sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
9c504203795285dc547aa3f8996db36f6c88918f3182c0c3dab9ec4a67930652 | Python | 27,854 | 839 | # Copyright 2018-2026
# Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH
# 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/LICE... |
f2728aa5d53cd73a2a2f167d59e789292785eb58d7f0aab44266918c1a82a54c | Python | 27,857 | 841 | import colorsys
from itertools import cycle
import numpy as np
import matplotlib as mpl
from .external import husl
from .utils import desaturate, get_color_cycle
from .colors import xkcd_rgb, crayons
from ._compat import get_colormap
__all__ = ["color_palette", "hls_palette", "husl_palette", "mpl_palette",
... |
2b22c52aacf38835236ea2e15765642988a52191532bb92c4070e8803ff00ba9 | Python | 27,876 | 589 | """
@file: trainer_agent_mxnet.py
Created on 18.05.19
@project: CrazyAra
@author: queensgambit
Definition of the main training loop done in mxnet.
"""
import os
import datetime
import logging
import random
from time import time
import numpy as np
from mxboard import SummaryWriter
from tqdm import tqdm_notebook
from rt... |
2a66d1757ea97ca4e02206d8b9fc61904f5888b437e4639b6f0e95c857519bfc | Python | 28,016 | 835 | # Copyright 2018-2025
# Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH
# 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/LICE... |
4a5e169143102ec9284c900f3be02ad9a0882bb290bde007ea83352bb01a150b | Python | 28,052 | 707 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Implements adapter for pytorch-forecasting models."""
import abc
import functools
import inspect
import os
import time
from copy import deepcopy
from random import randint
from typing import Any
import numpy as np
import pandas as pd
from pand... |
4e219c959d8be90f47bbda968d353d9353e51ae38bf1fad856657b17c0be38c9 | Python | 28,079 | 770 | # Copyright 2023 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
bcf6da3f11b51ff00c58323b7e93b6000052fcc3b52ac59fb0bfa1d804dd4f45 | Python | 28,091 | 789 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import math
import sys
from collections.abc import Sequence
from typing import TYPE_CHECKING, Any
import ml_dtypes
import numpy as np
import numpy.typing as npt
import onnx.external_data_helper
from o... |
d7a33e1f81a3776f25e3f220ac165e4aa6636264e0a69cd2c4772428d967e98d | Python | 28,091 | 696 | import os
import pandas as pd
import nrrd
import numpy as np
import random
from colormap import hex2rgb
from allensdk.core.reference_space_cache import ReferenceSpaceCache, ReferenceSpace
import json
import Switches_Dynamic #import get_rootpath
import pickle
prepath = Switches_Dynamic.get_rootpath()
allen_files_path =... |
7a0b680f872fa4e436aee08922d94ac5b70d8f7a83f40f59251f3295d74b6bab | Python | 28,118 | 648 | from __future__ import print_function
from collections import OrderedDict
from scipy import interpolate
import numpy as np
import pyqtgraph as pg
from neuron import h
import cnmodel.util as util
from .protocol import Protocol
from .. import cells
from ..synapses import GluPSD, GlyPSD, Exp2PSD
from ..util.find_point imp... |
447cbf55a0d49dc0964a206751631a19242068b67229aafa80efda8f990c7d38 | Python | 28,119 | 806 | # Copyright 2019 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
21745b200af140d3c6ff4dfb506be126412398c292cbe582504045e773014a80 | Python | 28,188 | 793 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""Backend-independent training driver abstractions.
The classes in this module intentionally know nothing about TensorFlow,
PyTorch, JAX, or Paddle tensor semantics. Backend trainers provide the
numerical hooks; this layer owns task/rank normalization, display scheduling,... |
bb97616052f1c3dcecec3f3b532635f43727dabf1a4faa7324f7892da18bd96d | Python | 28,266 | 818 | # Copyright 2026 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
b314d4305e7c2ae71053744e2c71208516d4f47c0b2612e7a7ce0a87cef4437f | Python | 28,343 | 663 | """
This script generates figure S6h from the paper
They are the disc plots comparing selectivity index for visual (left panel), auditory (middle panel) and
choice decoding (right panel)
Internal notes:
This is from notebook : 20.5-multispaceworld-quantify-selectivity-index-in-active-condition
"""
from matplotlib.coll... |
4c5f963af210952662acaf6afed5075e1b6cdb6a713ddb0058cd0ac2e3efe76c | Python | 28,416 | 571 | from utils import AverageMeter, str2bool, cm_visualize
from tqdm import tqdm
import torch
import torch.backends.cudnn as cudnn
import torch.nn as nn
import torch.optim as optim
import archs
from collections import OrderedDict
from metrics import Pearson
from metrics import RMSE
import pandas as pd
from sklearn.metrics ... |
97020b3683b504ce2c497050806af50a4d4bffea75d4d5d008ca27880b4d2334 | Python | 28,471 | 765 | # Copyright 2024 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
8c7a6a44134799cadc8d149ddf0210104c3bd9f4587fa8e331d8a4dd11e7e990 | Python | 28,514 | 741 | from __future__ import division
import os
import numpy as np
import pandas as pd
import seaborn as sns
import pylab as plt
from SPHARM.classes.image_stack import ImageStack
from SPHARM.classes.surface import Surface
from SPHARM.classes.spectrum import Spectrum
from SPHARM.classes.time_spectrum import TimeSpectrum
fro... |
a1d486a7d4e98087062c90d255bdaff1fc5d369d5ac651093efe1a47c37a9e00 | Python | 28,546 | 719 | """
GenerateRun is a class that sets up for a run after the cell has been decorated with channels.
