Given a n × m binary matrix, count the number of sets where a set can be formed one or more same values in a row or column.
Examples:
Input: 1 0 1 0 1 0 Output: 8 Explanation: There are six one-element sets (three 1s and three 0s). There are two two- element sets, the first one consists of the first and the third cells of the first row. The second one consists of the first and the third cells of the second row. Input: 1 0 1 1 Output: 6
The number of non-empty subsets of x elements is 2x – 1. We traverse every row and calculate numbers of 1’s and 0’s cells. For every u zeros and v ones, total sets is 2u – 1 + 2v – 1. We then traverse all columns and compute same values and compute overall sum. We finally subtract m x n from the overall sum as single elements are considered twice.
# Python3 program to compute number of sets # in a binary matrix. m = 3 # no of columns
n = 2 # no of rows
# function to calculate the number of # non empty sets of cell def countSets(a):
# stores the final answer
res = 0
# traverses row-wise
for i in range (n):
u = 0
v = 0
for j in range (m):
if a[i][j]:
u + = 1
else :
v + = 1
res + = pow ( 2 , u) - 1 + pow ( 2 , v) - 1
# traverses column wise
for i in range (m):
u = 0
v = 0
for j in range (n):
if a[j][i]:
u + = 1
else :
v + = 1
res + = pow ( 2 , u) - 1 + pow ( 2 , v) - 1
# at the end subtract n*m as no of
# single sets have been added twice.
return res - (n * m)
# Driver program to test the above function. a = [[ 1 , 0 , 1 ],[ 0 , 1 , 0 ]]
print (countSets(a))
# This code is contributed by shubhamsingh10 |
Output:
8
Time Complexity: O(n * m)
Space Complexity: O(1) as no extra space has been taken.
Please refer complete article on Counting sets of 1s and 0s in a binary matrix for more details!