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fittingWindow.py
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fittingWindow.py
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# general imports
import numpy
from scipy.optimize import curve_fit
# import PyQt5 elements
from PyQt5.QtCore import Qt
from PyQt5.QtGui import QCursor
from PyQt5.QtWidgets import QApplication, QComboBox, QMainWindow, QMessageBox, QProgressDialog, QPushButton,\
QTableWidgetItem, QToolTip, QWidget
# import fit functions
import fitting
# import UI
from UIs.fittingWidgetUi import UiFittingWidget
class FittingWidget(QWidget):
"""
FittingWidget
The fitting widget is used for the fitting of the map.
"""
# TODO: 1D Map Fitting
def __init__(self, parent, map_handle):
# call widget init
super().__init__()
# link app
self._app = QApplication.instance()
# link map handle
self._map = map_handle
# load and set up UI
self.ui = UiFittingWidget(self)
# fill threshold combo box
self.ui.threshold_type_combo.addItems(['spectra', '-- integral', '-- mean', '-- maximum'])
self.ui.threshold_type_combo.model().item(0).setEnabled(False)
self.ui.threshold_type_combo.setCurrentIndex(1)
for key, value in self._map.get_data_names().items():
self.ui.threshold_type_combo.addItems([value])
# set area slider limits
map_size = self._map.get_size()
if self._map.get_dimension() == 2:
self.ui.area_slider_x1.setMinimum(0)
self.ui.area_slider_x1.setMaximum(map_size[0]-1)
self.ui.area_slider_x2.setMinimum(0)
self.ui.area_slider_x2.setMaximum(map_size[0]-1)
self.ui.area_slider_x2.setValue(map_size[0]-1)
self.ui.area_slider_y1.setMinimum(0)
self.ui.area_slider_y1.setMaximum(map_size[1]-1)
self.ui.area_slider_y2.setMinimum(0)
self.ui.area_slider_y2.setMaximum(map_size[1]-1)
self.ui.area_slider_y2.setValue(map_size[1]-1)
else:
self.ui.area_slider_x1.setMinimum(0)
self.ui.area_slider_x1.setMaximum(map_size[0]-1)
self.ui.area_slider_x2.setMinimum(0)
self.ui.area_slider_x2.setMaximum(map_size[0]-1)
self.ui.area_slider_x2.setValue(map_size[0]-1)
# set maximum value for the limit selections
map_resolution = self._map.get_resolution()
self.ui.lower_limit_slider.setMaximum(map_resolution-1)
self.ui.upper_limit_slider.setMaximum(map_resolution-1)
self.ui.upper_limit_slider.setValue(map_resolution-1)
# fill parameter table with combo boxes for function selection and disable cells
self._function_combo_boxes = {}
for i_row in range(6):
for i_col in range(5):
self.ui.table_widget.setItem(i_row, i_col, QTableWidgetItem())
if i_col == 0:
self._function_combo_boxes['function_' + str(i_row)] = QComboBox()
self._function_combo_boxes['function_' + str(i_row)].setObjectName('function_'+str(i_row))
self._function_combo_boxes['function_' + str(i_row)].addItem("Off")
self._function_combo_boxes['function_' + str(i_row)].addItem("Gau.")
self._function_combo_boxes['function_' + str(i_row)].addItem("Lor.")
self._function_combo_boxes['function_' + str(i_row)].addItem("Voi.")
