def B_using_tree_l2c(leaf2clusters, bonding_calc = lambda common_path_fraction: common_path_fraction):
"""Generates bonding matrix for given tree.
leaf2clusters - tree given as a dictionary {leaf: descending-list-of-clusters}
bonding_calc(common_path_fraction) - returns bonding value
"""
B = []
#print "[B_using_tree_l2c] Considering:",leaf2clusters
max_levels = trees.tree_depth(leaf2clusters)
logging.info("[B_using_tree_l2c] max_levels="+str(max_levels))
for lix,leaf in enumerate(sorted(leaf2clusters)):
leaf_path = leaf2clusters[leaf]+[lix] #append leaf_no to path
bv = [] #bonding vector
for lix2,leaf2 in enumerate(sorted(leaf2clusters)):
leaf2_path = leaf2clusters[leaf2]+[lix2] #append leaf_no to path
common_levels = calc_common_levels(leaf_path, leaf2_path)
#common_path_fraction = float(common_levels) / max_levels
#common_path_fraction = 0.5*(float(common_levels) / len(leaf_path) + float(common_levels) / len(leaf2_path))
#common_path_fraction = max(float(common_levels) / len(leaf_path) , float(common_levels) / len(leaf2_path))
common_path_fraction = min(float(common_levels) / len(leaf_path) , float(common_levels) / len(leaf2_path))
bv.append(bonding_calc(common_path_fraction))
#print "leaf_path, leaf2_path =",leaf_path, leaf2_path,"->",bonding_calc(common_path_fraction)
B.append(bv)
return B
def find_regions(self, root):
data_regions = []
if tree_depth(root) >= 2:
scores = self.compare_generalized_nodes(root, self.max_generalized_nodes)
data_regions.extend(self.identify_regions(0, root, self.max_generalized_nodes, self.threshold, scores))
covered = set()
for data_region in data_regions:
for i in xrange(data_region.start, data_region.covered):
covered.add(data_region.parent[i])
for child in root:
if child not in covered:
data_regions.extend(self.find_regions(child))
return data_regions