It requires the celltype, and a section where the electrode will be inserted.
The stimulus in current clamp can consist of single pulses or pulse trains. cd is the
channelDecorator, which is also used to set the current r... |
c53b9387eeb06c08ed06fc8fef9e077ad6d1cdc0393ccd49a0d1c0c1d236f714 | Python | 28,599 | 429 | import argparse
import numpy as np
import sys
from hmm_functions import TrainModel, write_HMM_to_file, read_HMM_parameters_from_file, Write_Decoded_output, Calculate_Posterior_probabillities, PMAP_path, Viterbi_path, Hybrid_path, Convert_genome_coordinates, Write_posterior_probs, Make_inhomogeneous_transition_matrix, S... |
6f74e227acabc7f6a42c52a01d1299c8772e973cd122a6d9ed4dd33101f2ebe9 | Python | 28,618 | 733 | # Copyright 2018-2025
# Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH
# 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/LICE... |
97c4bc57c027fd05b42b00797a2d09a64271dc7ebd113aa3e3034555131e89b9 | Python | 28,618 | 734 | # Copyright 2019 DeepMind Technologies Ltd. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... |
cc9753cd624a8b14ee0144767f831c7fa1183f552dbf5dc413eb62873ae998c6 | Python | 28,625 | 722 | #!/usr/bin/env python3
# equivalent indexed as default
# equivalent indexed in map only
from urllib.parse import urlparse
import yaml
import idlib
import rdflib
import ontquery as oq
import augpathlib as aug
from ttlser import CustomTurtleSerializer
from pyontutils.core import OntGraph, OntTerm, OntResGit, OntResIri
... |
82e6702c0db9d3346a675f4c97483828478dcf5a6b67f06ee573de6e856d5d4f | Python | 28,640 | 711 | # -*- coding: utf-8 -*-
"""
Created on Sun Aug 27 13:38:21 2017
@author: daniel
"""
from neuron import h
import parameters as p
import synapse as s
import spine as sp
import sys
import re
import random as rnd
import json
filename = p.params_for_learning_functions
class Neuron(object):
"""Generic neuron class.""... |
321e4a7d8ef2db16dc34030c03fe66a972330512525b451d73f3d205b0840d29 | Python | 28,648 | 804 | """
Get cell configuration information. Reads an excel file, and generates
a data structure for the models with a focus on the synapses.
This module is part of *vcnmodel*
Support::
NIH grants:
DC R01 DC015901 (Spirou, Manis, Ellisman),
DC R01 DC004551 (Manis, 2013-2019, Early development)
... |
c6420db0113fdbdb193c8dac7668376b5d415133c20b2a91feab7a4618bfadd4 | Python | 28,652 | 874 | #!/usr/bin/env python3
"""
A collection of reused functions and classes.
Depends only on python standard library.
"""
import os
import ast
import inspect
import logging
from types import ModuleType
from pathlib import Path
from datetime import datetime, date, timezone
from functools import wraps
from collectio... |
3f886678234221082b4076e0533fd89cfb7212a54af19069ad3e97ca5604c3c3 | Python | 28,680 | 765 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Base class template for objects and fittable objects.
templates in this module:
BaseObject - object with parameters and tags
BaseEstimator - BaseObject that can be fitted
Interface specifications below.
---
class name: BaseObjec... |
997a8772b3f543f84bae1939f774474f4ff93d9fa6ec422b0b668963dac01936 | Python | 28,725 | 944 | """
Define data structures used for:
*Command line parsing*
*Specifying model parameters (general)*
*Specifying runInfo (run instance) parameters*
The aspiration is that all parameters that we vary between runs are defined
in either the Params dataclass or the RunInfo dataclass, and are stored along
... |
b8e764e9ba3e2b2e4a116071b66fa701d8d26bcd71f98a8fff43d6fe5e8be687 | Python | 28,743 | 373 | # predict with all documents (with either a weak or a strong supervised model) to get the rare diseases
from sent_bert_emb_viz_util import load_df,load_data, encode_data_tuple, retrieve_section_and_doc_structure, test_model_from_encoding_output
from rare_disease_id_util import umls2ordoListFromCSV, isNotGroupOfDisorde... |
cf7482efcf0ef89b3f6cffe534cea3676e58f662af6e83a8c07dc8389c25725d | Python | 28,774 | 697 | """Pipeline with a clusterer."""
# copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
import numpy as np
from sktime.base import _HeterogenousMetaEstimator
from sktime.clustering.base import BaseClusterer
from sktime.datatypes import convert_to
from sktime.utils.sklearn import is_sklearn_clusterer
... |
d6f0648cf42fd3cbcc698cb76e33773be872cc3fe377a7c26dfe385e1a2c2cb7 | Python | 28,825 | 673 | import logging
import re
from pathlib import Path
from typing import Optional, Union
import torch
from deprecated.sphinx import deprecated
import flair
from flair.data import Sentence, Token
from flair.embeddings.document import DocumentEmbeddings
from flair.embeddings.token import StackedEmbeddings, TokenEmbeddings
... |
1ed6fc64ef3034d25758f1dfa486293e0005c4ad6c18c53b6b6ce6a214971fb6 | Python | 28,829 | 741 | """
extended_ring_model.py
This module contains the full specification for the ring model from
the paper. The model is based on data from Pisokas et al. (2020), Goulard
et al. (2021), Fisher et al. (2019), Kim et al. (2019), Kim et al. (2017),
and Seelig and Jayaraman (2015).
[Biology]
Pisokas et al. (2020) provide a... |
e348fe006a1e60ef7fd1342614a1dfae039a536fe161d5d20797692cb5331686 | Python | 28,861 | 619 | #!/usr/bin/env python3
import csv
from pprint import pprint
from pathlib import Path
import rdflib
import ontquery as oq
from pyontutils.utils import byCol, relative_path, noneMembers
from pyontutils.core import resSource
from pyontutils.namespaces import OntCuries
from pyontutils.namespaces import interlex_namespace, ... |
9cc98b100b5cd55a2c99fbad897a33c278264a97415a231a1f892114e3dfda01 | Python | 28,890 | 774 | """Implements Chronos forecaster."""
__author__ = ["abdulfatir", "lostella", "Z-Fran", "benheid", "geetu040", "PranavBhatP"]
# abdulfatir and lostella for amazon-science/chronos-forecasting
__all__ = ["ChronosForecaster"]
from abc import ABC, abstractmethod
import numpy as np
import pandas as pd
from skbase.utils.d... |
9268b9d5cd4ea3bb98086433c3fbbacc3d62e4d172aa2202a5e89f2328668cb5 | Python | 28,891 | 790 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""
Radial building blocks for the DPA4/SeZM descriptor.
This module defines the cutoff envelope, inner-distance clamp, radial basis,
and radial multilayer perceptron used by SeZM.
This module is the dpmodel (array-API) port of
``deepmd.pt.model.descriptor.sezm_nn.radial``... |
9367b185f0d43838e4d97f07d33829dd22b7c89146369231578c4566bd0dfccc | Python | 28,923 | 551 | """
Prompted PatchTST-FM: prompt tuning on a pretrained PatchTST-FM time-series
foundation model.
Injection point: M prompt tokens are PREPENDED to
the patch-token sequence between (in_layer + pos_embed) and the transformer
blocks, so prompts carry no positional embedding (the analogue of position_id=0
in the Chronos-... |
8634ab18456f1bc4122ce87681b165b9d0c7ff73b30fe8c54e539568646df114 | Python | 28,973 | 881 | #!/usr/bin/env python3
"""
A collection of reused functions and classes.
Depends only on python standard library.
"""
import os
import ast
import inspect
import logging
from types import ModuleType
from pathlib import Path
from datetime import datetime, date, timezone
from functools import wraps
from collectio... |
dddf47c384fbc0e87716f7d22aff539187b9a028a56f86be68af4fc3abd4a089 | Python | 28,996 | 568 | """make_shared_dataset.py
Create a directory structure based on figure_data.py (in the plotters
subdirectory) and populate it with all of the simulation files and intermediate
analyses needed to regenerate the figures using DataTablesVCN.py This also
populates the Morphology directory for each cell with the .hoc and .s... |
7c8876b36ac3067b61ff78c829469ae488b274bb52be8ac248f5103707117c3b | Python | 29,001 | 699 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
from io import BytesIO
from typing import Any
import numpy as np
import onnx
import onnx.model_container
from onnx.onnx_pb import (
FunctionProto,
GraphProto,
ModelProto,
NodeProto,
... |
ff8603017bfaddd5b87f882d6b1a0a3121d7f975d77f97686cc8e1fd6abc1f39 | Python | 29,005 | 565 | """
Module for decomposing the prediction ANN into piecewise linear functions
via Taylor Series decomposition
"""
import model
import numpy as np
import tensorflow as tf
from numba import njit
from typing import List, Tuple
# def _dCa_dR_relu(mdl: model.ActivityPredictor, reg_input: np.ndarray) -> np.ndarray:
# ... |
7cfb0390ab61bbb54213dd5359899ddff115839856f12aa0a602f73e42112032 | Python | 29,011 | 591 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Extension template for transformers.
Purpose of this implementation template:
quick implementation of new estimators following the template
NOT a concrete class to import! This is NOT a base class or concrete class!
