sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
d0dd8875b4a81723d43869375fc838fed1058990c24eb7e4cd4386c33534c8bd | Python | 13,810 | 314 | #!/usr/bin/env python3
"""Install / switch / verify a CARLA Leaderboard stack at a chosen version.
Subcommands
detect which leaderboard, scenario_runner and CARLA are present (read-only)
plan print the exact commands for a target version (read-only)
install clone or switch both repos, then p... |
12327a33b694dad250440910aa8b7a2027560dc0b9593d0549b3d87cd1192e2d | Python | 13,813 | 385 | #!/usr/bin/python
"""PyMOL plugin that provides show_contacts command and GUI
for highlighting good and bad polar contacts. Factored out of
clustermols by Matthew Baumgartner.
The advantage of this package is it requires many fewer dependencies.
"""
import os
import sys
from pymol import cmd
DEBUG = 1
def show_c... |
42258e18cef5fb033e63f6e1a06c2897432c095a7177606ac6bb1119f5f2c856 | Python | 13,813 | 329 | # -*- coding: utf-8 -*-
# File : batchnorm.py
# Author : Jiayuan Mao
# Email : maojiayuan@gmail.com
# Date : 27/01/2018
#
# This file is part of Synchronized-BatchNorm-PyTorch.
# https://github.com/vacancy/Synchronized-BatchNorm-PyTorch
# Distributed under MIT License.
import collections
import torch
import tor... |
9fede157785de280f7df31cccd0b6d38a7e8d1ed378462a0905a974dfe33942c | Python | 13,825 | 425 | """Data-specific colormaps"""
from itertools import cycle
import logging
from math import ceil
from numbers import Real
# colormath starts out at 0; needs to be set before init
logger = logging.getLogger('colormath.color_conversions')
if logger.level == 0: # otherwise it was probably set by user (DEBUG=10)
logger... |
df1e2e976dd89ffd66fbc9422cbfe3c92cac9ae29f24e6959ab383e41035cb3b | Python | 13,830 | 409 | import tensorflow as tf
from typing import List, Tuple, Union
from .affine_transformation import AffineTransform
PI = 3.14159265359
#-------------------------------------------------------------------------
class DiffAug(tf.keras.layers.Layer):
""" DiffAug class for differentiable augmentation
Paper: h... |
814a0d1a91d557445e4cf4318a1ffe605279dc19e09ba809a1552b0d28e9a92e | Python | 13,843 | 329 | import time
import os
from sklearn import metrics
import numpy as np
from IPython.core.debugger import set_trace
from sklearn.metrics import accuracy_score, roc_auc_score
# Apply mask to input_feat
def mask_input_feat(input_feat, mask):
mymask = np.where(np.array(mask) == 0.0)[0]
return np.delete(input_feat, m... |
74adc6ed4773a7aa6857f2213396fb9b48b154e001006a31fed26c5221b1d5b5 | Python | 13,850 | 363 | # Copyright 2020 Google Research. 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 applicable law... |
566d0b04f6fe3e0a572a190da6d3812bc34ef3dc7e21380406f5a6b5d1b1a20f | Python | 13,855 | 390 | import nibabel as nib
import os
import os.path as op
from time import time
import numpy as np
import pandas as pd
import logging
import pimms
from AFQ.tasks.decorators import as_file
from AFQ.tasks.utils import get_fname, with_name, str_to_desc
from AFQ.recognition.recognize import recognize
from AFQ.utils.path impor... |
e9488bcfe54199ef0b654495f9cee5e781bbde7485ea978d5a7cf4542b538af4 | Python | 13,863 | 309 | # Copyright 2020 Google Research. 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 applicable law... |
58d19e86e3ac11999beab66bb493e578325ee7e0d62df140ab615e17a7e701b9 | Python | 13,865 | 241 | ## aen_attack.py -- attack a network optimizing elastic-net distance with an en decision rule
## when autoencoder loss is applied
##
## Copyright (C) 2018, IBM Corp
## Chun-Chen Tu <timtu@umich.edu>
## PaiShun Ting <paishun@umich.edu>
## ... |
55814f79082ea81bebd86c20f96598d9d815fb64604fe51cf227e828ebb10e41 | Python | 13,888 | 397 | #!/usr/bin/env python
"""
mask.py -- apply binary masks to an SPT movie
"""
import os
import sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.path import Path
from scipy import interpolate
from scipy.spatial import distance_matrix
from tqdm import tqdm
class MaskInterp... |
7c14f4fd534ddd9199e8e12d4207a948c3aa1ca20046cde7ac7b89bc7aef7062 | Python | 13,893 | 401 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon May 3 13:23:59 2021
@author: th
"""
import torch
from torch.nn import ReLU, Linear, Softmax, SmoothL1Loss, Tanh, LeakyReLU
from torch_geometric.nn import GCNConv, global_max_pool, global_mean_pool, SGConv, SAGEConv, GATConv, FastRGCNConv, GraphConv
i... |
0b0d7adc406d8defc40132cbb1880ad8cc5301228bafdc4d27eebabe1208b186 | Python | 13,896 | 362 | """Test mne interaction"""
import os
import numpy as np
from numpy.testing import assert_array_equal, assert_allclose
import mne
from nibabel.freesurfer import read_annot
import pytest
from eelbrain import (
datasets, load, testnd,
Dataset, Factor,
concatenate, labels_from_clusters, morph_source_space, se... |
0674554a1412109618a241a4fdd70090367a6bb9bde7a41316635e6b3979620b | Python | 13,897 | 367 | """Label segments with language and speaker by matching original transcript to CTM."""
