class MaskControllerTest(unittest.TestCase):
def setUp(self):
self.app = QtGui.QApplication(sys.argv)
self.working_dir = {}
self.img_model = ImgModel()
self.mask_model = MaskModel()
self.mask_widget = MaskWidget()
self.mask_controller = MaskController(self.working_dir, self.mask_widget, self.img_model, self.mask_model)
def tearDown(self):
del self.img_model
del self.mask_model
self.mask_widget.close()
del self.mask_widget
del self.mask_controller
del self.app
gc.collect()
def get_file_size(self, filename):
stat_info = os.stat(filename)
return stat_info.st_size
def test_loading_and_saving_mask_files(self):
self.mask_controller.load_mask_btn_click(os.path.join(data_path, 'test.mask'))
self.mask_model.mask_below_threshold(self.img_model, 1)
filename = os.path.join(data_path, 'dummy.mask')
self.mask_controller.save_mask_btn_click(filename)
self.assertTrue(os.path.exists(filename))
os.remove(filename)
def test_loading_and_saving_with_super_sampling(self):
self.mask_model.set_supersampling(2)
self.mask_controller.load_mask_btn_click(os.path.join(data_path, 'test.mask'))
self.assertEqual(self.mask_model.get_mask().shape[0], 4096)
self.assertEqual(self.mask_model.get_mask().shape[1], 4096)
self.assertEqual(self.mask_model.get_img().shape[0], 2048)
self.assertEqual(self.mask_model.get_img().shape[1], 2048)
self.mask_model.mask_below_threshold(self.img_model, 1)
filename = os.path.join(data_path, 'dummy.mask')
self.mask_controller.save_mask_btn_click(filename)
self.assertEqual(self.get_file_size(filename), self.get_file_size(os.path.join(data_path, 'test.mask')))
def test_grow_and_shrinking(self):
self.mask_model.mask_ellipse(100,100,20,20)
previous_mask = np.copy(self.mask_model._mask_data)
QTest.mouseClick(self.mask_widget.grow_btn, QtCore.Qt.LeftButton)
self.assertFalse(np.array_equal(previous_mask, self.mask_model._mask_data))
QTest.mouseClick(self.mask_widget.shrink_btn, QtCore.Qt.LeftButton)
self.assertTrue(np.array_equal(previous_mask, self.mask_model._mask_data))
class CbnAbsorptionCorrectionOptimizationTest(unittest.TestCase):
def setUp(self):
# creating Data objects
self.img_data = ImgModel()
self.img_data.load("Data/CbnCorrectionOptimization/Mg2SiO4_091.tif")
self.calibration_data = CalibrationModel(self.img_data)
self.calibration_data.load("Data/CbnCorrectionOptimization/LaB6_40keV side.poni")
self.mask_data = MaskModel()
self.mask_data.load_mask("Data/CbnCorrectionOptimization/Mg2SiO4_91_combined.mask")
# creating the ObliqueAngleDetectorAbsorptionCorrection
_, fit2d_parameter = self.calibration_data.get_calibration_parameter()
detector_tilt = fit2d_parameter['tilt']
detector_tilt_rotation = fit2d_parameter['tiltPlanRotation']
self.tth_array = self.calibration_data.spectrum_geometry.twoThetaArray((2048, 2048))
self.azi_array = self.calibration_data.spectrum_geometry.chiArray((2048, 2048))
self.oiadac_correction = ObliqueAngleDetectorAbsorptionCorrection(
self.tth_array, self.azi_array,
detector_thickness=40,
absorption_length=465.5,
tilt=detector_tilt,
rotation=detector_tilt_rotation,
)
self.img_data.add_img_correction(self.oiadac_correction, "oiadac")
def tearDown(self):
del self.calibration_data.cake_geometry
del self.calibration_data.spectrum_geometry
def test_the_world(self):
params = Parameters()
params.add("diamond_thickness", value=2, min=1.9, max=2.3)
params.add("seat_thickness", value=5.3, min=4.0, max=6.6, vary=False)
params.add("small_cbn_seat_radius", value=0.2, min=0.10, max=0.5, vary=True)
params.add("large_cbn_seat_radius", value=1.95, min=1.85, max=2.05, vary=False)
params.add("tilt", value=3.3, min=0, max=8)
params.add("tilt_rotation", value=0, min=-15, max=+15)
params.add("cbn_abs_length", value=14.05, min=12, max=16)
region = [8, 26]
self.tth_array = 180.0 / np.pi * self.tth_array
self.azi_array = 180.0 / np.pi * self.azi_array
def fcn2min(params):
cbn_correction = CbnCorrection(
tth_array=self.tth_array,
azi_array=self.azi_array,
diamond_thickness=params['diamond_thickness'].value,
