Skip to content

Instantly share code, notes, and snippets.

@ubershmekel
Created November 27, 2012 13:35
Show Gist options
  • Star 1 You must be signed in to star a gist
  • Fork 1 You must be signed in to fork a gist
  • Save ubershmekel/4154250 to your computer and use it in GitHub Desktop.
Save ubershmekel/4154250 to your computer and use it in GitHub Desktop.
Generate python code from orange-canvas decision trees
"""
How to use:
1. Place a "Python Script" node on your canvas
2. Hook your "Classification Tree" node out into the "Python Script" input
3. Paste this gist in the python script and hit "Execute"
The output should be similar to this:
# slope (<32.000, 34.000>)
if slope <=1.008: return False #(<7.000, 0.000>)
if slope >1.008:
# peak_i (<25.000, 34.000>)
if peak_i <=39.500: return False #(<19.000, 2.000>)
if peak_i >39.500: return True #(<6.000, 32.000>)
Based on http://orange.biolab.si/doc/reference/Orange.classification.tree/#tree-structure
"""
def print_tree0(node, level):
if not node:
print " "*level + "<null node>"
return
if node.branch_selector:
node_desc = node.branch_selector.class_var.name
node_cont = node.distribution
indent = " " * level
print "\n" + indent + "# %s (%s)" % (node_desc, node_cont),
for i in range(len(node.branches)):
print "\n{indent}if {var} {op}:".format(indent=indent, var=node_desc, op=node.branch_descriptions[i]),
print_tree0(node.branches[i], level+1)
else:
node_cont = node.distribution
major_class = node.node_classifier.default_value
print "return %s #(%s) " % (major_class, node_cont),
print_tree0(in_classifier.tree, 0)
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment