[Solved] What is the main functionality provided by scipy.sparse.linalg.cg in solving linear systems? — Ans: It solves symmetric positive definite linear systems using an iterative method. | SciPy

SciPy - Sparse Linear Algebra

What is the main functionality provided by scipy.sparse.linalg.cg in solving linear systems?

AIt performs direct LU decomposition on sparse matrices.

BIt solves symmetric positive definite linear systems using an iterative method.

CIt computes eigenvalues of sparse matrices.

DIt converts dense matrices to sparse format.

Step-by-Step Solution

Solution:

Step 1: Understand the function
cg stands for Conjugate Gradient, an iterative solver designed for symmetric positive definite matrices.
Step 2: Eliminate incorrect options
LU decomposition is a direct method, eigenvalue computation is unrelated, and conversion to sparse format is not the purpose of cg.
Final Answer:
It solves symmetric positive definite linear systems using an iterative method. -> Option B
Quick Check:
Conjugate Gradient is for SPD systems [OK]

Quick Trick: CG solves SPD linear systems iteratively [OK]

Common Mistakes:

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