sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
eafe4673958198a3e3e114d0bfd994b5f6e4d5e0eeba628c21177ba89b378070 | Python | 6,709 | 172 | from __future__ import annotations
import logging
import os
import numpy as np
import pandas as pd
import scanpy as sc
import scvi
from .. import settings
from ._base_algorithm import BaseAlgorithm
class SCANVI_POPV(BaseAlgorithm):
"""
Class to compute a classifier using the scANVI model.
"""
def ... |
c4be2a49bd6cc8c476bd77f3662003c5d28dee429ecbdb0f73df0abdfe036c10 | Python | 6,714 | 197 | from __future__ import division
import numpy as np
import scipy.special as special
# Import manually defined functions
from .variational_nodes import (
Constant_Variational_Node,
Beta_Unobserved_Variational_Node,
)
class ThetaW_Node(Beta_Unobserved_Variational_Node):
"""
This class contain a Theta no... |
dece605a7a863c20c71bd9904f11e384376578c11445e78f950641ce1eaff80f | Python | 6,714 | 162 | import json
import logging
import os
from enum import Enum
from urllib.parse import quote
import aiohttp
from aiohttp.web import Request, Response
import ray.dashboard.optional_utils as optional_utils
from ray.dashboard.modules.metrics.metrics_head import (
DEFAULT_PROMETHEUS_HEADERS,
DEFAULT_PROMETHEUS_HOST,... |
0633e018b82bb902d831b07dd7a967fb4d9de9e360c974ea6cfd0205a3111620 | Python | 6,715 | 190 | import pickle
import _reference_implementations
import numpy as np
import pytest
import torch
import cebra
import cebra.attribution
import cebra.data
import cebra.models
import cebra.solver
from cebra.data import ContrastiveMultiObjectiveLoader
from cebra.data import DatasetxCEBRA
from cebra.solver import MultiObject... |
1f418ee73cb8f2a97d431121575d280d72988c217ff65930d39c2279f77e8f89 | Python | 6,717 | 163 | from typing import List, Union
import numpy as np
from rdkit import Chem
import torch
import torch.nn as nn
from .mpn import MPN
from GR_pKa.args import TrainArgs
from GR_pKa.features import BatchMolGraph
from GR_pKa.nn_utils import get_activation_function, initialize_weights
class MoleculeModel(nn.Module):
"""... |
b8af509e98897291bab6c96a46b842a2188c38816c46a0491da4d971ef7562c8 | Python | 6,720 | 174 | # -*- 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.
#... |
2f8868d197216b3193e2c9b6ca0b8726602372d7df189f9f05df1e3aad01bc9a | Python | 6,721 | 151 | import os, sys
import time
import multiprocessing
import numpy as np
from functools import partial
# Define path
path_results = "../../Data/results"
path_output = os.path.join(path_results, "curve_fits", "compare_fitting_methods", "beta_simulate_N_ntrials250")
functions_modul = "../functions"
# Importing module for f... |
9d31351b6f165fd768060c6c3188612d772ae1607a23a141333babfed5dd3741 | Python | 6,721 | 148 | import os
import numpy as np
from pyfasta import Fasta
import json
from loguru import logger
from deltasplice.constant import Fapath, CL, EL, Train_Chromes, Valid_Chromes, Test_Chromes
from deltasplice.utils import parse_bed_line
import random
from bisect import bisect_left
def main(Data, Path):
logger.info("ha... |
1fe089ea2bcfcbd7e7c2d5ba47a90a299160e772877ff6fecbface6d4602731f | Python | 6,722 | 155 | # coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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 a... |
45de4b13c063732664935bc9e77640b3d6beac2f4a9510fb85520931b95c89cb | Python | 6,722 | 190 | """
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.
Unified Radial MLP: Computes all layers' radial functions in a single
batched operation.
Instead of running N separate RadialMLP forward passe... |
8bdda067f77826f87329ef1f9972f28bf703f26702e63152f9e6d65223c53c5f | Python | 6,722 | 193 | ####################################################################################################
# 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... |
f4a1a18295967076cf4328e63786fd6ec25984459bfaabc9d41a44f570503d8c | Python | 6,723 | 195 | #!usr/bin/python
# --------------------------------------------------------------
# Compute a UMAP for each major celltype alone for visualization
# Updated: 09/03/21
# --------------------------------------------------------------
import sys
bindir = '/home/cboix/data/DEVTRAJ/bin/'
sys.path.append(bindir + 'multiRegio... |
45ed1e39aab8eb8c9f8a0843b13c1bfaa79714a4214ebe8d9a6e45a1a2958c0e | Python | 6,724 | 145 | import sys, os
sys.path.insert(0, os.getcwd())
from src.models import get_model, get_trainer
import torch
from src.dataset.electrolytes import load_dset_electrolyte
import torch.optim as optim
from src.utils.argparser import parse_ecg_args, parse_eval_args, save_args
from src.utils.random import merge_configs
import n... |
581afb62785367eae354543f25ef724d4123cae726843ea8966c3d6c5d00cd35 | Python | 6,724 | 152 | import logging
import re
import pandas as pd
from sklearn.model_selection import train_test_split
from agent.data.entities.config import ROOT_LOGGER_ID
from agent.data.entities.config import TRAIN_ITEM_FILTER, TRAIN_LABEL
from agent.data.entities.config import DEV_ITEM_FILTER, DEV_LABEL
from agent.data.entities.confi... |
f695d2b6174d5c175fe0c8c67c4f4b5c7097af7859bc6730f2a94b2f87910a55 | Python | 6,724 | 205 | """Fixed GEO API methods."""
def get_series_matrix(self, gse_accession: str) -> Dict[str, Any]:
"""Get series matrix file.
