sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
4af954ebdfdec851c7923b8fdd54ab37741d3087ad746cbb62eb94e4f1bcca87 | Python | 310 | 10 | from click.testing import CliRunner
from GANDLF.entrypoints.cli_tool import gandlf
from GANDLF.version import __version__
def test_version_command():
runner = CliRunner()
result = runner.invoke(gandlf, ["--version"])
assert result.exit_code == 0
assert __version__ in result.output
|
0784d211087473b88d854ac21d9a05006be7cd33fb2705ca116ac997458bb9be | Python | 314 | 7 | """Classes modelling MEG sensor arrays"""
from .base import ConstraintPenalty, SensorArray, noise_max, noise_mean
from .BarbuteArray import BarbuteArray, GoldenRatioError
from .BarbuteArraySL import BarbuteArraySL
from .BarbuteArrayScalp import BarbuteArrayScalp
from .BarbuteArraySLGrid import BarbuteArraySLGrid |
6bd457e46d418e93091a55928e0625b688539292a95057628ab3983921dc2d18 | Python | 315 | 10 | from ._alphanumeric import Alphanumeric
from ._character import Character
from .name import CropImageName
from .name import ExternalImageName
from .name import FileImageName
from .name import GridName
from .name import ImageName
from .name import LabelName
from .name import Name
from .name import OutlineImageName
|
527a110ad21c067d38a604b24596fa3bc1387e3b2e1fe9b51e6f4799dc29f887 | Python | 316 | 9 | from enum import Enum
class SmoothingMethod(str, Enum):
FIT_POLYNOMIAL = "Fit Polynomial"
MEDIAN_FILTER = "Median Filter"
GAUSSIAN_FILTER = "Gaussian Filter"
SMOOTH_KEEPING_EDGES = "Smooth Keeping Edges"
CIRCULAR_AVERAGE_FILTER = "Circular Average Filter"
SM_TO_AVERAGE = "Smooth to Average" |
662b613621d77b5c8847dea9d59926d6fba75ed1989c203527868050a38330ac | Python | 317 | 16 |
class AminoAcid:
def __init__(self, name, code, letter):
self.name = name
self.code = code
self.letter = letter
def __repr__(self):
return self.name
def __eq__(self, other):
return self.name == other.name
def __hash__(self):
return hash(self.name)
|
6ff099ba255e4576fd80cd6f962fad9ca14a121b6887b96ed74090695588acea | Python | 317 | 10 | import numpy
from deeprank.models.variant import PdbVariantSelection
def __compute_target__(variant, target_group):
if type(variant) != PdbVariantSelection:
raise TypeError("PdbVariantSelection expected, got {}".format(type(variant)))
target_group.create_dataset("target1", data=numpy.array(1.0))
|
93e6b47f474e0edac4438559ebd3d2abbcc627a2e3aaa101c6cc7e2ac1243180 | Python | 317 | 9 | from ._file_image import FileImage
from ._flex_frame_image import FlexFrameImage
from ._movie_frame_image import MovieFrameImage
from ._stk_frame_image import STKFrameImage
from .url import ColorImage
from .url import MaskImage
from .url import MonochromeImage
from .url import ObjectsImage
from .url import URLImage
|
fe55dee558b8f66a5ba0f2dcd462096eb923d9af08a491fd3f5a3cbb7270ebcc | Python | 318 | 13 | import os
import sys
__file__ = globals()['javax.script.filename']
macro_path = os.path.dirname(__file__)
sys.path.append(macro_path)
from fwhm_of_spots import main
from ij import IJ
test_imp = IJ.openImage(os.path.join(macro_path, "test", "test_img.tif"))
main(test_imp, 50,7,20, os.path.join(macro_path, "test")) |
dbae3ca9b776910a9e5f7a929b1cc8282b276751322b3bfd3e7d199b7ac25aa2 | Python | 320 | 10 | class IntegerPreference(object):
"""User interface info for an integer preference
This signals that a preference should be displayed and edited as
an integer, optionally limited by a range.
"""
def __init__(self, minval=None, maxval=None):
self.minval = minval
self.maxval = maxval
|
6a5b138785319c391182f6061db5995312f8d6b506e944a3d19bee274aaa247e | Python | 321 | 12 | from .preprocess import preprocess_pipeline, preprocess_pipeline_fixed
from .dataset import PreprocessedDataset
from .file_queue import FileQueue
from .augment import augment_batch
__all__ = [
'preprocess_pipeline',
'preprocess_pipeline_fixed',
'PreprocessedDataset',
'FileQueue',
'augment_batch',
]... |
c508ed419ea7a08579d89852a541c5e388fdf01648e47ca4f697a9062729b5b8 | Python | 321 | 25 | """
test_pcrp
----------------------------------
Tests for `pcrp` module.
"""
import unittest
from pcrp import pcrp
class Testpcrp(unittest.TestCase):
def setUp(self):
pass
def test_something(self):
pass
def tearDown(self):
pass
if __name__ == '__main__':
unittest.main()... |
8d18b7ee90a3e79634c14b5a71a5765e1b47b8348e5b98e98925e95625d7a731 | Python | 325 | 21 | class TestCoordinates:
def test_set_value(self):
pass
def test_get_value(self):
pass
def test_get_x_text(self):
pass
def test_get_x(self):
pass
def test_get_y_text(self):
pass
def test_get_y(self):
pass
def test_test_valid(self):
... |
310f95dc30d2429ef9f378ca73460a963dc293d44b54acad6f18bced631518e7 | Python | 327 | 15 | from unittest import TestCase
import os
from .timer import Timer
class TestTimer(TestCase):
def test_init(self):
t = Timer(100)
self.assertEqual(t.time_threshold,100)
def test_time(self):
t = Timer(10)
t1 = t.start
if t.is_time():
self.assertNotEqual(t.start,... |
e2986a6ce43c27dd5aef0017dae95292f18fd07fdecddca823776efed89de0c0 | Python | 327 | 11 | # -- coding: utf-8 --
"""Methods for verification of deterministic, probabilistic and ensemble forecasts."""
