sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
35c32c87aabee69b30e4e4c8a575d44b77a22924c8572f951cf1d3840ac58463 | Python | 13,480 | 357 | from abc import ABC
from typing import List, Tuple
import torch
from torch import nn as tnn
from torch.autograd import Variable
from reinvent.models import meta_data
from reinvent.models.transformer.core.enums.sampling_mode_enum import SamplingModesEnum
from reinvent.models.transformer.core.network.encode_decode.mode... |
6053865d1ed9b4740a31bd6c0ea7429f611689b09cb030f43988dc6cb7e5a3dc | Python | 13,501 | 398 |
# Script containing the modular version of the code
# so far we have only implemented the non_linear_embedding layer
# for simplicity we can just use dense layers for the merge operations
import numpy as np
# import matplotlib.pyplot as plt
import torch
import h5py
import torch.nn as nn
from torch.utils import dat... |
2b82b6c26dd9842be0f026ceba60ce9585a713099835b399948b0a74a615859c | Python | 13,503 | 373 | """
Tests for ISC Group Difference (ISC Group) module.
Test organization follows the TDD plan (isc-group-tdd-plan.md):
Phase 1: Core ISC Group Difference Computation
Phase 2: Permutation Method
Phase 3: Bootstrap Method
Phase 4: Main Function
Phase 5: Statistical Correctness Tests
Phase 6: Inte... |
617361485970c0d5faa769ff7c00f259b00a16c1f89564e5e9cd8ce5af00ba3c | Python | 13,503 | 343 | # Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import logging
import os
import to... |
98bc4366345da181e743f87e6ba95e7e26d4458eee40d5c645934195c8cf6b38 | Python | 13,503 | 295 | from utils_ds import *
from models.reaction import *
try:
from torch.utils.tensorboard import SummaryWriter
except:
print("tensorboard, fail")
import pickle
from copy import deepcopy
import matplotlib as mpl
from rdkit import RDLogger
RDLogger.DisableLog('rdApp.warning')
mpl.use('Agg')
os.environ["CUBLAS_WORK... |
3f8ba4f0b048612a30902f04094675552f3194e57a9b5d9dc3411225ff653c1b | Python | 13,513 | 320 | """The two tiny parity anchors reproduce their committed references.
These are the numbers everything downstream is measured against: the
converted-architecture gate, the live in-process parity run, and the backend
parity goldens all reduce to "does this checkpoint still produce these
values". They run per pull reques... |
e6af7444f3a70d6dac45b3488443194040de5f7b8bb41a63433633c0c74e4229 | Python | 13,519 | 257 | import os
import math
import tensorflow as tf
if tf.__version__[0] == "2":
tf = tf.compat.v1
import numpy as np
from common.common import safe_make_dir
from common.batch_generator import BatchGenerator
import common.architecture as architecture
def experiment_run(config_dict):
tfrecords_folder = config_dic... |
e4899debae80ad67fe958bdf0043b4d8ea4e255f54642a824b127eab73098af9 | Python | 13,520 | 402 | import numpy as np
# import matplotlib.pyplot as plt
import torch
import h5py
import torch.nn as nn
from torch.utils import data
import itertools
import json
import sys
from os import path
sys.path.insert(0, '../')
from utilities import SequenceDataSet
import gc
gc.collect()
nameScript = sys.argv[0].split('/')[-1]
... |
40124cc863d8b4e4b0c2b7ee93fda0a03cae8a90bf1aff05b0411a0438c68231 | Python | 13,557 | 341 | import os
import pickle
import numpy as np
import pandas as pd
from tqdm import tqdm
from common.utils import read_sas7bdata_pd
sides = [None, 'R', 'L']
def build_single_img_based_multi_progression_meta(oai_src_dir, only_baseline=False, use_sas=False):
# visits = ['00', '12', '24', '36', '72', '96']
# ... |
3e03b98bc55eb8ac77b239bba9304a764a07c84f1cd09ad7014341278dba43bc | Python | 13,574 | 362 | from math import pi as PI
from typing import Optional
import torch
import torch.nn.functional as F
from torch.nn import Embedding, Linear, ModuleList, Sequential
from torch_scatter import scatter
from torch_geometric.nn import MessagePassing, radius_graph
from torch_geometric.utils import to_dense_batch
import torch... |
15d3cfc3c21a8792a46a7ce9f18e938bee339395c0b00215db1990a163a2abc2 | Python | 13,586 | 275 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from fairseq.dataclass.utils import gen_parser_from_dataclass
from fairseq.models import (
register_model,
register_model_architecture... |
ff33f0336e4685ed30bf4c21c7ddc292b1bb52d37140f4d1a1f75a7f777ffd21 | Python | 13,586 | 256 | """AIRR export: Rearrangement and Reactivity, projected from the definitive tables.
Two files, at the two levels AIRR models:
=============================== ==============================================================
``vdjdb.rearrangement.tsv`` one row per chain -- AIRR Rearrangement
``vdjdb.reactivity.tsv`... |
a99dbccd611e410243839f46d8f8384b2086b22dd2fc07cd9a82ab2a3bf09eee | Python | 13,589 | 375 | """Temporal signal processing — resampling, filtering, and basis functions."""
import warnings
import numpy as np
import polars as pl
from scipy.interpolate import interp1d
from scipy.signal import butter, filtfilt
def calc_bpm(beat_interval, sampling_freq):
"""Calculate instantaneous BPM from beat to beat inte... |
c1e0708d38070635a5cd5574762d0fc7dc66b104b75848e92a62b4a8526fea14 | Python | 13,591 | 402 | # copyright (c) 2020 PaddlePaddle Authors. All Rights Reserve.
