Files

import numpy as np
import prairielearn as pl
import scipy.linalg as sla


def generate(data):
    sf = 2

    # Matrix shape
    M = 3

    myNumber = 2.148233

    # Generating the orthogonal matrix U
    # (numbers rounded with 2 decimal digits)
    X = np.random.rand(M, M)
    Q, _ = sla.qr(X)  # type: ignore
    U = np.around(Q, sf + 1)

    b = np.random.rand(M)
    bc = b.reshape((M, 1))
    br = b.reshape(1, M)

    data["params"]["sf"] = sf
    data["params"]["M"] = M
    data["params"]["U"] = pl.to_json(U)
    data["params"]["myNumber"] = pl.to_json(myNumber)
    data["params"]["b"] = pl.to_json(br)
    data["params"]["c"] = pl.to_json(bc)