sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
23f1f374f3ac255ba2891c9d8f63dfe8d9c5e50f79e4ed1d72c1c7ebe4046496 | Python | 10,153 | 264 | """Test pipeline functionality."""
import re
import pytest
from langchain_core.callbacks.manager import (
AsyncCallbackManagerForChainRun,
CallbackManagerForChainRun,
)
from typing_extensions import override
from langchain_classic.chains.base import Chain
from langchain_classic.chains.sequential import Seque... |
dff73e5691251c5e7f3fad6ba7c3d60a413729ea8ce6e97fb16486ce677722cb | Python | 10,153 | 251 | """Functions for working with guides.
"""
import logging
logger = logging.getLogger(__name__)
# Store the unambiguous bases that make up each
# ambiguous base in the IUPAC notation
FASTA_CODES = {'A': set(('A')),
'T': set(('T')),
'C': set(('C')),
'G': set(('G')),
... |
fac1647e7e3f254330c0f88e92f5db1df9c3477e36e3c4fcb277cd0c93fbc676 | Python | 10,158 | 273 | """Configuration for run evaluators."""
from collections.abc import Callable, Sequence
from typing import Any
from langchain_core.embeddings import Embeddings
from langchain_core.language_models import BaseLanguageModel
from langchain_core.prompts import BasePromptTemplate
from langsmith import RunEvaluator
from lang... |
9f5377000e9c6928cef0bf5f6d9ebeb9a1b44ea1b9e74b3ee10d12f0b8eba213 | Python | 10,160 | 243 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import prl_preprocess_func
__all__ = ['prl_fictitious']
class PrlFictitious(TaskModel):
def __init__(self, **kwargs):
... |
5d4048595c6f6a277f106218f5070dc5eb09eaeef3be3fe2ab992eabb8ffc7cc | Python | 10,162 | 265 | import pickle as pk
import spglib
import numpy as np
from tqdm import tqdm
from pymatgen.core.lattice import Lattice
from pymatgen.core.structure import Structure
from e3nn import o3
from e3nn.io import CartesianTensor
import torch
import json
from pymatgen.io.vasp import Poscar
import pdb
from pymatgen.io.jarvis impor... |
9fefe2552f759f757c05aa4008063d27c9dc12fdc3cad077a6ee005beaa3db50 | Python | 10,167 | 222 | import numpy as np
from pensa import *
from pensa.comparison import *
from pensa.dimensionality import *
import random
import math
"""
Calculates the average and maximum Jensen-Shannon distance and the Kullback-Leibler divergences for each feature from two ensembles. Each of four functions uses the relative_entro... |
ab6b35fc3c66987d28bce586536d36a0bc5ddd837151fba6a860928e7fbb5189 | Python | 10,169 | 357 | '''
cgat_check_deps.py - check whether the software dependencies are on your PATH
=============================================================================
Purpose
-------
.. The goal of this script is to provide a list of third-party command-line
programs used in a Python script given as input, and check whether... |
2202fdb5c249f9279175c52210913f970c00f27c60dd815b9748b8d64f45c771 | Python | 10,172 | 238 | ### MAIN SCRIPT
"""
This is the main collection of functions for processing and analysis of calcium imaging cellsdata in the Packer lab.
The fundamental object of cellsdata is one t-series of imaging, along with its associated .Paq file, accessory files generated
from the microscope during cellsdata collection, and an... |
2bbfa910e429198dab8316b9fb109b272bd4973fd9fd0b5372e7bb759fe7623f | Python | 10,176 | 314 | """Implementation based on the template of ALIGNN."""
from multiprocessing.context import ForkContext
from re import X
import numpy as np
import pandas as pd
from jarvis.core.specie import chem_data, get_node_attributes
# from jarvis.core.atoms import Atoms
from collections import defaultdict
from typing import List, ... |
6007634d368610e86db3046a069514b72f7e5d32e22c4a4365645c54ecabaa64 | Python | 10,178 | 244 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import dd_single_preprocess_func
__all__ = ['dd_cs_single']
class DdCsSingle(TaskModel):
def __init__(self, **kwargs):
... |
8e03e58c19cd4bee7c37eb4e558ffb3d6fdcfafe1832fc5ae2ae98f7f9a4ff53 | Python | 10,178 | 311 | """Implementation based on the template of ALIGNN."""
from multiprocessing.context import ForkContext
from re import X
import numpy as np
import pandas as pd
from jarvis.core.specie import chem_data, get_node_attributes
# from jarvis.core.atoms import Atoms
from collections import defaultdict
from typing import List, ... |
d6162648e7ab47f43d6125c434b35821e240ec51780ccead52cc922b46a1b670 | Python | 10,180 | 287 | """
Generate Python codes for hBayesDM using model information defined in YAML
files.
.. moduleauthor:: Jethro Lee <dlemfh96@snu.ac.kr>
.. moduleauthor:: Jaeyeong Yang <jaeyeong.yang1125@gmail.com>
"""
import sys
import argparse
import re
from pathlib import Path
from collections import OrderedDict
import yaml
try:... |
c1a39f696329c8ead7d82e93c46fdbdb985fdd52ee7f2c2b0b616a935ae46e5f | Python | 10,187 | 236 | #!/usr/bin/env python3
"""
Some code in this script was generated in part with ChatGPT, OpenAI's large-scale
language-generation model. Upon generating draft code, the author reviewed, edited,
and revised the code to their own liking and takes ultimate responsibility for the
content of this script.
