holoviews.bokeh Package#

`bokeh` Package#

`annotation` Module#

Inheritance diagram of holoviews.plotting.bokeh.annotation

class holoviews.plotting.bokeh.annotation.ArrowPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.CompositeElementPlot, holoviews.plotting.bokeh.element.AnnotationPlot

Parameters inherited from:

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges=None, range_type='combined')[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

selection_display = None#

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.annotation.BoxAnnotationPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.ElementPlot, holoviews.plotting.bokeh.element.AnnotationPlot

Parameters inherited from:

apply_ranges = param.Boolean(bounds=(0, 1), default=False, label=’Apply ranges’): Whether to include the annotation in axis range calculations.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

selection_display = None#

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.annotation.DivPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.plot.BokehPlot, holoviews.plotting.plot.GenericElementPlot, holoviews.plotting.bokeh.element.AnnotationPlot

Parameters inherited from:

hooks = param.HookList(bounds=(0, None), default=[], label=’Hooks’): Optional list of hooks called when finalizing a plot. The hook is passed the plot object and the displayed element, and other plotting handles can be accessed via plot.handles.
width = param.Number(bounds=(0, None), default=300, inclusive_bounds=(True, True), label=’Width’): The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.
height = param.Number(bounds=(0, None), default=300, inclusive_bounds=(True, True), label=’Height’): The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.
sizing_mode = param.ObjectSelector(label=’Sizing mode’, objects=[‘fixed’, ‘stretch_width’, ‘stretch_height’, ‘stretch_both’, ‘scale_width’, ‘scale_height’, ‘scale_both’, None]): How the component should size itself. * “fixed” : Component is not responsive. It will retain its original width and height regardless of any subsequent browser window resize events. * “stretch_width” Component will responsively resize to stretch to the available width, without maintaining any aspect ratio. The height of the component depends on the type of the component and may be fixed or fit to component’s contents. * “stretch_height” Component will responsively resize to stretch to the available height, without maintaining any aspect ratio. The width of the component depends on the type of the component and may be fixed or fit to component’s contents. * “stretch_both” Component is completely responsive, independently in width and height, and will occupy all the available horizontal and vertical space, even if this changes the aspect ratio of the component. * “scale_width” Component will responsively resize to stretch to the available width, while maintaining the original or provided aspect ratio. * “scale_height” Component will responsively resize to stretch to the available height, while maintaining the original or provided aspect ratio. * “scale_both” Component will responsively resize to both the available width and height, while maintaining the original or provided aspect ratio.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

get_aspect(xspan, yspan)#: Should define the aspect ratio of the plot.

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)[source]#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

selection_display = None#

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None)[source]#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.annotation.LabelsPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.ColorbarPlot, holoviews.plotting.bokeh.element.AnnotationPlot

Parameters inherited from:

show_legend = param.Boolean(bounds=(0, 1), default=False, label=’Show legend’): Whether to show legend for the plot.
xoffset = param.Number(allow_None=True, inclusive_bounds=(True, True), label=’Xoffset’): Amount of offset to apply to labels along x-axis.
yoffset = param.Number(allow_None=True, inclusive_bounds=(True, True), label=’Yoffset’): Amount of offset to apply to labels along x-axis.
color_index = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘int’>), label=’Color index’): Deprecated in favor of color style mapping, e.g. color=dim(‘color’)

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.annotation.LineAnnotationPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.ElementPlot, holoviews.plotting.bokeh.element.AnnotationPlot

Parameters inherited from:

apply_ranges = param.Boolean(bounds=(0, 1), default=False, label=’Apply ranges’): Whether to include the annotation in axis range calculations.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges=None, range_type='combined')[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

selection_display = None#

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.annotation.SlopePlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.ElementPlot, holoviews.plotting.bokeh.element.AnnotationPlot

Parameters inherited from:

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges=None, range_type='combined')[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

selection_display = None#

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.annotation.SplinePlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.ElementPlot, holoviews.plotting.bokeh.element.AnnotationPlot

Draw the supplied Spline annotation (see Spline docstring). Does not support matplotlib Path codes.

Parameters inherited from:

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

selection_display = None#

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.annotation.TextPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.ElementPlot, holoviews.plotting.bokeh.element.AnnotationPlot

Parameters inherited from:

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges=None, range_type='combined')[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

selection_display = None#

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

`callbacks` Module#

Inheritance diagram of holoviews.plotting.bokeh.callbacks

class holoviews.plotting.bokeh.callbacks.BoundsCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.Callback

Returns the bounds of a box_select tool.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.BoundsXCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.Callback

Returns the bounds of a xbox_select tool.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.BoundsYCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.Callback

Returns the bounds of a ybox_select tool.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.BoxEditCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.GlyphDrawCallback

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.CDSCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.Callback

A Stream callback that syncs the data on a bokeh ColumnDataSource model with Python.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.Callback(plot, streams, source, **params)[source]#

Bases: object

Provides a baseclass to define callbacks, which return data from bokeh model callbacks, events and attribute changes. The callback then makes this data available to any streams attached to it.

The definition of a callback consists of a number of components:

modelsDefines which bokeh models the callback will be
attached on referencing the model by its key in the plots handles, e.g. this could be the x_range, y_range, plot, a plotting tool or any other bokeh mode.
attributesThe attributes define which attributes to send
back to Python. They are defined as a dictionary mapping between the name under which the variable is made available to Python and the specification of the attribute. The specification should start with the variable name that is to be accessed and the location of the attribute separated by periods. All models defined by the models and can be addressed in this way, e.g. to get the start of the x_range as ‘x’ you can supply {‘x’: ‘x_range.attributes.start’}. Additionally certain handles additionally make the cb_obj variables available containing additional information about the event.
on_eventsIf the Callback should listen to bokeh events this
should declare the types of event as a list (optional)
on_changesIf the Callback should listen to model attribute
changes on the defined models (optional)

If either on_events or on_changes are declared the Callback will be registered using the on_event or on_change machinery, otherwise it will be treated as a regular callback on the model. The callback can also define a _process_msg method, which can modify the data sent by the callback before it is passed to the streams.