from .interface import get_method
from .detcatscores import *
from .detcontscores import *
from .ensscores import *
from .plots import *
from .probscores import *
from .spatialscores import *
from .salscores im... |
9a600c1abd6a09d06b73e698c85e526cdd9c5b66cdec18c4ed4decc41758079f | Python | 328 | 8 | def test_oja():
"""Test if Oja learns from a cloud"""
import neurodynex3.ojas_rule.oja as oja
nr_samples = 5
cloud = oja.make_cloud(n=nr_samples, ratio=1.234, angle=56.789)
wcourse = oja.learn(cloud)
assert wcourse.shape == (nr_samples, 2),\
"oja.learn(cloud) did not return shape=(nrSamp... |
526dc6ccc19fb2fce0dc02316b2d0a60c57347ca9281e11643078709dfea8f62 | Python | 330 | 15 | from setuptools import find_packages, setup
setup(
name="perlin-numpy",
packages=find_packages(),
include_package_data=True,
python_requires='>=3',
url="https://github.com/pvigier/perlin-numpy",
author="pvigier",
license="MIT",
install_requires=[
"numpy>=1.15"
],
zip_saf... |
7127ab067fd7ec655c60bd83390c100a43675990707ca1aad9eedeca01a19d4e | Python | 334 | 9 | """
Author: Mingjian He <mh1@stanford.edu>
exact_inference module contains basic dynamic programming algorithms used in SOMATA
"""
from .dp_func import forward_backward, baum_welch, viterbi, logdet, logdet_torch, \
kalman, djkalman, djkalman_conv_torch, inverse, inverse_torch # noqa: F401
from .em import run_em ... |
cff1fd386637ee0c837f18e730761611504fcb73274c221da644895d0e9aab48 | Python | 334 | 12 | # -*- coding: utf-8 -*-
"""
Methods for browsing data archives, reading 2d precipitation fields and writing
forecasts into files.
"""
from .interface import get_method, discover_importers, importers_info
from .archive import *
from .exporters import *
from .importers import *
from .nowcast_importers import *
from .rea... |
f519675219e6853e0bcecc3d7425bdf70256e1dc4b9193556252aed1cf61d5da | Python | 334 | 15 | import numpy as np
re = np.array([1e-5,1e-4,1e-3,1e-2,1e-1])
freq = 50 #freq of disc electrode
omega = freq * np.pi*2 # Rotational freq
nu = 1e-6 #s^-1 kinematic viscosity
L = 0.51023*omega**1.5*nu**(-0.5)
D = 1e-9 # m^2 s^-1, diffusion coefficients
script_L = L * re**3 / D # The dimensionless form of L
p... |
86af8262ab32824dc8849b699a2232438db77afbf3fe50153e0f455164c0c10a | Python | 335 | 15 | from ._event import Event
class PipelineLoaded(Event):
"""Indicates that the pipeline has been (re)loaded
"""
def __init__(self):
super(PipelineLoaded, self).__init__(
is_pipeline_modification=True, is_image_set_modification=True
)
def event_type(self):
return "P... |
ebcfe302a91ae2785dc9407841904ee66397653ee6d355b7b67dccfb4f38a4c0 | Python | 337 | 12 | from cellprofiler_core.utilities.zmq.communicable.request._request import Request
class LockStatusRequest(Request):
"""A request for the status on some locked file
uid - the unique ID stored inside the file's lock
"""
def __init__(self, uid, **kwargs):
self.uid = uid
Request.__init__... |
05cea8895a6453a5722e04734a2b52d1b58e6d53138dd8818c6047d858c2fbe6 | Python | 338 | 31 | from numpy import *
flip=True
type_ori = False
w1=pi/30
w2=pi/2
xxx=arange(0,pi-w2/2,w1)
xxx2=xxx+w2/2
xxx_f=arange(0,pi-w2/2,w1)
xxx2_f =xxx_f +w2/2
xxx2_f = degrees(xxx2_f)
xxx_uf=arange(-pi,pi,w1)
xxx2_uf =xxx_uf +w2/2
xxx2_uf = degrees(xxx2_uf)
if flip:
xxx=xxx_f
else:
xxx=xxx_uf
xxx2 =xxx +w2/2
xxx... |
695b05c6ab6f6a16d7c2e616c70290506c84c719364bcae08a3733e7fe7999d3 | Python | 338 | 15 | #!/usr/bin/env python3
"""
The ciftify package uses tools from the Human Connectome Project (HCP)
adapted for working with non-HCP datasets
"""
from . import config
from . import utils
from . import html
from . import qc_config
from . import niio
from . import filenames
from . import meants
from . import report
#from ... |
454b448e63353d1c2d5f7b5f685bdae10c6ada3b1a4d0f884c48b3498409c5d2 | Python | 339 | 10 | from ._do_something import DoSomething
class RemoveSettingButton(DoSomething):
"""A button whose only purpose is to remove something from a list."""
