class CombinedDataTest(unittest.TestCase):
def setUp(self):
self.img_data = ImgData()
self.img_data.load('Data/LaB6_p49_40keV_006.tif')
self.calibration_data = CalibrationData(self.img_data)
self.calibration_data.calibrant.load_file('Data/Calibrants/LaB6.D')
self.calibration_data.calibrant.set_wavelength(0.31 * 1e-10)
self.calibration_data.load('Data/LaB6_p49_40keV_006.poni')
def test_recalibration(self):
self.calibration_data.recalibrate()
plt.imshow(self.img_data.img_data)
plt.plot(self.calibration_data.geometry.data[:, 0],
self.calibration_data.geometry.data[:, 1], 'g.')
plt.savefig('Results/recalib_massif.jpg')
self.calibration_data.recalibrate('blob')
plt.figure(2)
plt.imshow(self.img_data.img_data)
plt.plot(self.calibration_data.geometry.data[:, 0],
self.calibration_data.geometry.data[:, 1], 'g.')
plt.savefig('Results/recalib_blob.jpg')
self.calibration_data.recalibrate('blob')
plt.figure(3)
plt.imshow(self.img_data.img_data)
plt.plot(self.calibration_data.geometry.data[:, 0],
self.calibration_data.geometry.data[:, 1], 'g.')
plt.savefig('Results/recalib_blob2.jpg')
class CombinedDataTest(unittest.TestCase):
def setUp(self):
self.img_data = ImgData()
self.img_data.load('Data/LaB6_p49_40keV_006.tif')
self.calibration_data = CalibrationData(self.img_data)
self.calibration_data.calibrant.load_file('Data/Calibrants/LaB6.D')
self.calibration_data.calibrant.set_wavelength(0.31 * 1e-10)
self.calibration_data.load('Data/LaB6_p49_40keV_006.poni')
def test_recalibration(self):
self.calibration_data.recalibrate()
plt.imshow(self.img_data.img_data)
plt.plot(self.calibration_data.geometry.data[:, 0], self.calibration_data.geometry.data[:, 1], 'g.')
plt.savefig('Results/recalib_massif.jpg')
self.calibration_data.recalibrate('blob')
plt.figure(2)
plt.imshow(self.img_data.img_data)
plt.plot(self.calibration_data.geometry.data[:, 0], self.calibration_data.geometry.data[:, 1], 'g.')
plt.savefig('Results/recalib_blob.jpg')
self.calibration_data.recalibrate('blob')
plt.figure(3)
plt.imshow(self.img_data.img_data)
plt.plot(self.calibration_data.geometry.data[:, 0], self.calibration_data.geometry.data[:, 1], 'g.')
plt.savefig('Results/recalib_blob2.jpg')
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 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))
__author__ = 'Clemens Prescher'
from pyFAI.blob_detection import BlobDetection
from Data.ImgData import ImgData
import numpy as np
import pylab
img_data = ImgData()
# img_data.load('/Users/Doomgoroth/Programming/Large Projects/Dioptas/Testing/pyFAITest/17_LaB6_dc300-00000.tif')
img_data.load(
'/Users/Doomgoroth/Programming/Large Projects/Dioptas/Testing/pyFAITest/LaB6_WOS_30keV_005.tif'
)
bd = BlobDetection(np.log1p(img_data.get_img_data()))
bd.process()
x = []
y = []
int = []
sigma = []
print bd.keypoints.__len__()
for j in range(bd.keypoints.__len__()):
k = bd.keypoints[j]
int.append(k[2])
sigma.append(k[3])
if sigma[-1] > 0.25:
x.append(k[0])
y.append(k[1])
pylab.hist(int)
class CalibrationController(object):
def __init__(self, working_dir, view=None, img_data=None, calibration_data=None):
self.working_dir = working_dir
if view == None:
self.view = CalibrationView()
else:
self.view = view
if img_data == None:
self.data = ImgData()
else:
self.data = img_data
if calibration_data == None:
self.calibration_data = CalibrationData(self.data)
else:
self.calibration_data = calibration_data
self.data.subscribe(self.plot_image)
