sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
c0a2ebc14617a69f13dee7a2c32b4179952e8e8c20c2d2ca3d3f29c862c6bdaa | Python | 5,004 | 124 | import re
import nibabel as nib
from lib.qc import QCResult
from lib.qc_report import QCReport, fig_to_png, legend
from lib.qc_srcsink import DEFAULT_THRESHOLDS, plot_loop, plot_surfaces
from lib.surface import TERMINAL_NAMES
from lib.utils import setup_logger
log_file = snakemake.log[0] if snakemake.log else None
lo... |
010a6282ac6c48c523617d46b3ebd0581cb5de9910d3546129b6a46c49af76b5 | Python | 5,006 | 132 | # Copyright (c) 2017-present, Facebook, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed... |
53b39d41dc9d09226c4ba5995af6fcba226a6456ca93fbe3470fe533a290700a | Python | 5,007 | 151 | """An example of training a REINFORCE agent against OpenAI Gym envs.
This script is an example of training a REINFORCE agent against OpenAI Gym
envs. Both discrete and continuous action spaces are supported.
To solve CartPole-v0, run:
python train_reinforce_gym.py
To solve InvertedPendulum-v1, run:
python tr... |
6b330efe53f5f5980f0743ecfdf2db7a78cd12d20add9b179c536de87540a8e8 | Python | 5,007 | 109 |
import numpy
import os, glob
import pickle
import h5py
PATH = "../../data"
if __name__ == "__main__":
# # Resolution, Bleach, Squirrel
# directories = [
# "20210618-145645_optim_1params_3objectives_degree4",
# "20210619-071126_optim_1params_3objectives_degree4",
# "20210621-095150_op... |
f59ef41e54a5b7f27e9033f4b66e929bc41686a0b941f745d72aa9e33c7828e7 | Python | 5,007 | 102 | from typing import Dict
import numpy as np
from basis_functions.time_basis_functions import make_cosine_bump_family, trim_basis_by_cond_index, basis_shift_forward, \
backshift_n_samples, trim_basis_reduce_condition_number
from lib.dataset_specific_hyperparams.glm_hyperparameters import GLMModelHyperparameters
d... |
b09e4ef61196c99ce31c5c797c5e008a7714926d0fa0dbba718dfa7362ab0583 | Python | 5,008 | 112 | from abc import ABC, abstractmethod
import networkx as nx
import numpy as np
import matplotlib.pyplot as plt
from tqdm import tqdm
import os
import os.path as osp
import multiprocessing
class PGDataset(ABC):
"""Generic class for loading datasets. It has all of the methods required to write the dataset in order ... |
0b92695adf1f3c56b0e01f719d5d63c10814668f431f8e3a178ef85bf4958ab3 | Python | 5,010 | 147 | # Copyright 2023 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
322b46149b0c15a32ea25426698bc6d0c008263deab88fd613f219fe322786d7 | Python | 5,010 | 173 | from exputils.misc.attrdict import AttrDict, combine_dicts
import exputils as eu
import os
import copy
# TODO: Feature - tensorbord output
# TODO: Featrue - allow to log sub values, for example: agent.epsilon
class Logger:
"""
Configuration:
numpy_log_mode: String that defines how numpy data ... |
4fc09534bde8e7f80eda6e7cc681b935a8528a85eb52c41277cb55fa8a3aa107 | Python | 5,010 | 134 | import os
import shutil
import argparse
import subprocess
from argparse import RawTextHelpFormatter
def get_parser():
parser = argparse.ArgumentParser(
description='Convert BIDS datastructure to nnU-Netv2 datastructure.',
formatter_class=RawTextHelpFormatter,
prog=os.path.basename(__file__... |
6d1428e8a8563b3fa54c6245b23ef88347ee712c66997fb9f6cbc1dbf581f6bb | Python | 5,010 | 155 | import cv2
import numpy as np
import os
def show_cam_on_image(img: np.ndarray,
mask: np.ndarray,
use_rgb: bool = False,
colormap: int = cv2.COLORMAP_JET) -> np.ndarray:
""" This function overlays the cam mask on the image as an heatmap.
