7.5.5.1.6. pymodaq_gui.plotting.data_viewers.viewer2D module

class pymodaq_gui.plotting.data_viewers.viewer2D.Histogrammer(histogram_container: QWidget, histogram_refs=['red', 'green', 'blue'])

Bases: QObject

Attributes:

autolevels

Methods

set_gradient([histo, gradient])

Change the color gradient of the specified histogram :param histo: :type histo: (str) either 'red', 'green', 'blue', 'spread' or 'all' :param gradient: :type gradient: (str or Gradient)

activated
add_histogram
affect_histo_to_imageitems
get_histogram
get_histograms
gradient_changed
set_autolevels
setup_histograms
show_hide_histogram

activated(histo_action_checked)

add_histogram(histogram)

affect_histo_to_imageitems(image_items)

get_histogram(name)

get_histograms()

set_autolevels(isautolevels=True)

set_gradient(histo='red', gradient='grey')

Change the color gradient of the specified histogram :param histo: :type histo: (str) either ‘red’, ‘green’, ‘blue’, ‘spread’ or ‘all’ :param gradient: :type gradient: (str or Gradient)

setup_histograms()

show_hide_histogram(checked, are_items_visible)

property autolevels

gradient_changed

int = …, arguments: Sequence = …) -> PYQT_SIGNAL

types is normally a sequence of individual types. Each type is either a type object or a string that is the name of a C++ type. Alternatively each type could itself be a sequence of types each describing a different overloaded signal. name is the optional C++ name of the signal. If it is not specified then the name of the class attribute that is bound to the signal is used. revision is the optional revision of the signal that is exported to QML. If it is not specified then 0 is used. arguments is the optional sequence of the names of the signal’s arguments.

Type:

pyqtSignal(*types, name

Type:

str = …, revision

class pymodaq_gui.plotting.data_viewers.viewer2D.ImageDisplayer(plotitem, data_distribution: DataDistribution)

Bases: QObject

This Object deals with the display of 2D data with a plotitem

Attributes:

autolevels

labels

legend

Methods

get_image
get_images
set_autolevels
show_legend
update_data
update_display_items
update_image_visibility
updated_item

get_image(name)

get_images()

set_autolevels(isautolevel)

show_legend(show=True)

update_data(dwa: DataWithAxes)

update_display_items(labels: List[str] = None)

update_image_visibility(are_items_visible)

property autolevels

property labels

property legend

updated_item

int = …, arguments: Sequence = …) -> PYQT_SIGNAL

types is normally a sequence of individual types. Each type is either a type object or a string that is the name of a C++ type. Alternatively each type could itself be a sequence of types each describing a different overloaded signal. name is the optional C++ name of the signal. If it is not specified then the name of the class attribute that is bound to the signal is used. revision is the optional revision of the signal that is exported to QML. If it is not specified then 0 is used. arguments is the optional sequence of the names of the signal’s arguments.

Type:

pyqtSignal(*types, name

Type:

str = …, revision

class pymodaq_gui.plotting.data_viewers.viewer2D.IsoCurver(image_source, histogram_parent)

Bases: QObject

Methods

set_isocurve_data
setup_iso_curve
show_hide_iso
update_histogram_parent
update_image_source
update_isocurve

set_isocurve_data(data)

setup_iso_curve(parent_image_item='red')

show_hide_iso(show=True)

update_histogram_parent(histogram)

update_image_source(image_source)

update_isocurve()

class pymodaq_gui.plotting.data_viewers.viewer2D.View2D(parent_widget=None)

