sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
2225d1cac2c9112e30c6c0182bebc8891163db11a6b4e9f0a50aa2e5e3c54be8 | Python | 1,679 | 45 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
"""
Utility functions minipulating the prediction layers
"""
from ..utils import cat
import torch
def permute_and_flatten(layer, N, A, C, H, W):
layer = layer.view(N, -1, C, H, W)
layer = layer.permute(0, 3, 4, 1, 2)
layer = layer.re... |
d6027a0da6b4a3c8fe861c38c4d6b848e18a9989e1f6456ea970885d566ac7a5 | Python | 1,679 | 51 | # 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... |
56b740168f67c73c636969875065926cad23fec31821d7af9e5e0b678bc00a49 | Python | 1,680 | 48 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
from . import transforms as T
def build_transforms(cfg, is_train=True):
if is_train:
if cfg.INPUT.MIN_SIZE_RANGE_TRAIN[0] == -1:
min_size = cfg.INPUT.MIN_SIZE_TRAIN
else:
assert len(cfg.INPUT.MIN_SIZE_R... |
cafef1d926caadb0d5991fc3109b2cfbb0c896dd0b8a3eda8d51ac0a5bb4c272 | Python | 1,680 | 51 | # Copyright (c) Open-MMLab. All rights reserved.
def list_from_file(filename, prefix='', offset=0, max_num=0):
"""Load a text file and parse the content as a list of strings.
Args:
filename (str): Filename.
prefix (str): The prefix to be inserted to the begining of each item.
offset (in... |
2796e675493e30eabb50b0f7b984a101bca940203b715928f802bb2b7dea6036 | Python | 1,683 | 53 | #!/usr/bin/env python3
# encoding: utf-8
# @Time : 2018/8/1 上午1:50
# @Author : yuchangqian
# @Contact : changqian_yu@163.com
# @File : lr_policy.py.py
from abc import ABCMeta, abstractmethod
class BaseLR():
__metaclass__ = ABCMeta
@abstractmethod
def get_lr(self, cur_iter): pass
... |
6c3701d677519b0d05cf8fcda96b51d59fc7b2f1558a6d6d846f909fa7fd3700 | Python | 1,683 | 42 | # 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... |
c32549da28121341dbfd2c0591fb40d22804f84b475634ed1ede2735f991e222 | Python | 1,683 | 39 | import numpy as np
import torch
def duplicate_randomly(pc, size):
""" Make up for the point loss due to conflictions in the projection process. """
loss_cnt = size - pc.shape[0]
if loss_cnt <= 0:
return pc
rand_indices = np.random.randint(0, pc.shape[0], size=loss_cnt)
dup = pc[r... |
d45a22fa8bfa1259b6c8318720f4f9238998c060810fc99d5b7d59db0264bced | Python | 1,683 | 58 | from typing import Any, List, Optional
from zencfg import ConfigBase
from .distributed import DistributedConfig
from .opt import OptimizationConfig, PatchingConfig
from .wandb import WandbConfig
from .models import ModelConfig
class BurgersDatasetConfig(ConfigBase):
folder: str = "neuralop/data/datasets/data/"
... |
eba5495134f0b8cbf4fea762166da2355b6135014b5e82eaa87b9b4d074d72b6 | Python | 1,684 | 37 | ####################################################################################################
# Copyright (c) 2019 - 2023, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of VessMorphoVis <https://github.com/BlueBrain/VessMorphoVis>
#
# This program is free ... |
2597850a250cc154ebb768f20ed777244b927446c6d47b892b065ab8988a2ec5 | Python | 1,686 | 59 | """
LAMMPS module global members:
.. data:: __version__
Numerical representation of the LAMMPS version this
module was taken from. Has the same format as the
result of :py:func:`lammps.version`.
"""
from .constants import *
from .core import *
from .data import *
# convert installed module string version ... |
9873bd0fc6f1e4731da78da3abf1c9919bf2471c3142c40a170252ffaae4f938 | Python | 1,686 | 65 | import argparse
import json
from grr.Tools import check_dict_fields
generate_models_argparser = argparse.ArgumentParser()
generate_models_argparser.add_argument(
'--mods', type=str, help='Pickled principal cell models.',
)
generate_models_argparser.add_argument(
'--sermods', type=str, help='Pickled 5-HT cell ... |
a94ae775b343aaea35b9b6c2e0cb20e427193022d7f063b4e9e2ef1d90e360ad | Python | 1,686 | 62 | import pandas as pd
import random
import pickle
import numpy as np
from sklearn.utils import resample
from sklearn.metrics import confusion_matrix, accuracy_score, f1_score, classification_report, matthews_corrcoef, balanced_accuracy_score
# dataset import
infile = open('../../data/final/top50.pickle','rb')
top50 = p... |
0e55487138baa9c7d94a989a0bbad2a8c046e78e5aa755c4d0372a8b2e5a3f74 | Python | 1,687 | 66 |
from numpy.lib.function_base import append
from torch.autograd import Variable
import torch, torchvision
import torch.nn as nn
from torchvision import transforms
import torchvision.models as models
from PIL import Image
import numpy as np
import os
import argparse
from tqdm import tqdm
import json
from torchvision.mod... |
6154ef0bd81333f1f4aff6fe62c6760e6a99b5382c49d21b612cc6cd17575508 | Python | 1,687 | 59 | """
File: logger.py
Created: 2020/10/13
Last Changed:
Author(s): 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 version 3 of the Li... |
7425ab57f0228b4f73fe24a4db77463f9c9cbdd9c2ddb79a2375eb7f9f5b48cd | Python | 1,687 | 50 | """
This module specifies the MultiModelWrapper class, currently intended for
use through Selene's API (as opposed to the CLI).