"""
import sys
imp... |
d80a67ceb8af44f6252791f13b9b23f645cd09ee4cc344f225d9317a413f3731 | Python | 10,188 | 257 |
from jsonargparse import ArgumentParser, ActionConfigFile
r"""An important module that is used to define all arguments for both argument container and configuration container.
"""
import pathlib
import sys
from typing import List
from tap import Tap
from typing_extensions import Literal
from dataclasses import datacl... |
b70d906e1076f8fff25adb0164248b4c1593f65ce07794d7e057618bb56c4318 | Python | 10,190 | 160 | import argparse
import os
from util import util
import torch
import models
import data
os.environ["CUDA_VISIBLE_DEVICES"]="0"
class BaseOptions():
"""This class defines options used during both training and test time.
It also implements several helper functions such as parsing, printing, and saving the option... |
b5ade591db30bdf217d814abd9b4aa3eecdbecdfb5b334c3ac6593d4c1565737 | Python | 10,192 | 364 | import os
import re
import nibabel as nib
import matplotlib.pyplot as plt
import numpy as np
from tqdm import tqdm
from nilearn import plotting
from skimage import morphology
def rescale(array, tup) -> tuple:
"""
rescale Feature scales image to range tup
_extended_summary_
Parameters
----------
... |
39a0395d9d4d1f19512d49cc92d5cd77ae7a30e4a0b9d56f201c97a502260500 | Python | 10,193 | 304 | import torch.nn.functional
import torch_scatter
import e3nn
from e3nn import nn, o3
from .embs import MLP
from .irreps_tools import (
reshape_irreps,
get_feasible_irrep,
recollect_features,
)
from .symmetric_contraction import SymmetricContraction
class EdgeBoosterBlock(torch.nn.Module):
def __init__... |
10d7cf7f4b0e46fb6c1b58c31d126c47e3bed5721d285e6bd773c4645552a515 | Python | 10,198 | 139 | """Figures for corpus B (raw-curve corpus): physics indicators, twelve datasets, K = 11 calibration, cell-level CV+.
fig15_physics.pdf (a) MAPE by protocol and feature set, four-dataset subset and twelve-dataset corpus (log scale)
(b) P4 error per held-out dataset, statistics against st... |
16bd90fc3bc501083f16d2f221f5e485d054c9d1b12b4fc2476532eed1b55428 | Python | 10,211 | 281 | # Copyright (c) 2008-2026 the MRtrix3 contributors.
#
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/.
#
# Covered Software is provided under this License on an "as is"
#... |
3604f60bb45bd561307c4bf84a44c64cb5468101eeddbe8988d1319fc1343be2 | Python | 10,211 | 291 | import os
from typing import Dict
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import tabulate
import torch
import torch.nn as nn
import torch.optim as optim
from sklearn.metrics import classification_report
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWr... |
e2f90bfe4dc9446ec4ff199cfed1b08a8b0ead8764eb05ac0aff083945e580f5 | Python | 10,212 | 238 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import pst_preprocess_func
__all__ = ['pst_Q']
class PstQ(TaskModel):
def __init__(self, **kwargs):
super().__ini... |
cfafa867f56163ef6bb7b39572138695b303e7413f4f29b960e24d3bac628349 | Python | 10,213 | 237 | import os
# from config import args
import pandas as pd
from miga_emblaze.emblaze import ProjectionTechnique
from utils.distribution import DeviceManager
os.environ['RANK'] = '-1'
DeviceManager('1')
from collections import OrderedDict
import cv2
import umap
from rdkit.Chem import AllChem
from rdkit.Chem import Draw... |
26cc08bf5ee0a259b8467e8caebb8af6f5d6b7964f3115072b1a7b2e29f39108 | Python | 10,216 | 263 | # this script inference based on trained models
# Mask-RCNN on detectron2:
# the folder structure should be:
# data/test (images)
# pretrained: the pretrained model model_best.pth
# Running:
# module load Detectron2/0.3-fosscuda-2019b-Python-3.7.4-PyTorch-1.6.0
#
import argparse
import os
import random
import shu... |
3d3be4357a888e9fd94613df07b69b1fecb55dd861cf790c01432f3ec184cca6 | Python | 10,216 | 210 | """
Parameters used for analysis of 2p and behavioural data.
Author: jonas.braun@epfl.ch
"""
import os
import matplotlib.pyplot as plt
from datetime import date
today = date.today().strftime("%y%m%d")
"""
# FH version
# handling summary data of all recording
data_summary_dir_JB = "/mnt/nas2/JB/_data_summary"
data_s... |
a29d63a169098b02f28404f43933f4f35c88d2e068d40f416aa59eccae2129c1 | Python | 10,224 | 183 | import torch.nn.functional as F
import torch
import torch.nn as nn
from models.GFNO import GConv2d, GConv3d, GMLP2d, GMLP3d, GNorm
from functools import partial
# ----------------------------------------------------------------------------------------------------------------------
# GCNN2d
# ---------------------------... |
2681e1c9e155391eeebe0c6743e65fcf47397d0f4b61b04b2e7d6e50f75e1e98 | Python | 10,225 | 323 | # -*- coding: utf-8 -*-
"""
Methods to obtain a distribution for the water pockets which respresents
a combination of the water occupancy (binary variable) and the water polarisation (continuous variable).
