sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
d1f476ab279ff52c562635ba74b33a0e1446b940766f45ab061586bef1564fbf | Python | 637 | 15 | """Tests for pruned model adaptation (timm.models._prune)."""
import pytest
import torch
import timm
from timm.models import list_models
@pytest.mark.parametrize('model_name', list_models('*pruned*'))
def test_pruned_feature_info_matches_forward(model_name):
"""Pruning rebuilds layers with new widths; feature_in... |
933f0f18e7f258f308b6916fbcbd3fbb96f66793d9c3174ed120b3acb5c31b09 | Python | 639 | 34 | # -*- coding: utf-8 -*-
"""
Created on Wed Mar 1 10:31:23 2023
@author: yxliao
"""
import numpy as np
from sklearn.metrics import r2_score
def Rx(theta):
R_x = np.array([
[1, 0, 0],
[0, np.cos(theta), -np.sin(theta)],
[0, np.sin(theta), np.cos(theta)],
])
return R_x
def Ry(thet... |
c363b5a5bcf1461f63989f616af47baf7d4fb22dea53effba6aef592bd9d8167 | Python | 639 | 20 | from .adjacency import segmentation_adjacency
from .form_feature_extraction import FormFeatureExtraction
from .feature_extraction import extract_features, extract_features_fixed
from .form_feature_selection import FormFeatureSelection
from .algorithm import (slic, slic_fixed, quickshift, quickshift_fixed,
... |
f5d51a803d3fd104fba7ae8fd196369a7d6e005e9fed232586abfa0d088f762d | Python | 639 | 23 | import numpy as np
from pytorch_grad_cam.base_cam import BaseCAM
class GradCAM(BaseCAM):
def __init__(self, model, target_layers, use_cuda=False,
reshape_transform=None):
super(
GradCAM,
self).__init__(
model,
target_layers,
use_... |
e6d939ca6e46a07455ea532a11a1c0bc30ee6d2e0e8611d61b01e6719276aef0 | Python | 645 | 39 | class TestWorker:
def test_enter_thread(self):
pass
def test_exit_thread(self):
pass
def test_run(self):
pass
def test_do_job(self):
pass
def test_interaction_handler(self):
pass
def test_cancel_handler(self):
pass
def test_display_handle... |
28b28dc362e3d16c97b363b7754c98c34257b2a738e561a8c4602314913bf570 | Python | 647 | 22 | import numpy as np
import matplotlib.pyplot as plt
freq = 5.
time = np.arange(0., 1.0, 0.01)
sine = np.sin(2 * np.pi * freq * time)
fig = plt.figure()
fig.set_size_inches(5.5, 2.5)
ax = fig.add_subplot(111)
ax.plot(time, sine, color="dodgerblue", marker='.', markersize=5, label="sinewave",
ls="solid", lw=1.2... |
653957af80114156386e9fbc0114ca92654febc3a44ca6744413057d6d8753eb | Python | 647 | 22 | from ._image_subscriber import ImageSubscriber
class FileImageSubscriber(ImageSubscriber):
"""A setting that provides image names loaded from files"""
def __init__(
self,
text,
value="Do not use",
can_be_blank=False,
blank_text="Leave blank",
*args,
**k... |
8bd2b5876c0431167f72a879fe53c23979e8d63ec301e60bb143f9e91af516e1 | Python | 647 | 21 | from __future__ import absolute_import
import numpy
import scipy.ndimage.filters
def kirsch(image):
convolution_mask = [5, -3, -3, -3, -3, -3, 5, 5]
derivatives = numpy.zeros(image.shape)
kernel = numpy.zeros((3, 3), image.dtype)
kindex = numpy.array([[0, 1, 2], [7, -1, 3], [6, 5, 4]])
for _ in ... |
503dcbbeda98d3a0f77cab4628330b3b10a0201ea9459a816be42a3bfb805659 | Python | 648 | 20 | class ValidationError(ValueError):
"""An exception indicating that a setting's value prevents the pipeline from running
"""
def __init__(self, message, setting):
"""Initialize with an explanatory message and the setting that caused the problem
"""
super(ValidationError, self).__init... |
407511d4e778ddb897257dccaaeb1109fab83fcfa5e9ef96dea5609b11083d00 | Python | 649 | 21 | import re
from ._filter_predicate import FilterPredicate
class RegexpFilterPredicate(FilterPredicate):
def __init__(self, display_name, subpredicates):
super(self.__class__, self).__init__(
"containregexp",
display_name,
self.regexp_fn,
subpredicates,
... |
0e9fbdf7c8988224739ac5525e0b4cee74f6c64f752a62078a109c027e17fa27 | Python | 650 | 22 | import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import pandas as pd
import tensorflow as tf
from .tools.data_processing import *
def predict_fitness(AA_sequence,
model=None,
model_file='/mnt/shared/notebooks/albert/FitPred/Final_model_24K_v1.h5'
... |
2943a5472cb2b992318c5dd90bc735fa7cdd51c2ac29af7ba9359e7d67a7c71a | Python | 650 | 12 | import pyControl.hardware as _h
class Double_poke():
