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# See "Writing benchmarks" in the asv docs for more information.
# https://asv.readthedocs.io/en/latest/writing_benchmarks.html
import numpy as np
from scipy import ndimage as ndi
from skimage import color, data, filters, graph, morphology
class GraphSuite:
"""Benchmark for pixel graph routines in scikit-image."""
def setup(self):
retina = color.rgb2gray(data.retina())
t0, _ = filters.threshold_multiotsu(retina, classes=3)
mask = retina > t0
vessels = filters.sato(retina, sigmas=range(1, 10)) * mask
thresholded = filters.apply_hysteresis_threshold(vessels, 0.01, 0.03)
labeled = ndi.label(thresholded)[0]
largest_nonzero_label = np.argmax(np.bincount(labeled[labeled > 0]))
binary = labeled == largest_nonzero_label
self.skeleton = morphology.skeletonize(binary)
labeled2 = ndi.label(thresholded[::2, ::2])[0]
largest_nonzero_label2 = np.argmax(np.bincount(labeled2[labeled2 > 0]))
binary2 = labeled2 == largest_nonzero_label2
small_skeleton = morphology.skeletonize(binary2)
self.g, self.n = graph.pixel_graph(small_skeleton, connectivity=2)
def time_build_pixel_graph(self):
graph.pixel_graph(self.skeleton, connectivity=2)
def time_central_pixel(self):
graph.central_pixel(self.g, self.n)
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