Args:
gse_accession: GEO Series accession (e.g., "GSE1234")
Returns:
Series matrix data
"""
url = f"{self.geo_base_url}/acc.cgi"
params = {
... |
63f73bfa92d9eae79d8f38712c89bd8db501a9b66a75cfa1b76ec696e8c1b0fe | Python | 6,727 | 208 | import os
import random
from argparse import Namespace
from typing import Dict, List
# import nibabel as nib
import numpy as np
import pydicom
import torch
from torch.utils.data import Dataset
from ldctinv.utils import load_yaml
class LDCTMayo(Dataset):
"""Dataset class for the LDCT dataset"""
def __init__... |
5c340ebaee371a91b6d194052b787ba59e8238ab8afc02e493e6227a5bf11e5f | Python | 6,728 | 125 | ####################################################################################################
# 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... |
8977b0394a2296626f9e8155d8f45d1dfe987c9360097a24fbda58d1407bbbc0 | Python | 6,729 | 176 | # -*- coding: utf-8 -*-
"""
Created on Fri Jun 28 08:42:00 2019
@author: ju-bar
Calculations and data handling related to the Modulation Transfer Function (MTF)
pixelated imaging detectors.
This code is part of the 'emilys' repository
https://github.com/ju-bar/emilys
published under the GNU General Publishing Licens... |
6880c51d7fab4b0ca5d9a3fcef45e6487f9baa1e2f9d478394e4fdcfc0cee615 | Python | 6,730 | 148 | import os, sys
import time
import numpy as np
import itertools
import multiprocessing
from functools import partial
# Define path
path_results = "../../Data/results"
path_simulation_general = os.path.join(path_results, "curve_fits", "compare_fitting_methods")
path_output = os.path.join(path_simulation_general, "search... |
849b8f5e303cc41c5e423851d88f5e7ab76687a64ed96b13fb8d3725be1e8ea8 | Python | 6,730 | 222 | # -*- coding: utf-8 -*-
"""
Created on Tue Jul 4 20:15:15 2023
@author: Leyang Xue
"""
import sys
import numpy as np
from multiprocessing import Pool
# Add package path
packagepath = '../kcorePercolation' # Manually specify the path to your script
sys.path.append(packagepath)
from utils import kcorePercolation a... |
45ebb1159767c5a86fecac69e1c36209ea25ba9f8315db63ad9c870f4d4b9135 | Python | 6,734 | 190 | # Ultralytics YOLO 🚀, GPL-3.0 license
import lap
import numpy as np
import scipy
from scipy.spatial.distance import cdist
from .kalman_filter import chi2inv95
def merge_matches(m1, m2, shape):
O, P, Q = shape
m1 = np.asarray(m1)
m2 = np.asarray(m2)
M1 = scipy.sparse.coo_matrix((np.ones(len(m1)), (... |
6aebe8f8b479ee44c51afda9940fefcdacc4d48e79d8c6c3d0c250e03c9dff8c | Python | 6,734 | 166 | """
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 warnings
from typing import TYPE_CHECKING, Any
import numpy as np
from fairchem.data.oc.databas... |
99582ad989fa474c06f6778ee3db4be04141aa04ed36b5491d743990b6ba488e | Python | 6,735 | 181 | """Compare times to peak across layers"""
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
# Load data
data = pd.read_csv(f'/Users/sebastiandresbach/github/neurovascularCouplingVASO/results/ERAs_rawPlusZscored_equalizedNormalized.csv', sep=',')
layerNames = ['Deep', 'Middl... |
244f6f324481ae0feb7fdfa51cfe04da5898ecb4af849e1347fa31c1c29fd5d1 | Python | 6,736 | 196 | """Colocalization analysis for ``ov.genetics`` — coloc backend.
Wraps the standalone :mod:`pycoloc` package (Giambartolomei *et al.*
2014; Wallace 2020/2021). :func:`colocalize` tests whether two traits
(e.g. a GWAS signal and an eQTL) share a causal variant at a locus.
``method`` dispatches between the single-causal-... |
7aa55859802b3b08360a05a4b293e86d6cc098dccf3e6126c574208a5ad0ee67 | Python | 6,738 | 195 | import tracemalloc
from fractions import Fraction
import numpy as np
import pytest
from stl import mesh
from .test_mesh_mass_mixed import subdivide
from .test_mesh_mass_sliver import _unit_cube
def winding_parts():
narrow = np.array(
[
[565499, 1633004, 136135],
[0, 2888250, 240... |
c862ee365e13d13953cb789175a586a35ae392743f93c8c32dfc616bc602366d | Python | 6,738 | 242 | """
Segment audio files and write segmenting decisions.
TO DO:
- tune window size
- segment could be sped up if it operated file by file.