# Two IR beams, single LED and Solenoid.
def __init__(self, port, rising_event_A = None, falling_event_A = None,
rising_event_B = None, falling_event_B = None, debounce = 5):
self.input_A = _h.Digital_input(port.DIO_A, rising_e... |
31a4cefe7dcbd74cf72a732cd338a60886466c775275309ef66dcb215ba59604 | Python | 650 | 15 | from pathlib import Path
from imctools.data import Session
class TestSession:
def test_read_session(self, analysis_ometiff_path: Path):
session_file_path = analysis_ometiff_path / '20210305_NE_mockData1' / '20210305_NE_mockData1_session.json'
session = Session.load(session_file_path)
asse... |
d06a40144ae344aeebb4eb1482f5f2ac1be20fd762450ae3cb202d7dbe097b42 | Python | 650 | 23 | class ImageSetChannelDescriptor:
"""This class represents the metadata for one image set channel
An image set has a collection of channels which are either planar
images or objects. The ImageSetChannelDescriptor describes one
of these:
The channel's name
The channel's type - grayscale image /... |
235995e2e5ef37d1df4030de8d2e1a39c7183b21027099e0f7327fa7f1cd6140 | Python | 651 | 14 | from neurodynex3.exponential_integrate_fire import exp_IF
from neurodynex3.tools import input_factory
import brian2 as b2
def test_simulate_exponential_IF_neuron():
"""Test exponential-integrate-and-fire model"""
c = input_factory.get_step_current(0, 2, 1 * b2.ms, amplitude=8.5 * b2.namp)
m, spike_monitor... |
2a6624ff4bfb10b91fc88a8d0443fc74f8b581d19e8936cd6924a5db87b21930 | Python | 651 | 14 | from neurodynex3.adex_model import AdEx
from neurodynex3.tools import input_factory
import brian2 as b2
def test_simulate_exponential_IF_neuron():
"""Test if simulates simulate_AdEx_neuron generates two spikes"""
current = input_factory.get_step_current(0, 0, 1. * b2.ms, 0.5 * b2.nA)
state_monitor, spike_... |
33c169ee0a0c1e95ef1fa2ae3a9b4477164cfd3e4c9e39efb9598b2b43d8d721 | Python | 651 | 22 | from ._file_image import FileImage
class STKFrameImage(FileImage):
"""Provide an image by filename:frame from an STK file"""
def __init__(self, name, pathname, filename, frame, rescale_range=None):
"""Initialize the provider
name - name of the provider for access from image set
pathn... |
3813391fba92fc06339b84ac1c3308b3cdde305e3166ecca9cb6e89c43fd92a1 | Python | 651 | 23 | # Copyright (c) OpenMMLab. All rights reserved.
import random
import numpy as np
import torch
def worker_init_fn(worker_id: int, num_workers: int, rank: int, seed: int):
"""Function to initialize each worker.
The seed of each worker equals to
``num_worker * rank + worker_id + user_seed``.
Args:
... |
2606b3a6393f8eec183e4da327f5b9adeafc485499659777c5816a5f521c5cd7 | Python | 653 | 34 | import torch
from torch import nn
import pdb
class GAN(nn.Module):
"""
Wasserstein GAN
"""
def __init__(
self,
critic: nn.Module,
generator: nn.Module,
):
super().__init__()
self.critic = critic
self.generator = generator
self.latent_d... |
55f20a57b88201f8cfc06845265af5f18e8cc20eec9f7f0b9c9b11492fd61b5f | Python | 654 | 15 | from ._analysis_cancel import AnalysisCancel
from ._debug_complete import DebugComplete
from ._debug_waiting import DebugWaiting
from ._debug_waiting import DebugWaiting
from ._display import Display
from ._display_post_group import DisplayPostGroup
from ._display_post_run import DisplayPostRun
from ._exception_report ... |
619986b1f9da3fec23c47bc1474280da6ff5015b302857ffe2aa31bb917b5f39 | Python | 654 | 13 | # This file is part of pyunicorn.
# Copyright (C) 2008--2026 Jonathan F. Donges and pyunicorn authors
# URL: <https://www.pik-potsdam.de/members/donges/software-2/software>
# License: BSD (3-clause)
#
# Please acknowledge and cite the use of this software and its authors
# when results are used in publications or publi... |
023978e111668c4154ac45bbf7e39f9714c9305e36f8319bbd572f106b54c3eb | Python | 658 | 22 | from ._image_subscriber import ImageSubscriber
class CropImageSubscriber(ImageSubscriber):
"""A setting that provides image names that have cropping masks"""
def __init__(
self,
text,
value="Do not use",
can_be_blank=False,
blank_text="Leave blank",
*args,
... |
4c8b5034df43f83116c96a0eca145777bca015b0bb5a42f50a06e053ad43e351 | Python | 660 | 21 |
class Environment:
def __init__(self,
pdb_root=None,
pssm_root=None,
dssp_root=None,
conservation_root=None,
dbnsfp_path=None,
gnomad_path=None,
device=None,
zero_miss... |
842ec361584044cbfed66c3ffdc9b034329b18979ac1f5209dc8803ee071fdda | Python | 660 | 25 | from ._file_image import FileImage
class FlexFrameImage(FileImage):
"""Provide an image by filename:frame, loading the file as it is requested
"""
def __init__(self,
name,
pathname,
filename,
series,
index,
... |
91bec42ffcf55249174c7eb7d9d11b0a153a1f70eb6a3684ce95542aae1dd6f9 | Python | 660 | 21 | # 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 writing, software
# distributed under the... |
4d928842bf0ff614164fc9ddabc258b862e2b1c1f583b676df59e5103ce500a1 | Python | 661 | 18 | from ._setting import Setting
class FigureSubscriber(Setting):
"""A setting that subscribes to a figure indicator provider
"""
def __init__(self, text, value="Do not use", *args, **kwargs):
super(Setting, self).__init__(text, value, *args, **kwargs)
def get_choices(self, pipeline):
c... |
6054a310efa43021d132d56fde9be638b46821f078e616f1eb885f011cf674b1 | Python | 662 | 25 | from enum import Enum
class DistanceMethod(str, Enum):
NONE = "None"
CENTROID = "Centroid"
MINIMUM = "Minimum"
BOTH = "Both"
class TemplateMeasurementFormat(str):
FF_PARENT = "Parent_%s"
FF_CHILDREN_COUNT = "Children_%s_Count"
# Centroid distance measurement (FF_DISTANCE % parent)
FF_C... |
e682790d92172f3e1e2f4c0f00a80b58445a23bdf37b740c7d371fad117092b4 | Python | 663 | 22 | from ptsa.data.readers import LocReader
import os.path as osp
import pandas as pd
class TestLocReader:
@classmethod
def setup_class(cls):
loc_file = osp.join(osp.dirname(__file__), 'data', 'localization.json')
cls.localization = LocReader(filename=loc_file).read()
def test_split(... |
db140f4623848214abbf21e6a062bc23d62409d5b679b46592aa6062309433ed | Python | 665 | 24 | import torch.nn as nn
class Interpolate(nn.Module):
def __init__(self, interp_kwargs=None):
"""
Initialize the function.
