sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
9d28cddc7e37b46efa116fc3eb6f20e945003b2c27ab2afb6f523aff68d89b9c | Python | 21,595 | 444 | 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 = ... |
110c240ca63d6f43c8006463db33a03cb9d8b0029b429abce72d1a41ad833cf1 | Python | 21,614 | 579 | # 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... |
b577491880635b40b2ca1204c5e759f9bc175f215a6da38520f04f11f5b00dfd | Python | 21,647 | 563 | # Copyright 2022 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... |
ff882f8155116ca97daec52d20c78690f50be68b8141f0ba91e3b8065924c3ac | Python | 21,675 | 403 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import json
import logging
import os
import shutil
import time
from socket import gethostname
from termcolor import colored
import dill
import numpy as np
import ray
from mprl.utility_services.payoff_table imp... |
3828919724d0d60051c4c19b33cb951d67b62d8ddd8bfe7e3c548303af83dcc6 | Python | 21,678 | 512 | import csv
import logging
import multiprocessing
import numpy as np
import os
import pickle as cp
import random
import time
from base.processor_base import Processor
from collections import Counter, defaultdict
from gln.common.mol_utils import cano_smarts, cano_smiles, smarts_has_useless_parentheses
from gln.data_proce... |
5f35221e1d476430dfc56fab73d0192c6f08e4122179f96b615dfdd4a215fada | Python | 21,680 | 620 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Intermediate base class mixin with common functionality for panel tasks.
Inherits from BaseEstimator, descendents are:
BaseClassifier
BaseRegressor
"""
__author__ = ["fkiraly"]
__all__ = ["BasePanelMixin"]
import numpy as np
import pandas a... |
0a533e07284b37b1f287472f06056fbd7bb48da5ec5cbef6186e6c19746a51b6 | Python | 21,686 | 480 | """Abstract base class for the Pytorch neural network classifiers."""
__authors__ = ["geetu040", "RecreationalMath"]
__all__ = ["BaseDeepClassifierPytorch"]
import abc
from collections.abc import Callable
import numpy as np
from sklearn.preprocessing import LabelEncoder
from sktime.base.adapters._pytorch import _P... |
63ce0454e938c5a1dc04298e924335d638760eafb04c86ea6d723239ed9ef162 | Python | 21,729 | 386 | # Transform is the primary class in ARDENT.
import numpy as np
from pathlib import Path
import pickle
from .presets import get_registration_preset
from .lddmm._lddmm import lddmm_register, lddmm_transform_image, lddmm_transform_points
from . import file_io
class Transform:
"""
Transform stores the deformati... |
923431718f45d820f973a0a07e78f77e2166c4c2b7433cfdefd6ce8d3a19093c | Python | 21,788 | 600 | """ readmodel.py - tools to read model data files.
All reading should be done through this module, as it handles different formats,
and retuns a uniform "ModelData" data structure
This module is part of *vcnmodel*.
Support::
NIH grants:
DC R01 DC015901 (Spirou, Manis, Ellisman),
DC R01 DC004551 (Manis, 2... |
945006817b2ba30f20d7dd3a5c8bb49d73252fd4dd733487dc04ba7bc931b117 | Python | 21,807 | 557 | # 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... |
facb6530ac45bdfb267699628233294ea45f46b4442bfbd428311b49e1aa8d1a | Python | 21,818 | 451 | """
This script produces figure S7n (the right part) of the paper.
"""
import os
import numpy as np
import pickle as pkl
import pandas as pd
import src.models.kernel_regression as kernel_regression
import src.models.psth_regression as psth_regression
import src.visualization.vizregression as vizregression
import src.... |
61be50cfe1eaeb554efd8b7fcf1a60fa32fc3d12a0b1d3968227113eb4176276 | Python | 21,819 | 451 | """
This script produces figure S7p (the right part) of the paper.
"""
import os
import numpy as np
import pickle as pkl
import pandas as pd
import src.models.kernel_regression as kernel_regression
import src.models.psth_regression as psth_regression
import src.visualization.vizregression as vizregression
import src.... |
be04e1e26d47f32b3e279ef0fc314fcfc3b0932a81d751c856c82c5501d3d807 | Python | 21,839 | 483 | import argparse
import logging
import os
import pickle
import sys
from collections import Counter
from datetime import datetime
from pathlib import Path
from typing import Dict, List, Optional, Union
import pandas as pd
import rdkit.Chem as Chem
import rdkit.Chem.AllChem as AllChem
from rdkit import RDLogger
from tqdm... |
8f823d4b1e75ed2f0de22e3706bd33b1097f7c1e7e88f92d4e631fd251a34f99 | Python | 21,846 | 628 | # 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... |
42cc0b447b8a5ec92bca7358255b24e24d12e0bcfba695e453241ddc9aca6017 | Python | 21,853 | 579 | import numpy as np
import torch
from torch.utils.data.dataset import TensorDataset
from torch.utils.data import DataLoader
import torch.nn.functional as F
from torch.autograd import Variable
def my_softmax(input, axis=1):
trans_input = input.transpose(axis, 0).contiguous()
soft_max_1d = F.softmax(trans_input,... |
9e8feaa89d0ddc9257dc831423b016815dd468735527ea4c9cab8283ce4c5b4b | Python | 21,859 | 487 | #!/usr/bin/python
# @author Neil Munjal
# @date 2019-07-27
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import scipy.stats as stats
from functools import partial
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestRegressor
from sklearn.ensemble imp... |
8c3cf26d97d4bd01ead759266a488e53987d57ef74f10c7ea5af63f1aba349ef | Python | 21,891 | 573 | """Functions for computing the quantized Gromov-Wasserstein distance and the SLB between \
metric measure spaces, and related utilities for file IO and parallel computation."""
