Adding multivariate support on all partitioners

pyFTS/partitioners/CMeans.py

@@ -83,6 +83,9 @@ class CMeansPartitioner(partitioner.Partitioner):
 
     def build(self, data):
         sets = {}
+
+        kwargs = {'type': self.type, 'variable': self.variable}
+
         centroides = c_means(self.partitions, data, 1)
         centroides.append(self.max)
         centroides.append(self.min)
@@ -92,6 +95,6 @@ class CMeansPartitioner(partitioner.Partitioner):
             _name = self.get_name(c)
             sets[_name] = FuzzySet.FuzzySet(_name, Membership.trimf,
                                  [round(centroides[c - 1], 3), round(centroides[c], 3), round(centroides[c + 1], 3)],
-                                 round(centroides[c], 3))
+                                 round(centroides[c], 3), **kwargs)
 
         return sets

pyFTS/partitioners/Entropy.py

@@ -87,6 +87,8 @@ class EntropyPartitioner(partitioner.Partitioner):
     def build(self, data):
         sets = {}
 
+        kwargs = {'type': self.type, 'variable': self.variable}
+
         partitions = bestSplit(data, self.partitions)
         partitions.append(self.min)
         partitions.append(self.max)
@@ -96,13 +98,13 @@ class EntropyPartitioner(partitioner.Partitioner):
             _name = self.get_name(c)
             if self.membership_function == Membership.trimf:
                 sets[_name] = FuzzySet.FuzzySet(_name, Membership.trimf,
-                                              [partitions[c - 1], partitions[c], partitions[c + 1]],partitions[c])
+                                              [partitions[c - 1], partitions[c], partitions[c + 1]],partitions[c], **kwargs)
             elif self.membership_function == Membership.trapmf:
                 b1 = (partitions[c] - partitions[c - 1])/2
                 b2 = (partitions[c + 1] - partitions[c]) / 2
                 sets[_name] = FuzzySet.FuzzySet(_name, Membership.trapmf,
                                               [partitions[c - 1], partitions[c] - b1,
                                                partitions[c] + b2, partitions[c + 1]],
-                                              partitions[c])
+                                              partitions[c], **kwargs)
 
         return sets

pyFTS/partitioners/FCM.py

@@ -113,6 +113,8 @@ class FCMPartitioner(partitioner.Partitioner):
     def build(self, data):
         sets = {}
 
+        kwargs = {'type': self.type, 'variable': self.variable}
+
         centroids = fuzzy_cmeans(self.partitions, data, 1, 2)
         centroids.append(self.max)
         centroids.append(self.min)
@@ -124,13 +126,13 @@ class FCMPartitioner(partitioner.Partitioner):
                 sets[_name] = FuzzySet.FuzzySet(_name, Membership.trimf,
                                                 [round(centroids[c - 1], 3), round(centroids[c], 3),
                                                  round(centroids[c + 1], 3)],
-                                                round(centroids[c], 3))
+                                                round(centroids[c], 3), **kwargs)
             elif self.membership_function == Membership.trapmf:
                 q1 = (round(centroids[c], 3) - round(centroids[c - 1], 3)) / 2
                 q2 = (round(centroids[c + 1], 3) - round(centroids[c], 3)) / 2
                 sets[_name] = FuzzySet.FuzzySet(_name, Membership.trimf,
                                                 [round(centroids[c - 1], 3), round(centroids[c], 3) - q1,
                                                  round(centroids[c], 3) + q2, round(centroids[c + 1], 3)],
-                                                round(centroids[c], 3))
+                                                round(centroids[c], 3), **kwargs)
 
         return sets

pyFTS/partitioners/Huarng.py

@@ -32,6 +32,8 @@ class HuarngPartitioner(partitioner.Partitioner):
 
         sets = {}
 
+        kwargs = {'type': self.type, 'variable': self.variable}
+
         dlen = self.max - self.min
         npart = math.ceil(dlen / base)
         partition = math.ceil(self.min)
@@ -39,14 +41,14 @@ class HuarngPartitioner(partitioner.Partitioner):
             _name = self.get_name(c)
             if self.membership_function == Membership.trimf:
                 sets[_name] = FuzzySet.FuzzySet(_name, Membership.trimf,
-                                               [partition - base, partition, partition + base], partition)
+                                               [partition - base, partition, partition + base], partition, **kwargs)
             elif self.membership_function == Membership.gaussmf:
                 sets[_name] = FuzzySet.FuzzySet(_name, Membership.gaussmf,
                                               [partition, base/2], partition)
             elif self.membership_function == Membership.trapmf:
                 sets[_name] = FuzzySet.FuzzySet(_name, Membership.trapmf,
                                               [partition - base, partition - (base/2),
-                                               partition + (base / 2), partition + base], partition)
+                                               partition + (base / 2), partition + base], partition, **kwargs)
 
             partition += base
 

pyFTS/partitioners/Singleton.py

@@ -20,10 +20,10 @@ class SingletonPartitioner(partitioner.Partitioner):
     def build(self, data):
         sets = {}
 
-        for count, instance in enumerate(data):
-            _name = self.get_name(count)
-            sets[_name] = FuzzySet.FuzzySet(_name, Membership.singleton, [instance], instance)
-
         kwargs = {'type': self.type, 'variable': self.variable}
 
+        for count, instance in enumerate(data):
+            _name = self.get_name(count)
+            sets[_name] = FuzzySet.FuzzySet(_name, Membership.singleton, [instance], instance, **kwargs)
+
         return sets

pyFTS/tests/multivariate.py

@@ -72,7 +72,7 @@ print(_s2-_s1)
 Util.persist_obj(model, 'sonda_wmvfts')
 '''
 
-model = Util.load_obj('sonda_wmvfts')
+#model = Util.load_obj('sonda_wmvfts')
 
 '''
 from pyFTS.benchmarks import Measures
@@ -84,13 +84,13 @@ _s2 = time.time()
 print(_s2-_s1)
 '''
 
-print(len(model))
+#print(len(model))
 
 
 #
 
 #model.fit(data, distributed='dispy', nodes=['192.168.0.110'])
-'''
+#'''
 
 from pyFTS.models.multivariate import common, variable, mvfts, wmvfts, cmvfts, grid
 from pyFTS.models.seasonal import partitioner as seasonal
@@ -105,6 +105,11 @@ test_mv = dataset.iloc[24505:]
 
 sp = {'seasonality': DateTime.minute_of_day, 'names': [str(k)+'hs' for k in range(0,24)]}
 
+sp = {'seasonality': DateTime.day_of_week, 'names': ['mon','tue','wed','tur','fri','sat','sun']}
+
+vday = variable.Variable("DayOfWeek", data_label="date", partitioner=seasonal.TimeGridPartitioner, npart=7,
+                          data=train_mv, partitioner_specific=sp)
+
 vhour = variable.Variable("Hour", data_label="date", partitioner=seasonal.TimeGridPartitioner, npart=24,
                           data=train_mv, partitioner_specific=sp, data_type=pd.datetime, mask='%Y-%m-%d %H:%M:%S')