Args:
interp_kwargs (list, optional): Keyword arguments for initialization. Defaults to None.
"""
nn.Module.__init__(self)
if interp... |
149d568c2536b13647789a6585fed1a5861f041aef40b525a43f0eda8c9818ea | Python | 666 | 23 | import numpy as np
# define Izhikevich model
class Izhikevich:
def __init__(self, a, b, c, d, v_init=0.1, u_init=0.2, n_neurons=50):
self.a = a
self.b = b
self.c = c
self.d = d
self.v = np.full(n_neurons, v_init)
self.u = np.full(n_neurons, u_init)
def u... |
a82fc3e5feaca63533403da4aa979d55256910354b5be24a7e08f208fdc41d4e | Python | 666 | 21 | from ._name import Name
from ...._validation_error import ValidationError
class LabelName(Name):
"""
A setting that provides an image name
"""
def __init__(self, text, value="Do not use", *args, **kwargs):
super(LabelName, self).__init__(text, "objectgroup", value, *args, **kwargs)
def t... |
891e6f70355c27946c8e76f4338a5608d519da4d4f7732e5c501669db517212d | Python | 667 | 10 | data_param = {
'per_sys' : ["Be","B", "C", "N", "O", "F" , "Ne", "Na", "Mg", "Al", "Si", "P","S", "Cl", "Ar"
, "K", "Ca", "Sc", "Ti", "V", "Cr", "Mn", "Fe", "Co", "Ni", "Cu", "Zn", "Ga", "Ge", "As", "Se"
, "Br", "Kr", "Rb", "Sr", "Y", "Zr", "Nb", "Mo", "Tc", "Ru", "Rh", "Pd", "Ag", "C... |
ab99a7cbcaad1d3a9e5dff57151b5d7a1d8cdc4be50722b5abad1d7e0b61e638 | Python | 667 | 16 |
import datetime
from ipyparallel import Client
rc = Client(profile="benchmark.")
# rc.get_result('77cdf201-5925-4199-bdd8-0eae0d833d2a')
# incomplete = rc.db_query({'completed' : None}, keys=['msg_id', 'started'])
completed = rc.db_query(
{'completed': {'$ne': None}}, keys=['msg_id', 'started', 'completed',
... |
8ea60952da4a5990bba6cfa23d9bd2b94453eb35c0909b1059e937fedd9ba91e | Python | 670 | 17 | from ._grayscale_image import GrayscaleImage
from ._image import Image
from ._image_set import ImageSet
from ._image_set_list import ImageSetList
from ._rgb_image import RGBImage
from .abstract_image import AbstractImage
from .abstract_image import CallbackImage
from .abstract_image import ColorImage
from .abstract_ima... |
d0f29ff54f6159d67719277751192499f9ef6e99e60fb40fcee9c90bef8d4212 | Python | 670 | 25 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Util functions for megsim.
"""
import IPython
def _ipython_setup(enable_reload=False, use_qt5=True, matplotlib_qt=True):
"""Performs some IPython magic if we are running in IPython"""
try:
__IPYTHON__
except NameError:
return
from IPy... |
02d4bb22b64aeaec285065e9dd55754c3c2498a95ee9b13c19c257f699d00809 | Python | 673 | 22 | import keras.backend as K
import tensorflow as tf
def depth_loss_function(y_true, y_pred, theta=0.1, maxDepthVal=1000.0/10.0):
# Point-wise depth
l_depth = K.mean(K.abs(y_pred - y_true), axis=-1)
# Edges
dy_true, dx_true = tf.image.image_gradients(y_true)
dy_pred, dx_pred = tf.image.image_gra... |
2072a4c80f6776d2fff197967b1139c7606673db4da90402c382b29ebabbb698 | Python | 673 | 20 | """
@author: Johanna Rahm
Research group Heilemann
Institute for Physical and Theoretical Chemistry, Goethe University Frankfurt a.M.
Save localizations of single frames found by DeepSTORM2D to one csv file. Filter out localizations below a
confidence threshold.