from __future__ import annotations # for difflib.SequenceMatcher type annotation
import difflib
from collections import deque
from collections import namedtuple
from itertools import islice
from typing import Any
from typing import... |
aee01f2f6fcd775e68994ee6583e468623c9845071b9072eafd4526140ce5bdf | Python | 13,904 | 430 | import torch
from torchvision import transforms
import cv2
import numpy as np
import types
from numpy import random
def intersect(box_a, box_b):
max_xy = np.minimum(box_a[:, 2:], box_b[2:])
min_xy = np.maximum(box_a[:, :2], box_b[:2])
inter = np.clip((max_xy - min_xy), a_min=0, a_max=np.inf)
return in... |
cc99b4a0c7bbab0ed20405dcc24f5c090b04a16af00a0b1af80a8a90e39ec0cd | Python | 13,905 | 368 | #!/usr/bin/env python3
"""
File: correlate_ct_fractions_to_pcs.py
Created: 2021/02/02
Last Changed:
Author: M.Vochteloo
Copyright (C) 2020 M.Vochteloo
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 S... |
9d1c8bc7bc3f1f6c36f26b53d68290bc1b2419800816efb75f10e2d24b071055 | Python | 13,926 | 433 | #%% Imports and file loading
from pathlib import Path
import glob
import json
from os import listdir
from operator import itemgetter
import pandas as pd
import networkx as nx
import numpy as np
from graspy.plot import gridplot
from src.data import load_networkx
# File locations
base_path = Path("./maggot_models/data/... |
e68d4dfad6a3458cdb601fcf6ac395bc37e247551e4d69bd8a2a598f3e39ebaa | Python | 13,934 | 430 | #!/usr/bin/env python
# Copyright (c) 2026 Computer Vision Center (CVC) at the Universitat Autonoma de
# Barcelona (UAB).
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""
Tester for vehicle physics utility for CARLA
Uses:
Basics scenearios ... |
199a1c55dd7e7e619586a8351312e92b208d7bbdb3e72f3afe1f9c2efcd7a795 | Python | 13,937 | 295 | # Copyright (c) 2026 Computer Vision Center (CVC) at the Universitat Autonoma de
# Barcelona (UAB).
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""Smoke tests for the carla.Road / carla.LaneSection / carla.Lane API.
These cover the load-bearin... |
5956158461773610ab5e01ff682591af4aab494c8c7d82c92e44f296f6cb2b45 | Python | 13,938 | 433 | #%% Imports and file loading
from pathlib import Path
import glob
import json
from os import listdir
from operator import itemgetter
import pandas as pd
import networkx as nx
import numpy as np
from graspy.plot import gridplot
from src.data import load_networkx
# File locations
base_path = Path("./maggot_models/data/... |
d46ba7e9fc7b596e5e7878f4ee07b53f5883877a603c40e0d348a597bb5c87aa | Python | 13,939 | 441 | import logging
from abc import ABC
from dataclasses import dataclass, field
from typing import Dict, List, Iterable, Tuple, Optional, Any, Iterator
from oaklib.interfaces.ontology_interface import OntologyInterface
from oaklib.types import CURIE, URI, PRED_CURIE, SUBSET_CURIE
from oaklib.datamodels.vocabulary import I... |
aa3c50238c17810557704e5ca8f68b0674b9ba7e4795dc1919533224d8b7b012 | Python | 13,941 | 378 | # Copyright (c) 2026 Computer Vision Center (CVC) at the Universitat Autonoma de
# Barcelona (UAB).
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
from . import SmokeTest
import carla
import time
import numpy as np
import filecmp
import shutil
im... |
3d81bdc38babfe9599dfcc87b19862bc0d0b4f00deedf96814a03f915b2b2336 | Python | 13,942 | 506 | #%% Imports and file loading
import glob
import json
import pprint
import sys
from operator import itemgetter
from os import listdir
from pathlib import Path
import networkx as nx
import numpy as np
import pandas as pd
import pymaid
from graspy.plot import gridplot
from src.data import load_networkx
from src.pymaid i... |
bd3092688929d30a5bd42a98d89bdb032f9a8631a4a77617815c88b91549ff67 | Python | 13,946 | 319 | # Copyright 2020-2021 Huawei Technologies Co., Ltd
#
# 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 agre... |
e70e62731be6870a4d572be10676d4e30c63f0598d4aa13baed34017147c7b81 | Python | 13,948 | 352 | # Copyright (c) # Copyright (c) 2018-2020 CVC.
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
""" This module contains a local planner to perform low-level waypoint following based on PID controllers. """
from enum import IntEnum
from collections... |
2808735b961a618b538d62c373a742cabdb49b8c0b24c0847eb366d816620c42 | Python | 13,960 | 325 | # coding=utf-8
# Copyright 2020 The Google Research Authors.
#
# 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 applicab... |
1c44941d96cf6b15df75e548ea205fa7a9722c579fd4062984ee6df83f64f80e | Python | 13,963 | 302 | """Occlusion-aware obstacle visibility: a z-buffer test against the captured depth AOVs.
