holoviews.bokeh Package


bokeh Package


annotation Module

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"holoviews.plotting.bokeh.element.AnnotationPlot" -> "holoviews.plotting.bokeh.annotation.BoxAnnotationPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.annotation.DivPlot" [URL="#holoviews.plotting.bokeh.annotation.DivPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.plot.BokehPlot" -> "holoviews.plotting.bokeh.annotation.DivPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.plot.GenericElementPlot" -> "holoviews.plotting.bokeh.annotation.DivPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.element.AnnotationPlot" -> "holoviews.plotting.bokeh.annotation.DivPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.annotation.LabelsPlot" [URL="#holoviews.plotting.bokeh.annotation.LabelsPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.element.ColorbarPlot" -> "holoviews.plotting.bokeh.annotation.LabelsPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.element.AnnotationPlot" -> "holoviews.plotting.bokeh.annotation.LabelsPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.annotation.LineAnnotationPlot" [URL="#holoviews.plotting.bokeh.annotation.LineAnnotationPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.element.ElementPlot" -> "holoviews.plotting.bokeh.annotation.LineAnnotationPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.element.AnnotationPlot" -> "holoviews.plotting.bokeh.annotation.LineAnnotationPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.annotation.SlopePlot" [URL="#holoviews.plotting.bokeh.annotation.SlopePlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.element.ElementPlot" -> "holoviews.plotting.bokeh.annotation.SlopePlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.element.AnnotationPlot" -> "holoviews.plotting.bokeh.annotation.SlopePlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.annotation.SplinePlot" [URL="#holoviews.plotting.bokeh.annotation.SplinePlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Draw the supplied Spline annotation (see Spline docstring)."]; "holoviews.plotting.bokeh.element.ElementPlot" -> "holoviews.plotting.bokeh.annotation.SplinePlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.element.AnnotationPlot" -> "holoviews.plotting.bokeh.annotation.SplinePlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.annotation.TextPlot" [URL="#holoviews.plotting.bokeh.annotation.TextPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.element.ElementPlot" -> "holoviews.plotting.bokeh.annotation.TextPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.element.AnnotationPlot" -> "holoviews.plotting.bokeh.annotation.TextPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.element.AnnotationPlot" [URL="#holoviews.plotting.bokeh.element.AnnotationPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Mix-in plotting subclass for AnnotationPlots which do not have a legend."]; "holoviews.plotting.bokeh.element.ColorbarPlot" [URL="#holoviews.plotting.bokeh.element.ColorbarPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="ColorbarPlot provides methods to create colormappers and colorbar"]; "holoviews.plotting.bokeh.element.ElementPlot" -> "holoviews.plotting.bokeh.element.ColorbarPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.element.CompositeElementPlot" [URL="#holoviews.plotting.bokeh.element.CompositeElementPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="A CompositeElementPlot is an Element plot type that coordinates"]; "holoviews.plotting.bokeh.element.ElementPlot" -> "holoviews.plotting.bokeh.element.CompositeElementPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.element.ElementPlot" [URL="#holoviews.plotting.bokeh.element.ElementPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.plot.BokehPlot" -> "holoviews.plotting.bokeh.element.ElementPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.plot.GenericElementPlot" -> "holoviews.plotting.bokeh.element.ElementPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.plot.BokehPlot" [URL="#holoviews.plotting.bokeh.plot.BokehPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Plotting baseclass for the Bokeh backends, implementing the basic"]; "holoviews.plotting.plot.DimensionedPlot" -> "holoviews.plotting.bokeh.plot.BokehPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.plot.CallbackPlot" -> "holoviews.plotting.bokeh.plot.BokehPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.plot.CallbackPlot" [fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)"]; "holoviews.plotting.plot.DimensionedPlot" [URL="holoviews.plotting.html#holoviews.plotting.plot.DimensionedPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="DimensionedPlot implements a number of useful methods"]; "holoviews.plotting.plot.Plot" -> "holoviews.plotting.plot.DimensionedPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.plot.GenericElementPlot" [URL="holoviews.plotting.html#holoviews.plotting.plot.GenericElementPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Plotting baseclass to render contents of an Element. Implements"]; "holoviews.plotting.plot.DimensionedPlot" -> "holoviews.plotting.plot.GenericElementPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.plot.Plot" [URL="holoviews.plotting.html#holoviews.plotting.plot.Plot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Base class of all Plot classes in HoloViews, designed to be"]; "param.parameterized.Parameterized" -> "holoviews.plotting.plot.Plot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "param.parameterized.Parameterized" [fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",tooltip="params(name=String)"]; }
class holoviews.plotting.bokeh.annotation.ArrowPlot(element, plot=None, **params)[source]

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

fontsize = param.Parameter(default={‘title’: ‘12pt’})

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’}

fontscale = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Scales the size of all fonts.

show_title = param.Boolean(bounds=(0, 1), default=True)

Whether to display the plot title.

title = param.String(default=’{label} {group} {dimensions}’)

The formatting string for the title of this plot, allows defining a label group separator and dimension labels.

title_format = param.String()

Alias for title.

normalize = param.Boolean(bounds=(0, 1), default=True)

Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.

projection = param.Parameter()

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

apply_ranges = param.Boolean(bounds=(0, 1), default=True)

Whether to compute the plot bounds from the data itself.

apply_extents = param.Boolean(bounds=(0, 1), default=True)

Whether to apply extent overrides on the Elements

bgcolor = param.ClassSelector(class_=(<class ‘str’>, <class ‘tuple’>))

If set bgcolor overrides the background color of the axis.

default_span = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=2.0)

Defines the span of an axis if the axis range is zero, i.e. if the lower and upper end of an axis are equal or no range is defined at all. For example if there is a single datapoint at 0 a default_span of 2.0 will result in axis ranges spanning from -1 to 1.

hooks = param.HookList(bounds=(0, None), default=[])

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.

invert_axes = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the x- and y-axis

invert_xaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot y-axis.

finalize_hooks = param.HookList(bounds=(0, None), default=[])

Deprecated; use hooks options instead.

logx = param.Boolean(bounds=(0, 1), default=False)

Whether the x-axis of the plot will be a log axis.

logy = param.Boolean(bounds=(0, 1), default=False)

Whether the y-axis of the plot will be a log axis.

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0.1)

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=True)

Whether to show legend for the plot.

show_grid = param.Boolean(bounds=(0, 1), default=False)

Whether to show a Cartesian grid on the plot.

xaxis = param.ObjectSelector(default=’bottom’, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None, True, False])

Whether and where to display the xaxis. The “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=’left’, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None, True, False])

Whether and where to display the yaxis. The “bare” options allow suppressing all axis labels, including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’, ‘left-bare’ and ‘right-bare’.

xlabel = param.String()

An explicit override of the x-axis label, if set takes precedence over the dimension label.

ylabel = param.String()

An explicit override of the y-axis label, if set takes precedence over the dimension label.

xlim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

ylim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

zlim = param.Tuple(default=(nan, nan), length=2)

User-specified z-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

xrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the xticks.

yrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the yticks.

xticks = param.Parameter()

Ticks along x-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

yticks = param.Parameter()

Ticks along y-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

shared_datasource = param.Boolean(bounds=(0, 1), default=True)

Whether Elements drawing the data from the same object should share their Bokeh data source allowing for linked brushing and other linked behaviors.

toolbar = param.ObjectSelector(default=’right’, objects=[‘above’, ‘below’, ‘left’, ‘right’, ‘disable’, None])

The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.

width = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

height = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

active_tools = param.List(bounds=(0, None), default=[])

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.

align = param.ObjectSelector(objects=[‘start’, ‘center’, ‘end’])

Alignment (vertical or horizontal) of the plot in a layout.

border = param.Number(default=10, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimum border around plot.

aspect = param.Parameter()

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(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Defines the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.

frame_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

frame_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

min_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

min_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

max_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

max_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

margin = param.Parameter()

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, objects=[False, True, ‘width’, ‘height’])

gridstyle = param.Dict(class_=<class ‘dict’>, default={})

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’])

Whether to plot the ‘x’ and ‘y’ labels.

lod = param.Dict(class_=<class ‘dict’>, default={‘factor’: 10, ‘interval’: 300, ‘threshold’: 2000, ‘timeout’: 500})

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)

Whether or not to show a complete frame around the plot.

shared_axes = param.Boolean(bounds=(0, 1), default=True)

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’])

A list of plugin tools to use on the plot.

tools = param.List(bounds=(0, None), default=[])

A list of plugin tools to use on the plot.

xformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

yformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

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.

