import numpy as np

'''
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Use dynamic programming (DP) to solve 0/1 knapsack problem
Time complexity: O(nW), where n is number of items and W is capacity

Author: Kaiyang Zhou
Website: https://kaiyangzhou.github.io/
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knapsack_dp(values,weights,n_items,capacity,return_all=False)

Input arguments:
  1. values: a list of numbers in either int or float, specifying the values of items
  2. weights: a list of int numbers specifying weights of items
  3. n_items: an int number indicating number of items
  4. capacity: an int number indicating the knapsack capacity
  5. return_all: whether return all info, defaulty is False (optional)

Return:
  1. picks: a list of numbers storing the positions of selected items
  2. max_val: maximum value (optional)
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'''
def knapsack_dp(values,weights,n_items,capacity,return_all=False):
    check_inputs(values,weights,n_items,capacity)

    table = np.zeros((n_items+1,capacity+1),dtype=np.float32)
    keep = np.zeros((n_items+1,capacity+1),dtype=np.float32)

    for i in range(1, n_items + 1):
        for w in range(0, capacity + 1):
            wi = weights[i-1] # weight of current item
            vi = values[i-1] # value of current item
            if (wi <= w) and (vi + table[i-1,w-wi] > table[i-1,w]):
                table[i,w] = vi + table[i-1,w-wi]
                keep[i,w] = 1
            else:
                table[i,w] = table[i-1,w]

    picks = []
    K = capacity

    for i in range(n_items, 0, -1):
        if keep[i,K] == 1:
            picks.append(i)
            K -= weights[i-1]

    picks.sort()
    picks = [x-1 for x in picks] # change to 0-index

    if return_all:
        max_val = table[n_items,capacity]
        return picks,max_val
    return picks

def check_inputs(values,weights,n_items,capacity):
    # check variable type
    assert(isinstance(values,list))
    assert(isinstance(weights,list))
    assert(isinstance(n_items,int))
    assert(isinstance(capacity,int))
    # check value type
    assert(all(isinstance(val,int) or isinstance(val,float) for val in values))
    assert(all(isinstance(val,int) for val in weights))
    # check validity of value
    assert(all(val >= 0 for val in weights))
    assert(n_items > 0)
    assert(capacity > 0)

if __name__ == '__main__':
    values = [2,3,4]
    weights = [1,2,3]
    n_items = 3
    capacity = 3
    picks = knapsack_dp(values,weights,n_items,capacity)
    print(picks)