"""
import os
def save(dir_path, threshold, locs):
... |
0db44a84291cd4d9f684524940c218dba272e779276087129824fa66ac918498 | Python | 674 | 34 | from cellprofiler_core.constants.measurement import (
C_URL,
C_FILE_NAME,
C_PATH_NAME,
C_OBJECTS_URL,
C_OBJECTS_FILE_NAME,
C_OBJECTS_PATH_NAME,
)
from cellprofiler_core.preferences import (
DEFAULT_INPUT_FOLDER_NAME,
DEFAULT_OUTPUT_FOLDER_NAME,
NO_FOLDER_NAME,
ABSOLUTE_FOLDER_NAM... |
9566a6847e71b57c7d6fff1b5b45e22b114ccdff690723f71414755d8f2d1b2b | Python | 674 | 17 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
1be2e513e14182c8d540624d2a0732728de17f4c829b9be3227c0d29e8e32159 | Python | 675 | 16 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
d43fa95778c18f37eae966089086e05142475bbd6482ce257128549f2734a8a3 | Python | 679 | 26 | from ._dependency import Dependency
class ImageDependency(Dependency):
"""A dependency on an image"""
def __init__(
self,
source_module,
destination_module,
image_name,
source_setting=None,
destination_setting=None,
):
super(type(self), self).__init... |
0dfc9661ac5e84b7aefbf985e30cf75a2a0ca10e0213be1b59c23721e0e1f81f | Python | 680 | 22 | from pdb2sql import pdb2sql
import numpy
from deeprank.operate.pdb import get_pdb_path
def __compute_feature__(environment, cutoff_distance, featgrp, variant):
pdb_path = get_pdb_path(environment.pdb_root, variant.pdb_ac)
pdb = pdb2sql(pdb_path)
try:
chain_ids = sorted(set(pdb.get("chainID")))... |
fee403497fb2c3fef136eb26973abfc14f6b3d172faf927301e77655b0008ee1 | Python | 681 | 31 | # -*- coding: utf-8 -*-
"""
Created on Fri Aug 9 10:23:56 2019
@author: Xiaoxuan Jia
"""
import numpy as np
from scipy.optimize import curve_fit
from scipy.ndimage import gaussian_filter
def fit_exp(rsc_time_matrix, color):
intr = np.abs(rsc_time_matrix)
tmp = np.nanmean(intr, axis=0)
n=intr.... |
3825e074401352e243cbd74eb5050072d8f148c52b4cb89bcb51ebbe8ec2fe94 | Python | 682 | 45 | class TestFileImage:
def test_series(self):
pass
def test_series(self):
pass
def test_channel(self):
pass
def test_channel(self):
pass
def test_index(self):
pass
def test_index(self):
pass
def test_get_name(self):
pass
def te... |
bdae368d06763abcfa8f4210c03944deddd2b9b20c5cc81a5b58666209910781 | Python | 682 | 17 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
4e7b091987a09067467c7d57d9bbb0970b9ab1e066892c84edd15d33265d3f26 | Python | 684 | 22 | import tensorflow as tf
import tensorflow.keras.backend as K
def depth_loss_function(y_true, y_pred, theta=0.1, maxDepthVal=1000.0/10.0):
# Point-wise depth
l_depth = K.mean(K.abs(y_pred - y_true), axis=-1)
# Edges
dy_true, dx_true = tf.image.image_gradients(y_true)
dy_pred, dx_pred = tf.imag... |
84a2ed2d5f2eb25d3731a9f7db01b2bf99cad6bf8b3882ea3e02c0b552760d14 | Python | 685 | 35 | import math
import numpy as np
from scipy.integrate import odeint
from scipy.interpolate import interp1d
import matplotlib.pyplot as plt
def calcW(Y):
# This function converts Y (which is after Hale transformation) to W.
def dWdY(W,Y):
dWdY = np.sqrt(1.65894)*np.exp(1.0/3.0*W**3)
return dWdY
... |
e8a30525ebd497e88061f3d875924a3f1fb96a1fecedd744b3dfa86a108a0887 | Python | 686 | 20 | from torch.optim.lr_scheduler import _LRScheduler
from torch import optim
import numpy as np
class CosineWarmupScheduler(optim.lr_scheduler._LRScheduler):
def __init__(self, optimizer, warmup, max_iters):
self.warmup = warmup
self.max_num_iters = max_iters
super().__init__(optimizer)
... |
d87e3d7db3f13c230d829507b3caab7d9560f25b85f779b2400cafdb40c62d30 | Python | 687 | 25 |
class Atom:
def __init__(self, id_, position, chain_id, name, element, residue=None, altloc=None, occupancy=None):
self.id = id_
self.name = name
self.element = element
self.chain_id = chain_id
self.position = position
self.residue = residue
self.altloc = al... |
0d9da6f4b794f430eb215bc8144211dc8d52db94687a5234b1525b7c7e7ca18e | Python | 689 | 19 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
aba93b89ba11332d2d604ab9d7f046ed21addb6dd7799040de9911d292328362 | Python | 689 | 26 | def show_image(image, grayscale = True, ax=None, title=''):
if ax is None:
plt.figure()
plt.axis('off')
if len(image.shape) == 2 or grayscale == True:
if len(image.shape) == 3:
image = np.sum(np.abs(image), axis=2)
vmax = np.percentile(image, 99)
... |
ac54f3ecd042d3558ea9fa05b8dfeb97fc91adb12d1ef868bcfb344e39f3a7c2 | Python | 690 | 24 | from ._change_setting_event import ChangeSettingEvent