Why
---
NVIDIA's RDS-HQ obstacle tracks come from lidar auto-labelling, so a car parked behind a
building simply has no label, while a car half-hidden behind another car usually still has
one. The exporter's ground truth is the s... |
43d10a94f73b9df1b8b124bcf5d395ecbb669cd18cb37a5270798b301a710f5e | Python | 13,980 | 353 | from math import sqrt
from zlib import crc32
import tarfile
import urllib
import numpy as np
import pandas as pd
import os
import matplotlib.pyplot as plt
import category_encoders as ce
from sklearn.model_selection import StratifiedShuffleSplit
from sklearn.ensemble import RandomForestClassifier
from sklearn... |
844019d4471310cb9aaee03388b579bef284df4fafda05c22e98d734ed335542 | Python | 13,990 | 325 | #!/usr/bin/env python3
"""Install / switch / verify a ScenarioRunner checkout for the CARLA in use.
Subcommands
detect what CARLA and what scenario_runner are present (read-only)
plan recommend a branch and print the exact commands (read-only)
install clone or checkout the branch, then pip install r... |
7659d0e33840d2a7f17aa61375874773f92e36a735b17d8b0878abf56004e80b | Python | 13,995 | 316 | # Copyright 2020-2021 Huawei Technologies Co., Ltd
#
# 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 agre... |
a8e3b299836234250e82371a2d2984a8af6bffc969d3a3acd46eccbae8db6586 | Python | 14,000 | 304 | import numpy as np
#import matplotlib
#import matplotlib.pyplot as plt
#import seaborn as sns
import networkx as nx
import pandas as pd
import random
import string
import scipy.stats
import network_prop
import sys
#import visJS2jupyter.visJS_module
#import visJS2jupyter.visualizations
# for parallel processing
#from j... |
0f13fb99a32bb5f69782e8b91564841735dbf4fcf8fbcf215d29a93e2823362c | Python | 14,007 | 336 | #!/usr/bin/env python
# Copyright 2020 Ivan Medennikov, Maxim Korenevsky (STC-innovations Ltd)
# Apache 2.0.
"""This script prepares overlapped 4-speaker dense targets for TS-VAD training
using segments and VAD alignment of kinect and worn utterances
(VAD alignment from worn utterances is more reliable than ... |
9d1e5ee07cf1dcea4bcfb6728507200888cafd87a1afff6fff8ea70becffe2de | Python | 14,010 | 266 | #!/usr/bin/env python3.9
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 25 10:03:59 2021
@author: paulmueller
Takes a configuration file as first argument and datafiles as the others to calculate autocorrelation functions and
crosscorrelation functions from the data. Then calculates lrtc and lrsc measures from these.
"... |
fcbaad786dfe67ed5ac08f32dfad1426acfefc6d7d4676136dbe58f9dac9ab1a | Python | 14,026 | 392 | import torch
import torch.nn as nn
import torch.nn.functional as F
__all__ = ["ESPNet_Encoder", "ESPNet"]
class ESPNet(nn.Module):
'''
This class defines the ESPNet network
'''
def __init__(self, classes=2, aux=True, p=2, q=8, encoderFile=None):
'''
:param classes: number of classes... |
37f3cfaf7962f560164a0861aa3e4dde8cc8480d3838fc2e7006d6f0d40295a7 | Python | 14,027 | 489 | """
interfaces
Created by: Martin Sicho
On: 01.06.22, 11:29
"""
from abc import ABC, abstractmethod
from copy import deepcopy
import torch
from torch import nn
from drugex import DEFAULT_GPUS, DEFAULT_DEVICE
from drugex.utils import gpu_non_dominated_sort, cpu_non_dominated_sort
class ModelEvaluator(ABC):
"""
... |
edbee30f1442623e2012cf75a56299644ebb6e417796abd32d05e7010a69a911 | Python | 14,028 | 358 | # -*- coding: utf-8 -*-
import logging
from os.path import isfile, join
from os import listdir
import numpy as np
import pandas as pd
import datetime as dt
from skimage.util import view_as_windows
from PIL import Image
import itertools as it
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from math import c... |
ffd0974d171e3ad001fd3e6960fa2b5e0e5b5e397c4606d4f30f43d3c3232866 | Python | 14,034 | 329 | #%%
import os
import sys
try:
os.chdir('/Volumes/GoogleDrive/My Drive/python_code/connectome_tools/')
print(os.getcwd())
except:
pass
from pymaid_creds import url, name, password, token
import pymaid
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
# allows text... |
bd093c3cf734b615610d802ed4571cb0ccb0da10cdc060777b676d5bb21322fd | Python | 14,036 | 304 | import numpy as np
import torch
import os
from torch.autograd import Variable
from util.image_pool import ImagePool
from .base_model import BaseModel
from . import networks
class Pix2PixHDModel(BaseModel):
def name(self):
return 'Pix2PixHDModel'
def init_loss_filter(self, use_gan_feat_loss, use_vg... |
b6408c73e1b7342e2bfdd7ce35dbdc769ff50946f76729b3220a70270ad902ab | Python | 14,037 | 648 | # %% [markdown]
# # THE MIND OF A MAGGOT
# %% [markdown]
# ## Imports
import os
