bec_widgets.widgets.plots.image.image_base

Classes

ImageBase	Base class for the Image widget.
ImageLayer	Model for the image layer.
ImageLayerManager	Manager for the image layers.
ImageLayerSync	Model for the image layer synchronization.

Module Contents

class ImageBase(*args, **kwargs)

Bases: bec_widgets.widgets.plots.plot_base.PlotBase

Base class for the Image widget.

Initialize the ImageBase widget.

_add_roi_plots()

Initialize the ROI plots and side panels.

_apply_colormap_to_colorbar(color_map: str) → None

_init_image_base_toolbar()

_roi_mgr_closed()

_set_autorange(enabled: bool, sync: bool = True)

Set the autorange for all layers.

Parameters:

• enabled (bool) – Whether to enable autorange.

• sync (bool) – Whether to synchronize the autorange state across all layers.

_set_vrange(value: tuple | list | qtpy.QtCore.QPointF, disable_autorange: bool = True)

_sync_autorange_switch()

Synchronize the autorange switch with the current autorange state and mode if changed from outside.

_sync_colorbar_actions()

Synchronize the colorbar actions with the current colorbar state.

_sync_colorbar_levels()

Immediately propagate current levels to the active colorbar.

add_layer(name: str | None = None, **kwargs) → ImageLayer

Add a new image layer to the widget.

Parameters:

• name (str | None) – The name of the image layer. If None, a default name is generated.

• **kwargs – Additional arguments for the image layer.

Returns:

The added image layer.

Return type:

ImageLayer

add_roi(kind: Literal['rect', 'circle', 'ellipse'] = 'rect', name: str | None = None, line_width: int | None = 5, pos: tuple[float, float] | None = (10, 10), size: tuple[float, float] | None = (50, 50), movable: bool = True, **pg_kwargs) → bec_widgets.widgets.plots.roi.image_roi.RectangularROI | bec_widgets.widgets.plots.roi.image_roi.CircularROI

Add a ROI to the image.

Parameters:

• kind (str) – The type of ROI to add. Options are “rect” or “circle”.

• name (str) – The name of the ROI.

• line_width (int) – The line width of the ROI.

• pos (tuple) – The position of the ROI.

• size (tuple) – The size of the ROI.

• movable (bool) – Whether the ROI is movable.

• **pg_kwargs – Additional arguments for the ROI.

Returns:

The created ROI object.

Return type:

RectangularROI | CircularROI

add_side_menus()

Adds multiple menus to the side panel.

apply_theme(theme: str)

Apply the theme to the widget.

Parameters:

theme (str, optional) – The theme to be applied.

cleanup()

Cleanup the widget.

static cleanup_histogram_lut_item(histogram_lut_item: pyqtgraph.HistogramLUTItem)

Clean up HistogramLUTItem safely, including open ViewBox menus and child widgets.

Parameters:

histogram_lut_item (pg.HistogramLUTItem) – The HistogramLUTItem to clean up.

color_map() → str

Set the color map of the image.

enable_colorbar(enabled: bool, style: Literal['full', 'simple'] = 'full', vrange: tuple[int, int] | None = None)

Enable the colorbar and switch types of colorbars.

Parameters:

• enabled (bool) – Whether to enable the colorbar.

• style (Literal["full", "simple"]) – The type of colorbar to enable.

• vrange (tuple) – The range of values to use for the colorbar.

enable_full_colorbar() → bool

Enable the full colorbar.

enable_simple_colorbar() → bool

Enable the simple colorbar.

layers() → list[ImageLayer]

Get the list of image layers.

Returns:

The list of image layers.

Return type:

list[ImageLayer]

lock_aspect_ratio() → bool

Whether the aspect ratio is locked.

remove_layer(layer: ImageLayer | str)

Remove an image layer from the widget.

Parameters:

layer (ImageLayer | str) – The image layer to remove. Can be the layer object or the name of the layer.

remove_roi(roi: int | str)

Remove an ROI by index or label via the ROIController.

show_roi_manager_popup()

toggle_autorange(enabled: bool, mode: str)

Toggle autorange.

Parameters:

• enabled (bool) – Whether to enable autorange.

• mode (str) – The autorange mode. Options are “max” or “mean”.

toggle_roi_panels(checked: bool)

Show or hide the ROI panels based on the test action toggle state.

Parameters:

checked (bool) – Whether the test action is checked.

update_image_slices(coordinates: tuple[int, int, int] = None)

Update the image slices based on the crosshair position.

Parameters:

coordinates (tuple) – The coordinates of the crosshair.

v_range() → qtpy.QtCore.QPointF

Set the v_range of the main image.

MAX_TICKS_COLORBAR = 10

autorange = True

autorange_mode = 'mean'

image_updated

layer_added

layer_manager: ImageLayerManager

layer_removed

roi_controller

roi_manager_dialog = None

property rois: list[bec_widgets.widgets.plots.roi.image_roi.BaseROI]

Get the list of ROIs.

sync_colorbar_with_autorange

property v_max: float

Get the maximum value of the v_range.

property v_min: float

Get the minimum value of the v_range.

x_roi = None

y_roi = None

class ImageLayer(/, **data: Any)

Bases: pydantic.BaseModel

Model for the image layer.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

image: bec_widgets.widgets.plots.image.image_item.ImageItem = None

model_config

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

name: str = None

sync: ImageLayerSync = None

class ImageLayerManager(parent: ImageBase, plot_item: pyqtgraph.PlotItem, on_add: qtpy.QtCore.SignalInstance | None = None, on_remove: qtpy.QtCore.SignalInstance | None = None)

Manager for the image layers.

__getitem__(name: str) → ImageLayer

Get an image layer by name.

Parameters:

name (str) – The name of the image layer.

Returns:

The image layer with the given name.

Return type:

ImageLayer

__iter__()

Iterate over the image layers.

Returns:

An iterator over the image layers.

Return type:

Iterator[ImageLayer]

__len__() → int

Get the number of image layers.

Returns:

The number of image layers.

Return type:

int

_get_bottom_z_position() → int

Get the bottom z position of the image layers, capping it to the minimum z value.

Returns:

The bottom z position of the image layers.

Return type:

int

_get_top_z_position() → int

Get the top z position of the image layers, capping it to the maximum z value.

Returns:

The top z position of the image layers.

Return type:

int

_remove_destroyed_layer(layer: str)

Remove a layer that has been destroyed.

Parameters:

layer (str) – The name of the layer to remove.

add(name: str | None = None, z_position: int | Literal['top', 'bottom'] | None = None, sync: ImageLayerSync | None = None, **kwargs) → ImageLayer

Add an image layer to the widget.

Parameters:

• name (str | None) – The name of the image layer. If None, a default name is generated.

• image (ImageItem) – The image layer to add.

• z_position (int | None) – The z position of the image layer. If None, the layer is added to the top.

• sync (ImageLayerSync | None) – The synchronization settings for the image layer.

• **kwargs – ImageLayerSync settings. Only used if sync is None.

clear()

Clear all image layers from the manager.

remove(layer: ImageLayer | str)

Remove an image layer from the widget.

Parameters:

layer (ImageLayer | str) – The image layer to remove. Can be the layer object or the name of the layer.

Z_RANGE_USER

layers: dict[str, ImageLayer]

on_add = None

on_remove = None

parent

plot_item

class ImageLayerSync(/, **data: Any)

Bases: pydantic.BaseModel

Model for the image layer synchronization.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

autorange: bool = None

autorange_mode: bool = None

color_map: bool = None

fft: bool = None

log: bool = None

rotation: bool = None

transpose: bool = None

v_range: bool = None