A callback supports three different throttling modes:

adaptive (default): The callback adapts the throttling timeout depending on the rolling mean of the time taken to process each message. The rolling window is controlled by the adaptive_window value.
throttle: Uses the fixed throttle_timeout as the minimum amount of time between events.
debounce: Processes the message only when no new event has been received within the throttle_timeout duration.

async on_change(attr, old, new)[source]#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)[source]#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)[source]#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)[source]#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)[source]#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.CurveEditCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.GlyphDrawCallback

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.DoubleTapCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.TapCallback

Returns the mouse x/y-position on doubletap event.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.DrawCallback(*args, **kwargs)[source]#

Bases: holoviews.plotting.bokeh.callbacks.PointerXYCallback

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.FreehandDrawCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.PolyDrawCallback

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.GlyphDrawCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.CDSCallback

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.LassoCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.Callback

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.MouseEnterCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.PointerXYCallback

Returns the mouse x/y-position on mouseenter event, i.e. when mouse enters the plot canvas.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.MouseLeaveCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.PointerXYCallback

Returns the mouse x/y-position on mouseleave event, i.e. when mouse leaves the plot canvas.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.PanEndCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.TapCallback

Returns the mouse x/y-position of a pan end event.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.PlotSizeCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.Callback

Returns the actual width and height of a plot once the layout solver has executed.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.PointDrawCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.GlyphDrawCallback

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.PointerXCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.PointerXYCallback

Returns the mouse x-position on mousemove event.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.PointerXYCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.Callback

Returns the mouse x/y-position on mousemove event.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.PointerYCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.PointerXYCallback

Returns the mouse x/y-position on mousemove event.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.PolyDrawCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.GlyphDrawCallback

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.PolyEditCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.PolyDrawCallback

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.PressUpCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.TapCallback

Returns the mouse x/y-position of a pressup mouse event.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.RangeXCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.RangeXYCallback

Returns the x-axis range of a plot.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.RangeXYCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.Callback

Returns the x/y-axis ranges of a plot.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)[source]#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.RangeYCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.RangeXYCallback

Returns the y-axis range of a plot.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.ResetCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.Callback

Signals the Reset stream if an event has been triggered.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.SelectModeCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.Callback

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.Selection1DCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.Callback

Returns the current selection on a ColumnDataSource.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.SelectionXYCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.BoundsCallback

Converts a bounds selection to numeric or categorical x-range and y-range selections.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.SingleTapCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.TapCallback

Returns the mouse x/y-position on tap event.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.TapCallback(plot, streams, source, **params)[source]#

Bases: holoviews.plotting.bokeh.callbacks.PointerXYCallback

Returns the mouse x/y-position on tap event.

Note: As of bokeh 0.12.5, there is no way to distinguish the individual tap events within a doubletap event.

async on_change(attr, old, new)#: Process change events adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async on_event(event)#: Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

async process_on_event(timeout=None)#: Trigger callback change event and triggering corresponding streams.

classmethod resolve_attr_spec(spec, cb_obj, model=None)#: Resolves a Callback attribute specification looking the corresponding attribute up on the cb_obj, which should be a bokeh model. If not model is supplied cb_obj is assumed to be the same as the model.

set_callback(handle)#: Set up on_change events for bokeh server interactions.

`chart` Module#

Inheritance diagram of holoviews.plotting.bokeh.chart

class holoviews.plotting.bokeh.chart.AreaPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.mixins.AreaMixin, holoviews.plotting.bokeh.chart.SpreadPlot

Parameters inherited from:

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=(0, 0.1), label=’Padding’): Fraction by which to increase auto-ranged extents to make datapoints more visible around borders. To compute padding, the axis whose screen size is largest is chosen, and the range of that axis is increased by the specified fraction along each axis. Other axes are then padded ensuring that the amount of screen space devoted to padding is equal for all axes. If specified as a tuple, the int or float values in the tuple will be used for padding in each axis, in order (x,y or x,y,z). For example, for padding=0.2 on a 800x800-pixel plot, an x-axis with the range [0,10] will be padded by 20% to be [-1,11], while a y-axis with a range [0,1000] will be padded to be [-100,1100], which should make the padding be approximately the same number of pixels. But if the same plot is changed to have a height of only 200, the y-range will then be [-400,1400] so that the y-axis padding will still match that of the x-axis. It is also possible to declare non-equal padding value for the lower and upper bound of an axis by supplying nested tuples, e.g. padding=(0.1, (0, 0.1)) will pad the x-axis lower and upper bound as well as the y-axis upper bound by a fraction of 0.1 while the y-axis lower bound is not padded at all.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined')#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.chart.BarPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.mixins.BarsMixin, holoviews.plotting.bokeh.element.ColorbarPlot, holoviews.plotting.bokeh.element.LegendPlot

BarPlot allows generating single- or multi-category bar Charts, by selecting which key dimensions are mapped onto separate groups, categories and stacks.

Parameters inherited from:

multi_level = param.Boolean(bounds=(0, 1), default=True, label=’Multi level’): Whether the Bars should be grouped into a second categorical axis level.
stacked = param.Boolean(bounds=(0, 1), default=False, label=’Stacked’): Whether the bars should be stacked or grouped.
color_index = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘int’>), label=’Color index’): Deprecated in favor of color style mapping, e.g. color=dim(‘color’)

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined')#: Make adjustments to plot extents by computing stacked bar heights, adjusting the bar baseline and forcing the x-axis to be categorical.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_stack(xvals, yvals, baselines, sign='positive')[source]#: Iterates over a x- and y-values in a stack layer and appropriately offsets the layer on top of the previous layer.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.chart.CurvePlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.ElementPlot

Parameters inherited from:

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=(0, 0.1), label=’Padding’): Fraction by which to increase auto-ranged extents to make datapoints more visible around borders. To compute padding, the axis whose screen size is largest is chosen, and the range of that axis is increased by the specified fraction along each axis. Other axes are then padded ensuring that the amount of screen space devoted to padding is equal for all axes. If specified as a tuple, the int or float values in the tuple will be used for padding in each axis, in order (x,y or x,y,z). For example, for padding=0.2 on a 800x800-pixel plot, an x-axis with the range [0,10] will be padded by 20% to be [-1,11], while a y-axis with a range [0,1000] will be padded to be [-100,1100], which should make the padding be approximately the same number of pixels. But if the same plot is changed to have a height of only 200, the y-range will then be [-400,1400] so that the y-axis padding will still match that of the x-axis. It is also possible to declare non-equal padding value for the lower and upper bound of an axis by supplying nested tuples, e.g. padding=(0.1, (0, 0.1)) will pad the x-axis lower and upper bound as well as the y-axis upper bound by a fraction of 0.1 while the y-axis lower bound is not padded at all.
interpolation = param.ObjectSelector(default=’linear’, label=’Interpolation’, objects=[‘linear’, ‘steps-mid’, ‘steps-pre’, ‘steps-post’]): Defines how the samples of the Curve are interpolated, default is ‘linear’, other options include ‘steps-mid’, ‘steps-pre’ and ‘steps-post’.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.chart.ErrorPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.ColorbarPlot

