Defined generative and expandAlignment as categorical columns

data/tableDisplay.py

@@ -25,12 +25,18 @@ def typeTableColumns( df ):
     if 'ops' in df.columns:
         df['ops'] = pd.Categorical(df['ops'], ["nothing", "delete", "replace", "refine", "add", "addjoin", "refadd"])
     if 'str' in df.columns:
-        df['str'] = pd.Categorical(df['str'], ["strgen", "strspc", "strrdm"])
+        df['str'] = pd.Categorical(df['str'], ['_',"strgen", "strspc", "strrdm"])
     if 'strenghen' in df.index.names:
-        df['strenthen'] = pd.Categorical(df['strenghen'], ["strgen", "strspc", "strrdm"])
-# MAY BE USED TO NORMALIZE
-#avg_tosv['generative'] = pd.Categorical(avg_tosv['generative'], ['_NOT_',1])
-#avg_tosv['expandAlignments'] = pd.Categorical(avg_tosv['expandAlignments'], ['memory','clever','_NOT_'])
+        df['strenthen'] = pd.Categorical(df['strenghen'], ['_',"strgen", "strspc", "strrdm"])
+    # ??
+    if 'generative' in df.columns or 'generative' in df.index.names:
+        df['generative'] = pd.Categorical(df['generative'], ['_NOT_','_','1'])
+    if 'expandAlignments' in df.columns or 'expandAlignments' in df.index.names:
+        df['expandAlignments'] = pd.Categorical(df['expandAlignments'], ['_','_NOT_','memory','clever'])
+    # Better keep these as strings...
+    #if 'immediateRatio' in df.columns or 'immediateRatio' in df.index.names:
+    #    df.replace({'immediateRatio':{'_':'0'}}, inplace = True)        
+    #    df['immediateRatio'] = df['immediateRatio'].astype(float)
 
 ###### STRIPPING COLUMNS