def __init__(self, text, label, list, entry, **kwargs):
super(RemoveSettingButton, self).__init__(
text, label, lambda: list.remove(entry), ... |
b606f2d1442d01b985881987454b0f51bbee0abaa860896030a7c6294be2b5aa | Python | 339 | 4 | from torchmeta.transforms.categorical import Categorical, FixedCategory
from torchmeta.transforms.augmentations import Rotation, HorizontalFlip, VerticalFlip
from torchmeta.transforms.splitters import Splitter, ClassSplitter, WeightedClassSplitter
from torchmeta.transforms.target_transforms import TargetTransform, Defa... |
ff98ed39e1cfd2208106cc40936f3b7a2259cfd0f6f4dba3ecbc90117a30fdd1 | Python | 339 | 13 | from ..functions.image_processing import overlay_objects
def overlayobjects(
image, labels, opacity=0.3, max_label=None, seed=None, colormap="jet"
):
return overlay_objects(
image=image,
labels=labels,
opacity=opacity,
max_label=max_label,
seed=seed,
colormap... |
1a449679fd8b33df5cebfbc60f827d7490016f0348c8689dd848a9c3a8f33be1 | Python | 340 | 21 | class TestImageSet:
def test_get_image(self):
pass
def test_providers(self):
pass
def test_get_image_provider(self):
pass
def test_remove_image_provider(self):
pass
def test_clear_image(self):
pass
def test_names(self):
pass
def test_add(... |
d9bb9cacb72899e18a0ac85b41e3d1bf46511bc7bac9c927f595c0d18477e2ca | Python | 341 | 19 | from .config import (
TrainerConfig,
DataConfig,
ModelConfig,
ExperimentConfig,
OptimizerConfig,
ExperimentRunManager,
_validate_choices,
)
__all__ = [
"TrainerConfig",
"DataConfig",
"ModelConfig",
"ExperimentConfig",
"OptimizerConfig",
"ExperimentRunManager",
"_... |
5cdb21d9b134e4ba8e7aae451382e8087212dbf0f4f09fab6e3f0637b644fe1f | Python | 343 | 9 | from .exportacquisitioncsv import export_acquisition_csv
from .mcdfolder2imcfolder import mcdfolder_to_imcfolder
from .ome2analysis import omefile_2_analysisfolder, omefolder_to_analysisfolder
from .ome2histocat import (
omefile_to_histocatfolder,
omefile_to_tifffolder,
omefolder_to_histocatfolder,
)
from .... |
f5d1ba2e64d4207a5912f116cbafb15e3d8fb885d9a469160e4662f491275d18 | Python | 343 | 11 | from ._setting import Setting
class Divider(Setting):
"""The divider setting inserts a vertical space, possibly with a horizontal line, in the GUI"""
save_to_pipeline = False
def __init__(self, text="", line=True, doc=None):
super(Divider, self).__init__(text, "n/a", doc=doc)
self.line =... |
8e040929d12d4c167473a08584a108c93af86cab10403200d75ee6c3e13364ad | Python | 344 | 14 |
import numpy as np
from scipy.ndimage import center_of_mass
from mrHARDI.compute.math.linalg import homo_vec
def center_of_mass_difference(
_arr1, _arr2, _aff2to1=np.eye(4), _spacing=np.ones((3,))
):
_cm1 = center_of_mass(_arr1)
_cm2in1 = (_aff2to1 @ homo_vec(center_of_mass(_arr2)))[:3]
return (_cm... |
a6d01a9cb416f62320407802ef1bd895b21bb2105de5deee138f2dd85d19e5ef | Python | 344 | 19 | from enum import Enum
class ConversionMethod(str, Enum):
COMBINE = "Combine"
SPLIT = "Split"
class ImageChannelType(str, Enum):
RGB = "RGB"
HSV = "HSV"
CHANNELS = "Channels"
class Channel(str, Enum):
RED = "Red"
GREEN = "Green"
BLUE = "Blue"
HUE = "Hue"
SATURATION = "Saturati... |
b208745ad807d33dca000f62de39fcbe983525345ba7161bbca9a8acaf8230b1 | Python | 345 | 12 | class Config:
def __init__(self):
self.input_path = ''
self.output_path = ''
self.cpu_worker_num = 32
# file suffix of final url
self.file_type = '_genomic.fna.gz'
self.csv_col = 'urls'
# times of re-downloads
self.retry_times = 10
... |
77085044a3f86d6e222d06e89c0e93d917a32ad5f36c5e0305d84551f910353a | Python | 347 | 12 | from ._integer import Integer
from ...._validation_error import ValidationError
class OddInteger(Integer):
def test_valid(self, pipeline):
super(self.__class__, self).test_valid(pipeline)
value = self.str_to_value(self.value_text)
if value % 2 == 0:
raise ValidationError("Mus... |
5b1d5862e2a7bb13f46e03798fdad0594937703e3e5c9fe1137701fbbc6f4e98 | Python | 349 | 10 | from pydantic import BaseModel, ConfigDict, Field
from typing_extensions import Any
class PostProcessingConfig(BaseModel):
model_config = ConfigDict(extra="forbid", exclude_none=True)
fill_holes: Any = Field(default=None)
mapping: dict = Field(default=None)
morphology: Any = Field(default=None)
cc... |
ee843e40a3642fe5f78b959e5af7cd63af6ccd298b3b04d47d5a8450384d68f7 | Python | 350 | 7 | # Graphical user interface settings.
update_interval = 20 # Interval between calls to the GUIs update function (ms).
event_history_len = 200 # Length of event history to plot (# events).
state_history_len = 100 # Length of state history to plot (# states).