For a water molecule to exist within a water pocket, just the oxygen must occupy the pocket.
If there is ever an... |
a01ff7b9f7c579e71b970ce205e02aa954c01099403c81d9618587b370771444 | Python | 10,226 | 267 | """Tests for SSRF protection utilities."""
import socket
from collections.abc import Iterator
from typing import Any
from unittest.mock import patch
import pytest
from pydantic import BaseModel, ValidationError
from langchain_core._security._ssrf_protection import (
SSRFProtectedUrl,
SSRFProtectedUrlRelaxed,... |
1370154d8237fc060c47514d09688b4fab24eea99556262f1e291f5cf45d6ed7 | Python | 10,228 | 258 | import numpy as np
import csv
import pandas as pd
import os
from argparse import ArgumentParser
from utils.util import print_environ
import nibabel as nib
from scipy.ndimage import zoom
from icecream import ic
from tqdm import tqdm
brain_regions = {1.:'TL hippocampus R',
2.:'TL hippocampus L',
3.:'TL amygdala R',
4.:'... |
046773c769b51ec7099cdc6db1a2e6bf9031a0ec253d6a69e5f045d6669780a4 | Python | 10,229 | 241 | # -*- coding: utf-8 -*-
"""
Created on Thu Apr 23 11:36:41 2020
@author: gritti
"""
import sys, time, tqdm, copy, os
sys.path.append(os.path.join('..'))
from orgseg.ImageTools.morphology import meshgrid
from orgseg.DatasetTools.straightmorphology import io as ioStr
from orgseg.DatasetTools.morphology import io as io... |
e6513c7fe6e26680541af03cf84fc5bb6b8c235b2e060dfaecc24ab899337e6c | Python | 10,232 | 267 | # Copyright (c) MONAI Consortium
# 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, so... |
68e7efac3d23dc991189a152a8121000e7546b55896ca6d7cd8bba48f8b3ef93 | Python | 10,237 | 283 | # Copyright 2020 DeepMind Technologies Limited.
#
# 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... |
e5cc2a34c465d039f590f2e16414cd08f2be346028ca82a1a3ef0647259f8b03 | Python | 10,237 | 251 | """tests for api/routers/longitudinal.py's LongitudinalMeshRef.template
support - the "distance heatmap" overlay's custom-reference mode (see the
Longitudinal workspace's 3D Morphing tab) needs to diff an arbitrary
NICP-fit session against a bare shipped template, not just another
session. self-contained rather than im... |
9951e0704ddb9d7b9e19c99395f2100a4b196a06757ca74e2c5b7e92721267ff | Python | 10,240 | 253 | from copy import copy
import numpy as np
import pandas as pd
from patsy import PatsyError
from patsy import dmatrix
from statsmodels.stats.multitest import multipletests
def Spline_Model_Full(self, pdata, df):
"""
Natural Cubic Spline
This algorithm perform the Natural Cubic Spline regression
Args:
... |
9f1af44ee204121a1b890b08c89aabe6365f9c5ca2e6201ff3fde05acf07bc7f | Python | 10,247 | 309 | import os
import numpy as np
import mne
class EEGLoader():
""" Class to load raw EEG data.
The EEG data is loaded and bad as well as reference channels are set based on previous visual
data inspection. The reference channels are set to the average mastoids or to T7 and T8, depending on the subject.
... |
1dea65833f46cdc5bc15b22e9dab81584174953e1c594ac484a56cc28975be19 | Python | 10,258 | 249 | #!/bin/env python
import numpy as np
from openff.toolkit.typing.engines.smirnoff.forcefield import ForceField
# Function definitions for parsing sections within parameter file
def _parse_nonbon_line( line ):
"""Parse an AMBER frcmod nonbon line and return relevant parameters in a dictionary. AMBER uses rmin_half ... |
32112569e5702aa5614fc67e19309c1cf20e9760622dd1db553f48840066faf1 | Python | 10,266 | 244 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import bandit4arm2_preprocess_func
__all__ = ['bandit4arm2_kalman_filter']
class Bandit4Arm2KalmanFilter(TaskModel):
def ... |
7857272a6a2a98075cf823a8b59f9ec6ab2d408c7bf4d6c21f026a226f6b3350 | Python | 10,270 | 291 | """
Sei architecture (see https://github.com/FunctionLab/sei-framework for more details)
"""
import numpy as np
import torch
import torch.nn as nn
from selene_sdk.utils import NonStrandSpecific
import numpy as np
from scipy.interpolate import splev
def bs(x, df=None, knots=None, degree=3, intercept=False):
"""
... |
e646089b43960d63dad1a21bfe271636e600f5383bc842a3d949c404927ef173 | Python | 10,270 | 243 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import prl_multipleB_preprocess_func
__all__ = ['prl_rp_multipleB']
class PrlRpMultipleb(TaskModel):
def __init__(self, *... |
85fd4edceef10a1c93b51877397283746e177f85a7198d9dfb640bd6963dc505 | Python | 10,271 | 310 | """
===============================================================================
File: painn
Date: 6/16/2024
Description: Code is adapted from PaiNN OC20 implementation https://github.com/facebookresearch/fairchem/tree/fairchem_core-1.10.0/src/fairchem/core/models/painn.