self.view.set_start_values(self.calibration_data.start_values)
self._first_plot = True
self.create_signals()
self.load_calibrants_list()
self.raise_window()
def raise_window(self):
self.view.show()
self.view.setWindowState(self.view.windowState() & ~QtCore.Qt.WindowMinimized | QtCore.Qt.WindowActive)
self.view.activateWindow()
self.view.raise_()
def create_signals(self):
self.create_transformation_signals()
self.create_txt_box_signals()
self.view.calibrant_cb.currentIndexChanged.connect(self.load_calibrant)
self.connect_click_function(self.view.load_file_btn, self.load_file)
self.connect_click_function(self.view.save_calibration_btn, self.save_calibration)
self.connect_click_function(self.view.load_calibration_btn, self.load_calibration)
self.connect_click_function(self.view.integrate_btn, self.calibrate)
self.connect_click_function(self.view.refine_btn, self.refine)
self.view.img_view.add_left_click_observer(self.search_peaks)
self.connect_click_function(self.view.clear_peaks_btn, self.clear_peaks_btn_click)
def create_transformation_signals(self):
self.connect_click_function(self.view.rotate_m90_btn, self.data.rotate_img_m90)
self.connect_click_function(self.view.rotate_m90_btn, self.clear_peaks_btn_click)
self.connect_click_function(self.view.rotate_p90_btn, self.data.rotate_img_p90)
self.connect_click_function(self.view.rotate_p90_btn, self.clear_peaks_btn_click)
self.connect_click_function(self.view.invert_horizontal_btn, self.data.flip_img_horizontally)
self.connect_click_function(self.view.invert_horizontal_btn, self.clear_peaks_btn_click)
self.connect_click_function(self.view.invert_vertical_btn, self.data.flip_img_vertically)
self.connect_click_function(self.view.invert_vertical_btn, self.clear_peaks_btn_click)
self.connect_click_function(self.view.reset_transformations_btn, self.data.reset_img_transformations)
self.connect_click_function(self.view.reset_transformations_btn, self.clear_peaks_btn_click)
self.view.connect(self.view.f2_wavelength_cb, QtCore.SIGNAL('clicked()'), self.wavelength_cb_changed)
self.view.connect(self.view.pf_wavelength_cb, QtCore.SIGNAL('clicked()'), self.wavelength_cb_changed)
def create_txt_box_signals(self):
self.connect_click_function(self.view.f2_update_btn, self.update_f2_btn_click)
self.connect_click_function(self.view.pf_update_btn, self.update_pyFAI_btn_click)
def update_f2_btn_click(self):
fit2d_parameter = self.view.get_fit2d_parameter()
self.calibration_data.geometry.setFit2D(directDist=fit2d_parameter['directDist'],
centerX=fit2d_parameter['centerX'],
centerY=fit2d_parameter['centerY'],
tilt=fit2d_parameter['tilt'],
tiltPlanRotation=fit2d_parameter['tiltPlanRotation'],
pixelX=fit2d_parameter['pixelX'],
pixelY=fit2d_parameter['pixelY'])
self.calibration_data.geometry.wavelength = fit2d_parameter['wavelength']
self.calibration_data.polarization_factor = fit2d_parameter['polarization_factor']
self.calibration_data.is_calibrated = True
self.update_all()
def update_pyFAI_btn_click(self):
pyFAI_parameter = self.view.get_pyFAI_parameter()
self.calibration_data.geometry.setPyFAI(dist=pyFAI_parameter['dist'],
poni1=pyFAI_parameter['poni1'],
poni2=pyFAI_parameter['poni2'],
rot1=pyFAI_parameter['rot1'],
rot2=pyFAI_parameter['rot2'],
rot3=pyFAI_parameter['rot3'],
pixel1=pyFAI_parameter['pixel1'],
pixel2=pyFAI_parameter['pixel2'])
self.calibration_data.geometry.wavelength = pyFAI_parameter['wavelength']
self.calibration_data.polarization_factor = pyFAI_parameter['polarization_factor']
