[Solved] What will be the output of the following code snippet?import numpy as np from scipy.sparse.linalg import cg A = np.array([[4,1],[1,3]]) b = np.array([1,2]) x, info = cg(A, b) print(np.round(x, 2)) | SciPy

SciPy - Sparse Linear Algebra

What will be the output of the following code snippet?

import numpy as np
from scipy.sparse.linalg import cg
A = np.array([[4,1],[1,3]])
b = np.array([1,2])
x, info = cg(A, b)
print(np.round(x, 2))

A[0.09 0.64]

B[0.25 0.5]

C[0.2 0.6]

D[0.1 0.7]

Step-by-Step Solution

Solution:

Step 1: Understand the problem setup
The matrix A and vector b define the system Ax = b. We solve using Conjugate Gradient.
Step 2: Solve the system manually or by code
Solving gives x ≈ [0.1, 0.7]. Rounding to 2 decimals matches [0.1 0.7].
Final Answer:
[0.1 0.7] -> Option D
Quick Check:
cg solution vector ≈ [0.1 0.7] [OK]

Quick Trick: cg solves Ax=b; round solution to check answer [OK]

Common Mistakes:

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