sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
5909eb533454493c9d21943adb337f0deb338c51b6bbb9390c551cb50193a39f | Python | 19,354 | 487 | # ***********************************************************************************
# * Copyright 2010 - 2016 Paulo A. Herrera. All rights reserved. *
# * *
# * Redistribution and use in source and binary forms, with o... |
939d75ae757d7b726a9aff5424c04819df2861333565207b483f0fc328a66a5e | Python | 19,371 | 441 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# encoding=utf8
from collections import namedtuple
import rrc_evaluation_funcs
import importlib
def evaluation_imports():
"""
evaluation_imports: Dictionary ( key = module name , value = alias ) with python modules used in the evaluation.
"""
retur... |
5fa668ce60b4b5df2667d4a38b35b3d25575f10c4e0845e833ab05f1816cfc65 | Python | 19,374 | 524 | import numpy as np
import pandas as pd
import os
from collections import defaultdict
from typing import Union, Tuple, List
from statistics.utilities import (
CONFIG,
bootstrap_ci,
pchip_interpolator,
benjamini_hochberg_correct,
)
from statistics.clustered_mlp_output_wrappers import (
load_metadata_s... |
f4737bcc2a65e010ab587b50ba6e32422faaab0f40d2af0ac1b44dd5142e70dc | Python | 19,382 | 481 | # -*- coding: utf-8 -*-
"""
Created on Wed Oct 12 13:38:23 2022
@author: Daniel
"""
from phase_to_rate.neural_coding import load_spikes, rate_n_phase, load_spikes_DMK
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
import os
import sys
import matplotlib as mpl
import pdb
i... |
89fdf89014e2d0e75ccee574bf103535b4e23d4062aa2ecd320ab4df3dfb1463 | Python | 19,417 | 489 | ############################################
# imports
############################################
import os
import shutil
import unittest
from abc import abstractmethod
from oligo_designer_toolsuite.database import OligoDatabase, ReferenceDatabase
from oligo_designer_toolsuite.oligo_specificity_filter import (
... |
2941dd52e3819f79643ec78cd74e8bade6aaf9e22cf6e479a9e123db58d3a05f | Python | 19,427 | 522 | # Copyright (c) OpenMMLab. All rights reserved.
import math
import os
import warnings
import cv2
import mmcv
import numpy as np
from matplotlib import pyplot as plt
from mmcv.utils.misc import deprecated_api_warning
from mmcv.visualization.color import color_val
try:
import trimesh
has_trimesh = True
except (... |
7989962cd81b6b5a8ae516ccf9326087a1e7a710f7717088c2663545a0aa4386 | Python | 19,429 | 481 | #!/usr/bin/env python
import sys
from os import path, chdir, getcwd
import json
import numpy as np
from picrust2.util import (system_call_check, make_output_dir, read_fasta,
read_phylip, write_fasta, write_phylip,
read_stockholm)
def place_seqs_pipeline(study_fas... |
fb6849e974ac8c3eda12f8508cab5f5142eec3baee8867e25229d9cb5b28e683 | Python | 19,442 | 478 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
import logging
import warnings
from pathlib import Path
from typing import Mapping, Optional, Tuple, Union
import torch
from torch import Tensor, nn
try... |
e8153aeaa6f09604ce4fa74ae24c74eb9139507e3c8c8ddd9b808dbe1833d304 | Python | 19,443 | 612 | #!/usr/bin/python
# -*- coding: UTF-8 -*-
import numpy as np
from pylab import *
def zgrid(W,H=None,):
if H is None: H=W
cw = arange(W)-W//2
ch = arange(H)-H//2
return 1j*ch[:,None]+cw[None,:]
def p2c(p):
p = np.array([*p])
if np.any(np.iscomplex(p)): return p
which = np.where(int32(p.shap... |
db00b9404c411c02b96fab241590acc4fb67b33f55626f9738cfb5568698d7f1 | Python | 19,485 | 540 |
# 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 program is distributed in the hope that it will be usef... |
c47e81cc6475145960c2ba9f459afe4eda59f20e64414ca5131e0c102bb14f35 | Python | 19,511 | 511 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
"""Unit tests for the MoG (Mixture of Gaussians) dataclass."""
from __future__ import annotations
import pytest
import torch
from torch.distributions im... |
33f58942fd58297ac0e6460a522670d5d54332fae8754de54f0c4f480d2df9ce | Python | 19,521 | 541 | #import warnings
#from nengo.exceptions import ValidationError
from nengo.params import NumberParam #, IntParam, FrozenObject, Parameter
#from nengo.utils.compat import is_iterable, is_string, itervalues
import nengo.learning_rules
from nengo.synapses import Lowpass
import numpy as np
from nengo.builder.operator impo... |
bf37655d6344db89389d009f4f35b3dada7a6e4c16cbe4d08d5425865da8baa5 | Python | 19,528 | 453 | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import Scale
from mmcv.runner import force_fp32
from mmdet.core import multi_apply, reduce_mean
from ..builder import HEADS, build_loss
from .anchor_free_head import AnchorF... |
ab0e9b0a888c52d6b44b6c1c6548e2fdd58dd38cb0ab0aa1695c7a05bfecd493 | Python | 19,564 | 457 | """
Step 2 pattern separation analysis with Pearson's R.
