1570. Dot Product of Two Sparse Vectors

문제 §

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) = 10 + 03 + 00 + 24 + 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) = 00 + 10 + 00 + 00 + 0*2 = 0

Example 3:

Input: nums1 = [0,1,0,0,2,0,0], nums2 = [1,0,0,0,3,0,4] Output: 6

제한조건 §

• n == nums1.length == nums2.length
• 1 <= n <= 10^5
• 0 <= nums1[i], nums2[i] <= 100

아이디어 §

• 둘의 length가 같음 -> length가 0 인경우 진행 x
• 둘중 하나만 0인 경우 -> continue

풀이 §

class SparseVector:
	def __init__(self, nums: List[int]):
	self.vec = nums
 
	# Return the dotProduct of two sparse vectors
 
	def dotProduct(self, vec: 'SparseVector') -> int:
		if len(self.vec) == 0:	
		return 0
		ans = 0
		for item in zip(self.vec, vec.vec):
			if item[0] == 0 or item[1] == 0:
				continue
			ans += item[0]*item[1]
		return ans
# Your SparseVector object will be instantiated and called as such:
# v1 = SparseVector(nums1)
# v2 = SparseVector(nums2)
# ans = v1.dotProduct(v2)

후기 §

이정도는 쉬웠다 #python