Source code for mantidimaging.gui.windows.spectrum_viewer.view

# Copyright (C) 2022 ISIS Rutherford Appleton Laboratory UKRI
# SPDX - License - Identifier: GPL-3.0-or-later
from pathlib import Path
from typing import TYPE_CHECKING, Optional

from PyQt5.QtGui import QPixmap
from PyQt5.QtWidgets import QCheckBox, QVBoxLayout, QFileDialog, QPushButton, QLabel

from mantidimaging.core.utility import finder
from mantidimaging.gui.mvp_base import BaseMainWindowView
from mantidimaging.gui.widgets.dataset_selector import DatasetSelectorWidgetView
from .presenter import SpectrumViewerWindowPresenter
from .spectrum_widget import SpectrumWidget

if TYPE_CHECKING:
    from mantidimaging.gui.windows.main import MainWindowView  # noqa:F401  # pragma: no cover
    from uuid import UUID
    import numpy as np



[docs]
class SpectrumViewerWindowView(BaseMainWindowView):
    sampleStackSelector: DatasetSelectorWidgetView
    normaliseStackSelector: DatasetSelectorWidgetView

    normaliseCheckBox: QCheckBox
    imageLayout: QVBoxLayout
    exportButton: QPushButton
    normaliseErrorIcon: QLabel
    _current_dataset_id: Optional['UUID']
    normalise_error_issue: str = ""

    def __init__(self, main_window: 'MainWindowView'):
        super().__init__(main_window, 'gui/ui/spectrum_viewer.ui')

        self.main_window = main_window

        icon_path = finder.ROOT_PATH + "/gui/ui/images/exclamation-triangle-red.png"
        self.normalise_error_icon_pixmap = QPixmap(icon_path)

        self.presenter = SpectrumViewerWindowPresenter(self, main_window)

        self.spectrum = SpectrumWidget(self)
        self.imageLayout.addWidget(self.spectrum)

        self.spectrum.range_changed.connect(self.presenter.handle_range_slide_moved)
        self.spectrum.roi_changed.connect(self.presenter.handle_roi_moved)

        self._current_dataset_id = None
        self.sampleStackSelector.stack_selected_uuid.connect(self.presenter.handle_sample_change)
        self.normaliseStackSelector.stack_selected_uuid.connect(self.presenter.handle_normalise_stack_change)
        self.normaliseCheckBox.stateChanged.connect(self.set_normalise_dropdown_state)
        self.normaliseCheckBox.stateChanged.connect(self.presenter.handle_enable_normalised)

        self._configure_dropdown(self.sampleStackSelector)
        self._configure_dropdown(self.normaliseStackSelector)

        self.sampleStackSelector.select_eligible_stack()
        self.try_to_select_relevant_normalise_stack("Flat")

        self.exportButton.clicked.connect(self.presenter.handle_export_csv)


[docs]
    def cleanup(self):
        self.sampleStackSelector.unsubscribe_from_main_window()
        self.normaliseStackSelector.unsubscribe_from_main_window()
        self.main_window.spectrum_viewer = None


    @property
    def current_dataset_id(self) -> Optional['UUID']:
        return self._current_dataset_id

    @current_dataset_id.setter
    def current_dataset_id(self, uuid: Optional['UUID']) -> None:
        self._current_dataset_id = uuid

    def _configure_dropdown(self, selector: DatasetSelectorWidgetView) -> None:
        selector.presenter.show_stacks = True
        selector.subscribe_to_main_window(self.main_window)


[docs]
    def set_normalise_dropdown_state(self) -> None:
        if self.normaliseCheckBox.isChecked():
            self.normaliseStackSelector.setEnabled(True)
        else:
            self.normaliseStackSelector.setEnabled(False)



[docs]
    def try_to_select_relevant_normalise_stack(self, name: str) -> None:
        self.normaliseStackSelector.try_to_select_relevant_stack(name)



[docs]
    def get_normalise_stack(self) -> Optional['UUID']:
        return self.normaliseStackSelector.current()



[docs]
    def get_csv_filename(self) -> Optional[Path]:
        path = QFileDialog.getSaveFileName(self, "Save CSV file", "", "CSV file (*.csv)")[0]
        if path:
            return Path(path)
        else:
            return None



[docs]
    def set_image(self, image_data: Optional['np.ndarray'], autoLevels: bool = True):
        self.spectrum.image.setImage(image_data, autoLevels=autoLevels)



[docs]
    def set_spectrum(self, spectrum_data: 'np.ndarray'):
        self.spectrum.spectrum.clearPlots()
        self.spectrum.spectrum.plot(spectrum_data)



[docs]
    def clear(self) -> None:
        self.spectrum.clear_data()



[docs]
    def auto_range_image(self):
        self.spectrum.image.vb.autoRange()



[docs]
    def set_normalise_error(self, norm_issue: str):
        self.normalise_error_issue = norm_issue

        self.display_normalise_error()



[docs]
    def display_normalise_error(self):
        if self.normalise_error_issue and self.normaliseCheckBox.isChecked():
            self.normaliseErrorIcon.setPixmap(self.normalise_error_icon_pixmap)
            self.normaliseErrorIcon.setToolTip(self.normalise_error_issue)
        else:
            self.normaliseErrorIcon.setPixmap(QPixmap())
            self.normaliseErrorIcon.setToolTip("")