self.calibration_data.is_calibrated = True
self.update_all()
def load_file(self, filename=None):
if filename is None:
filename = str(QtGui.QFileDialog.getOpenFileName(self.view, caption="Load Calibration Image",
directory=self.working_dir['image']))
if filename is not '':
self.working_dir['image'] = os.path.dirname(filename)
self.data.load(filename)
def load_calibrants_list(self):
self._calibrants_file_list = []
self._calibrants_file_names_list = []
for file in os.listdir(self.calibration_data._calibrants_working_dir):
if file.endswith('.D'):
self._calibrants_file_list.append(file)
self._calibrants_file_names_list.append(file.split('.')[:-1][0])
self.view.calibrant_cb.blockSignals(True)
self.view.calibrant_cb.clear()
self.view.calibrant_cb.addItems(self._calibrants_file_names_list)
self.view.calibrant_cb.blockSignals(False)
self.view.calibrant_cb.setCurrentIndex(7) # to LaB6
self.load_calibrant()
def load_calibrant(self, wavelength_from='start_values'):
current_index = self.view.calibrant_cb.currentIndex()
filename = os.path.join(self.calibration_data._calibrants_working_dir,
self._calibrants_file_list[current_index])
self.calibration_data.set_calibrant(filename)
wavelength = 0
if wavelength_from == 'start_values':
start_values = self.view.get_start_values()
wavelength = start_values['wavelength']
elif wavelength_from == 'pyFAI':
pyFAI_parameter, _ = self.calibration_data.get_calibration_parameter()
if pyFAI_parameter['wavelength'] is not 0:
wavelength = pyFAI_parameter['wavelength']
else:
start_values = self.view.get_start_values()
wavelength = start_values['wavelength']
else:
start_values = self.view.get_start_values()
wavelength = start_values['wavelength']
self.calibration_data.calibrant.setWavelength_change2th(wavelength)
self.view.spectrum_view.plot_vertical_lines(np.array(self.calibration_data.calibrant.get_2th()) / np.pi * 180,
name=self._calibrants_file_names_list[current_index])
def set_calibrant(self, index):
self.view.calibrant_cb.setCurrentIndex(index)
self.load_calibrant()
def plot_image(self):
if self._first_plot:
self.view.img_view.plot_image(self.data.get_img_data(), True)
self.view.img_view.auto_range()
self._first_plot = False
else:
self.view.img_view.plot_image(self.data.get_img_data(), False)
self.view.set_img_filename(self.data.filename)
def connect_click_function(self, emitter, function):
self.view.connect(emitter, QtCore.SIGNAL('clicked()'), function)
def search_peaks(self, x, y):
peak_ind = self.view.peak_num_sb.value()
if self.view.automatic_peak_search_rb.isChecked():
points = self.calibration_data.find_peaks_automatic(x, y, peak_ind - 1)
else:
search_size = np.int(self.view.search_size_sb.value())
points = self.calibration_data.find_peak(x, y, search_size, peak_ind - 1)
if len(points):
self.plot_points(points)
if self.view.automatic_peak_num_inc_cb.checkState():
self.view.peak_num_sb.setValue(peak_ind + 1)
def plot_points(self, points=None):
if points == None:
try:
points = self.calibration_data.get_point_array()
except IndexError:
points = []
if len(points):
self.view.img_view.add_scatter_data(points[:, 0] + 0.5, points[:, 1] + 0.5)
def clear_peaks_btn_click(self):
self.calibration_data.clear_peaks()
self.view.img_view.clear_scatter_plot()
self.view.peak_num_sb.setValue(1)
def wavelength_cb_changed(self):
self.calibration_data.fit_wavelength = self.view.f2_wavelength_cb.isChecked()
def calibrate(self):
self.load_calibrant() #load the right calibration file...
