sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
6ca0c32fab5b935856255353a1674f01c35ef19fae1db7d8d2e094fab3cd159a | Python | 12,076 | 337 | import argparse
import logging
import os
import shutil
import time
import warnings
from pathlib import Path
from pickle import dump
from typing import List
import matplotlib
matplotlib.use('Agg')
warnings.simplefilter(action='ignore', category=FutureWarning)
import numpy as np
import pandas as pd
from sklearn.model_... |
0b83a7c3f16bc09318b98f18473d84a7611ad2274f9dd37664747163994e5d25 | Python | 12,094 | 266 | # -*- coding: utf-8 -*-
"""
Created on Tue Jun 8 17:21:16 2021
@author: fhu14
"""
#%% Imports, definitions
from typing import Union, List, Dict
from h5py import File
import numpy as np
import collections
from copy import deepcopy
#%% Code behind
def get_data_type(specs: Union[List[str], str]) -> List[str]:
r"""... |
f25eccb1670abc515d8fa2435321067bc4fb748a80d26f5bf6f7e99d39094a0f | Python | 12,111 | 292 | # 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 typing import List, Optional, Tuple, Union
from torch import Tensor, nn
from sbi.neural_nets.embedding_nets.cnn import (
_validate_cnn_input_sh... |
00cd83ba1c7323d751d6521a1dfbcb77696f85d8add6aebfc97d604afe18df3b | Python | 12,124 | 311 | #!/usr/bin/python
# -*- coding: UTF-8 -*-
"""
Routines for loading and preparing Krupic lab datasets
Resolution for the camera used to record R1 is 350px/m;
resolution for other rats (R11 and R18) was 338px/m
Fs = 50.0 # Sample rate of data (samples/second)
"""
from numpy import *
from scipy.io import loadmat
from scip... |
f9accb836c1103691910cc44f9cf9f4884c7e73ae4cb8c77bec0a2e22584dba8 | Python | 12,124 | 338 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint as cp
from mmcv.cnn import build_conv_layer, build_norm_layer
from ..builder import BACKBONES
from .resnet import Bottleneck as _Bottleneck
from .resnet import ResLayer, ResN... |
b757cf02d2264f3b29dd8ac762a710660e462e159d5dc669a026f450af58974f | Python | 12,149 | 322 | # SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source... |
ab2dc6de0f8b5472190b599a03bef199cf5d3b4de7126e7b32724ee8f641c511 | Python | 12,166 | 316 | """HTML reports for fitted SLM objects."""
import html
import json
import os
import tempfile
from pathlib import Path
from typing import Mapping, Optional, Sequence, Union
import numpy as np
MapSpec = Optional[Sequence[str]]
SurfaceSpec = Optional[Union[str, Mapping[str, object], Sequence[object]]]
def _is_surface... |
7f74fa6d453884630990836046d41f9ae53f0a3146c3c7cd317499cdc42610c9 | Python | 12,169 | 244 | """
Michele, 02/09/2021, bugs fix and merge preprocessing 1D and 2D
bugs:
1D and 2D:
- Uses a different method to select 90% production regions (union of crops) but then uses stats90 in model evaluation (some regions will be thus missing)
2D:
- image norm was very strange (norm by cum with effect of having 1s in meteo... |
ab3371e5b5a7dce4832f6e525a3a32fea6c790e4fbce718572ceb4eddea77950 | Python | 12,188 | 310 | # -*- 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... |
c57c5020e20490b2a004f5748839f379192ec66021c2f7f671e311f2f218c06a | Python | 12,216 | 317 | # -*- 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... |
268c94637ff378ba6d1a50c93842aa9623c3a2437c96f138123ba2c9a80e1291 | Python | 12,222 | 304 | import abc
import argparse
import dataclasses
import typing
import warnings
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
from osgeo import ogr
from osgeo import osr
import argparse_types
import models.abstract
import scope_utils
from argparse_ext import DeprecatedStoreAction
from plots ... |
8bf6d0997843b34c765aaa014303e1181f92b4fb83402a21258ffcd9f4e21c27 | Python | 12,222 | 193 | """The metric class used during network training to record metrics of interest such as the readout accuracy or reconstruction error.
