Source code for pyFTS.models.multivariate.common
import numpy as np
import pandas as pd
from pyFTS.common import FuzzySet, Composite
[docs]class MultivariateFuzzySet(Composite.FuzzySet):
"""
Multivariate Composite Fuzzy Set
"""
def __init__(self, name, **kwargs):
"""
Create an empty composite fuzzy set
:param name: fuzzy set name
"""
super(MultivariateFuzzySet, self).__init__(name)
self.sets = {}
self.target_variable = kwargs.get('target_variable',None)
[docs] def append_set(self, variable, set):
"""
Appends a new fuzzy set from a new variable
:param variable: an multivariate.variable instance
:param set: an common.FuzzySet instance
"""
self.sets[variable] = set
if variable == self.target_variable.name:
self.centroid = set.centroid
[docs] def set_target_variable(self, variable):
#print(self.target_variable, variable)
self.target_variable = variable
#print(self.centroid,self.sets[variable.name].centroid)
self.centroid = self.sets[variable.name].centroid
[docs] def membership(self, x):
mv = []
for var in self.sets.keys():
data = x[var]
mv.append(self.sets[var].membership(data))
return np.nanmin(mv)
[docs]def fuzzyfy_instance(data_point, var):
fsets = FuzzySet.fuzzyfy(data_point, var.partitioner, mode='sets', method='fuzzy', alpha_cut=var.alpha_cut)
return [(var.name, fs) for fs in fsets]
[docs]def fuzzyfy_instance_clustered(data_point, cluster, **kwargs):
alpha_cut = kwargs.get('alpha_cut', 0.0)
mode = kwargs.get('mode', 'sets')
fsets = []
for fset in cluster.knn(data_point):
if cluster.sets[fset].membership(data_point) > alpha_cut:
if mode == 'sets':
fsets.append(fset)
elif mode =='both':
fsets.append( (fset, cluster.sets[fset].membership(data_point)) )
return fsets