bug fix: missing values when generated

data/gan.py

@@ -594,6 +594,7 @@ class Predict(GNet):
                         #
                         # In case we are dealing with actual values like diagnosis codes we can perform 
                         #
+                        
                         INDEX = np.random.choice(np.arange(len(found)),1)[0]
                         INDEX = ratio.index(np.max(ratio))
                         df = found[INDEX]
@@ -609,7 +610,9 @@ class Predict(GNet):
                                 # let's get the missing rows (if any) ...
                                 #
                                 ii = df.apply(lambda row: np.sum(row) == 0 ,axis=1)
-                                if ii.shape[0] == 0 :
+                                # print ([' **** ',ii.sum()])
+
+                                if ii.shape[0] > 0 :
                                         #
                                         #@TODO Have this be a configurable variable
                                         missing = np.repeat(0, np.where(ii==1)[0].size)