seat_thickness=params['seat_thickness'].value,
small_cbn_seat_radius=params['small_cbn_seat_radius'].value,
large_cbn_seat_radius=params['large_cbn_seat_radius'].value,
tilt=params['tilt'].value,
tilt_rotation=params['tilt_rotation'].value,
cbn_abs_length=params["cbn_abs_length"].value
)
self.img_data.add_img_correction(cbn_correction, "cbn")
tth, int = self.calibration_data.integrate_1d(mask=self.mask_data.get_mask())
self.img_data.delete_img_correction("cbn")
ind = np.where((tth > region[0]) & (tth < region[1]))
int = gaussian_filter1d(int, 20)
return (np.diff(int[ind])) ** 2
def output_values(param1, iteration, residual):
report_fit(param1)
result = minimize(fcn2min, params, iter_cb=output_values)
report_fit(params)
# plotting result:
cbn_correction = CbnCorrection(
tth_array=self.tth_array,
azi_array=self.azi_array,
diamond_thickness=params['diamond_thickness'].value,
seat_thickness=params['seat_thickness'].value,
small_cbn_seat_radius=params['small_cbn_seat_radius'].value,
large_cbn_seat_radius=params['large_cbn_seat_radius'].value,
tilt=params['tilt'].value,
tilt_rotation=params['tilt_rotation'].value,
cbn_abs_length=params['cbn_abs_length'].value
)
self.img_data.add_img_correction(cbn_correction, "cbn")
tth, int = self.calibration_data.integrate_1d(mask=self.mask_data.get_mask())
ind = np.where((tth > region[0]) & (tth < region[1]))
tth = tth[ind]
int = int[ind]
int_smooth = gaussian_filter1d(int, 10)
int_diff1 = np.diff(int)
int_diff1_smooth = np.diff(int_smooth)
int_diff2 = np.diff(int_diff1)
int_diff2_smooth = np.diff(int_diff1_smooth)
plt.figure()
plt.subplot(3, 1, 1)
plt.plot(tth, int)
plt.plot(tth, int_smooth)
plt.subplot(3, 1, 2)
plt.plot(int_diff1)
plt.plot(int_diff1_smooth)
plt.subplot(3, 1, 3)
plt.plot(int_diff2)
plt.plot(int_diff2_smooth)
plt.savefig("Results/optimize_cbn_absorption.png", dpi=300)
os.system("open " + "Results/optimize_cbn_absorption.png")
class MaskControllerTest(unittest.TestCase):
@classmethod
def setUpClass(cls):
cls.app = QtGui.QApplication([])
@classmethod
def tearDownClass(cls):
cls.app.quit()
cls.app.deleteLater()
def setUp(self):
self.working_dir = {}
self.img_model = ImgModel()
self.mask_model = MaskModel()
self.mask_widget = MaskWidget()
self.mask_controller = MaskController(self.working_dir,
self.mask_widget, self.img_model,
self.mask_model)
def tearDown(self):
del self.img_model
del self.mask_model
self.mask_widget.close()
del self.mask_widget
del self.mask_controller
gc.collect()
def get_file_size(self, filename):
stat_info = os.stat(filename)
return stat_info.st_size
def test_loading_and_saving_mask_files(self):
self.mask_controller.load_mask_btn_click(
os.path.join(data_path, 'test.mask'))
self.mask_model.mask_below_threshold(self.img_model, 1)
filename = os.path.join(data_path, 'dummy.mask')
self.mask_controller.save_mask_btn_click(filename)
self.assertTrue(os.path.exists(filename))
os.remove(filename)
def test_loading_and_saving_with_super_sampling(self):
self.mask_model.set_supersampling(2)
self.mask_controller.load_mask_btn_click(
os.path.join(data_path, 'test.mask'))
self.assertEqual(self.mask_model.get_mask().shape[0], 4096)
self.assertEqual(self.mask_model.get_mask().shape[1], 4096)
self.assertEqual(self.mask_model.get_img().shape[0], 2048)
self.assertEqual(self.mask_model.get_img().shape[1], 2048)
self.mask_model.mask_below_threshold(self.img_model, 1)
filename = os.path.join(data_path, 'dummy.mask')
self.mask_controller.save_mask_btn_click(filename)
self.assertAlmostEqual(self.get_file_size(filename),
self.get_file_size(
os.path.join(data_path, 'test.mask')),
delta=20)
def test_grow_and_shrinking(self):
self.mask_model.mask_ellipse(100, 100, 20, 20)
previous_mask = np.copy(self.mask_model._mask_data)
QTest.mouseClick(self.mask_widget.grow_btn, QtCore.Qt.LeftButton)
self.assertFalse(
np.array_equal(previous_mask, self.mask_model._mask_data))
QTest.mouseClick(self.mask_widget.shrink_btn, QtCore.Qt.LeftButton)
self.assertTrue(
np.array_equal(previous_mask, self.mask_model._mask_data))