Load the raw data, extract phase and rate code and calculate
Pearson's R between pairs of input and output patterns.
The results are stored in a .csv file. These results are necessary
to reproduce Figures 1 & 2.
"""
from phase_to_rate.neural_coding import load_... |
57ac029c3bacf9e124bd364b07e8a3140a9e860212ad995f396d5522eca11f15 | Python | 19,568 | 581 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
from __future__ import annotations
from dataclasses import asdict
import pytest
import torch
from torch import eye, ones, zeros
from torch.distributions... |
f2aa5e688191a5b254246db0eea287856f3e11e13af618ead505e9cb553e4b1a | Python | 19,586 | 648 | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import tkinter as tk
from tkinter import filedialog, messagebox
import os
import sys
def Peri_events_post_processing():
# ------------------------------------------------------------
# SELECT DATA FILES
# ------------------... |
9ceb902d708d4523d352c5b1f979b1c341c0b2061ebe646d0bea4d1e96577b05 | Python | 19,594 | 466 | # -*- coding: utf-8 -*-
"""
Created on Wed Oct 12 13:38:23 2022
@author: Daniel
"""
from phase_to_rate.neural_coding import load_spikes, rate_n_phase, load_spikes_DMK
from phase_to_rate.information_measure import skaggs_information
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn ... |
ffada61e134b353646e03f92ef2038215aa461cf388ac1aed7c0a17f13bba818 | Python | 19,594 | 458 | """
Step 2 pattern separation analysis with Pearson's R.
Load the raw data, extract phase and rate code and calculate
Pearson's R between pairs of input and output patterns.
The results are stored in a .csv file. These results are necessary
to reproduce Figures 1 & 2.
"""
from phase_to_rate.neural_coding import load_... |
c61f411c468334d94a76d478959e1214713cc6ddf72d015292cfd3a9ef82d089 | Python | 19,636 | 499 | import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import pywt
import seaborn as sns
import pandas as pd
from sklearn.metrics import r2_score, mean_squared_error, mean_absolute_error
from sklearn.impute import KNNImputer
from matplotlib.ticker import MaxNLocator
from scipy.signal impo... |
08757fda408a8d0604a63d4deffd0847ac5d01d15bf3bda69882a75e5bf623de | Python | 19,684 | 463 | import queue
import collections
import threading
import functools
import torch
import torch.nn.functional as F
from torch.nn.modules.batchnorm import _BatchNorm
from torch.nn.parallel._functions import ReduceAddCoalesced, Broadcast
from torch.nn.parallel.data_parallel import DataParallel
__all__ = ['FutureResult',... |
edbc6c683b8c7d1488ccb9bdb289c5cb92a75782218cc599b41e15b62af3a389 | Python | 19,696 | 605 | # (c) 2015-2018 Acellera Ltd http://www.acellera.com
# All Rights Reserved
# Distributed under HTMD Software License Agreement
# No redistribution in whole or part
#
import parmed
import numpy as np
from torchmd.forcefields.forcefield import ForceField
from torchmd.parameters import Parameters
from torchmd.forces impor... |
1430f0c464fd9de20abd4102d1a3b20b06410750e8b237f63b9e4155c4c8bdf6 | Python | 19,720 | 499 | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import tempfile
import warnings
from collections import OrderedDict
import json_tricks as json
import numpy as np
from mmcv import Config, deprecated_api_warning
from mmpose.core.evaluation.top_down_eval import keypoint_epe
from mmpose.datasets.bui... |
91e4373c9b45695dae7b89b4904fa9468aec9035acd87a1d52c381a3309307fb | Python | 19,747 | 467 | from math import ceil
from scipy.interpolate import PPoly
from typing import List, Tuple
from util import path_check
from util import mpl_default_setting
import imageio
import matplotlib.pyplot as plt
import numpy as np
import os
import pandas as pd
import seaborn as sns
HARTREE = 627.50947406
# TODO: SKF.__init__()... |
7b0532ec24bd81329b5e39a5c846bde8edc9626600ff43ebbf425eb509457758 | Python | 19,773 | 521 | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import (build_conv_layer, build_norm_layer, build_upsample_layer,
constant_init, normal_init)
from mmpose.core.evaluation.top_down_eval import (
... |
718d65b10b5c60715b87710d053d8ca7d317a534314823a322d420ccab25448a | Python | 19,793 | 522 | import matplotlib
matplotlib.use('agg')
import os
import sys
import argparse
import h5py
import random
import numpy as np
import matplotlib.pyplot as plt
from skimage.transform import resize
import torch
import torch.utils.data as data
import yaml
sys.path.insert(0, os.path.abspath(os.path.join(os.getcwd(), "../../../"... |
95901caeac0d9a683d23a3741f94b6a5660fd174d930ace279398ca90d1cd853 | Python | 19,803 | 453 | from plotly.subplots import make_subplots
import plotly.graph_objects as go
import pandas as pd
import numpy as np
import scipy
import plotly.express as px
from app_main.constants import color_types, color_types_title, font_size, marker_size
from operations.preprocessing import preprocess
from operator import itemgette... |
6acacf9b9dcf9ca549b2736bed4e9e14cfd91848c6a99a3f19481d9034b37f15 | Python | 19,809 | 396 | # permutate confounds (other than 'sex', 'site') with random binary values to test stability
'''
File with configurations to run MLpipeline() class from MLpipeline.py on the IMAGEN data.