Example:
all_metrics = metrics(evaluate_on_validation_data=args.use_validation_data)
all_metrics.add_run()
all_metrics.compute_and_append(results_path, flags['eval_steps'], r... |
18687debd95fcd11ba9aa3eaec43b8e6560cb662584976d5e2538d444b494efc | Python | 12,275 | 382 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Sep 6 13:52:52 2021
@author: baris
"""
import numpy as np
import copy
import shelve
import os
import glob
import pdb
def _spike_counter(spike_times, bin_size_ms=100, dur_ms=2000):
n_bins = int(dur_ms / bin_size_ms)
n_cells = len(spike_times... |
a17bffe85b0778f47b6ec7fc1e93dceea1fc184545ad9d90c4e45d5543fa55e8 | Python | 12,276 | 328 |
import torch
import csv
from dateutil import parser
import numpy as np
import time
import random
import os
# !wget https://files.ipd.uw.edu/pub/training_sets/pdb_2021aug02_sample.tar.gz
# !tar xvf "pdb_2021aug02_sample.tar.gz"
# !wget https://files.ipd.uw.edu/pub/training_sets/pdb_2021aug02.tar.gz
# !tar xvf "pdb_20... |
8fc4b7f5272d54bd5dd77bc4e5e7db7bd3bee2fcb90093b92ae6fb9affe1101b | Python | 12,277 | 262 | ############################################
# imports
############################################
import pandas as pd
from joblib import Parallel, delayed
from joblib_progress import joblib_progress
from oligo_designer_toolsuite._exceptions import ConfigurationError
from oligo_designer_toolsuite.database import Oli... |
0ce90c3e5fad90b34be72cb292db4d0f042dd2f5efbd583b417785ad0afe6fb1 | Python | 12,280 | 374 | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import logging
import os
import os.path as osp
import tempfile
from unittest.mock import MagicMock, patch
import mmcv
import numpy as np
import pytest
import torch
import torch.nn as nn
from mmcv.runner import EpochBasedRunner
from torch.utils.data import Dat... |
fd16a7034fd51d10b5a4ee00a754ee4e4277d49d9578f4c07b6d0693f973eb20 | Python | 12,284 | 372 | '''
Author: ----
Date: 2022-04-16 11:47:44
LastEditors: GhMa
LastEditTime: 2022-10-02 19:25:28
'''
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
import torch.backends.cudnn as cudnn
from torch.utils.tensorboard import SummaryWriter
import os
import uuid
import argparse
... |
726d84e705e85352bab3b5e1e55492d3d2d5a66b4af98036651f54741307fa81 | Python | 12,295 | 304 | import numpy as np
from sklearn.base import BaseEstimator, TransformerMixin
from scipy.stats import ttest_ind, pearsonr
from sklearn.model_selection import StratifiedKFold, train_test_split, cross_val_predict, \
RepeatedStratifiedKFold, GridSearchCV
from sklearn.feature_selection import VarianceThreshold
from sklea... |
11b5725686ba0e6b7b4d7ebc1cb59f5b045fdd7b67c78194d1366a3e143cf501 | Python | 12,303 | 304 | """
This test file contains tests that involve fitting distributions to
reference data and checking that the results are similar to previously
saved values.
All of the test datasets can be loaded using ``powerlaw.load_test_dataset()``
if you would like to experiment with them.
Note: in the original repo, quakes.txt w... |
c636dd2b812367fb520413fbb9d35564c95e825bcfea48d75322905be2723807 | Python | 12,306 | 317 |
import os
os.environ['XLA_PYTHON_CLIENT_PREALLOCATE'] = 'false'
from pprint import pprint
import jax
import jax.numpy as jnp
import jax.tree_util as tree
import numpy as np
from functools import partial
import haiku as hk
import optax
from absl import app, flags, logging
from collections import namedtuple
from tqdm i... |
76e8c4c2cf156f4b849f16ab725f8c915a0765d5531e3b8bd6ab5c84b768ae11 | Python | 12,308 | 351 | # -*- coding: utf-8 -*-
#
# LightGBM documentation build configuration file, created by
# sphinx-quickstart on Thu May 4 14:30:58 2017.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# ... |
8ea84f7e248c260d2ac24a232b187f5315a53f44f1c7bd6379a43da0da28fece | Python | 12,327 | 293 | # -*- coding: utf-8 -*-
"""
Created on Sun Jun 25 11:09:32 2023
@author: Anandita
"""
'''In this file we consider product of two different tuning curves, sigmoidal and
Gaussian. We consider an even no. of dimensions and assume tuning along half of
the dimensions are sigmoidal and along half of the dimensions... |
27f305d822599b32971242cadc1061720cbf8bdc218c9d0750fb86eb923d42e0 | Python | 12,350 | 286 | # -*- coding: UTF-8 -*
import numpy as np
import networkx as nx
from graph import *
import random
import time
import math
import numpy
import scipy
import networkx as nx
import matplotlib
import pylab
from collections import defaultdict
import matplotlib.pyplot as plt
from utils import *
###############################... |
73f380f58fe71219d451d8f45f198105e62bf317df3246510690df6b2c2bad35 | Python | 12,351 | 297 | import argparse
import logging
import os
import random
import socket
import sys
import datetime
import numpy as np
import psutil
import setproctitle
import torch
import wandb
import yaml
# add the FedML root directory to the python path
sys.path.insert(0, os.path.abspath(os.path.join(os.getcwd(), "../../../")))
fro... |
22ef48b734ed4dc5cbe55248dc688157b7e8b4aaa98b98e247350752df21cbaa | Python | 12,354 | 240 | """Packed periodic neighbor lists for stress training with the built-in loader.