self.calibration_data.set_start_values(self.view.get_start_values())
self.calibration_data.calibrate()
self.update_calibration_parameter()
if self.view.options_automatic_refinement_cb.isChecked():
self.refine()
self.update_all()
def refine(self):
self.clear_peaks_btn_click()
self.load_calibrant(wavelength_from='pyFAI') #load right calibration file
# get options
algorithm = str(self.view.options_peaksearch_algorithm_cb.currentText())
delta_tth = np.float(self.view.options_delta_tth_txt.text())
intensity_min_factor = np.float(self.view.options_intensity_mean_factor_sb.value())
intensity_max = np.float(self.view.options_intensity_limit_txt.text())
num_rings = self.view.options_num_rings_sb.value()
self.calibration_data.search_peaks_on_ring(0, delta_tth, algorithm, intensity_min_factor, intensity_max)
self.calibration_data.search_peaks_on_ring(1, delta_tth, algorithm, intensity_min_factor, intensity_max)
try:
self.calibration_data.refine()
except IndexError:
print 'Did not find any Points with the specified parameters for the first two rings!'
self.plot_points()
for i in xrange(num_rings - 2):
points = self.calibration_data.search_peaks_on_ring(i + 2, delta_tth, algorithm, intensity_min_factor,
intensity_max)
self.plot_points(points)
QtGui.QApplication.processEvents()
QtGui.QApplication.processEvents()
try:
self.calibration_data.refine()
except IndexError:
print 'Did not find enough points with the specified parameters!'
self.calibration_data.integrate()
self.update_all()
def load_calibration(self, filename=None):
if filename is None:
filename = str(QtGui.QFileDialog.getOpenFileName(self.view, caption="Load calibration...",
directory=self.working_dir['calibration'],
filter='*.poni'))
if filename is not '':
self.working_dir['calibration'] = os.path.dirname(filename)
self.calibration_data.load(filename)
self.update_all()
def update_all(self):
if not self._first_plot:
self.calibration_data.integrate_1d()
self.calibration_data.integrate_2d()
self.view.cake_view.plot_image(self.calibration_data.cake_img, True)
self.view.spectrum_view.plot_data(self.calibration_data.tth, self.calibration_data.int)
self.view.spectrum_view.plot_vertical_lines(np.array(self.calibration_data.calibrant.get_2th()) /
np.pi * 180)
self.view.spectrum_view.view_box.autoRange()
if self.view.tab_widget.currentIndex() == 0:
self.view.tab_widget.setCurrentIndex(1)
if self.view.ToolBox.currentIndex() is not 2 or \
self.view.ToolBox.currentIndex() is not 3:
self.view.ToolBox.setCurrentIndex(2)
self.update_calibration_parameter()
def update_calibration_parameter(self):
pyFAI_parameter, fit2d_parameter = self.calibration_data.get_calibration_parameter()
self.view.set_calibration_parameters(pyFAI_parameter, fit2d_parameter)
def save_calibration(self, filename=None):
if filename is None:
filename = str(QtGui.QFileDialog.getSaveFileName(self.view, "Save calibration...",
self.working_dir['calibration'], '*.poni'))
if filename is not '':
self.working_dir['calibration'] = os.path.dirname(filename)
self.calibration_data.geometry.save(filename)
class CalibrationController(object):
def __init__(self,
working_dir,
view=None,
img_data=None,
calibration_data=None):
self.working_dir = working_dir
if view == None:
self.view = CalibrationView()
else:
self.view = view
if img_data == None:
self.data = ImgData()
else:
self.data = img_data
if calibration_data == None:
self.calibration_data = CalibrationData(self.data)
else:
self.calibration_data = calibration_data
