Description#
Given two sparse matrices mat1
of size m x k
and mat2
of size k x n
, return the result of mat1 x mat2
. You may assume that multiplication is always possible.
Example 1:
Input: mat1 = [[1,0,0],[-1,0,3]], mat2 = [[7,0,0],[0,0,0],[0,0,1]]
Output: [[7,0,0],[-7,0,3]]
Example 2:
Input: mat1 = [[0]], mat2 = [[0]]
Output: [[0]]
Constraints:
m == mat1.length
k == mat1[i].length == mat2.length
n == mat2[i].length
1 <= m, n, k <= 100
-100 <= mat1[i][j], mat2[i][j] <= 100
Solutions#
Solution 1: Direct Multiplication#
We can directly calculate each element in the result matrix according to the definition of matrix multiplication.
The time complexity is $O(m \times n \times k)$, and the space complexity is $O(m \times n)$. Where $m$ and $n$ are the number of rows of matrix $mat1$ and the number of columns of matrix $mat2$ respectively, and $k$ is the number of columns of matrix $mat1$ or the number of rows of matrix $mat2$.
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| class Solution:
def multiply(self, mat1: List[List[int]], mat2: List[List[int]]) -> List[List[int]]:
m, n = len(mat1), len(mat2[0])
ans = [[0] * n for _ in range(m)]
for i in range(m):
for j in range(n):
for k in range(len(mat2)):
ans[i][j] += mat1[i][k] * mat2[k][j]
return ans
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| class Solution {
public int[][] multiply(int[][] mat1, int[][] mat2) {
int m = mat1.length, n = mat2[0].length;
int[][] ans = new int[m][n];
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j) {
for (int k = 0; k < mat2.length; ++k) {
ans[i][j] += mat1[i][k] * mat2[k][j];
}
}
}
return ans;
}
}
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| class Solution {
public:
vector<vector<int>> multiply(vector<vector<int>>& mat1, vector<vector<int>>& mat2) {
int m = mat1.size(), n = mat2[0].size();
vector<vector<int>> ans(m, vector<int>(n));
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j) {
for (int k = 0; k < mat2.size(); ++k) {
ans[i][j] += mat1[i][k] * mat2[k][j];
}
}
}
return ans;
}
};
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| func multiply(mat1 [][]int, mat2 [][]int) [][]int {
m, n := len(mat1), len(mat2[0])
ans := make([][]int, m)
for i := range ans {
ans[i] = make([]int, n)
}
for i := 0; i < m; i++ {
for j := 0; j < n; j++ {
for k := 0; k < len(mat2); k++ {
ans[i][j] += mat1[i][k] * mat2[k][j]
}
}
}
return ans
}
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| function multiply(mat1: number[][], mat2: number[][]): number[][] {
const [m, n] = [mat1.length, mat2[0].length];
const ans: number[][] = Array.from({ length: m }, () => Array.from({ length: n }, () => 0));
for (let i = 0; i < m; ++i) {
for (let j = 0; j < n; ++j) {
for (let k = 0; k < mat2.length; ++k) {
ans[i][j] += mat1[i][k] * mat2[k][j];
}
}
}
return ans;
}
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Solution 2: Preprocessing#
We can preprocess the sparse representation of the two matrices, i.e., $g1[i]$ represents the column index and value of all non-zero elements in the $i$th row of matrix $mat1$, and $g2[i]$ represents the column index and value of all non-zero elements in the $i$th row of matrix $mat2$.
Next, we traverse each row $i$, traverse each element $(k, x)$ in $g1[i]$, traverse each element $(j, y)$ in $g2[k]$, then $mat1[i][k] \times mat2[k][j]$ will correspond to $ans[i][j]$ in the result matrix, and we can accumulate all the results.
The time complexity is $O(m \times n \times k)$, and the space complexity is $O(m \times n)$. Where $m$ and $n$ are the number of rows of matrix $mat1$ and the number of columns of matrix $mat2$ respectively, and $k$ is the number of columns of matrix $mat1$ or the number of rows of matrix $mat2$.