class BeforeChangeSettingEvent(ChangeSettingEvent):
"""Indicates that a setting is about to change, allows a listener to cancel the change
"""
def __init__(self, old_value, new_value):
ChangeSettingEvent.__init__(self, old_value, new_value)
... |
96cd43e8d5db8adfb96732af9ad3e1794224b0ef983e4a71c6458061a13492dc | Python | 691 | 30 | from scipy.stats import circmean,circvar
from cmath import phase
from numpy import array
from scipy.stats import circmean,circvar,circstd
from numpy import *
from cmath import phase
from matplotlib.pylab import *
def len2(x):
if type(x) is not type([]):
if type(x) is not type(array([])):
return -1
return len(... |
a3541d0a2a9a2cff22927cc92b5a95274e8145cc4f4c940fe727e8278e62a4d0 | Python | 692 | 21 | import matplotlib.pyplot as plt
import numpy as np
if __name__ == "__main__":
event_times = np.arange(1, 20, 2.5)
event_times += np.random.randn(len(event_times))*0.5
fig = plt.figure()
fig.set_size_inches(5.5, 1.25)
ax = fig.add_subplot(111)
ax.scatter(event_times, np.ones(event_times.shape),... |
bb42ff1499509a82958dab1226b5bee78ee327c62589fd51dc447b332e4f84d9 | Python | 693 | 24 | from enum import Enum
class HaralickFeatures(str, Enum):
AngularSecondMoment = "AngularSecondMoment",
Contrast = "Contrast",
Correlation = "Correlation",
Variance = "Variance",
InverseDifferenceMoment = "InverseDifferenceMoment",
SumAverage = "SumAverage",
SumVariance = "SumVariance",
... |
c5172c59668265047dd8f0024b95b4bf2eef9d89e4d6fcaa7b69a9248350e1d5 | Python | 693 | 45 | class TestRange:
def test_str_to_value(self):
pass
def test_value_to_str(self):
pass
def test_get_value(self):
pass
def test_set_value(self):
pass
def test_get_min_text(self):
pass
def test_get_min(self):
pass
def test_get_max_text(self):... |
deafdbc63bfbb06b575851942c38f5001dcdb71ec0dc73dcb64fecafa80be96a | Python | 694 | 32 | """
Run pipelines on imagesets to produce measurements.
"""
import sys
use_analysis = True
DEBUG = "DEBUG"
ANNOUNCE_DONE = "DONE"
###############################
# Request, Replies, Events
###############################
if sys.platform == "darwin":
pass
if __name__ == "__main__":
# This is an ugly hac... |
2d664867d82f742f4fa646968485edd65aedcb3ff6ce136dceaebd99d76d198a | Python | 695 | 21 | # This file is part of pyunicorn.
# Copyright (C) 2008--2026 Jonathan F. Donges and pyunicorn authors
# URL: <https://www.pik-potsdam.de/members/donges/software-2/software>
# License: BSD (3-clause)
#
# Please acknowledge and cite the use of this software and its authors
# when results are used in publications or publi... |
3776c63fcae6ffb3a86695e2f7fa782d7d9100dac227ca820de7c06f7e61758f | Python | 696 | 39 | class TestMeasurement:
def test_construct_value(self):
pass
def test_get_measurement_object(self):
pass
def test_get_category_choices(self):
pass
def test_get_category(self):
pass
def test_get_feature_name_choices(self):
pass
def test_get_feature_name... |
986041fcdb6bb65d9fb4309f18ea5fb5fe145090f6512fc6d812f79c2a6ca50e | Python | 696 | 21 | from ._directory import Directory
from ._filename import Filename
from ._text import Text
from .alphanumeric import Alphanumeric
from .alphanumeric import Character
from .alphanumeric import CropImageName
from .alphanumeric import ExternalImageName
from .alphanumeric import FileImageName
from .alphanumeric import GridN... |
ab4ac23d8ce25253f5e13cd61b6c627fd2d2e97b8f23f9c9066472284ca92103 | Python | 697 | 33 | # -*- coding: utf-8 -*-
import time
from pysteps.decorators import memoize
def test_memoize():
@memoize(maxsize=1)
def _slow_function(x, **kwargs):
time.sleep(1)
return x
for i in range(2):
out = _slow_function(i, hkey=i)
assert out == i
# cached result
t0 = time... |
a9498fefcd384f9ab5d17a33193b9abaee7d381f294bb5c17faa73671dc79c06 | Python | 699 | 26 | from ._dependency import Dependency
class ObjectDependency(Dependency):
"""A dependency on an object labeling"""
def __init__(
self,
source_module,
destination_module,
object_name,
source_setting=None,
destination_setting=None,
):
super(type(self), ... |
17ee4e6564e9a003a8d3987766c1dbfecbbf12c76ff0f9447e33dd757e3c07bf | Python | 705 | 22 | # -*- coding: utf-8 -*-
"""
Script used to install the pysteps data in a test environment and set a pystepsrc
configuration file that points to that data.
The test data is downloaded in the `PYSTEPS_DATA_PATH` environmental variable.
