ALL_NODES = []
for name, obj in inspect.getmembers(sys.modules["nir.ir"]):
if inspect.isclass(obj) and obj.__module__ == "nir.ir":
ALL_NODES.append(obj)
... |
e7c71c81fbf0a691634a863994a69018aa57ced4154a307fd9ed73495051567c | Python | 10,741 | 327 | import numpy as np
import scanpy as sc
import pandas as pd
import scipy
import math
from typing import List
from anndata import AnnData
from sklearn.neighbors import kneighbors_graph
from scipy.sparse import csr_matrix
from scipy.sparse.csgraph import dijkstra
# Read in
def load_data(path):
"""
Read from the... |
5cf959192fbb562fe4e534797d167434363934a01187767e1fd7f607594a417d | Python | 10,743 | 284 |
'''
save_training_data('data/my_training_data.npz', X, Y, XY_axes)
XY_axes="SCYX"
'''
import numpy as np
from tifffile import imsave,imread
from .image import *
from .filter import discard_slices
import mrcfile
class Tomogram:
def __init__(self, volume):
self.__volume = volume
def rotate_aroundZ(s... |
a8fd3af0d6411bd2afe0f339a341d75340331684e10518271f5156ad57e583ab | Python | 10,744 | 280 | #
# 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... |
9166bf2b28fdd0540b0eb2d98e358afea3356afcb24782c8dfa1f5f83fd24492 | Python | 10,751 | 286 | from __future__ import annotations
from typing import TYPE_CHECKING
import torch
import torch.nn as nn
import torch.nn.functional as F
if TYPE_CHECKING:
from fairchem.core.models.allscaip.configs import (
GlobalConfigs,
GraphNeuralNetworksConfigs,
MolecularGraphConfigs,
Regulariza... |
3cf75644e9b9f39f2df169431d277f9f9a3e9d7257d49e4979fa281b7fe9ca20 | Python | 10,755 | 312 | #!/usr/bin/env python
# Written by Greg Ver Steeg
# See readme.pdf for documentation
# Or go to http://www.isi.edu/~gregv/npeet.html
import warnings
import numpy as np
import numpy.linalg as la
from numpy import log
from scipy.special import digamma
from sklearn.neighbors import BallTree, KDTree
# CONTINUOUS ESTIMAT... |
2363cf3055517877a30b2dc150965173784f9eae7eff448a93a82434827470e4 | Python | 10,757 | 301 | """ Module matching %GC compo distribution b/w fg and bg. """
import sys
import random
from Bio import SeqIO
from utils import GC
def fg_GC_bins(fg_file):
"""
Compute G+C content for all sequences in the foreground.
It computes the %GC content and store the information in a list. To each
G+C percen... |
df6e2d7538a7d79db253127b5ff7975e2647074ae0657b1a07917228cc588756 | Python | 10,760 | 305 | #!/bin/env python
import argparse
import sys
import pysam
import math
from numpy import median
from typing import List, Text, Dict, Optional
_gt_no_call_map = dict()
_gt_hom_var_map = dict()
_gt_ref_map = dict()
_gt_to_filter_status_map = dict()
_gt_to_filter_gt_map = dict()
_cnv_types = ('DEL', 'DUP')
_HIGH_NCR_FILT... |
4973e8a5b832fc39523961fff49406a1f30874d2fa872171e193be6b7e866a10 | Python | 10,761 | 321 | import os
from itertools import repeat
from tqdm import tqdm
import numpy as np
import torch
from torch_geometric.data import Data, InMemoryDataset
from torch_geometric.utils import subgraph, to_networkx
from .molecule_datasets import MoleculeDataset
from .molecule_motif_datasets import rdkit_functional_group_label_f... |
b6b3361605cecd19922c471324ed5e7fdee0cad2f6fe8852c8c0d174d8fb86ab | Python | 10,763 | 172 | import torch
import logging
from torch.utils.data import TensorDataset
from sklearn.model_selection import train_test_split
from scipy.special import softmax
from agent.data.sql.sql_mgmt import get_connection, select_fields_where, update_non_text_field, update_text_field
from agent.classifiers.data.tfidf_dataset_mgmt... |
a584ba91b5a17a35f6735b18b66577ae0fe9ac35e360252a2ffaeb0dd4243bc6 | Python | 10,765 | 224 | import time
from DataPrepare import DataCook
import Net
import matplotlib
from sklearn.metrics import mean_absolute_percentage_error, r2_score
matplotlib.use('TkAgg',force=True)
import matplotlib.dates as dates
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import pandas as pd
impor... |
201449e779c714678051f207b1738f17ef1a15840ce7e58b940b06683f48b9db | Python | 10,769 | 308 | import json
import logging
import pickle
from pathlib import Path
from typing import Optional, Union
import numpy as np
