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# Untitled

a guest Apr 18th, 2019 72 Never
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1.     def update_isolatedness(self, maxima, step, point_data_list):
2.         for maximum_a in maxima[:self.parameters['maxima_per_iter']]:
3.             distances = []
4.             for maximum_b in maxima:
5.                 distances.append(Util.distance_eu(maximum_a[0], maximum_b[0]))
6.             distances.sort()
7.             isolatedness = 0
8.             for d in distances[1:self.parameters['furthest_index']]:
9.                 isolatedness += d
10.             point_data_list.set(maximum_a, isolatedness, step)
11.
12.     def update_point_data_list(self, smoothed, sigma, step, point_data_list):
13.         """"""
14.         maxima = Util.local_maxima(smoothed)
15.         if sigma >= 0.5:
16.             maxima = gi.optimize_maxima(smoothed, maxima, sigma)
17.         maxima = Util.sort_list(maxima, 1, True)
18.         self.update_isolatedness(maxima, step, point_data_list)
19.
20.     def smooth_image(self, sigma, last_sigma, smoothed):
21.         if last_sigma == 0 or sigma <= last_sigma:
22.             smoothed = cv.GaussianBlur(self.matrix, Util.kernel_size(sigma), sigma)
23.         else:
24.             sigma_to_add = math.sqrt(pow(sigma, 2) - pow(last_sigma, 2))
26.         return smoothed
27.
28.     def compute_measure(self):
29.         """"""
30.         smoothed = None
31.         last_sigma = 0
32.         point_data_list = PointDataList(self.parameters['dist_thresh'])
33.
34.         for step in range(0, len(self.parameters['sigma_array'])):
35.             sigma = self.parameters['sigma_array'][step]
36.             smoothed = self.smooth_image(sigma, last_sigma, smoothed)
37.             last_sigma = sigma
38.             self.update_point_data_list(smoothed, sigma, step, point_data_list)
39.
40.         return point_data_list
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