After this script is run, the `PYSTEPSRC` environmental variable should be set to
PY... |
26805b7578d69ffebf54a4f8df3b2bc8e476f50428b29b9b846eb23ad768cb03 | Python | 713 | 32 | """
/!\ WARNING - DEPRECATED /!\
utf16encode.py - encode unicode strings as escaped utf16
This is only used for pipeline version < 3 files
"""
def utf16decode(x):
"""Decode an escaped utf8-encoded string
"""
y = ""
state = -1
for z in x:
if state == -1:
if z == "\\":
... |
d9bc56681253895d8b8772af5cbba4a0c61b3de82d7f3d3fe14824a16a8411f5 | Python | 713 | 19 | from .b0_utils import B0Utils
from .dimensions import FitBox, FitToBox
from .dwi import (AssertDwiDimensions,
CheckDuplicatedBvecsInShell,
DetermineSHOrder,
DisplacementFieldToFieldmap,
DwiMetadataUtils,
ExtractShells,
... |
dd1cc580cea884d3721101a1c5d8dcc2a697b91dcad1e9c5205910399f8ece01 | Python | 713 | 20 | import numpy as np
from scipy.linalg import cho_solve_banded, solve_triangular
from ..utils.linalg import unband_matrix
def log_det_from_banded_cholesky(banded_cholesky):
diag_cholesky = banded_cholesky[0, :]
return 2 * np.sum(np.log(diag_cholesky))
def sum_elements_from_inv_banded_cholesky(inv_banded_chol... |
6fe526ab242b7a98ec298d1ce6c3687962fbe82084421c65acfc816568ae4b65 | Python | 714 | 30 | #!/usr/bin/env python2
import sys,os
if len(sys.argv)!=3:
print '<broadpeak file> <track name>'
sys.exit()
infile,outfile=sys.argv[1:]
# all values on 9th field are -1, exclude them
id=1
fout=open(outfile,'w')
with open(infile) as fin:
for line in fin:
lst=line.rstrip().split('\t')
fout.write('{0[0]}\t{0[1]... |
6ce30f3b0135abf032d1a70f78466889b21b13cc67644864a7b2602c856068d3 | Python | 715 | 22 | # this program makes sure each protein alignment has more sequences that "min_seqs".
import os
import sys
from shutil import copyfile
perc_sims = ["20","40","60","80","100"]
#perc_sims = ["40"]
min_seqs = 10
min_lines = min_seqs * 2
for perc_sim in perc_sims:
input_path = "../../data/PSICOV/aln_" + perc_sim + "/"
... |
b7e8f490498c32f39049d244f35c3962baf086a78a1b26b3f55c58335776e396 | Python | 716 | 34 | from enum import Enum
class BrightnessMode(str, Enum):
MAX_IMAGE = "Max of image"
MAX_POSSIBLE = "Max possible"
class LineMode(str, Enum):
INNER = "Inner"
OUTER = "Outer"
THICK = "Thick"
class SourceMode(str, Enum):
FROM_IMAGES = "Image"
FROM_OBJECTS = "Objects"
class OutlineMode(str, ... |
b4b95e14067ac17340b3b0355ef7d38e02b678696f99e99692e70bf331027eeb | Python | 718 | 16 | import pyControl.hardware as _h
import pyControl.audio as _a
class Audio_poke():
# Single IR beam, LED and Solenoid. Audio amplifier to drive speaker.
def __init__(self, port, rising_event = None, falling_event = None, debounce = 5):
assert port.DAC is not None, '! Audio poke needs port with DAC... |
1085c6c22a1230b4c254c16c10ffd905b07e978e69d7e5bae7f8e7a58324517d | Python | 720 | 20 | import pyControl.hardware as _h
class Stepper_motor():
def __init__(self, port=None, direction_pin=None, step_pin=None):
if port:
direction_pin = port.DIO_A
step_pin = port.DIO_B
self._direction = _h.Digital_output(direction_pin)
self._step = _h.Digital_outpu... |
aaf1c1cd4872a0d0faf52bb8ad11d6a36e9262842013fe6929daa619b99cb5ac | Python | 721 | 17 | from .asymmetric_loss import AsymmetricLossMultiLabel, AsymmetricLossSingleLabel
from .binary_cross_entropy import BinaryCrossEntropy
from .class_weights import (
CLASS_WEIGHT_METHODS,
CLASS_WEIGHT_METHOD_KINDS,
compute_class_weights,
load_class_stats,
load_class_weights,
resolve_class_weights,
... |
ee98a30ffb5e384a8dee6303eb35e0b76cf0d7f509546ba79b688e5fb36674b9 | Python | 722 | 23 | import numpy as np
import matplotlib.pyplot as plt
freq = 5.
time = np.arange(0., 1.0, 0.01)
times = time[np.sort(np.random.permutation(range(0, len(time)))[:40])]
sine = np.sin(2 * np.pi * freq * times)
fig = plt.figure()
fig.set_size_inches(5.5, 2.5)
ax = fig.add_subplot(111)
ax.plot(times, sine, color="dodgerblue... |
8fb60e35f16e3d0196b49b045c1c06ab96e8a648fc14e6ea33df20b7188ef911 | Python | 724 | 24 | import click
from .subcommands import cli_subcommands
from GANDLF.entrypoints import append_copyright_to_help
from GANDLF.utils import logger_setup
from GANDLF import version
@click.group()
@click.version_option(version, "--version", "-v", message="GANDLF Version: %(version)s")
@click.pass_context # Pass th... |
c67c79b0455ebadb1e7900416c5ad3f2b0d2b79da2d9d33e38ec674564e97bbe | Python | 725 | 31 | from scipy.stats import circmean,circvar
from cmath import phase
from numpy import array
from scipy.stats import circmean,circvar,circstd
from numpy import *
from cmath import phase
from matplotlib.pylab import *
warnings.filterwarnings("ignore")
def len2(x):
if type(x) is not type([]):
if type(x) is not type(arr... |
f32a23a0e4eecd049301097e58160b6b2eda0e6ab93f450a619639d36576e1bc | Python | 726 | 19 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
c0227c309d6265400fa52cc735845406ac9d1bcb3bc7221f56fdac25e0054a47 | Python | 727 | 21 | from ._abstract_image import AbstractImage
class CallbackImage(AbstractImage):
"""An image provider proxy that calls the indicated callback functions (presumably in your module) to implement the methods
"""
def __init__(self, name, image_provider_fn):
"""Constructor
name - na... |
139fc3319481c2f624bf5e961db4a8683be5c1f0fbb7a81c580afb5e500d3356 | Python | 731 | 17 | # This file is part of pyunicorn.
