def test_resolution(self, n = 100):
dense = np.arange(n*n).reshape(n,n)
R1 = Resolution(dense)
assert scipy.sparse.isspmatrix_dia(R1),'Resolution is not recognized as a scipy.sparse.dia_matrix.'
assert len(R1.offsets) == desispec.resolution.default_ndiag, 'Resolution.offsets has wrong size'
R2 = Resolution(R1)
assert np.array_equal(R1.toarray(),R2.toarray()),'Constructor broken for dia_matrix input.'
R3 = Resolution(R1.data)
assert np.array_equal(R1.toarray(),R3.toarray()),'Constructor broken for array data input.'
sparse = scipy.sparse.dia_matrix((R1.data[::-1],R1.offsets[::-1]),(n,n))
R4 = Resolution(sparse)
assert np.array_equal(R1.toarray(),R4.toarray()),'Constructor broken for permuted offsets input.'
R5 = Resolution(R1.to_fits_array())
assert np.array_equal(R1.toarray(),R5.toarray()),'to_fits_array() is broken.'
#- test different sizes of input diagonals
for ndiag in [3,5,11]:
R6 = Resolution(np.ones((ndiag, n)))
assert len(R6.offsets) == ndiag, 'Constructor broken for ndiag={}'.format(ndiag)
#- An even number if diagonals is not allowed
try:
ndiag = 10
R7 = Resolution(np.ones((ndiag, n)))
raise RuntimeError('Incorrectly created Resolution with even number of diagonals')
except ValueError, err:
#- it correctly raised an error, so pass
pass
def test_resolution(self, n=100):
dense = np.arange(n * n).reshape(n, n)
R1 = Resolution(dense)
assert scipy.sparse.isspmatrix_dia(
R1), 'Resolution is not recognized as a scipy.sparse.dia_matrix.'
assert len(
R1.offsets
) == desispec.resolution.default_ndiag, 'Resolution.offsets has wrong size'
R2 = Resolution(R1)
assert np.array_equal(
R1.toarray(),
R2.toarray()), 'Constructor broken for dia_matrix input.'
R3 = Resolution(R1.data)
assert np.array_equal(
R1.toarray(),
R3.toarray()), 'Constructor broken for array data input.'
sparse = scipy.sparse.dia_matrix((R1.data[::-1], R1.offsets[::-1]),
(n, n))
R4 = Resolution(sparse)
assert np.array_equal(
R1.toarray(),
R4.toarray()), 'Constructor broken for permuted offsets input.'
R5 = Resolution(R1.to_fits_array())
assert np.array_equal(R1.toarray(),
R5.toarray()), 'to_fits_array() is broken.'
#- test different sizes of input diagonals
for ndiag in [3, 5, 11]:
R6 = Resolution(np.ones((ndiag, n)))
assert len(
R6.offsets) == ndiag, 'Constructor broken for ndiag={}'.format(
ndiag)
#- An even number if diagonals is not allowed
try:
ndiag = 10
R7 = Resolution(np.ones((ndiag, n)))
raise RuntimeError(
'Incorrectly created Resolution with even number of diagonals')
except ValueError as err:
#- it correctly raised an error, so pass
pass
#- Test creation with sigmas - it should conserve flux
R9 = Resolution(np.linspace(1.0, 2.0, n))
self.assertTrue(np.allclose(np.sum(R9.data, axis=0), 1.0))