Loads multiple models and concatenates their outputs.
"""
import torch
import torch.nn as nn
class MultiModelWrapper(nn.Module):
def __init__(self, sub_models, concat_dim=1):
"... |
896a7eff4c51d261e9660d9e2c19f3f27d1f9d0a361f5fba8c9879c314d59897 | Python | 1,687 | 55 | import fnmatch
def heur(physinfo, name, task='', acq='', direct='', rec='', run=''):
# ############################## #
# ## Modify here! ## #
# ## ## #
# ## Possible variables are: ## #
# ## -task (required) ## #
# ## -run ## #... |
faaa429cdf370b88ee079088a9f81c092621b6589e3677514512240e4a3acf68 | Python | 1,687 | 40 | from shutil import move, copy2
import os
OR_DIR = '/mnt/EncryptedData1/Users/javier/ext_datasets/COMET_dataset/OSLO_COMET_CT/Formatted_128x128x128'
val_split = '/mnt/EncryptedData1/Users/javier/ext_datasets/COMET_dataset/OSLO_COMET_CT/For_validation.txt'
test_split = '/mnt/EncryptedData1/Users/javier/ext_datasets/COME... |
2a24d4797bea9736d19612c15257608cd2bae9c10a1a5c45835f7001f515c104 | Python | 1,688 | 51 | import itertools
import logging
from typing import Iterator, List, Optional
from oaklib.datamodels.association import Association
from oaklib.interfaces.association_provider_interface import (
AssociationProviderInterface,
SubjectOrObjectRole,
)
from oaklib.types import CURIE, PRED_CURIE
def get_association_... |
7cda645b1f45ca90d0dd8353bf170543a4ee0531f3ebd86a2f216eb10ed88a80 | Python | 1,688 | 52 | #!/usr/bin/env python3
# encoding: utf-8
# @Time : 2018/9/12 下午3:03
# @Author : yuchangqian
# @Contact : changqian_yu@163.com
# @File : sgd.py
import torch
from torch.optim.sgd import SGD
class StandardSGD(SGD):
def step(self, closure=None):
"""Performs a single optimization step.
Argument... |
4c60436c512b8ea0916e12c638e6cc355d129f968f9a6917415e89cbceaeaecd | Python | 1,690 | 46 | import sys
import numpy as np
import torch
from torch_geometric.datasets import TUDataset
from graphxai.explainers import GradExplainer
from graphxai.explainers.utils.visualizations import visualize_mol_explanation
from graphxai.gnn_models.graph_classification import GCN, load_data, train, test
import matplotlib.pypl... |
b027e5386916b10210d13046c86d3a0a52d34316c056fff0feafd8003256005f | Python | 1,690 | 51 | import os
import sys
import json
import datetime
import pandas as pd
from dicom_scu_class import Retriever_SCU
def find_daily_cts(day):
infofile = "setup_information.json"
f = open(infofile)
info = json.load(f)
scu = Retriever_SCU(info['ARIA']['AETITLE'],
info['ARIA']['HOST'],... |
8711c4a22d502c1accad5f3c45525eee7dda36a4f7397f81e213dd79aebd8234 | Python | 1,691 | 43 | # %%
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from pymaid_creds import url, name, password, token
import pymaid
rm = pymaid.CatmaidInstance(url, token, name, password)
from contools import Celltype, Celltype_Analyzer, Promat, Analyze_Cluster
# %%
# set up annotatio... |
614c5c414d0d8faf52fb309097ecc7b18c7ecda522302540b87641cd5eb6295e | Python | 1,693 | 46 | # 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... |
828af1eb04fac0eb54ba0fec43d5aac1b2d372c3e2d37fbf2a9b2405eee16b69 | Python | 1,693 | 51 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import logging
import time
import os
import sys
from tensorboardX import SummaryWriter
def setup_logger(name, save_dir, distributed_rank):
logger = logging.getLogger(name)
logger.setLevel(logging.DEBUG)
# don't log results for the non-... |
4ab09ca316de5821ebd28fbff9c3ee10a589190525df3b02005c75fbfd539bed | Python | 1,694 | 67 | """
Title
-----
AdEx neuron
Description
-----------
The Dendrify implementation of the Adaptive exponential integrate-and-fire model
(adapted from `Brian's examples <https://brian2.readthedocs.io/en/stable/examples/frompapers.Brette_Gerstner_2005.html>`_).
Resources:
- http://www.scholarpedia.org/article/Adaptive_ex... |
b518f7db75baf5315e454deaff83ed176fbaef436b92b6be520c946d10f17b97 | Python | 1,694 | 19 | """plot_telemetry.py TELEMETRY.json OUT.png: controls, speed, engine RPM and gear, and wheel omega from telemetry_run.py."""
import json, sys
import matplotlib; matplotlib.use('Agg'); import matplotlib.pyplot as plt
R = json.load(open(sys.argv[1])); t = [r['t'] for r in R]
C = ['#2980b9', '#3c9a5f', '#e69138', '#d9534f... |
ff5cec1001011f64cd1b05a7967f1f78e04e10f283e5af7bc084badf0fdfd14f | Python | 1,694 | 76 | """
In reduced tasks, we use two modes, which
are quoted in two different directions. Some
of the tasks can only be transferred to one mod.
