def update_dict_profile_to_fit(self):
[left_range, right_range] = self.bragg_edge_range
o_selection = BraggEdgeSelectionTab(parent=self)
[x0, y0, x1, y1] = o_selection.get_shrinking_roi_dimension()
o_get = Get(parent=self)
profile = o_get.profile_of_roi(x0=x0, y0=y0,
x1=x1, y1=y1)
yaxis = profile[left_range: right_range]
all_x_axis = o_get.all_x_axis()
index_array = all_x_axis['index'][0]
tof_array = all_x_axis['tof'][0]
lambda_array = all_x_axis['lambda'][0]
index_selected = index_array[left_range: right_range]
tof_selected = tof_array[left_range: right_range]
lambda_selected = lambda_array[left_range: right_range]
profile_to_fit = {'yaxis': yaxis,
'xaxis': {'index': index_selected,
'tof': tof_selected,
'lambda': lambda_selected},
}
self.dict_profile_to_fit = profile_to_fit
def configuration(self):
# bring file dialog to locate where the file will be saved
base_folder = Path(self.parent.working_dir)
directory = str(base_folder.parent)
_export_folder = QFileDialog.getExistingDirectory(
self.parent,
directory=directory,
caption="Select Output Folder",
options=QFileDialog.ShowDirsOnly)
if _export_folder:
data, metadata = self.get_data_metadata_from_selection_tab()
# collect initial selection size (x0, y0, width, height)
o_get = Get(parent=self.parent)
[x0, y0, x1, y1, width, height] = o_get.selection_roi_dimension()
name_of_ascii_file = ExportHandler.makeup_name_of_profile_ascii_file(
base_name=str(base_folder.name),
export_folder=_export_folder,
x0=x0,
y0=y0,
width=width,
height=height)
make_ascii_file(metadata=metadata,
data=data,
output_file_name=name_of_ascii_file,
dim='1d')
self.parent.ui.statusbar.showMessage(
"{} has been created!".format(name_of_ascii_file),
10000) # 10s
self.parent.ui.statusbar.setStyleSheet("color: green")
def update_roi_labels(self):
[global_left_range, global_right_range] = self.parent.bragg_edge_range
[left_range, right_range] = list(self.parent.fitting_peak_ui.getRegion())
o_get = Get(parent=self.parent)
x_axis_selected = o_get.x_axis_checked()
xaxis_dict = self.parent.fitting_input_dictionary['xaxis']
xaxis_index, _ = xaxis_dict[x_axis_selected]
[left_xaxis_index, right_xaxis_index] = [global_left_range, global_right_range]
xaxis = xaxis_index[left_xaxis_index: right_xaxis_index]
left_index = find_nearest_index(array=xaxis, value=left_range)
right_index = find_nearest_index(array=xaxis, value=right_range)
xaxis_in_selected_axis = self.parent.fitting_input_dictionary['xaxis'][x_axis_selected][0][
global_left_range: global_right_range]
real_left_value = xaxis_in_selected_axis[left_index]
real_right_value = xaxis_in_selected_axis[right_index]
if x_axis_selected == 'lambda':
str_format = "{:02f}"
elif x_axis_selected == 'tof':
str_format = "{:04.2f}"
else:
str_format = "{}"
real_left_value = str_format.format(real_left_value)
real_right_value = str_format.format(real_right_value)
units = Get.units(name=x_axis_selected)
self.parent.ui.bragg_peak_range_from_value.setText(str(real_left_value))
self.parent.ui.bragg_peak_range_to_value.setText(str(real_right_value))
self.parent.ui.from_bragg_peak_range_units.setText(units)
self.parent.ui.to_bragg_peak_range_units.setText(units)
def update_selection_plot(self):
self.parent.ui.profile.clear()
o_get = Get(parent=self.parent)
x_axis, x_axis_label = o_get.x_axis()
max_value = self.parent.ui.profile_of_bin_size_slider.maximum()
roi_selected = max_value - self.parent.ui.profile_of_bin_size_slider.value(
)
y_axis = self.parent.fitting_input_dictionary['rois'][roi_selected][
'profile']