This is to be us... |
81eaa351a9f0a87716c66cdd65e42131c077795245727a473441f88c9c6e4fd8 | Python | 29,103 | 741 | #!/usr/bin/env python
""" Translator Class and builder """
from __future__ import print_function
import codecs
import os
import time
import numpy as np
from itertools import count, zip_longest
import torch
import onmt.model_builder
import onmt.inputters as inputters
import onmt.decoders.ensemble
from onmt.translate.b... |
eaf93ef1b06c0fc99b13f0eb70b1c9283429b745bb4316ff3edba955bb635867 | Python | 29,231 | 1,032 | # Copyright 2026 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
243cfe27e45852cfbcd846ba8d875919a42a4c9ff23914c46bc3bd6f0c01b4fe | Python | 29,254 | 676 | #!/usr/bin/env python3
# this should be run at NIF-Ontology 9ef5b9e63d60f92cd01733be9d480ac3e5aee31c
# TODO need to retrieve the FMA hierarchy...
import os
from collections import defaultdict, namedtuple
import rdflib
from rdflib import URIRef, RDFS, RDF, OWL
from rdflib.namespace import SKOS
import requests
from py... |
a0e476766df00107e6ade50a2922fe8c57d5b9d233bd6a0bc19736f12be01487 | Python | 29,286 | 666 | from __future__ import print_function
from neuron import h
from ..util import nstomho
from .cell import Cell
from ..util import Params
from .. import synapses
from .. import data
__all__ = ['DStellate', 'DStellateRothman', 'DStellateEager']
class DStellate(Cell):
celltype = 'dstellate'
scaled = False
... |
0376b0c9dd1522e9aa8a8ea53da5070ae8c6d1cbf6652dce87931ed7cf49ed63 | Python | 29,298 | 632 | from __future__ import annotations
import json
from typing import Any
from typing import TYPE_CHECKING
import numpy as np
import optuna
from optuna import _deprecated
from optuna._experimental import warn_experimental_argument
from optuna._warnings import optuna_warn
from optuna.samplers._base import _INDEPENDENT_SA... |
63189a272ea986e9065f7f63eb68a1be1bda4e1ee616f67dc78ebf8b0d4dcbdc | Python | 29,377 | 842 | # Copyright 2019-2026 The AmpliGraph Authors. All Rights Reserved.
#
# This file is Licensed under the Apache License, Version 2.0.
# A copy of the Licence is available in LICENCE, or at:
#
# http://www.apache.org/licenses/LICENSE-2.0
#
import numpy as np
import tensorflow as tf
from ampligraph.latent_features.lo... |
cd8fe8b1072487e4e546cf17566e0649dd944b8e36cf2f4293813cab34f0bfac | Python | 29,404 | 849 | # Copyright 2019 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agr... |
1f8ab5d79619c825c4bfc36cd0c494d76817328020f1344209bc78d3504f5ddf | Python | 29,517 | 699 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Implements adapter for Darts models."""
import abc
import pandas as pd
from skbase.utils.dependencies import _check_soft_dependencies
from sktime.forecasting.base import BaseForecaster, ForecastingHorizon
from sktime.utils.warnings import war... |
7b70ebb035f51a5dc182de9e1117dde7b89ca7e6625765bd843c6feb830fb40a | Python | 29,534 | 908 | """Utility functions, mostly for internal use."""
import os
import inspect
import warnings
import colorsys
from contextlib import contextmanager
from urllib.request import urlopen, urlretrieve
from types import ModuleType
import numpy as np
import pandas as pd
import matplotlib as mpl
from matplotlib.colors import to_... |
15d4fd6e1040ebe4a9f918a2fdf0839939e24a1a947a068639cda0bb3ede6e8c | Python | 29,628 | 785 | from pprint import pprint
from contextlib import nullcontext # 3.7
from functools import wraps
import rdflib # FIXME decouple
import ontquery as oq
from hyputils.hypothesis import idFromShareLink, shareLinkFromId
from pyontutils import sheets
from pyontutils.sheets import update_sheet_values, get_note, Sheet
from pyo... |
9bd94cba5bf5bba9ac8b166d327e8df463fb4a06fff0e34ce72961f795730acd | Python | 29,675 | 874 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Wed Jan 4 13:14:00 2017
@author: wanglab
"""
from math import ceil
import multiprocessing as mp
import numpy as np
#import dill as pickle
import pickle
import os, sys, time, shutil
import tifffile
from skimage.exposure import rescale_intensity
from scipy.n... |
86773970f6e6e5e9d9a0904341cecaabecca727f8d43f5b5136a77fa5a9e52fc | Python | 29,721 | 505 | from __future__ import print_function
"""
******************
NOTE: This version of the file is OBSELETE
The numbers for the synapse area have been updated
******************
"""
"""cell_config generates the configuration of synaptic inputs and devines a cell
The synaptic input structure consists of a list of tuples.