import time
import warnings
import colorcet as cc
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.transforms as transforms
import numpy as np
import pandas as pd
import seaborn as sns
from anytree import LevelOr... |
c5f29894cfcefb9071ac215545d00639020a717d018cba146c403553edaf62f2 | Python | 14,039 | 362 | import logging
from abc import ABC
from typing import Collection, Dict, Iterable, List, Optional, Union
from deprecation import deprecated
from sssom_schema import Mapping
from oaklib.datamodels.mapping_cluster_datamodel import MappingCluster
from oaklib.interfaces.basic_ontology_interface import BasicOntologyInterfa... |
8e721decdddb3622ca29d95f858f316c3623d518c84853b42db07860ef30ec69 | Python | 14,046 | 308 | #%%
import os
import sys
try:
os.chdir('/Volumes/GoogleDrive/My Drive/python_code/connectome_tools/')
sys.path.append('/Volumes/GoogleDrive/My Drive/python_code/maggot_models/')
sys.path.append('/Volumes/GoogleDrive/My Drive/python_code/connectome_tools/')
except:
pass
import pymaid as pymaid
from pyma... |
77629a31094eb06454f44a62764f92cf4c52643c1523e240fe55bf2ce18c7935 | Python | 14,055 | 396 | import logging
import tempfile
import os
import torch
from collections import OrderedDict
from tqdm import tqdm
from maskrcnn_benchmark.modeling.roi_heads.mask_head.inference import Masker
from maskrcnn_benchmark.structures.bounding_box import BoxList
from maskrcnn_benchmark.structures.boxlist_ops import boxlist_iou
... |
0b82b0165d39ad27cfb7fbf0478b5ced78dab5911c8e70a8f6357e494263135a | Python | 14,057 | 351 | import os
import nibabel as nib
import numpy as np
from bruker2nifti._utils import (
bruker_read_files,
eliminate_consecutive_duplicates,
data_corrector,
compute_affine_from_visu_pars,
compute_resolution_from_visu_pars,
)
def get_list_scans(start_path, print_structure=True):
"""
Given a p... |
6d322739876aa0f56ab685b3ccad54794c4d0757eee3d4831dd0363cf42f0501 | Python | 14,058 | 465 | import math
import torch
from torch import autograd
from torch.nn import functional as F
import numpy as np
from model.stylegan2_pytorch.distributed import reduce_sum
from model.stylegan2_pytorch.op import upfirdn2d
class AdaptiveAugment:
def __init__(self, ada_aug_target, ada_aug_len, update_every,... |
2726cbb06dc760cbb81f385cf2228fca286506484c368ff49ebf2fa8e668953b | Python | 14,066 | 508 | #%%
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from sklearn.cluster import AgglomerativeClustering, KMeans
from sklearn.metrics import pairwise_distances
from graspy.embed import AdjacencySpectralEmbed
from graspy.models import DCSBMEstimator, ... |
329900799cd37acbd12377ddb0da21231bcc1f820b11447c4f9f9121b1822908 | Python | 14,066 | 319 | # Copyright 2020-21 Huawei Technologies Co., Ltd
#
# 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... |
ba7a012208dc730f050508173ca19982cb52a848aead4702faa5fc9b798da28b | Python | 14,073 | 371 | import os
import numpy as np
from deepsleep.sleep_stage import print_n_samples_each_class
from deepsleep.utils import get_balance_class_oversample
import re
class NonSeqDataLoader(object):
def __init__(self, data_dir, n_folds, fold_idx):
self.data_dir = data_dir
self.n_folds = n_... |
01003815dce83679e614be50bc964b327ee3f1c0d5c16ce81ae533f86eff5802 | Python | 14,082 | 400 | import numpy as np
import torch
import argparse
from typing import Dict
class Optimiser:
"""custom optimiser for SGD + Hebbian training updates"""
def __init__(self, args: argparse.Namespace):
"""Constructor for optimiser
Args:
args (argparse.Namespace): training params specifie... |
70139c67e5a118699053af806ee590562ebfb134dd4ae0ea7a316e918201fed1 | Python | 14,083 | 338 | #!/usr/bin/env python3
"""
File: add_ie_results_to_mr_table.py
Created: 2021/02/026
Last Changed:
Author: M.Vochteloo
Copyright (C) 2020 M.Vochteloo
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 Sof... |
b4e754625dacb073d6d55e2b956c627fe96d0cb970f585792e139b8a74e14c33 | Python | 14,094 | 271 | #!/usr/bin/env python3
"""Condition Cosmos on a NuRec scene: by the world map, by the neural RGB, or by both.
A NuRec artifact is twenty seconds of real driving reconstructed as a Gaussian splat. This
demo turns one into a Cosmos clip package and submits it three different ways:
``--mode wm``
**The world model o... |
f48947483bc7c6d0b3d31afa00add4c51838c544dcdb543010c99f643375f203 | Python | 14,094 | 438 | import math
import torch
import torch.nn as nn
from mmdet.core import bbox_overlaps
from ..builder import LOSSES
from .utils import weighted_loss
@weighted_loss
def iou_loss(pred, target, eps=1e-6):
"""IoU loss.