#
# 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... |
cff0dd5307340d0a233db6b7f1043ecaf0e3858ffae6fff4902666ea62e4cbbc | Python | 13,598 | 350 | """Permutation tests for autocorrelated time series.
Shuffling the samples of a time series destroys its autocorrelation and inflates
false positives. These surrogate-data methods build the null while preserving
temporal structure:
- `circle_shift`: rotate the series (preserves autocorrelation exactly)
- `phase_rando... |
9adc7990a0bd54dd074872fc001c4dc4fd81612195b83536c8fa51f16a95be51 | Python | 13,607 | 359 | """Normalize relation matrices and construct owned, metadata-consistent results."""
from copy import deepcopy
from dataclasses import dataclass
from math import isqrt
from pathlib import Path
import numpy as np
import polars as pl
from scipy.spatial.distance import squareform
from nltools.data.ownership import _copy... |
8e92a8c953575bdf2173c7a2452e8a7a86dcb911cbf073382f26400c1bf288a5 | Python | 13,613 | 302 | import numpy as np
import torch
import torch.nn as nn
from torch.utils.data import DataLoader
from metric import *
from models import *
import csv
import random
from data import *
import argparse
import os
import sys
class PreTester():
def __init__(self, smile_list, conf_tester):
self.config = conf_teste... |
1f8871285941f0904ba4d02a6c0f07939cc0fcb791650e7cf4137cb7ca975594 | Python | 13,614 | 354 | import copy
from pymonntorch.NetworkCore.Base import *
class SynapseGroup(NetworkObject):
"""This is the class to construct synapses between neuronal populations.
Attributes:
src (NeuronGroup): The pre-synaptic neuron group.
dst (NeuronGroup): The post-synaptic neuron group.
net (Net... |
0bc31bc13b867222fbe1329feacca2dd51a3b94843013468c50dda1420192408 | Python | 13,616 | 277 | import numpy as np
# import tensorflow as tf
import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()
import os
class stdp:
def __init__(self,
stdp_LR_fixed_potentiation,
res_LR_decay_factor,
number_of_networks_IN,
w_res_exc_min_m... |
4b23f6c01e714299a378dd255e6337964c4422a2c484c4ec384d1b7a9c1c982c | Python | 13,629 | 412 | from abc import ABC, abstractmethod
from typing import Dict, Optional
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import torch
from tensorboardX import SummaryWriter
from torchvision.utils import make_grid
from .plotting import plot_spikes, plot_voltages, plot_conv2d_weights
from ..utils im... |
e24f402d9eb122be6b0d0fe1aa798d661e1060ace56e66552a0e17dcca754370 | Python | 13,632 | 240 | """Where each self epitope occurs in its own species' reference proteome, and how exactly. #632.
**What this is and is not.** The antigen a receptor engages is the **pMHC**, and the epitope is the
part of it that is recognised (``docs/standards/terminology.md``). ``antigen.gene`` and
``antigen.species`` are neither: t... |
37d2f5e68dcd0866fca2a207c5a74c660c2323ad4bf2fd743c67b0f51aec00cf | Python | 13,633 | 414 | """Transfer learning (TL)
Train a given model with new data. The data comes from a file with SMILES
strings. The file is assumed to be in multi-column format separated by commas
(CSV) or spaces. The SMILES string is extracted from the first column.
The SMILES strings is expected to be a complete molecule.
"""
fro... |
c032cdb5cc1458fe09f56e400c4522282be6e5ae2bf8e23499c833d4c0a40f06 | Python | 13,642 | 449 | from copy import deepcopy
from pathlib import Path
import ase.io
import numpy as np
import pytest
from ase.atoms import Atoms
from mace.calculators.mace import MACECalculator
from mace.cli.run_train import run as run_mace_train
from mace.data.utils import KeySpecification
from mace.tools import build_default_arg_pars... |
f63e0cfc4098c3c34502b3dd314fa684011e93ec2dee6d02d59d0d4260dc70c7 | Python | 13,644 | 240 | """The definitive tables: tidy, flat, linked by ``record_id``.
These are the pipeline's output. Everything shipped -- legacy, AIRR, the new format -- is a join and
a pivot away from here, never a parallel assembly.
