Nonstationary Fuzzy Sets

pyFTS/nonstationary/common.py

@@ -36,12 +36,19 @@ class MembershipFunction(object):
         self.width_params = kwargs.get("width_params", None)
         self.noise = kwargs.get("noise", None)
         self.noise_params = kwargs.get("noise_params", None)
+        self.cache = {}
 
     def perform_location(self, t, param):
         if self.location is None:
             return param
 
-        inc = self.location(t, self.location_params)
+        if not isinstance(self.location, (list,set)):
+            self.location = [self.location]
+            self.location_params = [self.location_params]
+
+        l = len(self.location)
+
+        inc = sum([self.location[k](t, self.location_params[k]) for k in np.arange(0,l)] )
 
         if self.mf == Membership.gaussmf:
             #changes only the mean parameter
@@ -59,7 +66,13 @@ class MembershipFunction(object):
         if self.width is None:
             return param
 
-        inc = self.width(t, self.width_params)
+        if not isinstance(self.width, (list, set)):
+            self.width = [self.width]
+            self.width_params = [self.width_params]
+
+        l = len(self.width)
+
+        inc = sum([self.width[k](t, self.width_params[k]) for k in np.arange(0, l)])
 
         if self.mf == Membership.gaussmf:
             #changes only the variance parameter
@@ -68,12 +81,12 @@ class MembershipFunction(object):
             #changes only the smooth parameter
             return [param[0] + inc, param[1]]
         elif self.mf == Membership.trimf:
-            return [param[0] + inc, param[1], param[2] - inc]
+            return [param[0] - inc, param[1], param[2] + inc]
         elif self.mf == Membership.trapmf:
             l = (param[3]-param[0])
             rab = (param[1] - param[0]) / l
             rcd = (param[3] - param[2]) / l
-            return [param[0] + inc, param[1] + inc*rab, param[2] - inc*rcd, param[3] - inc]
+            return [param[0] - inc, param[1] - inc*rab, param[2] + inc*rcd, param[3] + inc]
         else:
             return param
 
@@ -84,11 +97,13 @@ class MembershipFunction(object):
         :return: membership value of x at this fuzzy set
         """
 
+        if t not in self.cache:
             param = self.parameters
             param = self.perform_location(t, param)
             param = self.perform_width(t, param)
+            self.cache[t] = param
 
-        tmp = self.mf(x, param)
+        tmp = self.mf(x, self.cache[t])
 
         if self.noise is not None:
             tmp += self.noise(t, self.noise_params)

pyFTS/nonstationary/util.py

@@ -0,0 +1,25 @@
+import numpy as np
+import pandas as pd
+import matplotlib as plt
+import matplotlib.colors as pltcolors
+import matplotlib.pyplot as plt
+from pyFTS.common import Membership, Util
+
+
+def plot_sets(uod, sets, num=10, tam=[5, 5], colors=None, save=False, file=None):
+    ticks = []
+    fig, axes = plt.subplots(nrows=1, ncols=1, figsize=tam)
+    for t in np.arange(0,num,1):
+        for ct, set in enumerate(sets):
+            x = [2*t + set.membership(v, t) for v in uod]
+            if colors is not None: c = colors[ct]
+            axes.plot(x, uod, c=c)
+        ticks.extend(["t+"+str(t),""])
+
+    axes.set_ylabel("Universe of Discourse")
+    axes.set_xlabel("Time")
+    plt.xticks([k for k in np.arange(0,2*num,1)], ticks, rotation='vertical')
+
+    plt.tight_layout()
+
+    Util.showAndSaveImage(fig, file, save)

pyFTS/partitioners/Util.py

@@ -11,6 +11,7 @@ all_methods = [Grid.GridPartitioner, Entropy.EntropyPartitioner, FCM.FCMPartitio
 
 mfs = [Membership.trimf, Membership.gaussmf, Membership.trapmf]
 
+
 def plot_sets(data, sets, titles, tam=[12, 10], save=False, file=None):
     num = len(sets)
     #fig = plt.figure(figsize=tam)

pyFTS/seasonal/common.py

@@ -1,7 +1,8 @@
 import numpy as np
 import pandas as pd
 from enum import Enum
-from pyFTS.common import FuzzySet
+from pyFTS.common import FuzzySet, Membership
+from pyFTS.partitioners import partitioner, Grid
 
 
 class DateTime(Enum):

pyFTS/tests/nonstationary.py

@@ -0,0 +1,20 @@
+import numpy as np
+from pyFTS.common import Membership
+from pyFTS.nonstationary import common,pertubation,util
+import importlib
+
+importlib.reload(util)
+
+uod = np.arange(0,20,0.1)
+
+kwargs = {'location': pertubation.linear, 'location_params': [1,0],
+          'width': pertubation.linear, 'width_params': [1,0]}
+
+mf1 = common.MembershipFunction('A1',Membership.trimf,[0,1,2], **kwargs)
+mf2 = common.MembershipFunction('A2',Membership.trimf,[1,2,3], **kwargs)
+mf3 = common.MembershipFunction('A3',Membership.trimf,[2,3,4], **kwargs)
+mf4 = common.MembershipFunction('A4',Membership.trimf,[3,4,5], **kwargs)
+
+sets = [mf1, mf2, mf3, mf4]
+
+util.plot_sets(uod, sets)

setup.py

@@ -1,7 +1,9 @@
 from distutils.core import setup
 setup(
   name = 'pyFTS',
-  packages = ['pyFTS','pyFTS.benchmarks','pyFTS.common','pyFTS.data', 'pyFTS.ensemble','pyFTS.models','pyFTS.models.seasonal','pyFTS.partitioners','pyFTS.probabilistic','pyFTS.tests'], 
+  packages = ['pyFTS','pyFTS.benchmarks','pyFTS.common','pyFTS.data', 'pyFTS.ensemble',
+              'pyFTS.models','pyFTS.seasonal','pyFTS.partitioners','pyFTS.probabilistic',
+              'pyFTS.tests','pyFTS.nonstationary'],
   package_data = {'benchmarks':['*'], 'common':['*'], 'data':['*'], 'ensemble':['*'], 'models':['*'], 'seasonal':['*'], 'partitioners':['*'], 'probabilistic':['*'], 'tests':['*']},
   version = '1.1.1',
   description = 'Fuzzy Time Series for Python',