All rights reserved t... |
fd2139ee16c2438c472b5aa8da7a7cd2147ec68a092e4d19dab4ac90355ef675 | Python | 10,272 | 204 | ''' Test module for RBM estimators.
:Version:
1.1.0
:Date:
04.04.2017
:Author:
Jan Melchior
:Contact:
JanMelchior@gmx.de
:License:
Copyright (C) 2017 Jan Melchior
This file is part of the Python library PyDeep.
PyDeep is free so... |
baf8e968d144d8ee585adfe055256ef82a80fa2a7a1f6e019ba00a24d9e320ba | Python | 10,276 | 248 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import gng_preprocess_func
__all__ = ['gng_m3']
class GngM3(TaskModel):
def __init__(self, **kwargs):
super().__i... |
81fb137f8b499d42caea32df8fdc85380ce4c8bc7ca9b84cae4985fe5da367de | Python | 10,277 | 283 | # Copyright (c) MONAI Consortium
# 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, so... |
509de3a41ecc7c23aeba05fce86977cb25d39e834f878f8ca3ce46a517ee42cf | Python | 10,278 | 248 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import peer_preprocess_func
__all__ = ['peer_ocu']
class PeerOcu(TaskModel):
def __init__(self, **kwargs):
super(... |
e0c611cb9354610ca336a7cb3078bf5ba0df87cb18ab0cba73d93d3dbe6c215e | Python | 10,278 | 179 | # Copyright 2020 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 of the License at
#
# http://w... |
d1d4698e7181525457efeebe3fafcc2831fab3948128af415f7e557fd09d7377 | Python | 10,279 | 244 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import igt_preprocess_func
__all__ = ['igt_pvl_delta']
class IgtPvlDelta(TaskModel):
def __init__(self, **kwargs):
... |
ea1b07a569766998f7682e4cb057553f2aba76388b33c25b117b89bd6ffc1e31 | Python | 10,282 | 228 | """
Runs a simulation with OpenMM.
"""
import sys
# Configure logging
import logging
from rich.logging import RichHandler
FORMAT = "%(message)s"
from rich.console import Console
logging.basicConfig(
level=logging.INFO, format=FORMAT, datefmt="[%X]", handlers=[RichHandler(markup=True)]
)
log = logging.getLogger("ri... |
a28a01ce3e6cf2add09f478a162d6d1427d5490be135b9d88a41f0053ee6d6f0 | Python | 10,286 | 276 | # coding: utf-8
import os
import tensorflow as tf
import keras
from absl import flags
from absl import app
from dlutils.layers.input_scaler import ScalingLayer
from dlutils.models.unet import GenericUnetBase
from retchat.callbacks import CosineAnnealingSchedule
from retchat.callbacks import ExtendedTensorBoard
from... |
f3c9f74c549c25d54ada9d8efaee2e2dffc6476bf45ff304ff6b7a844cea9b9e | Python | 10,286 | 279 | from ChipseqReport import *
class TrackerROI(TrackerSQL):
def getTracks(self, subset):
return self.getValues("SELECT DISTINCT(class) FROM regions_of_interest")
##########################################################################
#####################################################################... |
4e62ed588ba74d0a84f42c00fea01967b419b0424d5d9ff3cc607d49d9f39c44 | Python | 10,287 | 276 | # coding: utf-8
import os
import tensorflow as tf
import keras
from absl import flags
from absl import app
from dlutils.layers.input_scaler import ScalingLayer
from dlutils.models.unet import GenericUnetBase
from retchat.callbacks import CosineAnnealingSchedule
from retchat.callbacks import ExtendedTensorBoard
from... |
32200e9379d86e157016835522f218ece9a9305528b061ceb836160c9d798458 | Python | 10,293 | 174 | import numpy as np
import pandas as pd
import pytest
from skbase.utils.dependencies import _check_soft_dependencies
from sklearn.base import BaseEstimator, ClassifierMixin
from sklearn.dummy import DummyClassifier, DummyRegressor
from sklearn.ensemble import HistGradientBoostingClassifier, RandomForestRegressor
from sk... |
a2fde23c37045658514b206e1ee4f22ea0a98e9c52d6c07a0ecbc095c70b8ce5 | Python | 10,295 | 338 | # -*- coding:utf-8 -*-
"""
A file for utilities used in other files.