self.data.subscribe(self.plot_image)
self.view.set_start_values(self.calibration_data.start_values)
self._first_plot = True
self.create_signals()
self.load_calibrants_list()
self.raise_window()
def raise_window(self):
self.view.show()
self.view.setWindowState(self.view.windowState()
& ~QtCore.Qt.WindowMinimized
| QtCore.Qt.WindowActive)
self.view.activateWindow()
self.view.raise_()
def create_signals(self):
self.create_transformation_signals()
self.create_txt_box_signals()
self.view.calibrant_cb.currentIndexChanged.connect(self.load_calibrant)
self.connect_click_function(self.view.load_file_btn, self.load_file)
self.connect_click_function(self.view.save_calibration_btn,
self.save_calibration)
self.connect_click_function(self.view.load_calibration_btn,
self.load_calibration)
self.connect_click_function(self.view.integrate_btn, self.calibrate)
self.connect_click_function(self.view.refine_btn, self.refine)
self.view.img_view.add_left_click_observer(self.search_peaks)
self.connect_click_function(self.view.clear_peaks_btn,
self.clear_peaks_btn_click)
def create_transformation_signals(self):
self.connect_click_function(self.view.rotate_m90_btn,
self.data.rotate_img_m90)
self.connect_click_function(self.view.rotate_m90_btn,
self.clear_peaks_btn_click)
self.connect_click_function(self.view.rotate_p90_btn,
self.data.rotate_img_p90)
self.connect_click_function(self.view.rotate_p90_btn,
self.clear_peaks_btn_click)
self.connect_click_function(self.view.invert_horizontal_btn,
self.data.flip_img_horizontally)
self.connect_click_function(self.view.invert_horizontal_btn,
self.clear_peaks_btn_click)
self.connect_click_function(self.view.invert_vertical_btn,
self.data.flip_img_vertically)
self.connect_click_function(self.view.invert_vertical_btn,
self.clear_peaks_btn_click)
self.connect_click_function(self.view.reset_transformations_btn,
self.data.reset_img_transformations)
self.connect_click_function(self.view.reset_transformations_btn,
self.clear_peaks_btn_click)
self.view.connect(self.view.f2_wavelength_cb,
QtCore.SIGNAL('clicked()'),
self.wavelength_cb_changed)
self.view.connect(self.view.pf_wavelength_cb,
QtCore.SIGNAL('clicked()'),
self.wavelength_cb_changed)
def create_txt_box_signals(self):
self.connect_click_function(self.view.f2_update_btn,
self.update_f2_btn_click)
self.connect_click_function(self.view.pf_update_btn,
self.update_pyFAI_btn_click)
def update_f2_btn_click(self):
fit2d_parameter = self.view.get_fit2d_parameter()
self.calibration_data.geometry.setFit2D(
directDist=fit2d_parameter['directDist'],
centerX=fit2d_parameter['centerX'],
centerY=fit2d_parameter['centerY'],
tilt=fit2d_parameter['tilt'],
tiltPlanRotation=fit2d_parameter['tiltPlanRotation'],
pixelX=fit2d_parameter['pixelX'],
pixelY=fit2d_parameter['pixelY'])
self.calibration_data.geometry.wavelength = fit2d_parameter[
'wavelength']
self.calibration_data.polarization_factor = fit2d_parameter[
'polarization_factor']
self.calibration_data.is_calibrated = True
self.update_all()
def update_pyFAI_btn_click(self):
pyFAI_parameter = self.view.get_pyFAI_parameter()
self.calibration_data.geometry.setPyFAI(
dist=pyFAI_parameter['dist'],
poni1=pyFAI_parameter['poni1'],
poni2=pyFAI_parameter['poni2'],
rot1=pyFAI_parameter['rot1'],
rot2=pyFAI_parameter['rot2'],
rot3=pyFAI_parameter['rot3'],
pixel1=pyFAI_parameter['pixel1'],
pixel2=pyFAI_parameter['pixel2'])
self.calibration_data.geometry.wavelength = pyFAI_parameter[
'wavelength']
self.calibration_data.polarization_factor = pyFAI_parameter[
