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* Changing the code to return tuple * Changing the code to return tuple * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update dynamic_programming/subset_generation.py Co-authored-by: Christian Clauss <cclauss@me.com> * Adding doctests in subset_generation.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update subset_generation.py * Update subset_generation.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update subset_generation.py * Update subset_generation.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update dynamic_programming/subset_generation.py Co-authored-by: Christian Clauss <cclauss@me.com> * Update stock_span_problem.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update subset_generation.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update subset_generation.py * Update subset_generation.py * Update subset_generation.py * Update subset_generation.py --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Christian Clauss <cclauss@me.com>
61 lines
2.2 KiB
Python
61 lines
2.2 KiB
Python
def subset_combinations(elements: list[int], n: int) -> list:
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"""
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Compute n-element combinations from a given list using dynamic programming.
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Args:
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elements: The list of elements from which combinations will be generated.
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n: The number of elements in each combination.
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Returns:
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A list of tuples, each representing a combination of n elements.
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>>> subset_combinations(elements=[10, 20, 30, 40], n=2)
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[(10, 20), (10, 30), (10, 40), (20, 30), (20, 40), (30, 40)]
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>>> subset_combinations(elements=[1, 2, 3], n=1)
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[(1,), (2,), (3,)]
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>>> subset_combinations(elements=[1, 2, 3], n=3)
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[(1, 2, 3)]
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>>> subset_combinations(elements=[42], n=1)
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[(42,)]
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>>> subset_combinations(elements=[6, 7, 8, 9], n=4)
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[(6, 7, 8, 9)]
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>>> subset_combinations(elements=[10, 20, 30, 40, 50], n=0)
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[()]
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>>> subset_combinations(elements=[1, 2, 3, 4], n=2)
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[(1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)]
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>>> subset_combinations(elements=[1, 'apple', 3.14], n=2)
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[(1, 'apple'), (1, 3.14), ('apple', 3.14)]
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>>> subset_combinations(elements=['single'], n=0)
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[()]
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>>> subset_combinations(elements=[], n=9)
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[]
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>>> from itertools import combinations
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>>> all(subset_combinations(items, n) == list(combinations(items, n))
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... for items, n in (
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... ([10, 20, 30, 40], 2), ([1, 2, 3], 1), ([1, 2, 3], 3), ([42], 1),
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... ([6, 7, 8, 9], 4), ([10, 20, 30, 40, 50], 1), ([1, 2, 3, 4], 2),
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... ([1, 'apple', 3.14], 2), (['single'], 0), ([], 9)))
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True
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"""
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r = len(elements)
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if n > r:
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return []
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dp: list[list[tuple]] = [[] for _ in range(r + 1)]
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dp[0].append(())
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for i in range(1, r + 1):
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for j in range(i, 0, -1):
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for prev_combination in dp[j - 1]:
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dp[j].append(tuple(prev_combination) + (elements[i - 1],))
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try:
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return sorted(dp[n])
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except TypeError:
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return dp[n]
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if __name__ == "__main__":
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from doctest import testmod
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testmod()
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print(f"{subset_combinations(elements=[10, 20, 30, 40], n=2) = }")
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