Methods:
segment_words
"""
import sys
import random
import numpy as np
reload(sys)
sys.setdefaultencoding('utf-8')
random.seed(1)
###############
# English pre-processing
###############
def tokenize_sentence(senlist, choice="string"):
im... |
e4764ede6da7ec6ae9388c5590b0ce07ea879a137e77ab89717ce97a900ac249 | Python | 10,302 | 235 | from pgmpy.base import ADMG, DAG
from pgmpy.identification import BaseFormulaIdentification
from pgmpy.identification.probability_expression import (
DivisionNode,
ProbabilityExpressionTree,
ProbabilityNode,
ProductNode,
)
class ID(BaseFormulaIdentification):
r"""
Given a causal graph, identif... |
60b224d57fe7a508a88f2ee7bad217f5996ddfcd005aa59e63386bf215382fa3 | Python | 10,308 | 262 | import torch
import torch.nn.functional as F
from ogb.graphproppred.mol_encoder import AtomEncoder, BondEncoder
from torch_geometric.nn import MessagePassing
from torch_geometric.nn import global_add_pool, global_mean_pool, global_max_pool, GlobalAttention, Set2Set
from torch_geometric.utils import add_self_loops
from... |
8bb8fa28bf95b65b9d704e51275a5f6e881dac9b9d44e71042373a7d0eb6fe01 | Python | 10,308 | 247 | import random
from collections import defaultdict
from itertools import compress
import numpy as np
import torch
from rdkit.Chem.Scaffolds import MurckoScaffold
from sklearn.model_selection import StratifiedKFold
def generate_scaffold(smiles, include_chirality=False):
""" Obtain Bemis-Murcko scaffold from smiles... |
e1f531d1f8837ec94485a76f3fa0356ef00dc303d37fe7b9fcb26fc73b9ccc2d | Python | 10,313 | 352 | # -*- coding: utf-8 -*-
"""
Created on Thu Oct 25 11:43:39 2018
@author: 2624224
"""
import random
import os
import sys
from OCC.Core.TopExp import TopExp_Explorer, topexp, topexp_MapShapesAndAncestors
from OCC.Core.TopAbs import TopAbs_FACE, TopAbs_REVERSED, TopAbs_EDGE, TopAbs_VERTEX
from OCC.Core.TopoDS import top... |
6f81e74264ad5fc69bcaf9a069080fc23ad9db262625192dcf60ec767e355b67 | Python | 10,314 | 209 | import torch
import torch.nn as nn
import torch.nn.functional as F
"""Springer2023
最近，深度学习已被证明在多视角立体视觉 (MVS) 中表现出色。然而，基于深度学习的 MVS 方法很难平衡其效率和有效性。为此，我们提出了 DSC-MVSNet，这是一种新颖的粗到精和端到端框架，用于在 MVS 中更高效、更准确地估计深度。
具体来说，我们提出了一种注意力感知的 3D UNet-shape 网络，它首先使用深度可分离卷积进行成本体积正则化。该机制通过将成本体积上的普通卷积转换为深度卷积和点卷积，实现了信息的有效聚合，并显著减少了模型参数和计算量。
此外... |
59ad4a3884cf9d8be50ed7bbd2c5058439f3cdcbb3031e2826cfc5e26c879d14 | Python | 10,322 | 278 | ####################################################################################
#
# STEPS - STochastic Engine for Pathway Simulation
# Copyright (C) 2007-2023 Okinawa Institute of Science and Technology, Japan.
# Copyright (C) 2003-2006 University of Antwerp, Belgium.
#
# See the file AUTHORS for d... |
219952463f43b30237e5fc20d2678aa2a9c607b28c82984f61af307633820864 | Python | 10,329 | 270 | from sumstats import Sumstats
from trace import Trace
import time
import datetime
import numpy as np
import os
def _get_time():
"""Return current epoch time (float)."""
return time.time()
def _get_timestr(current_time):
"""Format a timestamp with local timezone."""
timezone = datetime.datetime.now(d... |
6e11fb445d31706bbee70e62be049adbd7e841eae14ab3986d9ee2ff29148daa | Python | 10,333 | 211 | import logging
import sys
import argparse
from datetime import date
import json
import numpy as np
import torch
from torch.optim import lr_scheduler
import monai
from monai.transforms import \
Compose, ToTensord, AddChanneld, EnsureTyped, NormalizeIntensityd, \
RandFlipd, RandZoomd, RandAffined, RandAdjustCon... |
a467eebedddb98c08335822c96f041fb7b871324807164912596c8fb0e2c9814 | Python | 10,337 | 247 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import cra_preprocess_func
__all__ = ['cra_linear']
class CraLinear(TaskModel):
def __init__(self, **kwargs):
sup... |
65706c13663a33aeab5ec770d43628bcf23e59b4ca724e4235471bdce47e21de | Python | 10,342 | 274 | """Private helpers for resolving LangSmith gateway configuration.