self._function_combo_boxes['function_' + str(i_row)].currentIndexChanged.connect(self.cb_function_selected)
self.ui.table_widget.setCellWidget(i_row, i_col, self._function_combo_boxes['function_' + str(i_row)])
else:
self.ui.table_widget.item(i_row, i_col).setFlags(Qt.NoItemFlags)
# fill boundary tables
for i_row in range(6):
for i_col in range(4):
self.ui.table_widget_2.setItem(i_row, i_col, QTableWidgetItem())
self.ui.table_widget_3.setItem(i_row, i_col, QTableWidgetItem())
self.ui.table_widget_2.item(i_row, i_col).setText('0')
self.ui.table_widget_3.item(i_row, i_col).setText('Inf')
# set parent
self.setParent(parent)
# link callbacks for radio buttons
self.ui.focused_pixel_radio_button.toggled.connect(self.cb_radio_button_buttons)
# link callbacks for sliders
self.ui.lower_limit_slider.sliderPressed.connect(self.cb_limit_slider_pressed)
self.ui.lower_limit_slider.sliderMoved.connect(self.cb_limit_slider_moved)
self.ui.lower_limit_slider.sliderReleased.connect(self.cb_limit_slider_released)
self.ui.upper_limit_slider.sliderPressed.connect(self.cb_limit_slider_pressed)
self.ui.upper_limit_slider.sliderMoved.connect(self.cb_limit_slider_moved)
self.ui.upper_limit_slider.sliderReleased.connect(self.cb_limit_slider_released)
self.ui.lower_threshold_slider.sliderPressed.connect(self.cb_threshold_slider_pressed)
self.ui.lower_threshold_slider.sliderMoved.connect(self.cb_threshold_slider_moved)
self.ui.lower_threshold_slider.sliderReleased.connect(self.cb_threshold_slider_released)
self.ui.upper_threshold_slider.sliderPressed.connect(self.cb_threshold_slider_pressed)
self.ui.upper_threshold_slider.sliderMoved.connect(self.cb_threshold_slider_moved)
self.ui.upper_threshold_slider.sliderReleased.connect(self.cb_threshold_slider_released)
self.ui.area_slider_x1.sliderPressed.connect(self.cb_area_slider_pressed)
self.ui.area_slider_x1.sliderMoved.connect(self.cb_area_slider_moved)
self.ui.area_slider_x1.sliderReleased.connect(self.cb_area_slider_released)
self.ui.area_slider_x2.sliderPressed.connect(self.cb_area_slider_pressed)
self.ui.area_slider_x2.sliderMoved.connect(self.cb_area_slider_moved)
self.ui.area_slider_x2.sliderReleased.connect(self.cb_area_slider_released)
self.ui.area_slider_y1.sliderPressed.connect(self.cb_area_slider_pressed)
self.ui.area_slider_y1.sliderMoved.connect(self.cb_area_slider_moved)
self.ui.area_slider_y1.sliderReleased.connect(self.cb_area_slider_released)
self.ui.area_slider_y2.sliderPressed.connect(self.cb_area_slider_pressed)
self.ui.area_slider_y2.sliderMoved.connect(self.cb_area_slider_moved)
self.ui.area_slider_y2.sliderReleased.connect(self.cb_area_slider_released)
# link callbacks for buttons
self.ui.clear_push_button.clicked.connect(self.cb_clear_push_button)
self.ui.fit_push_button.clicked.connect(self.cb_fit_push_button)
def cb_area_slider_moved(self):
# update area map on the map canvas
if self._map.get_dimension() == 2:
self._app.windows['mapWindow'].ui.tab_widget.currentWidget().update_area_map(
self.ui.area_slider_x1.value(), self.ui.area_slider_x2.value(),
self.ui.area_slider_y1.value(), self.ui.area_slider_y2.value())
else:
self._app.windows['mapWindow'].ui.tab_widget.currentWidget().update_area_map(
self.ui.area_slider_x1.value(), self.ui.area_slider_x2.value())
def cb_area_slider_pressed(self):
# create area map on the map canvas
if self._map.get_dimension() == 2:
self._app.windows['mapWindow'].ui.tab_widget.currentWidget().create_area_map(
self.ui.area_slider_x1.value(), self.ui.area_slider_x2.value(),
self.ui.area_slider_y1.value(), self.ui.area_slider_y2.value())
else:
self._app.windows['mapWindow'].ui.tab_widget.currentWidget().create_area_map(
self.ui.area_slider_x1.value(), self.ui.area_slider_x2.value())
def cb_area_slider_released(self):
# remove area map from the map canvas
self._app.windows['mapWindow'].ui.tab_widget.currentWidget().destroy_area_map()
# bring this window to front again
self.setWindowState(self.windowState() & ~Qt.WindowMinimized | Qt.WindowActive)