"""
__date__ = "December 2018 - November 2020"
import matplotlib.pyplot as plt
plt.switch_backend('agg')
import numpy as np
import os
from scipy.io import wavfile, loadmat
from... |
e96da9117fbf4ac58ff22ec1ab4d34812db250e51e506b7f66f8baec3f8fa6e6 | Python | 6,738 | 144 | #
# ATENCIÓN, para cargar los archivos pt de julio 2023 se debe utilizar:
# - transformers==4.16.2
# - protobuf==3.20.3 (no comprobado que sea necesario)
#
import logging
from datetime import datetime
from agent.classifiers.utils.device_mgmt import get_gradient_accumulation_steps
from agent.classifiers.transformer_... |
58f27dd925bd3db8b7aa223c05ff9a975fabbc533e6a60e9dbdbfeca879604ba | Python | 6,740 | 160 | """
Behavioral transition / timescale analysis (Berman, Bialek & Shaevitz, PNAS 2016).
Clean, public versions of the transition tools that previously lived only in ``demoutils``.
Two improvements over the ``demoutils`` versions (which are kept, unchanged, for backward
compatibility):
* :func:`makeTransitionMatrix` a... |
c6860a6a03f92f7ae7d12a6392db4b769fc28aea37183d490d2820771504adff | Python | 6,740 | 157 | """ This file defines necessary parameters (constants?) for the model.
The order of the cell types is [EXC, PV, SST, VIP]
"""
# %%
import numpy as np
import pickle
# fmt: off
""" 11/23/2021: The final influence matrix is recalculated based on the mean values.
(previously they were medians.), and the errors are evalu... |
c0ed9a2904793b9954c41220483861d88d7b4a5ed6bca88868e4fe7b5740728f | Python | 6,741 | 153 | import numpy as np
import scanpy as sc
import pandas as pd
import io
import anndata
def ligand_receptor_database(
database = "CellChat",
species = "mouse",
heteromeric_delimiter = "_",
signaling_type = "Secreted Signaling" # or "Cell-Cell contact" or "ECM-Receptor" or None
):
"""
Extract ligan... |
7fb28d6ec318b0d01eeacbddac7414f15210997cacb2538b51810af53f8c8d7c | Python | 6,742 | 209 | """
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 math
from contextlib import suppress
from dataclasses import dataclass
import torch
import torc... |
e5d20269b1c17aa494ede1658db8f8e6a0750f0421ee9482eb0541cb8edb807b | Python | 6,744 | 183 | import json
import os
import pprint
import sys
import jsonschema
import pytest
from ray._common.test_utils import (
run_string_as_driver,
wait_for_condition,
)
from ray._private.test_utils import (
format_web_url,
request_with_auth_token,
run_string_as_driver_nonblocking,
)
from ray.dashboard impo... |
060bc50524f9c11e5ded36ab025143086ae81beb7d3570ec5e82452dead00189 | Python | 6,745 | 222 | from typing import Any, Dict, Tuple
import numpy as np
import pandas as pd
from scipy.fft import fft as scipy_fft
from scipy.signal import find_peaks
from statsmodels.tsa.stattools import adfuller
from data_profiling.config import Settings
from data_profiling.model.summary_algorithms import (
describe_numeric_1d,... |
9d17023b421bee96b41d0b80a7be3cb407f3245908b7980b914a375092291719 | Python | 6,746 | 200 | # -*- coding: utf-8 -*-
import numpy as np
from numpy.testing import assert_array_almost_equal
from scipy.sparse import csc_matrix
from scipy.linalg import orthogonal_procrustes
from fmralign.alignment_methods import (
DiagonalAlignment,
Hungarian,
Identity,
OptimalTransportAlignment,
POTAlignment... |
2c2b3f95042c4cecb608033d35a1d693f77dfea5c8e7db8cb3bcc58eadc21cf5 | Python | 6,747 | 196 | import tempfile
import shutil
import os
from os.path import *
from . import tdir
import subprocess
from ngs_mapper import compat
class BaseTester(object):
def _C( self, *args, **kwargs ):
'''
Set modulepath as instance variable to be the name of the module
Set functionname as instance varia... |
dfbafd33e9f240bc922d722aff29faebe6a204de1b32f85b5e27e08bd6cf463a | Python | 6,747 | 238 |
from typing import Set, Callable, Any, Union, Optional, Type, Dict, Sequence, List, TypeVar
from functools import partial
import copy as cp
import inspect
from neuron_morphology.feature_extractor.mark import Mark
from neuron_morphology.feature_extractor.data import Data
from neuron_morphology.feature_extractor.featur... |
c36b8e3dca2ae286641fd43e079d86e6df93e3ddcbc08bc563ea082b03b76154 | Python | 6,748 | 209 | import os
import numpy as np
import mne
from scipy.io import wavfile
class SpeechWaveExtractor():
""" Class to load audio data.
Methods
-------
extract_wave()
Gets speech wave from audio segment.
get_wave()
Returns speech wave and sampling frequency.