The contextual task is transferred to two modes at once.
The network must ignore the wrong mod.
"""
from __future__ import annotations
from .ctxdm import *
from .dm import *
from ... |
3a9e308c9d2e5d577b4dcc55470398a720ec1ad7a100636e22a8dbc2a5fc75a7 | Python | 1,695 | 57 | #%%
import os
try:
os.chdir('/Volumes/GoogleDrive/My Drive/python_code/connectome_tools/')
print(os.getcwd())
except:
pass
#%%
import sys
sys.path.append("/Volumes/GoogleDrive/My Drive/python_code/connectome_tools/")
import networkx as nx
from networkx.utils import pairwise
import pandas as pd
import n... |
6df77cd0b850adeb33c1e990d558dbc7f7828a71e71854398d65e3baabf771d7 | Python | 1,698 | 62 | import torch
import numpy as np
from thop import profile
from thop import clever_format
def clip_gradient(optimizer, grad_clip):
"""
For calibrating misalignment gradient via cliping gradient technique
:param optimizer:
:param grad_clip:
:return:
"""
for group in optimizer.param_groups:
... |
880919b119b6f04e6805e0a3fabb2ea5ca06d75c7119a0d48d971cb10ddf3272 | Python | 1,698 | 65 | import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
def plot_2D_sequence(df, max_time_step=None, out_dir='./tmp.png'):
fig = plt.figure(figsize=(16, 4))
gs = GridSpec(1, 3)
ax1 = plt.subplot(gs[0, 0])
ax1.set_xlim(-1.0, 1.0)
ax1.set_ylim(-1.0, 1.0)
ax1... |
da526ee853325fc1a0ed921ca2c9a385ced0b8e985ef324b4a3d04cbc31fe7e5 | Python | 1,698 | 51 | import logging
from dataclasses import dataclass, field
from typing import List, Optional, Union
from linkml_renderer.renderers.html_renderer import HTMLRenderer
from linkml_renderer.style.model import Configuration, RenderRule
from linkml_renderer.style.style_engine import StyleEngine
from linkml_runtime.utils.yamlut... |
90d4c2fde712b83373eb4f81e650644fb55c2d8505172af69cdf1356473ad67d | Python | 1,699 | 48 | import os
import sqlite3
import unittest
from pathlib import Path
from oaklib.implementations.sqldb.sqlite_utils import (
sqlite_bulk_load,
sqlite_bulk_load2,
)
from tests import INPUT_DIR, OUTPUT_DIR
TSV = INPUT_DIR / "foo.tsv"
DB = OUTPUT_DIR / "test.db"
if os.name == "nt":
_, db = os.path.splitdrive(DB... |
8231824315e117fd72954f9e44d1c6004f2b3f0d510d3fa809f57d636d323b9c | Python | 1,700 | 65 | from os.path import basename
from pathlib import Path
import numpy as np
from sacred import Experiment
from sacred.observers import FileStorageObserver, SlackObserver
from graspy.datasets import load_drosophila_left
from graspy.utils import binarize, symmetrize
from src.models import select_rdpg
from src.utils import... |
ea34b35077bfbcbd8da9facd0f363f4be18c9a9cbd0a9b7359329c6872836280 | Python | 1,700 | 67 | import argparse
import importlib
import logging
from argparse import ArgumentDefaultsHelpFormatter
commands = [
"score",
"train",
"evaluate",
"analyse",
"vignettes",
"download_model",
]
COMMANDS = [importlib.import_module("cenfind.cli." + c) for c in commands]
def add_command_default(parser)... |
0990ab80b3e8b4a75bef5fe948a44095032e039d49212078d7044a48e747b613 | Python | 1,702 | 49 | # Copyright 2019 The TensorFlow Authors, Pavel Yakubovskiy. 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 ... |
3a624fbfd093e4ad9b5fbae5d92f43309ce6089292a81edb608c5b0546d2734c | Python | 1,702 | 57 | #!/usr/bin/env python3
# -*- coding:utf-8 -*-
#############################################################
# File: save_heatmap.py
# Created Date: Friday January 15th 2021
# Author: Chen Xuanhong
# Email: chenxuanhongzju@outlook.com
# Last Modified: Wednesday, 19th January 2022 1:22:47 am
# Modified By: Chen Xuanhong... |
57ad6f3daed19694f3efd4fbdbe726561de7c814ab1c010d0c87e25959113abf | Python | 1,703 | 72 | import numpy as np
from graspologic.utils import remove_loops
from graspologic.match import GraphMatch
def estimate_spring_rank_P(A, ranks, beta):
H = ranks[:, None] - ranks[None, :] - 1
H = np.multiply(H, H)
H *= 0.5
P = np.exp(-beta * H)
P *= np.mean(A) / np.mean(P) # TODO I might be off by a c... |
fad4f5fe16689ce9cd56d24482679eb48071283bc55c3503fc5fcd9844e2b488 | Python | 1,703 | 61 | import torch.nn as nn
class Mlp(nn.Module):
def __init__(
self,
in_features,
hidden_features=None,
out_features=None,
act_layer=nn.GELU,
drop=0.0,
):
super().__init__()
out_features = out_features or in_features
hidden_features = hidden_f... |
10f7fa2e6b542a46a103b6df03137c93dbb6d12c54e45bb00d4c20239f268b81 | Python | 1,709 | 50 | from scipy.io import arff
import numpy as np
class2idx = {"standing": 0, "walking": 1, "jumping": 2}
def data_look(path):
data, meta = arff.loadarff(path)
print(data.shape, len(data))
print(data[0][0].shape, len(data[0][0]))
print(data[0][0][0].shape, len(data[0][0][0]))
def class_label_... |
1f25194aeffa8f73e4626aa1cef704f6d593800580229c5f214d3d0f09890e52 | Python | 1,710 | 46 | import numpy as np