Computing the IoU loss between a set of predicted bboxes and target bboxes.
The loss is cal... |
2185eda6e792aebd3c1e904dbb2d7b030364ab89feb03e52664cd0caba648910 | Python | 14,108 | 397 | 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
@PIPELINES.register_module()
class LoadImageFromFile(object):
"""Load an image from file.
Required keys are "img_prefix" and "img_info" ... |
d4ab09552508b1ee0f7cfc5c4dc856570665bb847b395a8653544862f23743f8 | Python | 14,110 | 335 | # Copyright 2022 Huawei Technologies Co., Ltd
#
# 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 to... |
579378f2de10178dca5ffdfa1a40b7c9e2a61bc1703033ddb89f689120b14c0e | Python | 14,116 | 310 | """ this code establishes the real-time port b/t FDTD and Python to enable state and reward passes
for optimization of photonic crystals by RL. NOEL, Renjie Li, June 2021
"""
import numpy as np
import random
import gym
import sys
import os
sys.path.append("C:\\Program Files\\Lumerical\\v202\\api\\python\\... |
0fcb97b0cb3294a5df97bb59d3374fced4ae21ffbc934e25d2110022405e3c72 | Python | 14,118 | 379 | #!/usr/bin/env python
"""This is a function that would convert trajectories from the old format "blockXXX.dat" + "SMCXXX.dat" to the new
HDF5-based format.
This glbal docstring has FAQ, general motivation, and examples. To figure out how to use the function, either browse
to the function below and read the click decor... |
95106e387d5b4b43ee9c6a9236550eb27c0b849743a3edacef6b796d63f5e6f8 | Python | 14,120 | 390 | # SPDX-FileCopyrightText: © 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# SPDX-License-Identifier: MIT
"""
NUREC Scenario Management Module
This module provides classes and functions for loading and managing NUREC scenarios
from USDZ files. It handles the extraction and processing of trajectory data,... |
61e6b14035be336f91073156f02a7c47548ca36cbb2e96bd6eef3e084178c347 | Python | 14,125 | 426 | import sys
import os
import re
import re
import csv
import json
from collections import OrderedDict
import confusion_matrix
def read_csv(path):
cases = []
headers = []
with open(path, 'rb') as csvfile:
reader = csv.reader(csvfile, delimiter=',', quotechar='"')
for i, row in enumerate(reader... |
58874463389f256bfd15bc826ae573d06b72f9cf7dc97e9d1efddb64a8e1fade | Python | 14,131 | 246 | #%%
import os
import sys
try:
os.chdir('/Volumes/GoogleDrive/My Drive/python_code/connectome_tools/')
sys.path.append('/Volumes/GoogleDrive/My Drive/python_code/maggot_models/')
sys.path.append('/Volumes/GoogleDrive/My Drive/python_code/connectome_tools/')
except:
pass
from pymaid_creds import url, nam... |
6a4228d002dbcc8614d817f966de4fa48fda6b99437178d8f826873625ca13d0 | Python | 14,140 | 336 | import math
import copy
import torch
import networkx as nx
from functools import partial
from collections import Counter
from torch_geometric.data import Batch, Data
from torch_geometric.utils import to_networkx
from typing import Callable
from torch_geometric.utils.num_nodes import maybe_num_nodes
from .shapley import... |
18100f6d271ac24270b8a7c29efe95c6663ff4c90e4a12b5c59926e1b28b100d | Python | 14,141 | 376 | #!/usr/bin/env python3
"""Light/weather suite: L6 L7 L8 L9 L10, W2 W3, PW1 PW2.
Run against a live CARLA UE5 server on Town10HD_Opt. Each test prints
PASS/FAIL; exit code = number of failures. L10 reloads the world — always last.
"""
import argparse
import time
import numpy as np
from PIL import Image
import carla
O... |
b5e66b3bcc23ff6fb342302a474ce6f9ae7cb8be624c735456e818fb51ab98f2 | Python | 14,141 | 470 | import torch