# std lib dependencies
import csv
import itertools as it
import sys
from math import sqrt
from typing import Collection, Iterable, Ite... |
2c3611415c50c86d71521420b5634c48f3802d4f58e20b07967aa877b41a70fc | Python | 21,893 | 450 | """
This script produces figure S7H (the right part) of the paper.
This is the mean value of the auditory kernel as a function of ML and AP position
"""
import os
import numpy as np
import pickle as pkl
import pandas as pd
import src.models.kernel_regression as kernel_regression
import src.models.psth_regression as ps... |
402750b9d67960df92e8b3d2091d9aa38a4d0cf37723717de44aac6084f5b0bc | Python | 21,893 | 450 | """
This script produces figure S7F (the right part) of the paper.
This is the mean value of the auditory kernel as a function of ML and AP position
"""
import os
import numpy as np
import pickle as pkl
import pandas as pd
import src.models.kernel_regression as kernel_regression
import src.models.psth_regression as ps... |
04c90ab31188b0f7c7236b7b913eeca28c23fbb1fe5f744e158871defdf2365a | Python | 21,899 | 451 | """
This script produces figure S7l (the right part) of the paper.
This is the mean value of the auditory kernel as a function of ML and AP position
"""
import os
import numpy as np
import pickle as pkl
import pandas as pd
import src.models.kernel_regression as kernel_regression
import src.models.psth_regression as ps... |
07a9355fc6d72d6220a5632c8e7825dfe0191ad51969df037ab15ee2f65e1443 | Python | 21,899 | 451 | """
This script produces figure S7j (the right part) of the paper.
This is the mean value of the auditory kernel as a function of ML and AP position
"""
import os
import numpy as np
import pickle as pkl
import pandas as pd
import src.models.kernel_regression as kernel_regression
import src.models.psth_regression as ps... |
1a5fc7dbcfd65feeac89e490e8d369fd7fb009458e1baff6bc1cb3cce53b0ecf | Python | 21,906 | 26 | from regionscode.regions_per_sections_adult import regs_per_section, Regions_n_colors_List
def create_regs_n_colors_per_sec_list(atlasnum):
regs_per_sec_List = regs_per_section[int(atlasnum)] #list
regs_n_colors_per_sec_List = [('root', 'not detected', '000000', (0, 0, 0))]
for elem in Regions_n_colors_Li... |
a6517f80f82027be2e672edeb58aee1b6061e10997dc06e04a234b8b48f5d150 | Python | 21,906 | 592 | # coding=utf-8
# Copyright (C) 2021. Huawei Technologies Co., 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
#
# ... |
da9fdb038ba0d1ba6f7fe5ee7d2184b9db539ac029b72d08c202580fe3bdfea9 | Python | 21,918 | 500 | """Models for outlier detection"""
import numpy as np
import torch
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.functional as F
def reconstruction_loss(x, x_hat):
return F.mse_loss(input=x_hat, target=x)
def kl_divergence(mu, logvar):
return torch.mean(-0.5 * torch.sum(1 + logv... |
b0fcaa8000e7cd301aaa2d79e9fcdf462249f30fe63fe539f2f83ed021ab1b55 | Python | 21,923 | 654 | # 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... |
78471b6088f9ac27563b89fb0dc3e3303a3106126c2331363ab3a22a225dc322 | Python | 21,941 | 554 | # 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... |
bc11578864e1e70a87f469375f2a994692155180ee2b30c22233e64c963a4806 | Python | 21,951 | 566 | # -*- coding: utf-8 -*-
"""
@author: ronwd
"""
#%% Import everything
import numpy as np
import pandas as pd
import seaborn as sns
from pathlib import Path, PureWindowsPath
from scipy import io
import matplotlib.pyplot as plt
#%% Set seaborn stuff
sns.set_theme() #set seaborn default theme
#grabbed hex codes if n... |
c2c363bbfc6e3d870532633f2eae7247e4fd691914007c03411a4e4df0c33749 | Python | 21,960 | 470 | # this software is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
import imp
import signal
import numpy as np
#import tensorflow as tf
import tensorflow.compat.v1 as tf
tf.disable_v2_behavi... |
946192448e0eede4c3d01059670d548ea476f4e9173097003661cc3ea3f78c5f | Python | 21,967 | 733 | #!/usr/bin/env python
#
# Copyright 2006, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list... |
2d048fc669478adce11394e5709e4652488bbc6f84fbc6c650cf1f859942338f | Python | 21,975 | 550 | import math
import warnings
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import (Conv2d, build_activation_layer, build_norm_layer,
constant_init, normal_init, trunc_normal_init)
from mmcv.cnn.bricks.drop import build_dropout
from mmcv.cnn.bri... |
6595d8382b8f084764d73debad52ed6f60bb16e1ef177a21ed8ef1d8c004b107 | Python | 21,981 | 487 | import numpy as np
import sys
import json
from ray.rllib.env.base_env import BaseEnv
from mprl.rl.envs.stratego.stratego_spatial_multiagent_env import SpatialStrategoMultiAgentEnv