Parameters inherited from:

selected = param.List(allow_None=True, bounds=(0, None), label=’Selected’): The current selection as a list of integers corresponding to the selected items.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.chart.HistogramPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.ColorbarPlot

Parameters inherited from:

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined')[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.chart.PointPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.LegendPlot, holoviews.plotting.bokeh.element.ColorbarPlot

Parameters inherited from:

jitter = param.Number(allow_None=True, bounds=(0, None), inclusive_bounds=(True, True), label=’Jitter’): The amount of jitter to apply to offset the points along the x-axis.
selected = param.List(allow_None=True, bounds=(0, None), label=’Selected’): The current selection as a list of integers corresponding to the selected items.
color_index = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘int’>), label=’Color index’): Deprecated in favor of color style mapping, e.g. color=dim(‘color’)
size_index = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘int’>), label=’Size index’): Deprecated in favor of size style mapping, e.g. size=dim(‘size’)
scaling_method = param.ObjectSelector(default=’area’, label=’Scaling method’, objects=[‘width’, ‘area’]): Deprecated in favor of size style mapping, e.g. size=dim(‘size’)**2.
scaling_factor = param.Number(bounds=(0, None), default=1, inclusive_bounds=(True, True), label=’Scaling factor’): Scaling factor which is applied to either the width or area of each point, depending on the value of scaling_method.
size_fn = param.Callable(default=<ufunc ‘absolute’>, label=’Size fn’): Function applied to size values before applying scaling, to remove values lower than zero.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

size_fn = <ufunc 'absolute'>#

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.chart.SideHistogramPlot(*args, **kwargs)[source]#

Bases: holoviews.plotting.bokeh.chart.HistogramPlot

Parameters inherited from:

show_title = param.Boolean(bounds=(0, 1), default=False, label=’Show title’): Whether to display the plot title.
width = param.Integer(bounds=(0, None), default=125, inclusive_bounds=(True, True), label=’Width’): The width of the plot
height = param.Integer(bounds=(0, None), default=125, inclusive_bounds=(True, True), label=’Height’): The height of the plot
default_tools = param.List(bounds=(0, None), default=[‘save’, ‘pan’, ‘wheel_zoom’, ‘box_zoom’, ‘reset’], label=’Default tools’): A list of plugin tools to use on the plot.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined')#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.chart.SideSpikesPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.chart.SpikesPlot

SpikesPlot with useful defaults for plotting adjoined rug plot.

Parameters inherited from:

xaxis = param.ObjectSelector(default=’top-bare’, label=’Xaxis’, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None]): Whether and where to display the xaxis, bare options allow suppressing all axis labels including ticks and xlabel. Valid options are ‘top’, ‘bottom’, ‘bare’, ‘top-bare’ and ‘bottom-bare’.
yaxis = param.ObjectSelector(default=’right-bare’, label=’Yaxis’, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None]): Whether and where to display the yaxis, bare options allow suppressing all axis labels including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’ ‘left-bare’ and ‘right-bare’.
width = param.Integer(bounds=(0, None), default=50, inclusive_bounds=(True, True), label=’Width’): Width of plot
height = param.Integer(bounds=(0, None), default=50, inclusive_bounds=(True, True), label=’Height’): Height of plot
border = param.Integer(default=5, inclusive_bounds=(True, True), label=’Border’): Default borders on plot
selected = param.List(allow_None=True, bounds=(0, None), label=’Selected’): The current selection as a list of integers corresponding to the selected items.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined')#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.chart.SpikesPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.mixins.SpikesMixin, holoviews.plotting.bokeh.element.ColorbarPlot

Parameters inherited from:

show_legend = param.Boolean(bounds=(0, 1), default=True, label=’Show legend’): Whether to show legend for the plot.
spike_length = param.Number(default=0.5, inclusive_bounds=(True, True), label=’Spike length’): The length of each spike if Spikes object is one dimensional.
position = param.Number(default=0.0, inclusive_bounds=(True, True), label=’Position’): The position of the lower end of each spike.
color_index = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘int’>), label=’Color index’): Deprecated in favor of color style mapping, e.g. color=dim(‘color’)

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined')#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.chart.SpreadPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.ElementPlot

Parameters inherited from:

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=(0, 0.1), label=’Padding’): Fraction by which to increase auto-ranged extents to make datapoints more visible around borders. To compute padding, the axis whose screen size is largest is chosen, and the range of that axis is increased by the specified fraction along each axis. Other axes are then padded ensuring that the amount of screen space devoted to padding is equal for all axes. If specified as a tuple, the int or float values in the tuple will be used for padding in each axis, in order (x,y or x,y,z). For example, for padding=0.2 on a 800x800-pixel plot, an x-axis with the range [0,10] will be padded by 20% to be [-1,11], while a y-axis with a range [0,1000] will be padded to be [-100,1100], which should make the padding be approximately the same number of pixels. But if the same plot is changed to have a height of only 200, the y-range will then be [-400,1400] so that the y-axis padding will still match that of the x-axis. It is also possible to declare non-equal padding value for the lower and upper bound of an axis by supplying nested tuples, e.g. padding=(0.1, (0, 0.1)) will pad the x-axis lower and upper bound as well as the y-axis upper bound by a fraction of 0.1 while the y-axis lower bound is not padded at all.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.chart.VectorFieldPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.ColorbarPlot

Parameters inherited from:

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0.05, label=’Padding’): Fraction by which to increase auto-ranged extents to make datapoints more visible around borders. To compute padding, the axis whose screen size is largest is chosen, and the range of that axis is increased by the specified fraction along each axis. Other axes are then padded ensuring that the amount of screen space devoted to padding is equal for all axes. If specified as a tuple, the int or float values in the tuple will be used for padding in each axis, in order (x,y or x,y,z). For example, for padding=0.2 on a 800x800-pixel plot, an x-axis with the range [0,10] will be padded by 20% to be [-1,11], while a y-axis with a range [0,1000] will be padded to be [-100,1100], which should make the padding be approximately the same number of pixels. But if the same plot is changed to have a height of only 200, the y-range will then be [-400,1400] so that the y-axis padding will still match that of the x-axis. It is also possible to declare non-equal padding value for the lower and upper bound of an axis by supplying nested tuples, e.g. padding=(0.1, (0, 0.1)) will pad the x-axis lower and upper bound as well as the y-axis upper bound by a fraction of 0.1 while the y-axis lower bound is not padded at all.
arrow_heads = param.Boolean(bounds=(0, 1), default=True, label=’Arrow heads’): Whether or not to draw arrow heads.
magnitude = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘holoviews.util.transform.dim’>), label=’Magnitude’): Dimension or dimension value transform that declares the magnitude of each vector. Magnitude is expected to be scaled between 0-1, by default the magnitudes are rescaled relative to the minimum distance between vectors, this can be disabled with the rescale_lengths option.
pivot = param.ObjectSelector(default=’mid’, label=’Pivot’, objects=[‘mid’, ‘tip’, ‘tail’]): The point around which the arrows should pivot valid options include ‘mid’, ‘tip’ and ‘tail’.
rescale_lengths = param.Boolean(bounds=(0, 1), default=True, label=’Rescale lengths’): Whether the lengths will be rescaled to take into account the smallest non-zero distance between two vectors.
color_index = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘int’>), label=’Color index’): Deprecated in favor of dimension value transform on color option, e.g. color=dim(‘Magnitude’).
size_index = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘int’>), label=’Size index’): Deprecated in favor of the magnitude option, e.g. magnitude=dim(‘Magnitude’).
normalize_lengths = param.Boolean(bounds=(0, 1), default=True, label=’Normalize lengths’): Deprecated in favor of rescaling length using dimension value transforms using the magnitude option, e.g. dim(‘Magnitude’).norm().