One observational unit per table, one variable per column, one observation per row:
=============== =... |
0689cb881a9beb28434c545b59d039bd6040e00cde9b07e359d2ee3113de176b | Python | 13,652 | 396 | # sys
import sys
import os
import dill
import configparser
from pathlib import Path
# sci
import numpy as np
import pandas as pd
import quantities as pq
# ephys
import neo
import elephant as ele
# plotting
import matplotlib as mpl
import matplotlib.pyplot as plt
# own
import sssort.functions as sf
import sssort.plo... |
195c7b5d587684e4e4cba6ee99912eace7b453c721f41301351fefc681b40606 | Python | 13,668 | 366 | # Copyright (c) 2021 PaddlePaddle 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 appli... |
ee076627e46f4f5fc84c1c3576a4ed64e113ad9b3c3fdc631d162beb307284c8 | Python | 13,671 | 347 | import torch
import torch.nn as nn
from .mol_tree import Vocab, MolTree
from .nnutils import create_var
from .jtnn_enc_bo import JTNNEncoderBO
from .jtnn_dec import JTNNDecoder
from .mpn import MPN, mol2graph
from .jtmpn import JTMPN
from .chemutils import enum_assemble, set_atommap, copy_edit_mol, attach_mols, atom_e... |
b2b8d4d7cbb044274c0265934acd588e3ee579d78ecdde5444ec7fba5e8f47a7 | Python | 13,673 | 350 | import torch
import torch.nn as nn
from functools import partial
from typing import Union, List
import torch.nn.functional as F
from torch_geometric.data import Batch
from torch_geometric.nn.conv.gcn_conv import gcn_norm
from torch_geometric.nn.conv import GCNConv
from torch_geometric.nn.glob import global_mean_pool, g... |
975e78914afa852803c0629d048deaebeebe8162686d2f0aefc965726f117931 | Python | 13,677 | 366 | from __future__ import division
from __future__ import print_function
import os
import re
import sys
from scipy.io import wavfile
import numpy as np
from numpy.lib.stride_tricks import as_strided
# store as a global variable, since we only support a few models for now
models = {
'tiny': None,
'small': None,
... |
f6ba8f5c51f3afe559d4537269d01b01c3eb621bc42aec37d8a969e017cb669b | Python | 13,679 | 393 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
import os
import sys
import io
import numpy as np
import torch
import torch.nn.functional as F
from .. import FairseqDataset... |
9f4267841f7c2908223a91a457f8f35ea3e26b4dcffddd4d11e35c75b120b874 | Python | 13,681 | 466 | """Manifold module.
In other words, a topological space that locally resembles
Euclidean space near each point.
Lead author: Nina Miolane.
"""
import abc
import inspect
import types
import geomstats.backend as gs
import geomstats.errors
from geomstats.geometry.connection import ConnectionFromMetric
from geomstats.g... |
5648ed75498e2dcde088e1e869ffe4f37627e100a284128e797cc5c5cca16b2e | Python | 13,690 | 389 | """
Runs the network with given parameters.
Saves the spike counts at different trials and the average Na current magnituted
for different stimuli
"""
from brian2 import *
import numpy as np
from tqdm import tqdm
import os
from pathos.multiprocessing import ProcessingPool as Pool
from scipy.ndimage import gaussian_fil... |
e5c84b182b29f12457832b06ed08c42315ebbd71621b03bc39d02185fd07811d | Python | 13,721 | 308 | '''
Description:
Author: voicebeer
Date: 2020-09-14 01:01:51
LastEditTime: 2021-12-28 01:46:52
'''
# standard
import argparse
import torch
import torch.nn.functional as F
import torch.nn as nn
import numpy as np
import copy
import random
import time
import math
from torch.utils.tensorboard import SummaryWriter
#
impo... |
7e1f036b364fe124418bd54e1c927b0a01d550f730ff33c1acc9c87d3a27e84a | Python | 13,728 | 362 | # Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# This work is licensed under the Creative Commons Attribution-NonCommercial
# 4.0 International License. To view a copy of this license, visit
# http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to
# Creative Commons, PO Box 1866, Mountain ... |
7e56a594260cfb7174dfa280e6a261232ae38ed09f115bdbb8fa26448279c48f | Python | 13,734 | 427 | import numpy as np
from scipy import signal as sig
# Filtering functions
def butter_lowpass(lowcut, fs, order=8, sos=False):
''' Create a lowpass butterworth filter '''
nyq = 0.5 * fs
low = lowcut / nyq
if sos:
sos_out = sig.butter(order, low, analog=False, btype='low', output='sos')
r... |
b9934c06ff5688a12901bd57cccdd67970ec9de0a13c6ed3606983aaf22c9626 | Python | 13,734 | 413 | #cript containing the modular version of the code
# so far we have only implemented the non_linear_embedding layer
# for simplicity we can just use dense layers for the merge operations
import numpy as np
# import matplotlib.pyplot as plt
import torch
import h5py
import torch.nn as nn
from torch.utils import data
im... |
5f65a40bb6b3d8c3f36ef44d4dbc5a7b94db08ebef5408d54c64c9e431a820f6 | Python | 13,736 | 245 | import pandas as pd
import numpy as np
import subprocess
def check_abnormal_aa(peptide_seq):
len_seq = len(peptide_seq)
cnt = 0
standard_aa = ['G','A','P','V','L','I','M','F','Y','W','S','T','C','N','Q','K','H','R','D','E']
for i in peptide_seq:
if i in standard_aa :
cnt = cnt+1
... |
b225a1d76ac0ec4c007d5a09be008c553f0042b8b4097bbdde12a34345d51827 | Python | 13,746 | 363 | # Copyright 2020-2025 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import pytest
import logging
import time
import math
from tests.end_to_end.utils.tr_common_fixtures import (
fx_federation_tr,
fx_federation_tr_dws,
)
from tests.end_to_end.utils import db_helper as db_helper
from tests.end_to_end.u... |
9428f4a78d2d67eed6d523fb7051919a29ef7bd07c1bc25e0dd9a218d3614d31 | Python | 13,752 | 387 | import os
from collections import OrderedDict
from pprint import pprint
from typing import Union, Dict, List, Tuple, Optional
import numpy as np
import pandas as pd
import sanpy
from sanpy.bAnalysisResults import get_analysis_result_definitions
from sanpy.sanpyLogger import get_logger
logger = get_logger(__name__)
... |
fbdba4d93405c06f8c98de956bcc673a69eb060437cc9177779c01a234d8da9e | Python | 13,756 | 405 | # Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# This work is licensed under the Creative Commons Attribution-NonCommercial
# 4.0 International License. To view a copy of this license, visit
# http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to
# Creative Commons, PO Box 1866, Mountain ... |
7f7674d01825b30cfefe16e1ce73c1b1c1c46abbeba28b25f5dc0c398516bfad | Python | 13,772 | 360 | import numpy as np
import scipy as sp
import pandas
import brian2
import copy
import seaborn as sns
from adjustText import adjust_text
import matplotlib.pyplot as plt
import statsmodels.api as sm
from sklearn.metrics import roc_auc_score
from sklearn.model_selection import train_test_split
from sklearn.linear_model im... |
41bd48495d89931e09185d7b0a8329f40d605b0a30167f156109702f469e2135 | Python | 13,777 | 300 | """Inference baselines recorded while legacy is still the live stack.