``SizeGroupedDataset`` batches are dense ``(B, N)`` arrays, while stress needs
explicit neighbor topology with periodic shifts. :class:`PeriodicNeighborCollate`
converts each batch to the packed mode-1 layout the calculator uses: real
atom... |
f3fdc930287cdbf96192db71d29652eb8f67619cb2eb5bfdd258c750e06c7033 | Python | 12,373 | 231 | import numpy as np
import tensorflow as tf
tf_rng_seq = tf.random.Generator.from_seed(1234)
@tf.function
def select_kv(key, val, len_full, len_select, select_method):
'''
select some k-v pairs from the full set of k-v pairs, and append them to the list of k-v pair lists
if len_select > len_full, then sele... |
3834545101ceb94238612a6f333d6b0f4a781cf58adba7fa0939f87326601e55 | Python | 12,376 | 368 | """File IO for daart package."""
import csv
import numpy as np
import os
import pickle
from typing import List, Optional, Union
from typeguard import typechecked
import yaml
@typechecked
def get_subdirs(path: str) -> List[str]:
"""Get all first-level subdirectories in a given path (no recursion).
Parameters... |
7c1bf5f33fa8e2f179b834ab50e6e1895f28faaf697ce1c5cccb03d1faedb497 | Python | 12,389 | 339 | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import os
from argparse import ArgumentParser
from multiprocessing import Pool
import matplotlib.pyplot as plt
import numpy as np
from pycocotools.coco import COCO
from pycocotools.cocoeval import COCOeval
def makeplot(rs, ps, outDir, class_name, iou_type):... |
1584e9ef5af733d0c9657bc08e1ee0b867a6f151fed149056022686b2acdfb51 | Python | 12,395 | 383 | import argparse
import numpy as np
import os
import pandas as pd
from pathlib import Path
import pickle
import shutil
import subprocess
import time
import yaml
from daart.io import find_experiment
# https://stackoverflow.com/a/39452138
CEND = '\33[0m'
BOLD = '\033[1m'
CBLACK = '\33[30m'
CRED = '\33[31m'
CGREEN = '\3... |
28a315fde3b348ad3c8d7fed2142a063f57e016deaf555b62ad7ed0130fc6800 | Python | 12,400 | 319 | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch.nn as nn
from mmcv.cnn import build_conv_layer, constant_init, kaiming_init
from mmcv.utils.parrots_wrapper import _BatchNorm
from mmpose.core import (WeightNormClipHook, compute_similarity_transform,
fliplr_regres... |
7e37094628da13d720f42f914af0aa7ff2def66bd28ec6a054bb20040e36ed0a | Python | 12,409 | 286 | """
Created on Wed Dec 1 11:46:36 2021
@author: baris
"""
from phase_to_rate.neural_coding import load_spikes, rate_n_phase
from phase_to_rate.perceptron import run_perceptron
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
# parameters
phase_bin = 360
time_bin = 250
dur... |
6f7b9a3dbc7470e2d0440f7c9ce2056e492640f6b0a635e188b563f5dedc1d1f | Python | 12,414 | 306 | # 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 typing import Any, Callable, List, Optional, Tuple, Union
import torch
import torch.distributions.transforms as torch_tf
from torch import Tensor
fr... |
0535a1a47caaa5a784d492cf755a4fba52d8ad2cd7330a3a13fdec8ce14b1e20 | Python | 12,423 | 338 | # 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 typing import Optional, Tuple
import torch
from torch import Tensor, nn
from torchmdnet.models.utils import (
... |
93263a7dc273836afa0a1aa6d55674be53cf591fcb89aac9cd4b3930a3f2d130 | Python | 12,437 | 340 | # __author__ = haitham elmarakeby
from sklearn import metrics
from sklearn.metrics import average_precision_score
import seaborn as sns
from mpl_toolkits.axes_grid1 import make_axes_locatable
from utils.stat_utils import score_ci
from sklearn.metrics import confusion_matrix
from matplotlib import pyplot as plt, ticker... |
e8c79984fa3fde9383241e7b9f3bf0f5f14facc60e89bd3450d314160f631e6e | Python | 12,456 | 337 | from typing import Union, List, Optional
import numpy as np
import pandas as pd
import re
from .depth_estimation import calculate_brain_center_depths
from .plane_alignment_functions import plane_alignment
def trim_mean(arr: np.array, percent: int) -> float:
""" "
Calculates the trimmed mean of an array, sourc... |
7a71e0e9d01e678e0f4395313fc27cb0676cc7f603b2a91ae86d1933b645e690 | Python | 12,476 | 202 | import argparse
