00db6a30ad
- Refactoring generate_flrg and train methods - Introducing batches and model saving on fit method
56 lines
1.4 KiB
Python
56 lines
1.4 KiB
Python
"""
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Composite Fuzzy Sets
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"""
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import numpy as np
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from pyFTS import *
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from pyFTS.common import Membership, FuzzySet
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class FuzzySet(FuzzySet.FuzzySet):
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"""
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Composite Fuzzy Set
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"""
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def __init__(self, name, superset=False):
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"""
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Create an empty composite fuzzy set
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:param name: fuzzy set name
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"""
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super(FuzzySet, self).__init__(name, None, None, None, type='composite')
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self.superset = superset
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if self.superset:
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self.sets = []
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else:
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self.mf = []
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self.parameters = []
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def membership(self, x):
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"""
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Calculate the membership value of a given input
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:param x: input value
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:return: membership value of x at this fuzzy set
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"""
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if self.superset:
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return max([s.membership(x) for s in self.sets])
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else:
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return min([self.mf[ct](x, self.parameters[ct]) for ct in np.arange(0, len(self.mf))])
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def append(self, mf, parameters):
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"""
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Adds a new function to composition
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:param mf:
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:param parameters:
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:return:
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"""
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self.mf.append(mf)
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self.parameters.append(parameters)
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def append_set(self, set):
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"""
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Adds a new function to composition
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:param mf:
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:param parameters:
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:return:
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"""
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self.sets.append(set) |