import os
import shutil
from subprocess import Popen, PIPE
from sklearn import KDTree
from Bio.PDB import *
# Generate surface file for probis for the MaSIF benchmark.
# Pablo Gainza 2019.
probisexe="probis/probis"
cofactors = ['HEM', 'NAD', 'NAP', 'SAM', 'ADP', 'FAD', 'COA']
# Go through all... |
73b61644ef3493c4f24161e61d13a4f47eb13ca2db6b73605f64114f7f9f24c9 | Python | 1,710 | 46 | import sys
import numpy as np
import torch
from torch_geometric.datasets import TUDataset
from graphxai.explainers import IntegratedGradExplainer
from graphxai.explainers.utils.visualizations import visualize_mol_explanation
from graphxai.gnn_models.graph_classification import GCN, load_data, train, test
import matpl... |
dd5c71943777460323159895df29285311c292391497c2c2779848d61590ab6b | Python | 1,710 | 49 | import torch
from cgtasknet.instruments.instrument_disable_neurons import DisableSomeNeurons
from cgtasknet.net.lif import SNNLif
def test_init_disables():
net = SNNLif(3, 10, 3)
DisableSomeNeurons(net)
def test_output_disables():
net = SNNLif(3, 10, 3)
number_of_neurons = (0, 1, 2)
disables = ... |
c36c1f9dca85a5a346b908773dafff3056045f27054342291c85a90e865c15bc | Python | 1,711 | 55 | '''
Make fit tables with parameters from fits of all cells.
'''
import sys
from file_management import *
import yaml
import pandas as pd
from brian2 import *
from os.path import join, split
import os
### Command line argument: path
try:
path = sys.argv[1]
except:
path = os.path.expanduser('~/hodgkin/Paramecium... |
804310b8da2d50c383226b3373dc32f5651dd94568fe077108915cf38f62f78b | Python | 1,712 | 47 | import os.path as op
from glob import glob
import nibabel as nib
import numpy as np
import pandas as pd
from nilearn import image
output_dir = "/home/data/abcd/abcd-hispanic-via/atlas"
template = "/home/data/cis/templateflow/tpl-MNI152NLin2009cAsym/tpl-MNI152NLin2009cAsym_res-02_desc-brain_T1w.nii.gz"
template_img = ... |
591122a0975ab1d8de09553ce8906809acae63d3312baa6aa50b2987218bc55f | Python | 1,713 | 54 | from AFQ.utils.path import drop_extension
import os.path as op
import inspect
__all__ = ["get_fname", "with_name", "get_base_fname"]
def get_base_fname(output_dir, dwi_data_file):
# setup up path and base file name for outputs
# remove suffix and desc from dwi data file name
used_key_list = ["desc", "spa... |
d7183645d5cd88f1f91fafb803660ff1d066496f4f65779b4877fdbe2164eae2 | Python | 1,713 | 46 | import os
import pickle as pkl
import sys
import time
import networkx as nx
import numpy as np
from tqdm import tqdm
from utils.data_utils import load_data_lp
def hyperbolicity_sample(G, num_samples=50000):
curr_time = time.time()
hyps = []
for i in tqdm(range(num_samples)):
curr_time = time.tim... |
d6a6c673ee5f682aaf92696d055bd61c4850b511f821b8363bde0b8e0ff7f15f | Python | 1,714 | 49 | import numpy as np
# Computed feature mean from the task 1 train split.
# Only needed for normalizing features.
feature_mean = "data/train_mean.npy"
feature_stdev = "data/train_stdev.npy"
def transpose_last_axis(orig_pose_dictionary, sequence_key = 'keypoints'):
for key in orig_pose_dictionary:
X = orig_pose_di... |
55060b5a27b548d0a6488a315608a7e94acc6f6c8bb06a49206bbcab3dd9133d | Python | 1,715 | 73 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Nov 19 14:12:40 2021
@author: alexandra
This script convert the pickle database (python format) to a CSV format.
It will clean the data before export.