from collections import namedtuple
import math
import torch
# Generates bash scripts for random-search-based hyperparameter optimization.
# AUXILIARY TYPES AND FUNCTIONS
VarRange = namedtuple('VarRange', ['min', 'max', 'type'])
rescale_rand = lambda rand_val, min_val, max_val: min_val + (max_val - min... |
a99df89eab1e59af11ea2dd511b378c88be01fe768fb68f732b19d355ac589ae | Python | 12,485 | 319 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Aug 28 15:41:50 2020
@author: bariskuru
"""
import seaborn as sns, numpy as np
import matplotlib.pyplot as plt
from grid_short_traj import grid_maker, grid_population, draw_traj
from scipy import interpolate
from skimage.measure import profile_line
fro... |
71606f3c2a0135fc9f2cdb2b73163162798e195e8feab3c5f0988f3a9061e2dd | Python | 12,492 | 293 | import torch
import numpy as np
from tqdm import tqdm
from functools import partial
from .diffusion_utils import make_ddim_sampling_parameters, make_ddim_timesteps, noise_like
from .ddim import DDIMSampler
class DDIMSampler_VD(DDIMSampler):
@torch.no_grad()
def sample(self,
steps,
... |
8c472a9bcf530583f775608166360f78e724553f52201c0adae94c61bed16304 | Python | 12,497 | 347 | # -*- 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... |
f15f0168a6b2a0d8fbd640976a4c4fc081ddc467aa6c3733fe111dbf79393fbd | Python | 12,497 | 268 | # -*- coding: utf-8 -*-
"""
Created on Mon Jul 4 13:44:36 2022
@author: fhu14
Training process for the repulsive model only. The electronic aspects of the
SKF files are maintained as constant (not trained).
The workflow looks like this:
1) Add DFTB+ predictions to the molecules using the existing analysis code
... |
47f002b8b3992e9bf75bda9230dab755e9c4d183dd32a747cb7ccf76082b048a | Python | 12,500 | 366 | # ------------------------------------------------------------------------------
# Adapted from https://github.com/leoxiaobin/deep-high-resolution-net.pytorch
# Original licence: Copyright (c) Microsoft, under the MIT License.
# ------------------------------------------------------------------------------
import math... |
2f22cd6e3ff60c6e3e5c73be5020ef0cfee3bf7ab7aaf4a43ae715bfbe42faf7 | Python | 12,514 | 329 | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import torch
import torch.nn as nn
from mmcv.cnn import (build_conv_layer, build_norm_layer, constant_init,
normal_init)
from mmcv.utils import digit_version
from torch.nn.modules.batchnorm import _BatchNorm
from mmpose.models.utils.ops ... |
0737655b52b7363f4169938c9e30ad5bc66980f3d16fe04b76324f13baf6b722 | Python | 12,525 | 330 | import numpy as np
import pandas as pd
import math
def get_eye_speed_outlier_threshold(eye_speed):
"""
Get the eye speed outlier threshold, defined as the maximum of 10 and three
standard deviations above the mean eye speed in the entire experiment. All times
where the eye exceeds this threshold will ... |
4c347039504ed28f9f9c982c0a5ea3e552d09d5850a376799ec3c803918be2b7 | Python | 12,541 | 353 | # 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 dataclasses import asdict, dataclass, field
from typing import Any, Dict, List, Optional, Tuple
import matplotlib as mpl
from matplotlib import pypl... |
4772eee75eafa86d0a0931bd9c4c09d79fdba5ed6094ba525d814a5b5d51fff8 | Python | 12,544 | 343 | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import tempfile
import warnings
from collections import OrderedDict, defaultdict
import mmcv
import numpy as np
from mmcv import Config, deprecated_api_warning
from mmpose.core.evaluation import keypoint_mpjpe
from mmpose.datasets.datasets.base imp... |
0a205d1b176379527674f98160bf147ce2d3b1d9cb5cc2a185ef663b44c36015 | Python | 12,550 | 399 | # Copyright (c) OpenMMLab. All rights reserved.
import cv2
import mmcv
import numpy as np
import torch
from mmpose.core.post_processing import (affine_transform, fliplr_joints,
get_affine_transform)
from mmpose.datasets.builder import PIPELINES
def _flip_smpl_pose(pose):
... |
4ac63a24350ebed14e1d32785bfac6547f1d46760d83526d62734600c6db76db | Python | 12,550 | 305 | """
Training dataset for AnySleep model with variable channel counts.
This module extends the U-Sleep sampling strategy for attention-based models
that can handle variable numbers of input channels. Unlike USleep which always
uses exactly 2 channels (1 EEG + 1 EOG), AnySleep can process any number of
channels and lear... |
f780abae554d05c77219416345f91fa122ec5c30aba789d881e8739360a51dcc | Python | 12,565 | 347 | # @author semese
import torch
import shutil
import numpy as np
import matplotlib.pyplot as plt
from torch.optim.lr_scheduler import ReduceLROnPlateau
device = torch.device(
'cpu') if not torch.cuda.is_available() else torch.device('cuda:0')
class Trainer:
''' Wrapper class for model training and evaluation.... |
b2eaea86899d85ba2ea9682d4a46d44b32c5d59cfccf3144641ae8e9d170d883 | Python | 12,632 | 308 |
import argparse
import sys
import pysam
def parse_options():
parser = argparse.ArgumentParser(description="This program checks "
"whether reads that overlap SNPs map "
"back to the same location as the "
... |
b75d40012b517721cc95c45e305688d4179f6f876f4f3a2e73c93427a3b3a11c | Python | 12,636 | 368 | #!/usr/bin/python
