97 lines
2.4 KiB
Python
97 lines
2.4 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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self.lower = min(parameters)
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self.upper = max(parameters)
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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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class FLR:
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def __init__(self,LHS,RHS):
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self.LHS = LHS
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self.RHS = RHS
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def __str__(self):
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return str(self.LHS) + " -> " + str(self.RHS)
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def fuzzyInstance(inst, fuzzySets):
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mv = np.array([ fs.membership(inst) for fs in fuzzySets])
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return mv
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def getMaxMembershipFuzzySet(inst, fuzzySets):
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mv = fuzzyInstance(inst,fuzzySets)
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return fuzzySets[ np.argwhere(mv == max(mv) )[0,0] ]
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def fuzzySeries(data,fuzzySets):
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fts = []
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for item in data:
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fts.append(getMaxMembershipFuzzySet(item,fuzzySets))
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return fts
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def generateNonRecurrentFLRs(fuzzyData):
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flrs = {}
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for i in range(2,len(fuzzyData)):
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tmp = FLR(fuzzyData[i-1],fuzzyData[i])
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flrs[str(tmp)] = tmp
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ret = [value for key, value in flrs.items()]
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return ret
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def generateRecurrentFLRs(fuzzyData):
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flrs = []
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for i in np.arange(1,len(fuzzyData)):
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flrs.append(FLR(fuzzyData[i-1],fuzzyData[i]))
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return flrs
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