import pandas as pd
from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor
from sklearn.metrics import (
log_loss,
mean_absolute_error,
)
from sklearn.model_selection impo... |
9aae4ac45ee6ae097289ced9e9fe5c3b9aa8c64c2eba3681847ecbb1fe43640e | Python | 10,769 | 277 | # 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 os
import numpy as np
from unicore.data import (
Dictionary,
NestedDictionaryDataset,
LMDBDataset,
AppendTokenDataset,
Pr... |
9353a0e14e40cf9b2ba7e1421261b48df3ecbf87096c2b5c59bcb83841c8e171 | Python | 10,774 | 270 | 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 torchvision
import scipy
import scipy.ndimage
import PySpin
import matplotlib.pyplot as plt
from ... |
52fe38ee48e8aacadac277d7dff959553de05c932e5ef2a26850bca9629b3aa7 | Python | 10,775 | 253 | import logging
import math
import warnings
from collections import defaultdict
from typing import TYPE_CHECKING, Dict
from .backpressure_policy import BackpressurePolicy
from .downstream_capacity_backpressure_policy import (
get_available_object_store_budget_fraction,
)
from ray._common.utils import env_float
from... |
53d92079820b24396cb7013afcb8260269c4dbf7bafbcba3502ab8996946b915 | Python | 10,775 | 234 | # Copyright 2021 HIP Applied Computer Vision Lab, Division of Medical Image Computing, German Cancer Research Center
# (DKFZ), Heidelberg, Germany
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy... |
5cc5b4d32b28e2dff3a2e8250c4152739b0397e9471422bee065af905ca73513 | Python | 10,777 | 307 | # ML4H is released under the following BSD 3-Clause License:
#
# Copyright (c) 2020, Broad Institute, Inc. and The General Hospital Corporation.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
#... |
07a48d7b737881adbe26df1e4471667b968b522dc3d7337f1a03582d5b10ad08 | Python | 10,780 | 363 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
# pylint: disable=too-many-instance-attributes
"""Utility enumerators for resistive processing units."""
from enum import Enum
from torch import dtype, float32... |
36505a32616fb155ab6ad7b5c06158099e0516e044fdf7915602ad028449c8d5 | Python | 10,780 | 268 | """
Train ridge regressors on the augmented dataset
train dataset: half (2 trials) from exp, half (2 trials) from synthetic
test dataset: one trial from exp other than the trials in train dataset
"""
import argparse
import os
import pickle
import numpy as np
import pandas as pd
from itertools import combinations
f... |
b57523ca6ca55926e75784c93f26d6bc00bc7b12f188040ccdf85b0478b57e8f | Python | 10,780 | 183 | #-----------------------------------------------------------------------------------------------------------------------------------------------
# Author: Brandon S Coventry Purdue University, UW Madison Neurosurgery
# Date: 01/2024
# Purpose: This program simply plots figures of the illustrative ... |
3393a7e33f20a017843e9e2ebb9ae019beccb6e3d4f472f5ecaa5007590a28d3 | Python | 10,783 | 259 | from torch.utils.data import Dataset, DataLoader
import torchvision.transforms as transforms
import random
import numpy as np
from PIL import Image
import json
import torch
import os
import matplotlib
from autoaugment import CIFAR10Policy
def unpickle(file):
fo = open(file, 'rb').read()
size = 64 ... |
663efe7a2787e39724bba5cf7bcd9e56d0d40b88a55d0a4f2b1157a661db430e | Python | 10,786 | 227 | import asyncio
import logging
from typing import List, Optional, Set
import ray
from ray._private.gcs_pubsub import GcsAioJobSubscriber, GcsAioWorkerDeltaSubscriber
from ray.core.generated import gcs_pb2, gcs_service_pb2, gcs_service_pb2_grpc
from ray.dashboard.modules.task_events.task_event_storage import (
GC_JO... |
bbe099880726a339b0febdbf3ef8752b0ef877b89f62aa4a5c8ba2cf21e4d4db | Python | 10,789 | 295 | import torch
from torch import nn
from torch import optim
from torchvision import models
from sklearn.metrics import roc_auc_score
from torch.optim.lr_scheduler import MultiStepLR
import numpy as np
def get_model(model_name, device, pretrained=False, freeze = False):
#if model_name.startswith('vgg11'):
# m... |
92f714d2075eae802b70cbe91022693e3dc72081374f5917eb7c3a1186f2c191 | Python | 10,790 | 222 | #%%