"""
import pickle
import pandas as pd
import os
from os import listdir
from os.path import isfile, ... |
7dcc031bd02a2f63bedcfc2832c9d36522b72b22fcb2d56de44218c6c7fd1709 | Python | 1,715 | 74 | """Miscellaneous functions"""
import random
import numpy as np
import torch
import torch.nn.functional as F
def np2torch(tensor, device='cuda'):
if isinstance(tensor, list):
tensor = [torch.from_numpy(t).to(device) for t in tensor]
else:
tensor = torch.from_numpy(tensor).to(device)
return... |
89cdbefdb7344a05e00ee48c7fa0719f5fd3b5142682a236e254f4091848f752 | Python | 1,715 | 48 | from timm.models.layers.helpers import to_2tuple
import timm
import torch.nn as nn
class ConvStem(nn.Module):
def __init__(self, img_size=224, patch_size=4, in_chans=3, embed_dim=768, norm_layer=None, flatten=True):
super().__init__()
assert patch_size == 4
assert embed_dim % 8 == 0
... |
7a3fbbfd76ad678f9f28d591d84528820e021d5f2bd053c001561f5cab1c143d | Python | 1,716 | 40 | #!/usr/bin/env python
import time
import sys
import os
import shutil
from rectool import *
rt = RecognizerToolbox()
command = sys.argv
if rt.adaptation is not None:
if (not rt.use_existing_lnas()) and (not rt.use_existing_adaptation()):
command[0] = script_path('recognize-stateseg.py')
# estimate_adaptation() ... |
af15cce362d52b4960320e634929de45c694abf86a2047c02042895668d4fcf8 | Python | 1,716 | 60 | import unittest
import grr.ThresholdModel_testutil as tmt
from grr.iGIF import iGIF_NP, iGIF_Na
# iGIF_NP tests.
class TestiGIF_NPSimulateDoesNotCrash_VectorInput(
tmt.TestSimulateDoesNotCrash_VectorInput, unittest.TestCase
):
def setUp(self):
super(TestiGIF_NPSimulateDoesNotCrash_VectorInput, self).... |
5b5c9589ff39d8e3c0a6f7e013a35ee1938b409f470ca05335e9ac86ea7e69fd | Python | 1,717 | 49 | ####################################################################################################
# Copyright (c) 2019, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of VessMorphoVis <https://github.com/BlueBrain/VessMorphoVis>
#
# This program is free softwar... |
fd23800d0df6d6f19e16e2e092333549b17a02bc1672f774af44b6edbbacb531 | Python | 1,717 | 35 | import click
import multiprocessing
from slideflow.test import TestSuite
@click.command()
@click.option('--slides', help='Path to directory containing slides', required=True, metavar='DIR')
@click.option('--out', help='Directory in which to store test project files.', required=False, metavar='DIR')
@click.option('--ex... |
3014be3a61588b34076e58122196947b813aa5c44a51140876c8438a34182879 | Python | 1,719 | 44 | import os
import sys
import slideflow as sf
import argparse
import logging
import multiprocessing
if __name__=='__main__':
multiprocessing.freeze_support()
parser = argparse.ArgumentParser(description = "Helper to guide through the Slideflow pipeline")
parser.add_argument('-p', '--project', required=True... |
46285cfd43cfd39fac8b6f00c486afea4aec1b937a94722b0ad6f8879cac900b | Python | 1,719 | 73 | """Configurations."""
import json
from easydict import EasyDict as edict
efficientnet_b1_config_ascend = edict({
"train_url": None,
"train_path": None,
"data_url": None,
"data_path": None,
"checkpoint_url": None,
"checkpoint_path": None,
"eval_data_url": None,
"eval_data_path": None,
... |
af99aa44e5e0f75b7bb96cffd11206e58559f59e2dae490c87df652d78386b28 | Python | 1,719 | 42 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
def average_gradients(tower_grads):
"""Calculate the average gradient for each shared variable across all towers.
Copied from https://github.com/tensorflow/models/blob/master/t... |
d2872a9f368b94a5f117a20c8a0de0e0bbac398d250244729ae18cab2af6caf1 | Python | 1,719 | 80 | """
Tuning curve related functions.
"""
import numpy as np
from scipy.stats import percentileofscore
def tuning_curve(tdarray):
u, s, vh = np.linalg.svd(tdarray, full_matrices=False)
tune = np.abs(vh[0,:])
return tune
def dsi(tune):
tune = tune.reshape((-1,1))
angles = np.linspace(0, 2*np.... |
0c3d284ee527f6d49d407d3e7314e0619cc5d5d7bfee3fbc97944981cf5bba2b | Python | 1,721 | 72 | """cxconfig -- cxsystem config file converter
Usage:
cxconfig (-h | --help)
cxconfig FILEPATH
A configuration file converter for `CxSystem`.
Arguments:
FILENAME Path to configuration file to convert
Options:
-h --help Show this screen
Description:
cxconfig ./sample_conf.json
... |
c67e816e8415857ebc51447805d5903c54fd342f745cdfbb53cc0306fd3d6ec3 | Python | 1,721 | 53 | from dataclasses import dataclass
import rdflib
import oaklib.datamodels as dm
from oaklib.implementations.sparql.abstract_sparql_implementation import (
AbstractSparqlImplementation,
)
from oaklib.interfaces.differ_interface import DifferInterface
from oaklib.interfaces.mapping_provider_interface import MappingP... |
e1ddd6cfc26b79955e7b36126f7dee3778a006a4ebfca75ab8f7783fae3f743d | Python | 1,721 | 41 | ##########################################################
## ccAF: calculatingErrors_CV.py ##
## ______ ______ __ __ ##
## /\ __ \ /\ ___\ /\ \/\ \ ##
## \ \ __ \ \ \___ \ \ \ \_\ \ ##
## \ \_\ \_\ \/\_____\ ... |
219b2f8da1ded60618a584c449ae637e89cfb50808480a077c7d51101b8e039a | Python | 1,722 | 67 | # -*- coding: utf-8 -*-
# @Author : WenHan
import numpy as np
def conv_1d(data, filters, bias, stride, pad):
input_size = data.shape[0]
input_channels = data.shape[-1]
filter_length = filters.shape[0]
output_channels = filters.shape[-1]
output_size = round((input_size - filter_length + 2 * pad) ... |
8e0e65037a204f2311c4ef58aff4d356c098b33e05e17364704e4fc5652a49a2 | Python | 1,722 | 48 | '''
Explain one node prediction by the model.
