[Solved] What will be the output of the following code?import numpy as np from scipy.sparse import csr_matrix arr = np.array([[0, 1], [2, 0]]) sparse_mat = csr_matrix(arr) result = sparse_mat.dot(np.... | SciPy

SciPy - Sparse Matrices (scipy.sparse)

What will be the output of the following code?

import numpy as np
from scipy.sparse import csr_matrix

arr = np.array([[0, 1], [2, 0]])
sparse_mat = csr_matrix(arr)
result = sparse_mat.dot(np.array([1, 2]))
print(result.toarray())

A[[2] [2]]

B[[2 4] [1 2]]

C[[2 0] [0 1]]

D[[2] [1]]

Step-by-Step Solution

Solution:

Step 1: Understand matrix and vector multiplication
The sparse matrix is [[0,1],[2,0]]. Multiplying by vector [1,2] means:
Row 1: 0*1 + 1*2 = 2
Row 2: 2*1 + 0*2 = 2
Step 2: Check the printed output
The result is a 2x1 matrix with values [[2],[2]]. But the code prints result.toarray(), which shows a 2D array.
So output is:
[[2]
[2]]
Final Answer:
[[2] [2]] -> Option A
Quick Check:
Dot product result = [[2],[2]] [OK]

Quick Trick: Multiply rows by vector elements and sum for dot product [OK]

Common Mistakes:

MISTAKES

Mixing element-wise and dot product multiplication
Confusing shape of output array
Incorrectly summing elements

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More SciPy Quizzes

What will be the output of the following code?

Step 1: Understand matrix and vector multiplication

Step 2: Check the printed output

Final Answer:

Quick Check:

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