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 SpectrumDataTest(unittest.TestCase):
def setUp(self):
self.spectrum = Spectrum()
self.spectrum_data = SpectrumData()
def test_spectrum_class(self):
self.spectrum.save('Data/spec_test.txt')
self.spectrum.save(
'Data/spec_test2.txt',
header='This is not only ridiculous\n but more and more '
'challenging...')
self.spectrum.load('Data/spec_test.txt')
self.spectrum.load('Data/spec_test2.txt')
self.assertTrue(
np.array_equal(self.spectrum.data[0], np.linspace(0, 30, 100)))
self.assertTrue(self.spectrum.load('Data/test_001.tif') == -1)
self.spectrum.data = (np.linspace(0, 30), np.linspace(0, 20))
self.spectrum.offset = 100
self.assertTrue(
np.array_equal(self.spectrum.data[1],
np.linspace(0, 20) + 100))
self.assertTrue(
np.array_equal(self.spectrum.data[0], np.linspace(0, 30)))
self.spectrum.scaling = 10
self.assertTrue(
np.array_equal(self.spectrum.data[1],
np.linspace(0, 20) * 10 + 100))
self.spectrum.data = (np.linspace(0, 20), np.linspace(0, 30))
self.assertTrue(
np.array_equal(self.spectrum.data[1], np.linspace(0, 30)))
self.spectrum.scaling = -100
self.assertTrue(
np.array_equal(self.spectrum.data[1],
np.zeros(self.spectrum.data[0].shape)))
def test_spectrum_data_class(self):
self.spectrum_data.set_spectrum(np.linspace(0, 10),
np.linspace(0, 10)**2, 'SQUARED')
self.spectrum_data.add_overlay(np.linspace(0, 10),
np.linspace(0, 10)**3, 'CUBED')
self.spectrum_data.add_overlay(np.linspace(0, 10),
np.linspace(0, 10)**4, 'QUADRUPOLED')
self.assertTrue(len(self.spectrum_data.overlays) == 2)
self.spectrum_data.del_overlay(0)
self.assertTrue(self.spectrum_data.overlays[0].name == 'QUADRUPOLED')
self.spectrum_data.add_overlay_file('Data/spec_test2.txt')
self.assertTrue(self.spectrum_data.overlays[-1].name == 'spec_test2')
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.load_mask('Data/test.mask')
self.spectrum_data = SpectrumData()
def test_dependencies(self):
tth1, int1 = self.calibration_data.integrate_1d()
self.img_data.load_next()
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.jpg')
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.jpg')
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.jpg')
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.jpg')
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()
y2 = self.spectrum_data.spectrum.data[1]
self.assertFalse(np.array_equal(y1, y2))
class SpectrumDataTest(unittest.TestCase):
def setUp(self):
self.spectrum = Spectrum()
self.spectrum_data = SpectrumData()
def test_spectrum_class(self):
self.spectrum.save('Data/spec_test.txt')
self.spectrum.save('Data/spec_test2.txt',
header='This is not only ridiculous\n but more and more '
'challenging...')
