mirror of
https://github.com/TheAlgorithms/Python.git
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parent
0febbd397e
commit
25164bb638
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@ -3,15 +3,16 @@
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numbers out of 1 ... n. We use backtracking to solve this problem.
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Time complexity: O(C(n,k)) which is O(n choose k) = O((n!/(k! * (n - k)!)))
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"""
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from typing import List
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def generate_all_combinations(n: int, k: int) -> [[int]]:
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def generate_all_combinations(n: int, k: int) -> List[List[int]]:
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"""
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>>> generate_all_combinations(n=4, k=2)
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[[1, 2], [1, 3], [1, 4], [2, 3], [2, 4], [3, 4]]
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"""
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result = []
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result: List[List[int]] = []
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create_all_state(1, n, k, [], result)
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return result
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@ -20,8 +21,8 @@ def create_all_state(
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increment: int,
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total_number: int,
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level: int,
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current_list: [int],
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total_list: [int],
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current_list: List[int],
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total_list: List[List[int]],
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) -> None:
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if level == 0:
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total_list.append(current_list[:])
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@ -33,7 +34,7 @@ def create_all_state(
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current_list.pop()
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def print_all_state(total_list: [int]) -> None:
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def print_all_state(total_list: List[List[int]]) -> None:
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for i in total_list:
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print(*i)
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@ -5,14 +5,18 @@
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Time complexity: O(n! * n),
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where n denotes the length of the given sequence.
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"""
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from typing import List, Union
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def generate_all_permutations(sequence: [int]) -> None:
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def generate_all_permutations(sequence: List[Union[int, str]]) -> None:
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create_state_space_tree(sequence, [], 0, [0 for i in range(len(sequence))])
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def create_state_space_tree(
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sequence: [int], current_sequence: [int], index: int, index_used: int
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sequence: List[Union[int, str]],
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current_sequence: List[Union[int, str]],
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index: int,
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index_used: List[int],
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) -> None:
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"""
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Creates a state space tree to iterate through each branch using DFS.
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@ -40,8 +44,8 @@ print("Enter the elements")
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sequence = list(map(int, input().split()))
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"""
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sequence = [3, 1, 2, 4]
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sequence: List[Union[int, str]] = [3, 1, 2, 4]
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generate_all_permutations(sequence)
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sequence = ["A", "B", "C"]
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generate_all_permutations(sequence)
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sequence_2: List[Union[int, str]] = ["A", "B", "C"]
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generate_all_permutations(sequence_2)
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@ -7,10 +7,12 @@
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diagonal lines.
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"""
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from typing import List
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solution = []
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def isSafe(board: [[int]], row: int, column: int) -> bool:
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def isSafe(board: List[List[int]], row: int, column: int) -> bool:
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"""
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This function returns a boolean value True if it is safe to place a queen there
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considering the current state of the board.
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@ -38,7 +40,7 @@ def isSafe(board: [[int]], row: int, column: int) -> bool:
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return True
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def solve(board: [[int]], row: int) -> bool:
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def solve(board: List[List[int]], row: int) -> bool:
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"""
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It creates a state space tree and calls the safe function until it receives a
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False Boolean and terminates that branch and backtracks to the next
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@ -53,7 +55,7 @@ def solve(board: [[int]], row: int) -> bool:
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solution.append(board)
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printboard(board)
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print()
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return
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return True
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for i in range(len(board)):
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"""
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For every row it iterates through each column to check if it is feasible to
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@ -68,7 +70,7 @@ def solve(board: [[int]], row: int) -> bool:
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return False
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def printboard(board: [[int]]) -> None:
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def printboard(board: List[List[int]]) -> None:
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"""
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Prints the boards that have a successful combination.
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"""
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@ -1,4 +1,7 @@
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def solve_maze(maze: [[int]]) -> bool:
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from typing import List
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def solve_maze(maze: List[List[int]]) -> bool:
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"""
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This method solves the "rat in maze" problem.
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In this problem we have some n by n matrix, a start point and an end point.
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@ -67,7 +70,7 @@ def solve_maze(maze: [[int]]) -> bool:
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return solved
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def run_maze(maze: [[int]], i: int, j: int, solutions: [[int]]) -> bool:
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def run_maze(maze: List[List[int]], i: int, j: int, solutions: List[List[int]]) -> bool:
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"""
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This method is recursive starting from (i, j) and going in one of four directions:
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up, down, left, right.
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@ -106,6 +109,7 @@ def run_maze(maze: [[int]], i: int, j: int, solutions: [[int]]) -> bool:
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solutions[i][j] = 0
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return False
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return False
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if __name__ == "__main__":
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@ -6,11 +6,12 @@
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Summation of the chosen numbers must be equal to given number M and one number
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can be used only once.
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"""
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from typing import List
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def generate_sum_of_subsets_soln(nums: [int], max_sum: [int]) -> [int]:
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result = []
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path = []
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def generate_sum_of_subsets_soln(nums: List[int], max_sum: int) -> List[List[int]]:
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result: List[List[int]] = []
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path: List[int] = []
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num_index = 0
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remaining_nums_sum = sum(nums)
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create_state_space_tree(nums, max_sum, num_index, path, result, remaining_nums_sum)
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def create_state_space_tree(
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nums: [int],
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nums: List[int],
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max_sum: int,
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num_index: int,
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path: [int],
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result: [int],
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path: List[int],
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result: List[List[int]],
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remaining_nums_sum: int,
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) -> None:
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"""
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