class CombinedDataTest(unittest.TestCase): def setUp(self): self.img_data = ImgData() self.img_data.load('Data/Mg2SiO4_ambient_001.tif') self.calibration_data = CalibrationData(self.img_data) self.calibration_data.load('Data/calibration.poni') self.mask_data = MaskData() self.mask_data.mask_ellipse(500, 500, 100, 100) self.spectrum_data = SpectrumData() def test_dependencies(self): tth1, int1 = self.calibration_data.integrate_1d() self.img_data.load_next_file() self.assertEqual(os.path.abspath(self.img_data.filename), os.path.abspath('Data/Mg2SiO4_ambient_002.tif')) tth2, int2 = self.calibration_data.integrate_1d() self.assertFalse(np.array_equal(int1, int2)) plt.figure(1) plt.plot(tth1, int1) plt.plot(tth2, int2) plt.savefig('Results/dependencies1.png') tth3, int3 = self.calibration_data.integrate_1d(mask=self.mask_data.get_mask()) self.assertFalse(np.array_equal(int2, int3)) plt.figure(2) plt.plot(tth2, int2) plt.plot(tth3, int3) plt.savefig('Results/dependencies2.png') tth4, int4 = self.calibration_data.integrate_1d(polarization_factor=0.90, mask=None) plt.figure(3) plt.plot(tth2, int2) plt.plot(tth4, int4) plt.savefig('Results/dependencies3.png') tth5, int5 = self.calibration_data.integrate_1d(polarization_factor=.5, mask=None) plt.figure(4) plt.plot(tth4, int4) plt.plot(tth5, int5) plt.savefig('Results/dependencies4.png') def test_automatism(self): def integrate_and_set_spectrum(): tth, I = self.calibration_data.integrate_1d() self.spectrum_data.set_spectrum(tth, I, self.img_data.filename) self.img_data.subscribe(integrate_and_set_spectrum) y1 = self.spectrum_data.spectrum.data[1] self.img_data.load_next_file() y2 = self.spectrum_data.spectrum.data[1] self.assertFalse(np.array_equal(y1, y2))
class ImgDataUnitTest(unittest.TestCase): def setUp(self): self.img_data = ImgData() self.img_data.load('Data/Mg2SiO4_ambient_001.tif') def perform_transformations_tests(self): self.assertEqual(np.sum(np.absolute(self.img_data.get_img_data())), 0) self.img_data.rotate_img_m90() self.assertEqual(np.sum(np.absolute(self.img_data.get_img_data())), 0) self.img_data.flip_img_horizontally() self.assertEqual(np.sum(np.absolute(self.img_data.get_img_data())), 0) self.img_data.rotate_img_p90() self.assertEqual(np.sum(np.absolute(self.img_data.get_img_data())), 0) self.img_data.flip_img_vertically() self.assertEqual(np.sum(np.absolute(self.img_data.get_img_data())), 0) self.img_data.reset_img_transformations() self.assertEqual(np.sum(np.absolute(self.img_data.get_img_data())), 0) def test_flipping_images(self): original_image = np.copy(self.img_data._img_data) self.img_data.flip_img_vertically() self.assertTrue(np.array_equal(self.img_data._img_data, np.flipud(original_image))) def test_simple_background_subtraction(self): self.first_image = np.copy(self.img_data.get_img_data()) self.img_data.load_next_file() self.second_image = np.copy(self.img_data.get_img_data()) self.img_data.load('Data/Mg2SiO4_ambient_001.tif') self.img_data.load_background('Data/Mg2SiO4_ambient_002.tif') self.assertFalse(np.array_equal(self.first_image, self.img_data.get_img_data())) self.img_data.load_next_file() self.assertEqual(np.sum(self.img_data.get_img_data()), 0) def test_background_subtraction_with_supersampling(self): self.img_data.load_background('Data/Mg2SiO4_ambient_002.tif') self.img_data.set_supersampling(2) self.img_data.get_img_data() self.img_data.set_supersampling(3) self.img_data.get_img_data() self.img_data.load_next_file() self.img_data.get_img_data() def test_background_subtraction_with_transformation(self): self.img_data.load_background('Data/Mg2SiO4_ambient_002.tif') original_img = np.copy(self.img_data._img_data) original_background = np.copy(self.img_data._background_data) self.assertNotEqual(self.img_data._background_data, None) self.assertFalse(np.array_equal(self.img_data.img_data, self.img_data._img_data)) original_img_background_subtracted = np.copy(self.img_data.get_img_data()) self.assertTrue(np.array_equal(original_img_background_subtracted, original_img-original_background)) ### now comes the main process - flipping the image self.img_data.flip_img_vertically() flipped_img = np.copy(self.img_data._img_data) self.assertTrue(np.array_equal(np.flipud(original_img), flipped_img)) flipped_background = np.copy(self.img_data._background_data) self.assertTrue(np.array_equal(np.flipud(original_background), flipped_background)) flipped_img_background_subtracted = np.copy(self.img_data.get_img_data()) self.assertTrue(np.array_equal(flipped_img_background_subtracted, flipped_img-flipped_background)) self.assertTrue(np.array_equal(np.flipud(original_img_background_subtracted), flipped_img_background_subtracted)) self.assertEqual(np.sum(np.flipud(original_img_background_subtracted)-flipped_img_background_subtracted), 0) self.img_data.load('Data/Mg2SiO4_ambient_002.tif') self.perform_transformations_tests() def test_background_subtraction_with_supersampling_and_image_transformation(self): self.img_data.load_background('Data/Mg2SiO4_ambient_002.tif') self.img_data.load('Data/Mg2SiO4_ambient_002.tif') self.img_data.set_supersampling(2) self.assertEqual(self.img_data.get_img_data().shape, (4096, 4096)) self.perform_transformations_tests() self.img_data.set_supersampling(3) self.assertEqual(self.img_data.get_img_data().shape, (6144, 6144)) self.perform_transformations_tests() self.img_data.load('Data/Mg2SiO4_ambient_002.tif') self.assertEqual(self.img_data.get_img_data().shape, (6144, 6144)) self.perform_transformations_tests() def test_background_scaling_and_offset(self): self.img_data.load_background('Data/Mg2SiO4_ambient_002.tif') #assure that everything is correct before self.assertTrue(np.array_equal(self.img_data.get_img_data(), self.img_data._img_data-self.img_data._background_data)) #set scaling and see difference self.img_data.set_background_scaling(2.4) self.assertTrue(np.array_equal(self.img_data.get_img_data(), self.img_data._img_data-2.4*self.img_data._background_data)) #set offset and see the difference self.img_data.set_background_scaling(1.0) self.img_data.set_background_offset(100.0) self.assertTrue(np.array_equal(self.img_data.img_data, self.img_data._img_data-(self.img_data._background_data+100.0))) #use offset and scaling combined self.img_data.set_background_scaling(2.3) self.img_data.set_background_offset(100.0) self.assertTrue(np.array_equal(self.img_data.img_data, self.img_data._img_data-(2.3*self.img_data._background_data+100))) def test_background_with_different_shape(self): self.img_data.load_background('Data/CeO2_Pilatus1M.tif') self.assertEqual(self.img_data._background_data, None) self.img_data.load_background('Data/Mg2SiO4_ambient_002.tif') self.assertTrue(self.img_data._background_data is not None) self.img_data.load('Data/CeO2_Pilatus1M.tif') self.assertEqual(self.img_data._background_data, None) def test_absorption_correction_with_supersampling(self): original_image = np.copy(self.img_data.get_img_data()) dummy_correction = DummyCorrection(self.img_data.get_img_data().shape, 0.6) self.img_data.add_img_correction(dummy_correction, "Dummy 1") self.assertAlmostEqual(np.sum(original_image)/0.6, np.sum(self.img_data.get_img_data()), places=4) self.img_data.set_supersampling(2) self.img_data.get_img_data() def test_absorption_correction_with_different_image_sizes(self): dummy_correction = DummyCorrection(self.img_data.get_img_data().shape, 0.4) # self.img_data.set_absorption_correction(np.ones(self.img_data._img_data.shape)*0.4) self.img_data.add_img_correction(dummy_correction, "Dummy 1") self.assertTrue(self.img_data._img_corrections.has_items()) self.img_data.load('Data/CeO2_Pilatus1M.tif') self.assertFalse(self.img_data.has_corrections()) def test_adding_several_absorption_corrections(self): original_image = np.copy(self.img_data.get_img_data()) img_shape = original_image.shape self.img_data.add_img_correction(DummyCorrection(img_shape, 0.4)) self.img_data.add_img_correction(DummyCorrection(img_shape, 3)) self.img_data.add_img_correction(DummyCorrection(img_shape, 5)) self.assertTrue(np.sum(original_image)/(0.5*3*5), np.sum(self.img_data.get_img_data())) self.img_data.delete_img_correction(1) self.assertTrue(np.sum(original_image)/(0.5*5), np.sum(self.img_data.get_img_data())) def test_saving_data(self): self.img_data.load('Data/Mg2SiO4_ambient_001.tif') self.img_data.save('Data/TestSaving.tif') first_img_array = np.copy(self.img_data._img_data) self.img_data.load('Data/TestSaving.tif') self.assertTrue(np.array_equal(first_img_array, self.img_data._img_data))