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

`element` Module#

Inheritance diagram of holoviews.plotting.bokeh.element

class holoviews.plotting.bokeh.element.AnnotationPlot[source]#

Bases: object

Mix-in plotting subclass for AnnotationPlots which do not have a legend.

class holoviews.plotting.bokeh.element.ColorbarPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.ElementPlot

ColorbarPlot provides methods to create colormappers and colorbar models which can be added to a glyph. Additionally it provides parameters to control the position and other styling options of the colorbar. The default colorbar_position options are defined by the colorbar_specs, but may be overridden by the colorbar_opts.

Parameters inherited from:

color_levels = param.ClassSelector(allow_None=True, class_=(<class ‘int’>, <class ‘list’>, <class ‘range’>), label=’Color levels’): Number of discrete colors to use when colormapping or a set of color intervals defining the range of values to map each color to.
cformatter = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>), label=’Cformatter’): Formatter for ticks along the colorbar axis.
clabel = param.String(allow_None=True, label=’Clabel’): An explicit override of the color bar label. If set, takes precedence over the title key in colorbar_opts.
clim = param.Tuple(default=(nan, nan), label=’Clim’, length=2): User-specified colorbar axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.
clim_percentile = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘bool’>), default=False, label=’Clim percentile’): Percentile value to compute colorscale robust to outliers. If True, uses 2nd and 98th percentile; otherwise uses the specified numerical percentile value.
cnorm = param.ObjectSelector(default=’linear’, label=’Cnorm’, objects=[‘linear’, ‘log’, ‘eq_hist’]): Color normalization to be applied during colormapping.
colorbar = param.Boolean(bounds=(0, 1), default=False, label=’Colorbar’): Whether to display a colorbar.
colorbar_position = param.ObjectSelector(default=’right’, label=’Colorbar position’, objects=[‘right’, ‘left’, ‘bottom’, ‘top’, ‘top_right’, ‘top_left’, ‘bottom_left’, ‘bottom_right’]): Allows selecting between a number of predefined colorbar position options. The predefined options may be customized in the colorbar_specs class attribute.
colorbar_opts = param.Dict(class_=<class ‘dict’>, default={}, label=’Colorbar opts’): Allows setting specific styling options for the colorbar overriding the options defined in the colorbar_specs class attribute. Includes location, orientation, height, width, scale_alpha, title, title_props, margin, padding, background_fill_color and more.
clipping_colors = param.Dict(class_=<class ‘dict’>, default={}, label=’Clipping colors’): Dictionary to specify colors for clipped values, allows setting color for NaN values and for values above and below the min and max value. The min, max or NaN color may specify an RGB(A) color as a color hex string of the form #FFFFFF or #FFFFFFFF or a length 3 or length 4 tuple specifying values in the range 0-1 or a named HTML color.
logz = param.Boolean(bounds=(0, 1), default=False, label=’Logz’): Whether to apply log scaling to the z-axis.
rescale_discrete_levels = param.Boolean(bounds=(0, 1), default=True, label=’Rescale discrete levels’): If cnorm='eq_hist and there are only a few discrete values, then rescale_discrete_levels=True decreases the lower limit of the autoranged span so that the values are rendering towards the (more visible) top of the palette, thus avoiding washout of the lower values. Has no effect if cnorm!=`eq_hist.
symmetric = param.Boolean(bounds=(0, 1), default=False, label=’Symmetric’): Whether to make the colormap symmetric around zero.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.element.CompositeElementPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.ElementPlot

A CompositeElementPlot is an Element plot type that coordinates drawing of multiple glyphs.

Parameters inherited from:

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.element.ElementPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.plot.BokehPlot, holoviews.plotting.plot.GenericElementPlot

Parameters inherited from:

fontsize = param.Parameter(allow_None=True, default={‘title’: ‘12pt’}, label=’Fontsize’): Specifies various fontsizes of the displayed text. Finer control is available by supplying a dictionary where any unmentioned keys reverts to the default sizes, e.g: {‘ticks’: ‘20pt’, ‘title’: ‘15pt’, ‘ylabel’: ‘5px’, ‘xlabel’: ‘5px’}
toolbar = param.ObjectSelector(default=’right’, label=’Toolbar’, objects=[‘above’, ‘below’, ‘left’, ‘right’, ‘disable’, None]): The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.
width = param.Integer(allow_None=True, bounds=(0, None), default=300, inclusive_bounds=(True, True), label=’Width’): The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.
height = param.Integer(allow_None=True, bounds=(0, None), default=300, inclusive_bounds=(True, True), label=’Height’): The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.
active_tools = param.List(allow_None=True, bounds=(0, None), label=’Active tools’): Allows specifying which tools are active by default. Note that only one tool per gesture type can be active, e.g. both ‘pan’ and ‘box_zoom’ are drag tools, so if both are listed only the last one will be active. As a default ‘pan’ and ‘wheel_zoom’ will be used if the tools are enabled.
align = param.ObjectSelector(default=’start’, label=’Align’, objects=[‘start’, ‘center’, ‘end’]): Alignment (vertical or horizontal) of the plot in a layout.
autorange = param.ObjectSelector(label=’Autorange’, objects=[‘x’, ‘y’]): Whether to auto-range along either the x- or y-axis, i.e. when panning or zooming along the orthogonal axis it will ensure all the data along the selected axis remains visible.
border = param.Number(default=10, inclusive_bounds=(True, True), label=’Border’): Minimum border around plot.
aspect = param.Parameter(allow_None=True, label=’Aspect’): The aspect ratio mode of the plot. By default, a plot may select its own appropriate aspect ratio but sometimes it may be necessary to force a square aspect ratio (e.g. to display the plot as an element of a grid). The modes ‘auto’ and ‘equal’ correspond to the axis modes of the same name in matplotlib, a numeric value specifying the ratio between plot width and height may also be passed. To control the aspect ratio between the axis scales use the data_aspect option instead.
data_aspect = param.Number(allow_None=True, inclusive_bounds=(True, True), label=’Data aspect’): Defines the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.
frame_width = param.Integer(allow_None=True, bounds=(0, None), inclusive_bounds=(True, True), label=’Frame width’): The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.
frame_height = param.Integer(allow_None=True, bounds=(0, None), inclusive_bounds=(True, True), label=’Frame height’): The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.
min_width = param.Integer(allow_None=True, bounds=(0, None), inclusive_bounds=(True, True), label=’Min width’): Minimal width of the component (in pixels) if width is adjustable.
min_height = param.Integer(allow_None=True, bounds=(0, None), inclusive_bounds=(True, True), label=’Min height’): Minimal height of the component (in pixels) if height is adjustable.
max_width = param.Integer(allow_None=True, bounds=(0, None), inclusive_bounds=(True, True), label=’Max width’): Minimal width of the component (in pixels) if width is adjustable.
max_height = param.Integer(allow_None=True, bounds=(0, None), inclusive_bounds=(True, True), label=’Max height’): Minimal height of the component (in pixels) if height is adjustable.
margin = param.Parameter(allow_None=True, label=’Margin’): Allows to create additional space around the component. May be specified as a two-tuple of the form (vertical, horizontal) or a four-tuple (top, right, bottom, left).