analog_history_dur = 12 # Duration of analog sig... |
244931f55ed460f95191ed0ea20df84a9d0de5cb89a9d50f087a2cbebba59408 | Python | 352 | 13 | from unittest import TestCase
from .transforms import Crop
import numpy as np
class TestTransfroms(TestCase):
def test_crop(self):
xx = np.linspace(0, 1, 512)
yy = np.linspace(0, 1, 512)
X,Y = np.meshgrid(xx,yy)
Z = X**2+Y**2
crop = Crop(100,100,50,50,graph_mode=False)
... |
4f41ec2da65aa25339c8ff1c1476397037e6a0b3549dfdb15d2922e06e1d060e | Python | 353 | 11 | def secs_to_timestr(duration):
dur = int(round(duration))
hours = dur // (60 * 60)
rest = dur % (60 * 60)
minutes = rest // 60
rest %= 60
seconds = rest
minutes = ("%02d:" if hours > 0 else "%d:") % minutes
hours = "%d:" % (hours,) if hours > 0 else ""
seconds = "%02d" % seconds
... |
5f63f5c42c3c38f1d5b9e95fac7840b9ad9acffd97b3b01a94ecef13ef839e6c | Python | 353 | 15 | from ._event import Event
class PipelineCleared(Event):
"""Indicates that all modules have been removed from the pipeline
"""
def __init__(self):
super(PipelineCleared, self).__init__(
is_pipeline_modification=True, is_image_set_modification=True
)
def event_type(self):
... |
209714d9b7ff78fc492ff58b8cfe38616cafe55e24ca6a85b69700e890774771 | Python | 357 | 14 | from unittest import TestCase
from .csv import csv_to_dict
import io
def create_split_file():
# TODO: create a mock of a split.txt file. Check here:
data = {'1000':'train', "1021":"val"}
# this should go into a mock file that is used in the utils.csv_to_dict
pass
class Test(TestCase):
def test_cs... |
63eba759f0d84d954192ee2598ff9a946e620bbab8995e9a453eb61679afa285 | Python | 357 | 21 | class TestObjectSet:
def test_add_objects(self):
pass
def test_get_object_names(self):
pass
def test_get_objects(self):
pass
def test_all_objects(self):
pass
def test_get_types(self):
pass
def test_add_type_instance(self):
pass
def test_g... |
d42163841ec875f770d1c9179725702be74304a62572e5eb0e2fae45d2633c0e | Python | 357 | 11 | from pydantic import BaseModel, Field
from typing_extensions import Literal
TYPE_OPTIONS = Literal["uniform", "label"]
class PatchSamplerConfig(BaseModel):
type: TYPE_OPTIONS = Field(default="uniform")
enable_padding: bool = Field(default=False)
padding_mode: str = Field(default="symmetric")
biased_s... |
d8323ac7e5a07ec9f0ae90f6df1bbd1afb4ad86d70df4d552fa32e8f7e14a256 | Python | 357 | 13 | import torch.nn as nn
import math
class Embeddings(nn.Module):
def __init__(self, d_model, vocab):
super(Embeddings, self).__init__()
# weight matrix, each row present one word
self.lut = nn.Embedding(vocab, d_model)
self.d_model = d_model
def forward(self, x):
return ... |
1e831aa9cd246882c310aeec9a036d9c908fb3cd8784588c0dcc64a2930e29e4 | Python | 359 | 20 | # Preprocessing
DATA_DIR = 'EGFR'
CLASS_NUM = 1
TRAIN_LIST = 'train_EGFR.csv'
TEST_LIST = 'test_EGFR.csv'
# Data
IMAGE_HEIGHT = 320
IMAGE_WIDTH = 320
IMAGE_CHANNEL = 3
# Train
BATCH_SIZE = 64
TRAIN_ITERATION = 100000
SAVE_INTERVAL = 1000
CHECKPOINT_DIR = 'resnet_50'
# Test
RESTORE_FROM = 'EGFR/resnet_50/model.ckpt-3... |
3ce781a0f8da20e32759f34875a4b69d88092a22b90005632c9734b8379b5ff3 | Python | 359 | 11 | from ..functions.image_processing import reduce_noise
def reducenoise(image, patch_size, patch_distance, cutoff_distance, channel_axis=None):
denoised = reduce_noise(
image,
patch_size=patch_size,
patch_distance=patch_distance,
cutoff_distance=cutoff_distance,
channel_axis=c... |
b0ee757032cf3a7854d03056e9aa85680ebe898ad92f86507b50d3b739f1f0a1 | Python | 360 | 11 | # The same structure with the open-mmlab/mmclassification (https://github.com/open-mmlab/mmclassification)
# from .inference import inference_model, init_model
from .test import single_gpu_test
from .train import init_random_seed, set_random_seed, train_model
__all__ = [
'set_random_seed', 'train_model',
'si... |
088dbc0dcef53554f4747604e6deafd798a3f3fe1bc01727e6dc15ef1489d4a4 | Python | 361 | 5 | from .utils import merge_pdfs, object_from_dict, to_categorical_np, flatten_dict
from .plotting import plot_mapping_prediction, plot_mapping_predicted_contours, plot_acdc_prediction, plot_iou_histograms, plot_confmat
from .inference_utils import pad_to_next_multiple_of_32, summarize_results
from .pretty_print import pr... |
c39e606a31a2c27e110eef1b121a1516c3a4b2fbd94d8be8ee7c977b7e1b5955 | Python | 362 | 6 | from ._image_name_subscriber_multichoice import ImageNameSubscriberMultiChoice
from ._measurement_multichoice import MeasurementMultiChoice
from ._multichoice import MultiChoice
from ._object_subscriber_multichoice import ObjectSubscriberMultiChoice
from ._subdirectory_filter import SubdirectoryFilter
from ._subscriber... |
4aa3310d343026fd3c5fee932c6b44e9cf1b546066d6497a29cccf3f20543653 | Python | 363 | 19 | from pyunicorn import Network, mpi
def do_one():
net = Network.Model("BarabasiAlbert", n_nodes=100, n_links_each=10)
return net.global_clustering()
def master():
n = 1000
for i in range(0, n):
mpi.submit_call("do_one", ())
s = 0
for i in range(0, n):
s += mpi.get_next_result(... |
20c46ce86f7bd25fa33d051b4f05830d4d0aa851a868eed08548da81d032af10 | Python | 364 | 21 | class TestImageSetList:
def test_add_provider_to_all_image_sets(self):
pass
def test_count(self):
pass
def test_get_groupings(self):
pass
def test_get_image_set(self):
pass
def test_load_state(self):
pass
def test_purge_image_set(self):
pass
... |
bbd05ae4eddada91c3297beed79fdaea384556453d421e660fe0ddbc90b87191 | Python | 364 | 15 | import numpy.random
from cellprofiler_core.image import GrayscaleImage
from cellprofiler_core.image import Image
class TestGrayscaleImage:
def test_pixel_data(self):
data = numpy.random.random((224, 224, 3))
image = Image(data)
grayscale_image = GrayscaleImage(image)
assert gra... |
a091748454d20d201e93ab2a8fe3c0d966ea7c2b13dfcf9e3911f36e83c4783e | Python | 365 | 9 | from .cosine_lr import CosineLRScheduler
from .multistep_lr import MultiStepLRScheduler
from .plateau_lr import PlateauLRScheduler
from .poly_lr import PolyLRScheduler
from .step_lr import StepLRScheduler
from .tanh_lr import TanhLRScheduler
from .wsd_lr import WSDLRScheduler
from .scheduler_factory import create_sche... |
d569f01aef5bfbc0f6794428a88096b06d03b06b9d03f0523519bf3645c94abf | Python | 365 | 15 | """Miscellaneous utility functions."""