By defau... |
0a7c801441135b2bc71879eaf10258b140d0de2388c2601907c7700444a96dd4 | Python | 5,012 | 128 | # -*- coding: utf-8 -*-
"""
Creating probabilitic activation maps from Neurosynth data
Created on Wed Aug 2 13:41:55 2023
@author: JoshB
- Downloads neurosynth data (version 7 - can be modified) and converts into NiMARE dataset using individual terms (can be modified to topics)
- Conducts coordinate-based ... |
18cb3910bcd91c3fa2e904ce0f1a76054389700808e4444000b4f5d4510fa980 | Python | 5,012 | 104 | import argparse
import projectmetis.proto.metis_pb2 as metis_pb2
from projectmetis.python.learner.learner import Learner
from projectmetis.python.learner.learner_servicer import LearnerServicer
from projectmetis.python.utils.proto_messages_factory import MetisProtoMessages
from projectmetis.python.logging.metis_logg... |
dc7a3020a7a094bb6c8af3a58ee4f96cc04ad827e456bb79c07c3cef9294cd66 | Python | 5,013 | 161 | import numpy as np
import cv2 as cv
import torch
from torch import nn
import skimage
from scipy.ndimage import uniform_filter
def impute_missing(x, mask, radius=3, method='ns'):
method_dict = {
'telea': cv.INPAINT_TELEA,
'ns': cv.INPAINT_NS}
method = method_dict[method]
x = x.cop... |
a0a208c0641dec10e7f44a3b0935f8122f1bafa766bcceb2e588bbb66f86f117 | Python | 5,016 | 153 | #!/usr/bin/env python3
"""
nii_deface.py — mask+crop a 3D NIfTI with an MNI-space face mask
Usage:
python nii_deface.py /path/to/img.nii.gz
Requirements:
- antspyx, nibabel, numpy
- The files "MNI152_T1_2mm.nii.gz" and "mniMask.nii.gz" must be in the same
folder as this script (used as moving image and ma... |
e2176ac3050bc80339b4dd9347e9cf4d077b232acdb8934bc8d3331acb9aeccb | Python | 5,016 | 158 | import torch
import numpy as np
import scanpy as sc
from scipy import sparse
from torch.utils.data import Dataset, DataLoader
class MetaQDataset(Dataset):
def __init__(self, x_list, sf_list, raw_list):
super().__init__()
self.x_list = x_list
self.sf_list = sf_list
self.raw_list = r... |
55a9a71ee89d9bde632bbe7b3a2bb192e0137d99eb83ae320b37217871b30ebb | Python | 5,018 | 140 |
import torch
from datetime import datetime
from torch.optim import AdamW
from transformers import get_linear_schedule_with_warmup
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler
from agent.classifiers.evaluation.evaluation_mgmt import get_evaluation_measures, get_f1_measure
from agent.class... |
525cc02e2607bd5ca7672899f7f2c9484fc720762a2c487cd1b90957addd9bb5 | Python | 5,019 | 174 | import os
import tempfile
import pytest
from pfrl.replay_buffers import PersistentEpisodicReplayBuffer
@pytest.mark.parametrize("capacity", [None, 100])
class TestEpisodicReplayBuffer(object):
def setup_method(self, method):
self.tempdir = tempfile.TemporaryDirectory()
def teardown_method(self, met... |
9323f7cbe6482a838418e231e48e5043b08b618e547687cfa542fadb82926e3a | Python | 5,020 | 128 | ####################################################################################################
# Copyright (c) 2020 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
e95a1d24acd12d80ba8c937733a21335e95d0f6bdb4047dae1efa330dfbfc676 | Python | 5,020 | 157 | from typing import List
from dataclasses import dataclass, asdict
import itertools
import logging
import pandas as pd
@dataclass
class DataColumns:
protein_col: str = "pdb_code"
chain_col: str = "chain_id"
pos_col: str = "position"
wtAA_col: str = "wtAA"
mutAA_col: str = "mutAA"
from_col: str... |
cbe44c848881c9e5bf0717825241aab45f25b70fe098357e52ff263b954dea30 | Python | 5,021 | 91 | # coding: utf-8
"""
# # SCRIPT: IDENTIFY THE FMRI-BASED REACTIVATION ONSETS ONSETS IN REST
# # PROJECT: FMRIREPLAY
# # WRITTEN BY QI HUANG 2022
# # CONTACT: STATE KEY LABORATORY OF COGNITIVE NEUROSCIENCE AND LEARNING, BEIJING NORMAL UNIVERSITY
"""
# In[1]: import relevant packages
import os
import warnings
... |
2d8f926bcc69062b3171edef8ecfc8915364b157ace5000eba7cbde5a9ec1a04 | Python | 5,022 | 152 | #!/usr/bin/env python
# import
from __future__ import print_function
## batteries
import os
import sys
import gzip
import bz2
import argparse
import logging
import csv
import urllib.request
import codecs
from collections import OrderedDict
## package
from bin import __version__
import gtdb2td
# argparse
desc = 'Conver... |
4111646abd69fe2e2ea12d3b5f1cd75f109aa69578f5b3bf1f7615c6adf1cf99 | Python | 5,022 | 124 | from sklearn.datasets import make_blobs
from sklearn.model_selection import train_test_split
from reval.best_nclust_cv import FindBestClustCV
from sklearn.neighbors import KNeighborsClassifier
from sklearn.cluster import AgglomerativeClustering
from sklearn.metrics import zero_one_loss, adjusted_mutual_info_score
from ... |
86fc97890c8192177f306c69a9bccc6a757ddb91f3857460b0c3eb1047a953da | Python | 5,022 | 158 | import pandas as pd
import pytest
from data_profiling import ProfileReport
# Enhanced fixture with more diverse data types
@pytest.fixture
def sample_categorical_data():
return pd.DataFrame(
{
"dummy_cat": [
"Amadeou_plus",
"Amadeou_plus",
"Beta... |
d760eb6bba458cdd5c2120c35f5be4792704869985df44ed1134f5360ed33154 | Python | 5,022 | 64 | import json,numpy as np
import matplotlib; matplotlib.use("Agg"); import matplotlib.pyplot as plt
plt.rcParams.update({"font.family":"DejaVu Serif","font.size":8.5})
def cm(ax,C,labs,title):
C=np.array(C); ax.imshow(C/C.sum(1,keepdims=True),cmap="Blues",vmin=0,vmax=1)
for i in range(C.shape[0]):
for j i... |
99493e1aa0c049d03489b0de55dc7cbc7645385241114e47a5fd8eae9f096cd3 | Python | 5,023 | 175 | from pathlib import Path
from typing import Literal
import math
import pickle
import json
import matplotlib.pyplot as plt
import argparse
import logging
import pandas as pd
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.utils import ModelEma
from timm.loss import Label... |
9c53b31fd2fe82414657897b0bf201fbf59bf9d506f96335e1b72a26cec7dd91 | Python | 5,025 | 180 | from __future__ import annotations
from abc import ABCMeta, abstractmethod
from pathlib import Path
from typing import TYPE_CHECKING
#from cytoolz import memoize
from .ctdb import CisTargetDatabase
from .datatypes import RegionOrGeneIDs
if TYPE_CHECKING:
import pandas as pd
from .genesig import GeneSignatu... |
87d7dbec01bb5926086a51eb251203891e48a34e30decfa2b7ba982cd6cfde70 | Python | 5,027 | 135 | r"""Cross-reference metabolite names ↔ HMDB / KEGG / ChEBI / LipidMaps IDs.
