Create-Add files to greedy_method directory

greedy_method/greedy_knapsack.py

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+# To get an insight into Greedy Algorithm through the Knapsack problem
+
+
+"""
+A shopkeeper has bags of wheat that each have different weights and different profits.
+eg.
+profit 5 8 7 1 12 3 4
+weight 2 7 1 6  4 2 5
+max_weight 100
+
+Constraints:
+max_weight > 0
+profit[i] >= 0
+weight[i] >= 0
+Calculate the maximum profit that the shopkeeper can make given maxmum weight that can
+be carried.
+"""
+from typing import Union
+
+
+def calc_profit(profit: list, weight: list, max_weight: int) -> Union[str, int]:
+    """
+    Function description is as follows-
+    :param profit: Take a list of profits
+    :param weight: Take a list of weight if bags corresponding to the profits
+    :param max_weight: Maximum weight that could be carried
+    :return: Maximum expected gain
+
+    >>> calc_profit([1, 2, 3], [3, 4, 5], 15)
+    6
+    >>> calc_profit([10, 9 , 8], [3 ,4 , 5], 25)
+    27
+    """
+    if len(profit) != len(weight):
+        raise ValueError("The length of profit and weight must be same.")
+    if max_weight <= 0:
+        raise ValueError("max_weight must greater than zero.")
+    if any(p < 0 for p in profit):
+        raise ValueError("Profit can not be negative.")
+    if any(w < 0 for w in weight):
+        raise ValueError("Weight can not be negative.")
+
+    # List created to store profit gained for the 1kg in case of each weight
+    # respectively.  Calculate and append profit/weight for each element.
+    profit_by_weight = [p / w for p, w in zip(profit, weight)]
+
+    # Creating a copy of the list and sorting profit/weight in ascending order
+    sorted_profit_by_weight = sorted(profit_by_weight)
+
+    # declaring useful variables
+    length = len(sorted_profit_by_weight)
+    limit = 0
+    gain = 0
+    i = 0
+
+    # loop till the total weight do not reach max limit e.g. 15 kg and till i<length
+    while limit <= max_weight and i < length:
+        # flag value for encountered greatest element in sorted_profit_by_weight
+        biggest_profit_by_weight = sorted_profit_by_weight[length - i - 1]
+        """
+        Calculate the index of the biggest_profit_by_weight in profit_by_weight list.
+        This will give the index of the first encountered element which is same as of
+        biggest_profit_by_weight.  There may be one or more values same as that of
+        biggest_profit_by_weight but index always encounter the very first element
+        only.  To curb this alter the values in profit_by_weight once they are used
+        here it is done to -1 because neither profit nor weight can be in negative.
+        """
+        index = profit_by_weight.index(biggest_profit_by_weight)
+        profit_by_weight[index] = -1
+
+        # check if the weight encountered is less than the total weight
+        # encountered before.
+        if max_weight - limit >= weight[index]:
+            limit += weight[index]
+            # Adding profit gained for the given weight 1 ===
+            # weight[index]/weight[index]
+            gain += 1 * profit[index]
+        else:
+            # Since the weight encountered is greater than limit, therefore take the
+            # required number of remaining kgs and calculate profit for it.
+            # weight remaining / weight[index]
+            gain += (max_weight - limit) / weight[index] * profit[index]
+            break
+        i += 1
+    return gain
+
+
+if __name__ == "__main__":
+    print(
+        "Input profits, weights, and then max_weight (all positive ints) separated by "
+        "spaces."
+    )
+
+    profit = [int(x) for x in input("Input profits separated by spaces: ").split()]
+    weight = [int(x) for x in input("Input weights separated by spaces: ").split()]
+    max_weight = int(input("Max weight allowed: "))
+
+    # Function Call
+    calc_profit(profit, weight, max_weight)

greedy_method/test_knapsack.py

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+import unittest
+import greedy_knapsack as kp
+
+
+class TestClass(unittest.TestCase):
+    """
+    Test cases for knapsack
+    """
+
+    def test_sorted(self):
+        """
+        kp.calc_profit takes the required argument (profit, weight, max_weight)
+        and returns whether the answer matches to the expected ones
+        """
+        profit = [10, 20, 30, 40, 50, 60]
+        weight = [2, 4, 6, 8, 10, 12]
+        max_weight = 100
+        self.assertEqual(kp.calc_profit(profit, weight, max_weight), 210)
+
+    def test_negative_max_weight(self):
+        """
+        Returns ValueError for any negative max_weight value
+        :return: ValueError
+        """
+        # profit = [10, 20, 30, 40, 50, 60]
+        # weight = [2, 4, 6, 8, 10, 12]
+        # max_weight = -15
+        self.assertRaisesRegex(ValueError, "max_weight must greater than zero.")
+
+    def test_negative_profit_value(self):
+        """
+        Returns ValueError for any negative profit value in the list
+        :return: ValueError
+        """
+        # profit = [10, -20, 30, 40, 50, 60]
+        # weight = [2, 4, 6, 8, 10, 12]
+        # max_weight = 15
+        self.assertRaisesRegex(
+            ValueError, "Weight can not be negative.",
+        )
+
+    def test_negative_weight_value(self):
+        """
+        Returns ValueError for any negative weight value in the list
+        :return: ValueError
+        """
+        # profit = [10, 20, 30, 40, 50, 60]
+        # weight = [2, -4, 6, -8, 10, 12]
+        # max_weight = 15
+        self.assertRaisesRegex(ValueError, "Profit can not be negative.")
+
+    def test_null_max_weight(self):
+        """
+        Returns ValueError for any zero max_weight value
+        :return: ValueError
+        """
+        # profit = [10, 20, 30, 40, 50, 60]
+        # weight = [2, 4, 6, 8, 10, 12]
+        # max_weight = null
+        self.assertRaisesRegex(ValueError, "max_weight must greater than zero.")
+
+    def test_unequal_list_length(self):
+        """
+        Returns IndexError if length of lists (profit and weight) are unequal.
+        :return: IndexError
+        """
+        # profit = [10, 20, 30, 40, 50]
+        # weight = [2, 4, 6, 8, 10, 12]
+        # max_weight = 100
+        self.assertRaisesRegex(IndexError, "The length of profit and weight must be same.")
+
+
+if __name__ == "__main__":
+    unittest.main()