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ae0fc85401
* Fix ruff errors
Renamed neural_network/input_data.py to neural_network/input_data.py_tf
because it should be left out of the directory for the following
reasons:
1. Its sole purpose is to be used by neural_network/gan.py_tf, which is
itself left out of the directory because of issues with TensorFlow.
2. It was taken directly from TensorFlow's codebase and is actually
already deprecated. If/when neural_network/gan.py_tf is eventually
re-added back to the directory, its implementation should be changed
to not use neural_network/input_data.py anyway.
* updating DIRECTORY.md
* Change input_data.py_tf file extension
Change input_data.py_tf file extension because algorithms-keeper bot is being picky about it
---------
Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
138 lines
3.2 KiB
Python
138 lines
3.2 KiB
Python
"""
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Author : Alexander Pantyukhin
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Date : November 7, 2022
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Task:
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You are given a tree root of a binary tree with n nodes, where each node has
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node.data coins. There are exactly n coins in whole tree.
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In one move, we may choose two adjacent nodes and move one coin from one node
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to another. A move may be from parent to child, or from child to parent.
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Return the minimum number of moves required to make every node have exactly one coin.
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Example 1:
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3
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/ \
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0 0
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Result: 2
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Example 2:
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0
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/ \
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3 0
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Result 3
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leetcode: https://leetcode.com/problems/distribute-coins-in-binary-tree/
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Implementation notes:
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User depth-first search approach.
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Let n is the number of nodes in tree
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Runtime: O(n)
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Space: O(1)
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import NamedTuple
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@dataclass
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class TreeNode:
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data: int
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left: TreeNode | None = None
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right: TreeNode | None = None
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class CoinsDistribResult(NamedTuple):
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moves: int
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excess: int
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def distribute_coins(root: TreeNode | None) -> int:
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"""
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>>> distribute_coins(TreeNode(3, TreeNode(0), TreeNode(0)))
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2
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>>> distribute_coins(TreeNode(0, TreeNode(3), TreeNode(0)))
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3
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>>> distribute_coins(TreeNode(0, TreeNode(0), TreeNode(3)))
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3
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>>> distribute_coins(None)
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0
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>>> distribute_coins(TreeNode(0, TreeNode(0), TreeNode(0)))
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Traceback (most recent call last):
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...
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ValueError: The nodes number should be same as the number of coins
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>>> distribute_coins(TreeNode(0, TreeNode(1), TreeNode(1)))
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Traceback (most recent call last):
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...
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ValueError: The nodes number should be same as the number of coins
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"""
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if root is None:
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return 0
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# Validation
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def count_nodes(node: TreeNode | None) -> int:
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"""
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>>> count_nodes(None)
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0
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"""
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if node is None:
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return 0
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return count_nodes(node.left) + count_nodes(node.right) + 1
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def count_coins(node: TreeNode | None) -> int:
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"""
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>>> count_coins(None)
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0
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"""
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if node is None:
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return 0
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return count_coins(node.left) + count_coins(node.right) + node.data
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if count_nodes(root) != count_coins(root):
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raise ValueError("The nodes number should be same as the number of coins")
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# Main calculation
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def get_distrib(node: TreeNode | None) -> CoinsDistribResult:
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"""
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>>> get_distrib(None)
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namedtuple("CoinsDistribResult", "0 2")
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"""
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if node is None:
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return CoinsDistribResult(0, 1)
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left_distrib_moves, left_distrib_excess = get_distrib(node.left)
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right_distrib_moves, right_distrib_excess = get_distrib(node.right)
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coins_to_left = 1 - left_distrib_excess
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coins_to_right = 1 - right_distrib_excess
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result_moves = (
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left_distrib_moves
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+ right_distrib_moves
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+ abs(coins_to_left)
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+ abs(coins_to_right)
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)
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result_excess = node.data - coins_to_left - coins_to_right
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return CoinsDistribResult(result_moves, result_excess)
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return get_distrib(root)[0]
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if __name__ == "__main__":
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import doctest
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doctest.testmod()
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