The [LangSmith LLM gateway](https://docs.langchain.com/langsmith/llm-gateway)
lets a chat model reach a provider through a proxy configured via environment
variables. These helpers centralize the (non-trivial) precedence rules so that
each provider inte... |
0f5286257608618ba42af43c0e3862e3f2f6886213f0bc092e23597378a621cb | Python | 10,347 | 244 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import banditNarm_preprocess_func
__all__ = ['banditNarm_4par']
class Banditnarm4Par(TaskModel):
def __init__(self, **kwa... |
aa37412e41d25020a259f0191e7615bf56ce7d83125d0a68f5a47349cc86ab9a | Python | 10,347 | 247 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import cra_preprocess_func
__all__ = ['cra_exp']
class CraExp(TaskModel):
def __init__(self, **kwargs):
super()._... |
4ae97c4b01cb3abb781cf3a13ee3e2dcc0e0faea881cee45a2e4e78058a12b3d | Python | 10,348 | 290 | import os
import numpy as np
import scipy.stats as stats
import matplotlib.pyplot as plt
import pandas as pd
from net_utils import load_from_file
from plotting import get_all_pkl, plot_recog_generalization, plot_recog_positive_rates
from data import generate_recog_data
def plot_fit(X, Y, ax=None, color=No... |
9f948a4c44f381cf1655793876c5b73953e86b7c8adc5c827386e63bed475117 | Python | 10,348 | 326 | """
##############################################################################
#
# Prepare tables for samples' Z-scores heatmaps (all windows/all sites)
#
# AUTHOR: Maciej_Bak
# AFFILIATION: University_of_Basel
# AFFILIATION: Swiss_Institute_of_Bioinformatics
# CONTACT: wsciekly.maciek@gmail.com
# CREAT... |
3ec111dada14a7043569d4a23878b6559252ae1b864410af16321077ed95dd1c | Python | 10,349 | 345 | import random
import numpy as np
import os
import torch
import torch.nn.functional as F
import csv
import datetime
import pandas as pd
def current_time():
return datetime.datetime.now().strftime("%Y-%m-%d_%H.%M.%S")
def cv_shuffle(pos, neg, shuffle):
pass
def fix_seed(seed):
"""
Seed all necessary... |
a23da557e6ac1187f8fe6217a9d30642c86246a2dfb7a1d2920fddcc58fc5af7 | Python | 10,351 | 294 | import numpy as numx
import pydeep.base.numpyextension as numxExt
import pydeep.misc.io as IO
import pydeep.misc.measuring as MEASURE
import pydeep.misc.visualization as VIS
from pydeep.base.activationfunction import Sigmoid
def binary_unit(activation):
return numx.float64(Sigmoid.f(activation) > numx.random.ran... |
da399f3b307f4908b82bb08b3fef487f345a1a59465b54989219542eb2bbf598 | Python | 10,358 | 246 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import bandit4arm_preprocess_func
__all__ = ['bandit4arm_lapse_decay']
class Bandit4ArmLapseDecay(TaskModel):
def __init_... |
d1cefaa17c62c8addf0e949a5252337e252681673ec40453a47597796247e185 | Python | 10,363 | 228 | import bisect
import collections
import torch
from .interp import _interp_evaluate, _interp_fit
from .misc import (_compute_error_ratio,
_select_initial_step,
_optimal_step_size)
from .solvers import AdaptiveStepsizeODESolver
_ButcherTableau = collections.namedtuple('_ButcherTabl... |
2e75ec041a3d956a392d0278e1ca2c10ac5a9e00a4bc856549dbedd0ebaace29 | Python | 10,364 | 302 | from pycromanager import multi_d_acquisition_events
import numpy as np
import pytest
x = np.arange(0, 5)
y = np.arange(0, -5, -1)
z = np.arange(0, 5)
xy = np.hstack([x[:, None], y[:, None]])
xyz = np.hstack([x[:, None], y[:, None], z[:, None]])
labels = [f'Pos{i}' for i in range(5)]
def test_xy_positions():
exp... |
ef38ab793ad7439cf412170b0b683ef0eb10c9ff3617a78194a6a814474d94b1 | Python | 10,365 | 272 | """Optional caching layer for language models.
Distinct from provider-based [prompt caching](https://docs.langchain.com/oss/python/langchain/models#prompt-caching).
!!! warning "Beta feature"
This is a beta feature. Please be wary of deploying experimental code to production
unless you've taken appropriate p... |
9be7406f0a86d8bd610bbe28ea86900d2254fba53cc70d87a1c45ba75dd0b59c | Python | 10,366 | 274 | # pylint: skip-file
import copy
from absl.testing import absltest
import numpy as np
import torch
import pytest
from .embanded_torch import EMBanded
class EMBandedTests(absltest.TestCase):
"""Test cases for EMBanded."""
def test_compare_model_settings(self):
"""Fit models with different settings and... |
8f7fe38f4e86b2ea3a272b9d2c7c5cb5942dbda8526ae92345b9f52f5e8f21f6 | Python | 10,370 | 194 | import os
import numpy as np
from tqdm import tqdm
from torch.utils.data import Dataset
class S3DISDataset(Dataset):
def __init__(self, split='train', data_root='trainval_fullarea', num_point=4096, test_area=5, block_size=1.0, sample_rate=1.0, transform=None):
super().__init__()
self.num_point = ... |
8809bbcca8726a3f42cc29aeded677d1d702213e96d31120ba773c1110497658 | Python | 10,378 | 368 | """Plasticity using SNN. Section ...."""
import csv
import dataset
import model
import matplotlib.pyplot as plt
import trainer
import torch
def convergence(
device,
elastic_modulus,
batch_size,
num_samples_train,
num_samples_val,
num_samples_test,
hidden,
epochs,
):
"""Convergence ... |
d09edf34e5311d97d99a4ba9573da550fa31cae71a2c1b01df9f7986d53c7dbf | Python | 10,382 | 332 | import colorsys
import cv2
import matplotlib.pyplot as plt
import numpy as np
import torch
import torch.nn.functional as F
from .io import *
# core utilities for ZephIR
def blur3d(input_tensor, kernel_size, sigmas, dev=torch.device('cpu')):
return F.conv3d(
input_tensor.view(-1, *input_tensor.shape[2:]),... |
6250627f782d52bcb9a587c5c9df27feb96ea36e93678936359b7fa7599e6b07 | Python | 10,384 | 340 | import math
import numpy as np
import numba as nb
import Utils.numba_vec as nbv
@nb.njit(fastmath=True)
def search_rect_inside_bound_1(verts, vec1, vec2, bnd_pnts):
in_pnts = points_in_polygon(bnd_pnts, verts)
if in_pnts.shape[0] == 0:
return verts
# find perpendicular unit vector of normal and l... |
dd5f12686cb800ef59ea947136f4bfa15f1b5074d95bfeb7eaf70e9d0d75735f | Python | 10,384 | 285 | # t-leNet model: t-leNet + WW
import tensorflow.keras as keras
import tensorflow as tf
import numpy as np
import time
from utils.utils import save_logs_t_leNet as save_logs
from utils.utils import calculate_metrics
class Classifier_TLENET:
def __init__(self, output_directory, verbose,build=True):
s... |
94bc54b0a2a481d54394163b32e5a6e71d378d4d2a274a70bd751ec59b3cf583 | Python | 10,385 | 289 | """
Algorithm introducing volumes of 33 barrel columns coming from segmentation of the
average brain atlas images from Allen institute. Barrel columns are introduced as children
to somatosensory area of barrel cortex and then subdivided into layers. Each barrel is
subdivided into layers.