self.spectrum.load('Data/spec_test.txt')
self.spectrum.load('Data/spec_test2.txt')
self.assertTrue(np.array_equal(self.spectrum.data[0], np.linspace(0, 30, 100)))
self.assertTrue(self.spectrum.load('Data/test_001.tif') == -1)
self.spectrum.data = (np.linspace(0, 30), np.linspace(0, 20))
self.spectrum.offset = 100
self.assertTrue(np.array_equal(self.spectrum.data[1], np.linspace(0, 20) + 100))
self.assertTrue(np.array_equal(self.spectrum.data[0], np.linspace(0, 30)))
self.spectrum.scaling = 10
self.assertTrue(np.array_equal(self.spectrum.data[1], np.linspace(0, 20) * 10 + 100))
self.spectrum.data = (np.linspace(0, 20), np.linspace(0, 30))
self.assertTrue(np.array_equal(self.spectrum.data[1], np.linspace(0, 30)))
self.spectrum.scaling = -100
self.assertTrue(np.array_equal(self.spectrum.data[1], np.zeros(self.spectrum.data[0].shape)))
def test_spectrum_data_class(self):
self.spectrum_data.set_spectrum(np.linspace(0, 10), np.linspace(0, 10) ** 2, 'SQUARED')
self.spectrum_data.add_overlay(np.linspace(0, 10), np.linspace(0, 10) ** 3, 'CUBED')
self.spectrum_data.add_overlay(np.linspace(0, 10), np.linspace(0, 10) ** 4, 'QUADRUPOLED')
self.assertTrue(len(self.spectrum_data.overlays) == 2)
self.spectrum_data.del_overlay(0)
self.assertTrue(self.spectrum_data.overlays[0].name == 'QUADRUPOLED')
self.spectrum_data.add_overlay_file('Data/spec_test2.txt')
self.assertTrue(self.spectrum_data.overlays[-1].name == 'spec_test2')
class SpectrumDataTest(unittest.TestCase):
def setUp(self):
self.x = np.linspace(0.1, 15, 100)
self.y = np.sin(self.x)
self.spectrum = Spectrum(self.x, self.y)
self.spectrum_data = SpectrumData()
def test_spectrum_class(self):
self.spectrum.save('Data/spec_test.txt')
self.spectrum.save('Data/spec_test2.txt',
header='This is not only ridiculous\n but more and more '
'challenging...')
self.spectrum.load('Data/spec_test.txt', 0)
self.spectrum.load('Data/spec_test2.txt', 0)
self.assertTrue(np.array_equal(self.spectrum.data[0], np.linspace(0.1, 15, 100)))
self.assertTrue(self.spectrum.load('Data/test_001.tif') == -1)
self.spectrum.data = (np.linspace(0, 30), np.linspace(0, 20))
self.spectrum.offset = 100
self.assertTrue(np.array_equal(self.spectrum.data[1], np.linspace(0, 20) + 100))
self.assertTrue(np.array_equal(self.spectrum.data[0], np.linspace(0, 30)))
self.spectrum.scaling = 10
self.assertTrue(np.array_equal(self.spectrum.data[1], np.linspace(0, 20) * 10 + 100))
self.spectrum.data = (np.linspace(0, 20), np.linspace(0, 30))
self.assertTrue(np.array_equal(self.spectrum.data[1], np.linspace(0, 30)))
self.spectrum.scaling = -100
self.assertTrue(np.array_equal(self.spectrum.data[1], np.zeros(self.spectrum.data[0].shape)))
def test_spectrum_data_class(self):
self.spectrum_data.set_spectrum(np.linspace(0, 10), np.linspace(0, 10) ** 2, 'SQUARED')
self.spectrum_data.add_overlay(np.linspace(0, 10), np.linspace(0, 10) ** 3, 'CUBED')
self.spectrum_data.add_overlay(np.linspace(0, 10), np.linspace(0, 10) ** 4, 'QUADRUPOLED')
self.assertTrue(len(self.spectrum_data.overlays) == 2)
self.spectrum_data.del_overlay(0)
self.assertTrue(self.spectrum_data.overlays[0].name == 'QUADRUPOLED')
self.spectrum_data.add_overlay_file('Data/spec_test2.txt')
self.assertTrue(self.spectrum_data.overlays[-1].name == 'spec_test2')
def test_background(self):
x_spectrum = np.linspace(0,100,1001)
y_spectrum = np.sin(x_spectrum)
x_background = np.linspace(0,91, 1002)
y_background = np.cos(x_background)
spec = Spectrum(x_spectrum, y_spectrum)
spec.set_background(Spectrum(x_background, y_background))
x, y = spec.data
self.assertTrue(x[-1]<1000)
self.assertEqual(len(x), 911)
test_x = np.linspace(0,91, 911)
test_y = np.sin(test_x) - np.cos(test_x)
diff = abs(np.sum(test_y-y))
self.assertLess(diff, 1e-3)
def test_background_not_in_spectrum_range(self):
x_spectrum = np.linspace(0,30,101)
y_spectrum = np.sin(x_spectrum)
x_background = np.linspace(50,60, 102)
y_background = np.cos(x_background)
spec = Spectrum(x_spectrum, y_spectrum)
spec.set_background(Spectrum(x_background, y_background))
self.assertRaises(BkgNotInRangeError)