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.ArrowPlot'>)
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_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.ArrowPlot'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.ArrowPlot'>)
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.

inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.ArrowPlot'>)

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

message(**kwargs)

Inspect .param.message method for the full docstring

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.

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.ArrowPlot'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

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.

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.ArrowPlot'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.ArrowPlot'>)
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.

state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

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.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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

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

fontsize = param.Parameter(default={‘title’: ‘12pt’})

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’}

fontscale = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Scales the size of all fonts.

show_title = param.Boolean(bounds=(0, 1), default=True)

Whether to display the plot title.

title = param.String(default=’{label} {group} {dimensions}’)

The formatting string for the title of this plot, allows defining a label group separator and dimension labels.

title_format = param.String()

Alias for title.

normalize = param.Boolean(bounds=(0, 1), default=True)

Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.

projection = param.Parameter()

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

apply_ranges = param.Boolean(bounds=(0, 1), default=False)

Whether to include the annotation in axis range calculations.

apply_extents = param.Boolean(bounds=(0, 1), default=True)

Whether to apply extent overrides on the Elements

bgcolor = param.ClassSelector(class_=(<class ‘str’>, <class ‘tuple’>))

If set bgcolor overrides the background color of the axis.

default_span = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=2.0)

Defines the span of an axis if the axis range is zero, i.e. if the lower and upper end of an axis are equal or no range is defined at all. For example if there is a single datapoint at 0 a default_span of 2.0 will result in axis ranges spanning from -1 to 1.

hooks = param.HookList(bounds=(0, None), default=[])

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.

invert_axes = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the x- and y-axis

invert_xaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot y-axis.

finalize_hooks = param.HookList(bounds=(0, None), default=[])

Deprecated; use hooks options instead.

logx = param.Boolean(bounds=(0, 1), default=False)

Whether the x-axis of the plot will be a log axis.

logy = param.Boolean(bounds=(0, 1), default=False)

Whether the y-axis of the plot will be a log axis.

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0.1)

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=True)

Whether to show legend for the plot.

show_grid = param.Boolean(bounds=(0, 1), default=False)

Whether to show a Cartesian grid on the plot.

xaxis = param.ObjectSelector(default=’bottom’, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None, True, False])

Whether and where to display the xaxis. The “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=’left’, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None, True, False])

Whether and where to display the yaxis. The “bare” options allow suppressing all axis labels, including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’, ‘left-bare’ and ‘right-bare’.

xlabel = param.String()

An explicit override of the x-axis label, if set takes precedence over the dimension label.

ylabel = param.String()

An explicit override of the y-axis label, if set takes precedence over the dimension label.

xlim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

ylim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

zlim = param.Tuple(default=(nan, nan), length=2)

User-specified z-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

xrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the xticks.

yrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the yticks.

xticks = param.Parameter()

Ticks along x-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

yticks = param.Parameter()

Ticks along y-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

shared_datasource = param.Boolean(bounds=(0, 1), default=True)

Whether Elements drawing the data from the same object should share their Bokeh data source allowing for linked brushing and other linked behaviors.

toolbar = param.ObjectSelector(default=’right’, objects=[‘above’, ‘below’, ‘left’, ‘right’, ‘disable’, None])

The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.

width = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

height = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

active_tools = param.List(bounds=(0, None), default=[])

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.

align = param.ObjectSelector(objects=[‘start’, ‘center’, ‘end’])

Alignment (vertical or horizontal) of the plot in a layout.

border = param.Number(default=10, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimum border around plot.

aspect = param.Parameter()

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(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Defines the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.

frame_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

frame_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

min_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

min_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

max_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

max_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

margin = param.Parameter()

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, objects=[False, True, ‘width’, ‘height’])

gridstyle = param.Dict(class_=<class ‘dict’>, default={})

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’])

Whether to plot the ‘x’ and ‘y’ labels.

lod = param.Dict(class_=<class ‘dict’>, default={‘factor’: 10, ‘interval’: 300, ‘threshold’: 2000, ‘timeout’: 500})

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)

Whether or not to show a complete frame around the plot.

shared_axes = param.Boolean(bounds=(0, 1), default=True)

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’])

A list of plugin tools to use on the plot.

tools = param.List(bounds=(0, None), default=[])

A list of plugin tools to use on the plot.

xformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

yformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

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.

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.BoxAnnotationPlot'>)
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_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.BoxAnnotationPlot'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.BoxAnnotationPlot'>)
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.

inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.BoxAnnotationPlot'>)

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

message(**kwargs)

Inspect .param.message method for the full docstring

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.

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.BoxAnnotationPlot'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

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.

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.BoxAnnotationPlot'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.BoxAnnotationPlot'>)
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.

state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

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.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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

fontsize = param.Parameter()

Specifies various font sizes of the displayed text. Finer control is available by supplying a dictionary where any unmentioned keys revert to the default sizes, e.g: {‘ticks’:20, ‘title’:15, ‘ylabel’:5, ‘xlabel’:5, ‘zlabel’:5, ‘legend’:8, ‘legend_title’:13} You can set the font size of ‘zlabel’, ‘ylabel’ and ‘xlabel’ together using the ‘labels’ key.

fontscale = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Scales the size of all fonts.

show_title = param.Boolean(bounds=(0, 1), default=True)

Whether to display the plot title.

title = param.String(default=’{label} {group} {dimensions}’)

The formatting string for the title of this plot, allows defining a label group separator and dimension labels.

title_format = param.String()

Alias for title.

normalize = param.Boolean(bounds=(0, 1), default=True)

Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.

projection = param.Parameter()

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

apply_ranges = param.Boolean(bounds=(0, 1), default=True)

Whether to compute the plot bounds from the data itself.

apply_extents = param.Boolean(bounds=(0, 1), default=True)

Whether to apply extent overrides on the Elements

bgcolor = param.ClassSelector(class_=(<class ‘str’>, <class ‘tuple’>))

If set bgcolor overrides the background color of the axis.

default_span = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=2.0)

Defines the span of an axis if the axis range is zero, i.e. if the lower and upper end of an axis are equal or no range is defined at all. For example if there is a single datapoint at 0 a default_span of 2.0 will result in axis ranges spanning from -1 to 1.

hooks = param.HookList(bounds=(0, None), default=[])

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.

invert_axes = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the x- and y-axis

invert_xaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot y-axis.

finalize_hooks = param.HookList(bounds=(0, None), default=[])

Deprecated; use hooks options instead.

logx = param.Boolean(bounds=(0, 1), default=False)

Whether the x-axis of the plot will be a log axis.

logy = param.Boolean(bounds=(0, 1), default=False)

Whether the y-axis of the plot will be a log axis.