responsive = param.ObjectSelector(default=False, label=’Responsive’, objects=[False, True, ‘width’, ‘height’])

gridstyle = param.Dict(class_=<class ‘dict’>, default={}, label=’Gridstyle’): Allows customizing the grid style, e.g. grid_line_color defines the line color for both grids while xgrid_line_color exclusively customizes the x-axis grid lines.
labelled = param.List(bounds=(0, None), default=[‘x’, ‘y’], label=’Labelled’): Whether to plot the ‘x’ and ‘y’ labels.
lod = param.Dict(class_=<class ‘dict’>, default={‘factor’: 10, ‘interval’: 300, ‘threshold’: 2000, ‘timeout’: 500}, label=’Lod’): Bokeh plots offer “Level of Detail” (LOD) capability to accommodate large (but not huge) amounts of data. The available options are: * factor : Decimation factor to use when applying decimation. * interval : Interval (in ms) downsampling will be enabled after an interactive event. * threshold : Number of samples before downsampling is enabled. * timeout : Timeout (in ms) for checking whether interactive tool events are still occurring.
show_frame = param.Boolean(bounds=(0, 1), default=True, label=’Show frame’): Whether or not to show a complete frame around the plot.
shared_axes = param.Boolean(bounds=(0, 1), default=True, label=’Shared axes’): Whether to invert the share axes across plots for linked panning and zooming.
default_tools = param.List(bounds=(0, None), default=[‘save’, ‘pan’, ‘wheel_zoom’, ‘box_zoom’, ‘reset’], label=’Default tools’): A list of plugin tools to use on the plot.
tools = param.List(bounds=(0, None), default=[], label=’Tools’): A list of plugin tools to use on the plot.
xformatter = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>), label=’Xformatter’): Formatter for ticks along the x-axis.
yformatter = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>), label=’Yformatter’): Formatter for ticks along the x-axis.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)[source]#: Computes the aspect ratio of the plot

get_data(element, ranges, style)#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)[source]#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)[source]#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)[source]#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.element.LegendPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.ElementPlot

Parameters inherited from:

legend_cols = param.Integer(bounds=(0, None), default=0, inclusive_bounds=(True, True), label=’Legend cols’): Number of columns for legend.
legend_labels = param.Dict(allow_None=True, class_=<class ‘dict’>, label=’Legend labels’): Label overrides.
legend_muted = param.Boolean(bounds=(0, 1), default=False, label=’Legend muted’): Controls whether the legend entries are muted by default.
legend_offset = param.NumericTuple(default=(0, 0), label=’Legend offset’, length=2): If legend is placed outside the axis, this determines the (width, height) offset in pixels from the original position.
legend_position = param.ObjectSelector(default=’top_right’, label=’Legend position’, objects=[‘top_right’, ‘top_left’, ‘bottom_left’, ‘bottom_right’, ‘right’, ‘left’, ‘top’, ‘bottom’]): Allows selecting between a number of predefined legend position options. The predefined options may be customized in the legend_specs class attribute.
legend_opts = param.Dict(class_=<class ‘dict’>, default={}, label=’Legend opts’): Allows setting specific styling options for the colorbar.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.element.OverlayPlot(overlay, ranges=None, batched=True, keys=None, group_counter=None, **params)[source]#

Bases: holoviews.plotting.plot.GenericOverlayPlot, holoviews.plotting.bokeh.element.LegendPlot

Parameters inherited from:

tabs = param.Boolean(bounds=(0, 1), default=False, label=’Tabs’): Whether to display overlaid plots in separate panes
multiple_legends = param.Boolean(bounds=(0, 1), default=False, label=’Multiple legends’): Whether to split the legend for subplots into multiple legends.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(overlay, ranges, range_type='combined')#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None)[source]#: Initialize the matplotlib figure.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, element=None)[source]#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

`geometry` Module#

Inheritance diagram of holoviews.plotting.bokeh.geometry

class holoviews.plotting.bokeh.geometry.RectanglesPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.mixins.GeomMixin, holoviews.plotting.bokeh.element.LegendPlot, holoviews.plotting.bokeh.element.ColorbarPlot

Parameters inherited from:

selected = param.List(allow_None=True, bounds=(0, None), label=’Selected’): The current selection as a list of integers corresponding to the selected items.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined')#: Use first two key dimensions to set names, and all four to set the data range.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.geometry.SegmentPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.mixins.GeomMixin, holoviews.plotting.bokeh.element.ColorbarPlot

Segments are lines in 2D space where each two each dimensions specify a (x, y) node of the line.