"The rewrite is not slower" is only falsifiable against an *old* number, so
these cases exist to be measured now and frozen, not to gate anything. They
publish through the nightly ``benchmarks`` job's ``--benchmark-json``
artifact; the downstream co... |
dd55ff15f7d623865c99db9b102522152624c26bdda2dc14da863768bec5a63e | Python | 13,780 | 347 | ################################################################################
# Import, Set up MPI Variables, Load Necessary Files
################################################################################
import os
from os.path import join
import sys
import matplotlib
import matplotlib.pyplot as plt
from matp... |
839e0fbe871ac36e94f6d5b9d0ce9dca1d9c96d04fd96e885b21e0942e415d33 | Python | 13,794 | 383 | # Copyright (c) 2021 PaddlePaddle 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 appli... |
d85c7c542b1729b513e379a4021cea8198a7d7cfabd9fd324310a1e92fcc2888 | Python | 13,795 | 399 | """
source:
https://github.com/open-neuromorphic/open-neuromorphic.github.io/tree/main/content/english/blog/spiking-neural-network-framework-benchmarking
"""
from typing import Callable, Optional, List, Tuple
import warnings
from time import time
def timeit(
callable: Callable,
min_runs: int = ... |
7e53747701057ec94b8a122997dfc11379e4a683c6a2275c70bca5324257df88 | Python | 13,814 | 357 | """HDF5 I/O utilities for nltools data types.
Shared serialization logic for BrainData and Adjacency objects.
"""
import io
from pathlib import Path, PureWindowsPath
import nibabel as nib
import numpy as np
import polars as pl
try:
import h5py
from h5py import File as h5File
except ImportError as _h5_import... |
dd164cf1f535c90889d049b9b912abfacce7915b78d35cb3b113a496939dddb6 | Python | 13,819 | 401 | import os
import numpy as np
import pandas as pd
from nltools.data import Adjacency, Design_Matrix
import networkx as nx
from scipy.stats import pearsonr
from scipy.linalg import block_diag
from pathlib import Path
def test_type_single(sim_adjacency_single):
assert sim_adjacency_single.matrix_type == "distance"
... |
e2687ed51fd8b9fe39051f8c0704204a0c208ebe080ab7b076d0d9cca5c8005b | Python | 13,819 | 345 | """Computes crossval performance while also fits detection threshold of model.
Always run this script after training a model, otherwise you will not have the
best performing output threshold for the model.
In the "Experiment settings" block of this script, set the location of the training run.
In the "Data settings"... |
f72308f7164203bfea7a45fe516980b7b17d4db3ebe67041db8c80ff025744e4 | Python | 13,827 | 362 | # Copyright (c) 2020 PaddlePaddle 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 app... |
d2971ce56ff08d907b2f9f24765cc9e352d9f2241f455ad9922e095dee97533e | Python | 13,841 | 404 | # Copyright (c) 2022 PaddlePaddle 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
#
# Unle... |
ada23ea1a4afda3b88ebf2aef574a74a2c6d3772cdf63e63789bbce3100d1747 | Python | 13,851 | 394 | # Copyright (c) 2021 PaddlePaddle 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 appli... |
88024557711973ef4227648749f9598f4272b2e5aeab08b9e496e1ab93518773 | Python | 13,858 | 352 | """
Utilities for real-time multi-thread data generator
"""
import scipy
import numpy as np
from tensorflow.keras.utils import Sequence, to_categorical
class CustomDataGenerator(Sequence):
def __init__(self, hdf5_file, brain_idx, batch_size=16, view="axial", mode='train', horizontal_flip=False,... |
2d362b6d072be32a251cab219da5c435c23e7e1786b333eba0085a4dc1e879a5 | Python | 13,871 | 309 | #!/usr/bin/python3