# Need raw numba functions
from stratego_env.game.stratego_procedural_impl import _get_game_result_is_invalid
# Numba Methods
from mprl.r... |
094768374ef42208c2b90976f8ea1e5ebf1fe0c9866250c4378a96a66ae4e07c | Python | 21,999 | 306 | import matplotlib.pyplot as plt
import numpy as np
import numpy.ma as ma
import sys
from scipy.stats import norm
from PIL import Image
from sklearn.linear_model import LinearRegression
sys.path.insert(1, "/Users/hyung/Research23_Network_Analysis/mBIN/Python/NetworkAnalysisGeneral/Code/SupportFunctions/")
from analysis... |
b7a00831154373a6f784a1c166e47227a3cce73182bcfd92d35ea7c722aea066 | Python | 22,019 | 504 | from abc import ABCMeta, abstractmethod
import os
import pandas as pd
from tensorflow.keras.callbacks import EarlyStopping
from tensorflow.data import TFRecordDataset
import tensorflow as tf
##################################################################################
################### Meta classes ... |
9d6906cbd2d9f62d29643aa786073f1c51a62689e7f7c4becabf313fbaeddea1 | Python | 22,037 | 515 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jul 4 11:38:51 2021
@author: Mesfin Diro
"""
from typing import Callable, Optional
import os.path as osp
import torch
from torch_geometric.data import InMemoryDataset, Data
import re
import numpy as np
from tqdm import tqdm
#from tqdm.notebook import t... |
3d61edfd21fe053eb6c77b181f04a9087091d09346b887b593411f6ca56d303f | Python | 22,045 | 605 | """Tests for source/odp_color_manager.py.
Focus on the pure-function color utilities — hex↔rgb conversion, hex
validation, contrasting-color picker, brightness / saturation math,
random / palette color generators. These run without any I/O, so they
exercise the helpers used everywhere downstream (synteny plots, ribbon... |
3dae41563f2438f05a5858bee28c192fcc9ba8dac485c43da80a1b9f72e90406 | Python | 22,051 | 536 | """Module with functions for creating plots for training report"""
import matplotlib.pyplot as plt
from matplotlib.ticker import MaxNLocator
import seaborn as sns
import numpy as np
import pandas as pd
from torch_geometric.loader import DataLoader
from sklearn.metrics import r2_score
import torch
from gnn_eads.functi... |
dd2371dd2f9cf792db26b2abf420d409d251b2c8391bd4368e85bffd7313058c | Python | 22,056 | 436 | from __future__ import print_function
from functools import reduce
from operator import or_
import numpy as np
import pickle
from os import listdir
from os.path import splitext
import random
from classicalClassifier import ClassicalClassifier
from deepClassifier import DeepClassifier
'''
def classifierMetadata(finalCl... |
3299d12751cc2b73426ed3590c6992f202724c3ec4aa5cb99c14a1f64425fd5f | Python | 22,066 | 681 | # SPDX-License-Identifier: LGPL-3.0-or-later
import argparse
import io
import json
import logging
import os
from pathlib import (
Path,
)
from typing import (
Any,
)
import torch
import torch.distributed as dist
import torch.version
from torch.distributed.elastic.multiprocessing.errors import (
record,
)
... |
bedbc6a5bd74c071d69d73a2ecc83fcea1166874cfc440ddbef3a5f35fe503b4 | Python | 22,089 | 642 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
"""Every class imported in this module defines an implementation of
an operator of the main domain. Any class name uses `_` to specify a
version defined in a specific opset. The class name without `_`
defines the current implementation. If... |
6e98607bf4d824359d7dc567cf8c416ac4b829904a40f24ec7f7822ef3f09622 | Python | 22,094 | 456 | #!/usr/bin/env python
import logging
import os
import importlib
import sys
import pickle
import numpy as np
import pandas as pd
from keras.callbacks import ModelCheckpoint, LearningRateScheduler
from keras.models import load_model
from scipy.stats import spearmanr
from keras.layers import Input
import tensorflow as tf... |
66673bc09f12f57c5ff0b4b234d29d2c2ac28c5a64614a1ba2c51ba9b52e1537 | Python | 22,111 | 725 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
from onnx.reference.ops.op_pool_common import (
get_output_shape_auto_pad,... |
f1e978d4a3de739db730252a5a352e3312503fbbff9ee102369790da1f5d28e9 | Python | 22,128 | 634 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import struct
import sys
import zipfile
from typing import TYPE_CHECKING
from onnx import TensorProto, helper
if TYPE_CHECKING:
from collections.abc import Mapping
def _make_model(
op_type: st... |
df4c83c4b83dbaf3c68009c77836614f35da51167f292a55dc844ac149ced0e2 | Python | 22,146 | 578 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""BLAST real-data streaming utilities for PatchTST-FM pretraining.
