code: Comparing Wasserstein and Euclidean distance

code/lib/lmdk_sel.py

@@ -6,6 +6,7 @@ import exp_mech
 import numpy as np
 import random
 import time
+from scipy.spatial.distance import cdist
 
 
 '''
@@ -174,7 +175,8 @@ def get_opts_from_top_h(seq, lmdks):
         hist_tmp = np.copy(hist_cur)
         hist_tmp[i] += 1
         # Find difference from original
-        diff_cur = get_norm(hist, hist_tmp)
+        diff_cur = get_norm(hist, hist_tmp)  # Euclidean
+        # diff_cur = get_emd(hist, hist_tmp)  # Wasserstein
         # Remember if it is the best that you've seen
         if diff_cur < diff_min:
           diff_min = diff_cur
@@ -331,6 +333,12 @@ def find_lmdks(seq, lmdks, epsilon):
   return lmdks_new, epsilon - eps_sel
 
 def test():
+
+  A = np.array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])
+  B = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
+  print(get_norm(A, B))
+  exit()
+
   # Start and end points of the sequence
   # # Nonrandom
   # start = 1