Corrected the directory of Fractional Knapsack algorithm (#7086)

* Moved fractional knapsack from 'dynamic_programming' to 'greedy_methods'

* Updated DIRECTORY.md

dynamic_programming/fractional_knapsack.py

@@ -1,27 +0,0 @@
-from bisect import bisect
-from itertools import accumulate
-
-
-def frac_knapsack(vl, wt, w, n):
-    """
-    >>> frac_knapsack([60, 100, 120], [10, 20, 30], 50, 3)
-    240.0
-    """
-
-    r = sorted(zip(vl, wt), key=lambda x: x[0] / x[1], reverse=True)
-    vl, wt = [i[0] for i in r], [i[1] for i in r]
-    acc = list(accumulate(wt))
-    k = bisect(acc, w)
-    return (
-        0
-        if k == 0
-        else sum(vl[:k]) + (w - acc[k - 1]) * (vl[k]) / (wt[k])
-        if k != n
-        else sum(vl[:k])
-    )
-
-
-if __name__ == "__main__":
-    import doctest
-
-    doctest.testmod()

dynamic_programming/fractional_knapsack_2.py

@@ -1,53 +0,0 @@
-# https://en.wikipedia.org/wiki/Continuous_knapsack_problem
-# https://www.guru99.com/fractional-knapsack-problem-greedy.html
-# https://medium.com/walkinthecode/greedy-algorithm-fractional-knapsack-problem-9aba1daecc93
-
-from __future__ import annotations
-
-
-def fractional_knapsack(
-    value: list[int], weight: list[int], capacity: int
-) -> tuple[float, list[float]]:
-    """
-    >>> value = [1, 3, 5, 7, 9]
-    >>> weight = [0.9, 0.7, 0.5, 0.3, 0.1]
-    >>> fractional_knapsack(value, weight, 5)
-    (25, [1, 1, 1, 1, 1])
-    >>> fractional_knapsack(value, weight, 15)
-    (25, [1, 1, 1, 1, 1])
-    >>> fractional_knapsack(value, weight, 25)
-    (25, [1, 1, 1, 1, 1])
-    >>> fractional_knapsack(value, weight, 26)
-    (25, [1, 1, 1, 1, 1])
-    >>> fractional_knapsack(value, weight, -1)
-    (-90.0, [0, 0, 0, 0, -10.0])
-    >>> fractional_knapsack([1, 3, 5, 7], weight, 30)
-    (16, [1, 1, 1, 1])
-    >>> fractional_knapsack(value, [0.9, 0.7, 0.5, 0.3, 0.1], 30)
-    (25, [1, 1, 1, 1, 1])
-    >>> fractional_knapsack([], [], 30)
-    (0, [])
-    """
-    index = list(range(len(value)))
-    ratio = [v / w for v, w in zip(value, weight)]
-    index.sort(key=lambda i: ratio[i], reverse=True)
-
-    max_value: float = 0
-    fractions: list[float] = [0] * len(value)
-    for i in index:
-        if weight[i] <= capacity:
-            fractions[i] = 1
-            max_value += value[i]
-            capacity -= weight[i]
-        else:
-            fractions[i] = capacity / weight[i]
-            max_value += value[i] * capacity / weight[i]
-            break
-
-    return max_value, fractions
-
-
-if __name__ == "__main__":
-    import doctest
-
-    doctest.testmod()