def compare_to_random_tree(msc_leaf2clusters, \
bonding_calc, membership_calc, membership_bonding,\
only_fast_calculations = False):
leaves = list( msc_leaf2clusters )
rand_tree,num_l,num_m = get_random_tree2(leaves)
rand_leaf2clusters = trees.bottomup2topdown_tree_converter(rand_tree)
indexes_dict = tree_distance.get_indexes_dict(msc_leaf2clusters, rand_leaf2clusters, \
bonding_calc, membership_calc, membership_bonding,\
only_fast_calculations)
#print indexes_dict
return (num_l, num_m, indexes_dict)
results = {} #{index-name: list of results}
start = time.clock()
for i in xrange(NUM_TRIES):
print "",(time.clock()-start),i,"out of",NUM_TRIES,
(num_l, num_m, indexes_dict) = compare_to_random_tree(msc_leaf2clusters, \
bonding_calc, membership_calc, membership_bonding,\
only_fast_calculations)
indexes_dict["num_l"] = num_l
indexes_dict["num_m"] = num_m
for id, val in indexes_dict.iteritems():
results[id] = results.get(id,[])+[val]
print "Results:",results
print "Tree self-comparison..."
print "",tree_distance.get_indexes_dict(msc_leaf2clusters, msc_leaf2clusters, \
bonding_calc, membership_calc, membership_bonding,\
only_fast_calculations)
print "Stats..."
print "\tid\tavg\tstd"
for id,vals in results.iteritems():
print "\t",id,"\t",avg(vals),"\t",std(vals)
print "Num clusters vs index..."
for id,vals in results.iteritems():
if id == "num_l" or id == "num_m": continue
num_l = results["num_l"]
num_m = results["num_m"]
print "\t",id,"----------"
print "\tnum_l\tnum_m\tval"
for i in xrange(len(vals)):