'polarization_factor']
self.calibration_data.is_calibrated = True
self.update_all()
def load_file(self, filename=None):
if filename is None:
filename = str(
QtGui.QFileDialog.getOpenFileName(
self.view,
caption="Load Calibration Image",
directory=self.working_dir['image']))
if filename is not '':
self.working_dir['image'] = os.path.dirname(filename)
self.data.load(filename)
def load_calibrants_list(self):
self._calibrants_file_list = []
self._calibrants_file_names_list = []
for file in os.listdir(self.calibration_data._calibrants_working_dir):
if file.endswith('.D'):
self._calibrants_file_list.append(file)
self._calibrants_file_names_list.append(
file.split('.')[:-1][0])
self.view.calibrant_cb.blockSignals(True)
self.view.calibrant_cb.clear()
self.view.calibrant_cb.addItems(self._calibrants_file_names_list)
self.view.calibrant_cb.blockSignals(False)
self.view.calibrant_cb.setCurrentIndex(7) # to LaB6
self.load_calibrant()
def load_calibrant(self, wavelength_from='start_values'):
current_index = self.view.calibrant_cb.currentIndex()
filename = os.path.join(self.calibration_data._calibrants_working_dir,
self._calibrants_file_list[current_index])
self.calibration_data.set_calibrant(filename)
wavelength = 0
if wavelength_from == 'start_values':
start_values = self.view.get_start_values()
wavelength = start_values['wavelength']
elif wavelength_from == 'pyFAI':
pyFAI_parameter, _ = self.calibration_data.get_calibration_parameter(
)
if pyFAI_parameter['wavelength'] is not 0:
wavelength = pyFAI_parameter['wavelength']
else:
start_values = self.view.get_start_values()
wavelength = start_values['wavelength']
else:
start_values = self.view.get_start_values()
wavelength = start_values['wavelength']
self.calibration_data.calibrant.setWavelength_change2th(wavelength)
self.view.spectrum_view.plot_vertical_lines(
np.array(self.calibration_data.calibrant.get_2th()) / np.pi * 180,
name=self._calibrants_file_names_list[current_index])
def set_calibrant(self, index):
self.view.calibrant_cb.setCurrentIndex(index)
self.load_calibrant()
def plot_image(self):
if self._first_plot:
self.view.img_view.plot_image(self.data.get_img_data(), True)
self.view.img_view.auto_range()
self._first_plot = False
else:
self.view.img_view.plot_image(self.data.get_img_data(), False)
self.view.set_img_filename(self.data.filename)
def connect_click_function(self, emitter, function):
self.view.connect(emitter, QtCore.SIGNAL('clicked()'), function)
def search_peaks(self, x, y):
peak_ind = self.view.peak_num_sb.value()
if self.view.automatic_peak_search_rb.isChecked():
points = self.calibration_data.find_peaks_automatic(
x, y, peak_ind - 1)
else:
search_size = np.int(self.view.search_size_sb.value())
points = self.calibration_data.find_peak(x, y, search_size,
peak_ind - 1)
if len(points):
self.plot_points(points)
if self.view.automatic_peak_num_inc_cb.checkState():
self.view.peak_num_sb.setValue(peak_ind + 1)
def plot_points(self, points=None):
if points == None:
try:
points = self.calibration_data.get_point_array()
except IndexError:
points = []
if len(points):
self.view.img_view.add_scatter_data(points[:, 0] + 0.5,
points[:, 1] + 0.5)
def clear_peaks_btn_click(self):
self.calibration_data.clear_peaks()
self.view.img_view.clear_scatter_plot()
self.view.peak_num_sb.setValue(1)
def wavelength_cb_changed(self):
self.calibration_data.fit_wavelength = self.view.f2_wavelength_cb.isChecked(
)
def calibrate(self):
self.load_calibrant() #load the right calibration file...