self.parent.ui.profile.plot(x_axis,
y_axis,
pen=(self.parent.shrinking_roi_rgb[0],
self.parent.shrinking_roi_rgb[1],
self.parent.shrinking_roi_rgb[2]))
self.parent.ui.profile.setLabel("bottom", x_axis_label)
self.parent.ui.profile.setLabel("left", 'Mean transmission')
# full region
y_axis = self.parent.fitting_input_dictionary['rois'][0]['profile']
self.parent.ui.profile.plot(x_axis,
y_axis,
pen=(self.parent.selection_roi_rgb[0],
self.parent.selection_roi_rgb[1],
self.parent.selection_roi_rgb[2]))
def bragg_edge_range_changed(self):
[left_range, right_range] = list(self.bragg_edge_range_ui.getRegion())
o_get = Get(parent=self)
x_axis, _ = o_get.x_axis()
left_index = find_nearest_index(array=x_axis, value=left_range)
right_index = find_nearest_index(array=x_axis, value=right_range)
self.bragg_edge_range = [left_index, right_index]
def add_profile_to_dict_of_all_regions(self, dict_regions=None):
for _key in dict_regions.keys():
current_region = dict_regions[_key]
x0 = current_region['x0']
y0 = current_region['y0']
width = current_region['width']
height = current_region['height']
o_get = Get(parent=self)
profile = o_get.profile_of_roi(x0=x0, y0=y0,
x1=x0 + width,
y1=y0 + height)
current_region['profile'] = profile
def update_vertical_line_in_profile_plot(self):
o_get = Get(parent=self)
x_axis, x_axis_label = o_get.x_axis()
bragg_edge_range = [x_axis[self.bragg_edge_range[0]],
x_axis[self.bragg_edge_range[1]]]
if self.bragg_edge_range_ui:
self.ui.profile.removeItem(self.bragg_edge_range_ui)
self.bragg_edge_range_ui = pg.LinearRegionItem(values=bragg_edge_range,
orientation=None,
brush=None,
movable=True,
bounds=None)
self.bragg_edge_range_ui.sigRegionChanged.connect(self.bragg_edge_range_changed)
self.bragg_edge_range_ui.setZValue(-10)
self.ui.profile.addItem(self.bragg_edge_range_ui)
def get_data_metadata_from_selection_tab(self):
base_folder = Path(self.parent.working_dir)
o_get = Get(parent=self.parent)
index_axis, _ = o_get.specified_x_axis(xaxis='index')
tof_axis, _ = o_get.specified_x_axis(xaxis='tof')
lambda_axis, _ = o_get.specified_x_axis('lambda')
fitting_peak_range = self.parent.bragg_edge_range
distance_detector_sample = str(
self.parent.ui.distance_detector_sample.text())
detector_offset = str(self.parent.ui.detector_offset.text())
kropff_fitting_values = self.collect_all_kropff_fitting_values()
march_dollase_fitting_values = self.collect_all_march_dollase_fitting_values(
)
dict_regions = o_get.all_russian_doll_region_full_infos()
metadata = ExportHandler.make_metadata(
base_folder=base_folder,
fitting_peak_range=fitting_peak_range,
dict_regions=dict_regions,
distance_detector_sample=distance_detector_sample,
detector_offset=detector_offset,
kropff_fitting_values=kropff_fitting_values,
march_dollase_fitting_values=march_dollase_fitting_values)
self.add_fitting_infos_to_metadata(metadata)
metadata.append("#")
metadata.append(
"#File Index, TOF(micros), lambda(Angstroms), ROIs (see above)")
data = ExportHandler.format_data(col1=index_axis,
col2=tof_axis,
col3=lambda_axis,
dict_regions=dict_regions)
return data, metadata
def fit_that_selection_pushed_by_program(self, initialize_region=True):
o_get = Get(parent=self)
x_axis = o_get.all_x_axis()
dict_regions = o_get.all_russian_doll_region_full_infos()
o_init = PeakFittingInitialization(parent=self)
fitting_input_dictionary = o_init.fitting_input_dictionary(nbr_rois=len(dict_regions))
o_init.set_top_keys_values(fitting_input_dictionary,
{'xaxis': x_axis,
'bragg_edge_range': self.bragg_edge_range})
