Changeset 1102

Timestamp:

03/10/21 21:13:26 (4 years ago)

Author:

Maciej Komosinski

Message:

Do not fail when the dissimilarity matrix is not symmetric, print a warning message instead

File:

• framspy/FramsticksLib.py (modified) (3 diffs)

framspy/FramsticksLib.py

@@ -138 +138 @@
                 for i in range(n):
                         assert square_matrix[i][i] == 0, "Not a correct dissimilarity matrix, diagonal expected to be 0"
-                assert (square_matrix == square_matrix.T).all(), "Probably not a correct dissimilarity matrix, expecting symmetry, verify this"  # could introduce tolerance in comparison (e.g. class field DISSIMIL_DIFF_TOLERANCE=10^-5) so that miniscule differences do not fail here
+                non_symmetric_diff = square_matrix - square_matrix.T
+                non_symmetric_count = np.count_nonzero(non_symmetric_diff)
+                if non_symmetric_count > 0:
+                        non_symmetric_diff_abs = np.abs(non_symmetric_diff)
+                        max_pos1d = np.argmax(non_symmetric_diff_abs)  # location of largest discrepancy
+                        max_pos2d_XY = np.unravel_index(max_pos1d, non_symmetric_diff_abs.shape)  # 2D coordinates of largest discrepancy
+                        max_pos2d_YX = max_pos2d_XY[1], max_pos2d_XY[0]  # 2D coordinates of largest discrepancy mirror
+                        worst_guy_XY = square_matrix[max_pos2d_XY]  # this distance and the other below (its mirror) are most different
+                        worst_guy_YX = square_matrix[max_pos2d_YX]
+                        print("[WARN] Dissimilarity matrix: expecting symmetry, but %g out of %d pairs were asymmetrical, max difference was %g (%g %%)" %
+                              (non_symmetric_count / 2,
+                               n * (n - 1) / 2,
+                               non_symmetric_diff_abs[max_pos2d_XY],
+                               non_symmetric_diff_abs[max_pos2d_XY] * 100 / ((worst_guy_XY + worst_guy_YX) / 2)))  # max diff is not necessarily max %
                 return square_matrix
 
@@ -147 +160 @@
                 for g in genotype_list:
                         valid.append(frams.Geno.newFromString(g).is_valid._int() == 1)
-                assert len(genotype_list) == len(valid), "Submitted %d genotypes, received %d validity values" % (len(genotype_list), len(valid))
+                assert len(genotype_list) == len(valid), "Tested %d genotypes, received %d validity values" % (len(genotype_list), len(valid))
                 return valid
 
@@ -175 +188 @@
 
         parsed_args = parseArguments()
-        framsDLL = FramsticksLib(parsed_args.path, parsed_args.lib, parsed_args.simsettings)
+        framsLib = FramsticksLib(parsed_args.path, parsed_args.lib, parsed_args.simsettings)
 
         print("Sending a direct command to Framsticks library that calculates \"4\"+2 yields", frams.Simulator.eval("return \"4\"+2;"))
 
-        simplest = framsDLL.getSimplest('1' if parsed_args.genformat is None else parsed_args.genformat)
+        simplest = framsLib.getSimplest('1' if parsed_args.genformat is None else parsed_args.genformat)
         print("\tSimplest genotype:", simplest)
-        parent1 = framsDLL.mutate([simplest])[0]
+        parent1 = framsLib.mutate([simplest])[0]
         parent2 = parent1
         MUTATE_COUNT = 10
         for x in range(MUTATE_COUNT):  # example of a chain of 10 mutations
-                parent2 = framsDLL.mutate([parent2])[0]
+                parent2 = framsLib.mutate([parent2])[0]
         print("\tParent1 (mutated simplest):", parent1)
         print("\tParent2 (Parent1 mutated %d times):" % MUTATE_COUNT, parent2)
-        offspring = framsDLL.crossOver(parent1, parent2)
+        offspring = framsLib.crossOver(parent1, parent2)
         print("\tCrossover (Offspring):", offspring)
-        print('\tDissimilarity of Parent1 and Offspring:', framsDLL.dissimilarity([parent1, offspring])[0, 1])
-        print('\tPerformance of Offspring:', framsDLL.evaluate([offspring]))
-        print('\tValidity of Parent1, Parent 2, and Offspring:', framsDLL.isValid([parent1, parent2, offspring]))
+        print('\tDissimilarity of Parent1 and Offspring:', framsLib.dissimilarity([parent1, offspring])[0, 1])
+        print('\tPerformance of Offspring:', framsLib.evaluate([offspring]))
+        print('\tValidity of Parent1, Parent 2, and Offspring:', framsLib.isValid([parent1, parent2, offspring]))