###
# Master controller for the TreeMaze. It communicates with the arduino through serial port.
# Receives data through GPIO inputs and serial.
###
import threading
from MazeHeader2 import *
PythonControlSet = ['T2','T3a','T3b','T3c','T3d','T3e','T3f','T3g','T3h','T3i','T3j',
... |
36d7cb983970884d4e6d414b6f4273ffd21a7f8058f5bd9ef62a1fe57aba951a | Python | 13,872 | 398 | # Copyright (c) 2022 PaddlePaddle 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 appli... |
3bee881392b56e7ec2dea1e9ddf1eb86a7cae2d56ab7131be1b3744108481d5e | Python | 13,873 | 364 | import hashlib
import importlib
import logging
import os
import tarfile
import sys
from functools import cached_property
from pathlib import Path
from typing import List, Dict, Any, Optional, cast
import numpy as np
import numpy.typing as npt
import httpx
from tenacity import retry, retry_if_exception, stop_after_atte... |
d1036e07fe02771439b895af4ff0d41a78e16e40840d2ca6a99e85b6730a0843 | Python | 13,876 | 341 | # Copyright (c) 2022 PaddlePaddle 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
#
# Unle... |
6a2a04b205d57bd62a5c13d8719bee90611b911c757d797d46edff5432e074f6 | Python | 13,894 | 321 | import argparse
import json
import os
import sys
import numpy as np
from pydfc.ml_utils import (
PLSEmbedder,
dFC_feature_extraction,
find_available_subjects,
process_SB_features,
select_num_components_binary_groupcv,
subject_center,
)
sys.path.append(os.path.dirname(os.path.abspath(__file__)... |
02a9312fb730ff647ce258d4081b5f4124899b11af7e79515c760b2c7321cb70 | Python | 13,902 | 372 | from __future__ import annotations
import argparse
import copy
import functools as ft
import itertools as it
import re
from pathlib import Path
from typing import Any, ClassVar
import pytest
from hypothesis import given
from hypothesis import strategies as st
import snakebids.tests.strategies as sb_st
from snakebids... |
3d0d3d32921b7a0cb66863940987ed2787335aad065ec9594b6c1351712e5302 | Python | 13,903 | 440 | """Diffeomorpism implementation."""
import abc
import math
import geomstats.backend as gs
from geomstats.vectorization import get_batch_shape, repeat_out_multiple_ndim
class Diffeo:
r"""Diffeormorphism.
Let :math:`f` be the diffeomorphism
:math:`f: M \rightarrow N` of the manifold
:math:`M` into th... |
9f8f95425bf3db5ffb6df1a5ea2c67d79030135c90a91c468dc7668528082de9 | Python | 13,908 | 521 | """Benchmarking parameters generation file."""
import argparse
from itertools import chain, product
import pandas as pd
parser = argparse.ArgumentParser(
description="Generate parameters for which benchmark is run"
)
parser.add_argument(
"-m",
"--manifold",
type=str,
default="all",
help="Man... |
d72fce86ea17af8a7c8415ff85facc2adbb5085c821741d8eff48ce0de165de3 | Python | 13,910 | 350 | import sklearn
import numpy as np
from scipy.special import expit
from sklearn.metrics import roc_curve, precision_recall_curve
def get_multitask_classification_measures(true, pred, are_logits):
multitask_measures = dict()
per_task_measures = dict()
y_measures_list = list()
y_weight_list = list()
... |
c0b105430b63c91205af7b13adac89151afae063654a1a3291cf99c29d497d69 | Python | 13,920 | 310 | #!/usr/bin/python3
###
# Master controller for the TreeMaze. It communicates with the arduino through serial port.
# Receives data through GPIO inputs and serial.
###
import threading
from MazeHeader_PyCMDv2 import *
PythonControlSet = ['T2','T3a','T3b','T3c','T3d','T3e','T3f','T3g','T3h','T3i','T3j',
... |
b2b3be14902a5506164a0698f2288043be5f2465431d8b85a5d04cdaa917758b | Python | 13,928 | 343 | # -*- coding: utf-8 -*-
import os
import numpy as np
import tensorflow as tf
from tensorflow.keras import layers
import skimage.measure as skm
from scipy.interpolate import griddata
#Build CNN with desired architecture
def BuildCNN(conv_layers,features,win_size,dense_layers,dense_size,dropout,initializer,regu... |
89884789a87808589df0e1d8a60d223afb90367a0bb1094af933288375b2b984 | Python | 13,939 | 343 | # -*- coding: utf-8 -*-
import os
import numpy as np
import tensorflow as tf
from tensorflow.keras import layers
import skimage.measure as skm
from scipy.interpolate import griddata
#Build CNN with desired architecture
def BuildCNN(conv_layers,features,win_size,dense_layers,dense_size,dropout,initializer,regu... |
4bd2da9b842a1fed6e0f0796f072546907546f16ab066530fb61c4eb5f722e6f | Python | 13,948 | 316 | import json
import logging as log
import os
import pickle
import coloredlogs
import hydra
import numpy as np
import pandas as pd
import torch
from common.itemloader import ItemLoader
from omegaconf import OmegaConf
import random
from omegaconf.listconfig import ListConfig
from sklearn.metrics import roc_auc_score, bal... |
54caded6d8c50636444f0ea80bfc55951023d3d0af878e958c9681c885151147 | Python | 13,949 | 304 | import io
import json
import numpy as np
import pandas as pd
from django.contrib.auth.models import User
from django.db import transaction
from rest_framework_simplejwt.tokens import AccessToken
from uniprotparser.betaparser import UniprotParser
from celsus.models import Project, GeneNameMap, UniprotRecord, Compariso... |
0279e2bdc8c74162ee22a11ba3abe9e384e10d810b359f69f77b163c17e5976d | Python | 13,951 | 322 | import random
import Augmentor
import cv2
import glob
import os
import numpy as np
from PIL import Image
from skimage import util
from skimage import io,transform as t,img_as_ubyte
from skimage.filters import threshold_otsu
from skimage.morphology import opening,closing,disk
from skimage.metrics import peak_... |
775f928c3c54e8da1eb18e4cf7b387c37cbf90c7174f79bbb470311a6d8aaa07 | Python | 13,956 | 375 | import importlib.util
import os
import resource
import shutil
import sys
import tempfile
from pathlib import Path
import numpy as np
import pytest
from ase.atoms import Atoms
# ---------------------------------------------------------------------------
# Capability model
#
# Each optional requirement of a test (a GPU... |
c208c824932cd4b28a6a686aa3e6be9cf4be27b17b2f38c295674437813f322c | Python | 13,956 | 400 | """Class for the Sasaki metric.
