SpectAcoular documentation

spectacoular.factory.get_widgets

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spectacoular.factory.get_widgets

spectacoular.factory.get_widgets(self, trait_widget_mapper={}, trait_widget_args={})

Creates a mapping between several class trait attributes and Bokeh widgets.

This function is implemented in all SpectAcoular classes and is added to Acoular’s classes via the the bokehview module. For each attribute provided, it builds a corresponding Bokeh widget.

The function handles multiple cases of View construction:

  • Default View: the function is called as a method by a BaseSpectacoular derived instance without specifying trait_widget_mapper and trait_widget_args explicitly as function arguments. In this case, the default widget mapping, defined in bokehview, will be used:

    from spectacoular import RectGrid
    from bokeh.io import show
    from bokeh.layouts import gridplot
    
    grid = RectGrid()
    
    widgets = list(grid.get_widgets().values())
    show(gridplot(widgets, ncols=5, sizing_mode='stretch_both'))
    
  • No Predefined View: get_widgets() is called and a HasTraits derived instance is given as the first argument to the function without any further arguments. In this case, a default mapping is created from all editable traits to create the view.

from acoular import RectGrid
from spectacoular import get_widgets
from bokeh.io import show
from bokeh.layouts import gridplot

grid = RectGrid()

widgets = list(get_widgets(grid).values())
show(gridplot(widgets, ncols=5, sizing_mode='stretch_both'))
  • Custom View: get_widgets() is called by a BaseSpectacoular derived instance and an explicit mapping is given. In this case, the instance attributes (self.trait_widget_mapper,self.`trait_widget_args`) will be superseded.

    from spectacoular import RectGrid
    from bokeh.io import show
    from bokeh.models.widgets import Slider
    from bokeh.layouts import column
    
    grid = RectGrid()
    
    trait_widget_mapper = {'x_min': Slider}
    trait_widget_args = {'x_min': {'title': 'X Min', 'start': -1, 'end': 1, 'step':0.1}}
    
    widgets = list(grid.get_widgets(
          trait_widget_mapper=trait_widget_mapper, 
          trait_widget_args=trait_widget_args
    ).values())
    show(column(widgets,sizing_mode='stretch_both'))
    

    The same functionality can also be used with HasTraits derived classes, not part of Spectacoular:

    from acoular import RectGrid
    from spectacoular import get_widgets
    from bokeh.io import show
    from bokeh.models.widgets import Slider
    from bokeh.layouts import column
    
    grid = RectGrid()
    
    trait_widget_mapper = {'x_min': Slider}
    trait_widget_args = {'x_min': {'title': 'X Min', 'start': -1, 'end': 1, 'step':0.1}}
    
    widgets = list(get_widgets(grid,
          trait_widget_mapper=trait_widget_mapper, 
          trait_widget_args=trait_widget_args
    ).values())
    show(column(widgets,sizing_mode='stretch_both'))
    
Parameters:
trait_widget_mapperdict, optional

contains the desired mapping of a variable name (dict key) to a Bokeh widget type (dict value), by default {}

trait_widget_argsdict, optional
contains the desired widget kwargs (dict values) for each variable name (dict key),

by default {}

Returns:
dict

A dictionary containing the variable names as the key and the Bokeh widget instance as value.

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