Args:
x (torch.Tensor): Tensor of node features from the entire graph
node_idx (int): Node index for which to explain a prediction around
edge_index (torch.Tensor): edge_index of entire graph
label (int, optional): Label on which to compute the explanation ... |
f397c4871d6e6e9e477e13f7e00b58bb495ebe94590fec8debc5daa9b4c99dad | Python | 1,723 | 49 | # 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... |
9ece0e859a848232320c726d9e6d031e1424f7271e184cd3e491c2da76e64a35 | Python | 1,724 | 45 | # SPDX-FileCopyrightText: © 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# SPDX-License-Identifier: MIT
# Track identifier for the ego (main) vehicle
EGO_TRACK_ID = "ego"
# Default vehicle class for the ego vehicle in CARLA.
# CARLA UE5 renamed the vehicle catalog; the UE4-era Mercedes coupe is gone.
#... |
1802323f600a40790bc494a89d1c8892278ccac0bef0289a45f27807b2fd88ad | Python | 1,725 | 40 | from tensorflow.keras import *
class TransformerNet:
def __init__(self, input_shape, nb_classes, verbose=False, build=True, is_train=True):
if build:
self.model = self.build_model(input_shape, nb_classes, mlp_units=[2], is_train=is_train)
if verbose:
self.model.sum... |
68fbb49031bcabf2a3dc535c8bdbddf4b0fbd0a4ee0572fbb77b527dfb501f73 | Python | 1,725 | 49 | from typing import Any, List, Optional
from zencfg import ConfigBase
from .distributed import DistributedConfig
from .models import ModelConfig, FNO_Small2d
from .opt import OptimizationConfig, PatchingConfig
from .wandb import WandbConfig
class BurgersDatasetConfig(ConfigBase):
folder: str = "neuralop/data/data... |
8a714a54f30f665f1af25e1244e38bea07c2e81efb9e2a1df53b1f74c7641cc8 | Python | 1,725 | 47 | # 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... |
db283076b5ca94805c883fc5107bff29e03c2c57d39a4ccb78d56facd6536758 | Python | 1,725 | 50 | """Helper functions for downloading plenary session videos.
The current video API is documented at `https://verkkolahetys.eduskunta.fi/api-documentation/`.
"""
import re
from typing import Dict
def form_date_parameter(date: str, name: str) -> str:
"""Form the date parameter for the API query after checking wheth... |
457008c7352fa23c067598b41c546bb001a81accd0b036b8ad15cc6c121ec6ff | Python | 1,726 | 47 | '''
From fit v01, remove the dff trace with related low snr
'''
from dff import *
import os, sys
import warnings
warnings.filterwarnings('ignore')
from glob import glob
# get cell list information
flist = sorted(glob('GCaMP8_exported_ROIs_s2f_full/data/*.npz'))
cell_info=["_".join(os.path.basename(f).split('_')[:6]) f... |
841595e71d7c97cfcb01f3505a6eb022fc2276066107ec3b30e75f54ef60777c | Python | 1,726 | 39 | # 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... |
6a93752f5e1b54f37cbd99ec5a7c1887192b1684450ff99406e80a1fbab90056 | Python | 1,727 | 46 | from .base import *
class ConservativeTracker(Tracker):
def __init__(self, max_diffusivity: float = 5.0):
# Attributes will automatically be detected as parameters of the step and stored/loaded.
# Parameters must have default values
self.max_diffusivity = max_diffusivity
def track(sel... |
8c158eacb3bc0b69522a1121e7de32621686a0168bb3cfbdfdae5327a0d9dfef | Python | 1,728 | 45 | import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from . import utils as ut
def analysis_plots(
df,
filenames_map,
plot_path,
feature_cols
):
"""Creates box plots to compare groups of statistics, using filenames_map.
Args:
... |
930e721f5539db2033c8b807ce7c803113581eae358e8adaf39d718a0623e5d6 | Python | 1,729 | 62 | import re
from typing import Iterable, Tuple, Type
from kgcl_schema.datamodel.kgcl import (
Change,
NodeRename,
NodeTextDefinitionChange,
SynonymReplacement,
)
from oaklib import BasicOntologyInterface
from oaklib.interfaces.patcher_interface import PatcherInterface
from oaklib.types import CURIE
ISS... |
bc36da6fdbae6390191ac9f75ecb1dbfc683e830864d99edb40e8ccc19a107fe | Python | 1,729 | 31 | """pie_shot.py SHOTS.json OUTDIR: one CARLA RGB capture per shot, for material and scene examples.