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| class Solution:
def multiply(self, mat1: List[List[int]], mat2: List[List[int]]) -> List[List[int]]:
def f(mat: List[List[int]]) -> List[List[int]]:
g = [[] for _ in range(len(mat))]
for i, row in enumerate(mat):
for j, x in enumerate(row):
if x:
g[i].append((j, x))
return g
g1 = f(mat1)
g2 = f(mat2)
m, n = len(mat1), len(mat2[0])
ans = [[0] * n for _ in range(m)]
for i in range(m):
for k, x in g1[i]:
for j, y in g2[k]:
ans[i][j] += x * y
return ans
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| class Solution {
public int[][] multiply(int[][] mat1, int[][] mat2) {
int m = mat1.length, n = mat2[0].length;
int[][] ans = new int[m][n];
var g1 = f(mat1);
var g2 = f(mat2);
for (int i = 0; i < m; ++i) {
for (int[] p : g1[i]) {
int k = p[0], x = p[1];
for (int[] q : g2[k]) {
int j = q[0], y = q[1];
ans[i][j] += x * y;
}
}
}
return ans;
}
private List<int[]>[] f(int[][] mat) {
int m = mat.length, n = mat[0].length;
List<int[]>[] g = new List[m];
Arrays.setAll(g, i -> new ArrayList<>());
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j) {
if (mat[i][j] != 0) {
g[i].add(new int[] {j, mat[i][j]});
}
}
}
return g;
}
}
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| class Solution {
public:
vector<vector<int>> multiply(vector<vector<int>>& mat1, vector<vector<int>>& mat2) {
int m = mat1.size(), n = mat2[0].size();
vector<vector<int>> ans(m, vector<int>(n));
auto g1 = f(mat1), g2 = f(mat2);
for (int i = 0; i < m; ++i) {
for (auto& [k, x] : g1[i]) {
for (auto& [j, y] : g2[k]) {
ans[i][j] += x * y;
}
}
}
return ans;
}
vector<vector<pair<int, int>>> f(vector<vector<int>>& mat) {
int m = mat.size(), n = mat[0].size();
vector<vector<pair<int, int>>> g(m);
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j) {
if (mat[i][j]) {
g[i].emplace_back(j, mat[i][j]);
}
}
}
return g;
}
};
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| func multiply(mat1 [][]int, mat2 [][]int) [][]int {
m, n := len(mat1), len(mat2[0])
ans := make([][]int, m)
for i := range ans {
ans[i] = make([]int, n)
}
f := func(mat [][]int) [][][2]int {
m, n := len(mat), len(mat[0])
g := make([][][2]int, m)
for i := range g {
g[i] = make([][2]int, 0, n)
for j := range mat[i] {
if mat[i][j] != 0 {
g[i] = append(g[i], [2]int{j, mat[i][j]})
}
}
}
return g
}
g1, g2 := f(mat1), f(mat2)
for i := range g1 {
for _, p := range g1[i] {
k, x := p[0], p[1]
for _, q := range g2[k] {
j, y := q[0], q[1]
ans[i][j] += x * y
}
}
}
return ans
}
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| function multiply(mat1: number[][], mat2: number[][]): number[][] {
const [m, n] = [mat1.length, mat2[0].length];
const ans: number[][] = Array.from({ length: m }, () => Array.from({ length: n }, () => 0));
const f = (mat: number[][]): number[][][] => {
const [m, n] = [mat.length, mat[0].length];
const ans: number[][][] = Array.from({ length: m }, () => []);
for (let i = 0; i < m; ++i) {
for (let j = 0; j < n; ++j) {
if (mat[i][j] !== 0) {
ans[i].push([j, mat[i][j]]);
}
}
}
return ans;
};
const g1 = f(mat1);
const g2 = f(mat2);
for (let i = 0; i < m; ++i) {
for (const [k, x] of g1[i]) {
for (const [j, y] of g2[k]) {
ans[i][j] += x * y;
}
}
}
return ans;
}
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