This configuration was used for Evert's thesis' experiments and serves as an example for how to
configure the MLpipeline class and ... |
33ac63875d41e6f93e00fa2511db9e929f707e0c3fa3285e0e2d29f8b92e0e5c | Python | 19,811 | 427 | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from mmcv.cnn import ConvModule, normal_init
from mmcv.ops import DeformConv2d
from mmdet.core import multi_apply
from ..builder import HEADS, build_loss
from .corner_head import CornerHead
@HEADS.register_module()
class CentripetalHead(CornerHead... |
338bc347f9d0160fbaf5ea4781d380045d97ac0557f4001c6c01f4f46bac1a78 | Python | 19,840 | 538 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
from functools import partial
from typing import Callable, Dict, List, Optional, Type, Union
import torch
import torch.nn as nn
from torch import Tensor
... |
bf99e0633769047fce12c2df09061767918a1cbc788f5b1ec1be3bed9655c3a9 | Python | 19,850 | 441 | """
This test file contains tests that involve generating synthetic data (using
internal functions from powerlaw) and then fitting to make sure we get the
expected result.
So a full test of most aspects of the library; these tests are meant to
ensure that the library works as it would likely be used. That being said,
... |
656a99acab2f5c3b2a2362eb9bdfc90163577e228d3f48089f693127c77ec31f | Python | 19,857 | 519 | import math
from abc import abstractmethod, ABC
from typing import Union, Optional, Any, Tuple
import eagerpy as ep
from eagerpy.astensor import T
from .base import MinimizationAttack, raise_if_kwargs, get_criterion, get_is_adversarial
from .gradient_descent_base import (
uniform_l1_n_balls,
normalize_lp_norm... |
124dd1fbbb97c1846a82f941bba3e436addd8bbfe878a0a63ad2d8267a148f4e | Python | 19,869 | 427 | # Module containing the genetic algorithms
#
# Author: Fernando García Gutiérrez
# Email: fgarcia@fundacioace.org
#
import random
import pandas as pd
import sklearn
from sklearn.model_selection import RepeatedKFold, RepeatedStratifiedKFold
from deap import creator
from deap import base
from deap import tools... |
afdcbc989142ddb39bf33b81d2e03837e6008c7fa8d634cd1be1df860f763d74 | Python | 19,900 | 494 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Dec 30 11:21:33 2021
@author: baris
"""
import shelve
import numpy as np
import glob
import os
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import copy
def load_spikes(grid_seed, network_type, shuffling, pp_weight):
t... |
9dcc9322e786f35b94304ceed82200a15070dfe92369619fc5a3528f317a5878 | Python | 19,926 | 457 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
#
# 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/LICEN... |
fece7ee3fe1f8befb52ab5cac927cd4d8426d5486db3764bcfc7bdd07974038d | Python | 19,926 | 547 | import warnings
from nengo.config import SupportDefaultsMixin
from nengo.exceptions import ValidationError
from nengo.params import (
Default,
IntParam,
FrozenObject,
NumberParam,
Parameter,
Unconfigurable,
NdarrayParam,
BoolParam,
)
from nengo.synapses import Lowpass, SynapseParam
from... |
ccd5ea2aec05055a45882b3c80cf2d7d32ba1d4941b00e2a68aab345852a370c | Python | 19,955 | 471 | # -*- coding: utf-8 -*-
"""
Created on Wed Oct 12 13:38:23 2022
@author: Daniel
"""
from phase_to_rate.neural_coding import load_spikes, rate_n_phase, load_spikes_DMK
from phase_to_rate.information_measure import skaggs_information
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn ... |
cd4a2de8cac4e7c0a7aa9d175f78387f904c2c8db678fa6be30478d13b1b9094 | Python | 19,965 | 475 | #!/usr/bin/env python3
"""
simulate_sv_genome.py -- svaba SV simulator (genome construction + truth set)
Generates thousands of NON-OVERLAPPING structural variants spanning the full
size range (small indels -> inter-chromosomal rearrangements), applies them to a
reference genome to build a diploid DONOR genome (hap1... |
e8372c1747b1ac877d3d190a0e3a82441fbc4c9b8eeac32d78f0a9eb2211d905 | Python | 19,973 | 494 | class QuartetSet(object):
def __init__(self):
self.quartetLogic = QuartetLogic()
self.quartetSet = DualIndexNoDupes()
self.closureSet = DualIndexNoDupes()
self.conflictingSet = DualIndexNoDupes()
self.compatibleSet = DualIndexNoDupes()
self.compatibleClosure = DualI... |
9948978b47a42ba6e92f27527d82c697d35a7b74a7fa472a965f92f4306fa0d6 | Python | 19,975 | 604 | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import tempfile
import numpy as np
import pytest
from mmcv import Config
from mmpose.datasets import DATASETS
from mmpose.datasets.builder import build_dataset
def test_body3d_h36m_dataset():
# Test Human3.6M dataset
dataset = 'Body3DH36MDataset'
... |
61d4cee63ede11403a3bc7e7dd15d75d08d7adf952b0faf389b7ad1dada43ff3 | Python | 19,977 | 526 | # -*- coding: utf-8 -*-
#
# This file is part of the taxopy package, available at:
# https://github.com/apcamargo/taxopy
#
# Taxopy 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... |
e3d58b3265056ed73d3e9c96630b9c7b3d804717a4c4dac4228d0679f05b459d | Python | 19,980 | 497 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
from abc import abstractmethod
from pathlib import Path
from typing import Any, Callable, Dict, Optional, Self, Tuple, Union
from warnings import warn
im... |
cc4f7290aeb7027fba6c3812878ac62e053c744e3ad7f009d1a3502d36d80262 | Python | 19,985 | 516 | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import numpy as np
import pycocotools.mask as maskUtils
import pytest
from mmcv.utils import build_from_cfg
from mmdet.core.mask import BitmapMasks, PolygonMasks
from mmdet.datasets.builder import PIPELINES
def _check_keys(results, results_translated):
... |
0f4628e322372bf697301fd44a083a4771786f8cae3e9c86f8b3e96869e1d985 | Python | 20,023 | 469 | # Copyright (C) 2022-2025 ETH Zurich, Marc Lehner and other DASH contributors.