self.append_dict_regions_to_fitting_input_dictionary(dict_regions, fitting_input_dictionary)
# fitting_input_dictionary['xaxis'] = x_axis
# fitting_input_dictionary['bragg_edge_range'] = self.bragg_edge_range
self.fitting_input_dictionary = fitting_input_dictionary
o_kropff = Kropff(parent=self)
o_kropff.reset_all_table()
o_march = MarchDollase(parent=self)
o_march.reset_table()
if initialize_region:
self.initialize_default_peak_regions()
else:
if self.fitting_procedure_started['kropff']:
o_kropff.fill_table_with_fitting_information()
o_march.fill_tables_with_fitting_information()
if initialize_region:
o_march_fitting = MarchDollaseFittingJobHandler(parent=self)
o_march_fitting.initialize_fitting_input_dictionary()
self.ui.tabWidget.setTabEnabled(1, True)
self.ui.actionExport.setEnabled(True)
self.select_first_row_of_all_fitting_table()
def update_selection_profile_plot(self):
if self.parent.is_file_imported:
self.update_selection_plot()
self.parent.update_vertical_line_in_profile_plot()
else:
o_get = Get(parent=self.parent)
x_axis, x_axis_label = o_get.x_axis()
self.parent.ui.profile.clear()
# large selection region
[x0, y0, x1, y1, _, _] = o_get.selection_roi_dimension()
profile = o_get.profile_of_roi(x0, y0, x1, y1)
x_axis, y_axis = check_size(x_axis=x_axis, y_axis=profile)
self.parent.ui.profile.plot(x_axis,
y_axis,
pen=(self.parent.selection_roi_rgb[0],
self.parent.selection_roi_rgb[1],
self.parent.selection_roi_rgb[2]))
# shrinkable region
shrinking_roi = self.get_coordinates_of_new_inside_selection_box()
x0 = shrinking_roi['x0']
y0 = shrinking_roi['y0']
x1 = shrinking_roi['x1']
y1 = shrinking_roi['y1']
profile = o_get.profile_of_roi(x0, y0, x1, y1)
x_axis, y_axis = check_size(x_axis=x_axis, y_axis=profile)
self.parent.ui.profile.plot(x_axis,
y_axis,
pen=(self.parent.shrinking_roi_rgb[0],
self.parent.shrinking_roi_rgb[1],
self.parent.shrinking_roi_rgb[2]))
self.parent.ui.profile.setLabel("bottom", x_axis_label)
self.parent.ui.profile.setLabel("left", 'Mean transmission')
# vertical line showing peak to fit
bragg_edge_range = [
x_axis[self.parent.bragg_edge_range[0]],
x_axis[self.parent.bragg_edge_range[1]]
]
self.parent.bragg_edge_range_ui = pg.LinearRegionItem(
values=bragg_edge_range,
orientation=None,
brush=None,
movable=True,
bounds=None)
self.parent.bragg_edge_range_ui.sigRegionChanged.connect(
self.parent.bragg_edge_range_changed)
self.parent.bragg_edge_range_ui.setZValue(-10)
self.parent.ui.profile.addItem(self.parent.bragg_edge_range_ui)
def update_fitting_plot(self):
self.parent.ui.fitting.clear()
if self.parent.fitting_peak_ui:
self.parent.ui.fitting.removeItem(self.parent.fitting_peak_ui)
o_get = Get(parent=self.parent)
xaxis_checked = o_get.x_axis_checked()
xaxis = o_get.x_axis_data(x_axis_selected=xaxis_checked)
xaxis_label = o_get.x_axis_label(x_axis_selected=xaxis_checked)
o_table = TableHandler(
table_ui=self.parent.ui.march_dollase_result_table)
list_row_selected = o_table.get_rows_of_table_selected()
if list_row_selected is None:
return
for row_selected in list_row_selected:
yaxis = o_get.y_axis_data_of_selected_row(
row_selected=row_selected)
self.parent.ui.fitting.plot(xaxis,
yaxis,
pen=(self.parent.selection_roi_rgb[0],
self.parent.selection_roi_rgb[1],
self.parent.selection_roi_rgb[2]),
symbol='o')
self.parent.ui.fitting.setLabel("bottom", xaxis_label)
self.parent.ui.fitting.setLabel("left", "Average transmission")
if self.parent.ui.march_dollase_toolBox.currentIndex() == 0:
move_bragg_peak_range = True
else:
move_bragg_peak_range = False
