Generating all possible trees of depth N?

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一生所求
一生所求 2021-01-03 11:47

I have several different types of tree nodes, each of which may have anywhere from 0 to 5 children. I\'m trying to figure out an algorithm to generate all possible trees of

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  •  长情又很酷
    2021-01-03 11:56

    Here's a Python program I wrote up that I think does what you're asking. It'll return all of the possible trees given a starting node. Essentially, it boils down to a trick with bit manipulation: if a node has 5 children, then there are 25 = 32 different possible subtrees as each child can independently be present or not present in a subtree.

    Code:

    #!/usr/bin/env python
    
    def all_combos(choices):
        """
        Given a list of items (a,b,c,...), generates all possible combinations of
        items where one item is taken from a, one from b, one from c, and so on.
    
        For example, all_combos([[1, 2], ["a", "b", "c"]]) yields:
    
            [1, "a"]
            [1, "b"]
            [1, "c"]
            [2, "a"]
            [2, "b"]
            [2, "c"]
        """
        if not choices:
            yield []
            return
    
        for left_choice in choices[0]:
            for right_choices in all_combos(choices[1:]):
                yield [left_choice] + right_choices
    
    class Node:
        def __init__(self, value, children=[]):
            self.value    = value
            self.children = children
    
        def all_subtrees(self, max_depth):
            yield Node(self.value)
    
            if max_depth > 0:
                # For each child, get all of its possible sub-trees.
                child_subtrees = [list(self.children[i].all_subtrees(max_depth - 1)) for i in range(len(self.children))]
    
                # Now for the n children iterate through the 2^n possibilities where
                # each child's subtree is independently present or not present. The
                # i-th child is present if the i-th bit in "bits" is a 1.
                for bits in xrange(1, 2 ** len(self.children)):
                    for combos in all_combos([child_subtrees[i] for i in range(len(self.children)) if bits & (1 << i) != 0]):
                        yield Node(self.value, combos)
    
        def __str__(self):
            """
            Display the node's value, and then its children in brackets if it has any.
            """
            if self.children:
                return "%s %s" % (self.value, self.children)
            else:
                return str(self.value)
    
        def __repr__(self):
            return str(self)
    
    tree = Node(1,
    [
        Node(2),
        Node(3,
        [
            Node(4),
            Node(5),
            Node(6)
        ])
    ])
    
    for subtree in tree.all_subtrees(2):
        print subtree
    

    Here's a graphical representation of the test tree:

      1
     / \
    2   3
       /|\
      4 5 6
    

    And here's the output from running the program:

    1
    1 [2]
    1 [3]
    1 [3 [4]]
    1 [3 [5]]
    1 [3 [4, 5]]
    1 [3 [6]]
    1 [3 [4, 6]]
    1 [3 [5, 6]]
    1 [3 [4, 5, 6]]
    1 [2, 3]
    1 [2, 3 [4]]
    1 [2, 3 [5]]
    1 [2, 3 [4, 5]]
    1 [2, 3 [6]]
    1 [2, 3 [4, 6]]
    1 [2, 3 [5, 6]]
    1 [2, 3 [4, 5, 6]]
    

    If you'd like I could translate this into a different language. You didn't specify so I used Python; the code would be a bit more verbose in Java or C++ or whatever since I took advantage of Python's list comprehensions in a big way.

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