SHOTS.json is a list of {"name", "cam": [x, y, z], "at": [x, y, z], "fov": 70, "weather": {field: value}, "wait": 4}
in metres (CARLA coordinates). Each shot applies its weather fields on top of the current weather, poin... |
83a35d7e73d1bbdb1eda5e6ae66d42a255f945db0614d63eac3dbaad6822952c | Python | 1,730 | 63 | # Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#
import logging
import time
from datetime import timedelta
class LogFormatter():
def __init__(self):
self.start_t... |
bde8fd58f7de24cfcbfeae5b2c508a84f4c08757329d7e05de93b877ee5ce103 | Python | 1,730 | 55 | import numpy as np
def complete_graph(N):
edge_start = np.array([i // N for i in range(N ** 2) if (i % N) != i // N])
edge_end = np.array([i % N for i in range(N ** 2) if (i % N) != i // N])
return edge_start, edge_end
def edges_uniform(N, D):
delta = 1 + np.random.choice(N - 1, size=N * D, replace=... |
e4a9daf0198e143f4a0db4f180a6dca0c868734938033fbf3f5c0c24a918af3b | Python | 1,732 | 62 | import argparse
import torch
from mmcv import Config
from mmdet.models import build_detector
try:
from mmcv.cnn import get_model_complexity_info
except ImportError:
raise ImportError('Please upgrade mmcv to >0.6.2')
def parse_args():
parser = argparse.ArgumentParser(description='Train a detector')
... |
d9660cfe89139c79b2355282eeda6a322697e86b73b7ed1f8689678b381b69d6 | Python | 1,734 | 60 | from typing import Tuple
import cv2
import numpy as np
from skimage.exposure import rescale_intensity
from skimage.feature import blob_log
from spotipy.utils import points_matching
from cenfind.core.data import Field
from cenfind.core.structures import Centriole
def blob2point(keypoint: cv2.KeyPoint) -> tuple[int, ... |
1b76dc95140d8b7d9e8b281bf183e7a5529fef9c9d8f76630552140002136b79 | Python | 1,735 | 47 | import pandas as pd
import numpy as np
ind = 0
header = "BICCN2_gene_global_index_5000"
clusters = ['celltype', 'cluster', 'SubCluster'][ind:3]
head = 'BICCN2'
# header = 'GSE111586_gene_global_index_5000'
# clusters = ['celltype', 'id', 'Ident'][ind:3]
# head = 'GSE111'
header = 'GSE123576_gene_global_index_5000'
c... |
25e651d327996f3b9e6901a74b511381d184dcbf381091cc9b645c7c3584a3f5 | Python | 1,735 | 55 | import numpy as np
def IoU(box_a, box_b):
"""
Intersection over union of two boxes A and B.
Boxes must be parametrized as follows: Box = [X1, Y1, X2, Y2]
Returns
-------
IoU : float
Intersection over union
"""
#print('A:', box_a)
#print('B:', box_b)
# Extract... |
c2f59c637cc53f6f184333aea93c0ca3b43a0d0c9aa02f8953a76f1726d84bb8 | Python | 1,735 | 53 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Module containing useful functions for computing losses with PyTorch.
Created on Wed Feb 20 10:29:37 2019
@author: nicolas
"""
import torch
def get_BCEWithLogits_loss(reduction='mean',
pos_weight=1, neg_weight=1):
"""
Return a... |
d58e22e52cd87127d71ab2ddb8ed560f8cd4ac9b9fdf1e7ad84f365656bc78d2 | Python | 1,735 | 45 | '''
Selection of hyperpolarized cells (for Fig. 2).
Discards cell with abnormal passive properties.
'''
import pandas as pd
from file_management.configuration import *
from os.path import join
from numpy import exp
for concentration in ['0', '4']:
table_folder = join(config['root'],'Ciliated '+concentration+' mM K... |
dc8ddc8a0435c58db0a56f3cee4a49deda6c9b01e7d043d4426b3843f5afdb43 | Python | 1,735 | 57 | # import sys
# import fnmatch
def heur(physinfo, name, task='', acq='', direct='', rec='', run=''):
# ############################## #
# ## Modify here! ## #
# ## ## #
# ## Possible variables are: ## #
# ## -task (required) ## #
# ## -run ... |
1a6e20ecc54164937d28c3f831a4f9adb4f3d8a73f87bee91493aa00e1af4530 | Python | 1,736 | 53 | """Smoke tests for the connectome loader.
These check the *Winding 2023* invariants — if the published numbers ever change,
these tests pin down what we're working against.
"""
import numpy as np
from mb_dual_dan.connectome import load_winding, extract_mb
from mb_dual_dan.connectome.nt_signs import neuron_signs, sig... |
3fbc0139ceebce73dbb3525c224f312648b54de08374c5a6945b85e6f52620b4 | Python | 1,736 | 66 | '''
Figure 7.
Zoom: predicted currents.