# Copyright (C) 2008--2026 Jonathan F. Donges and pyunicorn authors
# URL: <https://www.pik-potsdam.de/members/donges/software-2/software>
# License: BSD (3-clause)
#
# Please acknowledge and cite the use of this software and its authors
# when results are used in publications or publi... |
2bebb8f07d2033b025b3780b6bb3570d533661677501df682919c4ceca64344b | Python | 732 | 27 | from .._setting import Setting
class DoSomething(Setting):
"""Do something in response to a button press
"""
save_to_pipeline = False
def __init__(self, text, label, callback, *args, **kwargs):
super(DoSomething, self).__init__(text, "n/a", **kwargs)
self.__label = label
self... |
5850f5ea0e1db3fa7dc0e0dce98ffe0ab7fc38b7ab59b61daf6a7aafe007ca07 | Python | 733 | 22 | import numpy as np
class ThetaNeuron:
def __init__(self, tau, v_reset, v_th, v_init=0.0):
self.tau = tau
self.v_reset = v_reset
self.v_th = v_th
self.v = v_init
self.theta = np.random.uniform(low=0, high=2 * np.pi)
self.weights = np.random.normal(loc=0.0, scale=1.0)
... |
ef9534cf4607b9e086503e73c559905325e4302b4ec2fad0aaa3dd6bba5f2fb3 | Python | 733 | 31 | #!/usr/bin/env python2
import sys,os
if len(sys.argv)!=3:
print '<narrowpeak file> <track name>'
sys.exit()
infile,outfile=sys.argv[1:]
id=1
fout=open(outfile,'w')
with open(infile) as fin:
for line in fin:
lst=line.rstrip().split('\t')
fout.write('{0[0]}\t{0[1]}\t{0[2]}\tscorelst:[{0[6]},{0[7]},{0[8]}],id:{... |
5dbfdd801607791d7168556ccba0f040cbcea0e30dc6ad1a7b5ec19be127366b | Python | 735 | 29 | from typing import Any, Dict, Iterable, Union, Protocol, Type
try:
from typing import TypeAlias
except ImportError:
from typing_extensions import TypeAlias
try:
from typing import TypeVar
except ImportError:
from typing_extensions import TypeVar
import torch
import torch.optim
try:
from torch.opti... |
771bbb0240dc732a2db8b7efbdbcc7ef3ab783f19ac6a773592df99b877d1372 | Python | 735 | 23 | #First run cliprunlistopt.py to get to do list
import numpy as np
folder = './Inputs/SDC20220929_invivoCA1pyrs5/'
inputsToDO = folder+'inputsToDO.csv'
ypossdefault = list(np.arange(0,2000,200)) # check simulation.gridFieldStimulation
splittype = 'ysplit'
delimiter = ','
with open(inputsToDO,'r') as f:
inputsToDO... |
a900ecf83ac786d968e6b276bf259c366556c1fa38999512d0d9c1e0b3b5d18f | Python | 735 | 21 | class TargetTransform(object):
def __call__(self, target):
raise NotImplementedError()
def __repr__(self):
return str(self.__class__.__name__)
class DefaultTargetTransform(TargetTransform):
def __init__(self, class_augmentations):
super(DefaultTargetTransform, self).__init__()
... |
f156a111db8a944d448dbe9768bd2ac8954557919d93ce9f8cff804ed081b8f2 | Python | 735 | 31 | import torch
import torch.nn as nn
from torch import sin, cos
def rot_z(gamma):
return torch.tensor([[cos(gamma), -sin(gamma), 0], [sin(gamma), cos(gamma), 0], [0, 0, 1]], dtype=gamma.dtype)
def rot_y(beta):
return torch.tensor([[cos(beta), 0, sin(beta)], [0, 1, 0], [-sin(beta), 0, cos(beta)]], dtype=beta.d... |
1007ffefd49c5bb263e0edb03a8345ac6bbb9c719b64fe2698dfdec40fbda453 | Python | 739 | 28 | import os
import sys
import numpy as np
import networkx as nx
import itertools as it
import random as rd
import umap
import pickle as pk
import pandas as pd
ppi = pd.read_csv("input/ppi_symbol_lcc.csv"delimiter= ',',
skipinitialspace=True)
G_ppi = nx.from_pandas_edgelist(ppi, 'symbol1', 'symbol2')
G_ppi... |
c4e0997680a21ceb8f0bc0d409cc57cb976c9466e655225584292659665de842 | Python | 740 | 17 | import pandas as pd
filename = r"D:/merged.csv"
df = pd.read_csv(filename)
counts_gold = df.groupby(['gold', 'split'])['split'].size().unstack(fill_value=0).add_prefix('count_')
with pd.option_context('display.max_rows', None, 'display.max_columns', None):
print(counts_gold)
counts_gold = df.groupby(['CT_Visual_... |
a7deeb91b81b47f3a8a271289ba0052ef538034df2d28577a7efe194b4eeb382 | Python | 741 | 21 | # -*- coding: utf-8 -*-
import pytest
from datetime import datetime
from pysteps.io.archive import _generate_path
test_argvalues = [
("20190130_1200", "%Y/foo/%m", "./2019/foo/01"),
("20190225_1200", "%Y/foo/%m", "./2019/foo/02"),
("20190122_2222", "%Y/foo/%m", "./2019/foo/01"),
("20190130_1200", "%Y... |