# -*- coding: iso-8859-1 -*-
#
# progressbar - Text progressbar library for python.
# Copyright (c) 2005 Nilton Volpato
#
# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundatio... |
62524136fc8340ecbbb72ab8e36e7fe8c8a2f3ab79618498016cc55bfe41ec05 | Python | 12,643 | 270 | # -*- coding: utf-8 -*-
"""
Created on Thu Nov 4 21:49:06 2021
@author: fhu14
"""
"""
Updated Cat1 DFTB+ analysis script with master functions written in
run_dftbplus.py
Analysis pipeline:
1) get test dataset
2) run add_dftb to compute and add targets based on trained SKFs
3) feed resultin... |
ce18fcdb0ee415661ae0efdd6a66b204a517f65ec49e989ebf8d6e97cd0e9413 | Python | 12,646 | 325 | import jax
import jax.numpy as jnp
import numpy as np
from functools import partial
import weno_3_coeff as coeff
def get_euler_eigen_vector(u, c, H, gamma):
# each of size [...]
# right eigen vectors of Euler equations, R
# [3, 3, ...]
# _ _
# | |
# | ... |
cf015678f56dbe041f8f0ddbce15d42c2140c95f04f33ad929079c945aeeef3d | Python | 12,646 | 340 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from ..builder import LOSSES
from ..utils.geometry import batch_rodrigues
def perspective_projection(points, rotation, translation, focal_length,
camera_center):
"""This function computes the perspective... |
ddc1286352dd19698c254bc8d9907e1f883f5685809f0ea5d6558015f881ba46 | Python | 12,646 | 317 | import math
import pytest
from usqc.phantom import Phantom
import usqc.qc as qc
import usqc.data
from pathlib import Path
import itk
@pytest.fixture(scope="session", autouse=True)
def phantom():
return Phantom()
@pytest.fixture(scope="session", autouse=False) # it takes forever to make the phantom image
def image(... |
91c08fef77750a6c06d59f22baa27e30924d6f5d5d128fa5a53cb01c2b37e28e | Python | 12,650 | 347 | import warnings
import numpy as np
import pytest
import torch
from aimnet.calculators import AIMNet2Calculator
pytestmark = pytest.mark.weights
def _set_method(calc, method):
with warnings.catch_warnings():
warnings.filterwarnings("ignore", message="Model has embedded Coulomb module", category=UserWarn... |
d90576793813bc31c93b5e655a59aeb9f184f0a7f4d99653f063c9323c5425ae | Python | 12,657 | 410 | #!/usr/bin/env python3
# Copyright 2021 Wen-Chin Huang and Tomoki Hayashi
# Copyright 2022 Shuai Guo
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Evaluate log-F0 RMSE between generated and groundtruth audios based on World."""
import argparse
import fnmatch
import logging
import multiprocessing as ... |
90fc2f858bf718ba633ff1e1208ed527ee060cdb96fd9672273917cb60edfa6b | Python | 12,664 | 245 |
import sys
#############################
# 1. Config file, run type, name, and where to tune
#############################
# run_name = 'ZM_20241220'# '20241016_75_100_maize_sunflower_soybeans_NorthernCape' #'20241004_75_100_maize_sunflower_soybeans'
# runtype is overwritten when called by manager_50_ope or manager_... |
c13ccd921fbf9630ed768d2b742b18340ad909b75b9e42d51e952cfa2bd2a0d1 | Python | 12,670 | 331 | import os
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from torchmdnet.models.energy_correction.functional import softplus_inverse, switch_function
from typing import Tuple, Optional
"""
computes D4 dispersion energy
HF s6=1.00000000, s8=1.61679827, a1=0.44959224, a2=3.35743605
"... |
0533cd38bd5de507a55367241715d5a03d9fb10f604cd0f098ba00bda0f64380 | Python | 12,697 | 310 | import pandas as pd
import numpy as np
from glob import glob
from os.path import join
import os
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
from matplotlib.patches import Rectangle
import seaborn as sns
import re
import sklearn.metrics as metrics
def plot_result(df_full, x="test_score", con... |
640aee60cccd284e3c977019b8326f7348b2652ef1ac9ff716a2e1e63f1b1167 | Python | 12,711 | 379 | # Copyright (c) OpenMMLab. All rights reserved.
from collections.abc import Sequence
import mmcv
import numpy as np
import torch
from mmcv.parallel import DataContainer as DC
from ..builder import PIPELINES
def to_tensor(data):
"""Convert objects of various python types to :obj:`torch.Tensor`.
