Lab 02 — NumPy & Linear Algebra

Solve Ax=b and perform least squares.

import numpy as np
A = np.array([[3.,2.],[1.,2.]])
b = np.array([5.,5.])
x = np.linalg.solve(A,b)
print('Solution x=', x)

# Least squares example
t = np.linspace(0,1,20)
y = 3*t + 1 + 0.1*np.random.randn(t.size)
X = np.c_[t, np.ones_like(t)]
beta, *_ = np.linalg.lstsq(X, y, rcond=None)
print('beta (slope, intercept)=', beta)