import datetime
import pickle
import random
import os
import logging
import time
from typing import NoReturn
import numpy as np
import pandas as pd
from rdkit import Chem
from tqdm import tqdm
from collections import defaultdict
from sere... |
267199c40282569d9a4d7fa315a84565fb8e23fefe095049f52cd3f7a9f990f5 | Python | 20,023 | 499 | ############################################
# imports
############################################
import os
import shutil
import unittest
import pandas as pd
from Bio.SeqUtils import MeltingTemp as mt
from oligo_designer_toolsuite._exceptions import DatabaseError
from oligo_designer_toolsuite.database import Oligo... |
86b8adb01565bb7f61b13302bf9285d6fba0962da1a603a989127700ac78d07c | Python | 20,031 | 545 | # Copyright (c) OpenMMLab. All rights reserved.
import os
import os.path as osp
import tempfile
from collections import OrderedDict, defaultdict
import json_tricks as json
import numpy as np
from mmcv import deprecated_api_warning
from ....core.post_processing import oks_nms, soft_oks_nms
from ...builder import DATAS... |
033fa67465bc7b1fbe5af4af56348644479da7007a846750ac624492cf6bebf1 | Python | 20,035 | 588 | import torch
import csv
import os
import shutil
import sys
import json
import time
# import matlab
# import matlab.engine
import numpy as np
import torch.nn as nn
import matplotlib.pyplot as plt
from numpy import random
from scipy import stats
from skimage import img_as_float
from skimage.metrics import structural_simi... |
ffdb96ab56a087c86398fd99ce6a74d49a4e33087ee69c56c4b46d836ac7601c | Python | 20,045 | 424 | from fold import *
from model_v0 import *
from util import get_sha256
from deprecated.solver_v1 import Solver
from sklearn.model_selection import ParameterGrid
from sklearn.linear_model import LinearRegression
class GridSearchCV:
def __init__(self, dataset_path, gammas_path, target_type,
param_g... |
645a54455d4238afd731048813023cfda2080217133acf6f3725e3515bb6d534 | Python | 20,048 | 572 | # Copyright (c) OpenMMLab. All rights reserved.
import copy as cp
import torch.nn as nn
from mmcv.cnn import (ConvModule, DepthwiseSeparableConvModule, Linear,
build_activation_layer, build_conv_layer,
build_norm_layer, build_upsample_layer, constant_init,
... |
2ed27563e016ebbb1a7e26b5b635994dc30d449df43631782902f21bb0ceb766 | Python | 20,068 | 464 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
import warnings
from abc import ABC
from typing import (
Any,
ClassVar,
Dict,
Literal,
Optional,
Self,
Sequence,
Tuple,
... |
cf534482df530d3bc3768be9368c9943fe461d92c87f737a906b05ed6e33db49 | Python | 20,116 | 494 | # -*- coding: utf-8 -*-
"""
Created on Mon Jul 5 12:07:56 2021
@author: fhu14
"""
#%% Imports, definitions
import re
from Elements import ELEMENTS
import numpy as np
import numbers
from MasterConstants import valence_dict
from typing import List, Dict
Array = np.ndarray
#%% Code behind
def named_re(name: str, re... |
b7f0dc75495c2cf92e14ed14a5edc7bff63e26fe804cb44693b7479f246d9fa8 | Python | 20,130 | 408 | import os
import torch
from collections import OrderedDict
from abc import ABC, abstractmethod
from . import networks
class BaseModel(ABC):
"""This class is an abstract base class (ABC) for models.
To create a subclass, you need to implement the following five functions:
-- <__init__>: ... |
1fc2df2dc1910b6b36a51b78985b62611f2b14a53f4d0ac0b1383eb6e02b733c | Python | 20,189 | 501 | # Imports #
import kivy
import zipimport
import sys
import os
import configparser
import time
import numpy as np
import random
import csv
from kivy.app import App
from kivy.uix.widget import Widget
from kivy.uix.button import Button
from kivy.uix.image import Image
from kivy.uix.label import Label
from kivy.uix.floatla... |
668a22f0c8d59312ff040aa85be53e383c935360403cce16653a6c02f2efc67c | Python | 20,208 | 621 | """
Multi-panel figure for arousal detection analysis on MASS dataset.