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0.1)

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=True)

Whether to show legend for the plot.

show_grid = param.Boolean(bounds=(0, 1), default=False)

Whether to show a Cartesian grid on the plot.

xaxis = param.ObjectSelector(default=’bottom’, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None, True, False])

Whether and where to display the xaxis. The “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=’left’, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None, True, False])

Whether and where to display the yaxis. The “bare” options allow suppressing all axis labels, including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’, ‘left-bare’ and ‘right-bare’.

xlabel = param.String()

An explicit override of the x-axis label, if set takes precedence over the dimension label.

ylabel = param.String()

An explicit override of the y-axis label, if set takes precedence over the dimension label.

xlim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

ylim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

zlim = param.Tuple(default=(nan, nan), length=2)

User-specified z-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

xrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the xticks.

yrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the yticks.

xticks = param.Parameter()

Ticks along x-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

yticks = param.Parameter()

Ticks along y-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

shared_datasource = param.Boolean(bounds=(0, 1), default=True)

Whether Elements drawing the data from the same object should share their Bokeh data source allowing for linked brushing and other linked behaviors.

toolbar = param.ObjectSelector(default=’above’, objects=[‘above’, ‘below’, ‘left’, ‘right’, None])

The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.

width = param.Number(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

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), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

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.

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.DivPlot'>)
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_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.DivPlot'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.DivPlot'>)
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.

inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.DivPlot'>)

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

message(**kwargs)

Inspect .param.message method for the full docstring

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.DivPlot'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

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.

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.DivPlot'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.DivPlot'>)
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.

state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

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.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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

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

fontsize = param.Parameter(default={‘title’: ‘12pt’})

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’}

fontscale = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Scales the size of all fonts.

show_title = param.Boolean(bounds=(0, 1), default=True)

Whether to display the plot title.

title = param.String(default=’{label} {group} {dimensions}’)

The formatting string for the title of this plot, allows defining a label group separator and dimension labels.

title_format = param.String()

Alias for title.

normalize = param.Boolean(bounds=(0, 1), default=True)

Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.

projection = param.Parameter()

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

apply_ranges = param.Boolean(bounds=(0, 1), default=True)

Whether to compute the plot bounds from the data itself.

apply_extents = param.Boolean(bounds=(0, 1), default=True)

Whether to apply extent overrides on the Elements

bgcolor = param.ClassSelector(class_=(<class ‘str’>, <class ‘tuple’>))

If set bgcolor overrides the background color of the axis.

default_span = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=2.0)

Defines the span of an axis if the axis range is zero, i.e. if the lower and upper end of an axis are equal or no range is defined at all. For example if there is a single datapoint at 0 a default_span of 2.0 will result in axis ranges spanning from -1 to 1.

hooks = param.HookList(bounds=(0, None), default=[])

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.

invert_axes = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the x- and y-axis

invert_xaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot y-axis.

finalize_hooks = param.HookList(bounds=(0, None), default=[])

Deprecated; use hooks options instead.

logx = param.Boolean(bounds=(0, 1), default=False)

Whether the x-axis of the plot will be a log axis.

logy = param.Boolean(bounds=(0, 1), default=False)

Whether the y-axis of the plot will be a log axis.

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0.1)

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)

Whether to show legend for the plot.

show_grid = param.Boolean(bounds=(0, 1), default=False)

Whether to show a Cartesian grid on the plot.

xaxis = param.ObjectSelector(default=’bottom’, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None, True, False])

Whether and where to display the xaxis. The “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=’left’, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None, True, False])

Whether and where to display the yaxis. The “bare” options allow suppressing all axis labels, including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’, ‘left-bare’ and ‘right-bare’.

xlabel = param.String()

An explicit override of the x-axis label, if set takes precedence over the dimension label.

ylabel = param.String()

An explicit override of the y-axis label, if set takes precedence over the dimension label.

xlim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

ylim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

zlim = param.Tuple(default=(nan, nan), length=2)

User-specified z-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

xrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the xticks.

yrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the yticks.

xticks = param.Parameter()

Ticks along x-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

yticks = param.Parameter()

Ticks along y-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

shared_datasource = param.Boolean(bounds=(0, 1), default=True)

Whether Elements drawing the data from the same object should share their Bokeh data source allowing for linked brushing and other linked behaviors.

toolbar = param.ObjectSelector(default=’right’, objects=[‘above’, ‘below’, ‘left’, ‘right’, ‘disable’, None])

The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.

width = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

height = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

active_tools = param.List(bounds=(0, None), default=[])

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.

align = param.ObjectSelector(objects=[‘start’, ‘center’, ‘end’])

Alignment (vertical or horizontal) of the plot in a layout.

border = param.Number(default=10, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimum border around plot.

aspect = param.Parameter()

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(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Defines the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.

frame_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

frame_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

min_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

min_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

max_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

max_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

margin = param.Parameter()

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, objects=[False, True, ‘width’, ‘height’])

gridstyle = param.Dict(class_=<class ‘dict’>, default={})

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’])

Whether to plot the ‘x’ and ‘y’ labels.

lod = param.Dict(class_=<class ‘dict’>, default={‘factor’: 10, ‘interval’: 300, ‘threshold’: 2000, ‘timeout’: 500})

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)

Whether or not to show a complete frame around the plot.

shared_axes = param.Boolean(bounds=(0, 1), default=True)

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’])

A list of plugin tools to use on the plot.

tools = param.List(bounds=(0, None), default=[])

A list of plugin tools to use on the plot.

xformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

yformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

color_levels = param.ClassSelector(class_=(<class ‘int’>, <class ‘list’>))

Number of discrete colors to use when colormapping or a set of color intervals defining the range of values to map each color to.

clabel = param.String()

An explicit override of the color bar label, if set takes precedence over the title key in colorbar_opts.

clim = param.NumericTuple(default=(nan, nan), 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.

cformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the colorbar axis.

colorbar = param.Boolean(bounds=(0, 1), default=False)

Whether to display a colorbar.

colorbar_position = param.ObjectSelector(default=’right’, 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={})

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={})

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)

Whether to apply log scaling to the z-axis.

symmetric = param.Boolean(bounds=(0, 1), default=False)

Whether to make the colormap symmetric around zero.

xoffset = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Amount of offset to apply to labels along x-axis.

yoffset = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Amount of offset to apply to labels along x-axis.

color_index = param.ClassSelector(class_=(<class ‘str’>, <class ‘int’>))

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.

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.LabelsPlot'>)
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_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.LabelsPlot'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.LabelsPlot'>)
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.

inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.LabelsPlot'>)

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

message(**kwargs)

Inspect .param.message method for the full docstring

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.

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.LabelsPlot'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

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.

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.LabelsPlot'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.LabelsPlot'>)
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.

state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

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.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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

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

fontsize = param.Parameter(default={‘title’: ‘12pt’})

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’}

fontscale = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Scales the size of all fonts.

show_title = param.Boolean(bounds=(0, 1), default=True)

Whether to display the plot title.

title = param.String(default=’{label} {group} {dimensions}’)

The formatting string for the title of this plot, allows defining a label group separator and dimension labels.

title_format = param.String()

Alias for title.

normalize = param.Boolean(bounds=(0, 1), default=True)

Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.

projection = param.Parameter()

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

apply_ranges = param.Boolean(bounds=(0, 1), default=False)

Whether to include the annotation in axis range calculations.

apply_extents = param.Boolean(bounds=(0, 1), default=True)

Whether to apply extent overrides on the Elements

bgcolor = param.ClassSelector(class_=(<class ‘str’>, <class ‘tuple’>))

If set bgcolor overrides the background color of the axis.

default_span = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=2.0)

Defines the span of an axis if the axis range is zero, i.e. if the lower and upper end of an axis are equal or no range is defined at all. For example if there is a single datapoint at 0 a default_span of 2.0 will result in axis ranges spanning from -1 to 1.

hooks = param.HookList(bounds=(0, None), default=[])

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.

invert_axes = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the x- and y-axis

invert_xaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot y-axis.

finalize_hooks = param.HookList(bounds=(0, None), default=[])

Deprecated; use hooks options instead.

logx = param.Boolean(bounds=(0, 1), default=False)

Whether the x-axis of the plot will be a log axis.

logy = param.Boolean(bounds=(0, 1), default=False)

Whether the y-axis of the plot will be a log axis.