* Introduction of barrels to ... |
2daad25cddfa22880265e0088bc92676967a01101c8ed66de2ddb07d41a5d8ff | Python | 10,389 | 276 | """
Given a (k-mer incomplete-trained) methylated 6-mer pore model, expand using NN to learn parameters for missing k-mers.
By default, only update parameters for methylated CpG k-mers which were not updated during initial training.
"""
import sys
from itertools import product
import numpy as np
import pandas as pd
... |
fdf582d79d8626eb09d5d4ebdc927e6c46c401996ac412122cdabd56d9b8feb2 | Python | 10,390 | 362 | import torch
import numpy as np
import torch
import math
from scipy.stats import truncnorm
from typing import Optional, Callable, List
def _standardize(kernel):
"""
Makes sure that Var(W) = 1 and E[W] = 0
"""
eps = 1e-6
if len(kernel.shape) == 3:
axis = [0, 1] # last dimension is output ... |
a484e2b060e69f2871754c32508bdb0e0d0e3caf649585d92be4c3c3c25fe9f6 | Python | 10,392 | 266 | import os
import sys
import re
import types
import itertools
import matplotlib.pyplot as plt
import numpy
import scipy.stats
import numpy.ma
import Stats
import Histogram
from cgatReport.Tracker import *
from cpgReport import *
##########################################################################
class replica... |
7b539f59583ca1cd3d7d5e24d51062352af227b351ac99c3b0989a642d66118a | Python | 10,394 | 232 | import argparse
from os.path import join
import torch
import pickle
from qm9.models import get_model
from configs.datasets_config import get_dataset_info
from qm9 import dataset
from qm9.utils import compute_mean_mad
from qm9.sampling import sample
from qm9.property_prediction.main_qm9_prop import test
from qm9.propert... |
665cdb8cb5ec64cc0af7724f46e09547a6b0bd438ee37ce929f98b57a0cfdaf5 | Python | 10,400 | 308 | import numpy as np
import numpy.testing as np_test
import pytest
from pgmpy.factors.discrete import DiscreteFactor, TabularCPD
from pgmpy.inference import VariableElimination
from pgmpy.models import DiscreteBayesianNetwork
@pytest.fixture
def sn2():
return {
"grade": ["A", "B", "F"],
"diff": ["h... |
0ed7978ff5ca0556d9359290dd8f2c0887f827ab98da89a040050275fecf012e | Python | 10,402 | 270 | from torch import nn
import torch
# egnn code is adapted from:
# https://github.com/vgsatorras/egnn/blob/main/models/egnn_clean/egnn_clean.py
# https://github.com/arneschneuing/DiffSBDD/blob/main/equivariant_diffusion/egnn_new.py
class E_GCL(nn.Module):
"""
E(n) Equivariant Convolutional Layer
r... |
1cf5ebeac44453625ad302cc140f19a56b3bfaec00fc6acc09e6734b3d9d4aca | Python | 10,402 | 250 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import gng_preprocess_func
__all__ = ['gng_m4']
class GngM4(TaskModel):
def __init__(self, **kwargs):
super().__i... |
9e228b0025c503fdddf2b88b153d130e023ea52de4de930b6244b269ab0ea71b | Python | 10,403 | 245 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import prl_multipleB_preprocess_func
__all__ = ['prl_fictitious_multipleB']
class PrlFictitiousMultipleb(TaskModel):
def ... |
a99e71f7d05b75770c77591cb606106430ab209ef815f5e91993916d4d8f06cf | Python | 10,404 | 246 | # -- coding: utf-8 --
# @Time : 2022/12/14 17:06
# @Author : Biao Zhang
# @Email : littlebiao@outlook.com
# @File : run_srrsc_6regions.py
# -- coding: utf-8 --
# @Time : 2022/10/18 16:19
# @Author : Biao Zhang
# @Email : littlebiao@outlook.com
# @File : run_analysis.py
import sys
sys.path.append('../../../')
from Bra... |
9ff0d9847e0e34e81bce4b761458ee6f409ad3c450624988ec586857bd183841 | Python | 10,405 | 366 | """Draws DAG in ASCII.
Adapted from https://github.com/iterative/dvc/blob/main/dvc/dagascii.py.