Supported ty... |
9bad90fea1ee6b5e0447b218bd676aa040ec7bacd0037ee320acdca132014237 | Python | 12,716 | 417 | #merge cnvnator output
import os
import sys
import sys
from optparse import OptionParser
import functions
#hard coded cutoffs
GAP_LEN_CUTOFF = 70
GAP_CUTOFF = 90
CNV_CUTOFF = 30
LEN_CUTOFF = 70
RATIO_CUTOFF = 10
header = ["#sample","chrm","start","end","cnv","size","normalized_rd","e-val2","q0"]
parser = OptionParse... |
8d17ce605590f17aa7b3027c295f048a79a144fcb94790625d721c417413f4db | Python | 12,725 | 383 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import binascii
import codecs
import marshal
import os
import re
import sys
import time
import types as python_types
import zipfile
import tarfile
import numpy as np
import six
class Progbar(object):
"""D... |
1fb5af2a86ef62ce24615301068d7f59584fed0c4975163fd01ed0ca3b7f2afa | Python | 12,736 | 353 | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
import torch.utils.checkpoint as cp
from mmcv.cnn import (build_conv_layer, build_norm_layer, constant_init,
kaiming_init)
from mmcv.runner import Sequential, load_checkpoint
from torch.nn.modules.batchnorm import _BatchNorm
fr... |
ba6eb6d23915b5064a0713b62556490d601f2c67014e63ae8e3e0d28447257e5 | Python | 12,736 | 382 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
from pathlib import Path
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import numpy as np
import pandas as pd
import seaborn as sns
# Biplot
def mybiplot(score, coeff,
path_name_saved_file=None,
score_... |
0d4b24270df8da1c0ae6c3b1a4cd6ded89fb57c2620e971889c18d045b786ab7 | Python | 12,748 | 292 | # -*- coding: utf-8 -*-
"""
Created on Sun May 29 14:04:15 2022
@author: fhu14
"""
#%% Imports, definitions
from typing import Dict, List
import random
import os, shutil, pickle
import re
#%% Code behind
def shuffle_dict(dictionary: Dict) -> None:
r"""Shuffles the molecule list for each empirical formula in the ... |
5c5af6e5f71dfdad17d85c3b87b6751c0cc515ca8e389ae90211573e520abf17 | Python | 12,759 | 341 | import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision
try:
from torchvision.models.utils import load_state_dict_from_url
except ImportError:
from torch.utils.model_zoo import load_url as load_state_dict_from_url
# Inception weights ported to Pytorch from
# http://download.tenso... |
9a50dbb78e7cb190335feb33a113d4904844c2d4bbcf0f81d9a27d8ed16ae6c1 | Python | 12,768 | 305 | import argparse
import os
import torch
import numpy as np
import cv2
from sep.training.JointModel.network import JointModel
from sep.eval.get_items import compute_metrics, get_items
import sep.helpers.utils as utils
from sep.helpers.eval_utils import si_sdr
from sep.helpers.constants import FS, SPEED_OF_SOUND
from ast... |
0ae2963fc8e302b4d87022f971ef54f2ee9dcb15ac034c9ecf568619d1831f01 | Python | 12,770 | 289 | ############################################
# imports
############################################
from typing import Any
from effidict import EffiDict, LRUReplacement, PickleBackend
from oligo_designer_toolsuite._constants import SEPARATOR_OLIGO_ID
from oligo_designer_toolsuite.utils._logging import logger
from .... |
41589b9a0ce744ea3170c4b4e747c2464fcaa8d98aef3db327d3f33e040241ff | Python | 12,770 | 357 | # 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_pck_accuracy
from ...builder... |
018e86900674b913c14b58e27c0bb6cad21607d6ffe7a5b7ebc48ddd03d15c93 | Python | 12,771 | 324 | '''
The code deeply follows and taken from the MRQy (https://github.com/ccipd/MRQy)
@article{sadri2020mrqy,
title={MRQy—An open-source tool for quality control of MR imaging data},
author={Sadri, Amir Reza and Janowczyk, Andrew and Zhou, Ren and Verma, Ruchika and Beig, Niha and Antunes, Jacob and Madabhushi, A... |
ca729a0bddf376a774d6abd065a009a6df1b5d375fc2c18509354f9118fd621e | Python | 12,788 | 417 | # 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)
import yaml
import argparse
import numpy as np
import torch
from os.path import dirname, join, exists
from lightning_ut... |
fd6a2f2d2d926a58857e2b653485a02d304a26b03f0b60138342ee271e7e6981 | Python | 12,792 | 294 | import copy
import logging
import time
import torch
import wandb
import numpy as np
from torch import nn
from fedml_api.distributed.fedavg.utils import transform_list_to_tensor
from fedml_core.robustness.robust_aggregation import RobustAggregator, is_weight_param
def test(model, device, test_loader, criterion, mode... |
fd79c640580f66560f7fe053a00a8fa2a3ad4c880aa06fe7fa116f67145acbe0 | Python | 12,797 | 357 | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import tempfile
import warnings
from collections import OrderedDict, defaultdict
import json_tricks as json
import numpy as np
from mmcv import Config, deprecated_api_warning
from xtcocotools.cocoeval import COCOeval
from ....core.post_processing i... |
381e6ea3f6110c07b1c906e0426b4d2d6f64433e8d944701ff7da45de2de5e80 | Python | 12,818 | 323 | import torch
from torch import nn
from pl_bolts.losses.self_supervised_learning import nt_xent_loss
class NT_Xent_Loss(nn.Module):
def __init__(self, temperature: float) -> None:
"""
Initializes NT Xent Loss (SimCLR).
Args:
temperature (float): Distillation temperature.