from .arrays import *
from .cleansing import *
from .conversion import *
from .dimension import *
from .images import *
from .interface import get_method
from .interpolate import *
from .fft import *
from .pca import *
from .reprojection import *
from .spectral import *
from .tap... |
b1d36982de78b0f42bb0378a96af26e462d46dbf658f69e7a18b5ae0eb21ecd6 | Python | 366 | 16 | from ._number import Number
class Float(Number):
"""
A class that only allows floating point input
"""
def str_to_value(self, str_value):
return float(str_value)
def value_to_str(self, value):
text_value = ("%f" % value).rstrip("0")
if text_value.endswith("."):
... |
be3f74edb92cee03830ed400e42f2a76452297fd90cd9255e922b6effa0aa8e0 | Python | 366 | 24 | class TestStructuringElement:
def test_get_choices(self):
pass
def test_get_value(self):
pass
def test_set_value(self):
pass
def test_shape(self):
pass
def test_shape(self):
pass
def test_size(self):
pass
def test_size(self):
pass... |
70fa9d71d951c04b1208938fd39601891824df2f0aab74a7f0976cd9e9362078 | Python | 368 | 15 | #!/usr/bin/python
import pandas as pd
import numpy as np
df = pd.read_csv('split.txt')
print(df.describe())
VAL_LEN = 6
TEST_LEN = 23
for col in df.columns:
if col != 'CASES':
indices = np.random.choice(df.index,VAL_LEN+TEST_LEN,replace=False)
df[col].iloc[indices[:VAL_LEN]] = 'val'
df[col].i... |
05c5e18bd07a39298042fb67b572f2534dc9f3a3f457e974577d4763cfb9dcf6 | Python | 369 | 17 | author = "Allen Goodman"
copyright = "Copyright © 2003 - 2021 Broad Institute, Inc. All rights reserved."
exclude_patterns = ["build", "Thumbs.db", ".DS_Store"]
extensions = ["sphinx.ext.autodoc", "sphinx_rtd_theme"]
html_static_path = ["_static"]
html_theme = "sphinx_rtd_theme"
project = "CellProfiler-core"
rel... |
2af1a50f3c6c54243bbb793544f72e3dbf9cf18955e6aaeb0855a2ed4b855d8f | Python | 370 | 10 | """
Options and enums for RemoveHoles module
"""
# Note: RemoveHoles is a simple morphological operation module that doesn't require
# complex enums. The main configuration is handled through the diameter setting
# which is managed by the core framework.
# Currently no custom enums needed for RemoveHoles as it uses s... |
79d90fb789c045006e5e7091c80bd2989079bdf158a4f0f0e7d243a885b863b2 | Python | 370 | 10 | from ...utilities.zmq.communicable.request import AnalysisRequest
class MeasurementsReport(AnalysisRequest):
def __init__(self, analysis_id, buf, image_set_numbers=None):
AnalysisRequest.__init__(
self, analysis_id, buf=buf, image_set_numbers=image_set_numbers
)
if image_set_nu... |
bb0e10f8002a45135e2718064c4de5f1aa890a06fc135e7a32e1ccf4955253e4 | Python | 371 | 15 | import setuptools
with open("README.md", "r",encoding='utf-8') as fh:
long_description = fh.read()
setuptools.setup(
name="mlatticeabc",
version="0.0.1",
long_description=long_description,
url="https://github.com/mlatticeabc",
classifiers=[
"Programming Language :: Python :: 3.6",
... |
928276cdb31709a329f537127e81b65ab8d003edb4071e2494b462f25b403ddd | Python | 372 | 15 | # -*- coding: utf-8 -*-
"""
Created on Wed Aug 31 23:56:04 2022
@author: Manuel
"""
import os
in_dir = "G:/Masterarbeit/MonitRaw"
out_dir = "G:/Masterarbeit/MonitRawTif"
files = os.listdir(in_dir)
from PIL import Image
for file in files:
im = Image.open(os.path.join(in_dir, file))
im.save(os.pat... |
4f82009d9afbc9db63110989af65550a2a32f5f33840edd3f2f1c84b079938ea | Python | 374 | 13 | from cellprofiler_core.utilities.zmq.communicable._communicable import Communicable
class Reply(Communicable):
"""The counterpart to a Request.
All subclasses must accept keyword arguments to __init__() corresponding to
their attributes.
