def __init__(self, dimension):
"""Create a new empty solver"""
Notifier.__init__(self)
self.dimension = dimension
self._graph = Graph()
self._graph.add_vertex("_root")
self._graph.add_vertex("_toplevel")
self._graph.add_vertex("_variables")
self._graph.add_vertex("_distances")
self._graph.add_vertex("_angles")
self._graph.add_vertex("_rigids")
self._graph.add_vertex("_hedgehogs")
self._graph.add_vertex("_balloons")
self._graph.add_vertex("_methods")
# queue of new objects to process
self._new = []
# methodgraph
self._mg = MethodGraph()
def test():
graph = MethodGraph()
graph.add_variable('a', 1)
graph.add_variable('b', 2)
mv_x = MultiVariable('x')
graph.add_variable(mv_x)
graph.add_method(SumProdMethod('a', 'b', mv_x))
graph.add_variable('p', 3)
graph.add_variable('q', 4)
mv_y = MultiVariable('y')
graph.add_variable(mv_y)
graph.add_method(SumProdMethod('p', 'q', mv_y))
mv_z = MultiVariable('z')
graph.add_variable(mv_z)
graph.add_method(SumProdMethod(mv_x, mv_y, mv_z))
print graph.get(mv_z)
graph.set('a', 100)
print graph.get(mv_z)
def __init__(self, methodclasses):
"""Create a new solver, using the given subclasses of ClusterMethod."""
# init superclasses
Notifier.__init__(self)
# store arguments
self._methodclasses = methodclasses
self._pattern_methods = filter(lambda m: hasattr(m, "patterngraph"),
self._methodclasses)
self._handcoded_methods = filter(
lambda m: hasattr(m, "handcoded_match"), self._methodclasses)
self._incremental_methods = filter(
lambda m: hasattr(m, "incremental_matcher"), self._methodclasses)
# init instance vars
self._graph = Graph()
#self._graph.add_vertex("_root")
# self._graph.add_vertex("_toplevel")
self._graph.add_vertex("_variables")
self._graph.add_vertex("_clusters")
self._graph.add_vertex("_methods")
self._new = []
self._mg = MethodGraph()
# add prototype_selection boolean var to method graph
self._prototype_selection_var = "_prototype_selection_enabled"
self._mg.add_variable(self._prototype_selection_var)
self._mg.set(self._prototype_selection_var, True)
# store map of selection_constraints to SelectionMethod (or None)
self._selection_method = {}
# store root cluster (will be assigned when first cluster added)
self._rootcluster = None
# an incrementally updated toplevel set
self._toplevel = MutableSet()
# incrementally updated set of applicable methods
self._incremental_matchers = map(
lambda method: method.incremental_matcher(self),
self._incremental_methods)
#print "incremental matchers:",self._incremental_matchers
self._applicable_methods = Union(*self._incremental_matchers)