... |
4ae91755fdd428835b5ba5953def038119a9f65c256de9b88fd08a7c95c98f3a | Python | 12,852 | 285 | import numpy as np
def weighted_component_reformat(U, V, K, indices, W):
""" Reconstruct A Denoised Movie
Parameter:
U: decomposed spatial matrix
V: decomposed temporal matrix
K:
indices:
W: weighting component matrix
Return:
U_full: expanded spatial compon... |
e3af076b4ce6f2af5dfc58c19df7c44c47e0e04efc5b1a06334d15bf68c97e1d | Python | 12,858 | 325 | import sys
import argparse
import numpy as np
import pysam
import util
import snptable
import tables
import os
def write_results(out_f, chrom_name, snp_tab, ref_matches,
alt_matches, oth_matches, geno_sample):
haps = None
has_haps = False
if geno_sample:
# get index for t... |
02ec129977a8ddec89883177583334d90d11e7d107da870498d848aa0eb571c4 | Python | 12,870 | 419 | #merge erds output
import os
import sys
import sys
from optparse import OptionParser
import functions
#hard coded cutoffs
GAP_LEN_CUTOFF = 70
GAP_CUTOFF = 90
CNV_CUTOFF = 30
LEN_CUTOFF = 70
RATIO_CUTOFF = 10
header = ["#sample","CHROM","START","END","SVTYPE","SIZE","FILTER","SAMPLE|REFCN","SAMPLE|CN","IMPRECISE","SVL... |
cb878dd57d6d5eabe6e2f502b25039ff70a400f8a768df8e23aa923ecb5383d2 | Python | 12,876 | 274 | import tensorflow as tf
import numpy as np
import jax.numpy as jnp
from einshape import jax_einshape as einshape
from pprint import pprint
tf.config.set_visible_devices([], device_type='GPU')
import sys
sys.path.append('..')
import utils
from absl import flags
FLAGS = flags.FLAGS
def serialize_element(equation, capti... |
33d6456378c98c515799b736d7967364cd7b52f271ae9899c2f5234b81f7911f | Python | 12,877 | 339 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.cnn import (build_conv_layer, build_norm_layer, build_upsample_layer,
constant_init, normal_init)
from mmpose.core.evaluation import pose_pck_accuracy
from mmpose.core.post_processing import flip_back
fro... |
bf222b0ac498dcfc2785d5d65a61b5a53b6173b2e15ddc5954d0ed56da0ba7f4 | Python | 12,879 | 363 | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import tempfile
import warnings
from collections import OrderedDict, defaultdict
import json_tricks as json
import numpy as np
from mmcv import Config, deprecated_api_warning
from xtcocotools.cocoeval import COCOeval
from ....core.post_processing i... |
3b8b3d7eb3a2e859ff1e8e5d499ec0d511e14311400d35211d42cf29c898ad84 | Python | 12,898 | 351 | """Genetic decoding using abagen."""
import tempfile
from contextlib import contextmanager
from pathlib import Path
from threading import RLock
from typing import Optional, Sequence, Union
import abagen.images
import nibabel as nib
import numpy as np
import pandas as pd
from abagen import check_atlas, get_expression_... |
5958c262b0c2d0d9744bac0e4010f7e43b6124476c8fb617963c1b69deaaa3d3 | Python | 12,904 | 202 | from Classes.Menu import MenuBase, ImageSetDropdown, ImageSetItem, dp
from kivy.uix.button import Button
from kivy.uix.label import Label
from kivy.uix.dropdown import DropDown
from kivy.uix.checkbox import CheckBox
class ConfigureScreen(MenuBase):
def __init__(self, **kwargs):
super(ConfigureScreen, self)... |
6ab2d350f2edfe55958d30a5013227478bdb1021616a30a5ee2ca1f0a9c57325 | Python | 12,913 | 359 | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import tempfile
import warnings
from collections import OrderedDict, defaultdict
import json_tricks as json
import numpy as np
from mmcv import Config, deprecated_api_warning
from xtcocotools.cocoeval import COCOeval
from ....core.post_processing i... |
d258d725c73be3c83be99aa1328b011953a2e84623b68e79398bbd9fb965190b | Python | 12,915 | 196 |
"""Train a predictive coding network.
PyTorch implementation of a Hebbian Predictive Coding network described in Brucklacher, Bohte et al., 2022.
Please cite: https://www.biorxiv.org/content/10.1101/2022.07.18.500392v2
Code author: Matthias Brucklacher (UvA Amsterdam).
