for data in dataset:
result_file = open('result_{}_nj.txt'.format(data), 'w')
for method in distance_methods:
#result_file.write(method + '\n')
for i in range(20):
truth = '../../{}/{}/R{}/rose.tt'.format(data, data, i)
predicted_tree_file = (data + '/' + method + '/R'+ str(i)
+ '/out_tree.nwk')
if (not os.path.isfile(predicted_tree_file) or
os.stat(predicted_tree_file).st_size == 0):
result_file.write(method+',R'+str(i)+',err,err\n')
continue
true_tree_file = (truth)
tree1 = Tree.get_from_path(
predicted_tree_file,
"newick",
taxon_namespace=tns)
tree2 = Tree.get_from_path(
true_tree_file,
"newick",
taxon_namespace=tns)
tree1.encode_bipartitions()
tree2.encode_bipartitions()
print('R'+str(i),treecompare.false_positives_and_negatives(tree1, tree2))
result_file.write(method+',R'+str(i)+','+','.join([str(x) for x in treecompare.false_positives_and_negatives(tree1, tree2)]))
result_file.write('\n')
result_file.close()