This module provides the BLAST stream used by the mixed-data trainer. It exposes
``BlastRealIterableDataset`` and preserves the trainer's sample contract::
{
"x": FloatTensor[context_length],
... |
a77890a3fc546f52600bf362dcd0c577fd0cb89d93c19dd42990c91fa20755c3 | Python | 22,157 | 458 | """
Implement the Numpy backend, and collect timing information with different parameters
William Nourse
August 26th, 2021
I have set myself beyond the pale. I am nothing. I am hardly human anymore.
"""
import numpy as np
import pickle
import time
import sys
"""
#######################################################... |
6766e60932fd1fc0695fb72d96f9116ac0da1feb4186c41921bc668ea3ad1c2c | Python | 22,213 | 492 | import numpy as np
import torch
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.functional as F
from losses import reconstruction_loss, kl_divergence
class ConvBlock(nn.Module):
def __init__(self, **kwargs):
super(ConvBlock, self).__init__()
self.conv = nn.... |
dab15d8ec69b84e4bca9a4c74b706831dff6749a0a049d56bda5e94de8eec794 | Python | 22,218 | 674 | #!/usr/bin/env python3
"""Configuration file for the Sphinx documentation builder."""
import datetime
import os
import sys
import warnings
from pathlib import Path
from bs4 import BeautifulSoup
import sktime
# -- Path setup --------------------------------------------------------------
# If extensions (or modules ... |
1d48624cb75c4eb4c736d8e2d80ba7b6a4bad29bb9e38f974f31e67aa75d65dd | Python | 22,246 | 499 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""Unit tests for the dpmodel DPA4 (SeZM) descriptor.
The suite runs on the dpmodel backend alone except for the source-gate
cross-backend check, whose pt import lives inside the test function because
ruff TID253 bans module-level ``deepmd.pt`` imports under ``source/tests`... |
391a2ad640e525e6f748897a100a5d36fcd7ebc99ecc31f36a9c2098f77155a9 | Python | 22,295 | 545 | from collections import defaultdict
import numpy as np
from numba import njit
import json
from helper_functions import find_runs, Annotate_with_ref_genome, Make_folder_if_not_exists, flatten_list
# ------------------------------------------------------------------------------------------------------------------------... |
198e465b65ccfb9e7a11ec151b9d3652e9b6a0d78cc252022f26579811d4f8e8 | Python | 22,308 | 530 | import random
from pathlib import Path
from functools import partial
import numpy as np
from scipy import ndimage
from scipy.ndimage import label, generate_binary_structure
from scipy.spatial.distance import cdist
from bcblib.tools.arrays_utils import coord_in_array
from bcblib.tools.blob import Blob
from bcblib.tool... |
17efa717af3cb69c416a31b4c12b6e20d6c7f96158b514ddcbceccb443bf235f | Python | 22,309 | 529 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""The Uni-Mol v1 backbone as a deepmd descriptor.
Wraps the ported Uni-Mol encoder (:mod:`deepmd.dpmodel.descriptor.unimol_nn`) in
the descriptor interface. Unlike every other descriptor here, Uni-Mol is global
rather than local: it attends over all atom pairs with no cut-... |
d5e725302a05fa90ad47b2a4c05485279c7273bd94999174915e2bf796291da9 | Python | 22,309 | 561 | """
Core Algorithm Implementation Module for pciSeq
This module implements the main Variational Bayes algorithm for spatial transcriptomics
analysis, primarily through the VarBayes class. The algorithm iteratively:
1. Assigns spots to cells
2. Determines cell types
3. Estimates gene expression patterns
4. Updates mode... |
a050835716028a3a63c0a74b82344ec312d79f95e98e47f65a2b36bc1fc6dd96 | Python | 22,314 | 515 | # Copyright 2019 Martin Haesemeyer. All rights reserved.
