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Fix sphinx/build_docs warnings for dynamic_programming (#12484)

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* Fix sphinx/build_docs warnings for dynamic_programming

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Fix

* Fix

* Fix

* Fix

* Fix

* Fix

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
Maxim Smolskiy
2024-12-30 14:52:03 +03:00
committed by GitHub
parent 493a7c153c
commit 7fa9b4bf1b
13 changed files with 294 additions and 285 deletions
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40
dynamic_programming/knapsack.py
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@ -11,7 +11,7 @@ def mf_knapsack(i, wt, val, j):
"""
This code involves the concept of memory functions. Here we solve the subproblems
which are needed unlike the below example
F is a 2D array with -1s filled up
F is a 2D array with ``-1`` s filled up
"""
global f # a global dp table for knapsack
if f[i][j] < 0:
@ -45,22 +45,24 @@ def knapsack_with_example_solution(w: int, wt: list, val: list):
the several possible optimal subsets.
Parameters
---------
----------
W: int, the total maximum weight for the given knapsack problem.
wt: list, the vector of weights for all items where wt[i] is the weight
of the i-th item.
val: list, the vector of values for all items where val[i] is the value
of the i-th item
* `w`: int, the total maximum weight for the given knapsack problem.
* `wt`: list, the vector of weights for all items where ``wt[i]`` is the weight
of the ``i``-th item.
* `val`: list, the vector of values for all items where ``val[i]`` is the value
of the ``i``-th item
Returns
-------
optimal_val: float, the optimal value for the given knapsack problem
example_optional_set: set, the indices of one of the optimal subsets
which gave rise to the optimal value.
* `optimal_val`: float, the optimal value for the given knapsack problem
* `example_optional_set`: set, the indices of one of the optimal subsets
which gave rise to the optimal value.
Examples
-------
--------
>>> knapsack_with_example_solution(10, [1, 3, 5, 2], [10, 20, 100, 22])
(142, {2, 3, 4})
>>> knapsack_with_example_solution(6, [4, 3, 2, 3], [3, 2, 4, 4])
@ -104,19 +106,19 @@ def _construct_solution(dp: list, wt: list, i: int, j: int, optimal_set: set):
a filled DP table and the vector of weights
Parameters
---------
----------
dp: list of list, the table of a solved integer weight dynamic programming problem
wt: list or tuple, the vector of weights of the items
i: int, the index of the item under consideration
j: int, the current possible maximum weight
optimal_set: set, the optimal subset so far. This gets modified by the function.
* `dp`: list of list, the table of a solved integer weight dynamic programming
problem
* `wt`: list or tuple, the vector of weights of the items
* `i`: int, the index of the item under consideration
* `j`: int, the current possible maximum weight
* `optimal_set`: set, the optimal subset so far. This gets modified by the function.
Returns
-------
None
``None``
"""
# for the current item i at a maximum weight j to be part of an optimal subset,
# the optimal value at (i, j) must be greater than the optimal value at (i-1, j).