import torch
import torch.nn.functional as F
import numpy as np
from sklearn import cluster
import torch.nn as nn
# THis file contains definitions of encoding and decoding functions.
# %%
# #############################################################################
# ENCODER DEFINITIONS
# Convention: x is a vect... |
d056e37ea5fdd337886d22a8f6118f2a03875b138d256b38c0cb4b3669087e99 | Python | 10,791 | 204 | __author__ = "Simon Andermatt"
__copyright__ = "Copyright (C) 2017 Simon Andermatt"
import numpy as np
import tensorflow as tf
import logging
from mdgru.helper import argget, collect_parameters, define_arguments, compile_arguments
from mdgru.model import save_summary_for_nd_images
from mdgru.model.mdrnn import MDGRUN... |
670fc931debd3bf113ec6fd785bfc3cfbee31b08a60ace39aafcb03df55a1cc7 | Python | 10,792 | 278 | # Caution: Due to the number of hyperparameter combinations this simulation takes between 4-6 days, on GPU.
import torch
import torchvision
import torchvision.transforms as transforms
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import numpy as np
if torch.cuda.is_available():
... |
c4a5e509c6aa313a3b81049afd592af3cc54468f63a93d38a919ba75c368b8c7 | Python | 10,792 | 375 | """
Make and save syllable spectrograms.
"""
__date__ = "December 2018 - July 2020"
import h5py
import matplotlib.pyplot as plt
plt.switch_backend('agg')
import numpy as np
import os
from scipy.io import wavfile
from scipy.io.wavfile import WavFileWarning
import warnings
from ava.preprocessing.utils import _mel, _i... |
f3b3cc6561a175b0118f72c8acbcd5da0d0e659368c9adef5b6fc6f903d34ac5 | Python | 10,792 | 334 | """
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 json
import os
from unittest.mock import patch
import numpy as np
import pytest
from fairchem.... |
bfe4a8f410b1c2d04513310598bb5af9eb5a61e7d2ed2a61ca3b99c598f3319d | Python | 10,796 | 315 | import numpy as np
import torch
import torch.nn as nn
from einops import repeat
from scipy.linalg import cholesky_banded, solve_banded
### Kernels
class OUProcess(nn.Module):
"""
Ornstein-Uhlenbeck process.
Provides a sample method and a Mahalabonis distance method.
Supports linear time operations.
... |
63198fe048eeccb2c014f8ef8a15a5c20f716aa2e09da2f17ec223f1eb3f8968 | Python | 10,798 | 110 | #!/usr/bin/env python3
import argparse
import os
def str_to_bool(value):
if value.lower() in ('true', '1', 'yes'):
return True
if value.lower() in ('false', '0', 'no'):
return False
raise argparse.ArgumentTypeError(f"expected True or False, got '{value}'")
def build_parser():
# The CL... |
dc13a930f6d682fff8c3e5bbc47346b0fcb9d49d901c8e8f295b195ec519d815 | Python | 10,799 | 345 | from sklearn.neighbors import NearestNeighbors
from scipy.spatial.distance import cdist
import numpy as np
import warnings
def opt_scale(X, Y, k_num, use_gpu=True, verbose=False):
"""
This function computes the optimal scales of landmarks.
