class SpectrumModelTest(unittest.TestCase):
# TODO: needs to be rewritten to be more in small units etc.
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_model = SpectrumModel()
def test_set_spectrum(self):
self.spectrum_model.set_spectrum(self.x, self.y, 'hoho')
assert_array_almost_equal(self.spectrum_model.get_spectrum().x, self.x)
assert_array_almost_equal(self.spectrum_model.get_spectrum().y, self.y)
self.assertEqual(self.spectrum_model.get_spectrum().name, 'hoho')
def test_load_spectrum(self):
self.spectrum_model.load_spectrum(os.path.join(data_path, 'spectrum_001.xy'))
self.assertEqual(self.spectrum_model.get_spectrum().name, 'spectrum_001')
self.assertNotEqual(len(self.x), len(self.spectrum_model.get_spectrum().x))
self.assertNotEqual(len(self.y), len(self.spectrum_model.get_spectrum().y))
def test_add_overlay(self):
x_overlay = np.linspace(0, 10)
y_overlay = np.linspace(0, 100)
self.spectrum_model.add_overlay(x_overlay, y_overlay, "dummy")
self.assertEqual(len(self.spectrum_model.overlays), 1)
new_overlay = self.spectrum_model.get_overlay(0)
self.assertEqual(new_overlay.name, "dummy")
assert_array_almost_equal(new_overlay.x, x_overlay)
assert_array_almost_equal(new_overlay.y, y_overlay)
def test_add_overlay_from_file(self):
filename = os.path.join(data_path, 'spectrum_001.xy')
self.spectrum_model.add_overlay_file(filename)
self.assertEqual(len(self.spectrum_model.overlays), 1)
self.assertEqual(self.spectrum_model.get_overlay(0).name, ''.join(os.path.basename(filename).split('.')[0:-1]))
def test_add_spectrum_as_overlay(self):
self.spectrum_model.add_spectrum_as_overlay()
self.assertEqual(len(self.spectrum_model.overlays), 1)
assert_array_almost_equal(self.spectrum_model.get_overlay(0).x, self.spectrum_model.spectrum.x)
assert_array_almost_equal(self.spectrum_model.get_overlay(0).y, self.spectrum_model.spectrum.y)
def test_auto_background_subtraction(self):
x = np.linspace(0, 24, 2500)
y = np.zeros(x.shape)
peaks = [
[10, 3, 0.1],
[12, 4, 0.1],
[12, 6, 0.1],
]
for peak in peaks:
y += gaussian(x, peak[0], peak[1], peak[2])
y_bkg = x * 0.4 + 5.0
y_measurement = y + y_bkg
self.spectrum_model.set_spectrum(x, y_measurement)
auto_background_subtraction_parameters = [2, 50, 50]
self.spectrum_model.set_auto_background_subtraction(auto_background_subtraction_parameters)
x_spec, y_spec = self.spectrum_model.spectrum.data
self.assertAlmostEqual(np.sum(y_spec- y),0)