Parameters inherited from:

selected = param.List(allow_None=True, bounds=(0, None), label=’Selected’): The current selection as a list of integers corresponding to the selected items.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined')#: Use first two key dimensions to set names, and all four to set the data range.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

`graphs` Module#

Inheritance diagram of holoviews.plotting.bokeh.graphs

class holoviews.plotting.bokeh.graphs.ChordPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.mixins.ChordMixin, holoviews.plotting.bokeh.graphs.GraphPlot

Parameters inherited from:

show_frame = param.Boolean(bounds=(0, 1), default=False, label=’Show frame’): Whether or not to show a complete frame around the plot.
labels = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘holoviews.util.transform.dim’>), label=’Labels’): The dimension or dimension value transform used to draw labels from.
label_index = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘int’>), label=’Label index’): Index of the dimension from which the node labels will be drawn

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined')#: A Chord plot is always drawn on a unit circle.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.graphs.GraphPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.CompositeElementPlot, holoviews.plotting.bokeh.element.ColorbarPlot, holoviews.plotting.bokeh.element.LegendPlot

Parameters inherited from:

tools = param.List(bounds=(0, None), default=[‘hover’, ‘tap’], label=’Tools’): A list of plugin tools to use on the plot.
arrowhead_length = param.Number(default=0.025, inclusive_bounds=(True, True), label=’Arrowhead length’): If directed option is enabled this determines the length of the arrows as fraction of the overall extent of the graph.
directed = param.Boolean(bounds=(0, 1), default=False, label=’Directed’): Whether to draw arrows on the graph edges to indicate the directionality of each edge.
selection_policy = param.ObjectSelector(default=’nodes’, label=’Selection policy’, objects=[‘edges’, ‘nodes’, None]): Determines policy for inspection of graph components, i.e. whether to highlight nodes or edges when selecting connected edges and nodes respectively.
inspection_policy = param.ObjectSelector(default=’nodes’, label=’Inspection policy’, objects=[‘edges’, ‘nodes’, None]): Determines policy for inspection of graph components, i.e. whether to highlight nodes or edges when hovering over connected edges and nodes respectively.
color_index = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘int’>), label=’Color index’): Deprecated in favor of color style mapping, e.g. node_color=dim(‘color’)
edge_color_index = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘int’>), label=’Edge color index’): Deprecated in favor of color style mapping, e.g. edge_color=dim(‘color’)

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined')[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.graphs.NodePlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.chart.PointPlot

Simple subclass of PointPlot which hides x, y position on hover.

Parameters inherited from:

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

size_fn = <ufunc 'absolute'>#

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.graphs.TriMeshPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.graphs.GraphPlot

Parameters inherited from:

filled = param.Boolean(bounds=(0, 1), default=False, label=’Filled’): Whether the triangles should be drawn as filled.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined')#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

`heatmap` Module#

Inheritance diagram of holoviews.plotting.bokeh.heatmap

class holoviews.plotting.bokeh.heatmap.HeatMapPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.ColorbarPlot

Parameters inherited from:

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0, label=’Padding’): Fraction by which to increase auto-ranged extents to make datapoints more visible around borders. To compute padding, the axis whose screen size is largest is chosen, and the range of that axis is increased by the specified fraction along each axis. Other axes are then padded ensuring that the amount of screen space devoted to padding is equal for all axes. If specified as a tuple, the int or float values in the tuple will be used for padding in each axis, in order (x,y or x,y,z). For example, for padding=0.2 on a 800x800-pixel plot, an x-axis with the range [0,10] will be padded by 20% to be [-1,11], while a y-axis with a range [0,1000] will be padded to be [-100,1100], which should make the padding be approximately the same number of pixels. But if the same plot is changed to have a height of only 200, the y-range will then be [-400,1400] so that the y-axis padding will still match that of the x-axis. It is also possible to declare non-equal padding value for the lower and upper bound of an axis by supplying nested tuples, e.g. padding=(0.1, (0, 0.1)) will pad the x-axis lower and upper bound as well as the y-axis upper bound by a fraction of 0.1 while the y-axis lower bound is not padded at all.
show_legend = param.Boolean(bounds=(0, 1), default=False, label=’Show legend’): Whether to show legend for the plot.
clipping_colors = param.Dict(class_=<class ‘dict’>, default={‘NaN’: ‘white’}, label=’Clipping colors’): Dictionary to specify colors for clipped values. Allows setting color for NaN values and for values above and below the min and max value. The min, max, or NaN color may specify an RGB(A) color as a either (1) a color hex string of the form #FFFFFF or #FFFFFFFF, (2) a length-3 or length-4 tuple specifying values in the range 0-1, or (3) a named HTML color.
radial = param.Boolean(bounds=(0, 1), default=False, label=’Radial’): Whether the HeatMap should be radial
xmarks = param.Parameter(allow_None=True, label=’Xmarks’): Add separation lines to the heatmap for better readability. By default, does not show any separation lines. If parameter is of type integer, draws the given amount of separations lines spread across heatmap. If parameter is of type list containing integers, show separation lines at given indices. If parameter is of type tuple, draw separation lines at given categorical values. If parameter is of type function, draw separation lines where function returns True for passed heatmap category.
ymarks = param.Parameter(allow_None=True, label=’Ymarks’): Add separation lines to the heatmap for better readability. By default, does not show any separation lines. If parameter is of type integer, draws the given amount of separations lines spread across heatmap. If parameter is of type list containing integers, show separation lines at given indices. If parameter is of type tuple, draw separation lines at given categorical values. If parameter is of type function, draw separation lines where function returns True for passed heatmap category.

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.heatmap.RadialHeatMapPlot(*args, **kwargs)[source]#

Bases: holoviews.plotting.bokeh.element.CompositeElementPlot, holoviews.plotting.bokeh.element.ColorbarPlot

Parameters inherited from:

