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))