Bases: ActionManager, QObject

Attributes:

plotitem

Methods

get_crosshair_position()	Convenience function from the Crosshair
get_crosshair_signal()	Convenience function from the Crosshair
move_scale_roi_target([pos, size])	Move and scale the target ROI (used to display a particular area, for instance the currently scanned points during a scan :param pos: :type pos: (iterable) setting the central position of the ROI in the view :param size: :type size: (iterable) setting the size of the ROI
scale_axis(xaxis, yaxis)	scale view coordinates from the regular axes to the scaled/offset ones
set_axis_label(position[, label, units])	Convenience method to set label and unit of any view axes :param position: :type position: (str) any of AXIS_POSITIONS :param label: :type label: (str) text of the axis label :param units: :type units: (str) units of the axis label
set_axis_scaling([position, scaling, ...])	Method used to update the scaling of the right and top axes in order to translate pixels to real coordinates :param position: :type position: (str) axis position either one of AXIS_POSITIONS :param scaling: :type scaling: (float) scaling of the axis :param offset: :type offset: (float) offset of the axis :param label: :type label: (str) text of the axis label :param units: :type units: (str) units of the axis label
set_crosshair_position(*positions)	Convenience function from the Crosshair
setup_actions()	Method where to create actions to be subclassed.
unscale_axis(xaxis, yaxis)	scale view coordinates from the scaled/offset axes to the regular ones
update_roi_channels(index[, roi_type])	Update the use_channel setting each time a ROI is added

add_roi_displayer
clear_plot_item
collapse_lineout_widgets
connect_things
display_crosshair_lineouts
display_images
display_roi_lineouts
get_axis
get_axis_label
get_data_at
get_double_clicked
get_view_range
get_visible_images
lock_aspect_ratio
move_left_splitter
move_right_splitter
notify_visibility_data_displayer
prepare_image_widget_for_lineouts
prepare_ui
remove_roi_displayer
roi_clicked
set_image_displayer
set_image_labels
setup_graphs
setup_widgets
show_ROI_select
show_hide_crosshair
show_hide_histogram
show_legend
show_lineout_widgets
show_roi_target
update_colors

add_roi_displayer(index, roi_type='', roi_name='')

clear_plot_item()

collapse_lineout_widgets()

connect_things()

display_crosshair_lineouts(crosshair_dte: DataToExport)

display_images(datas)

display_roi_lineouts(roi_dte: DataToExport)

get_axis(position='left') → AxisItem_Scaled

get_axis_label(position)

get_crosshair_position()

Convenience function from the Crosshair

get_crosshair_signal()

Convenience function from the Crosshair

get_data_at(name='red', xy=(0, 0))

get_double_clicked()

get_view_range()

get_visible_images()

lock_aspect_ratio()

move_left_splitter(pos, index)

move_right_splitter(pos, index)

move_scale_roi_target(pos=None, size=None)

Move and scale the target ROI (used to display a particular area, for instance the currently scanned points during a scan :param pos: :type pos: (iterable) setting the central position of the ROI in the view :param size: :type size: (iterable) setting the size of the ROI

notify_visibility_data_displayer()

prepare_image_widget_for_lineouts(ratio=0.7)

prepare_ui()

remove_roi_displayer(roi_name='')

roi_clicked(isroichecked=True)

scale_axis(xaxis, yaxis)

scale view coordinates from the regular axes to the scaled/offset ones

set_axis_label(position, label='', units='')

Convenience method to set label and unit of any view axes :param position: :type position: (str) any of AXIS_POSITIONS :param label: :type label: (str) text of the axis label :param units: :type units: (str) units of the axis label

set_axis_scaling(position='top', scaling=1, offset=0, label='', units='Pxls')

Method used to update the scaling of the right and top axes in order to translate pixels to real coordinates :param position: :type position: (str) axis position either one of AXIS_POSITIONS :param scaling: :type scaling: (float) scaling of the axis :param offset: :type offset: (float) offset of the axis :param label: :type label: (str) text of the axis label :param units: :type units: (str) units of the axis label

set_crosshair_position(*positions)

Convenience function from the Crosshair

set_image_displayer(data_distribution: DataDistribution)

set_image_labels(labels: List[str])

setup_actions()

Method where to create actions to be subclassed. Mandatory

Examples

>>> self.add_action('Quit', 'close2', "Quit program")
>>> self.add_action('Grab', 'camera', "Grab from camera", checkable=True)
>>> self.add_action('Load', 'Open', "Load target file (.h5, .png, .jpg) or data from camera", checkable=False)
>>> self.add_action('Save', 'SaveAs', "Save current data", checkable=False)