peak_range = self.parent.march_dollase_fitting_range_selected
local_peak_range = [xaxis[peak_range[0]], xaxis[peak_range[1]]]
if self.parent.march_dollase_fitting_peak_ui:
self.parent.ui.fitting.removeItem(
self.parent.march_dollase_fitting_peak_ui)
self.parent.march_dollase_fitting_peak_ui = pg.LinearRegionItem(
values=local_peak_range,
orientation=None,
brush=None,
movable=move_bragg_peak_range,
bounds=None)
self.parent.march_dollase_fitting_peak_ui.sigRegionChanged.connect(
self.parent.march_dollase_fitting_range_changed)
self.parent.march_dollase_fitting_peak_ui.setZValue(-10)
self.parent.ui.fitting.addItem(
self.parent.march_dollase_fitting_peak_ui)
def update_fitting_plot(self):
self.parent.ui.fitting.clear()
o_get = Get(parent=self.parent)
part_of_fitting_dict = o_get.part_of_fitting_selected()
name_of_page = part_of_fitting_dict['name_of_page']
table_ui = part_of_fitting_dict['table_ui']
o_table = TableHandler(table_ui=table_ui)
list_row_selected = o_table.get_rows_of_table_selected()
x_axis_selected = o_get.x_axis_checked()
if list_row_selected is None:
# first fitting tab where we only display the full data with bragg peak selection
if self.parent.fitting_peak_ui:
self.parent.ui.fitting.removeItem(self.parent.fitting_peak_ui)
xaxis_dict = self.parent.fitting_input_dictionary['xaxis']
xaxis_index, xaxis_label = xaxis_dict[x_axis_selected]
[left_xaxis_index, right_xaxis_index] = self.parent.bragg_edge_range
xaxis = xaxis_index[left_xaxis_index: right_xaxis_index]
selected_roi = self.parent.fitting_input_dictionary['rois'][0]
yaxis = selected_roi['profile']
yaxis = yaxis[left_xaxis_index: right_xaxis_index]
yaxis = -np.log(yaxis)
self.parent.ui.fitting.plot(xaxis, yaxis,
pen=(self.parent.selection_roi_rgb[0],
self.parent.selection_roi_rgb[1],
self.parent.selection_roi_rgb[2]),
symbol='o')
self.parent.ui.fitting.setLabel("bottom", xaxis_label)
peak_range_index = self.parent.kropff_fitting_range['bragg_peak']
if peak_range_index[0] is None:
peak_range = self.parent.bragg_edge_range
else:
peak_range = [xaxis[peak_range_index[0]], xaxis[peak_range_index[1]]]
if self.parent.fitting_peak_ui:
self.parent.ui.fitting.removeItem(self.parent.fitting_peak_ui)
self.parent.fitting_peak_ui = pg.LinearRegionItem(values=peak_range,
orientation=None,
brush=None,
movable=True,
bounds=None)
self.parent.fitting_peak_ui.sigRegionChanged.connect(self.parent.fitting_range_changed)
self.parent.fitting_peak_ui.setZValue(-10)
self.parent.ui.fitting.addItem(self.parent.fitting_peak_ui)
else:
for row_selected in list_row_selected:
selected_roi = self.parent.fitting_input_dictionary['rois'][row_selected]
xaxis_dict = self.parent.fitting_input_dictionary['xaxis']
[left_xaxis_index, right_xaxis_index] = self.parent.bragg_edge_range
yaxis = selected_roi['profile']
xaxis_index, xaxis_label = xaxis_dict[x_axis_selected]
xaxis = xaxis_index[left_xaxis_index: right_xaxis_index]
yaxis = yaxis[left_xaxis_index: right_xaxis_index]
self.parent.ui.fitting.setLabel("bottom", xaxis_label)
self.parent.ui.fitting.setLabel("left", 'Cross Section (arbitrary units)')
yaxis = -np.log(yaxis)
self.parent.ui.fitting.plot(xaxis, yaxis,
pen=(self.parent.selection_roi_rgb[0],
self.parent.selection_roi_rgb[1],
self.parent.selection_roi_rgb[2]),
symbol='o')
peak_range_index = self.parent.kropff_fitting_range[name_of_page]
if peak_range_index[0] is None:
peak_range = self.parent.bragg_edge_range
else:
peak_range = [xaxis[peak_range_index[0]], xaxis[peak_range_index[1]]]
if self.parent.fitting_peak_ui:
self.parent.ui.fitting.removeItem(self.parent.fitting_peak_ui)
self.parent.fitting_peak_ui = pg.LinearRegionItem(values=peak_range,
orientation=None,
brush=None,
movable=False,
bounds=None)
self.parent.fitting_peak_ui.sigRegionChanged.connect(self.parent.fitting_range_changed)
self.parent.fitting_peak_ui.setZValue(-10)
self.parent.ui.fitting.addItem(self.parent.fitting_peak_ui)
o_gui = GuiUtility(parent=self.parent)
algo_name = o_gui.get_tab_selected(self.parent.ui.tab_algorithm).lower()
if key_path_exists_in_dictionary(dictionary=self.parent.fitting_input_dictionary,
tree_key=['rois', row_selected, 'fitting', algo_name,
name_of_page, 'xaxis_to_fit']):
# show fit only if tof scale selected
if x_axis_selected == 'lambda':
_entry = self.parent.fitting_input_dictionary['rois'][row_selected]['fitting'][algo_name][name_of_page]
xaxis = _entry['xaxis_to_fit']
yaxis = _entry['yaxis_fitted']
yaxis = -np.log(yaxis)
self.parent.ui.fitting.plot(xaxis, yaxis,
pen=(self.parent.fit_rgb[0],
self.parent.fit_rgb[1],
self.parent.fit_rgb[2]))
if peak_range_index[0] is None:
self.parent.fitting_range_changed()
self.parent.ui.fitting.setLabel("left", "Cross Section (arbitrary Units)")
def export_data_of_selected_rows(self):
base_folder = Path(self.parent.working_dir)
directory = str(base_folder.parent)
_export_folder = QFileDialog.getExistingDirectory(
self.parent, directory=directory, caption="Select Output Folder")
if _export_folder:
o_table = TableHandler(
table_ui=self.parent.ui.march_dollase_result_table)
list_of_rows_selected = o_table.get_rows_of_table_selected()
str_list_of_rows_selected = [
str(_row) for _row in list_of_rows_selected
]
str_rows = "_".join(str_list_of_rows_selected)
output_file_name = os.path.join(
str(_export_folder),
"march_dollase_result_fitting_row{}.txt".format(str_rows))
fitting_input_dictionary = self.parent.fitting_input_dictionary
o_get = Get(parent=self.parent)
xaxis_index = o_get.x_axis_data(x_axis_selected='index')
xaxis_tof = o_get.x_axis_data(x_axis_selected='tof')
xaxis_lambda = o_get.x_axis_data(x_axis_selected='lambda')
# metadata
metadata = ["#Marche Dollase Result of Fitting"]
is_advance_mode = self.parent.ui.march_dollase_advanced_mode_checkBox.isChecked(
)
metadata.append(
"#Using advanced fitting mode: {}".format(is_advance_mode))
data_label = "#image index, TOF(micros), Lambda(Angstroms)"
temp_data = []
for _row in list_of_rows_selected:
_entry = fitting_input_dictionary['rois'][_row]['fitting'][
'march_dollase']
_top_entry = fitting_input_dictionary['rois'][_row]
_line = "#-> row {}: x0: {}, y0:{}, width:{}, height:{}, " \
"d_spacing:{}, sigma:{}, alpha:{}, a1:{}, " \
"a2:{}".format(_row,
_top_entry['x0'],
_top_entry['y0'],
_top_entry['width'],
_top_entry['height'],
_entry['d_spacing'],
_entry['sigma'],
_entry['alpha'],
_entry['a1'],
_entry['a2'])
if is_advance_mode:
_line += ", a5:{}, a6:{}".format(_entry['a5'],
_entry['a6'])
metadata.append(_line)
data_label += ", row {}".format(_row)
temp_data.append(
o_get.y_axis_data_of_selected_row(row_selected=_row))
metadata.append("#")
metadata.append(data_label)
# data
data = []
self.parent.debug_data = temp_data
for _index in np.arange(len(xaxis_index)):
str_data = "{}, {}, {}".format(xaxis_index[_index],
xaxis_tof[_index],
xaxis_lambda[_index])
for _col_index in np.arange(len(list_of_rows_selected)):
str_data += ", {}".format(temp_data[_col_index][_index])
data.append(str_data)
make_ascii_file(metadata=metadata,
data=data,
output_file_name=output_file_name,
dim='1d')
message = "{} has been created!".format(output_file_name)
