def test_normalize_flat_ok(self):
import IMAT.tomorec.reconstruction_command as cmd
cmd = cmd.ReconstructionCommand()
import IMAT.tomorec.configs as cfgs
pre_conf = cfgs.PreProcConfig()
# ignored, with just info message
norm = cmd.normalize_flat_dark(self.data_vol, pre_conf, None, None)
# ignored, with just info message
norm = cmd.normalize_flat_dark(self.data_vol, pre_conf, 45, None)
for img_idx in range(0, self.data_vol.shape[0]):
fake_white = self.data_vol[img_idx, :, :]
norm = cmd.normalize_flat_dark(self.data_vol, pre_conf, fake_white, None)
np.testing.assert_allclose(norm[img_idx, : :], np.ones(fake_white.shape),
err_msg="Epected normalized data volume not to changed "
"wheh using fake flat image, with index {0}".format(img_idx))
def test_normalize_flat_raises(self):
import IMAT.tomorec.reconstruction_command as cmd
cmd = cmd.ReconstructionCommand()
import IMAT.tomorec.configs as cfgs
pre_conf = cfgs.PreProcConfig()
alg_conf = cfgs.ToolAlgorithmConfig()
post_conf = cfgs.PostProcConfig()
conf = cfgs.ReconstructionConfig(pre_conf, alg_conf, post_conf)
# absolutely invalid data
with self.assertRaises(ValueError):
cmd.normalize_flat_dark([], pre_conf, np.ones((10, 23)), None)
# wrong data dimensions
with self.assertRaises(ValueError):
cmd.normalize_flat_dark(np.ones((3, 2)), pre_conf, np.ones((10, 23)), None)
# wrong dimensions of the flat image
with self.assertRaises(ValueError):
cmd.normalize_flat_dark(self.data_vol, pre_conf, np.ones((10, 23)), None)
# invalid configurations
with self.assertRaises(ValueError):
cmd.normalize_flat_dark(self.data_vol, alg_conf, None, None)
with self.assertRaises(ValueError):
cmd.normalize_flat_dark(self.data_vol, post_conf, None, None)
with self.assertRaises(ValueError):
cmd.normalize_flat_dark(self.data_vol, conf, None, None)