The lookup is **online-first**, cached forever:
1. :func:`map_ids` calls :func:`omicverse.metabol.fetch_hmdb_from_name`
per name, which hits the PubChem REST API (synonym-aware) and pulls
HMDB / KEGG / ChEBI IDs from the cross-reference... |
4e701f3186d284ef920afdeecc0c514adad4461e33247ae4ece4c2a46865f376 | Python | 5,030 | 176 | import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
def plot_assignment_entropy(
ad,
title="Entropy of Metacell Assignment",
save_as=None,
show=True,
bins=None,
figsize=(5, 5),
):
"""Plot the distribution of assignment entropy over all cells.
Each cell is assigne... |
93dde08bddc3c13888f0b941f472e07238e328a53987796c663f9055d54f1e8b | Python | 5,030 | 134 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Python version: 3.10.9
pandas version: 1.5.0
numpy version: 1.23.3
seaborn version: 0.11.0
matplotlib version: 3.6.3
pingouin version: 0.5.3
ptitprince version: 0.2.6
scipy version: 1.11.4
"""
#%% Import Modules
import pandas as pd
import glob
import seaborn as sns
i... |
ace18a0ebffa424e0aeb6eec514f2b95afe25444aaa532b12ada3f235f12bc1e | Python | 5,030 | 152 | """Correlations between variables."""
from typing import Optional
import pandas as pd
import pyspark
from packaging import version
from pyspark.ml.feature import VectorAssembler
from pyspark.ml.stat import Correlation
from pyspark.sql import DataFrame
from pyspark.sql.functions import PandasUDFType, lit, pandas_udf
fr... |
cfde2c1cd23901e4bb3bd99c2122fcc3ea134699bba76544f8fb3ad9d9e2e593 | Python | 5,030 | 131 | import torch
from torch import nn
from ..utils import create_norm
import math
def select_pe_encoder(pe):
if pe in ['sin', 'sinu', 'sinusoidal']:
return Sinusoidal2dPE
elif pe in ['learnable', 'bin']:
return Learnable2dPE
elif pe in ['naive', 'mlp']:
return NaivePE
elif pe in ['l... |
ea789ac7f7ed58f1aebe36dc9abac11bc49a8af538883b28e9a2f7c9ee0c2a93 | Python | 5,030 | 136 | r"""RNA secondary structure & thermodynamics (ViennaRNA).
RNA folding controls translation (RBS accessibility), riboswitches, sRNA
regulation and sgRNA activity. Thin, well-typed wrappers over ViennaRNA:
* :func:`rna_fold` — minimum-free-energy structure (dot-bracket) + ΔG.
* :func:`rna_accessibility` — opening ener... |
2349153829e8d0839b53a533e411ababd94a80ab8ff9fcbff9217320f3925754 | Python | 5,032 | 155 | import os
import sys
import cv2
import torch
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.image import imread
from gimpformats.gimpXcfDocument import GimpDocument
#from datasets import SkullUSDataset
from utils import load_xcf, makeDict
from metrics import hull, concave_hull, convex_hull
#from d... |
67a3c4dcc8490b74b43edf831da37edbb39a49427a69c8550b456adc94237d9f | Python | 5,035 | 151 | import tensorflow as tf
from tensorflow.keras import backend as K
import os, sys
import h5py
import matplotlib.pyplot as plt
from utils import *
import gc
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import matplotlib.pyplot as plt; plt.rcdefaults()
from tqdm import tqdm
import warnin... |
80f3645c63e240b31d79bb01ca219ffbf6464d5ded405724ec826cd1a4fca324 | Python | 5,035 | 106 | import os
import click
import torch
import itertools
import numpy as np
import pandas as pd
from Bio import SeqIO
from scripts.model import SPIRED_Fitness_Union
from scripts.utils_train_valid import getDataTest
amino_acid_list = list("ARNDCQEGHILKMFPSTWYV")
amino_acid_dict = {}
for index, value in enumerat... |
9b7d7b60601cddfed0b6d8614dfe267814fcbd6d34eb8d83a1ffd17d3ce07f18 | Python | 5,035 | 161 | import sys
from itertools import groupby
import pandas as pd
import numpy as np
window_size = 15
max_seq_len = 100
factorDict ={
"A":[-0.59,-1.30,-0.73,1.57,-0.15],
"C":[-1.34,0.47,-0.86,-1.02,-0.26],
"D":[1.05,0.30,-3.66,-0.26,-3.24],
"E":[1.36,-1.45,1.48,0.11,-0.84],
"F":[-1.01,-0.59,1.89,-0.40,0.41],
"G":[-0.38,1... |
bc3d547b98beb054c81689aabc0a9476582c2f8cef56ea33a158e04f4716602d | Python | 5,035 | 148 | #
# CEBRA: Consistent EmBeddings of high-dimensional Recordings using Auxiliary variables
# © Mackenzie W. Mathis & Steffen Schneider (v0.4.0+)
# Source code:
# https://github.com/AdaptiveMotorControlLab/CEBRA
#
# Please see LICENSE.md for the full license document:
# https://github.com/AdaptiveMotorControlLab/CEBRA/bl... |
18419c576b4a85089c411450719de35b54853f7745f6c014bca2448a8c4e0125 | Python | 5,036 | 151 | import abc
