def test_strOfMultilevelTree(self):
a = trees.Node(data="a")
b = trees.Node(data="b")
c = trees.Node(left=a, right=b, data="c")
e = trees.Node(data="e")
d = trees.Node(left=c, right=e, data="d")
self.assertEqual(str(d), "(d: (c: a b) e)")
def test_onNodeTraversalOrder(self):
d = trees.Node(data="d",
right=trees.Node(data="e"),
left=trees.Node(data="c",
right=trees.Node(data="b"),
left=trees.Node(data="a")))
path = []
def recordPath(node):
path.append(node.data)
trees.BFS(d, onNode=recordPath)
self.assertEqual(path, ["d", "c", "e", "a", "b"])
def input_tree():
a = trees.Node(50)
b = a.addleft(48)
i = a.addright(52)
c = b.addleft(25)
d = c.addleft(10)
f = c.addright(30)
e = d.addleft(5)
g = f.addleft(28)
h = f.addright(32)
j = i.addleft(51)
k = i.addright(54)
return a, b,i
if node1 == None and node2 == None:
return True
if (node1 == None and node2 != None) or (node2 == None and node1 != None):
return False
if node1.data == node2.data:
return same_tree(node1.left, node2.left) and same_tree(
node1.right, node2.right)
else:
return False
def check_subtree(root1, root2):
if same_tree(root1, root2):
return True
if not root1:
return False
return check_subtree(root1.left, root2) or check_subtree(
root1.right, root2)
n1 = trees.Node(10)
a = n1.addleft(5)
b = n1.addright(8)
a.addleft(1)
b.addleft(2)
n2 = trees.Node(8)
n2.addleft(3)
print check_subtree(n1, n2)
def test_strOfOneNodeTree(self):
root = trees.Node(data="data")
self.assertEqual(str(root), "data")
def test_strOfThreeNodeTree(self):
a = trees.Node(data="a")
b = trees.Node(data="b")
c = trees.Node(left=a, right=b, data="c")
self.assertEqual(str(c), "(c: a b)")
#!/usr/bin/python
import trees
import random
a = trees.Node(50)
b = a.addleft(48)
i = a.addright(52)
c = b.addleft(25)
d = c.addleft(10)
f = c.addright(30)
e = d.addleft(5)
g = f.addleft(28)
h = f.addright(32)
j = i.addleft(51)
k = i.addright(54)
def get_random_node(a):
""" Get random nodes """
if not a.left:
lc = 0
else:
lc = a.left.size
index = random.randint(1, a.size)
if node.left:
return leftmost(node.left)
else:
return node
def parent_until_greator(node, val):
if not node:
return None
if node.data > val:
return node
else:
return parent_until_greator(node.parent, val)
print a = trees.Node(50)
b = a.addleft(48)
i = a.addright(52)
c = b.addleft(25)
d = c.addleft(10)
f = c.addright(30)
e = d.addleft(5)
g = f.addleft(28)
h = f.addright(32)
j = i.addleft(51)
b = [['yes', 'yes', 'maybe'], ['yes', 'yes', 'maybe'], ['no', 'no', 'yes'],
['no', 'yes', 'no'], ['no', 'yes', 'no']]
'''tree=tr.DecisionTree()
node0=tr.Node(a)
child1=tr.splitNode(node0.getNode(), 0, 1)
print(child1)
child3=tr.Node(child1)
node0.getNodeChild().append(child3)
child2=tr.splitNode(node0.getNode(), 0, 0)
child4=tr.Node(child2)
node0.getNodeChild().append(child4)
'''
tree = tr.DecisionTree()
node0 = tr.Node(a)
tree.buildTree(node0)
print(node0.getNode())
'''
test=['no','yes','']
res=tr.predict(test, node0)
print(res)
'''