This script creates a publication figure combining:
1. Arousal detection performance metrics at different temporal resolutions
2. Sleep stage distribution during detected arousals
3. Example recording visualization with EEG, spectrogram, and predic... |
c0c83e6ca264c15bb08d3ff3a0cc723bf782fc93e85d07f77c55658eae1a7d65 | Python | 20,222 | 623 | """
Tutorial 01: Linear Models
=========================================
In this tutorial you will set up your first linear model with BrainStat.
To this end, we will first load some sample data from the MICS dataset.
"""
from brainstat.datasets import fetch_mask, fetch_template_surface
from brainstat.tutorial.utils... |
bcdb3621009304eba949f2a50f15f988d8d1d8bc23171177b7f7bab1df66fbcc | Python | 20,236 | 609 | # Copyright Universitat Pompeu Fabra 2020-2023 https://www.compscience.org
# Distributed under the MIT License.
# (See accompanying file README.md file or copy at http://opensource.org/licenses/MIT)
from abc import abstractmethod, ABCMeta
from typing import Optional
import torch
from torch import nn
from torchmdnet.m... |
17e51c012c6d48cb3b5673dbabe5d6f6eef24eff5c9ed831b04df7c0280452de | Python | 20,276 | 405 | import argparse
import sys
import os
import subprocess as sb
from sympy import *
from mpmath import *
import numpy as np
import re
class UMIException(Exception):
pass
#def dedupUMIs(fastq,fastq_out,head_to_trim_seq,tail_to_trim_seq):
def dedupUMIs(args,parser):
if not os.path.isfile(args.fastq):
raise... |
471f5fbbf92ad5855d54362a41fc2a81e8e68ea47c36038fab20a2864d9e0bce | Python | 20,282 | 462 | import ontotextapi as onto
import utils
import json
from os.path import isfile, join, split
import joblib as jl
import cohortanalysis as cohort
from ann_post_rules import AnnRuleExecutor
import sys
import xml.etree.ElementTree as ET
import concept_mapping
import urllib3
import logging
class StudyConcept(object):
... |
dcf91185663924a40a749d635121508709496032c1559a44bdf680501247e38c | Python | 20,288 | 554 | #import warnings
#from nengo.exceptions import ValidationError
from nengo.params import NumberParam #, IntParam, FrozenObject, Parameter
#from nengo.utils.compat import is_iterable, is_string, itervalues
import nengo.learning_rules
from nengo.synapses import Lowpass
import numpy as np
from nengo.builder.operator impo... |
20f89354ea2c510e91e3da90cfafa3320c61b94aabbeb2cca0b8f11e3131c270 | Python | 20,292 | 539 | #EEG MODELS: Introducing 5 Branches
#----------------------------
import model
from tensorflow.keras import backend as K
from tensorflow.keras.constraints import max_norm
from tensorflow.keras.layers import BatchNormalization
from tensorflow.keras.layers import Conv2D, MaxPooling2D, AveragePooling2D
from te... |
2da989609ba5a1cb01076575663b2b9b3c380edf00929235cfbb6ab000cafea6 | Python | 20,334 | 478 | import torch
from math import sqrt
import numpy as np
class Parameters:
def __init__(
self,
ff,
mol,
terms=None,
precision=torch.float,
device="cpu",
):
self.nonbonded_params = None
self.bond_params = None
self.charges = None
self... |
60ed23d1317ca0394f71f6bfa444073ff7ec4e62fcfcc333afb1cc550b761bbb | Python | 20,344 | 408 | # -*- coding: utf-8 -*-
"""
Created on Tue Jun 8 18:50:46 2021
@author: fhu14
TODO: Fix the link with DFTBrepulsive when everything's up
"""
#%% Imports, definitions
import torch
Tensor = torch.Tensor
from typing import List, Dict
import numpy as np
Array = np.ndarray
from MasterConstants import Model
from Spline im... |
1fae6d8ea66993568400cc04eaae1df7acf09e4c1b47b6c752b79916e2eff1f5 | Python | 20,423 | 502 | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import os
import os.path as osp
import warnings
from argparse import ArgumentParser
import cv2
import mmcv
import numpy as np
from mmpose.apis import (collect_multi_frames, extract_pose_sequence,
get_track_id, inference_pose_lifter_m... |
c684e7042aa9ef9b8ad19b883547ff96ec37e31dc16f44da2a9e14f259085e09 | Python | 20,445 | 532 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 3 20:54:08 2021
@author: ravinderjit
This script averages mcBTRFs across subjects and does a PCA analysis to get a
sBTRF. Also comparison with behavior
"""
import os
import pickle
import numpy as np
import mne
import matplotlib.pyplot as plt
impor... |
88b47f2ae3577f45b7841bb912e5d7f52722f045c38d9c1392c7d85dbf59f55b | Python | 20,447 | 498 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
import warnings
from typing import Callable, List, Optional, Tuple, Union
import torch
from torch import Tensor
from torch.distributions import Distribut... |
557d82ec567a8de5bd91feb571652ed8740a4af51ebe377a9b6e115fc20f9d3b | Python | 20,474 | 421 | from functools import partial
from typing import Dict, List, Tuple, Union
import torch
from torch.nn import CrossEntropyLoss, Module, ModuleDict, MSELoss
from torchmetrics import MeanAbsoluteError, PearsonCorrCoef, SpearmanCorrCoef
from selbstaufsicht import transforms
from selbstaufsicht.models.self_supervised.msa.t... |
92ebd13250f94b0ceca9cf1f2fcea8060a2fa228baf833bdfb3112d71ced4ebe | Python | 20,478 | 516 | from typing import Optional
from math import sqrt
from inspect import signature
import torch
from tqdm import tqdm
from torch_geometric.data import Data
from torch_geometric.nn import MessagePassing
from torch_geometric.utils import to_networkx
"""This is pyg 2.0.3 code for GNNExplainer made to work on pytorch-geome... |
f7fb84fe8bd69c1a7213ec8be3c4a54ae634208e410167b78d135d1e105f9eae | Python | 20,485 | 529 | from __future__ import annotations
import copy
from typing import Any, List, Mapping, Optional, Set
# import glob
import networkx as nx
import os
from pathlib import Path
from networkx.classes.reportviews import NodeView
import zipfile
from . import _checksum_validator
from ._archive_parser import (
Config, Parse... |
a37a352f9b8e97bc9f1e616d8f991de0fb964d02485dc61f2701441703ca0127 | Python | 20,496 | 664 | import os
import os.path as osp
import shutil
import copy
import time
import pprint
import numpy as np
import torch
import matplotlib
import argparse
import json
import yaml
from easydict import EasyDict as edict
from .model_zoo import get_model
############
# cfg_bank #
############
def cfg_solvef(cmd, root):
i... |
31a135cdd6e47746c1c901eee7bb3910431af854158c023db0ef060a81ec8640 | Python | 20,516 | 664 | import os
import os.path as osp
import shutil
import copy
import time
import pprint
import numpy as np
import torch
import matplotlib
import argparse
import json
import yaml
from easydict import EasyDict as edict
from .model_zoo import get_model
############
# cfg_bank #
############
def cfg_solvef(cmd, root):
i... |
35ab64367c575c24d4688fb737eb38346604d0febb15e0c5e941b694c80ec241 | Python | 20,521 | 583 | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import mmcv
import numpy as np
import pycocotools.mask as maskUtils
from mmdet.core import BitmapMasks, PolygonMasks
from ..builder import PIPELINES
try:
from panopticapi.utils import rgb2id
except ImportError:
rgb2id = None
@PIPELINES.r... |
121b131dec1ad9df0502d41448024025029837f22de38470c2de933d443f279e | Python | 20,554 | 549 | import torch
import torch.distributed as dist
from torchvision import transforms as tvtrans
import os
import os.path as osp
import time
import timeit
import copy
import json
import pickle
import PIL.Image
import numpy as np
from datetime import datetime
from easydict import EasyDict as edict
from collections import Ord... |
53893c29e891e7c00953421477e09c6070d82977ce2f7c9f132f77632ec58470 | Python | 20,554 | 423 | import pandas as pd
import numpy as np
import geopandas as gpd
import os
from pathlib import Path
import matplotlib.pyplot as plt
from B_preprocess import b101_load_cleaned
from B_preprocess import b50_yield_data_analysis
from B_preprocess import b100_load
import pymannkendall as mk
import matplotlib.ticker as mticker
... |
541234eca16415b0812a08eadd956aeea4ea4a3bcecfbeadd98b4c58d9c4b1c9 | Python | 20,604 | 456 | # -*- coding: utf-8 -*-
import ast
import difflib
import itertools
import collections
import numpy as np
from spacy import load
from spacy.matcher import Matcher
from spacy.pipeline import EntityRuler
from .captions import lists
from .utilities import files
from .captions import interpret as interpret
from .captions ... |
eb86e788f74d92618eb947bce941adc610f3a623265e14fd53284eb0cfa15dbb | Python | 20,629 | 402 | from GUI_and_data_processing.Data_processing import analyse_Ethovision_data
from Root_Morales_lab_codes.FibPhoEpocAveraging import FiPhoEpocAveraging
from tdt import StructType
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import os
def find_lists_of_events(inputs):
inputs['... |
9f3d690467a779a5c583afb7d8967324878108a6658f7f34c3ae64bbad225fdd | Python | 20,654 | 480 | ############################################
# imports
############################################
from Bio.Seq import Seq
from Bio.SeqUtils import MeltingTemp, gc_fraction
from seqfold import dg
from oligo_designer_toolsuite._exceptions import ConfigurationError
from oligo_designer_toolsuite.utils import cast_to_li... |
04c8d6f28066f668dbab0c6f72ca2fe5e151bb6e32b86b8b11ed59a24f16ef48 | Python | 20,671 | 509 | # ***********************************************************************************
# * Copyright 2010 - 2016 Paulo A. Herrera. All rights reserved. *
# * *
# * Redistribution and use in source and binary forms, with o... |
53beaca9d335af741add25580b64bbca4a96d68c13e802dd64845e3708aa514a | Python | 20,692 | 541 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
from copy import deepcopy
from typing import (
Callable,
Dict,
Iterable,
Optional,
TypeVar,
Union,
)
import torch
from torch impo... |
7667083549ed8e59ec2fc99cabfb171629207b17a2c65391943fccff0aa29a16 | Python | 20,714 | 602 | # Copyright 2021 Tomoki Hayashi
# MIT License (https://opensource.org/licenses/MIT)
"""StyleMelGAN Modules."""
