# Demonstration of using numpy to compute eigenvalues and eigenvalues
# CMP 464/788 Spring 2017
# Megan Owen

import numpy as np


# create a 2x2 matrix
m = np.array([[1,2],[3,4]])

print("Matrix is:",m)

evals, evects = np.linalg.eig(m)

print("Eigenvalues are: ",evals)

print("Corresponding eigenvectors are:",evects)

det = np.linalg.det(m)

print("Determinant is:",det)

identity = np.array([[1,0],[0,1]])

# 2x2 matrix multiplication is done using the dot() method in numpy.
# Using * performs coordinate-wise multiplication between the two arrays.

m_matmult_id = np.dot(m,identity)
print("Matrix multiplication of m with the identity matrix:",m_matmult_id)

m_coordmult_id = m*identity
print("Coordindate-wise multiplication of m with the identity matrix:",m_coordmult_id)