self.activateWindow()
def cb_clear_push_button(self):
if self.ui.focused_pixel_radio_button.isChecked():
# clear fit of the focused pixel
self._map.clear_fit(emit=True)
else:
# check dimension of the map
if self._map.get_dimension() == 2:
# get the area to be cleared
if self.ui.area_slider_x2.value() < self.ui.area_slider_x1.value():
x2 = self.ui.area_slider_x1.value()
x1 = self.ui.area_slider_x2.value()
else:
x1 = self.ui.area_slider_x1.value()
x2 = self.ui.area_slider_x2.value()
if self.ui.area_slider_y2.value() < self.ui.area_slider_y1.value():
y2 = self.ui.area_slider_y1.value()
y1 = self.ui.area_slider_y2.value()
else:
y1 = self.ui.area_slider_y1.value()
y2 = self.ui.area_slider_y2.value()
fit_area = [x1, x2, y1, y2]
# get the threshold and the threshold data
threshold_data = self._map.get_data(data_index=self.ui.threshold_type_combo.currentIndex())
min_data = numpy.min(threshold_data)
max_data = numpy.max(threshold_data)
lower_threshold = min_data+1./10000.*self.ui.lower_threshold_slider.value()*(max_data-min_data)
upper_threshold = min_data+1./10000.*self.ui.upper_threshold_slider.value()*(max_data-min_data)
# clear fits from the area which fulfills the threshold condition
for ix in range(int(numpy.ceil(fit_area[0])), int(numpy.ceil(fit_area[1]))):
for iy in range(int(numpy.ceil(fit_area[2])), int(numpy.ceil(fit_area[3]))):
if lower_threshold <= threshold_data[ix, iy] <= upper_threshold:
# check if this is the last cleared fit in this column
if numpy.sum(numpy.logical_and(
lower_threshold <= threshold_data[ix, iy:int(numpy.ceil(fit_area[3]))],
threshold_data[ix, iy] <= upper_threshold)) == 1:
self._map.clear_fit(pixel=[ix, iy], emit=True)
else:
self._map.clear_fit(pixel=[ix, iy], emit=False)
# process events
self._app.processEvents()
else:
return
def cb_fit_push_button(self):
# get fit functions
fit_functions = numpy.zeros(6)
n_parameters = 0
for i_peak in range(6):
fit_functions[i_peak] = self._function_combo_boxes['function_'+str(i_peak)] .currentIndex()
if fit_functions[i_peak] == 1 or fit_functions[i_peak] == 2:
n_parameters += 3
elif fit_functions[i_peak] == 3:
n_parameters += 4
# arrays for the submitted parameters
fit_initial_parameters = numpy.zeros(n_parameters)
fit_lower_boundaries = numpy.zeros(n_parameters)
fit_upper_boundaries = numpy.zeros(n_parameters)
# read array from table
j_parameter = 0
for i_peak in range(6):
# check which columns need to be read
parameters = []
if fit_functions[i_peak] == 1:
parameters = [1, 2, 3]
elif fit_functions[i_peak] == 2:
parameters = [1, 2, 4]
elif fit_functions[i_peak] == 3:
parameters = [1, 2, 3, 4]
# read the parameters and boundaries
for i_parameter in parameters:
# read parameter
try:
if 3 <= i_parameter <= 4:
fit_initial_parameters[j_parameter] = float(self.ui.table_widget.item(i_peak, i_parameter).text())/1000
else:
fit_initial_parameters[j_parameter] = float(self.ui.table_widget.item(i_peak, i_parameter).text())
except ValueError:
parameter_names = ['I', 'ε', 'σ', 'γ']
subscripts = [u'\u2081', u'\u2082', u'\u2083', u'\u2084', u'\u2085', u'\u2086']
message_box = QMessageBox(self._app.windows['fittingWindow'])
message_box.setIcon(QMessageBox.Information)
message_box.setWindowTitle('Wrong parameter!')
message_box.setText('Could not read parameter '+parameter_names[i_parameter-1]+subscripts[i_peak])
message_box.setStandardButtons(QMessageBox.Ok)
message_box.exec_()
return
# read lower boundary
try:
if 3 <= i_parameter <= 4:
fit_lower_boundaries[j_parameter] = float(self.ui.table_widget_2.item(i_peak, i_parameter-1).text())/1000
else:
fit_lower_boundaries[j_parameter] = float(self.ui.table_widget_2.item(i_peak, i_parameter-1).text())
except ValueError:
parameter_names = ['I', 'ε', 'σ', 'γ']
subscripts = [u'\u2081', u'\u2082', u'\u2083', u'\u2084', u'\u2085', u'\u2086']
message_box = QMessageBox(self._app.windows['fittingWindow'])
message_box.setIcon(QMessageBox.Information)
message_box.setWindowTitle('Wrong boundary!')
