def test_pseudo_inverse():
"Tests of the pseudo-inverse"
# Numerical version of the pseudo-inverse:
pinv_num = core.wrap_array_func(numpy.linalg.pinv)
##########
# Full rank rectangular matrix:
m = unumpy.matrix([[ufloat(10, 1), -3.1],
[0, ufloat(3, 0)],
[1, -3.1]])
# Numerical and package (analytical) pseudo-inverses: they must be
# the same:
rcond = 1e-8 # Test of the second argument to pinv()
m_pinv_num = pinv_num(m, rcond)
m_pinv_package = core.pinv(m, rcond)
assert arrays_close(m_pinv_num, m_pinv_package)
##########
# Example with a non-full rank rectangular matrix:
vector = [ufloat(10, 1), -3.1, 11]
m = unumpy.matrix([vector, vector])
m_pinv_num = pinv_num(m, rcond)
m_pinv_package = core.pinv(m, rcond)
assert arrays_close(m_pinv_num, m_pinv_package)
##########
# Example with a non-full-rank square matrix:
m = unumpy.matrix([[ufloat(10, 1), 0], [3, 0]])
m_pinv_num = pinv_num(m, rcond)
m_pinv_package = core.pinv(m, rcond)
assert arrays_close(m_pinv_num, m_pinv_package)
def test_pseudo_inverse():
"Tests of the pseudo-inverse"
# Numerical version of the pseudo-inverse:
pinv_num = core.wrap_array_func(numpy.linalg.pinv)
##########
# Full rank rectangular matrix:
m = unumpy.matrix([[ufloat(10, 1), -3.1], [0, ufloat(3, 0)], [1, -3.1]])
# Numerical and package (analytical) pseudo-inverses: they must be
# the same:
rcond = 1e-8 # Test of the second argument to pinv()
m_pinv_num = pinv_num(m, rcond)
m_pinv_package = core.pinv(m, rcond)
assert arrays_close(m_pinv_num, m_pinv_package)
##########
# Example with a non-full rank rectangular matrix:
vector = [ufloat(10, 1), -3.1, 11]
m = unumpy.matrix([vector, vector])
m_pinv_num = pinv_num(m, rcond)
m_pinv_package = core.pinv(m, rcond)
assert arrays_close(m_pinv_num, m_pinv_package)
##########
# Example with a non-full-rank square matrix:
m = unumpy.matrix([[ufloat(10, 1), 0], [3, 0]])
m_pinv_num = pinv_num(m, rcond)
m_pinv_package = core.pinv(m, rcond)
assert arrays_close(m_pinv_num, m_pinv_package)