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0.1)

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=True)

Whether to show legend for the plot.

show_grid = param.Boolean(bounds=(0, 1), default=False)

Whether to show a Cartesian grid on the plot.

xaxis = param.ObjectSelector(default=’bottom’, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None, True, False])

Whether and where to display the xaxis. The “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=’left’, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None, True, False])

Whether and where to display the yaxis. The “bare” options allow suppressing all axis labels, including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’, ‘left-bare’ and ‘right-bare’.

xlabel = param.String()

An explicit override of the x-axis label, if set takes precedence over the dimension label.

ylabel = param.String()

An explicit override of the y-axis label, if set takes precedence over the dimension label.

xlim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

ylim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

zlim = param.Tuple(default=(nan, nan), length=2)

User-specified z-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

xrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the xticks.

yrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the yticks.

xticks = param.Parameter()

Ticks along x-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

yticks = param.Parameter()

Ticks along y-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

shared_datasource = param.Boolean(bounds=(0, 1), default=True)

Whether Elements drawing the data from the same object should share their Bokeh data source allowing for linked brushing and other linked behaviors.

toolbar = param.ObjectSelector(default=’right’, objects=[‘above’, ‘below’, ‘left’, ‘right’, ‘disable’, None])

The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.

width = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

height = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

active_tools = param.List(bounds=(0, None), default=[])

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.

align = param.ObjectSelector(objects=[‘start’, ‘center’, ‘end’])

Alignment (vertical or horizontal) of the plot in a layout.

border = param.Number(default=10, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimum border around plot.

aspect = param.Parameter()

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(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Defines the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.

frame_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

frame_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

min_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

min_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

max_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

max_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

margin = param.Parameter()

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, objects=[False, True, ‘width’, ‘height’])

gridstyle = param.Dict(class_=<class ‘dict’>, default={})

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’])

Whether to plot the ‘x’ and ‘y’ labels.

lod = param.Dict(class_=<class ‘dict’>, default={‘factor’: 10, ‘interval’: 300, ‘threshold’: 2000, ‘timeout’: 500})

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)

Whether or not to show a complete frame around the plot.

shared_axes = param.Boolean(bounds=(0, 1), default=True)

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’])

A list of plugin tools to use on the plot.

tools = param.List(bounds=(0, None), default=[])

A list of plugin tools to use on the plot.

xformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

yformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

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.

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.LineAnnotationPlot'>)
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_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.LineAnnotationPlot'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.LineAnnotationPlot'>)
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.

inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.LineAnnotationPlot'>)

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

message(**kwargs)

Inspect .param.message method for the full docstring

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.

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.LineAnnotationPlot'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

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.

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.LineAnnotationPlot'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.LineAnnotationPlot'>)
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.

state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

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.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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

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

fontsize = param.Parameter(default={‘title’: ‘12pt’})

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’}

fontscale = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Scales the size of all fonts.

show_title = param.Boolean(bounds=(0, 1), default=True)

Whether to display the plot title.

title = param.String(default=’{label} {group} {dimensions}’)

The formatting string for the title of this plot, allows defining a label group separator and dimension labels.

title_format = param.String()

Alias for title.

normalize = param.Boolean(bounds=(0, 1), default=True)

Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.

projection = param.Parameter()

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

apply_ranges = param.Boolean(bounds=(0, 1), default=True)

Whether to compute the plot bounds from the data itself.

apply_extents = param.Boolean(bounds=(0, 1), default=True)

Whether to apply extent overrides on the Elements

bgcolor = param.ClassSelector(class_=(<class ‘str’>, <class ‘tuple’>))

If set bgcolor overrides the background color of the axis.

default_span = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=2.0)

Defines the span of an axis if the axis range is zero, i.e. if the lower and upper end of an axis are equal or no range is defined at all. For example if there is a single datapoint at 0 a default_span of 2.0 will result in axis ranges spanning from -1 to 1.

hooks = param.HookList(bounds=(0, None), default=[])

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.

invert_axes = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the x- and y-axis

invert_xaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot y-axis.

finalize_hooks = param.HookList(bounds=(0, None), default=[])

Deprecated; use hooks options instead.

logx = param.Boolean(bounds=(0, 1), default=False)

Whether the x-axis of the plot will be a log axis.

logy = param.Boolean(bounds=(0, 1), default=False)

Whether the y-axis of the plot will be a log axis.

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0.1)

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=True)

Whether to show legend for the plot.

show_grid = param.Boolean(bounds=(0, 1), default=False)

Whether to show a Cartesian grid on the plot.

xaxis = param.ObjectSelector(default=’bottom’, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None, True, False])

Whether and where to display the xaxis. The “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=’left’, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None, True, False])

Whether and where to display the yaxis. The “bare” options allow suppressing all axis labels, including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’, ‘left-bare’ and ‘right-bare’.

xlabel = param.String()

An explicit override of the x-axis label, if set takes precedence over the dimension label.

ylabel = param.String()

An explicit override of the y-axis label, if set takes precedence over the dimension label.

xlim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

ylim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

zlim = param.Tuple(default=(nan, nan), length=2)

User-specified z-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

xrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the xticks.

yrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the yticks.

xticks = param.Parameter()

Ticks along x-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

yticks = param.Parameter()

Ticks along y-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

shared_datasource = param.Boolean(bounds=(0, 1), default=True)

Whether Elements drawing the data from the same object should share their Bokeh data source allowing for linked brushing and other linked behaviors.

toolbar = param.ObjectSelector(default=’right’, objects=[‘above’, ‘below’, ‘left’, ‘right’, ‘disable’, None])

The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.

width = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

height = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

active_tools = param.List(bounds=(0, None), default=[])

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.

align = param.ObjectSelector(objects=[‘start’, ‘center’, ‘end’])

Alignment (vertical or horizontal) of the plot in a layout.

border = param.Number(default=10, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimum border around plot.

aspect = param.Parameter()

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(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Defines the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.

frame_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

frame_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

min_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

min_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

max_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

max_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

margin = param.Parameter()

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, objects=[False, True, ‘width’, ‘height’])

gridstyle = param.Dict(class_=<class ‘dict’>, default={})

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’])

Whether to plot the ‘x’ and ‘y’ labels.

lod = param.Dict(class_=<class ‘dict’>, default={‘factor’: 10, ‘interval’: 300, ‘threshold’: 2000, ‘timeout’: 500})

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)

Whether or not to show a complete frame around the plot.

shared_axes = param.Boolean(bounds=(0, 1), default=True)

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’])

A list of plugin tools to use on the plot.

tools = param.List(bounds=(0, None), default=[])

A list of plugin tools to use on the plot.

xformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

yformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

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.

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.SlopePlot'>)
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_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.SlopePlot'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.SlopePlot'>)
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.

inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.SlopePlot'>)

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

message(**kwargs)

Inspect .param.message method for the full docstring

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.

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.SlopePlot'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

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.