import logging
import os
from typing import List, Literal, Union
import mdtraj
from mdtraj.core.trajectory import Trajectory as mdtraj_trajectory
from mdtraj.reporters import HDF5Reporter
from openmm import Integrator, LangevinIntegrator, OpenMMException
from openmm import unit
from openmm.app import (
... |
3d739297434c03fd17fa328fe5dc82bbf68ed29f218691767e89187840bfbbed | Python | 5,037 | 132 | import torch
import torch.distributed as dist
import torch.multiprocessing as mp
import argparse
import os, glob
from sklearn.model_selection import train_test_split
from torch_geometric.loader import DataLoader
import socket
from src import AseReadDatasetAttr
from src import TrainerFineTuneClassification
from equifor... |
4f61cf2f7f8c6a695395d8b4ebc72fc27d6382062a5113e4325f755f435b446f | Python | 5,037 | 134 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 19 12:36:50 2022
@author: sam
"""
import pickle
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams['svg.fonttype']='none'
def evaluate_fit(model,synapse_mask_fun,syn_fractions,
n_genes,n_neuron,folder):
#check if... |
e6bb466071138d9bb4b08c5d7a1aa40dba1559fbb7462a01b76eca71d1fe080f | Python | 5,042 | 183 | # built-in dependencies
from typing import Any, List, Union
# project dependencies
from deepface.commons import package_utils, weight_utils
from deepface.models.FacialRecognition import FacialRecognition
from deepface.commons.logger import Logger
logger = Logger()
# pylint: disable=unsubscriptable-object
# -------... |
0e0b71278ae4fe8f0d5e209cb40be10a0f56d602eec725ebae29fa2a93d77344 | Python | 5,043 | 142 | import matplotlib.pyplot as plt
import math
label = "Phospho (STY)"
class Precursor:
def __init__(self, precursor: str, qvalue: float, is_human: bool, is_phospho: bool):
self.precursor = precursor
self.qvalue = qvalue
self.is_human = is_human
self.is_phospho = is_phosph... |
473f18ecea4b21a717458c3b68ab592e18343579fcd192df2d9b856c87a3ec82 | Python | 5,044 | 177 | # import torch
# import torch.nn as nn
# from pathlib import Path
# from sinabs.activation import ActivationFunction, MembraneSubtract
# MODELS_FOLDER = Path(__file__).resolve().parent / "models"
# def build_model():
# from sinabs.from_torch import from_model
# layers = [
# nn.Conv2d(2, 8, kernel_si... |
118d6ebce9e7afb1b52099d7677b9f2bb54633b3d3cc1145223ea525212fa67e | Python | 5,048 | 198 | #!/usr/bin/env python3
# Copyright 2004-present Facebook. All Rights Reserved.
import json
import os
import torch
model_params_subdir = "ModelParameters"
optimizer_params_subdir = "OptimizerParameters"
latent_codes_subdir = "LatentCodes"
logs_filename = "Logs.pth"
reconstructions_subdir = "Reconstructions"
reconstruc... |
dbd09e8f9ce1d39275e4a3af0f06749c1625544ada63441041925e4c7158a935 | Python | 5,048 | 142 | """Various utility functions."""
import numpy as np
import scipy.sparse as sp
import torch
from typing import Union
def l2_reg_loss(model, scale=1e-5):
"""Get L2 loss for model weights."""
loss = 0.0
for w in model.get_weights():
loss += w.pow(2.).sum()
return loss * scale
def to_sparse_ten... |
67bb7b4737e44f936c757b277e2e2a485c0f7f0ccf1c9b5c016aaad2cda92f79 | Python | 5,049 | 167 | import subprocess
import samtools
import filehandle
import logging
log = logging.getLogger(__name__)
def samtobam( sam, outbam ):
'''
Use samtools to convert a sam file to a bam file
outbam will be overwritten if it already exists
@sam - file path or file object(even pipe) of sam file inp... |
9445ef4befd609c5698ded788686a3246d99e23956b3452c203dc8a964e73b2b | Python | 5,049 | 109 | # Copyright 2023 The HuggingFace Team. 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 applicabl... |
70d1d2b47faf248e24af43283053d58e68ae8a38161433b0c4db8095703c95a6 | Python | 5,050 | 131 | """
The code for the research presented in the paper titled "Enabling inverse design of plasmon-based nonlinear square resonators with deep neural networks."
This code corresponds to the article's forward Deep Neural Network (DNN) section.
