Given two sparse vectors, compute their dot product.
Implement class SparseVector
:
SparseVector(nums)
Initializes the object with the vectornums
dotProduct(vec)
Compute the dot product between the instance of SparseVector andvec
A sparse vector is a vector that has mostly zero values, you should store the sparse vector efficiently and compute the dot product between two SparseVector.
Follow up: What if only one of the vectors is sparse?
Example 1:
Input: nums1 = [1,0,0,2,3], nums2 = [0,3,0,4,0] Output: 8 Explanation: v1 = SparseVector(nums1) , v2 = SparseVector(nums2) v1.dotProduct(v2) = 1*0 + 0*3 + 0*0 + 2*4 + 3*0 = 8
Example 2:
Input: nums1 = [0,1,0,0,0], nums2 = [0,0,0,0,2] Output: 0 Explanation: v1 = SparseVector(nums1) , v2 = SparseVector(nums2) v1.dotProduct(v2) = 0*0 + 1*0 + 0*0 + 0*0 + 0*2 = 0
Example 3:
Input: nums1 = [0,1,0,0,2,0,0], nums2 = [1,0,0,0,3,0,4] Output: 6
Constraints:
n == nums1.length == nums2.length
1 <= n <= 10^5
0 <= nums1[i], nums2[i] <= 100
class SparseVector:
def __init__(self, nums: List[int]):
self.v = {}
for i, num in enumerate(nums):
if num != 0:
self.v[i] = num
# Return the dotProduct of two sparse vectors
def dotProduct(self, vec: 'SparseVector') -> int:
res = 0
if len(self.v) > len(vec.v):
self.v, vec.v = vec.v, self.v
for i, num in self.v.items():
if i not in vec.v:
continue
res += num * vec.v[i]
return res
# Your SparseVector object will be instantiated and called as such:
# v1 = SparseVector(nums1)
# v2 = SparseVector(nums2)
# ans = v1.dotProduct(v2)
class SparseVector {
private Map<Integer, Integer> v;
SparseVector(int[] nums) {
v = new HashMap<>();
for (int i = 0; i < nums.length; ++i) {
if (nums[i] != 0) {
v.put(i, nums[i]);
}
}
}
// Return the dotProduct of two sparse vectors
public int dotProduct(SparseVector vec) {
int res = 0;
if (v.size() > vec.v.size()) {
Map<Integer, Integer> t = v;
v = vec.v;
vec.v = t;
}
for (Map.Entry<Integer, Integer> entry : v.entrySet()) {
int i = entry.getKey(), num = entry.getValue();
res += num * vec.v.getOrDefault(i, 0);
}
return res;
}
}
// Your SparseVector object will be instantiated and called as such:
// SparseVector v1 = new SparseVector(nums1);
// SparseVector v2 = new SparseVector(nums2);
// int ans = v1.dotProduct(v2);