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.SlopePlot'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.SlopePlot'>)
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.

state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

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.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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.

fontsize = param.Parameter(default={‘title’: ‘12pt’})

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’}

fontscale = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Scales the size of all fonts.

show_title = param.Boolean(bounds=(0, 1), default=True)

Whether to display the plot title.

title = param.String(default=’{label} {group} {dimensions}’)

The formatting string for the title of this plot, allows defining a label group separator and dimension labels.

title_format = param.String()

Alias for title.

normalize = param.Boolean(bounds=(0, 1), default=True)

Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.

projection = param.Parameter()

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

apply_ranges = param.Boolean(bounds=(0, 1), default=True)

Whether to compute the plot bounds from the data itself.

apply_extents = param.Boolean(bounds=(0, 1), default=True)

Whether to apply extent overrides on the Elements

bgcolor = param.ClassSelector(class_=(<class ‘str’>, <class ‘tuple’>))

If set bgcolor overrides the background color of the axis.

default_span = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=2.0)

Defines the span of an axis if the axis range is zero, i.e. if the lower and upper end of an axis are equal or no range is defined at all. For example if there is a single datapoint at 0 a default_span of 2.0 will result in axis ranges spanning from -1 to 1.

hooks = param.HookList(bounds=(0, None), default=[])

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.

invert_axes = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the x- and y-axis

invert_xaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot y-axis.

finalize_hooks = param.HookList(bounds=(0, None), default=[])

Deprecated; use hooks options instead.

logx = param.Boolean(bounds=(0, 1), default=False)

Whether the x-axis of the plot will be a log axis.

logy = param.Boolean(bounds=(0, 1), default=False)

Whether the y-axis of the plot will be a log axis.

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0.1)

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=True)

Whether to show legend for the plot.

show_grid = param.Boolean(bounds=(0, 1), default=False)

Whether to show a Cartesian grid on the plot.

xaxis = param.ObjectSelector(default=’bottom’, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None, True, False])

Whether and where to display the xaxis. The “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=’left’, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None, True, False])

Whether and where to display the yaxis. The “bare” options allow suppressing all axis labels, including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’, ‘left-bare’ and ‘right-bare’.

xlabel = param.String()

An explicit override of the x-axis label, if set takes precedence over the dimension label.

ylabel = param.String()

An explicit override of the y-axis label, if set takes precedence over the dimension label.

xlim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

ylim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

zlim = param.Tuple(default=(nan, nan), length=2)

User-specified z-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

xrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the xticks.

yrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the yticks.

xticks = param.Parameter()

Ticks along x-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

yticks = param.Parameter()

Ticks along y-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

shared_datasource = param.Boolean(bounds=(0, 1), default=True)

Whether Elements drawing the data from the same object should share their Bokeh data source allowing for linked brushing and other linked behaviors.

toolbar = param.ObjectSelector(default=’right’, objects=[‘above’, ‘below’, ‘left’, ‘right’, ‘disable’, None])

The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.

width = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

height = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

active_tools = param.List(bounds=(0, None), default=[])

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.

align = param.ObjectSelector(objects=[‘start’, ‘center’, ‘end’])

Alignment (vertical or horizontal) of the plot in a layout.

border = param.Number(default=10, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimum border around plot.

aspect = param.Parameter()

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(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Defines the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.

frame_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

frame_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

min_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

min_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

max_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

max_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

margin = param.Parameter()

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, objects=[False, True, ‘width’, ‘height’])

gridstyle = param.Dict(class_=<class ‘dict’>, default={})

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’])

Whether to plot the ‘x’ and ‘y’ labels.

lod = param.Dict(class_=<class ‘dict’>, default={‘factor’: 10, ‘interval’: 300, ‘threshold’: 2000, ‘timeout’: 500})

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)

Whether or not to show a complete frame around the plot.

shared_axes = param.Boolean(bounds=(0, 1), default=True)

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’])

A list of plugin tools to use on the plot.

tools = param.List(bounds=(0, None), default=[])

A list of plugin tools to use on the plot.

xformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

yformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

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.

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.SplinePlot'>)
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_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.SplinePlot'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.SplinePlot'>)
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.

inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.SplinePlot'>)

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

message(**kwargs)

Inspect .param.message method for the full docstring

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.

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.SplinePlot'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

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.

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.SplinePlot'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.SplinePlot'>)
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.

state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

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.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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

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

fontsize = param.Parameter(default={‘title’: ‘12pt’})

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’}

fontscale = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Scales the size of all fonts.

show_title = param.Boolean(bounds=(0, 1), default=True)

Whether to display the plot title.

title = param.String(default=’{label} {group} {dimensions}’)

The formatting string for the title of this plot, allows defining a label group separator and dimension labels.

title_format = param.String()

Alias for title.

normalize = param.Boolean(bounds=(0, 1), default=True)

Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.

projection = param.Parameter()

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

apply_ranges = param.Boolean(bounds=(0, 1), default=True)

Whether to compute the plot bounds from the data itself.

apply_extents = param.Boolean(bounds=(0, 1), default=True)

Whether to apply extent overrides on the Elements

bgcolor = param.ClassSelector(class_=(<class ‘str’>, <class ‘tuple’>))

If set bgcolor overrides the background color of the axis.

default_span = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=2.0)

Defines the span of an axis if the axis range is zero, i.e. if the lower and upper end of an axis are equal or no range is defined at all. For example if there is a single datapoint at 0 a default_span of 2.0 will result in axis ranges spanning from -1 to 1.

hooks = param.HookList(bounds=(0, None), default=[])

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.

invert_axes = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the x- and y-axis

invert_xaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot y-axis.

finalize_hooks = param.HookList(bounds=(0, None), default=[])

Deprecated; use hooks options instead.

logx = param.Boolean(bounds=(0, 1), default=False)

Whether the x-axis of the plot will be a log axis.

logy = param.Boolean(bounds=(0, 1), default=False)

Whether the y-axis of the plot will be a log axis.

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0.1)

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=True)

Whether to show legend for the plot.

show_grid = param.Boolean(bounds=(0, 1), default=False)

Whether to show a Cartesian grid on the plot.

xaxis = param.ObjectSelector(default=’bottom’, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None, True, False])

Whether and where to display the xaxis. The “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=’left’, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None, True, False])

Whether and where to display the yaxis. The “bare” options allow suppressing all axis labels, including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’, ‘left-bare’ and ‘right-bare’.

xlabel = param.String()

An explicit override of the x-axis label, if set takes precedence over the dimension label.

ylabel = param.String()

An explicit override of the y-axis label, if set takes precedence over the dimension label.

xlim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

ylim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

zlim = param.Tuple(default=(nan, nan), length=2)

User-specified z-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

xrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the xticks.

yrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the yticks.

xticks = param.Parameter()

Ticks along x-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

yticks = param.Parameter()

Ticks along y-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

shared_datasource = param.Boolean(bounds=(0, 1), default=True)

Whether Elements drawing the data from the same object should share their Bokeh data source allowing for linked brushing and other linked behaviors.

toolbar = param.ObjectSelector(default=’right’, objects=[‘above’, ‘below’, ‘left’, ‘right’, ‘disable’, None])

The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.

width = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

height = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

active_tools = param.List(bounds=(0, None), default=[])

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.

align = param.ObjectSelector(objects=[‘start’, ‘center’, ‘end’])

Alignment (vertical or horizontal) of the plot in a layout.

border = param.Number(default=10, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimum border around plot.

aspect = param.Parameter()

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(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Defines the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.

frame_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

frame_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

min_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

min_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

max_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

max_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

margin = param.Parameter()

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, objects=[False, True, ‘width’, ‘height’])

gridstyle = param.Dict(class_=<class ‘dict’>, default={})

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’])

Whether to plot the ‘x’ and ‘y’ labels.

lod = param.Dict(class_=<class ‘dict’>, default={‘factor’: 10, ‘interval’: 300, ‘threshold’: 2000, ‘timeout’: 500})

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)

Whether or not to show a complete frame around the plot.

shared_axes = param.Boolean(bounds=(0, 1), default=True)

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’])

A list of plugin tools to use on the plot.

tools = param.List(bounds=(0, None), default=[])

A list of plugin tools to use on the plot.

xformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

yformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

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.