self.parent.ui.statusbar.showMessage(message, 10000) # 10s
def prepare(self):
self.initialize_fitting_input_dictionary()
fitting_input_dictionary = self.parent.fitting_input_dictionary
march_dollase_fitting_history_table = self.parent.march_dollase_fitting_history_table
_is_advanced_mode = self.is_advanced_mode()
if _is_advanced_mode:
gmodel = Model(march_dollase_advanced_fit, missing='drop')
else:
# gmodel = Model(march_dollase_basic_fit, missing='drop')
gmodel = Model(march_dollase_basic_fit, nan_policy='propagate')
march_dollase_fitting_history_table = self.parent.march_dollase_fitting_history_table
nbr_row_in_fitting_scenario = len(march_dollase_fitting_history_table)
self.parent.ui.eventProgress.setValue(0)
nbr_roi_row = len(fitting_input_dictionary['rois'].keys())
self.parent.ui.eventProgress.setMaximum(nbr_roi_row)
self.parent.ui.eventProgress.setVisible(True)
def set_params(params_object, name_of_parameter, dict_entry,
parameter_flag):
params_object.add(name_of_parameter,
value=np.float(dict_entry[name_of_parameter]),
vary=parameter_flag)
def record_result_into_dict(entry_dict, result_object,
name_of_parameter, parameter_flag):
if parameter_flag:
print(f"-> name_of_parameter: {name_of_parameter}")
[value,
error] = result_object.get_value_err(tag=name_of_parameter)
entry_dict[name_of_parameter] = value
entry_dict[name_of_parameter + "_error"] = error
print(f" - value: {value}")
print(f" - error: {error}")
for _roi_row in np.arange(nbr_roi_row):
_entry = fitting_input_dictionary['rois'][_roi_row]['fitting'][
'march_dollase']
o_get = Get(parent=self.parent)
xaxis = o_get.x_axis_data(x_axis_selected='lambda')
yaxis = o_get.y_axis_data_of_selected_row(_roi_row)
for _history_row, _row_entry in enumerate(
march_dollase_fitting_history_table):
[
d_spacing_flag, sigma_flag, alpha_flag, a1_flag, a2_flag,
a5_flag, a6_flag
] = _row_entry
if _is_advanced_mode:
a5_flag = _entry['a5']
a6_flag = _entry['a6']
params = gmodel.make_params()
set_params(params, 'd_spacing', _entry, d_spacing_flag)
set_params(params, 'sigma', _entry, sigma_flag)
set_params(params, 'alpha', _entry, alpha_flag)
set_params(params, 'a1', _entry, a1_flag)
set_params(params, 'a2', _entry, a2_flag)
if _is_advanced_mode:
set_params(params, 'a5', _entry, a5_flag)
set_params(params, 'a6', _entry, a6_flag)
print("Parameters pre-initialized:")
if not d_spacing_flag:
print(f"- d_spacing: {_entry['d_spacing']}")
if not sigma_flag:
print(f"- sigma: {_entry['sigma']}")
if not alpha_flag:
print(f"- alpha: {_entry['alpha']}")
if not a1_flag:
print(f"- a1: {_entry['a1']}")
if not a2_flag:
print(f"- a2: {_entry['a2']}")
# try:
result = gmodel.fit(yaxis, params, t=xaxis)
# except ValueError:
# print(f"we are having an error row:{_roi_row}")
print(f"in _history_row: {_history_row}")
o_result = ResultValueError(result=result)
record_result_into_dict(_entry, o_result, 'd_spacing',
d_spacing_flag)
record_result_into_dict(_entry, o_result, 'sigma', sigma_flag)
record_result_into_dict(_entry, o_result, 'alpha', alpha_flag)
record_result_into_dict(_entry, o_result, 'a1', a1_flag)
record_result_into_dict(_entry, o_result, 'a2', a2_flag)
if _is_advanced_mode:
record_result_into_dict(_entry, o_result, 'a5', a5_flag)
record_result_into_dict(_entry, o_result, 'a6', a6_flag)
break # for debugging only (stop only after first row)
self.parent.ui.eventProgress.setValue(_roi_row + 1)
QApplication.processEvents()
self.parent.ui.eventProgress.setVisible(False)
self.parent.fitting_procedure_started['march-dollase'] = True