Please cite the paper in any publication using this code.
"""
import ma... |
5ffe64334aee8ecc56eefecb190af651ae425ce39a2b035e10e88d6a78f64620 | Python | 5,052 | 113 | import os
import torch
import anndata as ad
from ..model import OmicsFormer
from abc import ABC, abstractmethod
from typing import List, Union
from .experimental import symbol_to_ensembl
import json
import warnings
import scanpy as sc
def load_pretrain(
pretrain_prefix: str,
overwrite_config: dict = No... |
dc6d96f9e04c381acfe381476f3afb291cfa466c97c13ea3c19e3552517e1924 | Python | 5,058 | 140 | import pandas as pd
import numpy as np
import re
def moca(df):
"""
computes domain scores for moca.
run this before applying uds conversion.
"""
# naming
df['MOCANAMI'] = df[['LION', 'RHINO', 'CAMEL']].sum(axis = 1)
# memory registration
df['MOCAREGI'] = df[['IMMT1W1', 'IMMT1W2',
... |
073cd78d33f931bc31047ea7ec2addac22fb1d2f39502c12bb0788f950c027a1 | Python | 5,059 | 149 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
31aabb6a38fc960e0cdf05a3bf4256de86c5287a9cebcae95d884af789b9c481 | Python | 5,060 | 172 | #
# CEBRA: Consistent EmBeddings of high-dimensional Recordings using Auxiliary variables
# © Mackenzie W. Mathis & Steffen Schneider (v0.4.0+)
# Source code:
# https://github.com/AdaptiveMotorControlLab/CEBRA
#
# Please see LICENSE.md for the full license document:
# https://github.com/AdaptiveMotorControlLab/CEBRA/bl... |
8053dc6f63ab2f643be34d6df3ae07563123d77f644d4fecc68364033b08b3ef | Python | 5,062 | 130 | from abc import ABCMeta, abstractmethod
from typing import List, Tuple, Union
import torch
import torch.nn as nn
from mmengine.model import BaseModule
from mmengine.utils import is_list_of
from torch import Tensor
from lqit.common.structures import SampleList
from lqit.registry import MODELS
from lqit.utils import Op... |
a66288e0d1667012c9833bd351adc900926660e78212a97991b9649184b8cf58 | Python | 5,064 | 132 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# ======================================================================
# DEFINE FUNCTION: FUNCTION TO GET THE SUBJECT-SPECIFIC INFORMATION
# ======================================================================
def get_subject_info(events, confounds):
"""
FUNC... |
c9d2284b0ff89b82bb8bea8553772cdfc0687669faf45f567a2a930c1af4a644 | Python | 5,069 | 188 | """
implementing "two networks with merging outputs" in https://github.com/synsense/sinabs/issues/181
"""
import torch
import torch.nn as nn
from sinabs.activation.surrogate_gradient_fn import PeriodicExponential
from sinabs.layers import IAFSqueeze, Merge, SumPool2d
class SNN(nn.Module):
def __init__(self, bat... |
482455009549d6e862561cdbfc15164e1a3e1bcbd5a8d9fb1f7aceb1c8a41941 | Python | 5,070 | 136 | #------------------------------------------------------------------------------
# Libraries
#------------------------------------------------------------------------------
import torch
import torch.nn as nn
import torchsummary
import os, warnings, sys
from .flops_counter import add_flops_counting_methods, flops_to_s... |
9cf6f7926a789cea04917ed0e37c03cda3367adb9fa33bd6afdf8b6dc16ceb5a | Python | 5,072 | 143 | # %% this script creates formatted data for figures.
import pickle
from importlib import reload
from matplotlib.lines import Line2D
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.preprocessing import StandardScaler
import umap
import create_new_target_data as cnd
import matplotlib
i... |
84b5e631984607e981cb53be71009aad28e001aa4eb9e9a98191d6bc7b9393c6 | Python | 5,073 | 173 | #!/usr/bin/env python3
# Copyright 2004-present Facebook. All Rights Reserved.
import glob
import logging
import numpy as np
import os
import random
import torch
import torch.utils.data
import deep_sdf.workspace as ws
def get_instance_filenames(data_source, split):
npzfiles = []
for dataset in split:
... |
41c090b5d30ad0c43aca6705711e47ea9c1791b95ad7971e3d6daf08dbce3906 | Python | 5,075 | 153 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""Data classes for the AIHW Composer API."""
from dataclasses import dataclass, field
from datetime import datetime
from enum import Enum
from typing import An... |
8518bbcb32a6e48369832d54deaa2db36a1384aebd9b62e3928e50a5d85c5cc8 | Python | 5,076 | 130 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
import torch
from fairchem.core.datasets.atomic_data import AtomicData, atomicdata_list_to_batch
cla... |
8d886c376f7c1612d11743a75768681fbe58b9d08227e3eeb6be996ec0bce690 | Python | 5,077 | 142 | import json
import numpy as np
import pandas as pd
from sklearn.cluster import KMeans
from pathlib import Path
def get_window_boundary(df, make_plots: bool = False, figures_dir: Path = Path('figures')) -> np.ndarray:
""" Get time boundaries for each response type.