A class implementing the Sasaki metric: The natural metric on the tangent
bundle TM of a Riemannian manifold M.
Lead authors: E. Nava-Yazdani, F. Ambellan, M. Hanik and C. von Tycowicz.
"""
from joblib import Parallel, delayed
import geomstats.backend as gs
from geomstats.geometry.ba... |
1b4ea76e58c2c0432d6d7437eab82702506ab7cdef1e2f774af2e8d70b7eaafa | Python | 13,983 | 299 | """The spellings the evaluation command line writes onto its structures.
The third door, and the one that had none of this. ``mace_eval_configs``
(``mace/cli/eval_configs.py``) does not return a dict: it writes its results
back onto the ``ase.Atoms`` it was given, into ``info`` for graph-level
quantities and ``arrays`... |
f33a1a2d090a2b153d0be4e37cfff1be0198606eac5137011827b988b82a3685 | Python | 13,986 | 397 | from __future__ import annotations
import math
from typing import Callable, List, Tuple
import numpy as np
import pytest
import torch
from e3nn import o3
from mace import data, modules, tools
from mace.data import Configuration
from mace.modules.lora import inject_lora, merge_lora_weights
from mace.tools import torc... |
d189c1233132c8cff66e4512a9e95228ec8579e3e4534c1eb351bcbcb41a1409 | Python | 13,987 | 333 | import pytest
import pickle
import numpy as np
import matplotlib
from hnn_core import pyramidal
from hnn_core.cell import _ArtificialCell, Cell, Section
from hnn_core.network_builder import load_custom_mechanisms
matplotlib.use("agg")
def test_cell():
"""Test cells object."""
load_custom_mechanisms()
... |
7fa95698467f433b9cbc8ba4e815aab61564f2750a6483f8bf1616ac89b086d7 | Python | 13,990 | 305 | from typing import Any, Callable, List, Tuple, Union, Dict
import captum.attr as ca
import torch
import torch.nn as nn
import torch.nn.functional as F
from captum.attr._utils.common import (
_format_additional_forward_args,
_format_attributions,
_format_input,
)
from captum.attr._utils.gradient import (
... |
1d4717ac082e39b458719b1c5641666d77b62b30cf9efc79b7ed0f2834492811 | Python | 14,003 | 283 | #!/usr/bin/env python3
"""
CLI to process a single molecule.
"""
import copy
import os
import sys
import numpy as np
from jax.config import config as jax_config
from typing import Any, Tuple, Dict
from deeperwin.configuration import Configuration
import haiku as hk
def _setup_environment(raw_config: Dict, config: Conf... |
7be4cb042cfa76eca051fad338a427836c69891ada811949034f6d7c0e85b046 | Python | 14,015 | 310 | import pandas as pd
import numpy as np
import scipy.io as sio
import os
import multiprocessing
import time
import random
from tqdm import tqdm
from scipy import stats
from sklearn.linear_model import Ridge
from sklearn.svm import SVC
from sklearn.metrics import make_scorer
from sklearn.model_selection import GridSearch... |
9ffada173d6cdd675451ce29763a69d0b16a4af5b2a61ecb627be2daeb597b5b | Python | 14,018 | 265 | from typing import Tuple, List
import numpy as np
import jax
import jax.numpy as jnp
import e3nn_jax as e3nn
import haiku as hk
import functools
from deeperwin.utils.utils import tp_out_irreps_with_instructions, multi_vmap
from deeperwin.model.definitions import Edge, Embeddings, InputFeatures, DiffAndDistances
from de... |
7b82cc5cb03c2fc9e0b70c07687adf65484b4c1394d5c1f24ee3da65e6553514 | Python | 14,021 | 313 | import os
import numpy as np
import bisect
import sys
#import matplotlib.pyplot as plt
# import our MS libraries
from pyMSpec.mass_spectrum import mass_spectrum
from pyImagingMSpec.ion_datacube import ion_datacube
class inMemoryIMS():
def __init__(self, filename, min_mz=0., max_mz=np.inf, min_int=0., index_range=... |
4c6bfba471eab95d4ad98f6116dce22c10fdbf138457ede4d28aa9e87c336529 | Python | 14,023 | 204 | import torch
import torch.nn as nn
import torch.nn.functional as F
from .spherenet import SphereNet
from .net_utils import *
from .geometric_computing import *
from .att import MH_ATT
class SphGen(nn.Module):
def __init__(self, cutoff, num_node_types, num_layers,
hidden_channels, int_emb_size, basis_emb_... |
2f5a6f6b9f5c160d45b1fb70d46b767c4277a655c35a50afae39580168d5d525 | Python | 14,033 | 374 | """Public writer for self-contained SanPy Zarr collections."""