"""
def __init__(self, **kwargs):
# all keywords b... |
ac9d5074ceb103a4562b2b2263335b151c5908441caccf7533a0846ab513cef8 | Python | 374 | 13 | import matplotlib.pyplot
from ._choice import Choice
class Colormap(Choice):
"""Represents the choice of a colormap"""
def __init__(self, text, value="Default", *args, **kwargs):
names = matplotlib.pyplot.colormaps()
names.sort()
choices = ["Default"] + names
super(Colormap, ... |
3771fbbbd336ac151524c834df785096b39f8760a34ef6f5b6c90d2032ee6a1b | Python | 376 | 19 | # Copyright (C) 2014 SWIPO Project
#
# Authors (this file):
# Stefan Schinkel <stefan.schinkel@gmail.com>
"""
Provides simple type check for resistive networks
"""
import numpy as np
from pyunicorn import ResNetwork
res = ResNetwork.SmallTestNetwork()
def testAdmittiveDegreeType():
print("testing types")
... |
c04b9c424bca38f15b028a414775a727c5331f8e41b83d391114ebdbf89492f5 | Python | 376 | 13 | from ptsa.data import MatlabIO
import os.path as osp
import pytest
@pytest.fixture
def filename():
return osp.join(osp.dirname(__file__),'data','test_events.mat')
def test_read_matlab_struct(filename):
events = MatlabIO.read_single_matlab_matrix_as_numpy_structured_array(filename,'events')
assert len(even... |
2af376da16d242a26c085890432ca2ee19b8f27f28363320d23682ad247c6f74 | Python | 378 | 14 | import pandas as pd
def read(name):
df = pd.read_csv(name)
RSME = df['RMSE_test'].mean()
SD_RMSE = df['RMSE_test'].std()
R2 = df['R2_test'].mean()
SD_R2 = df['R2_test'].std()
print('RMSE is {}, SD of RMSE is {}\nR2 is {}, SD of R2 is {}'.format(RSME, SD_RMSE, R2, SD_R2))
read('liporesults.cs... |
ae2ad77b85b9f9b20016d9799f34f1f6219fa70ad4fc411079bbb03e53312d90 | Python | 378 | 20 | from enum import Enum
class Scheme(str, Enum):
RGB = "RGB"
CMYK = "CMYK"
STACK = "Stack"
COMPOSITE = "Composite"
LEAVE_THIS_BLACK = "Leave this black"
DEFAULT_COLORS = [
"#%02x%02x%02x" % color
for color in (
(255, 0, 0),
(0, 255, 0),
(0, 0, 255),
(128, 128,... |
b8ec588cf751e8df19a283ebf4c1fceae54bd38594f56da431a5a17b10ce22ee | Python | 380 | 15 | from ._event import Event
class ModuleShowWindow(Event):
"""A module had its "show_window" state changed
module - the module that had its state changed
"""
def __init__(self, module):
super(self.__class__, self).__init__(is_pipeline_modification=True)
self.module = module
def ev... |
5859e00a2717f5aeec3730d8d33a9919cfcd63a63e00816675130a608e264eca | Python | 388 | 11 | import re
from collections import OrderedDict
def get_subdict(dictionary, key=None):
if dictionary is None:
return None
if (key is None) or (key == ''):
return dictionary
key_re = re.compile(r'^{0}\.(.+)'.format(re.escape(key)))
return OrderedDict((key_re.sub(r'\1', k), value) for (k, v... |
c128a6797d4defc8e521bfe8349af5908a1417f092408c20873d824ec4d390b8 | Python | 391 | 14 | from cellprofiler_core.utilities.zmq.communicable.reply._reply import Reply
class LockStatusReply(Reply):
"""A reply to the LockStatusRequest
self.uid - the unique ID of the locked file
self.locked - true if locked, false if not
"""
def __init__(self, uid, locked, **kwargs):
Reply.__init... |
2e49f1bdd2d7c2cebb87454cfb8e30d510109c19912b05db49a7e7f2798d5136 | Python | 392 | 14 |
from calculate_multicollinearity import *
from train_models import *
from evaluate_models_performance import *
from evaluate_feature_importance import *
from create_table_for_performance_results import *
from plot_results import *
calculate_multicollinearity()
train_models()
evaluate_models_performance()
evaluate_fea... |
838209756f74be7018c2e1239693edaa3fb711069b7f73c1af89bad49d354beb | Python | 394 | 12 | from setuptools import setup
setup(name='neurodevsim',
version='1.0.0',
description='Neural Development Simulator',
url='https://github.com/CNS-OIST/NeuroDevSim',
author='Erik De Schutter',
author_email='erik@oist.jp',
license='GNU General Public License Version 3.0',
packages... |
8851c029602c91506d895383965bdb7bde81ad193e9f3f1701cf813623cd84c1 | Python | 395 | 17 | __all__ = ['imread']
try:
import osgeo.gdal as gdal
except ImportError:
raise ImportError("The GDAL Library could not be found. "
"Please refer to http://www.gdal.org/ "
"for further instructions.")
def imread(fname, dtype=None):
"""Load an image from file.