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.TextPlot'>)
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_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.TextPlot'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.TextPlot'>)
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.

inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.TextPlot'>)

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

message(**kwargs)

Inspect .param.message method for the full docstring

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.

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.TextPlot'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

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.

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.TextPlot'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.annotation.TextPlot'>)
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.

state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

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.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring


callbacks Module

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"holoviews.plotting.bokeh.callbacks.TapCallback" -> "holoviews.plotting.bokeh.callbacks.DoubleTapCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.DrawCallback" [URL="#holoviews.plotting.bokeh.callbacks.DrawCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.callbacks.PointerXYCallback" -> "holoviews.plotting.bokeh.callbacks.DrawCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.FreehandDrawCallback" [URL="#holoviews.plotting.bokeh.callbacks.FreehandDrawCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.callbacks.PolyDrawCallback" -> "holoviews.plotting.bokeh.callbacks.FreehandDrawCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.GlyphDrawCallback" [URL="#holoviews.plotting.bokeh.callbacks.GlyphDrawCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.callbacks.CDSCallback" -> "holoviews.plotting.bokeh.callbacks.GlyphDrawCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.LinkCallback" [URL="#holoviews.plotting.bokeh.callbacks.LinkCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "param.parameterized.Parameterized" -> "holoviews.plotting.bokeh.callbacks.LinkCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.MessageCallback" [URL="#holoviews.plotting.bokeh.callbacks.MessageCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="A MessageCallback is an abstract baseclass used to supply Streams"]; "holoviews.plotting.bokeh.callbacks.MouseEnterCallback" [URL="#holoviews.plotting.bokeh.callbacks.MouseEnterCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Returns the mouse x/y-position on mouseenter event, i.e. when"]; "holoviews.plotting.bokeh.callbacks.PointerXYCallback" -> "holoviews.plotting.bokeh.callbacks.MouseEnterCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.MouseLeaveCallback" [URL="#holoviews.plotting.bokeh.callbacks.MouseLeaveCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Returns the mouse x/y-position on mouseleave event, i.e. when"]; "holoviews.plotting.bokeh.callbacks.PointerXYCallback" -> "holoviews.plotting.bokeh.callbacks.MouseLeaveCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.PlotSizeCallback" [URL="#holoviews.plotting.bokeh.callbacks.PlotSizeCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Returns the actual width and height of a plot once the layout"]; "holoviews.plotting.bokeh.callbacks.Callback" -> "holoviews.plotting.bokeh.callbacks.PlotSizeCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.PointDrawCallback" [URL="#holoviews.plotting.bokeh.callbacks.PointDrawCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.callbacks.GlyphDrawCallback" -> "holoviews.plotting.bokeh.callbacks.PointDrawCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.PointerXCallback" [URL="#holoviews.plotting.bokeh.callbacks.PointerXCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Returns the mouse x-position on mousemove event."]; "holoviews.plotting.bokeh.callbacks.PointerXYCallback" -> "holoviews.plotting.bokeh.callbacks.PointerXCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.PointerXYCallback" [URL="#holoviews.plotting.bokeh.callbacks.PointerXYCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Returns the mouse x/y-position on mousemove event."]; "holoviews.plotting.bokeh.callbacks.Callback" -> "holoviews.plotting.bokeh.callbacks.PointerXYCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.PointerYCallback" [URL="#holoviews.plotting.bokeh.callbacks.PointerYCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Returns the mouse x/y-position on mousemove event."]; "holoviews.plotting.bokeh.callbacks.PointerXYCallback" -> "holoviews.plotting.bokeh.callbacks.PointerYCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.PolyDrawCallback" [URL="#holoviews.plotting.bokeh.callbacks.PolyDrawCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.callbacks.GlyphDrawCallback" -> "holoviews.plotting.bokeh.callbacks.PolyDrawCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.PolyEditCallback" [URL="#holoviews.plotting.bokeh.callbacks.PolyEditCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.callbacks.PolyDrawCallback" -> "holoviews.plotting.bokeh.callbacks.PolyEditCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.RangeToolLinkCallback" [URL="#holoviews.plotting.bokeh.callbacks.RangeToolLinkCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Attaches a RangeTool to the source plot and links it to the"]; "holoviews.plotting.bokeh.callbacks.LinkCallback" -> "holoviews.plotting.bokeh.callbacks.RangeToolLinkCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.RangeXCallback" [URL="#holoviews.plotting.bokeh.callbacks.RangeXCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Returns the x-axis range of a plot."]; "holoviews.plotting.bokeh.callbacks.RangeXYCallback" -> "holoviews.plotting.bokeh.callbacks.RangeXCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.RangeXYCallback" [URL="#holoviews.plotting.bokeh.callbacks.RangeXYCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Returns the x/y-axis ranges of a plot."]; "holoviews.plotting.bokeh.callbacks.Callback" -> "holoviews.plotting.bokeh.callbacks.RangeXYCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.RangeYCallback" [URL="#holoviews.plotting.bokeh.callbacks.RangeYCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Returns the y-axis range of a plot."]; "holoviews.plotting.bokeh.callbacks.RangeXYCallback" -> "holoviews.plotting.bokeh.callbacks.RangeYCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.RectanglesTableLinkCallback" [URL="#holoviews.plotting.bokeh.callbacks.RectanglesTableLinkCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.callbacks.DataLinkCallback" -> "holoviews.plotting.bokeh.callbacks.RectanglesTableLinkCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.ResetCallback" [URL="#holoviews.plotting.bokeh.callbacks.ResetCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Signals the Reset stream if an event has been triggered."]; "holoviews.plotting.bokeh.callbacks.Callback" -> "holoviews.plotting.bokeh.callbacks.ResetCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.Selection1DCallback" [URL="#holoviews.plotting.bokeh.callbacks.Selection1DCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Returns the current selection on a ColumnDataSource."]; "holoviews.plotting.bokeh.callbacks.Callback" -> "holoviews.plotting.bokeh.callbacks.Selection1DCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.SelectionLinkCallback" [URL="#holoviews.plotting.bokeh.callbacks.SelectionLinkCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.callbacks.LinkCallback" -> "holoviews.plotting.bokeh.callbacks.SelectionLinkCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.SelectionXYCallback" [URL="#holoviews.plotting.bokeh.callbacks.SelectionXYCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Converts a bounds selection to numeric or categorical x-range"]; "holoviews.plotting.bokeh.callbacks.BoundsCallback" -> "holoviews.plotting.bokeh.callbacks.SelectionXYCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.ServerCallback" [URL="#holoviews.plotting.bokeh.callbacks.ServerCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Implements methods to set up bokeh server callbacks. A ServerCallback"]; "holoviews.plotting.bokeh.callbacks.MessageCallback" -> "holoviews.plotting.bokeh.callbacks.ServerCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.SingleTapCallback" [URL="#holoviews.plotting.bokeh.callbacks.SingleTapCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Returns the mouse x/y-position on tap event."]; "holoviews.plotting.bokeh.callbacks.TapCallback" -> "holoviews.plotting.bokeh.callbacks.SingleTapCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.TapCallback" [URL="#holoviews.plotting.bokeh.callbacks.TapCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Returns the mouse x/y-position on tap event."]; "holoviews.plotting.bokeh.callbacks.PointerXYCallback" -> "holoviews.plotting.bokeh.callbacks.TapCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.callbacks.VertexTableLinkCallback" [URL="#holoviews.plotting.bokeh.callbacks.VertexTableLinkCallback",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.callbacks.LinkCallback" -> "holoviews.plotting.bokeh.callbacks.VertexTableLinkCallback" [arrowsize=0.5,style="setlinewidth(0.5)"]; "param.parameterized.Parameterized" [fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",tooltip="params(name=String)"]; }
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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_callback(handle)

Set up on_change events for bokeh server interactions.