"""
from __future__ import annotations
import math
import os
from typing import TYPE_CHECKING, Any
try:
from grandalf.graphs import Edge, Graph, Vertex # type: ignore[import-untyped]
from grandalf.layouts import... |
3ed7fa43e28f8f5aa8c171c959ad71882ed9624bab72f1ac128ace157f53b18b | Python | 10,406 | 241 | from typing import Sequence, Union, Any
from collections import OrderedDict
from numpy import inf, exp
import pandas as pd
from hbayesdm.base import TaskModel
from hbayesdm.preprocess_funcs import banditNarm_preprocess_func
__all__ = ['banditNarm_delta']
class BanditnarmDelta(TaskModel):
def __init__(self, **k... |
c90fee1147b70372855d372e1d6dbe1d9448f53a869cff3cf6b6e626b2f0dde6 | Python | 10,407 | 277 | """Checkpoint helpers for warm-start / finetune (weights-only load)."""
from __future__ import annotations
import logging
import shutil
from pathlib import Path
from typing import TYPE_CHECKING, Any, Dict, Optional, Tuple, Union
import torch
from lightning.pytorch import LightningModule
if TYPE_CHECKING:
from li... |
67ca2fb6adc706c7b9c33e59523d69a22ffb0c9111ad3130db2f797efc9c4032 | Python | 10,408 | 288 | import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision
import numpy as np
import matplotlib.pyplot as plt
import math
########################
# debug
########################
from utils.tensor_operator import sigmoid_with_clamp
def get_feature(feature):
return np.squeeze(feature.c... |
c4132b2999618bc779e41ffb7da8499ace70257df27fb8c2c0790e38221884f9 | Python | 10,412 | 272 | from rdkit import Chem
import os
import numpy as np
import torch
from torch.utils.data import BatchSampler, DataLoader, Dataset, SequentialSampler
import argparse
import collections
import pickle
import os
import json
from tqdm import tqdm
from IPython.display import display
from matplotlib import pyplot as plt
import ... |
28afef2cdd781e08fd3a19029df13ed32da3c76bb23b7f9720af6788d27591ae | Python | 10,418 | 294 | """Set of tests that complement the standard tests for vectorstore.
These tests verify that the base abstraction does appropriate delegation to
the relevant methods.
"""
from __future__ import annotations
import uuid
from typing import TYPE_CHECKING, Any
import pytest
from typing_extensions import override
from la... |
e321397c82063ea3fc9b1892d9d7985b860883d252fd17091bc0aad7a1cf783d | Python | 10,421 | 318 | import pickle
import pandas as pd
import numpy as np
import torch
import os
from sklearn import metrics
import matplotlib.pyplot as plt
import seaborn as sns
import datetime as dt
# Straight up stolen from main.py
def calc_roc_auc(gts, probs):
try:
auc = metrics.roc_auc_score(gts, probs)
if np.isn... |
39e0042ed63b60d50cfcbfc8396ce80ae9871fe919a97dd144cbdb2b801eebd7 | Python | 10,429 | 275 | """
This script aims to convert BRAT format data into BIO format data for NER
Entities will be mapped from their original offsets to the new offsets after sentence tokenization
Two sentences are separated by a empty line
entities and relations information are also provided in json format
"""
import os
import sys
impor... |
157cb47c48960a7a90ee571c425877e743f0800137503e125b0d3c34af43f0b3 | Python | 10,431 | 319 | import argparse
import os
import matplotlib.pyplot as plt
import numpy as np
import torch
from torchvision import transforms
from tqdm import tqdm
from bindsnet.analysis.plotting import (
plot_assignments,
plot_input,
plot_performance,
plot_spikes,
plot_voltages,
plot_weights,
)
from bindsnet.... |
75b0d92cb80c1e8fe8993ec7fee4c0b3f03341748e9f90b4337dde7dd64fe670 | Python | 10,431 | 297 | import math
from typing import Tuple, Union, Callable
import inspect
import numpy as np
import torch
import torch.nn as nn
from sam.coords import calc_dmap, torch_chain_dihedrals
from sam.nn.common import get_act_fn, AF2_PositionalEmbedding
from sam.nn.geometric import GaussianSmearing, ExpNormalSmearing
from sam.nn... |
c65b7dd29cc7639b467ca1b24277865ad4e8779eb90eeba62ee2d81af6a502a1 | Python | 10,436 | 321 | # -*- coding: UTF-8 -*-
"""
@author: Xingyan Liu
@file: utils.py
@time: 2021-06-12
"""
from typing import Union, Sequence, Optional, Mapping, Dict, Any, List, Callable
import logging
import numpy as np
import torch
from scipy import sparse
import torch as th
from torch import Tensor
import torch.nn as nn
import dgl
i... |
59d8d874b08780ff8ed813db7721e5a1706b6d774e4da0e8e322f0fe06cfbb48 | Python | 10,443 | 263 | import tkinter as tk
from tkinter import filedialog
import io,os,sys,shutil, argparse, requests
sys.path.append(os.path.dirname(__file__))
from load_save_helpers import create_sparse_default_params, save_parameters, load_parameters
from BBHP_function import param_types, BBHP
from PIL import Image
base_param_name = 'bas... |
db701d74bc06ba63fbfe2d957780d27a84c3e3ada09a70a02b84a50799149d7e | Python | 10,444 | 321 | # -*- coding: UTF-8 -*-
"""
@author: Xingyan Liu
@file: utils.py
@time: 2021-06-12
"""
from typing import Union, Sequence, Optional, Mapping, Dict, Any, List, Callable
import logging
import numpy as np
import torch
from scipy import sparse
import torch as th
from torch import Tensor
import torch.nn as nn
import dgl
i... |
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