... |
43d58dc333fbcfbdf7da8c0d4e4bef8d59b30c0d0f62e2dc48b46b616b5d0c6a | Python | 29,729 | 396 | # this program calculates
# (i) micro-level and macro-level precision, recall, and F1
# (ii) instance-based precision, recall, and F1 - optional, this has issue to deal with non-rare disease documents, i.e. for this (pred-true) pairs (0,0,0 - 0,0,0) and (1,0,0 - 0，0，0） will have the same precision, recall, and F1 sc... |
be6571fdea2f5118aeaf31f9677811adb94926ddb4982857a12b67ec9f56729e | Python | 29,748 | 772 | import bisect
import io
import json
import logging
import os
import re
from collections import defaultdict
from collections.abc import Iterable
from pathlib import Path
from typing import Any, Optional, Union
import conllu
import gdown
from conllu.models import Metadata, Token
import flair
from flair.data import Sent... |
8df27c79c24593a7253971a8cd1d6ec167c97d6dc8ef1593ef01d1245cee8671 | Python | 29,755 | 569 | # Copyright (c) 2019. Martin Haesemeyer. All rights reserved.
#
# Licensced under the MIT license. See LICENSE
"""
Class wrapper of experiments with support of serialization to/from HDF5 files
"""
import warnings
import h5py
import numpy as np
from datetime import datetime
from os import path
import json
from typin... |
92e011c0c9a77a8232fa6776c98e17277960e26a5f1cb504ae2616739f4ca877 | Python | 29,805 | 976 | """
"""
from .__init__ import *
import subprocess as sp
import os
from scipy import sparse
def diag_matrix(X, rows=np.array([]), cols=np.array([]), threshold=None):
"""Diagonalize a matrix as much as possible
"""
di, dj = X.shape
transposed = 0
if di > dj:
di, dj = dj, di
X = ... |
770a9ba9a73ecadcf455d6a9685d74ff88c6ff52fa15f11506629cfc4c35134a | Python | 29,846 | 810 | """
Fill in a table using pyqtgrph that summarizes the data in a directory.
Generates index files (pickled python dataclass) that summarize the results.
Set the force flag true to rebuild the pkl files.
This is meant to be called from DataTablesVCN.py
This module is part of *vcnmodel*.
Support::
NIH grants:
... |
c9565789d55eb994b6294a66973196e554bd122dfb5a99b07948416381483597 | Python | 29,861 | 760 | # SPDX-License-Identifier: LGPL-3.0-or-later
import logging
from collections.abc import (
Mapping,
)
from copy import (
deepcopy,
)
from typing import (
Any,
)
from deepmd.utils.model_branch_dict import (
get_model_dict,
)
from deepmd.utils.spin import (
normalize_spin_use_spin,
)
log = logging.ge... |
dc9aeef1636e98a93ecf17e785682c299c41332e4c435b45e3cb60a3aa9089b6 | Python | 29,896 | 698 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Abstract base class for early time series classifiers.
class name: BaseEarlyClassifier
Defining methods:
fitting - fit(self, X, y)
predicting - predict(self, X)
- predict_pro... |
98c9920272d92630dbf9b8bce853ca3505c36c83caa40fe487b2232a54cf9313 | Python | 29,935 | 768 | # Copyright 2018-2025
# Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH
# 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/LICE... |
5bd578237691227c4f9b83ce28a14277a8f58dfd83776074c97fd20b284450be | Python | 29,943 | 821 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import contextlib
from typing import TYPE_CHECKING
import pytest
import onnx
from onnx import TensorProto, defs, helper
MOD_OPSET_13 = 13
MOD_OPSET_28 = 28
if TYPE_CHECKING:
from collections.abc ... |
3162686afd6282a918117f625141d41753756af778aae8deb2cb52566b1ad7de | Python | 29,982 | 831 | """BOSS classifiers.
Dictionary based BOSS classifiers based on SFA transform. Contains a single BOSS and a
BOSS ensemble.
"""
__author__ = ["MatthewMiddlehurst", "patrickzib"]
__all__ = ["BOSSEnsemble", "IndividualBOSS", "pairwise_distances"]
from copy import copy
from itertools import compress
import numpy as np
... |
ab2ba7a87feb65299650141637f93086f05f20bccb66f4697ba6ad386872a8ab | Python | 30,054 | 820 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import math
from typing import TYPE_CHECKING, Any
import numpy as np
import onnx
from onnx.reference.op_run import OpRun
if TYPE_CHECKING:
from collections.abc import Callable
def _cartesian(arr... |
3f1af25e6e82dc858dce95533b74fe1c368d6eb242a77cd393d9a75e5de8408c | Python | 30,056 | 823 | #!/usr/bin/env python3
import os
import tempfile
from copy import deepcopy
from html import escape as html_escape
from urllib.parse import quote
from collections import namedtuple
from collections import defaultdict as base_dd
import htmlfn as hfn
from pyontutils.core import OntId, log as _log
from pyontutils.utils imp... |
fa14e107c1f2ed045db83cd41c4df4892683f32d5db2ad5ca5aad95e57b299eb | Python | 30,075 | 735 | """Pipeline with a classifier."""
# copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
import numpy as np
from sktime.base import _HeterogenousMetaEstimator
from sktime.classification.base import BaseClassifier
from sktime.datatypes import convert_to
from sktime.utils.sklearn import is_sklearn_clas... |
585761883d4217c5c7db06a8a2dc60ad13840e09b2319a9214e35c5f65967abb | Python | 30,099 | 869 | """Utilities for writing code that runs on Python 2 and 3"""
# Copyright (c) 2010-2015 Benjamin Peterson
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including with... |
18f0ca3aecf6888654e0a7ff5b729fb086b90ddcb4d1b01597bd9fcfd2fa05ae | Python | 30,113 | 695 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# 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 req... |
55534bbae027b6927ffd4210e513a14dc4ea956a939d6e7457493357aefb0f7d | Python | 30,181 | 805 | """Benchmarking interface for use with sktime objects."""
import logging
import warnings
from dataclasses import dataclass, field
import pandas as pd
from sktime.base import BaseEstimator
from sktime.benchmarking._benchmarking_dataclasses import (
ResultObject,
TaskObject,
)
from sktime.benchmarking._results... |
2468b6ecc74abc472dafa135f8c76f9e92983929fe575191dfd3cac0554c7a16 | Python | 30,257 | 635 | import tempfile
import itertools
import numpy as np
import pandas as pd
import mdtraj as mt
from biopandas.pdb import PandasPdb
from numba import vectorize, float64
class LigandProteinComplex(object):
"""Extract feature of protein-ligand interaction from pdb file.
The series of functions to extract feature... |
d883f2c4b4d52b2af82dea09fdfc998cab7cf9297e36186844c918fb3e0bbdf6 | Python | 30,259 | 812 | #!/usr/bin/env python
import argparse
from functools import partial
import gzip
from multiprocessing import Pool, cpu_count
import numpy as np
import os
import pandas as pd
from pybedtools import BedTool
import re
import sparse
import subprocess as sp
from __init__ import ENCODE, ParseUtils
usage_msg = """
usage: %s... |
ed2120a1a0b25cf7ea2b0a1d8fe3c7826dbd22017d963ac0ae4bf85822067e80 | Python | 30,259 | 725 | """Abstract base class for time series classifiers.
class name: BaseClassifier
Defining methods:
fitting - fit(self, X, y)
predicting - predict(self, X)
- predict_proba(self, X)
Inherited inspection methods:
hyper-parameter inspection - get_params()
fitted parame... |
f07acbb0e2c4c4e9dbd25e6728d264a66dfd411e174b3779913df45792941d62 | Python | 30,267 | 559 | # -*- encoding: utf-8 -*-
from ._db import add_table_data
"""
Ion channel density tables
All of the ion channel densities for the models implemented in cnmodel
are (or should be) stated here, and should not be modified in the
cnmodel code itself.
"""
add_table_data('RM03_channels', row_key='field', col_key='model_ty... |
dede3c7e9f46566d90d1f97cae51ff56cdbbe997ed48127a0fc418c58f6ae98f | Python | 30,290 | 731 | import numpy as np
import tensorflow as tf
import tensorflow.keras.backend as K
from tensorflow.keras.layers import Layer
import tensorflow.keras.layers as KL
import neurite as ne
import math
class SpatialTransformer_with_disp_swin(Layer):
"""
Adapted from Voxelmorph: https://github.com/voxelmorph/vo... |
3455676425cfba59cc6a4bfd59fd0b9b6e4334704f881050dd765d32528670e5 | Python | 30,297 | 575 | import time
import json
import os
import json
import joblib
from io import BytesIO
import base64
import boto3
import math
import io
import cv2
import numpy as np
# Grab environment variables
TEST_ID = os.environ['TEST_ID']
DETECTION_ENDPOINT_NAME = os.environ['DETECTION_ENDPOINT_NAME']
CLASSIFICATION_ENDPOINT_NAME = ... |
47a9e407626694c27569bf868530c7053c6e309a6c3bdd87695a64d562c896bb | Python | 30,337 | 768 | import warnings
from collections import OrderedDict
from copy import deepcopy
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as cp
from mmcv.cnn import build_norm_layer, constant_init, trunc_normal_init
from mmcv.cnn.bricks.transformer import FFN, build_dropout
from mm... |
535052787258f33f1e2ab1b4eaf8a12622a0cb64c43640d8e5eb22c3ed7cdfad | Python | 30,377 | 467 | #!/usr/bin/env python
import sys
import os
import math
import subprocess
#import pandas as pd
from os.path import isfile, join, isdir
from kn_common import pipetools,pipedef
from kn_pipeline_class import CPipeError,CPipeStep
import hashlib
def md5(fname):
hash_md5 = hashlib.md5()