"""
def __init__(self... |
590321100be8ff925e4246d4394feb56a249894d578706b366f5fa6d47c68274 | Python | 6,749 | 213 | import abc
import collections
import functools
import inspect
import json
import logging
import os
import traceback
from typing import Any
from ray.dashboard.optional_deps import PathLike, RouteDef, aiohttp, hdrs
from ray.dashboard.utils import CustomEncoder, HTTPStatusCode, to_google_style
logger = logging.getLogger... |
2d730f73eb687b76db85842b6ec14eed798ec7895b0122c18b19ee41534add93 | Python | 6,751 | 189 | # -*- coding: utf-8 -*-
"""
Created on Mon May 03 08:46:00 2021
@author: ju-bar
Functions handling input and output of structure data
via the CEL file format.
The CEL file format is a text format defining a volume in space
which is filled by atoms.
The supercell is defined by a sequence of numbers in the second
line... |
680ddaca92c4779785d72f5e9befe12d8c125f2564ce2e07e1fd69b45e4ba15e | Python | 6,751 | 169 | r"""``ov.epi.tl`` — epigenomics analysis tools (wraps :mod:`epione.tl`).
Dimensionality reduction (iterative LSI), clustering, gene-activity
scores, peak-to-gene linkage, chromVAR motif deviations, footprinting and
cross-modality integration — all delegating to
`epione <https://github.com/aristoteleo/epione>`_. Each f... |
b141b66fc5a00c7dfc3597d36945b6e097ec9a0728bc263c06972e031181f27d | Python | 6,752 | 182 | # -----------------------------------------------------------------------------
# MS lesion segmentation pipeline
# ---------------------------------
# - incorporates:
# - MRI identification
# - registration
# - skull stripping
# - MS lesion segmentation training and testing using th... |
92621ae4d534e8f224b1675a611a36bd88d6924ccf6468ba0586421d3cc3e3fe | Python | 6,753 | 220 | """
# ResNet-D backbone with deep-stem
# Code Adapted from:
# https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py
"""
import torch
import torch.nn as nn
import torch.utils.model_zoo as model_zoo
import network.nn.mynn as mynn
__all__ = ['ResNet', 'resnet18', 'resnet50', 'resnet101']
model_url... |
b289e468d6d02c0fca4fbb133b4f5123e7e3a482a0293e82e5aa34675e0c44bc | Python | 6,755 | 180 | import copy
from abc import ABCMeta, abstractmethod
from collections import defaultdict, namedtuple
from threading import Lock
from typing import Dict, List, Optional, Tuple
StoreStatus = namedtuple("StoreStatus", ["success", "version"])
VersionedValue = namedtuple("VersionedValue", ["value", "version"])
class Stora... |
a0f3e69254ca4f479503321217a87d3bffeefc85e728014bcd7a4e4a5da6b203 | Python | 6,760 | 152 | ####################################################################################################
# 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... |
3d968ffe53deafee8f87abff4a25e97532b3605cabd5fbaeb91fea11c6fa6530 | Python | 6,762 | 227 | """
Statistical functions
"""
import logging
import numpy as np
from scipy import stats
from tedana import utils
LGR = logging.getLogger("GENERAL")
RepLGR = logging.getLogger("REPORT")
def getfbounds(n_echos):
"""
Gets F-statistic boundaries based on number of echos
Parameters
----------
n_ech... |
86afb0495f86a21028264a924ba886ffb9c642fcc71c533c96711c8dda099237 | Python | 6,763 | 222 | # -*- coding: utf-8 -*-
"""
Created on Tue Jul 4 20:15:15 2023
@author: Leyang XUe
"""
import sys
import numpy as np
from multiprocessing import Pool
# Add package path
packagepath = '../kcorePercolation' # Manually specify the path to your script
sys.path.append(packagepath)
from utils import kcorePercolation a... |
4428f43f3d05eb4db8ae3e66d7d281a9db48a13c4feede25fed62ad4566a7656 | Python | 6,764 | 194 | CODE_DIR = 'C:/Users/mmall/Documents/github/'
SAVE_DIR = 'C:/Users/mmall/Documents/uni/columbia/assignment_errors/fits/'
import socket
import os
import sys
import pickle as pkl
import numpy as np
import scipy as sp
import matplotlib.pyplot as plt
import matplotlib.ticker as tkr
import matplotlib.font_manager as mfm
i... |
864dd741fab9c726cf33156c37806de7ac295d975f8f38feed6b796ee1d576ff | Python | 6,765 | 148 | """APIs-tab sidebar (Pattern B): a single shared API navigation, loaded client-side.
