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Formatted question description: https://leetcode.ca/all/1570.html
1570. Dot Product of Two Sparse Vectors
Given two sparse vectors, compute their dot product.
Implement class SparseVector:
SparseVector(nums) Initializes the object with the vector nums
dotProduct(vec) Compute the dot product between the instance of SparseVector and vec
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
Algorithm
Store in hashmap for only indexes with values.
Code
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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);
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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)