[docs]deffuzzyfy(data,partitioner,**kwargs):""" A general method for fuzzyfication.
@@ -191,7 +190,8 @@
:keyword alpha_cut: the minimal membership value to be considered on fuzzyfication (only for mode='sets') :keyword method: the fuzzyfication method (fuzzy: all fuzzy memberships, maximum: only the maximum membership)
- :keyword mode: the fuzzyfication mode (sets: return the fuzzy sets names, vector: return a vector with the membership values for all fuzzy sets)
+ :keyword mode: the fuzzyfication mode (sets: return the fuzzy sets names, vector: return a vector with the membership
+ values for all fuzzy sets, both: return a list with tuples (fuzzy set, membership value) ) :returns a list with the fuzzyfied values, depending on the mode """alpha_cut=kwargs.get('alpha_cut',0.)
@@ -200,11 +200,26 @@
ifisinstance(data,(list,np.ndarray)):ifmode=='vector':returnfuzzyfy_instances(data,partitioner.sets,partitioner.ordered_sets)
+ elifmode=='both':
+ mvs=fuzzyfy_instances(data,partitioner.sets,partitioner.ordered_sets)
+ fs=[]
+ formvinmvs:
+ fsets=[(partitioner.ordered_sets[ix],mv[ix])
+ forixinnp.arange(len(mv))
+ ifmv[ix]>=alpha_cut]
+ fs.append(fsets)
+ returnfselse:returnfuzzyfy_series(data,partitioner.sets,method,alpha_cut,partitioner.ordered_sets)else:ifmode=='vector':returnfuzzyfy_instance(data,partitioner.sets,partitioner.ordered_sets)
+ elifmode=='both':
+ mv=fuzzyfy_instance(data,partitioner.sets,partitioner.ordered_sets)
+ fsets=[(partitioner.ordered_sets[ix],mv[ix])
+ forixinnp.arange(len(mv))
+ ifmv[ix]>=alpha_cut]
+ returnfsetselse:returnget_fuzzysets(data,partitioner.sets,partitioner.ordered_sets,alpha_cut)
@@ -90,8 +90,8 @@
"""The cluster method to be called when a new model is build"""self.cluster_params=kwargs.get('cluster_params',{})"""The cluster method parameters"""
- self.cluster=None
- """The most recent trained clusterer"""
+ self.cluster=kwargs.get('cluster',None)
+ """The trained clusterer"""self.fts_method=kwargs.get('fts_method',hofts.WeightedHighOrderFTS)"""The FTS method to be called when a new model is build"""
@@ -110,42 +110,46 @@
self.shortname="ClusteredMVFTS"self.name="Clustered Multivariate FTS"
+ self.pre_fuzzyfy=kwargs.get('pre_fuzzyfy',True)
+
[docs]defforecast_ahead(self,data,steps,**kwargs):generators=kwargs.get('generators',None)
- start=kwargs.get('start',0)ifgeneratorsisNone:raiseException('You must provide parameter \'generators\'! generators is a dict where the keys'+
@@ -270,7 +273,7 @@
@@ -104,6 +104,8 @@
"""In a multivariate context, the variable that contains this partitioner"""self.type=kwargs.get('type','common')"""The type of fuzzy sets that are generated by this partitioner"""
+ self.extractor=kwargs.get('extractor',lambdax:x)
+ """Anonymous function used to extract a single primitive type from an object instance"""self.ordered_sets=Noneifkwargs.get('preprocess',True):
@@ -176,7 +178,10 @@
"""returnself.sets[self.ordered_sets[-1]]
-