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

Bases: holoviews.plotting.bokeh.callbacks.CustomJSCallback, holoviews.plotting.bokeh.callbacks.ServerCallback

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.

  • extra_models: Any additional models available in handles which

    should be made available in the namespace of the objects, e.g. to make a tool available to skip checks.

  • 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 extra_models attributes 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_data and cb_obj variables available containing additional information about the event.

  • skipConditions when the Callback should be skipped

    specified as a list of valid JS expressions, which can reference models requested by the callback, e.g. [‘pan.attributes.active’] would skip the callback if the pan tool is active.

  • codeDefines any additional JS code to be executed,

    which can modify the data object that is sent to the backend.

  • 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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_callback(handle)

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

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_callback(handle)

Set up on_change events for bokeh server interactions.

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

Bases: holoviews.plotting.bokeh.callbacks.MessageCallback

The CustomJSCallback attaches CustomJS callbacks to a bokeh plot, which looks up the requested attributes and sends back a message to Python using a Comms instance.

classmethod attributes_js(attributes)[source]

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)[source]

Creates a CustomJS callback that will send the requested attributes back to python.

set_customjs_callback(js_callback, handle)[source]

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

class holoviews.plotting.bokeh.callbacks.DataLinkCallback(root_model, link, source_plot, target_plot)[source]

Bases: holoviews.plotting.bokeh.callbacks.LinkCallback

Merges the source and target ColumnDataSource

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

Searches a GenericElementPlot for a Link.

Traverses the supplied plot and searches for any Links on the plotted objects.

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.DataLinkCallback'>)
get_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.DataLinkCallback'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.DataLinkCallback'>)
inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.DataLinkCallback'>)
message(**kwargs)

Inspect .param.message method for the full docstring

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.DataLinkCallback'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.DataLinkCallback'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.DataLinkCallback'>)
state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

validate()

Should be subclassed to check if the source and target plots are compatible to perform the linking.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_callback(handle)

Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.LinkCallback(root_model, link, source_plot, target_plot=None)[source]

Bases: param.parameterized.Parameterized

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

Searches a GenericElementPlot for a Link.

Traverses the supplied plot and searches for any Links on the plotted objects.

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.LinkCallback'>)
get_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.LinkCallback'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.LinkCallback'>)
inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.LinkCallback'>)
message(**kwargs)

Inspect .param.message method for the full docstring

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.LinkCallback'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.LinkCallback'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.LinkCallback'>)
state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

validate()[source]

Should be subclassed to check if the source and target plots are compatible to perform the linking.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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

Bases: object

A MessageCallback is an abstract baseclass used to supply Streams with events originating from bokeh plot interactions. The baseclass defines how messages are handled and the basic specification required to define a Callback.

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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_callback(handle)

Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.RangeToolLinkCallback(root_model, link, source_plot, target_plot)[source]

Bases: holoviews.plotting.bokeh.callbacks.LinkCallback

Attaches a RangeTool to the source plot and links it to the specified axes on the target plot

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

Searches a GenericElementPlot for a Link.

Traverses the supplied plot and searches for any Links on the plotted objects.

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.RangeToolLinkCallback'>)
get_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.RangeToolLinkCallback'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.RangeToolLinkCallback'>)
inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.RangeToolLinkCallback'>)
message(**kwargs)

Inspect .param.message method for the full docstring

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.RangeToolLinkCallback'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.RangeToolLinkCallback'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.RangeToolLinkCallback'>)
state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

validate()

Should be subclassed to check if the source and target plots are compatible to perform the linking.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_callback(handle)

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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_callback(handle)

Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.RectanglesTableLinkCallback(root_model, link, source_plot, target_plot=None)[source]

Bases: holoviews.plotting.bokeh.callbacks.DataLinkCallback

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

Searches a GenericElementPlot for a Link.

Traverses the supplied plot and searches for any Links on the plotted objects.

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.RectanglesTableLinkCallback'>)
get_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.RectanglesTableLinkCallback'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.RectanglesTableLinkCallback'>)
inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.RectanglesTableLinkCallback'>)
message(**kwargs)

Inspect .param.message method for the full docstring

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.RectanglesTableLinkCallback'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.RectanglesTableLinkCallback'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.RectanglesTableLinkCallback'>)
state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

validate()

Should be subclassed to check if the source and target plots are compatible to perform the linking.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_callback(handle)

Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.SelectionLinkCallback(root_model, link, source_plot, target_plot=None)[source]

Bases: holoviews.plotting.bokeh.callbacks.LinkCallback

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

Searches a GenericElementPlot for a Link.

Traverses the supplied plot and searches for any Links on the plotted objects.

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.SelectionLinkCallback'>)
get_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.SelectionLinkCallback'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.SelectionLinkCallback'>)
inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.SelectionLinkCallback'>)
message(**kwargs)

Inspect .param.message method for the full docstring

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.SelectionLinkCallback'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.SelectionLinkCallback'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.SelectionLinkCallback'>)
state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

validate()

Should be subclassed to check if the source and target plots are compatible to perform the linking.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_callback(handle)

Set up on_change events for bokeh server interactions.

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

Bases: holoviews.plotting.bokeh.callbacks.MessageCallback

Implements methods to set up bokeh server callbacks. A ServerCallback resolves the requested attributes on the Python end and then hands the msg off to the general on_msg handler, which will update the Stream(s) attached to the callback.

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.

on_event(event)[source]

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()[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_server_callback(handle)[source]

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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_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.

classmethod attributes_js(attributes)

Generates JS code to look up attributes on JS objects from an attributes specification dictionary. If the specification references a plotting particular plotting handle it will also generate JS code to get the ID of the object.

Simple example (when referencing cb_data or cb_obj):

Input : {‘x’: ‘cb_data.geometry.x’}

Output : data[‘x’] = cb_data[‘geometry’][‘x’]

Example referencing plot handle:

Input : {‘x0’: ‘x_range.attributes.start’}

Outputif ((x_range !== undefined)) {

data[‘x0’] = {id: x_range[‘id’], value: x_range[‘attributes’][‘start’]}

}

get_customjs(references, plot_id=None)

Creates a CustomJS callback that will send the requested attributes back to python.

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.

on_event(event)

Process bokeh UIEvents adding timeout to process multiple concerted value change at once rather than firing off multiple plot updates.

process_on_event()

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_customjs_callback(js_callback, handle)

Generates a CustomJS callback by generating the required JS code and gathering all plotting handles and installs it on the requested callback handle.

set_server_callback(handle)

Set up on_change events for bokeh server interactions.

class holoviews.plotting.bokeh.callbacks.VertexTableLinkCallback(root_model, link, source_plot, target_plot=None)[source]

Bases: holoviews.plotting.bokeh.callbacks.LinkCallback

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

Searches a GenericElementPlot for a Link.

Traverses the supplied plot and searches for any Links on the plotted objects.