The dataframe `df` contains the two largest ... |
ece5d505e1b3bad3919075a6f75f5928935dcd843bd99df72e68a52515939b04 | Python | 5,077 | 148 | from typing import Callable, List, Optional, Sequence, Tuple, Union
import torch
__all__ = ["box_to_seg", "seg_to_box", "instance_to_semantic", "pop_keys", "filter_keys"]
def box_to_seg(
boxes: Sequence[Sequence[int]],
shape: Optional[Sequence[int]] = None,
dtype: Optional[Union[torch.dtype, str]] = Non... |
31b82ccf190dc4d2af0b491933817540508c0baa7b6e238390cd72d28968d512 | Python | 5,078 | 128 | ########################################################
######### Philipp R. Steen #########
######### Jungmann Lab #########
######### Max Planck Institute of Biochemistry #########
######### Ludwig Maximilian University #########
######### 2024 ... |
85491cb4fbe0b09b2696932cbb685bd5c17647feee1fb59aa06675bea92284cc | Python | 5,078 | 145 | #Imports relevant modules.
import os
import numpy as np
import csv
#Defines the pipline ID. This will need to be updated.
pipeline = '4'
#Defines the filepath containing all output files.
data_folder = '/<directory root>/Sustainability_Output' #Full path removed for purpose of public sharing.
#Defines the path of ea... |
9b5d52f08b876608e947173ca74419160b27647ae7eceac7dbb1ba95690d68bd | Python | 5,080 | 159 | import matplotlib as mpl
mpl.use('Agg')
import matplotlib.colors as mcolors
import matplotlib.cm as cm
from matplotlib.colors import ListedColormap
import matplotlib.pyplot as plt
plt.rcParams['font.family'] = 'serif'
plt.rcParams['font.serif'] = ['Times New Roman'] + plt.rcParams['font.serif']
plt.rcParams.update({'fo... |
43f1e90fe68a0278d5f8178c7af571ff9ea15229383f3dc5d02f039cea680fc9 | Python | 5,081 | 188 | # flake8: noqa
# __class_api_checkpointing_start__
import os
import torch
from torch import nn
from ray import tune
class MyTrainableClass(tune.Trainable):
def setup(self, config):
self.model = nn.Sequential(
nn.Linear(config.get("input_size", 32), 32), nn.ReLU(), nn.Linear(32, 10)
)... |
59d96a5c23c41f26d7c8146caafe3f80243087fed40a4f26e79013e61d9f4fa4 | Python | 5,081 | 191 | import os
import torch
from tqdm import tqdm
import numpy as np
import pdb
import pickle
import matplotlib.pyplot as plt
from latent_time_stepping.datasets.AE_dataset import AEDataset
from latent_time_stepping.oracle import ObjectStorageClientWrapper
from latent_time_stepping.preprocessor import Preprocessor
from lat... |
7c0a22ab25914f294cc603e1054258fe9e26c73db75d11dfc5881f4d755b1d0f | Python | 5,081 | 166 | # Copyright (c) 2017-present, Facebook, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed... |
916bc622e452958e772c5ab4048a62ed799fe0d8221fdb387367046a5bbfc510 | Python | 5,081 | 124 | import argparse
import scipy.io as scio
import os
import time
import datetime
from skimage import io
from DWonder.MN.utils import list2contours, Joint_Mask_List_Simple_Merge_Mask, Joint_Mask_List_Mul, Joint_Mask_List_Simple
from DWonder.MN.utils import listAddcontours_Laplacian_pytorch, list2contours, listAddcontours_... |
52ba14c045a018fc5a9c452c6edb1d386247c1c465395fbb704d3673a65641d6 | Python | 5,083 | 125 | import torch
import torch.nn as nn
import copy
from .so3 import SO3_Embedding
from .radial_function import RadialFunction
class EdgeDegreeEmbedding(torch.nn.Module):
"""
Args:
sphere_channels (int): Number of spherical channels
lmax_list (list:int): List of ... |
61df246b5b3169a059713d96f259f62bc73508653b7a88c2181d3cdb1cbed1d0 | Python | 5,083 | 106 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import pickle
import pandas as pd
import numpy as np
import pcntoolkit as ptk
from pcntoolkit.dataio.fileio import load as ptkload
from pcntoolkit.dataio.fileio import save as ptksave
from pcntoolkit.normative import predict, evaluate
from pcntoolkit.util.utils ... |
a040bc11c37f876c9792734126397c4790621297a7c8fe483922175f67800d6a | Python | 5,083 | 160 | # stdlib dependencies
from typing import Any, List, Union
# 3rd party dependencies
import numpy as np
from numpy.typing import NDArray
import cv2
import torch
from torch import nn, Tensor
# project dependencies
from deepface.commons import weight_utils
from deepface.models.demography.DemographyUtils import EMOTION_LA... |
cff82e0612859f3ef54691bad0193e8c4b6c20402f76127546e5c8644586cd92 | Python | 5,090 | 156 | """Convert a V3 model to V4. See checkpoints/README.md for usage."""
from tqdm.auto import tqdm
import hydra
import torch
import numpy as np
from pathlib import Path
import pytorch_lightning as pl
import matplotlib.pyplot as plt
from torch.nn.modules import module
import torch.nn.functional as F
from torch.distributio... |
50b6ed72ab2a4c05c2b47a69dd947184c44e08266e8a5e4912d32490b2c4adcb | Python | 5,092 | 138 | #!/usr/bin/env python
"""
Compare the QC metrics of two HippUnfold runs (e.g. before and after a change
to the workflow) as a self-contained HTML report.