Ray's global sidebar server-renders the whole toctree into *every* page. The symbol-
level API nav has ~3k stub pages; rendering those into every page would bloat each one
(~250 KB of sidebar) and OOM the build. Instead:
1. Capture... |
51e3fa3f0c6014333f01c542c9e5a5a92d36aa881c8523ef6bbe6e8f7eceeee2 | Python | 6,767 | 196 | import sys
import random
import networkx as nx
# Add package path
packagepath = '../kcorePercolation' # Manually specify the path to your script
sys.path.append(packagepath)
from utils import kcorePercolation as kp # Import custom utility functions
def kcorepercolationPlateau(G, rm_nodes, k):
'''
Perform k-... |
fea8a13debc399ff2f343a66aa311d8c824a0fbe6633aa5915ad09b75a8d48c8 | Python | 6,767 | 160 | from __future__ import division
import os
import time
import argparse
import torch
from torchvision import datasets, transforms
import torch.optim as optim
import torch.nn as nn
from torch.optim.lr_scheduler import StepLR, MultiStepLR
import torch.nn.functional as F
from utils import accuracy, AverageMeter, save_checkp... |
c44369992ee020e47e283047c6926071c44e3c407292eb4bd85e9a1192692592 | Python | 6,770 | 206 | import argparse
import os
# Prevent numpy from using multiple threads
os.environ["OMP_NUM_THREADS"] = "1"
import numpy as np # NOQA:E402
from torch import nn # NOQA:E402
import pfrl # NOQA:E402
from pfrl import experiments, utils # NOQA:E402
from pfrl.agents import a3c # NOQA:E402
from pfrl.optimizers import Sh... |
96fdb51a76e9dbd9022de503ee4054e356baf867f5a7d5e085440c6c30ef4523 | Python | 6,771 | 168 | import math
import torch
from torch import nn
import torch.nn.functional as F
class DotProductAttention(nn.Module):
def __init__(self, dropout, **kwargs):
super(DotProductAttention, self).__init__(**kwargs)
self.dropout = nn.Dropout(dropout)
def forward(self, queries, keys, values):
d ... |
d2e83e47e86d4ee09801f1bcb2667bfa1bc893207ded6c7bcb197c5bf6739061 | Python | 6,771 | 193 | """
a lstm-a2c with context
context input is added to the linear layer of A2C
"""
import torch
import torch.nn as nn
import numpy as np
from model.A2C import A2C_linear
# from model.A2C import A2C
# constants
N_GATES = 4
# output format is either discrete (e.g. action selection) or continuous
OUTPUT_FORMAT = ['discre... |
90c37ef85e189e9c84c35e52c019a985f86fd8d4fc6b8159b447ff7fbdfe43bc | Python | 6,772 | 177 | import nibabel as nib
import numpy as np
import scipy.sparse as sp
from lib.surface import (
get_boundary_loop,
monotone_free_arcs,
read_surface_from_gifti,
write_metric_gii,
)
from lib.utils import setup_logger
from scipy.sparse import coo_matrix, diags
log_file = snakemake.log[0] if snakemake.log els... |
da1550bdc28de84f6619c3601ae48a8b129b38a1372e1a8752f75d574749bea9 | Python | 6,772 | 222 | from __future__ import annotations
from functools import singledispatch
from typing import TYPE_CHECKING
import numba
import numpy as np
from scipy import sparse
from sklearn.random_projection import sample_without_replacement
from ._compat import DaskArray, _CSMatrix, njit
if TYPE_CHECKING:
from typing import ... |
d4c1a3b1b992fd84e6f15426c9c53035998eceb470c3e3580b36e9efaea50d4f | Python | 6,774 | 193 | """ Creates a new table which maps patient ICD codes in UK Biobank to phecodes.
inputs in BQ
bigquery hesin table: <HESIN_TABLE>
previously loaded phecode data
outputs in BQ:
<OUTPUT_TABLE> with fields <sampleid, datetime, ICD10, Phecode>.
"""
from collections import defaultdict
import csv
from google.clo... |
134f9abd7071a3556ebd6ce18591235aab38db50311397459fc9db06e460471a | Python | 6,775 | 216 | '''
check if we can cluster the scene vectors
in particular, can we derive good clustering parameters from the training set
and generalize to the validation set
this is essential for the clustering based shortcut model to work
'''
import os
import pickle
import torch
import numpy as np
import pandas as pd
import seabo... |
565a7b28e5d07b95e14f051ceb6a962f0fb00edf7a392e2e128022ea121527cb | Python | 6,775 | 215 | import os
import sys
import tempfile
from unittest import mock
import pytest
from ci.ray_ci.automation.update_version_lib import (
get_current_version,
list_java_files,
update_file_version,
)
def test_list_java_files():
with tempfile.TemporaryDirectory() as tmp_dir:
os.mkdir(os.path.join(tmp... |
99d79b86c6d382d4f6ffd16636e3462ca210c20f30646fc5f267acf5e2a1ca86 | Python | 6,776 | 156 | # 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... |
ef413207899756a13362da7d06b1dec10ccd7d37d8bc8e7e37894d154c3373b1 | Python | 6,777 | 214 | import tensorflow as tf
from tensorflow.keras.layers import *
class CustomAttention(tf.keras.Model):
'''
LSTM attention layer
'''
def __init__(self, units):
super().__init__()
self.W1 = Dense(units, use_bias=False)
self.W2 = Dense(units, use_bias=False)
self.V = Dense(1)... |
fe7ae3ba8dc77b2fd8b824fa756b7027fb12c7bfe4749127a33745f346a12ada | Python | 6,777 | 139 | import numpy as np
import visionloader as vl
import argparse
import pickle
from typing import List, Tuple, Dict
# USES pycpd as a dependency, https://github.com/siavashk/pycpd
# you can install this with "pip install pycpd"
from pycpd import RigidRegistration
from lib.dataset_config_parser.dataset_config_parser impor... |
e9b5cd3922ea6916ad92e634af3dcd9ff8fd051cb1b8a829b8917f1b8c444f61 | Python | 6,784 | 201 | #
# Copyright (c) 2021, NVIDIA CORPORATION.
#
# 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 ... |
99acfd3d4fa8da3061cd6d24916eeb3146596f8f10862dfa7a900036d36047f0 | Python | 6,788 | 189 | import numpy as np
from lib.qc import ERROR
from lib.qc_surface import (
compute_qc,
compute_topology,
face_clusters,
plot_defects,
plot_distortion,
plot_histograms,
self_intersecting_faces,
unfold_distortion,
)
def grid(n=8, m=8, wrap_u=False, wrap_v=False):
"""Triangulated n x m ... |
c3e31593b914260cabbb8ff1107f148526dc5f537c179dbcfc1f0d84d2847d40 | Python | 6,789 | 191 | # -*- 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.