message_box.setText('Could not read lower boundary for '+parameter_names[i_parameter-1]+subscripts[i_peak])
message_box.setStandardButtons(QMessageBox.Ok)
message_box.exec_()
return
# read upper boundary
try:
if 3 <= i_parameter <= 4:
fit_upper_boundaries[j_parameter] = float(self.ui.table_widget_3.item(i_peak, i_parameter-1).text())/1000
else:
fit_upper_boundaries[j_parameter] = float(self.ui.table_widget_3.item(i_peak, i_parameter-1).text())
except ValueError:
parameter_names = ['I', 'ε', 'σ', 'γ']
subscripts = [u'\u2081', u'\u2082', u'\u2083', u'\u2084', u'\u2085', u'\u2086']
message_box = QMessageBox(self._app.windows['fittingWindow'])
message_box.setIcon(QMessageBox.Information)
message_box.setWindowTitle('Wrong boundary!')
message_box.setText('Could not read upper boundary for '+parameter_names[i_parameter-1]+subscripts[i_peak])
message_box.setStandardButtons(QMessageBox.Ok)
message_box.exec_()
return
j_parameter += 1
# define fit function
def fit_function(x, *p):
result = numpy.zeros(len(x))
k_parameter = 0
for k_peak in range(len(fit_functions)):
if fit_functions[k_peak] == 1:
result = result + fitting.gaussian(x, *p[k_parameter:k_parameter+3])
k_parameter += 3
elif fit_functions[k_peak] == 2:
result = result + fitting.lorentzian(x, *p[k_parameter:k_parameter+3])
k_parameter += 3
elif fit_functions[k_peak] == 3:
result = result + fitting.voigt(x, *p[k_parameter:k_parameter+4])
k_parameter += 4
return result
# check if only one or multiple pixels are to be fitted
if self.ui.focused_pixel_radio_button.isChecked():
# load spectrum
spectrum = self._map.get_spectrum()
# perform fit
try:
fit_optimized_parameters, covariance = curve_fit(fit_function,
spectrum[
self.ui.lower_limit_slider.value():
self.ui.upper_limit_slider.value(), 0],
spectrum[
self.ui.lower_limit_slider.value():
self.ui.upper_limit_slider.value(), 1],
p0=fit_initial_parameters,
bounds=(fit_lower_boundaries, fit_upper_boundaries))
# save fit
self._map.set_fit(fit_functions, fit_initial_parameters, fit_optimized_parameters, emit=True)
except RuntimeError:
message_box = QMessageBox(self._app.windows['fittingWindow'])
message_box.setIcon(QMessageBox.Information)
message_box.setWindowTitle('Fitting failed!')
message_box.setText('Fitting failed for focused pixel!')
message_box.setStandardButtons(QMessageBox.Ok)
message_box.exec_()
else:
if self._map.get_dimension() == 2:
# get the area to fit
if self.ui.area_slider_x2.value() < self.ui.area_slider_x1.value():
x2 = self.ui.area_slider_x1.value()
x1 = self.ui.area_slider_x2.value()
else:
x1 = self.ui.area_slider_x1.value()
x2 = self.ui.area_slider_x2.value()
if self.ui.area_slider_y2.value() < self.ui.area_slider_y1.value():
y2 = self.ui.area_slider_y1.value()
y1 = self.ui.area_slider_y2.value()
else:
y1 = self.ui.area_slider_y1.value()
y2 = self.ui.area_slider_y2.value()
fit_area = [x1, x2, y1, y2]
# threshold settings
threshold_data = self._map.get_data(data_index=self.ui.threshold_type_combo.currentIndex())
min_data = numpy.min(threshold_data)
max_data = numpy.max(threshold_data)
lower_threshold = min_data+1./10000.*self.ui.lower_threshold_slider.value()*(max_data-min_data)
upper_threshold = min_data+1./10000.*self.ui.upper_threshold_slider.value()*(max_data-min_data)
# get existing fit functions in order to check for already fitted pixels
existing_fit_functions = self._map.get_fit_functions()
# number of pixels to fit
n_pixels = numpy.count_nonzero(numpy.logical_and(
lower_threshold <= threshold_data[int(numpy.ceil(fit_area[0])):1+int(numpy.floor(fit_area[1])), int(numpy.ceil(fit_area[2])):1+int(numpy.floor(fit_area[3]))],
upper_threshold >= threshold_data[int(numpy.ceil(fit_area[0])):1+int(numpy.floor(fit_area[1])), int(numpy.ceil(fit_area[2])):1+int(numpy.floor(fit_area[3]))]))
# create progressbar dialog
progress_dialog = QProgressDialog('', '', 0, n_pixels, self._app.windows['fittingWindow'])
progress_dialog.setWindowTitle('Fitting')