#
# Licensed under the MIT license
"""
Module with general utility functions and classes
"""
try:
import Tkinter
import tkFileDialog
except ImportError:
import tkinter as Tkinter
import tkinter.filedialog as tkFileDialog
import numpy as np
im... |
e760a642f58c61d17e082f6a2445d1532473ad6fb9696e0609e36e0444fdc12c | Python | 22,350 | 624 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Implements Generalized Autoregressive Conditional Heteroskedasticity models."""
__author__ = ["Vasudeva-bit", "SzymonStolarski"]
__all__ = ["ARCH"]
import itertools
from collections import OrderedDict
import numpy as np
import pandas as pd
i... |
edf6cfe80422678bcc2c8e11148d9d330f36975bbba39d057cbca0429a44a135 | Python | 22,374 | 582 | # 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... |
81f72e7aa4ae843984dd07297399134b1f964e69bf910f1020eb84073d924b89 | Python | 22,417 | 619 | """
Results class that summarizes the results of scCODA and calculates test statistics.
This class extends the ´´InferenceData`` class in the ``arviz`` package and can use all plotting and diacgnostic
functionalities of it.
Additionally, this class can produce nicely readable outputs for scCODA.
:authors: Johannes Os... |
8c4e1ab9a7827805750e2cc71b047841fa9e4e7f91c8842fbeb246e716dd3d45 | Python | 22,424 | 466 | 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 = ... |
df126dc0ccb11c916bd425188d2bbb1015083ade6349b2a5aaa475900985d008 | Python | 22,436 | 616 | from typing import Sequence
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import build_activation_layer, build_norm_layer
from mmcv.cnn.bricks.drop import DropPath
from mmcv.cnn.utils.weight_init import trunc_normal_
from mmcls.utils import get_root_logger
from ..builder import BACK... |
f95dc6faa67b8566b965c95e45f0ae2cdb5fe72521831a086207eef4d4f346fb | Python | 22,447 | 558 | import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
import matplotlib.cm as cm
import numpy as np
import dolfin as df
# set font & text parameters
font = {'family': 'serif',
'weight': 'bold',
'size': 16}
plt.rc('font', **font)
plt.rc('text', usetex=True)
mpl.rcP... |
dc08f5c4e5eb8f3142333ed604fe92843d09bd0f70b5c9cbdbe74eca5b52e88e | Python | 22,457 | 597 | # coding=utf-8
# Copyright (C) 2021. Huawei Technologies Co., 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
#
# ... |
9ce3b891b79aa7afcdf9dbc85ca96a2bc9cef29c1bc8ccc1bb2946819436b936 | Python | 22,467 | 717 | import pytest
from unittest.mock import patch
import pandas as pd
import numpy as np
import scanpy as sc
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.markers import MarkerStyle
from palantir.plot import (
density_2d,
plot_molecules_per_cell_and_gene,
cell_types,
highlight_cells_on_... |
135c03455cf253cd6814107dd5b6e183c8e0287564775728034e84790e3bfd8a | Python | 22,485 | 626 | from __future__ import annotations
import datetime
import enum
import math
from typing import Any
from sqlalchemy import asc
from sqlalchemy import case
from sqlalchemy import CheckConstraint
from sqlalchemy import DateTime
from sqlalchemy import desc
from sqlalchemy import Enum
from sqlalchemy import Float
from sqla... |
64cb8e9c9739516166c19b98d55299b38e5955de47e1e620999311f9f47366c3 | Python | 22,513 | 555 | """
@file: input_representation
Created on 26.09.19
@project: CrazyAra
@author: queensgambit
Input representation for all available lichess chess variants board states (including crazyhouse)
which is passed to the neural network
"""
from chess.variant import CrazyhouseBoard
import DeepCrazyhouse.src.domain.variants.... |
e36050d8e6bdd92bc6a0f43c9a80b93f04815dd95fdde0bec4d834ae435c9d77 | Python | 22,529 | 566 | import numpy as np
import pandas as pd
import argparse
import os
import re
import random
import multiprocessing
from rdkit import Chem
from tqdm import tqdm
from rdkit import RDLogger
RDLogger.DisableLog('rdApp.*')
# Get the mapping numbers in a SMARTS.
def get_idx(smarts_item):
item = re.findall('(?<=:)\d+', ... |
17470c69041688523c682959ad0873e47cb35cb2829712430da67de6d3c02d69 | Python | 22,553 | 373 | # using huggingface transformer to fine-tune BERT for rare disease entity linking
# a mentionBERT is created, here we use the contextual mention representation (average of token represetntations in the mention of the second last layer of BERT).
from sent_bert_emb_viz_util import load_data, get_context_window, get_c... |
a4ede00463673ad798ee601662eb2ff47d996aa52d502c8dd128a8e8145efa7b | Python | 22,564 | 489 | """Contextual Time-series Neural Classifier for TSC.