yrotation = param.Number(bounds=(0, 360), default=90, inclusive_bounds=(True, True), label=’Yrotation’): Define angle along which yticks/annulars are shown. By default, yticks are drawn like a regular y-axis.
xticks = param.Parameter(default=4, label=’Xticks’): Ticks along x-axis/segments specified as an integer, explicit list of ticks or function. If None, no ticks are shown.
yticks = param.Parameter(default=4, label=’Yticks’): Ticks along y-axis/annulars specified as an integer, explicit list of ticks or function. If None, no ticks are shown.
show_frame = param.Boolean(bounds=(0, 1), default=False, label=’Show frame’): Whether or not to show a complete frame around the plot.
clipping_colors = param.Dict(class_=<class ‘dict’>, default={‘NaN’: ‘white’}, label=’Clipping colors’): Dictionary to specify colors for clipped values. Allows setting color for NaN values and for values above and below the min and max value. The min, max, or NaN color may specify an RGB(A) color as a either (1) a color hex string of the form #FFFFFF or #FFFFFFFF, (2) a length-3 or length-4 tuple specifying values in the range 0-1, or (3) a named HTML color.
start_angle = param.Number(default=1.5707963267948966, inclusive_bounds=(True, True), label=’Start angle’): Define starting angle of the first annulus segment. By default, begins at 12 o’clock.
radius_inner = param.Number(bounds=(0, 0.5), default=0.1, inclusive_bounds=(True, True), label=’Radius inner’): Define the radius fraction of inner, empty space.
radius_outer = param.Number(bounds=(0, 1), default=0.05, inclusive_bounds=(True, True), label=’Radius outer’): Define the radius fraction of outer space including the labels.
xmarks = param.Parameter(allow_None=True, label=’Xmarks’): Add separation lines between segments for better readability. By default, does not show any separation lines. If parameter is of type integer, draws the given amount of separations lines spread across radial heatmap. If parameter is of type list containing integers, show separation lines at given indices. If parameter is of type tuple, draw separation lines at given segment values. If parameter is of type function, draw separation lines where function returns True for passed segment value.
ymarks = param.Parameter(allow_None=True, label=’Ymarks’): Add separation lines between annulars for better readability. By default, does not show any separation lines. If parameter is of type integer, draws the given amount of separations lines spread across radial heatmap. If parameter is of type list containing integers, show separation lines at given indices. If parameter is of type tuple, draw separation lines at given annular values. If parameter is of type function, draw separation lines where function returns True for passed annular value.
max_radius = param.Number(default=0.5, inclusive_bounds=(True, True), label=’Max radius’): Define the maximum radius which is used for the x and y range extents.
radial = param.Boolean(bounds=(0, 1), default=True, label=’Radial’): Whether the HeatMap should be radial

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_default_mapping(z, cmapper)[source]#: Create dictionary containing default ColumnDataSource glyph to data mappings.

get_extents(view, ranges, range_type='combined')[source]#: Supply custom, static extents because radial heatmaps always have the same boundaries.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

`hex_tiles` Module#

Inheritance diagram of holoviews.plotting.bokeh.hex_tiles

class holoviews.plotting.bokeh.hex_tiles.HexTilesPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.ColorbarPlot

Parameters inherited from:

aggregator = param.ClassSelector(class_=(<class ‘collections.abc.Callable’>, <class ‘tuple’>), label=’Aggregator’): Aggregation function or dimension transform used to compute bin values. Defaults to np.size to count the number of values in each bin.
gridsize = param.ClassSelector(class_=(<class ‘int’>, <class ‘tuple’>), default=50, label=’Gridsize’): Number of hexagonal bins along x- and y-axes. Defaults to uniform sampling along both axes when setting and integer but independent bin sampling can be specified a tuple of integers corresponding to the number of bins along each axis.
min_count = param.Number(allow_None=True, inclusive_bounds=(True, True), label=’Min count’): The display threshold before a bin is shown, by default bins with a count of less than 1 are hidden.
orientation = param.ObjectSelector(default=’pointy’, label=’Orientation’, objects=[‘flat’, ‘pointy’]): The orientation of hexagon bins. By default the pointy side is on top.
color_index = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘int’>), default=2, label=’Color index’): Deprecated in favor of color style mapping, e.g. color=dim(‘color’)
max_scale = param.Number(bounds=(0, None), default=0.9, inclusive_bounds=(True, True), label=’Max scale’): When size_index is enabled this defines the maximum size of each bin relative to uniform tile size, i.e. for a value of 1, the largest bin will match the size of bins when scaling is disabled. Setting value larger than 1 will result in overlapping bins.
min_scale = param.Number(bounds=(0, None), default=0, inclusive_bounds=(True, True), label=’Min scale’): When size_index is enabled this defines the minimum size of each bin relative to uniform tile size, i.e. for a value of 1, the smallest bin will match the size of bins when scaling is disabled. Setting value larger than 1 will result in overlapping bins.
size_index = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘int’>), label=’Size index’): Index of the dimension from which the sizes will the drawn.

aggregator(axis=None)#

Return the number of elements along a given axis.

aarray_like: Input data.
axisint, optional: Axis along which the elements are counted. By default, give the total number of elements.

element_countint: Number of elements along the specified axis.

shape : dimensions of array ndarray.shape : dimensions of array ndarray.size : number of elements in array

>>> a = np.array([[1,2,3],[4,5,6]])
>>> np.size(a)
6
>>> np.size(a,1)
3
>>> np.size(a,0)
2

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined')[source]#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.hex_tiles.hex_binning(*args, **params)[source]#

Bases: holoviews.core.operation.Operation

Applies hex binning by computing aggregates on a hexagonal grid.

Should not be user facing as the returned element is not directly usable.

Parameters inherited from:

aggregator = param.ClassSelector(class_=(<class ‘collections.abc.Callable’>, <class ‘tuple’>), label=’Aggregator’): Aggregation function or dimension transform used to compute bin values. Defaults to np.size to count the number of values in each bin.

gridsize = param.ClassSelector(class_=(<class ‘int’>, <class ‘tuple’>), default=50, label=’Gridsize’)

invert_axes = param.Boolean(bounds=(0, 1), default=False, label=’Invert axes’)

min_count = param.Number(allow_None=True, inclusive_bounds=(True, True), label=’Min count’)

orientation = param.ObjectSelector(default=’pointy’, label=’Orientation’, objects=[‘flat’, ‘pointy’])

aggregator(axis=None)#

Return the number of elements along a given axis.

aarray_like: Input data.
axisint, optional: Axis along which the elements are counted. By default, give the total number of elements.

element_countint: Number of elements along the specified axis.

shape : dimensions of array ndarray.shape : dimensions of array ndarray.size : number of elements in array

>>> a = np.array([[1,2,3],[4,5,6]])
>>> np.size(a)
6
>>> np.size(a,1)
3
>>> np.size(a,0)
2

classmethod get_overlay_bounds(overlay)#: Returns the extents if all the elements of an overlay agree on a consistent extents, otherwise raises an exception.

classmethod get_overlay_label(overlay, default_label='')#: Returns a label if all the elements of an overlay agree on a consistent label, otherwise returns the default label.

instance(**params)#: Return an instance of this class, copying parameters from any existing instance provided.

process_element(element, key, **params)#: The process_element method allows a single element to be operated on given an externally supplied key.

script_repr(imports=[], prefix=' ')#: Same as Parameterized.script_repr, except that X.classname(Y is replaced with X.classname.instance(Y

classmethod search(element, pattern)#

Helper method that returns a list of elements that match the given path pattern of form {type}.{group}.{label}.

The input may be a Layout, an Overlay type or a single Element.

