Changed factorize to return error. The error value was being lost and could...

Changed factorize to return error.  The error value was being lost and could not be recalculated.  Global problem?

Multiplicative Algorithm/cSNMF.py

@@ -27,6 +27,7 @@ def sparsity_metric(H):
 
 
 def calculate_error(D, W, H):
+    norm_D = np.linalg.norm(D)
     return np.linalg.norm(D - N(W@H))/norm_D*100
 
 
@@ -39,7 +40,7 @@ def impose_L1_constraint(W, H):
 
 def axe_H(H, tail_cutoff = 0.25):
     H2 = H.copy()
-    for i, column in enumerate(H2.T):
+    for i, column in enumerate(H.T):
         sorted_column = sorted(column)
         cumulative_sum = it.accumulate(sorted_column)
         kill_count = sum(list(cumulative_sum) < tail_cutoff*sum(column))
@@ -51,14 +52,18 @@ def sort_WH(W, H):
     H2 = axe_H(H)
     weights = H2/sum(H2)
     signature_popularities = sum(weights.T)
-    signature_popularities = sorted(enumerate(signature_popularities), key = lambda x : x[1])
-    signature_popularities.reverse()
-    signature_popularities
+    signature_popularities = sorted(enumerate(signature_popularities), key = lambda x : x[1], reverse=True)
     W2 = W.copy()
     H3 = H2.copy()
     for i in range(len(signature_popularities)):
         W2[:, i] = W[:, signature_popularities[i][0]]
         H3[i] = H2[signature_popularities[i][0]]
+    try:
+        assert ( np.linalg.norm(W@H2 - W2@H3) / np.linalg.norm(W@H2) ) < 0.01
+    except AssertionError:
+        log.critical('Sorting is not working correctly')
+        return W2, H3
+    
     return W2, H3
 
 
@@ -130,7 +135,7 @@ def factorize(data_array,
     diff_H = 100
     
     global norm_D
-    norm_D = np.linalg.norm(D)
+    norm_D = np.linalg.norm(N(D))
     
     while abs(diff_W) + abs(diff_H) > threshold or iterations < 100:
         if iterations > max_iter:
@@ -177,4 +182,4 @@ def factorize(data_array,
     sparsity = sparsity_metric(H)
     log.info('Error= %s, Sparsity= %s', error, sparsity)
     
-    return W, H, results[column_names]
+    return W, H, results[column_names], error