'''
from brian2 import *
import yaml
from file_management import *
from pylab import *
import matplotlib.font_manager as fm
import os
from fitting import *
from plotting import *
from matplotlib import gridspec
fontprops = fm.FontProperties(size=18)
width, height = 3, 2
# Load... |
25f653bd6704c2ee30062ca7dd9912b50da5b17b7e60089dad8792fa407b5aaa | Python | 1,737 | 74 | # %% [markdown]
# ##
import os
import time
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from matplotlib.patches import Circle
from mpl_toolkits.axes_grid1 import make_axes_locatable
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
from sci... |
f98af31ec33c56ab17c0e8d80ce6b93a1df3d6a89f068b04b6d23607de44ada0 | Python | 1,737 | 53 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
import pathlib
import sys
root_path = str(pathlib.Path(__file__).parents[2].resolve())
sys.path.insert(0, root_path)... |
7918ba0b242b696759beccb46249c6ee3a20226ba5340367a36752408662a9aa | Python | 1,738 | 53 | # -*- coding: utf-8 -*-
import sys
import csv
import numpy as np
filename = sys.argv[1]
with open(filename, 'r') as f:
reader = csv.reader(f)
data = list(reader)
# GROUP TOGETHER CONSECUTIVE IDENTICAL UMIS, ASSUMING THEIR PROXIMITY
row_old = data[0]
data_aggegated_by_umi_identity = [row_old]
for row in data... |
a1a81de5cca8b4e2cdc95f17f0038b097b904a8ff9c35e27264e2e6ab7bc4895 | Python | 1,739 | 50 | from pathlib import Path, PosixPath
import pytest
from cenfind.core.data import Dataset, Field
ROOT_DIR = Path(__file__).parent.parent
if not (ROOT_DIR / "data/dataset_test").exists():
pytest.skip(
"data/dataset_test fixture is not present (it is gitignored and not "
"distributed with the repo); ... |
4cd6877950d0f6b774db7cf5cb724cd93233bddebcf6736da63c8a61cb398638 | Python | 1,740 | 50 | import os
import tensorflow as tf
from tensorflow.python.framework import ops
module_path = os.path.realpath(__file__)
module_dir = os.path.dirname(module_path)
lib_path = os.path.join(module_dir, 'roi_pooling.so')
roi_pooling_module = tf.load_op_library(lib_path)
def roi_pooling(input, rois, pool_height, pool_widt... |
76ff9571a4e50f5fd15b5c184eda9a75312b999a0a0d8c5b44b8a81f360fcdd9 | Python | 1,740 | 63 | import torch
import numpy as np
# `pip install thop`
from thop import profile
from thop import clever_format
def clip_gradient(optimizer, grad_clip):
"""
For calibrating mis-alignment gradient via cliping gradient technique
:param optimizer:
:param grad_clip:
:return:
"""
for group in opti... |
a23b003e7034faa5c7adeec28c7e188b7700c085335748b48001a72da2725ba3 | Python | 1,741 | 43 | #!/usr/bin/env python3
# encoding: utf-8
# @Time : 2017/12/16 下午8:41
# @Author : yuchangqian
# @Contact : changqian_yu@163.com
# @File : mclane.py
from datasets.BaseDataset import BaseDataset
class VOC(BaseDataset):
@classmethod
def get_class_colors(*args):
return [[0, 0, 0], [0, 0, 128], [0, ... |
2d2258d94a51c430405bb4ea87e4c9ef226aebeb87b8d558a601dd009520d48e | Python | 1,742 | 32 | # This file is added for back-compatibility. Thus, downstream codebase
# could still use and import mmdet.ops.
# yapf: disable
from mmcv.ops import (ContextBlock, Conv2d, ConvTranspose2d, ConvWS2d,
CornerPool, DeformConv, DeformConvPack, DeformRoIPooling,
DeformRoIPoolingPac... |
4578a623bad388d02768e0c968f4bf0ed01ec6a444c576ae2884ce96ced3bad9 | Python | 1,742 | 59 | """Mitochondria Segmentation
Usage:
mito_seg.py -i input.hdf -o output.hdf [-c] [-b] [-q]
mito_seg.py (-h | --help)
mito_seg.py --version
Options:
-i <file>, --input <file> Path to the input HDF file
-o <file>, --output <file> Path to the output file
-c, --copy Copy t... |
b02d470dd8c29c22a223effada30f91a1150fdb48c393a55f0ea6084a8ef97b8 | Python | 1,743 | 53 | import logging
from typing import Iterator, TextIO
from oaklib.datamodels.taxon_constraints import SubjectTerm, Taxon, TaxonConstraint
def parse_gain_loss_file(file: TextIO) -> Iterator[SubjectTerm]:
"""
Parses a file containing gains and losses
See `<https://github.com/geneontology/go-ontology/issues/1... |
ccd63034d2fde8eb5101caf2c6e73d466919db3ad59104eb73fdba72ebffce3d | Python | 1,743 | 59 | from typing import List
import numpy as np
from rdkit.Chem import MolToSmiles
from RAscore import RAscore_XGB
from drugex.training.scorers.interfaces import Scorer
XGB_MODEL_PATH = None
class RetrosyntheticAccessibilityScorer(Scorer):
"""
Given a SMILES string, returns a score in [0-1] that indicates how
... |
1f6bfa200fca7d339c33aed84af55af95aee2144c8af22a3cb7ef3502c368b0e | Python | 1,745 | 58 | from contextlib import contextmanager
from petsc4py import PETSc
import dolfin as df
import numpy as np
def transpose_matrix(A):
'''Create a transpose of PETScMatrix/PETSc.Mat'''
if isinstance(A, PETSc.Mat):
At = PETSc.Mat() # Alloc
A.transpose(At) # Transpose to At
return At
At... |
2c0d5898ceae5311df6ccc8e83e70e0d5e4eb18eacefca329c960fa357f3e648 | Python | 1,745 | 44 | # 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... |
18dbcc327891363c891afa9d452c966a7472354aef98069205675330144f4492 | Python | 1,746 | 45 | import torch
from torch_geometric.datasets import TUDataset
from graphxai.explainers import PGExplainer
from graphxai.explainers.utils.visualizations import visualize_mol_explanation
from graphxai.gnn_models.graph_classification import GCN, load_data, train, test
dataset = TUDataset(root='data/TUDataset', name='MUTA... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.