Implemented in torch backend.
"""
__authors__ = ["fnhirwa", "srupat"]
__all__ = ["CNTCClassifierTorch"]
from collections.abc import Callable
import numpy as np
from sktime.classification.deep_learning.base import BaseDeepClassifierPytorch
from sktime.networks.cn... |
c06284650de5397ed99bf0017dd782e4bb36b0dc4ffad52d057a100f5a99ce3d | Python | 22,599 | 612 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Aug 2 22:57:19 2021
Analysis on grid search results
- First a rough grid search (fingsearch=False) then a finer gridsearch
(finegsearch=True)
- standard SHJ (nbanks=False); or simulation with two banks of units modelling
anterior and posterior hpc (nb... |
570bb5cdee575cf2cb968953244612b4d691ea435fae3fdd658c599b44ec4f35 | Python | 22,627 | 583 | # imports
import os
import numpy as np
import pandas as pd
from skimage import io
import seaborn as sns
import matplotlib.pyplot as plt
import cv2
import torch
import torchvision
import torchvision.transforms as transforms
import torch.nn as nn
from scipy.stats import pearsonr
from scipy.stats import spearmanr
from ... |
a285cbf82b34755dbcd8250179f9b11471d06c3f72775286658a5fe3bc5874ed | Python | 22,652 | 539 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This prog... |
202395f75e38e976831b7e9c82f133e1c5262e81c45e6f42e6ebf308b0cd6190 | Python | 22,655 | 698 | # 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... |
e6c41a72487a5f1e2ee754af7484b3bbeeed2c320328ece9a954c3f711105b50 | Python | 22,665 | 631 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Eclectic utilities for the datatypes module."""
import numpy as np
import pandas as pd
def _get_index(x):
if hasattr(x, "index"):
return x.index
elif isinstance(x, np.ndarray):
if x.ndim < 3:
return pd.Rang... |
ebdb9efd8c3874ed8bc14196c7d24ba9a624739c79e5642ef526b384a7c8b3fe | Python | 22,668 | 589 | from itertools import chain
import numpy as np
from sklearn.metrics import normalized_mutual_info_score, adjusted_rand_score, r2_score, confusion_matrix
from scipy.optimize import linear_sum_assignment
import torch.nn as nn
import torch.optim as optim
import torch.utils.data as D
from tqdm import tqdm
from sr... |
ab34140ac59b06c952c7bccec7d311951abba8a0bb4a1503153d9fabc67c2261 | Python | 22,673 | 616 | """ Sparc View Tree
WorkFlow:
1. Create schema class
2. Create sheet importing schema class
3. update collect_sheets in GoogleSheets
4. any merging in graphs and harding is down in the following
functions in GoogleSheets (merge_graphs & hardcode_graph_paths)
5. rerun sheet.py to generate spa... |
b3c9e2f845f6f57c787feeb4daf8143080a6059878bcd373696d8c90275ce94d | Python | 22,676 | 648 | # 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... |
00cf257580af0c178c6e58f7bc1331677980f2e1cfa5a7a0ad626f803119a747 | Python | 22,705 | 502 | """
Generate clustered datasets for use in neuroimaging analyses
Authors: Chris Foulon & Michel Thiebaut de Scotten
Description:
------------
This script is designed to generate clustered datasets, particularly synthetic lesions, for neuroimaging analyses.
It supports multiple clustering methods, including KMeans and... |
276ee60a2dd803da427599259c83308ca4e437604f054333e0d3fb3b3f9cba69 | Python | 22,722 | 539 | import os
import warnings
from pathlib import Path
import csv
from typing import Union
from matplotlib import font_manager, pyplot as plt
from nilearn import plotting
from nilearn.image import image
from nilearn.regions import connected_regions
from tqdm import tqdm
import numpy as np
from scipy.spatial.distance impor... |
222cae65277e6fcd91d9fe63089c71692b8038d6f3cb20ba53454e24001923f0 | Python | 22,744 | 694 | #%%
import numpy as np
from scipy.stats import spearmanr, kendalltau
from numpy.typing import NDArray
from joblib import Parallel, delayed
from tqdm_joblib import tqdm_joblib
#%%
class RSA:
"""Perform RSA between RDMs.
