mantidimaging.gui.windows.spectrum_viewer.presenter module

class mantidimaging.gui.windows.spectrum_viewer.presenter.ExportMode(*values)

Bases: Enum

IMAGE_MODE = 1

ROI_MODE = 0

class mantidimaging.gui.windows.spectrum_viewer.presenter.SpectrumFitResult(params: dict[str, float], rss: float, rss_per_dof: float, status: Literal['Fitted', 'Failed'])

Bases: NamedTuple

Result of fitting single spectrum.

params: dict[str, float]

Alias for field number 0

rss: float

Alias for field number 1

rss_per_dof: float

Alias for field number 2

status: Literal['Fitted', 'Failed']

Alias for field number 3

class mantidimaging.gui.windows.spectrum_viewer.presenter.SpectrumViewerWindowPresenter(view: SpectrumViewerWindowView, main_window: MainWindowView)

Bases: BasePresenter

The presenter for the spectrum viewer window.

This presenter is responsible for handling user interaction with the view and updating the model and view accordingly to look after the state of the window.

add_rits_roi() → None

Add the RITS ROI to the spectrum widget and initialize it with default dimensions.

auto_find_flat_stack(new_dataset_id: UUID) → None

change_roi_colour(roi_name: str, new_colour: tuple[int, int, int, int]) → None

Change the colour of a given ROI in both the spectrum widget and the table.

@param roi_name: Name of the ROI to change color. @param new_colour: The new color for the ROI.

change_selected_menu_option(opt: str) → None

changed_roi: SpectrumROI

clear_spectrum() → None

compute_spectrum_fit(spectrum: ndarray, fitting_region: FittingRegion, tof_data: ndarray, init_params: list[float], bound_params: list[tuple[float | None, float | None]]) → SpectrumFitResult

Fit a single spectrum and return result, rss, rss_per_dof, and status.

Parameters

spectrum: The spectrum data to fit. fitting_region: The region of the spectrum to fit, defined as a tuple of (min, max) in the current ToF units. tof_data: The ToF data corresponding to the spectrum, used for determining the x-axis values for fitting. init_params: A dictionary of initial parameter guesses for the fitting function, keyed by parameter name. bound_params: A dictionary of parameter bounds for the fitting function, keyed by parameter name, where each

value is a tuple of (min_bound, max_bound).

Returns

SpectrumFitResult A named tuple containing: - params: A dictionary of fitted parameter values, keyed by parameter name. - rss: The residual sum of squares of the fit. - rss_per_dof: The residual sum of squares per degree of freedom of the fit. - status: A string indicating whether the fit was successful (“Fitted”) or failed (“Failed”).

current_norm_stack_uuid: UUID | None = None

current_stack_uuid: UUID | None = None

do_add_roi() → None

Add a new ROI to the spectrum

do_add_roi_to_table(roi_name: str) → None

Add a given ROI to the table by ROI name

@param roi_name: Name of the ROI to add

do_adjust_roi() → None

do_remove_roi(roi_name: str | None = None) → None

Remove a given ROI from the table by ROI name or all ROIs from the table if no name is passed as an argument

@param roi_name: Name of the ROI to remove

export_mode: ExportMode

fit_all_regions(progress: Progress) → list[tuple[str, SpectrumFitResult]]

Retrieves ROIs from get_rois_to_fit, computes a fit for each, and reports progress via the provided Progress object while supporting user cancellation.

Parameters

progress: Progress reporter used for updating the UI with the current progress and checking for cancellation.

Returns

list[tuple[str, SpectrumFitResult]]: A list of (ROI name, fit result) tuples for each processed ROI. If the operation is cancelled, only completed results are returned.

property fitting_spectrum: ndarray

get_dataset_id_for_stack(stack_id: UUID | None) → UUID | None

get_roi_names() → list[str]

@return: list of ROI names

get_rois_to_fit() → Iterator[tuple[str, SensibleROI]]

Get the ROIs to fit based on the current export mode. In ROI mode, yields user-defined ROIs from the spectrum widget. In Image mode, yields sub-ROIs defined by the current binner.

Yields

Iterator[tuple[str, SensibleROI]]: Tuples of (ROI name, ROI object) to be used for fitting.

handle_button_enabled() → None

Enable the export button if the current stack is not None and normalisation is valid

handle_enable_normalised(enabled: bool) → None

handle_experiment_setup_properties_change() → None

handle_export_csv() → None

handle_export_tab_change(index: int) → None

handle_export_table() → None

Export the ROI fitting results table to CSV.

handle_normalise_stack_change(normalise_uuid: UUID | None) → None

handle_notify_roi_moved(roi: SpectrumROI) → None

handle_open_beam_roi_choice_changed() → None

handle_range_slide_moved(tof_range: tuple[float, float] | tuple[int, int]) → None

handle_rits_export() → None

Handle the export of the current spectrum to a RITS file format

handle_roi_clicked(roi: SpectrumROI) → None

handle_roi_moved() → None

Handle changes to any ROI position and size.

handle_roi_name_change(old_name: str, new_name: str) → None

handle_sample_change(uuid: UUID | None) → None

Called when the stack has been changed in the stack selector.

handle_stack_modified() → None

Called when an image stack is modified somewhere else in MI, for example in the operations window

handle_tof_unit_change() → None

handle_tof_unit_change_via_menu(unit_name: str) → None

image_nan_mask_dict: dict[str, np.ma.MaskedArray] = {}

initial_roi_calc() → None

model: SpectrumViewerWindowModel

on_fit_all_regions(task: TaskWorkerThread) → None

Callback executed when the asynchronous fitting task completes. Handles errors, retrieves results, and updates the export table.

Parameters

task : The completed task containing either results or an error.

redraw_all_rois() → None

Redraw all ROIs and spectrum plots

redraw_spectrum(name: str) → None

Redraw the spectrum with the given name

refresh_spectrum_plot() → None

reset_units_menu() → None

roi_to_process_queue: dict[str, SpectrumROI] = {}

run_spectrum_calculation(roi: SpectrumROI, open_beam_roi: SensibleROI | None, spec_mode: SpecType, shutter_norm: bool, chunk_start: int, chunk_end: int) → np.ndarray

set_shuttercount_error(enabled: bool = False) → None

Set ShutterCount error message when a valid normalisation stack has been selected and shuttercount correction has been toggled on and redraw all ROIs to ensure the spectrum is updated when ShutterCount correction is toggled between enabled and disabled states.

show_new_sample() → None

Show the new sample in the view and update the spectrum and image view accordingly. Resets the ROIs.

spectrum_calculation_setup() → tuple[int, int]

spectrum_mode: SpecType = 1

thread_cleanup(thread: TaskWorkerThread) → None

thread_finished_processing(thread: TaskWorkerThread) → None

try_next_mean_chunk() → None

update_displayed_image(autoLevels: bool = True) → None

Fetches the correct image (normalized or not) and updates the display.

update_unit_labels_and_menus() → None

Update all unit-related axis and range labels, as well as unit selection menus in both the main spectrum plot in the image tab and the fitting tab.

view: SpectrumViewerWindowView