#... |
a140f4684a28909415f45c41db9b2045be7476e48e272139ea37d4b991e5846e | Python | 6,790 | 203 | """gRPC server interceptor for token-based authentication."""
import logging
from typing import Awaitable, Callable, Optional
import grpc
from grpc import aio as aiogrpc
from ray._private.authentication.authentication_constants import (
AUTHORIZATION_HEADER_NAME,
TOKEN_AUTH_ERROR_MESSAGE,
)
from ray._private... |
8ba05a28615c4d37416c19b953c4b8711f120e2c76e15a731d6018978b985c69 | Python | 6,793 | 161 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
def translate_nuc_to_aa(seq):
'''
The function receives a nucleotide sequence and translates it to an amino acid sequence
:param seq: string of nucleotide sequence
:return: string of amino acid sequence
'''... |
494170f3bc590722089f53040f990867caf7cacfea9b5a931ed3588329511e0b | Python | 6,794 | 212 | import os
import sys
import logging
from deeprvat.data import DenseGTDataset
import yaml
from typing import Dict, Tuple
import itertools
from torch.utils.data import DataLoader
from tqdm import tqdm
import copy
import numpy as np
from pathlib import Path
import pytest
import torch
import zarr
from deeprvat.deeprvat.tr... |
d49c038769602eb09969103fd4cccdeeaaacb4e026d6d966c101e1b183b502d9 | Python | 6,796 | 163 | #!/usr/bin/env python
from __future__ import print_function
import argparse
import glob
import sys
import numpy as np
import pysam
import time
import tempfile
import os
from subprocess import run
from contextlib import closing
from collections import defaultdict
import shutil
import subprocess
is_secondary = lambda x... |
90b809c885fc17eb57b8f8c7625135a3f7aa9674dbcc6199205c663aa2c3f906 | Python | 6,798 | 254 | from attr import dataclass
import ray
from data_assimilation.PDE_models import AdvectionEquation
import numpy as np
import matplotlib.pyplot as plt
import pdb
from matplotlib.animation import FuncAnimation
from data_assimilation.particle_filter_old import ParticleFilter
from data_assimilation.aux_particle_filter import... |
499322418554df81489b44c5adc93b0664b8ce5e820aae17db6ed31ecbd53e75 | Python | 6,799 | 180 | import torch.nn as nn
import torch
from torch import autograd
#把常用的2个卷积操作简单封装下
class DoubleConv(nn.Module):
def __init__(self, in_ch, out_ch):
super(DoubleConv, self).__init__()
self.conv = nn.Sequential(
nn.Conv2d(in_ch, out_ch, 3, padding=1),
nn.BatchNorm2d(out_ch), #添加了BN... |
b93c2e6fee98fadd938123dd31b75fee6249bd060c631b4a1c4e1e671253c1f8 | Python | 6,799 | 168 | """A small, dependency-free text-repel for label placement.
The third-party :mod:`adjustText` computes label positions against the axes
geometry at call time and, in a small or freshly-resized axes, can push labels
far outside the data limits (a volcano panel that ends up 60 mm tall in a
multi-panel figure sends its g... |
242a4668fd96344bf4e9656436c158fd93e37170ffb4ab7ac6363bd249d693f5 | Python | 6,801 | 187 | ####################################################################################################
# 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... |
ca06176b4e6509c870b17c809448572390f6631d78ad76db25a3cf77f1eb75f5 | Python | 6,802 | 165 | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
from typing import Optional, Sequence
import mmcv
import numpy as np
from mmdet.engine.hooks import DetVisualizationHook
from mmdet.structures import DetDataSample
from mmengine.fileio import get
from mmengine.runner import Runner
from mmengine.util... |
b25e84203eb3af598d34376aa93d4ba03156cbd68a18fd70278a78a2f52df2ae | Python | 6,803 | 128 | #!/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
INPUTEVENTS_CV = pd.read_csv("/home/maruthikumar.mutnuri/physionet/files/mimiciii/data/INPUTEVENTS_CV.csv.gz", sep = ',', compression = 'gzip',
... |
0d5df00aaebef50666c24be1a40aae12bd952caf35a73fdfee1e613be2952b5c | Python | 6,805 | 201 | """
Purpose
-------
This script is intended to aid in variant calling. It generates statistics about a given location in a BAM file.