Parameters
----------
rdm1 : NDArray
The first RDM or a set of RDMs.
rdm... |
2e43d6c3f049d4842d1260d036605c305c763f219d7a3fc128ec469863d3b522 | Python | 22,750 | 402 | """Isolated GPU pilot for competitive allocation; frozen benchmark data are read-only."""
from __future__ import annotations
import argparse
import gc
import json
import os
from pathlib import Path
import shutil
import sys
import tempfile
import time
import traceback
import numpy as np
import torch
from threadpoolctl... |
7a9ab71b07a008dc2ff9b4e26d4cc7748dfb18a74fded768b94666e51e48caeb | Python | 22,789 | 558 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import functools
import glob
import os
import re
import shutil
import sys
import tempfile
import time
import unittest
from collections import defaultdict
from re import Pattern
from typing import TYPE_... |
b2b871c4e016feac9f7bba0815fba25fa82f8a8bb90917e57b90d529ef05b41d | Python | 22,798 | 594 | # 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... |
7c5146cebf35ffce0bcfaf2778effb9f6c393e23c6db218d9f503e2d1e3e7758 | Python | 22,803 | 652 | # 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... |
ba95ced325dd4fe92927a1dac3b946970efb499637205cbc85154449192b84d6 | Python | 22,824 | 484 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""pt_expt SO(2) runtime bindings for accelerated inference kernels.
The dpmodel SO(2) modules are array-API only. These wrappers inject the
reference PT inference paths around three hot paths, mirroring
``deepmd.pt.model.descriptor.sezm_nn.so2``:
- the block-diagonal GEMM... |
5aa1213fc31fc6316741e6a7e34f5ab4e7eba681955f3b2c2bf8835a821cc3a6 | Python | 22,832 | 658 | """
Copyright (c) 2018 Ryuichiro Hataya
the source code of SELayer is released under the MIT License
https://github.com/moskomule/senet.pytorch/blob/master/LICENSE
We built our base CNN model using timm(https://github.com/rwightman/pytorch-image-models).
Copyright (c) 2019 Ross Wightman
the source code of timm... |
e703f2967b80b6ba7bac138c6c90818eb95c42776494662b8307e0e838571e32 | Python | 22,833 | 522 | import torch
import torch.nn as nn
import logging
from cormorant.cg_lib import CGModule, SphericalHarmonicsRel
from cormorant.nn import RadialFilters
from cormorant.nn import InputMPNN, InputLinear
from cormorant.nn import OutputPMLP, OutputLinear, GetScalarsAtom
from cormorant.nn import NoLayer
from cormorant.nn im... |
03fd6b1c043ec7b438570092f7b41961301b54ef7f98151f41779126d47e8655 | Python | 22,844 | 457 | # -*- coding: utf-8 -*-
"""Integer handling class `IntegerCentering` to be used in combination with CMA-ES.
Reference: Marty et al, LB+IC-CMA-ES: Two simple modifications of CMA-ES to
handle mixed-integer problems. PPSN 2024.
"""
import warnings as _warnings
import numpy as np
centering_on = True
'''convenience flag t... |
1efa7b30dbf1360af36b2a874e81c8305bfa464998fa8f7b0754fe367c70fa53 | Python | 22,854 | 435 |
"""
Script for identifying stimulus and behavior related neurons in random-wave experiment data
"""
import model
import numpy as np
import utilities
import h5py
from scipy.ndimage import gaussian_filter1d
import os
from os import path
from experiment import Experiment2P
from numba import njit
from multiprocessing imp... |
2ae3f76f95b548fc59489aa3359d3c9af553c13fdb4ce099b61ba22f42e48edf | Python | 22,943 | 504 | from futhark_ffi import Futhark
from types import MethodType
from typing import Union, Optional
from cajal.run_gw import DistanceMatrix
from cajal.run_gw import Distribution
from cajal.run_gw import cell_iterator_csv
from cajal.utilities import n_c_2, uniform
import numpy.typing as npt
from math import exp, log
import ... |
cffa13f439c6abab6ae9d5c1997f12b37d0f4311355d20d431996b5959bbfc4d | Python | 22,956 | 496 | import numpy as np
import tensorflow as tf
import tensorflow.keras.layers as KL
"""
copied from https://github.com/rishigami/Swin-Transformer-TF/
"""
CFGS = {
'swin_tiny_224': dict(input_size=(224, 224), window_size=7, embed_dim=96, depths=[2, 2, 6, 2], num_heads=[3, 6, 12, 24]),
'swin_small_224... |
0998db5b9074dc9413535ba86f17df2efa44a2605d7688b65bfeff9863058624 | Python | 22,981 | 638 |
from VesselGen.result_analysis.simulate_fow_pressure import *
from matplotlib import rcParams
rcParams.update({'figure.autolayout': True})
import scipy
import os
import matplotlib.pyplot as plt
import numpy as np
class VtkMorphAnalyer(VtkNetworkAnalysis):
def __init__(self, pt_file=None, root_loc=None, vsize=22... |
bd7fdbf88fa05c9ad34f71810be52000f48bd605436005e1c5a021eecdfa324f | Python | 23,028 | 667 | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
import torch.utils.checkpoint as cp
from mmcv.cnn import (ConvModule, build_conv_layer, build_norm_layer,
constant_init)
from mmcv.cnn.bricks import DropPath
from mmcv.utils.parrots_wrapper import _BatchNorm
from ..builder imp... |
1bbab26a219b1b0ae2dca8e903427ef08f6cf052ec7b14bc42a85a155b8c0d98 | Python | 23,035 | 671 | """Methods to convert between different file formats."""