progress_dialog.setWindowModality(Qt.WindowModal)
progress_dialog_cancel_button = QPushButton('Stop')
progress_dialog.setCancelButton(progress_dialog_cancel_button)
progress_dialog.show()
# start live plotting
self._app.start_live_plotting()
# start fitting
i_px = 0
for ix in range(int(numpy.ceil(fit_area[0])), 1+int(numpy.floor(fit_area[1]))):
for iy in range(int(numpy.ceil(fit_area[2])), 1+int(numpy.floor(fit_area[3]))):
# check if process was canceled
if progress_dialog.wasCanceled():
break
# check if pixel is within threshold area
if lower_threshold <= threshold_data[ix, iy] <= upper_threshold:
# check if pixel is already fitted
if self.ui.overwrite_check_box.isChecked() or \
numpy.sum(existing_fit_functions[ix, iy, :]) == 0:
# load spectrum
spectrum = self._map.get_spectrum(pixel=[ix, iy])
# get parameters from neighbours
if self.ui.neighbour_check_box.isChecked():
# define order in which to look for neighbours
neighbours = [[[ix-1, iy], [ix+1, iy], [ix, iy-1], [ix, iy+1]],
[[ix-1, iy-1], [ix-1, iy+1], [ix+1, iy-1], [ix+1, iy+1]],
[[ix-2, iy], [ix+2, iy], [ix, iy-2], [ix, iy+2]],
[[ix-1, iy-2], [ix-1, iy+2], [ix+1, iy-2], [ix+1, iy+2], [ix-2, iy-1], [ix-2, iy+1], [ix+2, iy-1], [ix+2, iy+1]]]
# counter for suitable neighbours
n_neighbours = 0
# averaged neighbour parameters
parameters_neighbours = numpy.zeros(n_parameters)
# iterate neighbour orders: check first closest neighbours, then second closest neighbours ...
for i_neighbour_order in range(len(neighbours)):
for i_neighbour in range(len(neighbours[i_neighbour_order])):
# check if potential neighbour is on map
if neighbours[i_neighbour_order][i_neighbour][0] < 0 or neighbours[i_neighbour_order][i_neighbour][0] >= self._map.get_size()[0]:
break
if neighbours[i_neighbour_order][i_neighbour][1] < 0 or neighbours[i_neighbour_order][i_neighbour][1] >= self._map.get_size()[1]:
break
# get fit functions from neighbour
fit_functions_neighbour = self._map.get_fit_functions(pixel=neighbours[i_neighbour_order][i_neighbour])
# check if fit functions are the same as the current ones
if (fit_functions == fit_functions_neighbour).all():
# get parameters at neighbour pixel
parameters_neighbour = self._map.get_fit_parameters(pixel=neighbours[i_neighbour_order][i_neighbour])
j_parameter = 0
for neighbour_peak in range(6):
if 1 <= fit_functions_neighbour[neighbour_peak] <= 2:
parameters_neighbours[j_parameter:j_parameter+3] += parameters_neighbour[neighbour_peak, 0:3]
j_parameter += 3
elif fit_functions_neighbour[neighbour_peak] == 3:
parameters_neighbours[j_parameter:j_parameter+4] += parameters_neighbour[neighbour_peak, 0:4]
j_parameter += 4
n_neighbours += 1
# if at least one neighbour was found do not look at higher neighbor orders
if n_neighbours > 0:
break
# if a neighbour was found, take the neighbour parameters, otherwise initial parameters
if n_neighbours > 0:
parameters_neighbours /= n_neighbours
start_parameters = parameters_neighbours
else:
start_parameters = fit_initial_parameters
# if neighbour function is not checked
else:
start_parameters = fit_initial_parameters
# perform fit
try:
fit_optimized_parameters, covariance = curve_fit(
fit_function,
spectrum[self.ui.lower_limit_slider.value():self.ui.upper_limit_slider.value(), 0],
spectrum[self.ui.lower_limit_slider.value():self.ui.upper_limit_slider.value(), 1],
p0=start_parameters, bounds=(fit_lower_boundaries, fit_upper_boundaries))
# check if this is the currently focused pixel
if ix == self._map.get_focus()[0] and iy == self._map.get_focus()[1]:
# save fit
self._map.set_fit(fit_functions, start_parameters, fit_optimized_parameters,
pixel=[ix, iy], emit=True)
else:
# save fit
self._map.set_fit(fit_functions, start_parameters, fit_optimized_parameters,
pixel=[ix, iy], emit=False)
except RuntimeError:
message_box = QMessageBox(self._app.windows['fittingWindow'])
message_box.setIcon(QMessageBox.Information)
message_box.setWindowTitle('Fitting failed!')