from __future__ import annotations
import json
import os
import re
import shutil
import tempfile
import uuid
from datetime import UTC, datetime
from pathlib import Path
from typing import Any, Iterable, Sequence
import numpy as np
import zarr
from .cont... |
f931991cdd7afd849889666cf6bd7339c74a0f9c5f82be8f014c228a3b696802 | Python | 14,035 | 328 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
import torch
from e3nn.o3._irreps import Irreps
from e3nn.util.jit import compile_mode
from nequip.data import AtomicDataDict
from ._graph_mixin import GraphModuleMixin
from .model_modifier_utils imp... |
32a9d1bbbfa312c3dfc686cabc6d5f31f335a9d75e2f0c13c2d71433d65b2ff7 | Python | 14,036 | 348 | import random
from typing import List, Literal, Optional, Tuple
import numpy as np
import scipy.ndimage as nimg
from PIL import Image
def add_norm(Xs: list[np.ndarray], per_layer: bool = True):
"""
Normalize arrays by subracting the mean and dividing by standard deviation. In-place operation.
Arguments:... |
d1f6e58132b54ec86cab64148fdbb0a44dcde99e642701e1269cf0c72ff4615e | Python | 14,041 | 397 | import torch
from torch.autograd import Variable
import torch.nn.functional as F
from torch.utils import data
from torch.utils.data import SequentialSampler
from torch import nn
from tqdm import tqdm
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from time import time
from sklearn.metrics impo... |
ba96264de4a4dc0f31139dc8aaeb96e8d504bf86886e56f1dac16adec1ea0374 | Python | 14,058 | 381 | """Permutation test for the correlation between two variables.
`correlation_permutation_test` asks whether the Pearson, Spearman, or Kendall
correlation between two arrays differs from zero, building the null distribution
by shuffling one array's observations. It assumes observations are independent;
for autocorrelate... |
53027f45593b589426fbd4eb6187c975162ddd1c0b7a5113535cc0a5ca28973a | Python | 14,061 | 308 | # This file is a part of the `nequip` package. Please see LICENSE and README at the root for information on using it.
import torch
from .lightning import NequIPLightningModule
from .ema import EMALightningModule
from nequip.data import AtomicDataDict
from nequip.utils.versions import _TORCH_GE_2_6
from itertools impor... |
613453c56484448ba11ac38046c5c0ade75811247bcb07b542f2372ffc303b94 | Python | 14,075 | 380 | # Copyright (c) 2022 PaddlePaddle 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
#
# Un... |
32fb669f1d6ef212bf068e14c66a08458717adc84b9b82163959b5f310134a3a | Python | 14,081 | 347 | """
Provides utilities related to PyTorch.
The classes and functions
:class:`TorchRayTrafoParallel2DModule`
:class:`TorchRayTrafoParallel2DAdjointModule`
:func:`get_torch_ray_trafo_parallel_2d`
:func:`get_torch_ray_trafo_parallel_2d_adjoint`.