python hippunfold/workflow/scripts/qc_compare_runs.py BEFORE_DIR AFTER_DIR \
--qc surface --labels main new -o comparison.html
Each *_desc-<qc>_qcmetric... |
38968feb45a1a603471498db6b99f4efa0d90424e9ee9445b6ba26144ed83e3a | Python | 5,094 | 140 | import tensorflow as tf
from utils.nn import linearND, linear
from mol_graph import atom_fdim as adim, bond_fdim as bdim, max_nb, smiles2graph
from models import *
import math, sys, random
from optparse import OptionParser
import threading
parser = OptionParser()
parser.add_option("-t", "--train", dest="train_path")
p... |
da73c0f2ec8716a4825234248de8d20f478ed659a1ea00dfdff91bbe3de47655 | Python | 5,094 | 182 | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch_scatter import scatter
from .utils import pyg_softmax
class MultiHeadAttention2Layer(nn.Module):
def __init__(self, gamma, in_dim, out_dim, num_heads, use_bias):
super().__init__()
self.out_dim = ou... |
206ff1f5395e7b82cb76087173e6d5e090d84203fc52258ffce611fb690cb019 | Python | 5,096 | 152 | # Copyright (C) 2022 Intel Corporation
# Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from enum import StrEnum
from django.conf import settings
from rest_framework.exceptions import ValidationError
from cvat.apps.engine.models import Project
from cvat.apps.engine.permissions import ProjectPermi... |
58d888d5f342e5c735cd04f9995fbcbfde0bae88d3a0b2b8ad8fb522f7a35367 | Python | 5,097 | 175 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
Creates LMDB files with extracted graph features from provided *.extxyz files
for the S2EF task.
"""
from __future__ import annotations
impor... |
b35cf16f2c5c540173ddae3b9b568e1c9548a83f3430e35cbf1c83fb31a9b375 | Python | 5,098 | 169 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
ce3bf460f86e3b091006389542039125f0308be0f4790b2c3942eca4ef9e8d26 | Python | 5,098 | 112 | # -*- coding: utf-8 -*-
"""Rolling shutter diffuserCam forward model with neural-space time model.
This module contains the forward models for rolling shutter diffuserCam and rolling shutter diffuserCam with space-time
modeling. The loss functions used for the rolling shutter diffuserCam reconstruction are also provid... |
3a5fdf3fb5e12345c4d8307ac49ffb5d7ce125d1c35171e7b242a17352c03be9 | Python | 5,100 | 139 | import copy
import random
import unittest
import torch
from rising.transforms import AbstractTransform
from rising.transforms.compose import Compose, DropoutCompose, OneOf, _TransformWrapper
from rising.transforms.spatial import Mirror
class TestCompose(unittest.TestCase):
def setUp(self) -> None:
self.... |
52d4ffb91d2775bf89069365803a993806d0d8b56fa1dd3605db1f29c1f2a4c4 | Python | 5,101 | 131 | import numpy as np
import struct
from spinnaker2.neuron_models.application import BaseApplication
from spinnaker2.configuration import PEConfig
from spinnaker2.neuron_models.common import (add_log_memory_region,
collect_routing_targets, format_routing_targets)
from spinnaker2.coordinates import ByteAddr, align... |
bcd208a1763e126263946fcbffbd6479260c18b60e9b96d2cb5ce27d44077460 | Python | 5,101 | 156 | #------------------------------------------------------------------------------
# Libraries
#------------------------------------------------------------------------------
import torch
import torch.nn as nn
import torch.nn.functional as F
from collections import OrderedDict
from .base_model import BaseModel
from .Res... |
1d5c6cb45b1c1814f2fc88e5b835b3ae11d9afc310ba749c83e93a724db737f2 | Python | 5,102 | 147 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
Add `extra_repr` into DropPath implemented by timm
for displaying more info.
"""
from __future__ import annotations
import torch
import torch... |
7f5f6bce5a04cf6608c2063e0b5802d82124d46fd74811368bd501b57ccc62de | Python | 5,103 | 162 | """load annotations from the SeizeIT dataset https://doi.org/10.48804/P5Q0OJ to a Annotations object."""
import math
import os
import re
from pathlib import Path
import pandas as pd
import pyedflib
from ..annotations import Annotation, Annotations, EventType, SeizureType
from ..eeg import Eeg
def _loadSeizures(
... |
3f2f33daedc05ab18b8c9027c01f62d4b05d672f9247d5f2a2f278bd595d0d14 | Python | 5,107 | 122 | # Copyright (c) DP Technology.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import absolute_import, division, print_function
import numpy as np
import joblib
import os
from .data import DataHub
from .models import NNModel
... |
34fb12fff811685d736a61c4e555820aff4a02e77d27b49f10b85d0deb0b2f50 | Python | 5,109 | 119 | # coding: utf-8
import os
import sys
import unittest
from queue import Queue
from unittest.mock import patch
import pytest # noqa
from ray._private.test_utils import load_test_config
from ray.autoscaler.tags import TAG_RAY_NODE_KIND
from ray.autoscaler.v2.instance_manager.config import AutoscalingConfig
from ray.aut... |
f8de6e3e3056847611705708e7b5b28051d6fadcd83dca40dd27d0e9eba242f8 | Python | 5,109 | 163 | r"""
Training functions with different strategy
"""
from math import ceil
from typing import List, Optional, Union
import torch
import torch.nn.functional as F
from .loss import feature_reconstruct_loss
def train_GAN(wdiscriminator:torch.nn.Module,
optimizer_d:torch.optim.Optimizer,
... |
79f0dfdca144e1a31c3a95997dd7d60e77f29bb1428b58cfc7db824b8be43ff9 | Python | 5,110 | 160 | #!/usr/bin/env python
# coding: utf-8
"""Run Braille inference on SpiNNaker2."""
