[Solved] You have two matrices:M = np.array([[1, 2], [3, 4]]) N = np.array([[2, 0], [1, 2]])Which code correctly computes the product P = M x N using scipy? | SciPy

SciPy - Linear Algebra (scipy.linalg)

You have two matrices:

M = np.array([[1, 2], [3, 4]])
N = np.array([[2, 0], [1, 2]])

Which code correctly computes the product P = M x N using scipy?

A

<code>from scipy.linalg import dot
P = dot(M, N)</code>

B

<code>import numpy as np
P = np.dot(M, N)</code>

C

<code>from scipy.linalg import matmul
P = matmul(M, N)</code>

D

<code>from scipy.linalg import inv
P = inv(M) * N</code>

Step-by-Step Solution

Solution:

Step 1: Identify correct matrix multiplication function
Scipy.linalg does not have dot or matmul functions; numpy provides np.dot() for matrix multiplication.
Step 2: Check options for correctness
import numpy as np P = np.dot(M, N) uses np.dot(M, N) which correctly multiplies matrices M and N. from scipy.linalg import inv P = inv(M) * N incorrectly uses inverse and element-wise multiplication.
Final Answer:
import numpy as np P = np.dot(M, N) -> Option B
Quick Check:
Matrix product = np.dot() [OK]

Quick Trick: Use np.dot() for matrix multiplication [OK]

Common Mistakes:

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