message_box.setText('Fitting failed for pixel ('+str(ix)+','+str(iy)+')')
message_box.addButton('Continue Fitting', QMessageBox.AcceptRole)
message_box.addButton('Stop Fitting', QMessageBox.AcceptRole)
message_box.exec_()
if message_box.result() == 1:
progress_dialog.close()
return
# process events
self._app.processEvents()
# update progress bar
i_px += 1
progress_dialog.setValue(i_px)
# check if process was canceled
if progress_dialog.wasCanceled():
break
# stop live plotting
self._app.stop_live_plotting()
else:
# get the area to fit
if self.ui.area_slider_x2.value() < self.ui.area_slider_x1.value():
x2 = self.ui.area_slider_x1.value()
x1 = self.ui.area_slider_x2.value()
else:
x1 = self.ui.area_slider_x1.value()
x2 = self.ui.area_slider_x2.value()
fit_area = [x1, x2]
# threshold settings
threshold_data = self._map.get_data(data_index=1+self.ui.threshold_type_combo.currentIndex())
min_data = numpy.min(threshold_data)
max_data = numpy.max(threshold_data)
lower_threshold = min_data+1./10000.*self.ui.lower_threshold_slider.value()*(max_data-min_data)
upper_threshold = min_data+1./10000.*self.ui.upper_threshold_slider.value()*(max_data-min_data)
# get existing fit functions in order to check for already fitted pixels
existing_fit_functions = self._map.get_fit_functions()
# number of pixels to fit
n_pixels = numpy.count_nonzero(numpy.logical_and(
lower_threshold <= threshold_data[int(numpy.ceil(fit_area[0])):1+int(numpy.floor(fit_area[1]))],
upper_threshold >= threshold_data[int(numpy.ceil(fit_area[0])):1+int(numpy.floor(fit_area[1]))]))
# create progressbar dialog
progress_dialog = QProgressDialog('', '', 0, n_pixels, self._app.windows['fittingWindow'])
progress_dialog.setWindowTitle('Fitting')
progress_dialog.setWindowModality(Qt.WindowModal)
progress_dialog_cancel_button = QPushButton('Stop')
progress_dialog.setCancelButton(progress_dialog_cancel_button)
progress_dialog.show()
# start live plotting
self._app.start_live_plotting()
# start fitting
i_px = 0
for ix in range(int(numpy.ceil(fit_area[0])), 1+int(numpy.floor(fit_area[1]))):
# check if process was canceled
if progress_dialog.wasCanceled():
break
# check if pixel is within threshold area
if lower_threshold <= threshold_data[ix] <= upper_threshold:
# check if pixel is already fitted
if self.ui.overwrite_check_box.isChecked() or \
numpy.sum(existing_fit_functions[ix, :]) == 0:
# load spectrum
spectrum = self._map.get_spectrum(pixel=[ix])
# get parameters from neighbours
if self.ui.neighbour_check_box.isChecked():
# define order in which to look for neighbours
neighbours = [[ix-1], [ix+1]]
# counter for suitable neighbours
n_neighbours = 0
# averaged neighbour parameters
parameters_neighbours = numpy.zeros(n_parameters)
