44 lines
1.3 KiB
Python
44 lines
1.3 KiB
Python
import numpy as np
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import math
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import random as rnd
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import functools, operator
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from pyFTS.common import FuzzySet, Membership, Transformations
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# K. H. Huarng, “Effective lengths of intervals to improve forecasting in fuzzy time series,”
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# Fuzzy Sets Syst., vol. 123, no. 3, pp. 387–394, Nov. 2001.
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from pyFTS.partitioners import partitioner
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class HuarngPartitioner(partitioner.Partitioner):
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def __init__(self, npart,data,func = Membership.trimf):
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super(HuarngPartitioner, self).__init__("Huarng",data,npart,func)
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def build(self, data):
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data2 = Transformations.differential(data)
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davg = np.abs( np.mean(data2) / 2 )
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if davg <= 1.0:
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base = 0.1
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elif 1 < davg <= 10:
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base = 1.0
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elif 10 < davg <= 100:
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base = 10
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else:
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base = 100
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sets = []
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dmax = max(data)
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dmax += dmax * 0.10
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dmin = min(data)
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dmin -= dmin * 0.10
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dlen = dmax - dmin
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npart = math.ceil(dlen / base)
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partition = math.ceil(dmin)
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for c in range(npart):
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sets.append(
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FuzzySet.FuzzySet(self.prefix + str(c), Membership.trimf, [partition - base, partition, partition + base], partition))
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partition += base
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return sets
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