[PYTHON MATRIX-SIG] Elementary test suite for LinearAlgebra

[Konrad Hinsen]

from Numeric import *
from LinearAlgebra import *


def test(a, b):

    print "All numbers printed should be (almost) zero:"

    x = solve_linear_equations(a, b)
    check = b - matrixmultiply(a, x)
    print check


    a_inv = inverse(a)
    check = matrixmultiply(a, a_inv)-identity(a.shape[0])
    print check


    ev = eigenvalues(a)

    evalues, evectors = eigenvectors(a)
    check = ev-evalues
    print check

    evectors = transpose(evectors)
    check = matrixmultiply(a, evectors)-evectors*evalues
    print check


    u, s, vt = singular_value_decomposition(a)
    check = a - Numeric.matrixmultiply(u*s, vt)
    print check


    a_ginv = generalized_inverse(a)
    check = matrixmultiply(a, a_ginv)-identity(a.shape[0])
    print check


    det = determinant(a)
    check = det-multiply.reduce(evalues)
    print check

    x, residuals, rank, sv = linear_least_squares(a, b)
    check = b - matrixmultiply(a, x)
    print check
    print rank-a.shape[0]
    print sv-s

a = array([[1.,2.], [3.,4.]])
b = array([2., 1.])
test(a, b)

a = a+0j
b = b+0j
test(a, b)

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