def test_flatfield_correction_differing_integration_times(self):
MSI_INTEGRATION_TIME = 3.0
FLATFIELD_INTEGRATION_TIME = 2.0
desired_image_data = np.ones_like(self.specialmsi.get_image()) * \
FLATFIELD_INTEGRATION_TIME / MSI_INTEGRATION_TIME
desired_image_data[2, 2, 0] = np.nan
self.specialmsi.add_property({"integration times":
np.ones_like(
self.specialmsi.get_image()[0, 0, :])
* MSI_INTEGRATION_TIME})
flatfield = copy.deepcopy(self.specialmsi)
flatfield.add_property({"integration times":
np.ones_like(
flatfield.get_image()[0, 0, :])
* FLATFIELD_INTEGRATION_TIME})
# for testing if flatfield does not changed by correction we copy it
flatfield_copy = copy.deepcopy(flatfield)
mani.flatfield_correction(self.specialmsi, flatfield_copy)
np.testing.assert_almost_equal(self.specialmsi.get_image(),
desired_image_data, 15,
"corrected image is a division of integration times")
np.testing.assert_equal(flatfield.get_image(),
flatfield_copy.get_image(),
"flatfield doesn't change by correction")
def test_flatfield_correction_differing_integration_times(self):
MSI_INTEGRATION_TIME = 3.0
FLATFIELD_INTEGRATION_TIME = 2.0
desired_image_data = np.ones_like(self.specialmsi.get_image()) * \
FLATFIELD_INTEGRATION_TIME / MSI_INTEGRATION_TIME
desired_image_data[2, 2, 0] = np.nan
self.specialmsi.add_property({"integration times":
np.ones_like(
self.specialmsi.get_image()[0, 0, :])
* MSI_INTEGRATION_TIME})
flatfield = copy.deepcopy(self.specialmsi)
flatfield.add_property({"integration times":
np.ones_like(
flatfield.get_image()[0, 0, :])
* FLATFIELD_INTEGRATION_TIME})
# for testing if flatfield does not changed by correction we copy it
flatfield_copy = copy.deepcopy(flatfield)
mani.flatfield_correction(self.specialmsi, flatfield_copy)
np.testing.assert_almost_equal(self.specialmsi.get_image(),
desired_image_data, 15,
"corrected image is a division of integration times")
np.testing.assert_equal(flatfield.get_image(),
flatfield_copy.get_image(),
"flatfield doesn't change by correction")
def test_flatfield_correction(self):
desired_image_data = np.ones_like(self.specialmsi.get_image())
desired_image_data[2, 2, 0] = np.nan
mani.flatfield_correction(self.specialmsi, self.specialmsi)
np.testing.assert_equal(self.specialmsi.get_image(),
desired_image_data,
"correct image by itself should lead to only 1s ")
def test_flatfield_correction(self):
desired_image_data = np.ones_like(self.specialmsi.get_image())
desired_image_data[2, 2, 0] = np.nan
mani.flatfield_correction(self.specialmsi, self.specialmsi)
np.testing.assert_equal(self.specialmsi.get_image(),
desired_image_data,
"correct image by itself should lead to only 1s ")
def test_flatfield_correction_with_single_value(self):
desired_image_data = np.ones_like(self.msi.get_image())
flatfield = copy.copy(self.msi)
mani.calculate_mean_spectrum(flatfield)
unchanged_flatfield = copy.deepcopy(flatfield)
mani.flatfield_correction(self.msi, flatfield)
np.testing.assert_equal(self.msi.get_image(),
desired_image_data,
"flatfield correctly accounted for from singular reference value")
np.testing.assert_equal(flatfield, unchanged_flatfield,
"flatfield not changed by algorithm")
def test_flatfield_correction_with_single_value(self):
desired_image_data = np.ones_like(self.msi.get_image())
flatfield = copy.copy(self.msi)
mani.calculate_mean_spectrum(flatfield)
unchanged_flatfield = copy.deepcopy(flatfield)
mani.flatfield_correction(self.msi, flatfield)
np.testing.assert_equal(self.msi.get_image(),
desired_image_data,
"flatfield correctly accounted for from singular reference value")
np.testing.assert_equal(flatfield, unchanged_flatfield,
"flatfield not changed by algorithm")