From 3356872eb91aa1ed889303e340a3877f7fd290f5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Petr=C3=B4nio=20C=C3=A2ndido?= Date: Mon, 22 Apr 2019 10:02:31 -0300 Subject: [PATCH] Documentation update --- .../pyFTS/models/multivariate/granular.html | 127 +++++++++++ .../pyFTS/models/multivariate/grid.html | 199 ++++++++++++++++++ 2 files changed, 326 insertions(+) create mode 100644 docs/build/html/_modules/pyFTS/models/multivariate/granular.html create mode 100644 docs/build/html/_modules/pyFTS/models/multivariate/grid.html diff --git a/docs/build/html/_modules/pyFTS/models/multivariate/granular.html b/docs/build/html/_modules/pyFTS/models/multivariate/granular.html new file mode 100644 index 0000000..13d874f --- /dev/null +++ b/docs/build/html/_modules/pyFTS/models/multivariate/granular.html @@ -0,0 +1,127 @@ + + + + + + + + + pyFTS.models.multivariate.granular — pyFTS 1.4 documentation + + + + + + + + + + + + + + + + +
+
+
+
+ +

Source code for pyFTS.models.multivariate.granular

+from pyFTS.models.multivariate import cmvfts, grid
+from pyFTS.models import hofts
+
+
+
[docs]class GranularWMVFTS(cmvfts.ClusteredMVFTS):
+    """
+    Granular multivariate weighted high order FTS
+    """
+
+    def __init__(self, **kwargs):
+        super(GranularWMVFTS, self).__init__(**kwargs)
+
+        self.fts_method = hofts.WeightedHighOrderFTS
+        self.model = None
+        """The most recent trained model"""
+        self.knn = kwargs.get('knn', 2)
+        self.order = kwargs.get("order", 2)
+        self.shortname = "GranularWMVFTS"
+        self.name = "Granular Weighted Multivariate FTS"
+
+
[docs]    def train(self, data, **kwargs):
+        self.partitioner = grid.IncrementalGridCluster(
+            explanatory_variables=self.explanatory_variables,
+            target_variable=self.target_variable,
+            neighbors=self.knn)
+        super(GranularWMVFTS, self).train(data,**kwargs)

+
+
+ +
+
+
+
+
+ + + + \ No newline at end of file diff --git a/docs/build/html/_modules/pyFTS/models/multivariate/grid.html b/docs/build/html/_modules/pyFTS/models/multivariate/grid.html new file mode 100644 index 0000000..d086d5d --- /dev/null +++ b/docs/build/html/_modules/pyFTS/models/multivariate/grid.html @@ -0,0 +1,199 @@ + + + + + + + + + pyFTS.models.multivariate.grid — pyFTS 1.4 documentation + + + + + + + + + + + + + + + + +
+
+
+
+ +

Source code for pyFTS.models.multivariate.grid

+from pyFTS.models.multivariate import partitioner
+from pyFTS.models.multivariate.common import MultivariateFuzzySet, fuzzyfy_instance_clustered
+from itertools import product
+from scipy.spatial import KDTree
+import numpy as np
+import pandas as pd
+
+
+
[docs]class GridCluster(partitioner.MultivariatePartitioner):
+    """
+    A cartesian product of all fuzzy sets of all variables
+    """
+
+    def __init__(self, **kwargs):
+        super(GridCluster, self).__init__(**kwargs)
+        self.name="GridCluster"
+        self.build(None)
+
+
[docs]    def build(self, data):
+
+        fsets = [[x for x in k.partitioner.sets.values()]
+                 for k in self.explanatory_variables]
+        c = 0
+        for k in product(*fsets):
+            mvfset = MultivariateFuzzySet(target_variable=self.target_variable)
+            for fset in k:
+                mvfset.append_set(fset.variable, fset)
+
+            self.sets[mvfset.name] = mvfset
+            c += 1
+
+        self.build_index()

+
+
+
[docs]class IncrementalGridCluster(partitioner.MultivariatePartitioner):
+    """
+    Create combinations of fuzzy sets of the variables on demand, incrementally increasing the
+    multivariate fuzzy set base.
+    """
+    def __init__(self, **kwargs):
+        super(IncrementalGridCluster, self).__init__(**kwargs)
+        self.name="IncrementalGridCluster"
+        self.build(None)
+
+
[docs]    def fuzzyfy(self, data, **kwargs):
+
+        if isinstance(data, pd.DataFrame):
+            ret = []
+            for index, inst in data.iterrows():
+                mv = self.fuzzyfy(inst, **kwargs)
+                ret.append(mv)
+            return ret
+
+        if self.kdtree is not None:
+            fsets = self.search(data, type='name')
+        else:
+            fsets = self.incremental_search(data, type='name')
+
+        mode = kwargs.get('mode', 'sets')
+        if mode == 'sets':
+            return fsets
+        elif mode == 'vector':
+            raise NotImplementedError()
+        elif mode == 'both':
+            ret = []
+            for key in fsets:
+                mvfset = self.sets[key]
+                ret.append((key, mvfset.membership(data)))
+            return ret

+
+
+
+
[docs]    def prune(self):
+        self.build_index()

+
+
+ +
+
+
+
+
+ + + + \ No newline at end of file