Now supports GPU acceleration via MLX (Apple Silicon) or ... |
0cdd59efecb7741eebbbc1010cc2b7bab536824881f0a94b8d58ee3d4c16e871 | Python | 10,800 | 308 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Created on Wed Feb 24 18:39:45 2016
@author: Andrea Giovannucci
For explanation consult at https://github.com/agiovann/Constrained_NMF/releases/download/v0.4-alpha/Patch_demo.zip
and https://github.com/agiovann/Constrained_NMF
"""
from __future__ import print_funct... |
8748f427cb29deb9cc54e9b1a9e5e6dbf9a383261fc94c7c0a49aeaed2cc826d | Python | 10,800 | 277 | ####################################################################################################
# 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 library is fre... |
0076abb2b89211e01ae23c0c0fd7bc818499d98a7225ace22bcff05b082d9e69 | Python | 10,803 | 268 | #!/usr/bin/env python
"""
GPU-accelerated KNN search for OmicVerse.
The previous implementation called ``torch_geometric.nn.knn(X, X, k)`` (which
under the hood is ``torch_cluster.knn``) on the full N x D matrix at once,
plus a ``torch.cdist(X, X)`` fallback. Both materialize an ``N x N`` distance
tensor at some point... |
e2575875b057fdafc2525774aa694f73d42dc302a3930cec68e0ad0db398499a | Python | 10,803 | 238 | #!/usr/bin/env python
from __future__ import print_function
import argparse
import gzip
import sys
import os
import numpy as np
import random as rand
import math
def parse_args():
parser = argparse.ArgumentParser("Downsample FASTQ based on length and total coverage")
parser.add_argument('--input', '-i', dest... |
fd6814a2bd2cf4cf934e2ee29816cc117b2ab1e5a73f8dc6ce0834bf9e7e71f9 | Python | 10,807 | 340 | # -*- coding: utf-8 -*-
#
# lavaburst documentation build configuration file, created by
# sphinx-quickstart on Fri Dec 12 11:33:09 2014.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
#... |
7da588669d571122bf1f6b760fac55e501782a1ae115dd9a407c5a237de7e782 | Python | 10,813 | 235 | # This is the main code used for training and testing random survival forest models for the paper
# "Machine learning predicts phenoconversion from poly-somnography in isolated REM sleep behavior disorder"
#%% Necessary imports
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn ... |
d1565b200e33c406febe9351695de9aa469a2d03f2dddc3905e73037802a288f | Python | 10,817 | 382 | """
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 functools import wraps
from typing import TYPE_CHECKING, Callable, ClassVar
import numpy as np
im... |
d746093b78b13a4951fde688b607492416af25a9fabae71926926151a0628ce8 | Python | 10,817 | 254 | import os
# os.environ["NCCL_DEBUG"] = "INFO"
import warnings
warnings.filterwarnings("ignore")
import scanpy as sc
from tqdm.auto import tqdm
from torch import nn, Tensor
from .model import TransformerModel
from .eval_data import MultiDatasetSentences, MultiDatasetSentenceCollator
from .utils import figshare_downl... |
6b3ae09fe647bf20a860e287bfbdcdb921fc6e838b0c684ed17f8d3daecb8a21 | Python | 10,819 | 279 | #!/usr/bin/env python
"""Train a CNN for Google speech commands."""
__author__ = 'Yuan Xu, Erdene-Ochir Tuguldur'
"""With modifications from Karan Goel."""
import argparse
import time
import torch
import torchvision
from torch.autograd import Variable
from torch.utils.data import DataLoader
from torch.utils.data.sa... |
2fa7e67fd4290d5610370baa2f68e2ff53dc9b73677ae3f337435d95a04839e9 | Python | 10,820 | 247 | #!/usr/bin/env python3
from __future__ import print_function
import argparse
import glob
import sys
import matplotlib.pyplot as plt
import pysam
import collections
import numpy as np
import os
GENE_GTF_CHROM_IDX=0
GENE_GTF_TYPE_IDX=2
GENE_GTF_START_POS_IDX=3
GENE_GTF_END_POS_IDX=4
GENE_GTF_INFO_IDX=8
TYPE_GENE="gene"... |
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