... |
cdfe8c1576082f65385607adb8cf98def049227fe2b267f8c216e78238c28b5f | Python | 398 | 16 | #%%
# This script calculates accuracy of predicting the sex from head circumference,
# based on the overlap between male and female head circumference distributions.
from statistics import NormalDist
import numpy as np
# Bushby et al. 1992
standard_deviation = 1.41
delta_mean = 1.38
d = NormalDist(mu=... |
8c7c174c33731912c1eaff1df3e3fe22b574f122316ad8a0a441037a315b1ec9 | Python | 399 | 10 | import os
import sys
path = os.path.dirname(os.path.abspath(__file__))
for py in [f[:-3] for f in os.listdir(path) if f.endswith('Track.py') and f != '__init__.py']:
mod = __import__('.'.join([__name__, py]), fromlist=[py])
classes = [getattr(mod, x) for x in dir(mod) if isinstance(getattr(mod, x), type)]
... |
fe43f702b50814adf1deed27415f068b6a0faee3081864d26716b86d2ca018fb | Python | 400 | 13 | from monai.optimizers import WarmupCosineSchedule as WCS
def warmupcosineschedule(parameters):
parameters["scheduler"]["warmup_steps"] = parameters["scheduler"].get(
"warmup_steps", 0.1 * parameters["num_epochs"]
)
return WCS(
parameters["optimizer_object"],
t_total=parameters["nu... |
2923e6fed2a81bafc98e3419f8c4037edcf5f64a6c2cc65a04e1cd46d7758063 | Python | 401 | 21 | from cellprofiler_core.setting import Binary
class TestBinary:
def test_set_value(self):
setting = Binary("example", "yes")
setting.set_value("no")
assert not setting.value
def test_get_value(self):
setting = Binary("example", "yes")
assert setting.get_value()
... |
02dbe0f028334a19ef3eaa2d481734d2a1bcc850113301e77f8d9681ae29bbe6 | Python | 402 | 7 | from .dist_utils import (get_dist_info, auto_select_device, sync_random_seed,
setup_multi_processes, init_dist)
from .distribution import wrap_distributed_model, wrap_non_distributed_model
__all__ = ['get_dist_info', 'auto_select_device', 'sync_random_seed',
'setup_multi_processes',... |
05e618b586eab8e41f7857a52048c2ccb88e241dd9002563c2ec1660913b5bb6 | Python | 402 | 12 | from __future__ import annotations
from pathlib import Path
import requests
def urlretrieve(url: str, filepath: str | Path) -> None:
"""`requests`-based alternative to `urllib.request.urlretrieve`"""
with requests.get(url, stream=True) as r:
r.raise_for_status()
with open(filepath, "wb") as fp... |
79cf74b07d5deea8a605ddee16822e38b87ba1d3c15510aca381f69a4eda6429 | Python | 402 | 16 | import numpy
from ..functions.image_processing import rgb_to_greyscale, medial_axis
def medialaxis(image, multichannel, volumetric):
if multichannel:
image = rgb_to_greyscale(image)
if volumetric:
data = numpy.zeros_like(image)
for z, plane in enumerate(image):
data[z] = ... |
d58ffb8162ce9be916ed85ca39a6c460d7c6e1f2f2d80aa9a276b5747bd29c63 | Python | 403 | 12 | from ._abstract_image import AbstractImage
from ._callback_image import CallbackImage
from ._vanilla_image import VanillaImage
from .file import FileImage
from .file import FlexFrameImage
from .file import MovieFrameImage
from .file import STKFrameImage
from .file import ColorImage
from .file import MaskImage
from .fil... |
cf1ef41afa66b14024016a41a15a0a1dab6afa011019e86270b5475d6194f4a5 | Python | 405 | 14 | from .morphology import torch_morphological, fill_holes, cca
from .tensor import get_mapped_label
global_postprocessing_dict = {
"fill_holes": fill_holes,
"mapping": get_mapped_label,
"morphology": torch_morphological,
"cca": cca,
}
# append post_processing functions that are to be be applied after ... |
8f5d634268cddd4532404f1dd86a4548ec4444cae3be634cf0700dd0bde9c17b | Python | 406 | 13 | from .._setting import Setting
class Text(Setting):
"""A setting that displays as an edit box, accepting a string
"""
def __init__(self, text, value, *args, **kwargs):
kwargs = kwargs.copy()
self.multiline_display = kwargs.pop("multiline", False)
self.metadata_display = kwargs.po... |
890060181ef5274868798995ebd94b8454998addf1ca4eb56c9e9037dbe03096 | Python | 407 | 23 | """ locCSN is python package for calculating local cell specific networks."""
from .csn import (
DISTp,
which,
sparsetoid,
csntoflat,
id_concat,
idtosparse,
upperlower,
upperlower_dev,
upperlower_soft,
csn,
csn_rec,
csn_block,
csn_loc,
csn_rec_loc,
csn_block_... |
bc5b82bb86871a21afe65377c33a530b65174518ed9ad4ca06d0f46d288f088e | Python | 407 | 24 | class TestTreeChoice:
def test_default_fn_is_leaf(self):
pass
def test_get_path_parts(self):
pass
def test_encode_path_parts(self):
pass
def test_get_leaves(self):
pass
def test_get_subnodes(self):
pass
def test_get_selected_leaf(self):
pass
... |
514bcc8c5652bdfc12c44ab04b5ba89e13da147735637f5a2b1e7ab565abaea9 | Python | 410 | 17 | # -*- coding: utf-8 -*-
"""Add Conv Block for SDNet"""
def add_downsample_conv_block(
Conv, BatchNorm, in_ch=1, out_ch=1, kernel_size=3, stride=2, dilate=1, last=False
):
"""
Helper function
"""
pad = dilate if not last else 0
conv_1 = Conv(
in_ch, out_ch, kernel_size, stride=stride, p... |
740a621cf2faf46828c7f7aee7d0db7588941e3445315a9b67d9a067bde81a1c | Python | 411 | 15 | from .base import BaseFilter
from .butterworth import ButterworthFilter
from .data_chopper import DataChopper
from .monopolar_to_bipolar_mapper import MonopolarToBipolarMapper
from .morlet import MorletWaveletFilter
from .resample import ResampleFilter
__all__ = [
"BaseFilter",
"ButterworthFilter",
"DataCh... |
cb4f159e89ebda36562e9f48c09c29a95b86af48fcf102c6f4eb13efdbf7ade1 | Python | 411 | 24 | class TestObjectProcessing:
def test_add_measurements(self):
pass
def test_create_settings(self):
pass
def test_display(self):
pass
def test_get_categories(self):
pass
def test_get_measurement_columns(self):
pass
def test_get_measurements(self):
... |
0531599d3068a25d6ceecc892176936158f057023f2e76f5d916bd20a079d83b | Python | 413 | 18 | import numpy as np
# Check NumPy version once
NP_MAJOR_VERSION = int(np.__version__.split(".")[0])
# Set up aliases based on version
if NP_MAJOR_VERSION >= 2:
# NumPy 2.x aliases
np_product = np.prod
np_cumproduct = np.cumprod
np_NaN = np.nan
np_Inf = np.inf
else:
# NumPy 1.x aliases
np_pr... |
e4e7e47cb49c2af3b9fe537f463462e7f3babbc23b9ddeedb21dabf2d3138292 | Python | 413 | 19 | from ._event import Event
class ModuleEnabled(Event):
"""A module was enabled
module - the module that was enabled.