import copy
import logging
import numpy as np
import torch
import torch.nn.functional as F
from parallel_wavegan.layers import PQMF, TADEResBlock
from parallel_wavegan.models import MelGANDiscriminator as... |
6ba290f525de29cf5cff2bb4387be220119c9b0330254dc6dfb039a08cd33b5b | Python | 20,724 | 509 | # Copyright (c) OpenMMLab. All rights reserved.
from multiprocessing import Pool
import mmcv
import numpy as np
from mmcv.utils import print_log
from terminaltables import AsciiTable
from .bbox_overlaps import bbox_overlaps
from .class_names import get_classes
def average_precision(recalls, precisions, mode='area')... |
aca8ea4b381230b19a6c4bc0cdde694e8bec1145e2ce93cb171565ff4cfb2617 | Python | 20,726 | 581 | import copy
import pickle
import numpy as np
import torch
import torch.utils.data as data
from PIL import Image
from torchvision import transforms
from torchvision.datasets import DatasetFolder
from torchvision.datasets import MNIST, EMNIST, CIFAR10
IMG_EXTENSIONS = ('.jpg', '.jpeg', '.png', '.ppm', '.bmp', '.pgm', '... |
5a9d7331bb503d1be98a09978e9b632b00a88defe852492b881665050c9e142a | Python | 20,735 | 512 | from typing import Annotated, Literal
from pydantic import (
AliasChoices,
BaseModel,
ConfigDict,
Field,
NonNegativeInt,
NonPositiveInt,
PositiveInt,
model_serializer,
model_validator,
)
from typing_extensions import Self
class General(BaseModel):
model_config = ConfigDict(ext... |
4f14f60ca9284ee6b4c5e5c9cacea910fcf250fecad20aa6108a072ffcdb3dc6 | Python | 20,762 | 571 | from os.path import join, exists
from matplotlib.ticker import FormatStrFormatter
from sklearn.metrics import confusion_matrix, precision_recall_curve
from paper_analysis.plot_utils import plot_confusion_matrix
from file_browser import get_models
import pandas as pd
from matplotlib import pyplot as plt
import os
from ... |
fdf0f9cc5f04cae7aaacbe45686ab222d25ea50f4ed27064db00650be2dd2126 | Python | 20,844 | 492 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, Scale
from mmcv.runner import force_fp32
from mmdet.core import (anchor_inside_flags, build_assigner, build_sampler,
images_to_levels, multi_apply, reduce_mean, unmap)
from ..buil... |
246781f5c75316369b47365f315b6cf050ead70d234630d64cf2a25994b65c78 | Python | 20,845 | 601 | import itk
import math
import numpy as np
from usqc.data import get_files
import usqc.phantom
import json
from usqc.util import clamped_region
from glob import glob
import usqc.phantom
import usqc.data
import pickle
import matplotlib.pyplot as plt
import scipy.optimize
from scipy.signal import find_peaks
from scipy.int... |
6ba63bf5abd4800fe92e8d7d8986777534ab32018f0ade03c66291f4ff74a669 | Python | 20,866 | 709 | '''
Author: ----
Date: 2022-04-08 11:09:07
LastEditors: GhMa
LastEditTime: 2022-10-02 19:26:00
'''
import torch
import torch.nn as nn
from .snn_modules import tdLayer, BN, Seq2ANN
def reset_snn(net: nn.Module):
for m in net.modules():
if hasattr(m, '_reset'):
m._reset()
# blocks ############... |
66b38b651d7161d2e1d90af9f792d2dea39c8e4d02a9162f2b1a15449687089d | Python | 20,878 | 490 | # Copyright (c) OpenMMLab. All rights reserved.
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import (ConvModule, DepthwiseSeparableConvModule,
bias_init_with_prob)
from mmcv.ops.nms import batched_nms
from mmcv.runner import force_fp32
from mmdet.c... |
b321eff938fda7b81ae50540112e1c17247076daeff31f6548c165009ca0f5cf | Python | 20,878 | 531 | import torch
import torch.testing as testing
import pytest
from selbstaufsicht.modules import Accuracy, EmbeddedJigsawAccuracy, EmbeddedJigsawLoss, SigmoidCrossEntropyLoss, BinaryFocalLoss, DiceLoss, BinaryPrecision, BinaryRecall, BinaryF1Score, BinaryConfusionMatrix, BinaryMatthewsCorrelationCoefficient
from selbstau... |
f6f7448e474fecf47e179b406a1d278e1f0741dbf073d587f562be253bfb77aa | Python | 20,891 | 607 | # Copyright (c) OpenMMLab. All rights reserved.
import math
from functools import partial
import torch
import torch.nn as nn
import torch.nn.functional as F
from ..builder import LOSSES
from ..utils.realnvp import RealNVP
@LOSSES.register_module()
class RLELoss(nn.Module):
"""RLE Loss.
