[Solved] Analyze the following code:from scipy.sparse.linalg import svds import numpy as np A = np.array([[1, 2], [3, 4]]) U, s, Vt = svds(A, k=1)What is the issue with this code? | SciPy

SciPy - Sparse Linear Algebra

Analyze the following code:

from scipy.sparse.linalg import svds
import numpy as np
A = np.array([[1, 2], [3, 4]])
U, s, Vt = svds(A, k=1)

What is the issue with this code?

Asvds cannot compute singular values for 2x2 matrices

BThe parameter k=1 is too large for the matrix size

CThe input matrix A is dense; svds expects a sparse matrix format

DThe import statement for svds is incorrect

Step-by-Step Solution

Solution:

Step 1: Check input matrix type
The matrix A is a dense NumPy array, not a sparse matrix.
Step 2: svds expects sparse matrices
svds is designed for sparse matrices (e.g., CSR or CSC format).
Step 3: Fix by converting to sparse
Convert A to a sparse format like csr_matrix(A) before calling svds.
Final Answer:
A -> Option C
Quick Check:
svds requires sparse matrix input [OK]

Quick Trick: svds needs sparse matrix input, not dense [OK]

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