import numpy as np
import pickle
from scipy.ndimage import gaussian_filter1d
import math as mh
from util.datasets import LabelFunction
from util.datasets.mouse_v1.preprocess import *
FRAME_WIDTH_TOP = 1024
FRAME_HEIGHT_TOP = 570
# Our dataset has 21 frames.
# TODO: Make this more flexible.
MIDDLE_INDEX... |
5b76c0d48cde37cfdfcab76766e96115f402056e2765d94c3f7d5674aaf7f2db | Python | 14,155 | 422 | import nibabel as nib
import numpy as np
import logging
from time import time
import os.path as op
from AFQ.definitions.utils import Definition, find_file
from dipy.align import syn_registration, affine_registration
import AFQ.registration as reg
from AFQ.utils.path import write_json
from AFQ.tasks.utils import get_fn... |
ae4c4672e4c4df878d7598851899572201b325ba9457e9206f694ec489bd1209 | Python | 14,157 | 352 | import os
import time
import logging
# Tensorflow
import tensorflow as tf
import tensorflow_probability as tfp
from .util import scope_name
def layer(h, dim = None, fun = None, name = 'dense', l2_scale = 1e-50, l1_scale = 1e-50,
drop = None, batch_norm = None, custom = False, W = None, b = None... |
c5698fcc0621dd9e0e7dbac863f8cede362ee45508e909d25a99ed7ea3065c5e | Python | 14,158 | 318 | """
File: create_matrices.py
Created: 2020/10/08
Last Changed: 2020/10/13
Author: M.Vochteloo
Copyright (C) 2020 M.Vochteloo
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 ... |
4bfc2e48906505c9c7350af0064b55219c1e0a00ef9a252f30cdff8f8c0a3cec | Python | 14,161 | 405 | import argparse
import pandas
import os
import numpy as np
import matplotlib.pyplot as plt
import functools
from collections import Counter
import math
import random
def neighbors(W, i):
n = []
for k, e in enumerate(W[i]):
if e > 0:
for j in range(len(W)):
if j != k and W[j]... |
c43303786f4fd40ff5bf271e5d0a6d586b41fd4fae568b2163a2bcc4701e9d97 | Python | 14,177 | 303 | import numpy as np
import tensorflow as tf
from random import shuffle
import os
import glob
from scipy import spatial
from default_config.masif_opts import masif_opts
params = masif_opts["ligand"]
ligands = ["ADP", "COA", "FAD", "HEM", "NAD", "NAP", "SAM"]
# List all structures that have been preprocessed
precomputed_... |
8a0e1d929c4446cc346bf1845856c32c5e2a0a906279ea08b459ab66f096edd3 | Python | 14,199 | 523 | # %% [markdown]
# ##
import os
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from graspy.match import GraphMatch
from graspy.utils import pass_to_ranks
from src.data import load_metagraph
from src.io import savecsv, savefig
from src.utils import ... |
fe435fa9f9e6951a4d6b2a2d4afc54a2803a3b21e625c7814c353d06abee7552 | Python | 14,204 | 409 | from __future__ import annotations
import fnmatch
import logging
import os.path
import re
import time
from datetime import datetime, timedelta
from pathlib import Path
from appdirs import user_config_dir
from click import ParamType
from pystow.utils import base_from_gzip_name, name_from_url
from oaklib.datamodels.vo... |
49e9c6b209bdb0fc27df712e65f97cd57b431d041e0b960caca8415db9394570 | Python | 14,208 | 323 | # @author: Miroslav Kuchta
# This is taken from FEniCS_ii to keep the code base free of many depen-
# dencies
from src.fem.utils.make_mesh_cpp import make_mesh
from collections import defaultdict
from itertools import chain, permutations
import dolfin as df
import numpy as np
import operator
from IPython import embed
... |
e7059f9c13810469cd0b903be80adfbda7d99d1cba63017e57a86939d8bb5d6f | Python | 14,209 | 386 | """
Utility functions for working with dcm2niix output in the work/ folder
MIT License
Copyright (c) 2017-2022 Mike Tyszka
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, incl... |
5d838603f5b932d41372d1b0828a63a5ce9250026aee379c101e1a2e46d00654 | Python | 14,210 | 523 | # %% [markdown]
# ## The goal of this notebook:
# investigate regularization approaches, for now, just on the full graph
# these include
# - truncate high degree
# - truncate low degree
# - plus c
# - levina paper on row normalization
# - others?
# %% [markdown]
# ##
import os
import time
import wa... |
bf11778554f0fc736d04f2fad0dbd750e8f45e6836ac100ece705d9be7a4fb21 | Python | 14,211 | 407 | # Copyright 2020-2022 Huawei Technologies Co., Ltd
#
# 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 agre... |
9c66801eeb2735ec90eff6e71997e7b08dd83ef10e60a4cb79606c9f09bc5736 | Python | 14,213 | 281 | # Auto generated from lexical_index.yaml by pythongen.py version: 0.9.0
# Generation date: 2022-04-11T17:33:31
# Schema: lexical-index
#
# id: https://w3id.org/linkml/lexical_index
# description: A datamodel for representing a lexical index of an ontology. A lexical index is keyed by optionally
# normalize... |
b45426453401a176e6bcd93f369999807abb1c54d046dff680f7bc0fe07f8873 | Python | 14,215 | 346 | from typing import List, Union, Tuple
import numpy as np
from rdkit import Chem
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.batchnorm import _BatchNorm
from .mpn import MPN
from chemprop.args import TrainArgs
from chemprop.features import BatchMolGraph
from chemprop.nn_util... |
c11c9bd902ff2f7523eb70c4fb404e38db127d44a09fdf5731a5c7ee4f25fc82 | Python | 14,221 | 357 | from os.path import dirname, exists, join, relpath
import torch
from mmcv.runner import build_optimizer
from mmdet.core import BitmapMasks, PolygonMasks
def _get_config_directory():
"""Find the predefined detector config directory."""
