Source code for

# Copyright (C) 2024 ISIS Rutherford Appleton Laboratory UKRI
# SPDX - License - Identifier: GPL-3.0-or-later
from __future__ import annotations

from pathlib import Path
from typing import TYPE_CHECKING
from import Callable
from logging import getLogger
import numpy as np

from imagecodecs._deflate import DeflateError
from tifffile import tifffile, TiffFileError
from import fits

from mantidimaging.gui.mvp_base import BasePresenter
from import LiveViewerWindowModel, Image_Data
from mantidimaging.core.operations.loader import load_filter_packages
from import ImageStack

    from import LiveViewerWindowView  # pragma: no cover
    from import MainWindowView  # pragma: no cover

logger = getLogger(__name__)

[docs] class LiveViewerWindowPresenter(BasePresenter): """ The presenter for the Live 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. """ view: LiveViewerWindowView model: LiveViewerWindowModel op_func: Callable def __init__(self, view: LiveViewerWindowView, main_window: MainWindowView): super().__init__(view) self.view = view self.main_window = main_window self.model = LiveViewerWindowModel(self) self.selected_image: Image_Data | None = None self.filters = {f.filter_name: f for f in load_filter_packages()}
[docs] def close(self) -> None: """Close the window.""" self.model.close() self.model = None # type: ignore # Presenter instance to be destroyed -type can be inconsistent self.view = None # type: ignore # Presenter instance to be destroyed -type can be inconsistent
[docs] def set_dataset_path(self, path: Path) -> None: """Set the path to the dataset.""" self.model.path = path
[docs] def clear_label(self) -> None: """Clear the label.""" self.view.label_active_filename.setText("")
[docs] def handle_deleted(self) -> None: """Handle the deletion of the image.""" self.view.remove_image() self.clear_label() self.view.live_viewer.z_slider.set_range(0, 1) self.view.live_viewer.show_error(None)
[docs] def update_image_list(self, images_list: list[Image_Data]) -> None: """Update the image in the view.""" if not images_list: self.handle_deleted() return self.view.set_image_range((0, len(images_list) - 1)) self.view.set_image_index(len(images_list) - 1)
[docs] def select_image(self, index: int) -> None: if not self.model.images: return self.selected_image = self.model.images[index] self.view.label_active_filename.setText(self.selected_image.image_name) self.display_image(self.selected_image.image_path)
[docs] def display_image(self, image_path: Path): """ Display image in the view after validating contents """ try: image_data = self.load_image(image_path) except (OSError, KeyError, ValueError, TiffFileError, DeflateError) as error: message = f"{type(error).__name__} reading image: {image_path}: {error}" logger.error(message) self.view.remove_image() self.view.live_viewer.show_error(message) return image_data = self.perform_operations(image_data) if image_data.size == 0: message = "reading image: {image_path}: Image has zero size" logger.error("reading image: %s: Image has zero size", image_path) self.view.remove_image() self.view.live_viewer.show_error(message) return self.view.show_most_recent_image(image_data) self.view.live_viewer.show_error(None)
[docs] @staticmethod def load_image(image_path: Path) -> np.ndarray: """ Load a .Tif, .Tiff or .Fits file only if it exists and returns as an ndarray """ if image_path.suffix.lower() in [".tif", ".tiff"]: with tifffile.TiffFile(image_path) as tif: image_data = tif.asarray() elif image_path.suffix.lower() == ".fits": with as fit: image_data = fit[0].data return image_data
[docs] def update_image_modified(self, image_path: Path): """ Update the displayed image when the file is modified """ if self.selected_image and image_path == self.selected_image.image_path: self.display_image(image_path)
[docs] def update_image_operation(self): """ Reload the current image if an operation has been performed on the current image """ self.display_image(self.selected_image.image_path)
[docs] def convert_image_to_imagestack(self, image_data): """ Convert the single image to an imagestack so the Operations framework can be used """ image_data_shape = image_data.shape image_data_temp = np.zeros(shape=(1, image_data_shape[0], image_data_shape[1])) image_data_temp[0] = image_data return ImageStack(image_data_temp)
[docs] def perform_operations(self, image_data): if not self.view.filter_params: return image_data image_stack = self.convert_image_to_imagestack(image_data) for operation in self.view.filter_params: op_class = self.filters[operation] op_func = op_class.filter_func op_params = self.view.filter_params[operation]["params"] op_func(image_stack, **op_params) return image_stack.slice_as_array(0)[0]