parallelized fuzzy logic code

fuzzylab/FuzzyInferenceSystem.py

@@ -46,7 +46,7 @@ def addRule(self, rule_matrix):
     def __addVariable(self, in_or_out, *varargin, **options):
         new_variable = fisvar(*varargin, **options)
 
-        if in_or_out == 'input':
+        if in_or_out is 'input':
             self.Inputs.append(new_variable)
             if(options.get('NumMFs')):
                 numMFs = options.get('NumMFs')
@@ -90,7 +90,7 @@ def __addVariable(self, in_or_out, *varargin, **options):
                     self.addMF(var_name, mf_type, params, Name='mf'+str(i+1))
                     b += step
 
-                if numMFs == 2:
+                if numMFs is 2:
                     i = 0
 
                 if(options.get('MFmaxr')):

fuzzylab/__init__.py

@@ -4,6 +4,7 @@
 from fuzzylab.trimf import trimf
 from fuzzylab.trapmf import trapmf
 from fuzzylab.defuzz import defuzz
+from fuzzylab.linspace import linspace
 from fuzzylab.arange import arange
 from fuzzylab.gbellmf import gbellmf
 from fuzzylab.gaussmf import gaussmf

fuzzylab/defuzz.py

@@ -1,15 +1,19 @@
 # defuzz.py
 # Eduardo Avelar
-# August 2022
+# October 2018
 
 import numpy as np
 
 def defuzz(x, y, defuzz_method):
-
+    x = x.reshape(len(x),1)
     if defuzz_method == 'centroid':
-        total_area = sum(y)
+        total_area = np.sum(y, axis = 0)
+        inner = np.sum(x*y, axis = 0)
+        output = sum(y * x) / total_area
         return sum(y * x) / total_area
+
     elif defuzz_method == 'bisector':
+        print("new version to be edited")
         total_area = sum(y)
         data_n = len(x)
         tmp = y[0]
@@ -19,12 +23,15 @@ def defuzz(x, y, defuzz_method):
                 break
         return x[k]
     elif defuzz_method == 'mom':
+        print("new version to be edited")
         return np.mean(x[y == max(y)])
     elif defuzz_method == 'som':
+        print("new version to be edited")
         tmp = x[y == max(y)]
         which = np.argmin(abs(tmp))
         return tmp[which]
     elif defuzz_method == 'lom':
+        print("new version to be edited")
         tmp = x[y == max(y)]
         which = np.argmax(abs(tmp))
         return tmp[which]