Reputation: 1177
I need to create a binary tree from a list of lists. My problem is that some of the nodes overlap(in the sense that the left child of one is the right of the other) and I want to separate them.
I duplicated the overlapping nodes and created a single list, but I am missing something. The code I use to do that:
self.root = root = BNodeItem(values[0][0], 0)
q = list()
q.append(root)
# make single tree list
tree_list = list()
tree_list.append(values[0][0])
for i in xrange(1, len(values[0])):
ll = [i for i in numpy.array(values)[:, i] if i is not None]
# duplicate the values
p = []
for item in ll[1:-1]:
p.append(item)
p.append(item)
new_ll = list()
new_ll.append(ll[0])
new_ll.extend(p)
new_ll.append(ll[-1])
tree_list.extend(new_ll)
# fix tree
for ind in xrange(len(tree_list)/2 - 1):
eval_node = q.pop(0)
eval_node.left = BNodeItem(tree_list[2*ind + 1], 0)
eval_node.right = BNodeItem(tree_list[2*ind + 2], 0)
q.append(eval_node.left)
q.append(eval_node.right)
the "values" variable looks like this(where 0 I get None
normally):
100 141.9068 201.3753 285.7651 405.5200 575.4603
0 70.4688 100 141.9068 201.3753 285.7651
0 0 49.6585 70.4688 100.0000 141.9068
0 0 0 34.9938 49.6585 70.4688
0 0 0 0 24.6597 34.9938
0 0 0 0 0 17.3774
So for example the 141.9 in row = 1 has children 201.3 and 100 in row = 2, but 70.4 has children 100 and 49.6 in row 2(100 is shared).
Any suggestions?
EDIT : Had an error in len() and in creating the nodes from list values(wrong lists). Seems to still have a bug.
Seems it's working
Use this to print the tree from @Arthur's solution:
class Node():
def __init__(self, value):
self.value = value
self.leftChild = None
self.rightChild= None
def __str__(self, depth=0):
ret = ""
if self.leftChild is not None:
ret += self.leftChild.__str__(depth + 1)
ret += "\n" + (" " * depth) + str(self.value)
if self.rightChild is not None:
ret += self.rightChild.__str__(depth + 1)
return ret
Upvotes: 5
Views: 3584
Reputation: 1571
Here comes a solution that return you a Node
object having left and right child allowing you to use most of the tree parsing algorithms. If needed you can easily add reference to the parent node.
data2 = [[1,2,3],
[0,4,5],
[0,0,6]]
def exceptFirstColumn(data):
if data and data[0] :
return [ row[1:] for row in data ]
else :
return []
def exceptFirstLine(data):
if data :
return data[1:]
def left(data):
""" Returns the part of the data use to build the left subTree """
return exceptFirstColumn(data)
def right(data):
""" Returns the part of the data used to build the right subtree """
return exceptFirstColumn(exceptFirstLine(data))
class Node():
def __init__(self, value):
self.value = value
self.leftChild = None
self.rightChild= None
def __repr__(self):
if self.leftChild != None and self.rightChild != None :
return "[{0} (L:{1} | R:{2}]".format(self.value, self.leftChild.__repr__(), self.rightChild.__repr__())
else:
return "[{0}]".format(self.value)
def fromData2Tree(data):
if data and data[0] :
node = Node(data[0][0])
node.leftChild = fromData2Tree(left(data))
node.rightChild= fromData2Tree(right(data))
return node
else :
return None
tree = fromData2Tree(data2)
print(tree)
This code give the following result :
[1 (L:[2 (L:[3] | R:[5]] | R:[4 (L:[5] | R:[6]]]
That is the requested following tree. Test it on your data, it works. Now try to understand how it works ;)
+-----1-----+
| |
+--2--+ +--4--+
| | | |
3 5 5 6
Upvotes: 1