import os
from itertools import islice
import matplotlib.pyplot as plt
import numpy as np
import torch
from spinnaker2 import brian2_sim, hardware, s2_nir
from torch.utils.data import DataLoader
import nir
seed = 42
os.environ["PYTHONH... |
2eb046d75cab2416e91d55c8f9de289d3bac580a11e3bdf7689b8a601b8e8bd4 | Python | 5,111 | 148 | import tensorflow as tf
import DECIMER.Efficient_Net_encoder as Efficient_Net_encoder
import DECIMER.Transformer_decoder as Transformer_decoder
TARGET_DTYPE = tf.float32
class Config:
"""Configuration class."""
def __init__(
self,
):
self.encoder_config = {}
self.transformer_con... |
074dc591d9c7b80a9b1b013ebd1141f8b5882f162b1c848bc1dc86f820ee34f6 | Python | 5,112 | 88 | import pandas as pd
from itertools import product
def Both_signif_pairs():
exp_signif_list = pd.read_csv('~/Downstream_analysis/Regulators/Lung.m6A_peak_RBP.m6A2me.signif.list', sep = '\t', header = None)
out_signif_list = pd.read_csv('~/Downstream_analysis/Regulators/Lung.DNAme_TF.m6A2me.signif.list', sep = '... |
7d6a33dd21eb8a6c6ec7a376a0e7b3556af2fda5d17586d2581d83bfcf7cc910 | Python | 5,112 | 160 | '''test our simple memory mechanism on meta scene vectors '''
import os
import pickle
import itertools
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from tqdm import tqdm
from copy import deepcopy
from scipy.spatial import distance_matrix
from sklearn.metrics import adjust... |
517618a0d8ae000149d5fff7d57b720c6420958d9b3675ec1397b9a865083775 | Python | 5,113 | 104 | import shutil
import getpass
from os import path
from samri.pipelines import glm
from samri.fetch.local import prepare_abi_connectivity_maps
def abi_connectivity_map(identifier,
exclude_experiments=[],
keep_work=False,
mask='/usr/share/mouse-brain-templates/dsurqec_200micron_mask.nii',
prepare_root='/var/tmp/{user... |
9627938699ea3c79dbe1fcb4ec9240a53e2f7b56d40d50838fa77c31edad0af3 | Python | 5,113 | 135 | from __future__ import annotations
"""
Unified Skill Builder for OmicVerse.
Given a JSON config (validated by config_validator), this module gathers
content from documentation, GitHub, and PDFs into a skill directory with
SKILL.md and reference markdown files.
Security: validates output paths and sanitizes generated... |
7f3ad49475517827493cc14f9485dfb74f4f51fb718a69ebd7fca89e6a7ccaee | Python | 5,116 | 145 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
8141da94d1239c26ab0c4a0da7496f03e123bf84c496af2250488cc078c8131f | Python | 5,116 | 161 | #!/usr/bin/env python
# Sample usage:
# python env-setup.py --version 1.5 --apt-packages libomp5
import argparse
import collections
from datetime import datetime
import os
import platform
import re
import requests
import subprocess
import threading
import sys
VersionConfig = collections.namedtuple('VersionConfig',
... |
df8ddfe21b789a9d6b78b96b564cd7c473b4a54c459e4d0ccb9867f2a8c7b469 | Python | 5,116 | 142 | #Train
import comet_ml
import glob
import geopandas as gpd
import os
import numpy as np
from src import main
from src import data
from src import start_cluster
from src.models import multi_stage
from src import visualize
from src import metrics
import subprocess
import sys
from pytorch_lightning import Trainer
from pyt... |
78398f733817284ba09196f838a10758c1b9d66f17aa527f0bb4f0814408e5a1 | Python | 5,117 | 109 | import os
import json
import torch
import numpy as np
import pandas as pd
from Bio import SeqIO
from biopandas.pdb import PandasPdb
int2AA = {0:'GLY', 1:'ALA', 2:'CYS', 3:'GLU', 4:'ASP', 5:'PHE', 6:'ILE', 7:'HIS', 8:'LYS',
9:'MET', 10:'LEU', 11:'ASN', 12:'GLN', 13:'PRO', 14:'SER', 15:'ARG', 16:'THR',
... |
906b03e367a8c538c5d60201fb3762f1ff4b0b1d8b8bbbd87a88b1d0d6f7f2a5 | Python | 5,118 | 122 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
10e7673d3b4d9be1f791745e88cacaccdb63253799f218fc69a4eb273af5b7a5 | Python | 5,120 | 146 | """Per-sample normalization for proteomics AnnData.
``ov.protein.normalize(adata, method=...)`` is the unified dispatcher
that picks between median centering, quantile normalization, and a
``log2-only`` no-op (for already-normalised inputs like Olink NPX).
"""
from __future__ import annotations
from typing import Opt... |
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