in this module rely on the
`tomosipo <https://github.com/a... |
360b92071da533173ecfd66bede4411cfca25a0ef39069f7466e3ca69595d078 | Python | 14,095 | 275 |
from __future__ import absolute_import
from .layer_utils import *
from .activations import GELU, Snake
from .unet_2d import UNET_left, UNET_right
from .backbone_zoo import backbone_zoo, bach_norm_checker
from tensorflow.keras.layers import Input
from tensorflow.keras.models import Model
def UNET_att_ri... |
7c906ccc2f044d4722cad3eb116e985ac2904ef0cac947298138117ba1a66d0a | Python | 14,128 | 355 | import torch.optim as optim
import torch
import torch.nn as nn
import torch.nn.functional as f
import torchvision.transforms as transforms
import torchvision as tv
import torch.utils.data as data
import os
import matplotlib.pyplot as plt
import random
from torch.utils.data import Dataset, DataLoader
import time
import ... |
aa92ed45b5ea9325a8876a5e65cc29412cbbf0e2f3803c14f9d1a790dea33e76 | Python | 14,128 | 335 | # -*- coding: utf-8 -*-
#
# Класс для работы с файлами TMLDA
# 28/01/2018
import ctypes
from ctypes.wintypes import BOOL, DWORD
import struct
import multiprocessing
import tmlda
import win32api, win32con, win32gui
from threading import Thread
import numpy as np
import csv
import similarwords2
import os
... |
a5eab5ecc2314dc3bc33acf612fb16eb08045070b7ccfe975a844a0e3d05066f | Python | 14,140 | 371 | # -*- coding: utf-8 -*-
#
#
# PyRates software framework for flexible implementation of neural
# network models and simulations. See also:
# https://github.com/pyrates-neuroscience/PyRates
#
# Copyright (C) 2017-2018 the original authors (Richard Gast and
# Daniel Rose), the Max-Planck-Institute for Human Cognitive... |
f065667f508056d0b36f76a8736899470c7cf2cf403b28199a3bbb67377e7b2c | Python | 14,141 | 434 | import numpy as np
# import matplotlib.pyplot as plt
import torch
import h5py
import torch.nn as nn
from torch.utils import data
import itertools
import json
import sys
from os import path
from modules import _ResidueModule
from modules import _ResidueModuleDense
nameScript = sys.argv[0].split('/')[-1]
# we are goi... |
767a099c55ba02476d0daaee09c3eae6b3c03ca4d3db4d5c96e898afdf7f1c44 | Python | 14,158 | 412 | # /// script
# requires-python = ">=3.11"
# dependencies = [
# "marimo",
# "nltools>=0.6.0",
# ]
# ///
# Working with Adjacency — marimo notebook. Source of truth for the docs page; rendered to the docs page by scripts/marimo_to_zensical.py.
import marimo
__generated_with = "0.24.0"
app = marimo.App(width="me... |
c8568a8522238dfcc9bb5449d463c5909861b4be79a7b4a324a58b97e865c2c3 | Python | 14,159 | 365 | """Tests for GatedEquivariantBlock vs e3nn nn.Gate.
Parametrized over irreps configs, dtypes, batch sizes, and layouts.
Compares forward values, backward gradients, second derivatives, and
verifies zero graph breaks under torch.compile for both mul_ir and ir_mul.
"""
import pytest
import torch
import torch.serializat... |
32bc6eba8e8de9a988f28ccb6ac2d14e92b9a1e209f97dfaa2b0457ca134bac9 | Python | 14,161 | 353 | #!/usr/bin/env python3
#
# Sniffles2
# A fast structural variant caller for long-read sequencing data
#
# Created: 29.08.2021
# Author: Moritz Smolka
# Contact: moritz.g.smolka@gmail.com
#
from dataclasses import dataclass
import statistics
import math
from sniffles import sv
from sniffles import leadprov
@dataclas... |
ca2581ca2c491e07bf96f5c93e404a37e764630b8b02f8c93e820962b8fde1d5 | Python | 14,161 | 435 | import numpy as np
# import matplotlib.pyplot as plt
import torch
import h5py
import torch.nn as nn
from torch.utils import data
import itertools
import json
import sys
from os import path
from modules import _ResidueModule
from modules import _ResidueModuleDense
nameScript = sys.argv[0].split('/')[-1]
# we are goi... |
ffc98536643dca9a5c13d93c4e903665d4b6d42f54531266677cc56e7296abe5 | Python | 14,163 | 305 | import eelbrain as eel
import numpy as np
import scipy, pathlib, importlib, mne, time, os
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator, AutoMinorLocator
import scipy.stats
from tqdm import tqdm
from matplotlib.lines import Line2D
def plot_fig_AVG(resdict, corrdict, savepath, sigbars=N... |
c3f1eabc288c618d4e95e7a807ad36b8ef7ae0e41dde58a592321f6ec22ec6dc | Python | 14,191 | 450 | import nrrd
import matplotlib.pyplot as plt
import numpy as np
import os
def visualize_image(
img_path,
img_idx=200,
axis=2,
show_axis=True,
show=True,
output_path=None,
flip=False,
default_spacing=False,
):
"""
Visualize a slice of a 3D imag... |
e5f1107c50175ffc5af4b402bccaee419df61b4aba557ceb8b4cedefed43ece2 | Python | 14,192 | 381 | # -*- coding: utf-8 -*-
from typing import Type, Any, Callable, Union, List, Optional
import torch
import torch.nn as nn
from torch import Tensor
def conv3x3(in_planes: int, out_planes: int, stride: int = 1, groups: int = 1, dilation: int = 1) -> nn.Conv2d:
"""3x3 convolution with padding"""
return nn.Conv2d... |
9330c25c4f126918f80d2407f161dcb7a5cd87590e2e7543b181681c62a4b083 | Python | 14,199 | 402 | """
Serial-MQTT Bridge
author: Tal Eisenberg <eisental@gmail.com>
"""
import time
import paho.mqtt.client as mqtt
import logging
import queue
from serial.tools import list_ports
from serial import Serial, SerialException
import threading
import json
def serial_port_by_id(serial_number):
"""
Return a port inf... |
f99bc464938a910051569d1b2531c52811ac5971088dda98d177ff88d85dd429 | Python | 14,205 | 320 | import torch
from torch import nn
from torch.nn import Linear, Embedding
from torch_geometric.nn.inits import glorot_orthogonal
from torch_geometric.nn import radius_graph
from torch_scatter import scatter
from math import sqrt
from ...utils import xyz_to_dat
from .features import dist_emb, angle_emb, torsion_emb
dev... |
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