See also

ActionManager.add_action

setup_graphs(graphs_layout)

setup_widgets()

show_ROI_select()

show_hide_crosshair(show=True)

show_hide_histogram(show=True)

show_legend(show=True)

show_lineout_widgets()

show_roi_target(show=True)

unscale_axis(xaxis, yaxis)

scale view coordinates from the scaled/offset axes to the regular ones

update_colors(colors: list)

update_roi_channels(index, roi_type='')

Update the use_channel setting each time a ROI is added

lineout_types = ['hor', 'ver', 'int']

property plotitem

class pymodaq_gui.plotting.data_viewers.viewer2D.Viewer2D(parent: QWidget = None, title='')

Bases: ViewerBase

Object managing plotting and manipulation of 2D data using a View2D

Attributes:

crosshair

Convenience method

image_widget

Convenience method

roi_manager

Convenience method

roi_target

To be implemented if necessary (Viewer1D and above)

x_axis

y_axis

Methods

activate_roi([activate])	Activate the Roi manager using the corresponding action
get_axes_from_view(data)	Obtain axes info from the view
get_data_at()	Convenience method
move_roi_target([pos, size])	move a specific read only ROI at the given position on the viewer
set_crosshair_position(xpos, ypos)	Convenience method to set the crosshair positions
set_gradient(image_key, gradient)	convenience function
set_image_transform()	Deactivate some tool buttons if data type is "spread" then apply transform_image
show_roi([show, show_roi_widget])	convenience function to control roi

autolevels_first
crosshair_changed
double_clicked
prepare_connect_ui
process_crosshair_lineouts
process_roi_lineouts
roi_changed
selected_region_changed
set_visible_items
transform_image
update_crosshair_data
update_data

activate_roi(activate=True)

Activate the Roi manager using the corresponding action

autolevels_first()

crosshair_changed()

double_clicked(posx, posy)

get_axes_from_view(data: DataWithAxes)

Obtain axes info from the view

Only for uniform data

get_data_at()

Convenience method

move_roi_target(pos: Iterable[float] = None, size: Iterable[float] = (1, 1))

move a specific read only ROI at the given position on the viewer

prepare_connect_ui()

process_crosshair_lineouts(dte)

process_roi_lineouts(roi_dte: DataToExport)

roi_changed(*args, **kwargs)

selected_region_changed()

set_crosshair_position(xpos, ypos)

Convenience method to set the crosshair positions

set_gradient(image_key, gradient)

convenience function

set_image_transform() → DataRaw

Deactivate some tool buttons if data type is “spread” then apply transform_image

set_visible_items()

show_roi(show=True, show_roi_widget=True)

convenience function to control roi

transform_image(dwa: DataWithAxes)

update_crosshair_data(crosshair_dte: DataToExport)

update_data()

property crosshair

Convenience method

property image_widget

Convenience method

property roi_manager

Convenience method

property roi_target: ROI

To be implemented if necessary (Viewer1D and above)

property x_axis

property y_axis

pymodaq_gui.plotting.data_viewers.viewer2D.generate_uniform_data() → DataRaw

pymodaq_gui.plotting.data_viewers.viewer2D.histogram_factory(image_item=None, gradient='red')

Create a pyqtgraph HistogramLUTWidget widget (histogram) and link it to the corresponding image_item :param image_item: :type image_item: (ImageItem) the image item to be linked with the histogram :param gradient: :type gradient: (str) either ‘red’, ‘green’, ‘blue’, ‘spread’ or one of the Gradients

Return type:

HistogramLUTWidget instance

pymodaq_gui.plotting.data_viewers.viewer2D.image_item_factory(item_type='uniform', axisOrder='row-major', pen='r')

pymodaq_gui.plotting.data_viewers.viewer2D.main(data_distribution='uniform')

either ‘uniform’ or ‘spread’

pymodaq_gui.plotting.data_viewers.viewer2D.main_spread()

pymodaq_gui.plotting.data_viewers.viewer2D.main_view()

pymodaq_gui.plotting.data_viewers.viewer2D.plot_data(viewer2D: Viewer2D, ndata: int = 2)

pymodaq_gui.plotting.data_viewers.viewer2D.print_roi_select(rect)