Problem:
Rooted Trees

A graph G = (V, E) is a data structure where V is a finite set of vertices and E is a binary relation on V represented by a set of edges. Fig. 1 illustrates an example of a graph (or graphs).

Fig. 1

A free tree is a connnected, acyclic, undirected graph. A rooted tree is a free tree in which one of the vertices is distinguished from the others. A vertex of a rooted tree is called "node."

Your task is to write a program which reports the following information for each node u of a given rooted tree T:

node ID of u

parent of u

depth of u

node type (root, internal node or leaf)

a list of chidlren of u

If the last edge on the path from the root r of a tree T to a node x is (p, x), then p is the parent of x, and x is a child of p. The root is the only node in T with no parent.

A node with no children is an external node or leaf. A nonleaf node is an internal node

The number of children of a node x in a rooted tree T is called the degree of x.

The length of the path from the root r to a node x is the depth of x in T.

Here, the given tree consists of n nodes and evey node has a unique ID from 0 to n-1.

Fig. 2 shows an example of rooted trees where ID of each node is indicated by a number in a circle (node). The example corresponds to the first sample input.

Fig. 2

Input

The first line of the input includes an integer n, the number of nodes of the tree.

In the next n lines, the information of each node u is given in the following format:

id k c1 c2 ... ck

where id is the node ID of u, k is the degree of u, c1 ... ck are node IDs of 1st, ... kth child of u. If the node does not have a child, the k is 0.

Output

Print the information of each node in the following format ordered by IDs:

node id: parent = p, depth = d, type, [c1...ck]

p is ID of its parent. If the node does not have a parent, print -1.

d is depth of the node.

type is a type of nodes represented by a string (root, internal node or leaf). If the root can be considered as a leaf or an internal node, print root.

c1...ck is the list of children as a ordered tree.

Please follow the format presented in a sample output below.

Constraints

1 ≤ n ≤ 100000

Sample Input 1

13
0 3 1 4 10
1 2 2 3
2 0
3 0
4 3 5 6 7
5 0
6 0
7 2 8 9
8 0
9 0
10 2 11 12
11 0
12 0

Sample Output 1

node 0: parent = -1, depth = 0, root, [1, 4, 10]
node 1: parent = 0, depth = 1, internal node, [2, 3]
node 2: parent = 1, depth = 2, leaf, []
node 3: parent = 1, depth = 2, leaf, []
node 4: parent = 0, depth = 1, internal node, [5, 6, 7]
node 5: parent = 4, depth = 2, leaf, []
node 6: parent = 4, depth = 2, leaf, []
node 7: parent = 4, depth = 2, internal node, [8, 9]
node 8: parent = 7, depth = 3, leaf, []
node 9: parent = 7, depth = 3, leaf, []
node 10: parent = 0, depth = 1, internal node, [11, 12]
node 11: parent = 10, depth = 2, leaf, []
node 12: parent = 10, depth = 2, leaf, []

Sample Input 2

4
1 3 3 2 0
0 0
3 0
2 0

Sample Output 2

node 0: parent = 1, depth = 1, leaf, []
node 1: parent = -1, depth = 0, root, [3, 2, 0]
node 2: parent = 1, depth = 1, leaf, []
node 3: parent = 1, depth = 1, leaf, []

Note

You can use a left-child, right-sibling representation to implement a tree which has the following data:

the parent of u

the leftmost child of u

the immediate right sibling of u

Reference

Introduction to Algorithms, Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. The MIT Press.

Solution in Ruby (judge verdict: Accepted)

# 左子右兄弟表現(一番左の子と、自分の右隣の兄弟へのリンクを持つ)
class TreeNode
	attr_accessor :parent, :left_child, :right_sibling, :depth

	def type
		return "root" unless @parent
		return "leaf" unless @left_child
		"internal node"
	end

	# stack overflow
	# def self.set_depth(nodes, id, depth)
	# 	nodes[id].depth = depth
	# 	if nodes[id].right_sibling
	# 		set_depth(nodes, nodes[id].right_sibling, depth)
	# 	end
	# 	if nodes[id].left_child
	# 		set_depth(nodes, nodes[id].left_child, depth + 1)
	# 	end
	# end

	def self.depth(nodes, id)
		depth = 0
		while nodes[id].parent
			id = nodes[id].parent
			depth += 1
		end
		depth
	end

	def self.description(nodes, id)
		node = nodes[id]
		children_id_list = []

		child_id = node.left_child
		while child_id
			children_id_list << child_id
			child_id = nodes[child_id].right_sibling
		end

		desc  = "node #{id}: "
		desc += "parent = #{node.parent ? node.parent : -1}, "
		desc += "depth = #{TreeNode.depth(nodes, id)}, "
		desc += "#{node.type}, "
		desc += "[#{children_id_list.join(", ")}]"
	end
end

# 木全体を配列で管理する, indexがidと紐づく
n = STDIN.gets.to_i
nodes = []
n.times { nodes << TreeNode.new }

n.times.each do |i|
	id, degree, *children = STDIN.gets.split.map(&:to_i)

	prev = nil
	children[0...degree].each_index do |j|
		child = children[j]

		if j == 0
			nodes[id].left_child = child
		else
			nodes[prev].right_sibling = child
		end

		prev = child
		nodes[child].parent = id
	end
end

nodes.each_index { |id| puts TreeNode.description(nodes, id) }