def condensation_nx( G, components) : """ G : DiGraph object. the nx.DiGraph attribute is extracted from this. components : Given components C_1 .. C_k which partition the nodes of G, the condensation graph cG has nodes <C_1> .. <C_k> and has edge (<C_i>,<C_j>) iff there was an edge in G from a node in C_i to a node in C_j. """ cG = DiGraph() cG.graph = nx.condensation( G.graph, components ) return cG
def prepare_regions( self ):
"""
Partition the phase space into disjoint, recurrent regions.
Must have initialized self with index_map matrix and
region2gen dictionary, or used one of the load_from_* methods
to initialize these values.
"""
# returns a DiGraph
self.map_on_regions = utils.index_map_to_region_map( self.index_map,
self.region2gen )
# graph_mis from graphs.algorithms
scc_list, scc_components, recurrent_regions = graph_mis( self.map_on_regions,
return_rsccs=True )
nbunch = [ scc_components[i] for i in recurrent_regions ]
self.recurrent_subgraphs = []
# the actual partition of phase space in graph format
for n in nbunch:
# ignore disjoint regions/nodes that have self-loops => no
# entropy
if len( n ) == 1:
continue
G = DiGraph()
G.graph = self.map_on_regions.graph.subgraph( n )
self.recurrent_subgraphs.append( G )
# construct IndexMapProcessor for each disjoint region
# assign entropies of -1 to each recurrent region.
for region in self.recurrent_subgraphs:
self.phase_space.append( [ IndexMapProcessor( self.index_map,
self.region2gen,
region,
debug=self.debug,
verbose=self.verbose ),
-1 # initial entropy for region
] )
########################
debug = True
verbose = False
scc_list, scc_components, recurrent_regions = algorithms.graph_mis( map_on_regions,
return_rsccs=True )
# separate nodes by recurrent component
nbunch = [ scc_components[i] for i in recurrent_regions ]
recurrent_subgraphs = []
for n in nbunch:
# ignore self-loops, no entropy
if len( n ) == 1:
continue
G = DiGraph()
G.graph = map_on_regions.graph.subgraph( n )
recurrent_subgraphs.append( G )
# compute entropy for each scc in the symbolic system
all_regions = []
for scc in recurrent_subgraphs:
all_regions.append( IndexMapProcessor( hom_matrix, region2gen,
scc, debug=debug, verbose=verbose ) )
# PARALLELIZE ME!
for job in all_regions:
job.find_bad_edge_sets( 4 ) # argument == max path length
job.cut_bad_edge_sets()
# print the best entropy for each SCC
for imp in all_regions:
