Merge pull request #52 from sharadbhat/master

Added fractional knapsack and minor changes

Author: OmkarPathak

pygorithm/__init__.py

@@ -56,7 +56,8 @@
     "Songzhuozhuo 'souo'",
     "Emil 'Skeen' Madsen",
     "Ian 'IanDoarn' Doarn",
-    "Timothy 'Tjstretchalot' Moore"
+    "Timothy 'Tjstretchalot' Moore",
+    "Sharad 'sharadbhat' Bhat"
 ]
 
 __all__ = [
@@ -69,5 +70,6 @@
     'sorting',
     'string',
     'pathfinding'
-    'geometry'
+    'geometry',
+    'greedy_algorithm'
 ]

pygorithm/dynamic_programming/binary_knapsack.py

@@ -3,13 +3,25 @@
 Created At: 25th August 2017
 '''
 
-def knapsack(W, value, weight, n):
+import inspect
+
+def knapsack(W, value, weight):
     '''
         :param W: maximum weight capacity
         :param value: an array of values of items in the knapsack
         :param weight: an array of weights of items in the knapsack
-        :param n: number of items in the knapsack
     '''
+    if type(value) is not list:
+        raise TypeError("binary knapsack only accepts lists, not {}".format(str(type(value))))
+    if type(weight) is not list:
+        raise TypeError("binary knapsack only accepts lists, not {}".format(str(type(weight))))
+
+    if len(value) != len(weight):
+        raise ValueError("both the lists must be of same length")
+
+    # n = number of items
+    n = len(value)
+
     knap_sack = [[0 for x in range(W+1)] for x in range(n+1)]
 
     for j in range(W + 1):

pygorithm/greedy_algorithm/__init__.py

@@ -0,0 +1,8 @@
+"""
+Collection for greedy algorithms
+"""
+from . import fractional_knapsack
+
+__all__ = [
+    'fractional_knapsack'
+]

pygorithm/greedy_algorithm/fractional_knapsack.py

@@ -0,0 +1,60 @@
+"""
+Author: SHARAD BHAT
+Created On: 22nd August 2017
+"""
+
+import inspect
+
+def knapsack(W, item_values, item_weights):
+    """
+    :param W: maximum weight capacity
+    :param item_values: a list of values of items in the knapsack
+    :param item_weights: a list of weights of items in the knapsack
+    """
+
+    if type(item_values) is not list:
+        raise TypeError("fractional knapsack only accepts lists, not {}".format(str(type(item_values))))
+    if type(item_weights) is not list:
+        raise TypeError("fractional knapsack only accepts lists, not {}".format(str(type(item_weights))))
+
+    if len(item_values) != len(item_weights):
+        raise ValueError("length of both lists must be same")
+
+    n = len(item_values)
+
+    fractional_weights = []
+    for i in range(0, n):
+        fractional_weights.append(item_values[i] / item_weights[i])
+
+    # Sorting items based on maximum fractional profit
+    for i in range(0, n):
+        maximum = i
+        for j in range(i, n):
+            if fractional_weights[maximum] < fractional_weights[j]:
+                maximum = j
+
+        fractional_weights[i], fractional_weights[maximum] = fractional_weights[maximum], fractional_weights[i]
+        item_values[i], item_values[maximum] = item_values[maximum], item_values[i]
+        item_weights[i], item_weights[maximum] = item_weights[maximum], item_weights[i]
+
+    # Placing items in knapsack
+    remaining_space = W
+    profit = 0
+    for i in range(0, n):
+        if remaining_space > item_weights[i]:
+            profit += item_values[i]
+            remaining_space -= item_weights[i]
+        else:
+            profit += fractional_weights[i] * remaining_space
+            remaining_space = 0
+            break
+
+    return profit
+
+
+
+def get_code():
+    """
+    returns the code for the knapsack function
+    """
+    return inspect.getsource(knapsack)