with open(fname, "rb") as f... |
45237b350d7a6c8d5271fbc969b0a31fe44a0fe0beec2b399410c0be19e432f4 | Python | 30,415 | 814 | # SPDX-License-Identifier: LGPL-3.0-or-later
import tempfile
import unittest
from pathlib import (
Path,
)
from typing import (
NoReturn,
)
from unittest.mock import (
patch,
)
import h5py
import numpy as np
import torch
from deepmd.dpmodel.atomic_model import DPAtomicModel as DPDPAtomicModel
from deepmd.... |
61f7d0a81ec63c056a699082f0f5b4314290073db5a00a941965cd06f787a5d3 | Python | 30,440 | 900 | # Copyright 2018-2026
# Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH
# 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/LICE... |
34a8037e39f822c987f44d4237af03d351409fdb3b5308ce92afad9e177e584c | Python | 30,495 | 773 | import logging
from typing import Any, Optional, Union, cast
import torch
from sklearn.feature_extraction.text import TfidfVectorizer
from torch.nn import RNNBase
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
import flair
from flair.data import Sentence
from flair.embeddings.base import (
... |
52da5ba536403c1b75c955fb7ca505e1b4182aa872208ab54eb96c3c7b426e8f | Python | 30,523 | 730 | # SPDX-License-Identifier: LGPL-3.0-or-later
import math
from collections.abc import (
Callable,
)
from typing import (
Any,
)
import array_api_compat
import numpy as np
from deepmd.dpmodel.array_api import (
Array,
)
from deepmd.dpmodel.common import (
GLOBAL_NP_FLOAT_PRECISION,
NativeOP,
to_... |
192615d0df9f36e4ca74c36e5cee15dbaa7fbd6b603b5ce6605cea70b2fbefd8 | Python | 30,613 | 834 | from __future__ import annotations
import itertools
import warnings
import numpy as np
from numpy.typing import ArrayLike
from pandas import Series
import matplotlib as mpl
from matplotlib.colors import to_rgb, to_rgba, to_rgba_array
from matplotlib.markers import MarkerStyle
from matplotlib.path import Path
from sea... |
f2872fca94880915c21175f3b2b22a0b26997ca2ff3b24996d8374ae38fbad3b | Python | 30,623 | 719 | #!/usr/bin/env python3
'''
Functions for creating metrics to classify ICA domains
Authors: Sydney C. Weiser and Brian R. Mullen
Date: 2019-04-06
'''
# import systems level
import os
import re
import sys
sys.path.append('/home/feldheimlab/Documents/pySEAS/') # dir of cloned repo
# key data management/manipulation pac... |
6bd03bfb1432a162339561ffe10b04f6474ded8d0594f8c1d902d5134d691e5a | Python | 30,702 | 626 | # ----------------------------------------------------------------------------
# Copyright (c) 2017-2026, QIIME 2 development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ------------------------------------------------... |
f743d226c8359e8a85ef67a234ea27ed5e3f559532a66dd19f3189a3198eccef | Python | 30,724 | 855 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import argparse
import csv
import json
import subprocess
import sys
from concurrent.futures import ThreadPoolExecutor
from datetime import UTC, date, datetime, timedelta
from pathlib import Path
from t... |
fd905a4a6664667ffa27462985869cc1d363fa232b513c3c5d059603de5ccd65 | Python | 30,787 | 798 | from __future__ import annotations
import sys
import warnings
from collections.abc import Callable, Iterable, Iterator, Mapping, Sequence
from typing import Any, cast
import numpy as np
import torch
from torch import nn
from torch.jit import ScriptModule
from torch.utils.hooks import RemovableHandle
from .enums impo... |
b15c427a6346fe704c20442e490ae4b7745c86d0561a512fa6bdd6cdc9b70bfa | Python | 30,793 | 806 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Implements compositors for performing forecasting by group."""
import pandas as pd
from sktime.base._meta import _HeterogenousMetaEstimator
from sktime.datatypes import ALL_TIME_SERIES_MTYPES, mtype_to_scitype
from sktime.forecasting.base impo... |
fc8d10e62069946614f0d1bb0f6925b7198377efa3312df02cd2fd177b290c99 | Python | 30,861 | 577 | """
Simulation backends for synthetic nervous system networks. Each of these are python-based, and are constructed using a
Network. They can then be run for a step, with the inputs being a vector of neural states and applied currents and the
output being the next step of neural states.
"""
"""
%%%%%%%%%%%%%%%%%%%%%%%%... |
bcb19213961f790303ccf443cce874c484a09ae7b2c6103329dc77928f4dab63 | Python | 30,959 | 852 | """Machine type checkers for Table scitype.
