Given a List, the task is to write a python program that can construct a list with products of consecutive elements for a given number of elements.
Input : test_list = [5, 6, 2, 1, 7, 5, 3], K = 3
Output : [60, 12, 14, 35, 105]
Explanation : 5 * 6 * 2 = 60, 6 * 2 * 1 = 12.. And so on.
Input : test_list = [5, 6, 2, 1, 7, 5, 3], K = 4
Output : [60, 84, 70, 105]
Explanation : 5 * 6 * 2 * 1 = 60, 6 * 2 * 1 * 7 = 84.. And so on.
Method 1 : Using list slicing and loop
In this, we perform task of getting K slice using list slicing and task of getting product is done by an external function call.
Example:
Python3
# getting productdef prod(sub): res = 1 for ele in sub: res = ele * res return res# initializing liststest_list = [5, 6, 2, 1, 7, 5, 3]# printing original listprint("The original list is : " + str(test_list))# initializing KK = 3res = []for idx in range(len(test_list) - K + 1): # getting product using external function res.append(prod(test_list[idx: idx + K]))# printing resultprint("Computed Products : " + str(res)) |
Output:
The original list is : [5, 6, 2, 1, 7, 5, 3]
Computed Products : [60, 12, 14, 35, 105]
Time Complexity: O(n)
Auxiliary Space: O(n)
Method 2 : Using generator, slicing, reduce() and mul operator
In this, generator is used to compute and return intermediate result. Task of getting sliced multiplication is done using inbuilt function reduce(), and mul operator.
Example:
Python3
from functools import reducefrom operator import mul# generator functiondef sliced_prod(sub, K): for idx in range(len(sub) - K + 1): # slicing and returning intermediate product sliced = sub[idx: idx + K] yield reduce(mul, sliced)# generator function# initializing liststest_list = [5, 6, 2, 1, 7, 5, 3]# printing original listprint("The original list is : " + str(test_list))# initializing KK = 3# calling fnc.res = list(sliced_prod(test_list, K))# printing resultprint("Computed Products : " + str(res)) |
Output:
The original list is : [5, 6, 2, 1, 7, 5, 3]
Computed Products : [60, 12, 14, 35, 105]
Time complexity: O(n), where n is the length of the test_list. The generator, slicing, reduce() and mul operator takes O(n) time to create the final list.
Auxiliary Space: O(1), extra space required is not required
Method 3 : Use the numpy library
Python3
import numpy as np# initializing liststest_list = [5, 6, 2, 1, 7, 5, 3]# printing original listprint("The original list is : " + str(test_list))# initializing KK = 3# using numpy libraryresult = np.prod(np.array([test_list[i:i+K] for i in range(len(test_list) - K + 1)]), axis=1)# printing resultprint("Computed Products : " + str(result)) |
OUTPUT : The original list is : [5, 6, 2, 1, 7, 5, 3] Computed Products : [ 60 12 14 35 105]
Time complexity: O(NK), where N is the length of the input list test_list and K is the size of the sliding window.
Auxiliary space: O(NK). We are storing all the intermediate products in an array before computing their product.
