change distance calculation to use scipy.distance

Author: PaulDebus

traveling-salesman-portrait/traveling-salesman-portrait.py

@@ -16,8 +16,8 @@
 import numpy as np
 import urllib.request
 from PIL import Image
-from itertools import combinations
 from tsp_solver.greedy_numpy import solve_tsp
+from scipy.spatial.distance import pdist, squareform
 
 image_url = 'http://ereaderbackgrounds.com/movies/bw/Frankenstein.jpg'
 image_path = 'Frankenstein.jpg'
@@ -32,26 +32,8 @@
 black_indices = np.argwhere(bw_image_array == 0)
 chosen_black_indices = black_indices[np.random.choice(black_indices.shape[0], replace=False, size=10000)]
 
-distance_lookup = {}
-
-for (p1, p2) in combinations(range(len(chosen_black_indices)), r=2):
- p1 = tuple(chosen_black_indices[p1])
- p2 = tuple(chosen_black_indices[p2])
- x1, y1 = p1
- x2, y2 = p2
- distance_lookup[(p1, p2)] = math.sqrt((x2 - x1)**2 + (y2 - y1)**2)
- 
-distance_matrix = []
-for row_num in range(0, len(chosen_black_indices)):
- row_list = []
- for col_num in range(0, row_num):
- p1 = tuple(chosen_black_indices[row_num])
- p2 = tuple(chosen_black_indices[col_num])
- if (p1, p2) in distance_lookup:
- row_list.append(distance_lookup[p1, p2])
- else:
- row_list.append(distance_lookup[p2, p1])
- distance_matrix.append(row_list)
+distances = pdist(chosen_black_indices)
+distance_matrix = squareform(distances)
 
 optimized_path = solve_tsp(distance_matrix)