Exports checkers for Table scitype:
check_dict: dict indexed by pairs of str
1st element = mtype - str
2nd element = scitype - str
elements are checker/validation functions for mtype
Function signature of all elements
check_dict[(mtype, scitype)]
Parameters
----------... |
3f659ed4b5561a3c208a4dac864eada8cfebc3d6e557fdb6d699c21b32b8764e | Python | 31,044 | 787 | # Copyright 2018-2026
# Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH
# 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/LICE... |
a5c65c0fac845b81916659615eda1b7077faaaadc8ee636cdda3ab5a74d49d90 | Python | 31,119 | 1,040 | """
"""
from __init__ import *
import numpy as np
import pandas as pd
import os
from scipy import sparse
import anndata
import logging
def get_size_in_GB(obj):
""""""
GB = 1024**3
return sys.getsizeof(obj)/GB
def scf_rna_format_to_h5ad(meta, gc_mat):
"""
input:
- meta (cell metadata)
... |
3fce94fbb438818a4ed819ea22432515e6b8cb7028307497f5b4c5716d4bc4a6 | Python | 31,167 | 545 | # Copyright 2007 Zachary Pincus
# This file is part of CellTool.
#
# CellTool is free software; you can redistribute it and/or modify
# it under the terms of version 2 of the GNU General Public License as
# published by the Free Software Foundation.
from . import contour_class
from celltool.numerics import utility_too... |
56975befa486b035697c18f2dfd12bed460cc8f69586c062a134eadfaabdc53d | Python | 31,167 | 810 | #!/usr/bin/env python3
# Copyright (C) 2019 Christoph Gorgulla
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# This file is part of VirtualFlow.
#
# VirtualFlow is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the ... |
9dac68f9c62b6520469166c96f44ff825de227724a2b9a4dbf365836e0f4ff04 | Python | 31,180 | 805 | # SPDX-License-Identifier: LGPL-3.0-or-later
r"""Native per-atom spin channels for DPA4C.
The magnetic moment :math:`\mathbf s` is an *axial* vector: under spatial
inversion the edge direction flips while the spin does not, and under time
reversal the spin flips while the geometry does not. Labelling every channel
by ... |
10f96a24a21466ab0e344fe29819c22bc70b84f0428e5d30217761a7f56efcf3 | Python | 31,236 | 455 | # for visualisation using brat
# generate brat annotation format files of all MIMIC-III documents regarding rare diseases
'''
reads mention-level pred results all docs[ sup].xlsx to get the mention offsets and ORDO IDs results from NLP
MIMIC-III DS-Rare-Disease-ICD9-new-filtered[-sup]-bp.xlsx (an output of st... |
17c91cc80c11d65092c8769142a9496355cc8254fb8ff203e94b07627960ec56 | Python | 31,262 | 853 | """Conditional Invertible Neural Network (cINN) for forecasting."""
__author__ = ["benHeid"]
import warnings
from copy import deepcopy
import numpy as np
import pandas as pd
from sktime.forecasting.base import ForecastingHorizon
from sktime.forecasting.base.adapters._pytorch import (
BaseDeepNetworkPyTorch,
... |
3db401fb6b4663130509f32239546890e5439aa4b17e9215eaa16f355f67c55e | Python | 31,309 | 771 | #-------------------------------------------------------------------------------
# elftools: dwarf/descriptions.py
#
# Textual descriptions of the various values and enums of DWARF
#
# Eli Bendersky (eliben@gmail.com)
# This code is in the public domain
#-----------------------------------------------------------------... |
67d6090b7093b8504a02d1fff74ca9b9d55aba3094cf626e9e8e446de088a87c | Python | 31,385 | 836 | """Advanced tests for the Orthofinder importer.
Coverage focuses on patterns common to ortholog inference test suites:
- **Inparalog handling**: tandem duplicates on the same chromosome.
- **Gene-family expansions**: orthogroups with 10+ paralogs in a species.
- **Adversarial ambiguity**: paralogs whose scores tie un... |
506c2c49064cc47389e908f768b8ee9c141b4d2d5725be4894a83d831883bfc8 | Python | 31,395 | 556 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import json
import logging
import os
import shutil
import time
import dill
import numpy as np
import ray
from ray.rllib.utils.memory import ray_get_and_free
from termcolor import colored
from mprl.utility_ser... |
5980bfb8a4ffee99130a9dbe84f716b3c17df03db258f7abb5db390cef9fba8c | Python | 31,473 | 766 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Implements and interface to the AutoTS library main entry point."""
__author__ = ["MBristle"]
import logging
import pandas as pd
from pandas.api.types import is_integer_dtype
from sktime.forecasting.base import BaseForecaster, ForecastingHor... |
77247df4737d6752b5a314ca2538de6e89318b0f8502d95bcfe27a3051af9639 | Python | 31,504 | 860 | # -*- coding: utf-8 -*-
import glob
import os
import codecs
import math
from collections import Counter, defaultdict
from itertools import chain, cycle
import torch
import torchtext.data
from torchtext.data import Field, RawField, LabelField
from torchtext.vocab import Vocab
from torchtext.data.utils import RandomShu... |
a375ef6debd17858459b8885b921698efd342a468eddabf2050fb656072a9fdf | Python | 31,509 | 1,006 | from __future__ import annotations
import math
from collections import namedtuple
from typing import Any, Sequence, cast
import numpy as np
import torch
from torch import nn
from torch.nn import functional as F
from torch.distributions import Categorical, Normal
from torch.nn.utils.rnn import pack_padded_sequence
c... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.