try:
# Assume we are running in the source mmdetection repo
... |
cc4ed2730af87e9cdd638e9e1d8edfa10c20f1f76a90ebba6d43d30fa1e1579d | Python | 14,223 | 399 | #!/usr/bin/env python
# coding: utf-8
import sys
import time
import sklearn.metrics
from geometry.open3d_import import *
import numpy as np
import os
from alignment_utils_masif_search import compute_nn_score, rand_rotation_matrix, \
get_center_and_random_rotate, get_patch_geo, multidock, test_alignments, \
... |
a58c96836eb612b4f7264832d11e81d4ba173dd48b2b28ed5604e26db3e3e2a6 | Python | 14,241 | 333 | # Modified from https://github.com/facebookresearch/detectron2/blob/master/detectron2/data/datasets/cityscapes.py # noqa
# and https://github.com/mcordts/cityscapesScripts/blob/master/cityscapesscripts/evaluation/evalInstanceLevelSemanticLabeling.py # noqa
import glob
import os
import os.path as osp
import tempfile
i... |
e82e981e498b8f0f81aeceeb8fc38f587482a64c3dee1534e3a652133be22ca5 | Python | 14,241 | 341 | #!/usr/bin/env python
# Copyright (c) 2026 Computer Vision Center (CVC) at the Universitat Autonoma de
# Barcelona (UAB).
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""CARLA client script: spawns a checkerboard/ChArUco calibration target and
... |
8da76d9ea59e1516f1ca23349d3b502b981b4d529c73c84a2b6cd48a13e7c38a | Python | 14,246 | 322 | import tempfile
import torch
import torch.nn as nn
from drugex import DEFAULT_GPUS, DEFAULT_DEVICE
from drugex.data.fragments import GraphFragmentEncoder, FragmentCorpusEncoder
from drugex.data.processing import Standardization
from drugex.data.datasets import GraphFragDataSet
from drugex.logs import logger
from drug... |
2bff5f6ab17ef2b7869190640d2f8f27aeebd8c29c6c941c7fdc1a6df2ba319c | Python | 14,250 | 247 | # Auto generated from cross_ontology_diff.yaml by pythongen.py version: 0.9.0
# Generation date: 2022-05-29T22:40:51
# Schema: cross-ontology-diff
#
# id: https://w3id.org/linkml/cross_ontology_diff
# description: A datamodel for representing the results of relational diffs across a pair of ontologies connected
# ... |
52f3c069f95662a2be61b23a95952de9071a221ce4e819d977a3eadd4160e038 | Python | 14,256 | 416 | import pdb
import torch
import torch.nn as nn
import math
import torch.utils.model_zoo as model_zoo
torch.backends.cudnn.benchmark = True
BatchNorm = nn.BatchNorm2d
# __all__ = ['DRN', 'drn26', 'drn42', 'drn58']
webroot = 'https://tigress-web.princeton.edu/~fy/drn/models/'
model_urls = {
'resnet50': 'https:/... |
7ac6b0a936296cc4a531da5d18689e3619523aad242ab05b2868a05003413a2f | Python | 14,265 | 349 | import sys
sys.path.insert(0, '.')
import loadData as ld
import os
import os.path as osp
import torch
import numpy as np
import torch.backends.cudnn as cudnn
import transforms as myTransforms
import dataset as myDataLoader
import time
from argparse import ArgumentParser
from IOUEval import iouEval
import torch.optim.lr... |
c74d7f635a81720b56ccc4541d439f40bdbde9135a3cd60e09ff1af9a25ad36d | Python | 14,268 | 328 | #!/usr/bin/env python
# Copyright (c) 2026 Computer Vision Center (CVC) at the Universitat Autonoma de
# Barcelona (UAB).
#
# This work is licensed under the terms of the MIT license.
# For a copy, see <https://opensource.org/licenses/MIT>.
"""World-space straight-line test: a real straight edge, imaged through a
dis... |
24c448b5b1119d8f3e6c36b7740861722637f43f9187c3f2a3016acfcad39c5a | Python | 14,270 | 319 | # basic imports
import os
import pickle
import numpy as np
import matplotlib.pyplot as plt
def count_pairs(replays: list) -> (list, list, list):
'''
This function counts the number of forward, reverse and unordered replay pairs.
Parameters
----------
replays : A list... |
d8a094300fa2bc8469976ce735192fe518d94323fc564874339fe7a2e6f2ec19 | Python | 14,270 | 398 | #!/usr/bin/python
# System imports
import sys, os, re, math
import subprocess
import argparse
import numpy as np
import seaborn as sns
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.font_manager
from matplotlib.ticker import PercentFormatter
from matplotlib.ticker import Format... |
7671e08b7c1d4f119ddae3d3f0f9e2af0e384d356e6fb427e36e745aba7d73f7 | Python | 14,274 | 389 | import os
import numpy as np
import shutil
import torch
from time import time
import networkx as nx
from pdb2sql import interface
from .tools import BioWrappers, PSSM, BSA
from .Graph import Graph
class ResidueGraph(Graph):
def __init__(self, pdb=None, pssm=None,
contact_distance=8.5, internal... |
17e07b2dc432ffddfc729e90488f85432a611fcb80224428e042eec2720e0c54 | Python | 14,292 | 375 | import torch
from torch_geometric.nn import MessagePassing
from torch_geometric.utils import add_self_loops, degree, softmax
from torch_geometric.nn import global_add_pool, global_mean_pool, global_max_pool, GlobalAttention, Set2Set
import torch.nn.functional as F
from torch_scatter import scatter_add
from torch_geomet... |
2c3a37f02ba70519a0ad9f90ebee6524b8f6a92f6c5564ab6c9e91e51e02458a | Python | 14,297 | 345 | """
This module provides the RandomPositionsSampler class.