# iterate neighbour orders: check first closest neighbours, then second closest neighbours ..
for i_neighbour in range(len(neighbours)):
# check if potential neighbour is on map
if neighbours[i_neighbour][0] < 0 or neighbours[i_neighbour][0] >= self._map.get_size()[0]:
break
# get fit functions from neighbour
fit_functions_neighbour = self._map.get_fit_functions(pixel=neighbours[i_neighbour])
# check if fit functions are the same as the current ones
if (fit_functions == fit_functions_neighbour).all():
# get parameters at neighbour pixel
parameters_neighbour = self._map.get_fit_parameters(pixel=neighbours[i_neighbour])
j_parameter = 0
for neighbour_peak in range(6):
if 1 <= fit_functions_neighbour[neighbour_peak] <= 2:
parameters_neighbours[j_parameter:j_parameter+3] += parameters_neighbour[neighbour_peak, 0:3]
j_parameter += 3
elif fit_functions_neighbour[neighbour_peak] == 3:
parameters_neighbours[j_parameter:j_parameter+4] += parameters_neighbour[neighbour_peak, 0:4]
j_parameter += 4
n_neighbours += 1
# if a neighbour was found, take the neighbour parameters, otherwise initial parameters
if n_neighbours > 0:
parameters_neighbours /= n_neighbours
start_parameters = parameters_neighbours
else:
start_parameters = fit_initial_parameters
# if neighbour function is not checked
else:
start_parameters = fit_initial_parameters
# perform fit
try:
fit_optimized_parameters, covariance = curve_fit(
fit_function,
spectrum[self.ui.lower_limit_slider.value():self.ui.upper_limit_slider.value(), 0],
spectrum[self.ui.lower_limit_slider.value():self.ui.upper_limit_slider.value(), 1],
p0=start_parameters, bounds=(fit_lower_boundaries, fit_upper_boundaries))
# check if this is the currently focused pixel
if ix == self._map.get_focus()[0]:
# save fit
self._map.set_fit(fit_functions, start_parameters, fit_optimized_parameters,
pixel=[ix], emit=True)
else:
# save fit
self._map.set_fit(fit_functions, start_parameters, fit_optimized_parameters,
pixel=[ix], emit=False)
except RuntimeError:
message_box = QMessageBox(self._app.windows['fittingWindow'])
message_box.setIcon(QMessageBox.Information)
message_box.setWindowTitle('Fitting failed!')
message_box.setText('Fitting failed for pixel ('+str(ix)+')')
message_box.addButton('Continue Fitting', QMessageBox.AcceptRole)
message_box.addButton('Stop Fitting', QMessageBox.AcceptRole)
message_box.exec_()
if message_box.result() == 1:
progress_dialog.close()
return
# process events
self._app.processEvents()
# update progress bar
i_px += 1
progress_dialog.setValue(i_px)
# stop live plotting
self._app.stop_live_plotting()
def cb_function_selected(self, index):
# get the peak number of the changed function
i_peak = int(self.sender().objectName()[-1])
# check which function has been selected and update the table flags accordingly
if index == 0:
# peak has been turned off
for i_row in range(1, 5):
self.ui.table_widget.item(i_peak, i_row).setFlags(Qt.NoItemFlags)
elif index == 1:
# gaussian has been selected
for i_row in range(1, 4):
self.ui.table_widget.item(i_peak, i_row).setFlags(
Qt.ItemIsSelectable | Qt.ItemIsEnabled | Qt.ItemIsEditable)
self.ui.table_widget.item(i_peak, 4).setFlags(Qt.NoItemFlags)
elif index == 2:
# lorentzian has been selected
for i_row in range(1, 3):
self.ui.table_widget.item(i_peak, i_row).setFlags(
Qt.ItemIsSelectable | Qt.ItemIsEnabled | Qt.ItemIsEditable)
self.ui.table_widget.item(i_peak, 3).setFlags(Qt.NoItemFlags)
self.ui.table_widget.item(i_peak, 4).setFlags(
Qt.ItemIsSelectable | Qt.ItemIsEnabled | Qt.ItemIsEditable)
elif index == 3:
# voigt has been selected
for i_row in range(1, 5):
self.ui.table_widget.item(i_peak, i_row).setFlags(
Qt.ItemIsSelectable | Qt.ItemIsEnabled | Qt.ItemIsEditable)
def cb_limit_slider_moved(self):
# update cursor on the spectrum canvas
self._app.windows['spectrumWindow'].get_current_widget().update_cursors(self.ui.lower_limit_slider.value(),
self.ui.upper_limit_slider.value())
def cb_limit_slider_pressed(self):
# create cursor on the spectrum canvas
self._app.windows['spectrumWindow'].get_current_widget().create_cursors(self.ui.lower_limit_slider.value(),
self.ui.upper_limit_slider.value())
def cb_limit_slider_released(self):
# remove cursor from the spectrum canvas
self._app.windows['spectrumWindow'].get_current_widget().destroy_cursors()
# bring window to front
self.show()
