def generate_lhs_flrg(self, sample):
lags = {}
flrgs = []
for ct, o in enumerate(self.lags):
lhs = [
key for key in self.partitioner.ordered_sets
if self.sets[key].membership(sample[o - 1]) > self.alpha_cut
]
lags[ct] = lhs
root = tree.FLRGTreeNode(None)
tree.build_tree_without_order(root, lags, 0)
# Trace the possible paths
for p in root.paths():
flrg = HighOrderFLRG(self.order)
path = list(reversed(list(filter(None.__ne__, p))))
for lhs in path:
flrg.append_lhs(lhs)
flrgs.append(flrg)
return flrgs
def generate_lhs_flrg_fuzzyfied(self, sample, explain=False):
lags = {}
flrgs = []
for ct, o in enumerate(self.lags):
lags[ct] = sample[o-1]
if explain:
print("\t (Lag {}) {} -> {} \n".format(o, sample[o-1], lhs))
root = tree.FLRGTreeNode(None)
tree.build_tree_without_order(root, lags, 0)
# Trace the possible paths
for p in root.paths():
flrg = WeightedHighOrderFLRG(self.order)
path = list(reversed(list(filter(None.__ne__, p))))
for lhs in path:
flrg.append_lhs(lhs)
flrgs.append(flrg)
return flrgs
def generate_lhs_flrg(self, sample):
lags = {}
flrgs = []
for ct, o in enumerate(self.lags):
lhs = FuzzySet.fuzzyfy(sample[o - 1],
partitioner=self.partitioner,
mode="sets",
alpha_cut=self.alpha_cut)
lags[ct] = lhs
root = tree.FLRGTreeNode(None)
tree.build_tree_without_order(root, lags, 0)
# Trace the possible paths
for p in root.paths():
flrg = HighOrderFLRG(self.order)
path = list(reversed(list(filter(None.__ne__, p))))
for lhs in path:
flrg.append_lhs(lhs)
flrgs.append(flrg)
return flrgs
def generate_lhs_flrg_fuzzyfied(self, sample, explain=False):
lags = []
flrgs = []
for ct, o in enumerate(self.lags):
lags.append(sample[o - 1])
if explain:
print("\t (Lag {}) {} \n".format(o, sample[o - 1]))
# Trace the possible paths
for path in product(*lags):
flrg = WeightedHighOrderFLRG(self.order)
for lhs in path:
flrg.append_lhs(lhs)
flrgs.append(flrg)
return flrgs
def generate_lhs_flrg_fuzzyfied(self, sample, explain=False):
lags = []
flrgs = []
for ct, o in enumerate(self.lags):
lhs = sample[o - 1]
lags.append(lhs)
if explain:
self.append_log("Ordering Lags",
"Lag {} Value {}".format(o, lhs))
# Trace the possible paths
for path in product(*lags):
flrg = HighOrderFLRG(self.order)
for lhs in path:
flrg.append_lhs(lhs)
flrgs.append(flrg)
return flrgs
def generate_lhs_flrg(self, sample):
lags = {}
flrgs = []
for o in np.arange(0, self.order):
lhs = self.fuzzyfication(sample[o])
lags[o] = lhs
root = tree.FLRGTreeNode(None)
tree.build_tree_without_order(root, lags, 0)
# Trace the possible paths
for p in root.paths():
flrg = ClusteredMultivariateHighOrderFLRG(self.order)
path = list(reversed(list(filter(None.__ne__, p))))
for lhs in path:
flrg.append_lhs(lhs)
flrgs.append(flrg)
return flrgs