Usage
-----
.. code-block:: bash
stats_at_refpos <bamfile> <regionstring>
Notes
-----
**regionstring**
The region string is a bit confusing if you are unsure what it is... |
5d6c2bd03a08def076189cba89077cb033d9971e91be8ad3e8e5c6996000ccd6 | Python | 6,805 | 183 | from typing import List, Optional, Tuple
import numpy as np
import torch
from .chips import (
Speck2EConfigBuilder,
Speck2FConfigBuilder,
)
from .config_builder import ConfigBuilder
from .utils import parse_device_id
class ChipFactory:
supported_devices = {
"speck2e": Speck2EConfigBuilder,
... |
a45a468fd191b16571d74c97e0e2e9a3f70be9fad229291f3f2d362553fe23cf | Python | 6,805 | 185 | # -*- 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.
#... |
a08a7ef7ed8577a3ad2fe4d7e884f73720696e0c007fd8cd511bbd96cbc1c8c9 | Python | 6,806 | 154 |
import numpy
import time
import random
from pysted import base, utils, raster, bleach_funcs
from pysted.microscopes import DyMINMicroscope, RESCueMicroscope, DyMINRESCueMicroscope
from matplotlib import pyplot
import sys
sys.path.insert(0, "..")
from src.tools import datamap_generator
from src.experiment import Expe... |
b05a3b85521ff39b0ce3a93e07c90ab3046874dce36ecc336a14cf8417550797 | Python | 6,806 | 157 | import numpy as np
import gurobipy as gp
import math
from utils.tool import get_dimension, read_img
def cal_feature(image):
"""优化后的频域特征计算"""
if len(image.shape) == 3:
f = np.fft.fftn(image)
else:
gray = np.mean(image, axis=-1)
f = np.fft.fftn(gray)
f_abs = np.abs(f)
return f... |
5a22cf3b1cacbca49cc32e6eee848d7f82b2ea03364b64b92891747a12fe7088 | Python | 6,807 | 123 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'custom_config.ui'
#
# Created by: PyQt5 UI code generator 5.15.2
#
# WARNING: Any manual changes made to this file will be lost when pyuic5 is
# run again. Do not edit this file unless you know what you are doing.
from PyQt5 import QtCore... |
9b9d5178f94b81ec62058ed3e2f2948a8b3b3eb97566e67d6814befc221fcdcd | Python | 6,809 | 145 | import pandas as pd
import numpy as np
from prepare_and_parse import reidentify_isoform_dataset
def identify_mapt_exon2_3_17(species, gencode):
'''
Aim: Identify from the flattened structure of MAPT (using the parse_gencode_reference()), the exons corresponding to
exon 2, exon 3 and exon 10 in the genome (... |
1988fd1d40daf5535bd2d282acab7202b5e436ab4a2f941e2be775caa7e61aa1 | Python | 6,811 | 156 | import os
import cv2
import numpy as np
import EAV_datasplit
from facenet_pytorch import MTCNN
import torch
class DataLoadVision:
def __init__(self, subject='all', parent_directory=r'C:\Users\minho.lee\Dropbox\EAV', face_detection=False,
image_size=224):
self.IMG_HEIGHT, self.IMG_WIDTH = ... |
58ea5f6b1e28d5179b87bf96ebe9493fe652ff762e55dceb22f49372e2608fde | Python | 6,815 | 218 | """Rendering of circular flash sequences on a hexagonal lattice."""
import logging
from itertools import product
from typing import Dict, List, Tuple, Union
import numpy as np
import pandas as pd
import torch
from datamate import Directory, root
from tqdm import tqdm
from flyvis import renderings_dir
from flyvis.uti... |
8965b7400f12cee4b0cba637238a2aaf5b01696ac02cca6416ecd5e512a68a37 | Python | 6,816 | 216 | """
a shortcut for predicting the context
"""
import torch
import torch.nn as nn
import numpy as np
from utils import to_sqpth, to_sqnp
from sklearn.model_selection import train_test_split
class ShortCut(nn.Module):
def __init__(self, input_dim, output_dim, hidden_dim=128, lr=1e-3,
buffer_size=512, allow... |
e4a639c74a68c5713e72e3e860b63cd9b0313159eed75c358fe47c2732ede798 | Python | 6,817 | 183 | # built-in dependencies
import os
from typing import Any, List, cast
# 3rd party dependencies
import cv2
import numpy as np
from numpy.typing import NDArray
# project dependencies
from deepface.commons.onnx_utils import build_session
from deepface.models.Detector import Detector, FacialAreaRegion
from deepface.common... |
f5e3b3fc55b2083c15964b2341e1f993df35a9c8adfa368c7655f6dd743cd5d8 | Python | 6,817 | 219 | import argparse
import json
import os
import numpy as np
import torch
import pfrl
from pfrl import agents, experiments, explorers
from pfrl import nn as pnn
from pfrl import replay_buffers, utils
from pfrl.q_functions import DistributionalDuelingDQN
from pfrl.wrappers import atari_wrappers
def main():
parser = ... |
32a1ec60fdb2bd3c7792507e70ea78abcbbbd02de25be57620e6c467e4250862 | Python | 6,818 | 193 | """Lightweight MCP client for BioContext biomedical knowledge tools.
Uses the MCP Streamable HTTP transport to communicate with the remote
BioContext server. No external dependencies — only ``urllib.request``
from the standard library.