import collections as col
import gzip
import os
import re
import Bio.PDB.Atom
import Bio.PDB.Chain
import Bio.PDB.Model
import Bio.PDB.Residue
import Bio.PDB.Structure
import numpy as np
import pandas as pd
# -- MANIPULATING DATAFRAMES --
def split_df(df, ke... |
1d7b87129b7b0d497507e890cd0f80976102ef7759bc396af598a59f6ba5e381 | Python | 23,068 | 618 | from pyontutils import identity_bnode as idbn
from collections import Counter, defaultdict
def nst_to_adj(l):
if not l:
return []
start = l[0]
if (isinstance(start, list) or isinstance(start, tuple)):
raise ValueError('malformed')
first = [] if start == "blank" else [(start, e[0]) fo... |
373d513ad2ba0da242fd87c0b071bc665a53ef596e6863ff6a29d1150180452a | Python | 23,069 | 427 | """Resumable unified matrix-only benchmark. External truth enters evaluate only.
Run: python -m short2long.unified_benchmark --output-root ... [--smoke]
The small smoke uses full catalogues but never becomes a main-table result.
"""
from __future__ import annotations
import argparse
import copy
import gc
import json
i... |
8f602fb276f9e6f2767eaf8a067946fd01c9f01647c78a6d63af8598dadf6076 | Python | 23,079 | 565 | # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
"""Base class templates for distances or kernels between time series and tabular data.
templates in this module:
BasePairwiseTransformer - distances/kernels for tabular data
BasePairwiseTransformerPanel - distances/kernels for time series... |
bfd765b0aec3893327bef37aa4c1fecef3ddbf6c96a2ffc860598a6bb78b5c3b | Python | 23,093 | 603 | #-------------------------------------------------------------------------------
# elftools: dwarf/enums.py
#
# Mappings of enum names to values
#
# Eli Bendersky (eliben@gmail.com)
# This code is in the public domain
#-------------------------------------------------------------------------------
# Keep dict(...) cons... |
5610270fc9932b6e981d5bf485a5a37d871d9c9b8783ab878590fe4d2b3c09fa | Python | 23,094 | 661 | # 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... |
535c047760a0b31977035aa1a5ba4faae751104c5b9e6e920ebf7aacb7fec7b9 | Python | 23,097 | 519 | # -*- coding: utf-8 -*-
"""
Copy for generating basic stats used in paper
@author: ronwd
"""
import numpy as np
from pathlib import Path, PureWindowsPath
from scipy import stats, io
#%% Feature sweep data
#Set file
filepath = "Your cool file path goes here"
results_file = PureWindowsPath( filepath + "\\GitHub\\Tem... |
cefffe0a6f3a227a3de750a992ff9917e80298a1ce1d7faa1dace47fbca85ec1 | Python | 23,143 | 471 | from __future__ import print_function
from neuron import h
from ..util import nstomho
import numpy as np
from .cell import Cell
from ..util import Params
from .. import data
__all__ = ['Pyramidal', 'PyramidalKanold', 'PyramidalCeballos']
class Pyramidal(Cell):
celltype = 'pyramidal'
scaled = False
@... |
ea17c6a7898e8db1157757ece54e3ac48cc11caf6da1e48d2d8cb2d4f806ab23 | Python | 23,176 | 606 | # SPDX-License-Identifier: LGPL-3.0-or-later
r"""Pair-clearance check for frame validity filtering.
A frame is admissible when every atom pair keeps the clearance the
training-frame filter prescribes. That clearance is a fraction of each pair's
own length scale, so the check is scale-free: the quantity compared agains... |
66ba055735e00fef3b23159bb19d3136a6bb1c40837cf238d9e433b5ac0c5e80 | Python | 23,188 | 457 | import os
import numpy as np
from collections import deque
from datetime import datetime, time, timedelta
from statistics_processing import standardizer, standardize
from connect_laser_device import connect_laser_device
from parameterSetup import ParameterSetup
from stagePredictor import StagePredictor
import timeForma... |
340b3eca5a0f791e3b903508661028c1beba7c90607c8b391ad7e74e552a6810 | Python | 23,256 | 522 | """
Functions for sampling points from an SWC reconstruction of a neuron.
"""
import math
from typing import Iterator, Callable
import numpy as np
import numpy.typing as npt
from scipy.spatial.distance import euclidean, pdist
from pathos.pools import ProcessPool
from .swc import (
NeuronNode,
N... |
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