def _color_minimum_energy_path(self, m1, m2):
"""find the minimum energy path between m1 and m2 and color the dgraph appropriately"""
# add weight attribute to the graph
# note: this is not actually the minimum energy path.
# This minimizes the sum of energies along the path
# TODO: use minimum spanning tree to find the minimum energy path
path = minimum_energy_path(self.graph, m1, m2)
# emin = min(( m.energy for m in self.graph.nodes_iter() ))
# for u, v, data in self.graph.edges_iter(data=True):
# data["weight"] = data["ts"].energy - emin
# path = nx.shortest_path(self.graph, m1, m2, weight="weight")
print("there are", len(path), "minima in the path from", m1._id, "to",
m2._id)
# color all trees up to the least common ancestor in the dgraph
trees = [self.dg.minimum_to_leave[m] for m in path]
ancestry = TreeLeastCommonAncestor(trees)
all_trees = ancestry.get_all_paths_to_common_ancestor()
# remove the least common ancestor so the coloring doesn't go to higher energies
all_trees.remove(ancestry.least_common_ancestor)
# color the trees
for tree in all_trees:
tree.data["colour"] = (1., 0., 0.)
self.redraw_disconnectivity_graph()
def test(self):
t1 = Tree()
t2_1 = Tree(t1)
t2_2 = Tree(t1)
lca = TreeLeastCommonAncestor([t2_1, t2_2])
self.assertEqual(lca.least_common_ancestor, t1)
t3_1 = Tree(t2_1)
t3_2 = Tree(t2_1)
t3_3 = Tree(t2_2)
self.assertEqual(
TreeLeastCommonAncestor([t3_1, t3_2]).least_common_ancestor, t2_1)
self.assertEqual(
TreeLeastCommonAncestor([t3_1, t3_2, t3_3]).least_common_ancestor,
t1)
self.assertEqual(
TreeLeastCommonAncestor([t2_1, t3_1]).least_common_ancestor, t2_1)
self.assertEqual(
TreeLeastCommonAncestor([t2_2, t3_1]).least_common_ancestor, t1)
lca = TreeLeastCommonAncestor([t3_1, t3_2])
try:
self.assertItemsEqual(lca.get_all_paths_to_common_ancestor(),
[t2_1, t3_1, t3_2])
except AttributeError:
self.assertCountEqual(lca.get_all_paths_to_common_ancestor(),
[t2_1, t3_1, t3_2])
def test(self):
t1 = Tree()
t2_1 = Tree(t1)
t2_2 = Tree(t1)
lca = TreeLeastCommonAncestor([t2_1, t2_2])
self.assertEqual(lca.least_common_ancestor, t1)
t3_1 = Tree(t2_1)
t3_2 = Tree(t2_1)
t3_3 = Tree(t2_2)
self.assertEqual(TreeLeastCommonAncestor([t3_1, t3_2]).least_common_ancestor, t2_1)
self.assertEqual(TreeLeastCommonAncestor([t3_1, t3_2, t3_3]).least_common_ancestor, t1)
self.assertEqual(TreeLeastCommonAncestor([t2_1, t3_1]).least_common_ancestor, t2_1)
self.assertEqual(TreeLeastCommonAncestor([t2_2, t3_1]).least_common_ancestor, t1)
lca = TreeLeastCommonAncestor([t3_1, t3_2])
self.assertItemsEqual(lca.get_all_paths_to_common_ancestor(), [t2_1, t3_1, t3_2])
def _color_minimum_energy_path(self, m1, m2):
"""find the minimum energy path between m1 and m2 and color the dgraph appropriately"""
# add weight attribute to the graph
# note: this is not actually the minimum energy path.
# This minimizes the sum of energies along the path
# TODO: use minimum spanning tree to find the minimum energy path
path = minimum_energy_path(self.graph, m1, m2)
# emin = min(( m.energy for m in self.graph.nodes_iter() ))
# for u, v, data in self.graph.edges_iter(data=True):
# data["weight"] = data["ts"].energy - emin
# path = nx.shortest_path(self.graph, m1, m2, weight="weight")
print "there are", len(path), "minima in the path from", m1._id, "to", m2._id
# color all trees up to the least common ancestor in the dgraph
trees = [self.dg.minimum_to_leave[m] for m in path]
ancestry = TreeLeastCommonAncestor(trees)
all_trees = ancestry.get_all_paths_to_common_ancestor()
# remove the least common ancestor so the coloring doesn't go to higher energies
all_trees.remove(ancestry.least_common_ancestor)
# color the trees
for tree in all_trees:
tree.data["colour"] = (1., 0., 0.)
self.redraw_disconnectivity_graph()