"""
from __future__ import annotations
import json
import logging
import threadi... |
a91299ad8f305f35160ca9d26aad41b988eaf08468a8328c23a4e10b3a48a95f | Python | 6,818 | 216 | """
a shortcut for predicting the context
"""
import torch
import torch.nn as nn
import numpy as np
from utils import to_sqpth, to_sqnp
from sklearn.model_selection import train_test_split
class NNShortCut(nn.Module):
def __init__(self, input_dim, output_dim, hidden_dim=128, lr=1e-3,
buffer_size=512, all... |
915df1863cea806f027d6462182ab884d14714c6a59f1b069a499feece7e8727 | Python | 6,820 | 158 | ####################################################################################################
# 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... |
d05f2b8e62a366a871807517bcf9d05d77d763a1489062f199c02e1e1d4ce877 | Python | 6,820 | 180 | # 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... |
c76c8adb46b46bc8d5ce63d07900ae55102b8be36c8abefa40260c0b685d7491 | Python | 6,825 | 229 | import json
import sys
from typing import List
import pytest
from ci.ray_ci.automation.determine_microcheck_tests import (
_get_failed_commits,
_get_failed_tests_from_master_branch,
_get_flaky_tests,
_get_test_with_minimal_coverage,
_update_high_impact_tests,
)
from ci.ray_ci.utils import ci_init
... |
6dcd300f17124964b746e70bcfcaf61275d275d2db62d0d3ff4c47888bbc22af | Python | 6,827 | 169 | ####################################################################################################
# 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... |
10a0daa8de31905e4fed00339167004a045fe4348ac358e5454f572a3f281b79 | Python | 6,828 | 189 | """ Calculates word-based phoneme surprisal and entropy for each phoneme in the audiobook segment. """
import os
import json
import numpy as np
import pandas as pd
from tqdm import tqdm
from pathlib import Path
def create_word_phoneme_df(words: pd.DataFrame, phones: pd.DataFrame) -> pd.DataFrame:
""" Builds a Da... |
dfddb6e99952e881e73fcf30989e5233f682ccd153f3b41ec24ef33ec7fc1956 | Python | 6,828 | 208 | import torch
import argparse
import json
import pickle
import numpy as np
from models import PretrainModel, load_model_arch
from utils.data_utils import fix_seed
from utils.chemistry_parse import augment_product_smiles, clear_map_number
from utils.graph_utils import smiles2graph
import torch_geometric
from rdkit impo... |
9614836e3e7c78b7f249a4886c58dcfb973e18a190d0be4cd28b67099ca1b130 | Python | 6,831 | 119 | import datetime
import torch
from torch.nn import LSTM
import torch.nn.functional as F
import numpy as np
from torch.optim import Adam
from pathlib import Path
class ConfigCore():
def __init__(self, data_path='./'):
# network
self.device = 'cuda:0' # 'cuda:0' if uses gpu; otherwise 'cpu'
... |
2af1281052bafbcdceeef93ff2275aad93bafed19d28d9d59d7751ee46c7fb86 | Python | 6,834 | 175 | '''
Optimizer Factory w/ Custom Weight Decay
Modified from timm
Use parameter name to remove weight decay since
tensor product weight is always one-dimensional.
'''
from typing import Optional
import torch
import torch.nn as nn
import torch.optim as optim
from timm.optim.adafactor import Adafacto... |
5c72a5bec91f3cbe8b66f7089ab77325e3ae39098d79f0ad862e78cb93abb9ea | Python | 6,834 | 202 | """Tests for display-independent HTML surface reports."""
import json
import re
import subprocess
import sys
import numpy as np
from brainspace.mesh.mesh_creation import build_polydata
from brainspace.plotting import write_surface_report
def _surfaces():
points_lh = np.array([
[-1.0, 0.0, 0.0],
... |
19e2a7a68c85e57b69c868ea4f3ea18f8ea3dc7108b354dc5ee057007e5a3042 | Python | 6,838 | 180 | """
***
built as part of the Russell Ray Lab Breathing And Physiology Analysis Pipeline
***
Breathe Easy - an automated waveform analysis pipeline
Copyright (C) 2022
Savannah Lusk, Andersen Chang,
Avery Twitchell-Heyne, Shaun Fattig,
Christopher Scott Ward, Russell Ray.
This program is free software: you can redist... |
1b8d9cd757d72efb7e24d878161f2418f2bed8d0ce78726edcfacf791ed1b47c | Python | 6,838 | 128 | import os
import torch
import scipy.ndimage
import numpy as np
import torch.nn as nn
import torch.utils
import nibabel as nib
from utils import orientation, find_bbox
from pytorch3dunet.unet3d.model import UNet3D
from nibabel.orientations import ornt_transform
class InVivoInference():
def __init__(self, devic... |
61d3809d83d2c3ae79a7fdaeb933834048d502af72b53af5f35ba1f658065b04 | Python | 6,838 | 215 | import argparse
import os
# Prevent numpy from using multiple threads
os.environ["OMP_NUM_THREADS"] = "1"
import gym # NOQA:E402
import gym.wrappers # NOQA:E402
import numpy as np # NOQA:E402
from torch import nn # NOQA:E402
import pfrl # NOQA:E402
from pfrl import experiments, utils # NOQA:E402
from pfrl.agen... |
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