diff --git a/test/test_spaces/test_lm_space.py b/test/test_spaces/test_lm_space.py index 8442a9647df7d8a6dc19cd7389d62116819257af..0d84a52fcad22e85f2d9f602a1968862a9654255 100644 --- a/test/test_spaces/test_lm_space.py +++ b/test/test_spaces/test_lm_space.py @@ -20,7 +20,7 @@ import unittest import numpy as np from numpy.testing import assert_, assert_equal, assert_raises,\ - assert_almost_equal + assert_almost_equal, assert_array_almost_equal from d2o import distributed_data_object from nifty import LMSpace from test.common import expand @@ -108,15 +108,12 @@ class LMSpaceFunctionalityTests(unittest.TestCase): for key, value in expected.iteritems(): assert_equal(getattr(l, key), value) - @expand(get_hermitian_configs()) - def test_hermitian_decomposition(self, x, real, imag): + def test_hermitianize_inverter(self): l = LMSpace(5) - assert_almost_equal( - l.hermitian_decomposition(distributed_data_object(x))[0], - real) - assert_almost_equal( - l.hermitian_decomposition(distributed_data_object(x))[1], - imag*1j) + v = distributed_data_object(global_shape=l.shape, dtype=np.complex128) + v[:] = np.random.random(l.shape) + 1j*np.random.random(l.shape) + inverted = l.hermitianize_inverter(v, axes=(0,)) + assert_array_almost_equal(inverted.get_full_data(), v.get_full_data()) @expand(get_weight_configs()) def test_weight(self, x, power, axes, inplace, expected): diff --git a/test/test_spaces/test_rg_space.py b/test/test_spaces/test_rg_space.py index 2b3e348e9edb49e6f29fba5a8d16114815b50be0..901afa27c2f365ef75e6007765ad172cd937a285 100644 --- a/test/test_spaces/test_rg_space.py +++ b/test/test_spaces/test_rg_space.py @@ -21,6 +21,8 @@ from __future__ import division import unittest import numpy as np +from d2o import distributed_data_object + from numpy.testing import assert_, assert_equal, assert_almost_equal from nifty import RGSpace from test.common import expand @@ -157,9 +159,8 @@ class RGSpaceFunctionalityTests(unittest.TestCase): [True, False])) def test_hermitianize_inverter(self, shape, zerocenter): r = RGSpace(shape, harmonic=True, zerocenter=zerocenter) - v = np.empty(shape, dtype=np.complex128) - v.real = np.random.random(shape) - v.imag = np.random.random(shape) + v = distributed_data_object(global_shape=shape, dtype=np.complex128) + v[:] = np.random.random(shape) + 1j*np.random.random(shape) inverted = r.hermitianize_inverter(v, axes=range(len(shape))) # test hermitian flipping of `inverted`