TODO: Currently, only works with sequences from `selene_sdk.sequences.Genome`.
We would like to generalize this to `selene_sdk.sequences.Sequence` if possible.
"""
from collections import namedtuple
import logging
import random
import numpy as np
from selen... |
e9a460d19bb8a937027a9a10c36af3cc9dcd6909093894a61df6ec28d66e3d99 | Python | 14,301 | 339 | import math
import torch
import functools
import torch.nn as nn
from torch.nn.modules.utils import _triple
import config as c
cuda = True if torch.cuda.is_available() else False
Tensor = torch.cuda.FloatTensor if cuda else torch.FloatTensor
class Discriminator(nn.Module):
def __init__(self, input_nc=2, dropou... |
9c4b471aabcfc958c3cc670d2a8cc845369a6ba3c03e2994ee1d95a8a97b8f7b | Python | 14,304 | 312 | # Copyright 2020 Huawei Technologies Co., Ltd
# 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 to in... |
d9a58360e2d9240858a622af038d25a94f25185de3e5ff1d155d572ccf01818a | Python | 14,322 | 404 | from collections import defaultdict
import pytorch_lightning as pl
from pytorch_lightning.metrics.regression import MeanAbsoluteError as MAE
from pytorch_lightning.metrics.regression import MeanSquaredError as MSE
from pytorch_lightning.metrics import F1
from pytorch_lightning.metrics import ExplainedVariance as EV
imp... |
0cd89a6af36fcc982f7721b6e9798197b50b36d8ca9f7afc134afd270fd7cf23 | Python | 14,329 | 380 | # Copyright 2021 Huawei Technologies Co., Ltd
#
# 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 to... |
a2580b02c4b0ceeba9a46e8eacf43c15a2ca5e18b5aea3f2a896c388e38d6468 | Python | 14,337 | 345 | # Author: Yoshimasa Kubo
# Date: 2020/03/09
# Updated: 2020/05/07
# Dataset: MNIST
# Purpose: Demonstration of network with predictive learning rule
import numpy as np
from keras.datasets import mnist
import torch
import os
from sklearn.preprocessing import OneHotEncoder
from sklearn import utils
... |
aefd267e65ecb5367a0468f7b82e94320b6dc84646bd56d6e103fb9e9807c84a | Python | 14,341 | 376 | from functools import reduce
from rl_analysis.util import rle, count_transitions
from typing import Sequence, Optional
import pandas as pd
import numpy as np
def normalize_df(
*args,
time_bins=[(0, 30)],
eps=0, # this is only added for division
baseline_smoothing=None,
outer_loop_key="target_syll... |
afd47ee14521a4180b19f608c294585402b77b7bce84b0f139ca8901733f66dc | Python | 14,343 | 329 | #!/usr/bin/env python3
"""Spawn and attach sensors to a CARLA actor, and destroy them.
Commands:
types list sensor blueprints
spawn --type camera.rgb [--attach-to hero | --parent-id N]
[--x 1.5 --y 0 --z 2.4 --pitch 0 --yaw 0 --roll 0]
[--attachment Rigid|Sp... |
8eaf28f4224bb2bcdffadbc0a06a3a81e5b74536bfa239054a0427bc974225f9 | Python | 14,345 | 386 | import pickle
from multiprocessing import Pool
import numpy as np
import pytest
import polychrom
import polychrom.polymer_analyses as polymer_analyses
import polychrom.starting_conformations
def test_calculate_contacts():
"""Test basic contact calculation"""
# Create a simple test case with known contacts
... |
0dbe46c62b99fb199cfc631db8d3f4012f6bd14c5aae15abdd8622c2c9394617 | Python | 14,354 | 383 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
##################### IMPORTS #######################
import os
import sys
from keras.models import model_from_json
from matplotlib import pyplot as plt
import numpy as np
from keras.callbacks import ModelCheckpoint
from rdkit.Chem.Draw import IPythonConsole
import os,... |
1fe5b0a935888694e4972416e1cfb3c6ab527bf987013baeaab95698095a27ff | Python | 14,356 | 391 | import glob
import json
import math
import re
import shutil
import subprocess
import sys
from os import remove
from os.path import isfile, join, split
import pytest
from phys2bids._version import get_versions
from phys2bids.phys2bids import phys2bids
def check_string(str_container, str_to_find, str_expected, is_num... |
6a13da0b0c78842a19ca2345f185b578edb1987a735b18575e696ea06bc07338 | Python | 14,365 | 354 | import sys
sys.path.insert(0, '.')
import loadData as ld
import os
import os.path as osp
import torch
import numpy as np
from torch.autograd import Variable
import torch.backends.cudnn as cudnn
import transforms as myTransforms
import dataset as myDataLoader
import time
from argparse import ArgumentParser
from IOUEval ... |
21619a0a130f4aa8bd13258220b5e14e6581e2a33e2a0aac055798b8cceebfb9 | Python | 14,366 | 356 | #!/usr/bin/env python3.9
# -*- coding: utf-8 -*-
import numpy as np
from iEEG_STC import utils
import pandas as pd
import glob
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import seaborn as sns
from scipy.stats import spearmanr
from scipy.optimize import curve_fit
from matplotlib.ticker imp... |
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