"""
def __init__(self, module):
"""Constructor
module - the module that was enabled
"""
super(self.__class__, self).__init__(is_pipeline_modification=T... |
58a6014f5fb54bb9d95b9beb5c33f0f91ee967d55077358ffec5c516f2d0edc8 | Python | 414 | 16 | """Directives and roles for documenting traitlets config options.
::
.. configtrait:: Application.log_datefmt
Description goes here.
Cross reference like this: :configtrait:`Application.log_datefmt`.
"""
def setup(app):
app.add_object_type('configtrait', 'configtrait', objname='Config option')... |
d588f727453e5948af9b9289f249ff9edc95f2a47ea5a84cc33e102452b47d4f | Python | 414 | 19 | from enum import Enum
class RelabelOption(str, Enum):
MERGE = "Merge"
SPLIT = "Split"
class MergeOption(str, Enum):
UNIFY_DISTANCE = "Distance"
UNIFY_PARENT = "Per-parent"
class MergingMethod(str, Enum):
DISCONNECTED = "Disconnected"
CONVEX_HULL = "Convex hull"
class ObjectIntensityMethod(st... |
222cc67fc985d212b81bdc3f99adc1f36c8c94415e655932e8d1ce7f21d3a5d5 | Python | 417 | 19 | from ._event import Event
class ModuleDisabled(Event):
"""A module was disabled
module - the module that was disabled.
"""
def __init__(self, module):
"""Constructor
module - the module that was enabled
"""
super(self.__class__, self).__init__(is_pipeline_modificatio... |
b4b2fb51a454a775617ce264e868f1e2fde71b9cca6e964fa485be2e8037b2fc | Python | 420 | 17 | from ._event import Event
class LoadException(Event):
"""An exception was caught during pipeline loading
"""
def __init__(self, error, module, module_name=None, settings=None):
self.error = error
self.cancel_run = True
self.module = module
self.module_name = module_name
... |
68f28ff7a7c46a642e2467cc41c033207d140c67a40a3d530ccee8b1e0d7f18c | Python | 422 | 10 | def test_runnable_get_trajectory():
"""Test if get_trajectory is runnable."""
from neurodynex3.phase_plane_analysis.fitzhugh_nagumo import get_trajectory
get_trajectory(v0=1., w0=2., I_ext=3., eps=0.4, a=5.0, tend=1.234)
def test_runnable_get_fixed_point():
"""Test if get_fixed_point is runnable."""
... |
e6e1679e94864243c29e9fc71c37219fc169c111450a4df81091ca001bd11659 | Python | 422 | 16 | import numpy as np
from numba import njit
@njit
def generate_design_matrix(batch_size, T):
"""
Generates an experimenmt wiht a random sequence of 4 conditions.
"""
obs_per_condition = int(T / 4)
context = np.zeros((batch_size, T), dtype=np.int32)
x = np.repeat([0, 1, 2, 3], obs_per_condition)
... |
78807bbccba38e67cebdb0413be82e0edf7a2407741436f43dae179fb8f40697 | Python | 426 | 20 |
import numpy as np
import pandas as pd
def normalize(data,
new_min=0,
new_max=1
):
old_range = data.max() - data.min()
new_range = new_max - new_min
new_data = (((data - data.min()) * new_range) / old_range) + new_min
return new_data
# a = (v... |
aa76617a7d36d3f96bdc54fb860d047a0b18c6600a302d1e9ffceeba0b64119c | Python | 429 | 7 | # lots of uses of these functions directly, ala 'import timm.optim.optim_factory as optim_factory', fun :/
from ._optim_factory import create_optimizer, create_optimizer_v2, optimizer_kwargs
from ._param_groups import param_groups_layer_decay, param_groups_weight_decay, group_parameters, _layer_map, _group
import war... |
758145ef0aa369e3335654d651e8957d7d44844e8fae1042cc49c8aacf89fd69 | Python | 430 | 17 | from ._event import Event
class ModuleAdded(Event):
"""A module was added to the pipeline
"""
def __init__(self, module_num, is_image_set_modification=False):
super(ModuleAdded, self).__init__(
is_pipeline_modification=True,
is_image_set_modification=is_image_set_modifica... |
e23d57a9745fb9a2eaf3ce548102eb89602b973cdc37ec284e057aa44db4b8c5 | Python | 431 | 17 | import os
import sys
def run_nose():
"""Runs nose tests, used mainly for anaconda deployment"""
import nose
nose_argv = sys.argv
nose_argv += ["--detailed-errors", "--exe", "-v"]
initial_dir = os.getcwd()
package_file = os.path.abspath(__file__)
package_dir = os.path.dirname(package_file)
... |
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