71 lines
1.8 KiB
Python
71 lines
1.8 KiB
Python
import numpy as np
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from pyFTS import *
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def differential(original):
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n = len(original)
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diff = [ original[t-1]-original[t] for t in np.arange(1,n) ]
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diff.insert(0,0)
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return np.array(diff)
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def trimf(x,parameters):
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if(x < parameters[0]):
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return 0
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elif(x >= parameters[0] and x < parameters[1]):
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return (x-parameters[0])/(parameters[1]-parameters[0])
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elif(x >= parameters[1] and x <= parameters[2]):
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return (parameters[2]-x)/(parameters[2]-parameters[1])
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else:
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return 0
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def trapmf(x, parameters):
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if(x < parameters[0]):
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return 0
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elif(x >= parameters[0] and x < parameters[1]):
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return (x-parameters[0])/(parameters[1]-parameters[0])
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elif(x >= parameters[1] and x <= parameters[2]):
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return 1
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elif(x >= parameters[2] and x <= parameters[3]):
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return (parameters[3]-x)/(parameters[3]-parameters[2])
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else:
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return 0
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def gaussmf(x,parameters):
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return math.exp(-0.5*((x-parameters[0]) / parameters[1] )**2)
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def bellmf(x,parameters):
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return 1 / (1 + abs((xx - parameters[2])/parameters[0])**(2*parameters[1]))
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def sigmf(x,parameters):
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return 1 / (1 + math.exp(-parameters[0] * (x - parameters[1])))
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class FuzzySet:
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def __init__(self,name,mf,parameters,centroid):
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self.name = name
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self.mf = mf
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self.parameters = parameters
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self.centroid = centroid
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def membership(self,x):
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return self.mf(x,self.parameters)
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def __str__(self):
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return self.name + ": " + str(self.mf) + "(" + str(self.parameters) + ")"
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def GridPartitionerTrimf(data,npart,names = None,prefix = "A"):
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sets = []
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dmax = max(data)
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dmin = min(data)
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dlen = dmax - dmin
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partlen = dlen / npart
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partition = dmin
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for c in range(npart):
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sets.append( FuzzySet(prefix+str(c),trimf,[partition-partlen, partition, partition+partlen], partition ) )
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partition = partition + partlen
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return sets
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