1d25b335dab94bc3a6d66ee7ac71188fdb191b70927a156e361aa5811597751e | Python | 745 | 23 | import numpy as np
# define QIF model
class QIF:
def __init__(self, tau, v_reset, v_th, v_init=0.0, beta=0.5):
self.tau = tau
self.v_reset = v_reset
self.v_th = v_th
self.v = v_init
self.beta = beta
self.num_ops = 0
def update(self, I, dt):
dvdt ... |
a4bc23c2492d2e8efc168b0e3c546e6d76f8b3b44860501dcf39108f0a649a70 | Python | 745 | 39 |
_args_template = """
POSITIONAL=()
while [ $# -gt 0 ]
do
key=\"$1\"
case $key in
{}
*)
POSITIONAL+=(\"$1\")
shift
;;
esac
done
"""
_named_template = """
{})
{}=\"$2\"
shift
shift
;;
"""
def build... |
20fe5109f0e857152b1ec8a5a2e56e9fb574d7cf396fe9c32e142a1a66846759 | Python | 746 | 25 | import numpy as np
# define AdEx model
class AdEX:
def __init__(self, tau_m, v_rheo, v_spike, delta_T, v_reset, v_init=0.0):
self.tau_m = tau_m
self.v_rheo = v_rheo
self.v_spike = v_spike
self.delta_T = delta_T
self.v_reset = v_reset
self.v = v_init
self.num_... |
859ed59ab4b1c2790943dd82b0d8f478b0a069362474280796a1aab81f20af69 | Python | 748 | 22 | # -*- coding: utf-8 -*-
import numpy as np
import pytest
from numpy.testing import assert_array_equal
from pysteps.utils import arrays
# compute_centred_coord_array
test_data = [
(2, 2, [np.array([[-1, 0]]).T, np.array([[-1, 0]])]),
(3, 3, [np.array([[-1, 0, 1]]).T, np.array([[-1, 0, 1]])]),
(3, 2, [np.a... |
5fb5cd11f615438fd5b837dcf7caa9c16619390c70a27f73ac95b05063021664 | Python | 751 | 18 | import numpy as np
class AdEX:
def __init__(self, tau_m, v_rheo, v_spike, delta_T, v_reset, v_init=0.0, n_neurons=1000):
self.tau_m = tau_m
self.v_rheo = v_rheo
self.v_spike = v_spike
self.delta_T = delta_T
self.v_reset = v_reset
self.v = np.full(n_neurons, v_init) ... |
9a75960c0028b022121366a11236134f7139907fc204bee32f5b2f79508e1d24 | Python | 752 | 34 | #!/usr/bin/env python
import time
import sys
from rgbmatrix import RGBMatrix, RGBMatrixOptions
from PIL import Image
if len(sys.argv) < 2:
sys.exit("Require an image argument")
else:
image_file = sys.argv[1]
image = Image.open(image_file)
# Configuration for the matrix
options = RGBMatrixOptions()
options.r... |
75341d05ec02a541e1abafec87ea568bc076889aefeff326b94d05de1d590167 | Python | 753 | 19 | import torch.nn as nn
from torchmeta.modules.module import MetaModule
from torchmeta.modules.utils import get_subdict
class MetaSequential(nn.Sequential, MetaModule):
__doc__ = nn.Sequential.__doc__
def forward(self, input, params=None):
for name, module in self._modules.items():
if isins... |
8cefb26c83f12f0db73960ef15d4ee91b7edd1933c50ea1f1a7a0bd82e42129b | Python | 754 | 21 | from typing import Optional, Union
from .config_manager import ConfigManager
def parseConfig(
config_file_path: Union[str, dict], version_check_flag: Optional[bool] = True
) -> None:
"""
This function parses the configuration file and returns a dictionary of parameters.
Args:
config_file_path... |
a4a9520558d2b824b8d5c6b526d7fa5dc98ce4cb48393b919a48455eb137d1cc | Python | 757 | 29 | from ...utilities.zmq.communicable.request import AnalysisRequest
class ExceptionReport(AnalysisRequest):
def __init__(
self,
analysis_id,
image_set_number,
module_name,
exc_type,
exc_message,
exc_traceback,
filename,
line_number,
):
... |
ab925cbc37f9861f768b89ead589bf6fda67430004658c92151798b589d06c1e | Python | 759 | 38 | # -*- coding: utf-8 -*-
#
# main.py
#
"""
Features selection and classifications
"""
__author__ = "Ahmed Albuni"
__email__ = "ahmed.albuni@gmail.com"
import argparse
import json
import imskaper.experiment.experiment as ex
import imskaper.validations.validate_config as validate
parser = argparse.ArgumentParser(
... |
02d7c3088426438b1d7c42cf5aa5677b2f5b3763d4deb3f07fa6b3b2ab2265f3 | Python | 761 | 33 | import numpy.testing
import skimage.restoration
import cellprofiler.modules.reducenoise
instance = cellprofiler.modules.reducenoise.ReduceNoise()
def test_run(image, module, image_set, workspace):
module.x_name.value = "example"
module.y_name.value = "ReduceNoise"
module.size.value = 7
module.dis... |
d06b3c0db3a1c67b9eaac854bed9bb9097612295ed4e49f03c177b71a27af2dc | Python | 761 | 18 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
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