self.setWindowState(self.windowState() & ~Qt.WindowMinimized | Qt.WindowActive)
self.activateWindow()
def cb_radio_button_buttons(self):
# check which radio button is clicked
if self.ui.focused_pixel_radio_button.isChecked():
self.ui.threshold_type_combo.setEnabled(False)
self.ui.lower_threshold_slider.setEnabled(False)
self.ui.upper_threshold_slider.setEnabled(False)
self.ui.area_slider_x1.setEnabled(False)
self.ui.area_slider_x2.setEnabled(False)
self.ui.area_slider_y1.setEnabled(False)
self.ui.area_slider_y2.setEnabled(False)
self.ui.overwrite_check_box.setEnabled(False)
self.ui.neighbour_check_box.setEnabled(False)
elif self.ui.multiple_pixels_radio_button.isChecked():
self.ui.threshold_type_combo.setEnabled(True)
self.ui.lower_threshold_slider.setEnabled(True)
self.ui.upper_threshold_slider.setEnabled(True)
self.ui.area_slider_x1.setEnabled(True)
self.ui.area_slider_x2.setEnabled(True)
if self._map.get_dimension() == 2:
self.ui.area_slider_y1.setEnabled(True)
self.ui.area_slider_y2.setEnabled(True)
self.ui.overwrite_check_box.setEnabled(True)
self.ui.neighbour_check_box.setEnabled(True)
def cb_threshold_slider_moved(self):
# get threshold data and calculate threshold value
data = self._map.get_data(data_index=self.ui.threshold_type_combo.currentIndex())
min_data = numpy.min(data)
max_data = numpy.max(data)
lower_threshold = min_data+1./10000.*self.ui.lower_threshold_slider.value()*(max_data-min_data)
upper_threshold = min_data+1./10000.*self.ui.upper_threshold_slider.value()*(max_data-min_data)
# update threshold map on map canvas
self._app.windows['mapWindow'].ui.tab_widget.currentWidget().update_threshold_map(
data, [lower_threshold, upper_threshold])
# update tool tip for the threshold value
if self.sender() == self.ui.lower_threshold_slider:
QToolTip.showText(QCursor.pos(), str(lower_threshold), self.ui.lower_threshold_slider)
else:
QToolTip.showText(QCursor.pos(), str(upper_threshold), self.ui.upper_threshold_slider)
def cb_threshold_slider_pressed(self):
# get threshold data and calculate threshold value
data = self._map.get_data(data_index=self.ui.threshold_type_combo.currentIndex())
min_data = numpy.min(data)
max_data = numpy.max(data)
lower_threshold = min_data+1./10000.*self.ui.lower_threshold_slider.value()*(max_data-min_data)
upper_threshold = min_data+1./10000.*self.ui.upper_threshold_slider.value()*(max_data-min_data)
# create threshold map on map canvas
self._app.windows['mapWindow'].ui.tab_widget.currentWidget().create_threshold_map(
data, [lower_threshold, upper_threshold])
# create tool tip for the threshold value
if self.sender() == self.ui.lower_threshold_slider:
QToolTip.showText(QCursor.pos(), str(lower_threshold), self.ui.lower_threshold_slider)
else:
QToolTip.showText(QCursor.pos(), str(upper_threshold), self.ui.upper_threshold_slider)
def cb_threshold_slider_released(self):
# destroy threshold map from the map canvas
self._app.windows['mapWindow'].ui.tab_widget.currentWidget().destroy_threshold_map()
# bring window to front
self.setWindowState(self.windowState() & ~Qt.WindowMinimized | Qt.WindowActive)
self.activateWindow()
class FittingWindow(QMainWindow):
"""
FittingWindow
The fitting window hosts a fitting widget for each loaded map.
"""
def __init__(self, parent=None):
# call widget init
QWidget.__init__(self, parent)
# link app
self._app = QApplication.instance()
# dictionary for fitting widgets
self._fitting_widgets = {}
# set fixed size
self.setFixedWidth(350)
self.setFixedHeight(600)
# set window title
self.setWindowTitle("Fitting")
def add_widget(self, map_id):
# get map handle
map_handle = self._app.maps.get_map(map_id)
# add a widget to the widgets list
self._fitting_widgets[map_handle.get_id()] = FittingWidget(self, map_handle)
def change_widget(self, map_id):
# get map handle
map_handle = self._app.maps.get_map(map_id)
# hide all widgets
for key in self._fitting_widgets.keys():
self._fitting_widgets[key].setVisible(False)
# make the widget for the select map visible
self._fitting_widgets[map_handle.get_id()].setVisible(True)
def remove_widget(self, map_id):
# remove the widget of the deleted map
self._fitting_widgets[map_id].setParent(None)
self._fitting_widgets[map_id].deleteLater()
del self._fitting_widgets[map_id]
# close the window if there are no more maps
if len(self._fitting_widgets) == 0:
self.close()