Given two matrices of the same dimensions, return the resultant matrix of their subtraction.
{
"matrix1": [
[1, 2, 3],
[10, 11, 12]
],
"matrix2": [
[7, 8, 9],
[4, 5, 6]
]
}
Output:
[
[-6, -6, -6],
[6, 6, 6]
]
The two matrix operands of the subtraction operation are provided as two arguments, matrix1
and matrix2
, to the function. The function should return the result of the subtraction of matrix2
from matrix1
.
Constraints:
/*
Asymptotic complexity in terms of the number of rows ( = \`n\`) and the number of columns ( = \`m\`):
* Time: O(n * m).
* Auxiliary space: O(1).
* Total space: O(n * m).
*/
vector<vector<int>> matrix_subtraction(vector<vector<int>> &matrix1, vector<vector<int>> &matrix2) {
int number_of_rows = matrix1.size();
int number_of_columns = matrix1[0].size();
// We'll store the result of the subtraction operation in the argument variable \`matrix1\` in-place and return it
// at the end. This way, we won't need any additional memory space for the resultant matrix, and so the auxiliary
// space complexity would stay at O(1).
for(int i = 0; i < number_of_rows; i++){
for(int j = 0; j < number_of_columns; j++){
matrix1[i][j] = matrix1[i][j] - matrix2[i][j];
}
}
return matrix1;
}
We hope that these solutions to the matrix subtraction problem have helped you level up your coding skills. You can expect problems like these at top tech companies like Amazon and Google.
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Given two matrices of the same dimensions, return the resultant matrix of their subtraction.
{
"matrix1": [
[1, 2, 3],
[10, 11, 12]
],
"matrix2": [
[7, 8, 9],
[4, 5, 6]
]
}
Output:
[
[-6, -6, -6],
[6, 6, 6]
]
The two matrix operands of the subtraction operation are provided as two arguments, matrix1
and matrix2
, to the function. The function should return the result of the subtraction of matrix2
from matrix1
.
Constraints:
/*
Asymptotic complexity in terms of the number of rows ( = \`n\`) and the number of columns ( = \`m\`):
* Time: O(n * m).
* Auxiliary space: O(1).
* Total space: O(n * m).
*/
vector<vector<int>> matrix_subtraction(vector<vector<int>> &matrix1, vector<vector<int>> &matrix2) {
int number_of_rows = matrix1.size();
int number_of_columns = matrix1[0].size();
// We'll store the result of the subtraction operation in the argument variable \`matrix1\` in-place and return it
// at the end. This way, we won't need any additional memory space for the resultant matrix, and so the auxiliary
// space complexity would stay at O(1).
for(int i = 0; i < number_of_rows; i++){
for(int j = 0; j < number_of_columns; j++){
matrix1[i][j] = matrix1[i][j] - matrix2[i][j];
}
}
return matrix1;
}
We hope that these solutions to the matrix subtraction problem have helped you level up your coding skills. You can expect problems like these at top tech companies like Amazon and Google.
If you are preparing for a tech interview at FAANG or any other Tier-1 tech company, register for Interview Kickstart’s FREE webinar to understand the best way to prepare.
Interview Kickstart offers interview preparation courses taught by FAANG+ tech leads and seasoned hiring managers. Our programs include a comprehensive curriculum, unmatched teaching methods, and career coaching to help you nail your next tech interview.
We offer 18 interview preparation courses, each tailored to a specific engineering domain or role, including the most in-demand and highest-paying domains and roles, such as:
To learn more, register for the FREE webinar.
Attend our free webinar to amp up your career and get the salary you deserve.