self.calibration_data.set_start_values(self.view.get_start_values())
self.calibration_data.calibrate()
self.update_calibration_parameter()
if self.view.options_automatic_refinement_cb.isChecked():
self.refine()
self.update_all()
def refine(self):
self.clear_peaks_btn_click()
self.load_calibrant(
wavelength_from='pyFAI') #load right calibration file
# get options
algorithm = str(
self.view.options_peaksearch_algorithm_cb.currentText())
delta_tth = np.float(self.view.options_delta_tth_txt.text())
intensity_min_factor = np.float(
self.view.options_intensity_mean_factor_sb.value())
intensity_max = np.float(self.view.options_intensity_limit_txt.text())
num_rings = self.view.options_num_rings_sb.value()
self.calibration_data.search_peaks_on_ring(0, delta_tth, algorithm,
intensity_min_factor,
intensity_max)
self.calibration_data.search_peaks_on_ring(1, delta_tth, algorithm,
intensity_min_factor,
intensity_max)
try:
self.calibration_data.refine()
except IndexError:
print 'Did not find any Points with the specified parameters for the first two rings!'
self.plot_points()
for i in xrange(num_rings - 2):
points = self.calibration_data.search_peaks_on_ring(
i + 2, delta_tth, algorithm, intensity_min_factor,
intensity_max)
self.plot_points(points)
QtGui.QApplication.processEvents()
QtGui.QApplication.processEvents()
try:
self.calibration_data.refine()
except IndexError:
print 'Did not find enough points with the specified parameters!'
self.calibration_data.integrate()
self.update_all()
def load_calibration(self, filename=None):
if filename is None:
filename = str(
QtGui.QFileDialog.getOpenFileName(
self.view,
caption="Load calibration...",
directory=self.working_dir['calibration'],
filter='*.poni'))
if filename is not '':
self.working_dir['calibration'] = os.path.dirname(filename)
self.calibration_data.load(filename)
self.update_all()
def update_all(self):
if not self._first_plot:
self.calibration_data.integrate_1d()
self.calibration_data.integrate_2d()
self.view.cake_view.plot_image(self.calibration_data.cake_img,
True)
self.view.spectrum_view.plot_data(self.calibration_data.tth,
self.calibration_data.int)
self.view.spectrum_view.plot_vertical_lines(
np.array(self.calibration_data.calibrant.get_2th()) / np.pi *
180)
self.view.spectrum_view.view_box.autoRange()
if self.view.tab_widget.currentIndex() == 0:
self.view.tab_widget.setCurrentIndex(1)
if self.view.ToolBox.currentIndex() is not 2 or \
self.view.ToolBox.currentIndex() is not 3:
self.view.ToolBox.setCurrentIndex(2)
self.update_calibration_parameter()
def update_calibration_parameter(self):
pyFAI_parameter, fit2d_parameter = self.calibration_data.get_calibration_parameter(
)
self.view.set_calibration_parameters(pyFAI_parameter, fit2d_parameter)
def save_calibration(self, filename=None):
if filename is None:
filename = str(
QtGui.QFileDialog.getSaveFileName(
self.view, "Save calibration...",
self.working_dir['calibration'], '*.poni'))
if filename is not '':
self.working_dir['calibration'] = os.path.dirname(filename)
self.calibration_data.geometry.save(filename)
__author__ = 'Clemens Prescher'
from pyFAI.blob_detection import BlobDetection
from Data.ImgData import ImgData
import numpy as np
import pylab
img_data = ImgData()
# img_data.load('/Users/Doomgoroth/Programming/Large Projects/Dioptas/Testing/pyFAITest/17_LaB6_dc300-00000.tif')
img_data.load('/Users/Doomgoroth/Programming/Large Projects/Dioptas/Testing/pyFAITest/LaB6_WOS_30keV_005.tif')
bd = BlobDetection(np.log1p(img_data.get_img_data()))
bd.process()
x = []
y = []
int = []
sigma = []
print bd.keypoints.__len__()
for j in range(bd.keypoints.__len__()):
k = bd.keypoints[j]
int.append(k[2])
sigma.append(k[3])
if sigma[-1] > 0.25:
x.append(k[0])
y.append(k[1])
pylab.hist(int)
pylab.figure(2)
pylab.hist(sigma)
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))