`Human Pose Regressi... |
4f5f0706f0081652338618827ce247a0c89412373731b43559122ba9c93b1f71 | Python | 20,892 | 635 | # -*- coding: utf-8 -*-
"""
Contains the primary functions for conducting similarity network fusion
workflows.
"""
import numpy as np
from scipy.spatial.distance import cdist
from scipy import sparse, stats
from sklearn.utils.validation import (check_array, check_symmetric,
check_... |
6f0c4e682003501a82526f2132f5d5b5cc6b8f4dd3c89ee746dbc3d254a93b9a | Python | 20,920 | 530 | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import os.path as osp
import cv2
import numpy as np
import pytest
import xtcocotools
from xtcocotools.coco import COCO
from mmpose.datasets.pipelines import BottomUpGenerateHeatmapTarget # noqa
from mmpose.datasets.pipelines import (BottomUpGenerateOffsetTa... |
6a685c62f1bffb7a2ed3cd95a69d5cdcfb049aba16ebe35fb3131ffd475b3270 | Python | 20,993 | 587 | """
YL
The nobiko_opt.neko names are for the LSTM options:
Maru - CRNN
Haku - CRNN
Pixel - CNN only
Requires util.restnet_3d.py for the 3D resnet.
"""
import torch
import torch.nn as nn
import util.resnet_3d as tora_3dresnet
class Maru(nn.Module):
def __init__(self, tora_opt):
super().__init__()
... |
05ef7dd083d5e75a1cbdddce946fc87f461aa5e22d07fa9425283d9d5c046081 | Python | 21,060 | 487 | #!/usr/bin/env python3
"""
mcnemar_inception.py
────────────────────
McNemar's test comparing MVLM against a faithful reimplementation of
InceptionDTA's multi-scale inception CNN architecture on the KIBA benchmark.
InceptionDTA reference:
Kalemati et al., Heliyon 2025, doi:10.1016/j.heliyon.2025.e42476
Why a reim... |
892071fe99a1577b7e3015744b1fe77c3999ec7fd88c2ab0ee5ace23707d7b14 | Python | 21,074 | 515 | # coding: utf-8
"""Callbacks library."""
from collections import OrderedDict
from dataclasses import dataclass
from functools import partial
from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple, Union
from .basic import (
Booster,
EvalResult,
_ConfigAliases,
_log_info,
_log... |
bb1f30f963d0dcf339f973298540b3710a89d8e1a7715e0bb234062838961d7d | Python | 21,111 | 605 | import json
from html import escape
from typing import Any
import numpy as np
from .ambiguity import is_nucleotide_alphabet
def _to_list(values: Any) -> list:
if values is None:
return []
if isinstance(values, np.ndarray):
return values.tolist()
return list(values)
def _site_class_valu... |
6eff3f2876e4bafd4a15941aa253aba34da03f448690cef4ea18d7ff2a21e31b | Python | 21,117 | 595 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
import warnings
from typing import Dict, Optional, Sequence, Union
import torch
from torch import Tensor, float32
from torch.distributions import (
B... |
b471b564e3c56474941dccd6bd827d942990a4a38211ebc295c2a30a87ff2b8c | Python | 21,126 | 599 | import os
import os.path as osp
import PIL
from PIL import Image
from pathlib import Path
import numpy as np
import numpy.random as npr
import torch
import torchvision.transforms as tvtrans
from lib.cfg_helper import model_cfg_bank
from lib.model_zoo import get_model
from lib.model_zoo.ddim_dualcontext import DDIMSamp... |
bdbbe9845a0adac8ba0a336c8cee8aaff327a6845c12945a1d24efd162eb3321 | Python | 21,179 | 551 | from p4.p4exceptions import P4Error
from p4.tree import Tree
import p4.nexus
from p4.var import var
import os
import string
import io
import copy
import math
import sys
class PosteriorSamples(object):
"""A container for mcmc samples from files.
This would be useful if you wanted to do eg posterior predictiv... |
961e84e5acce0c85530ba284dd693f4212ca1fcd82760f354f58b7d09b7b55f3 | Python | 21,181 | 382 | """Deep Hebbian Predictive Coding networks.
"""
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
import numpy as np
import os
import torch
import torch.nn as nn
class pclayer(nn.Module):
def __init__(self, layer_size, nextlayer_size, i_rate, device, l_rate):
""... |
6733679aed9a3362d43c874c5b68de6d45b5df3bbd010e7b5290bb8ff7b56e12 | Python | 21,205 | 591 | import copy
import numpy as np
import pytest
import torch
from mmdet.core import GeneralData, InstanceData
def _equal(a, b):
if isinstance(a, (torch.Tensor, np.ndarray)):
return (a == b).all()
else:
return a == b
def test_general_data():
# test init
meta_info = dict(
img_s... |
7a019af15211eea37bb0f92060ba75f1b6c1ae0fbfa3270598d383e4fe279390 | Python | 21,258 | 455 | import torch
from torch import nn
from .perception_loss import vgg16_feat, perceptual_loss
from .base_model import BaseModel
from . import networks
# from parse_config import ConfigParser
# import parse_config
import numpy as np
class DadganModelG(BaseModel):
""" This class implements the generator model only, f... |
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