`links` Module#

Inheritance diagram of holoviews.plotting.bokeh.links

class holoviews.plotting.bokeh.links.DataLinkCallback(root_model, link, source_plot, target_plot)[source]#

Bases: holoviews.plotting.bokeh.links.LinkCallback

Merges the source and target ColumnDataSource

classmethod find_link(plot, link=None)#: Searches a GenericElementPlot for a Link.

classmethod find_links(root_plot)#: Traverses the supplied plot and searches for any Links on the plotted objects.

validate()#: Should be subclassed to check if the source and target plots are compatible to perform the linking.

class holoviews.plotting.bokeh.links.RangeToolLinkCallback(root_model, link, source_plot, target_plot)[source]#

Bases: holoviews.plotting.bokeh.links.LinkCallback

Attaches a RangeTool to the source plot and links it to the specified axes on the target plot

classmethod find_link(plot, link=None)#: Searches a GenericElementPlot for a Link.

classmethod find_links(root_plot)#: Traverses the supplied plot and searches for any Links on the plotted objects.

validate()#: Should be subclassed to check if the source and target plots are compatible to perform the linking.

class holoviews.plotting.bokeh.links.RectanglesTableLinkCallback(root_model, link, source_plot, target_plot=None)[source]#

Bases: holoviews.plotting.bokeh.links.DataLinkCallback

classmethod find_link(plot, link=None)#: Searches a GenericElementPlot for a Link.

classmethod find_links(root_plot)#: Traverses the supplied plot and searches for any Links on the plotted objects.

validate()#: Should be subclassed to check if the source and target plots are compatible to perform the linking.

`path` Module#

Inheritance diagram of holoviews.plotting.bokeh.path

class holoviews.plotting.bokeh.path.ContourPlot(*args, **params)[source]#

Bases: holoviews.plotting.bokeh.path.PathPlot

Parameters inherited from:

show_legend = param.Boolean(bounds=(0, 1), default=False, label=’Show legend’): Whether to show legend for the plot.
selected = param.List(allow_None=True, bounds=(0, None), label=’Selected’): The current selection as a list of integers corresponding to the selected items.
color_index = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘int’>), default=0, label=’Color index’): Deprecated in favor of color style mapping, e.g. color=dim(‘color’)

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.path.PathPlot(element, plot=None, **params)[source]#

Bases: holoviews.plotting.bokeh.element.LegendPlot, holoviews.plotting.bokeh.element.ColorbarPlot

Parameters inherited from:

show_legend = param.Boolean(bounds=(0, 1), default=False, label=’Show legend’): Whether to show legend for the plot.
selected = param.List(allow_None=True, bounds=(0, None), label=’Selected’): The current selection as a list of integers corresponding to the selected items.
color_index = param.ClassSelector(allow_None=True, class_=(<class ‘str’>, <class ‘int’>), label=’Color index’): Deprecated in favor of color style mapping, e.g. color=dim(‘color’)

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)[source]#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

class holoviews.plotting.bokeh.path.PolygonPlot(*args, **params)[source]#

Bases: holoviews.plotting.bokeh.path.ContourPlot

Parameters inherited from:

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

property framewise#: Property to determine whether the current frame should have framewise normalization enabled. Required for bokeh plotting classes to determine whether to send updated ranges for each frame.

get_aspect(xspan, yspan)#: Computes the aspect ratio of the plot

get_data(element, ranges, style)#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

get_extents(element, ranges, range_type='combined', xdim=None, ydim=None, zdim=None)#

Gets the extents for the axes from the current Element. The globally computed ranges can optionally override the extents.

The extents are computed by combining the data ranges, extents and dimension ranges. Each of these can be obtained individually by setting the range_type to one of:

‘data’: Just the data ranges
‘extents’: Element.extents
‘soft’: Dimension.soft_range values
‘hard’: Dimension.range values

To obtain the combined range, which includes range padding the default may be used:

‘combined’: All the range types combined and padding applied

This allows Overlay plots to obtain each range and combine them appropriately for all the objects in the overlay.

get_padding(obj, extents)#: Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)#: Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

initialize_plot(ranges=None, plot=None, plots=None, source=None)#: Initializes a new plot object with the last available frame.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

model_changed(model)#: Determines if the bokeh model was just changed on the frontend. Useful to suppress boomeranging events, e.g. when the frontend just sent an update to the x_range this should not trigger an update on the backend.

push()#: Pushes plot updates to the frontend.

refresh(**kwargs)#: Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)#: Sets the root model on all subplots.

property state#: The plotting state that gets updated via the update method and used by the renderer to generate output.

sync_sources()#: Syncs data sources between Elements, which draw data from the same object.

traverse(fn=None, specs=None, full_breadth=True)#: Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)#: Update the internal state of the Plot to represent the given key tuple (where integers represent frames). Returns this state.

update_frame(key, ranges=None, plot=None, element=None)#: Updates an existing plot with data corresponding to the key.

`plot` Module#

Inheritance diagram of holoviews.plotting.bokeh.plot

class holoviews.plotting.bokeh.plot.AdjointLayoutPlot(layout, layout_type, subplots, **params)[source]#

Bases: holoviews.plotting.bokeh.plot.BokehPlot, holoviews.plotting.plot.GenericAdjointLayoutPlot

Parameters inherited from:

cleanup()#: Cleans up references to the plot after the plot has been deleted. Traverses through all plots cleaning up Callbacks and Stream subscribers.

compute_ranges(obj, key, ranges)#: Given an object, a specific key, and the normalization options, this method will find the specified normalization options on the appropriate OptionTree, group the elements according to the selected normalization option (i.e. either per frame or over the whole animation) and finally compute the dimension ranges in each group. The new set of ranges is returned.

property current_handles#: Should return a list of plot objects that have changed and should be updated.

get_data(element, ranges, style)#: Returns the data from an element in the appropriate format for initializing or updating a ColumnDataSource and a dictionary which maps the expected keywords arguments of a glyph to the column in the datasource.

initialize_plot(ranges=None, plots=[])[source]#: Plot all the views contained in the AdjointLayout Object using axes appropriate to the layout configuration. All the axes are supplied by LayoutPlot - the purpose of the call is to invoke subplots with correct options and styles and hide any empty axes as necessary.

property link_sources#: Returns potential Link or Stream sources.

matches(spec)#: Matches a specification against the current Plot.

push()

holoviews.bokeh Package#

bokeh Package#

annotation Module#

callbacks Module#

chart Module#

element Module#

geometry Module#

graphs Module#

heatmap Module#

hex_tiles Module#

links Module#

path Module#

plot Module#

`bokeh` Package#

`annotation` Module#

`callbacks` Module#

`chart` Module#

`element` Module#

`geometry` Module#

`graphs` Module#

`heatmap` Module#

`hex_tiles` Module#

`links` Module#

`path` Module#

`plot` Module#