"""
import argparse
from during_run_analysis.m... |
cef9ea31541b0eb60e7deab900f95992aa82179f48c2da1fa2d25068ffb7d0db | Python | 12,943 | 322 | import sys
import numpy as np
import numpy.typing as npt
from genomad import sequence, utils
from genomad._paths import GenomadOutputs
def branch_attention(
w: npt.NDArray[np.float64],
b1: npt.NDArray[np.float64],
b2: npt.NDArray[np.float64],
temperature: float = 2,
):
w_1 = np.array(
[[... |
5574b6f98f79f6fd42c2398f78e3e5f92a4a6ca41920001b03bbe60a379e60b9 | Python | 12,997 | 308 |
import pickle
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import matplotlib.gridspec as gridspec
import jax
from jax.config import config
import tensorflow as tf
import os
os.environ['XLA_PYTHON_CLIENT_PREALLOCATE'] = 'false'
tf.config.set_visible_devices([], device_type='GP... |
f0cf08bdf31206d7757182fb054986b7a0b8c292b3548393468bbf3104383fb8 | Python | 13,041 | 352 | import torch
import os, sys
import glob
from scipy import interpolate
import pandas as pd
import numpy as np
from torchviz import make_dot
from tqdm import tqdm
from torch.utils.data import DataLoader
from sksurv.metrics import concordance_index_censored, integrated_brier_score
from torch.optim import Adam
from weibull... |
9de4aa650e334b51b27460c2edfc2da3767ea10a8e265eb6caf1b2a03ddff37e | Python | 13,042 | 296 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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://w... |
0152a2096aae05a3e62b59445e22e552d0740a42276c2119c34e6bb0aeffaace | Python | 13,058 | 313 | """
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_s... |
269030a98997ae3802c9993c35fb3f8182522fe65c6449a95b40ed5ea22450fb | Python | 13,072 | 406 | """File IO for daart package."""
from pathlib import Path
import csv
import numpy as np
import os
import pickle
from typing import List, Optional, Union
from typeguard import typechecked
import yaml
__all__ = [
'get_subdirs',
'get_expt_dir',
'get_model_dir',
'get_model_params',
'find_experiment'... |
b5fe1fa671dfbd22233614f6f592ff1a2760f43ec94667282c674b636e11ac22 | Python | 13,078 | 253 | import argparse
from my_tools import *
import matplotlib.pyplot as plt
from matplotlib import rcParams, cycler
rcParams.update({'font.size': 17,'font.family':'STIXGeneral'})
def cherry_colors ():
col = plt.get_cmap('tab20')
col = list(col.colors)
col[0::2]+col[1::2]
colors = np.asarray([list(el) + [1.... |
553e0ee39e746a47aaf9994a04f2899c85e33d57ea8d12d71339ddbff32d2221 | Python | 13,089 | 302 | import pickle
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import matplotlib.gridspec as gridspec
from absl import app, flags, logging
import sys
sys.path.append('../')
from jax.config import config
import tensorflow as tf
import os
os.environ['XLA_PYTHON_CLIENT_PREALLOCATE']... |
12277db0618abf9b47b0025fb0433e266d20906bc24f30c889bfa37e4822b34b | Python | 13,095 | 414 | # SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source... |
f42fcca3ef0187617ce24fd56fdd75a9fb275a1510ecbf8962aee289ade56a4b | Python | 13,105 | 370 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Tomoki Hayashi
# MIT License (https://opensource.org/licenses/MIT)
"""Decode with trained Parallel WaveGAN Generator."""
import argparse
import logging
import os
import time
import numpy as np
import soundfile as sf
import torch
import yaml
from tqdm ... |
bb7f62bcd832557163603905b4ef495122a44493bd1a3d77a52234d8a140250e | Python | 13,107 | 357 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Jul 8 14:47:21 2021
@author: bariskuru
"""
import numpy as np
import copy
def _spike_counter(spike_times, bin_size_ms=100, dur_ms=2000):
n_bins = int(dur_ms/bin_size_ms)
n_cells = len(spike_times)
counts = np.zeros((n_cells, n_bins))
... |
a86aea9681b97a170f05a62efe9f05689134f49f05af624f094c64dbe312b6a9 | Python | 13,139 | 361 | from collections import namedtuple
from copy import deepcopy
import numpy as np
from sklearn.svm import SVC, SVR
from tpot.config.classifier import classifier_config_dict
from tpot.config.regressor import regressor_config_dict
def get_grid(task, model):
"""A general function to obtain a grid for specific task and... |
fef5d3ff0fddd6778ecf70e3e1adc97d70888338f211ddb7d65d368a81e4305f | Python | 13,150 | 409 | #!/bin/env python
#
# Copyright 2013-14 Graham McVicker and Bryce van de Geijn
#
# 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 re... |
672a65945bc3ad3a4925dcc8824de1521ea46602a762531e66d1252b82cf33cc | Python | 13,154 | 361 | # 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)
import h5py
import numpy as np
import torch as pt
from torch_geometric.data import Data, Dataset, download_url, extract... |
a287c285485f0373d0738204ce57635f29583092bc79f42d9e3bc52430b9fbb9 | Python | 13,157 | 365 | # Copyright (c) OpenMMLab. All rights reserved.
import math
from typing import Sequence
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import build_conv_layer, build_norm_layer
from mmcv.runner.base_module import BaseModule
from mmcv.utils import to_2tuple
def nlc_to_nchw(x, hw_shape):
"""Co... |
66ad51fa47534fb424be56bc5c8121d290c934d11b43f4896576889a97788776 | Python | 13,161 | 370 | # Copyright (c) OpenMMLab. All rights reserved.
"""Optimize anchor settings on a specific dataset.
This script provides two method to optimize YOLO anchors including k-means
anchor cluster and differential evolution. You can use ``--algorithm k-means``
and ``--algorithm differential_evolution`` to switch two method.
... |
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