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.VertexTableLinkCallback'>)
get_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.VertexTableLinkCallback'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.VertexTableLinkCallback'>)
inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.VertexTableLinkCallback'>)
message(**kwargs)

Inspect .param.message method for the full docstring

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.VertexTableLinkCallback'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.VertexTableLinkCallback'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.callbacks.VertexTableLinkCallback'>)
state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

validate()

Should be subclassed to check if the source and target plots are compatible to perform the linking.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring


chart Module

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"holoviews.plotting.bokeh.element.ColorbarPlot" -> "holoviews.plotting.bokeh.chart.BarPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.element.LegendPlot" -> "holoviews.plotting.bokeh.chart.BarPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.chart.CurvePlot" [URL="#holoviews.plotting.bokeh.chart.CurvePlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.element.ElementPlot" -> "holoviews.plotting.bokeh.chart.CurvePlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.chart.ErrorPlot" [URL="#holoviews.plotting.bokeh.chart.ErrorPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.element.ColorbarPlot" -> "holoviews.plotting.bokeh.chart.ErrorPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.chart.HistogramPlot" [URL="#holoviews.plotting.bokeh.chart.HistogramPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.element.ColorbarPlot" -> "holoviews.plotting.bokeh.chart.HistogramPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.chart.PointPlot" [URL="#holoviews.plotting.bokeh.chart.PointPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.element.LegendPlot" -> "holoviews.plotting.bokeh.chart.PointPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.element.ColorbarPlot" -> "holoviews.plotting.bokeh.chart.PointPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.chart.SideHistogramPlot" [URL="#holoviews.plotting.bokeh.chart.SideHistogramPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.chart.HistogramPlot" -> "holoviews.plotting.bokeh.chart.SideHistogramPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.chart.SideSpikesPlot" [URL="#holoviews.plotting.bokeh.chart.SideSpikesPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="SpikesPlot with useful defaults for plotting adjoined rug plot."]; "holoviews.plotting.bokeh.chart.SpikesPlot" -> "holoviews.plotting.bokeh.chart.SideSpikesPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.chart.SpikesPlot" [URL="#holoviews.plotting.bokeh.chart.SpikesPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.mixins.SpikesMixin" -> "holoviews.plotting.bokeh.chart.SpikesPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.element.ColorbarPlot" -> "holoviews.plotting.bokeh.chart.SpikesPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.chart.SpreadPlot" [URL="#holoviews.plotting.bokeh.chart.SpreadPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.element.ElementPlot" -> "holoviews.plotting.bokeh.chart.SpreadPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.chart.VectorFieldPlot" [URL="#holoviews.plotting.bokeh.chart.VectorFieldPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.element.ColorbarPlot" -> "holoviews.plotting.bokeh.chart.VectorFieldPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.element.ColorbarPlot" [URL="#holoviews.plotting.bokeh.element.ColorbarPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="ColorbarPlot provides methods to create colormappers and colorbar"]; "holoviews.plotting.bokeh.element.ElementPlot" -> "holoviews.plotting.bokeh.element.ColorbarPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.element.ElementPlot" [URL="#holoviews.plotting.bokeh.element.ElementPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.plot.BokehPlot" -> "holoviews.plotting.bokeh.element.ElementPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.plot.GenericElementPlot" -> "holoviews.plotting.bokeh.element.ElementPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.element.LegendPlot" [URL="#holoviews.plotting.bokeh.element.LegendPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top"]; "holoviews.plotting.bokeh.element.ElementPlot" -> "holoviews.plotting.bokeh.element.LegendPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.bokeh.plot.BokehPlot" [URL="#holoviews.plotting.bokeh.plot.BokehPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Plotting baseclass for the Bokeh backends, implementing the basic"]; "holoviews.plotting.plot.DimensionedPlot" -> "holoviews.plotting.bokeh.plot.BokehPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.plot.CallbackPlot" -> "holoviews.plotting.bokeh.plot.BokehPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.mixins.AreaMixin" [fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)"]; "holoviews.plotting.mixins.BarsMixin" [fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)"]; "holoviews.plotting.mixins.SpikesMixin" [fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)"]; "holoviews.plotting.plot.CallbackPlot" [fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)"]; "holoviews.plotting.plot.DimensionedPlot" [URL="holoviews.plotting.html#holoviews.plotting.plot.DimensionedPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="DimensionedPlot implements a number of useful methods"]; "holoviews.plotting.plot.Plot" -> "holoviews.plotting.plot.DimensionedPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.plot.GenericElementPlot" [URL="holoviews.plotting.html#holoviews.plotting.plot.GenericElementPlot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Plotting baseclass to render contents of an Element. Implements"]; "holoviews.plotting.plot.DimensionedPlot" -> "holoviews.plotting.plot.GenericElementPlot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "holoviews.plotting.plot.Plot" [URL="holoviews.plotting.html#holoviews.plotting.plot.Plot",fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",target="_top",tooltip="Base class of all Plot classes in HoloViews, designed to be"]; "param.parameterized.Parameterized" -> "holoviews.plotting.plot.Plot" [arrowsize=0.5,style="setlinewidth(0.5)"]; "param.parameterized.Parameterized" [fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5)",tooltip="params(name=String)"]; }
class holoviews.plotting.bokeh.chart.AreaPlot(element, plot=None, **params)[source]

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

fontsize = param.Parameter(default={‘title’: ‘12pt’})

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’}

fontscale = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Scales the size of all fonts.

show_title = param.Boolean(bounds=(0, 1), default=True)

Whether to display the plot title.

title = param.String(default=’{label} {group} {dimensions}’)

The formatting string for the title of this plot, allows defining a label group separator and dimension labels.

title_format = param.String()

Alias for title.

normalize = param.Boolean(bounds=(0, 1), default=True)

Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.

projection = param.Parameter()

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

apply_ranges = param.Boolean(bounds=(0, 1), default=True)

Whether to compute the plot bounds from the data itself.

apply_extents = param.Boolean(bounds=(0, 1), default=True)

Whether to apply extent overrides on the Elements

bgcolor = param.ClassSelector(class_=(<class ‘str’>, <class ‘tuple’>))

If set bgcolor overrides the background color of the axis.

default_span = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=2.0)

Defines the span of an axis if the axis range is zero, i.e. if the lower and upper end of an axis are equal or no range is defined at all. For example if there is a single datapoint at 0 a default_span of 2.0 will result in axis ranges spanning from -1 to 1.

hooks = param.HookList(bounds=(0, None), default=[])

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.

invert_axes = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the x- and y-axis

invert_xaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot y-axis.

finalize_hooks = param.HookList(bounds=(0, None), default=[])

Deprecated; use hooks options instead.

logx = param.Boolean(bounds=(0, 1), default=False)

Whether the x-axis of the plot will be a log axis.

logy = param.Boolean(bounds=(0, 1), default=False)

Whether the y-axis of the plot will be a log axis.

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=(0, 0.1))

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=True)

Whether to show legend for the plot.

show_grid = param.Boolean(bounds=(0, 1), default=False)

Whether to show a Cartesian grid on the plot.

xaxis = param.ObjectSelector(default=’bottom’, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None, True, False])

Whether and where to display the xaxis. The “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=’left’, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None, True, False])

Whether and where to display the yaxis. The “bare” options allow suppressing all axis labels, including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’, ‘left-bare’ and ‘right-bare’.

xlabel = param.String()

An explicit override of the x-axis label, if set takes precedence over the dimension label.

ylabel = param.String()

An explicit override of the y-axis label, if set takes precedence over the dimension label.

xlim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

ylim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

zlim = param.Tuple(default=(nan, nan), length=2)

User-specified z-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

xrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the xticks.

yrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the yticks.

xticks = param.Parameter()

Ticks along x-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

yticks = param.Parameter()

Ticks along y-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

shared_datasource = param.Boolean(bounds=(0, 1), default=True)

Whether Elements drawing the data from the same object should share their Bokeh data source allowing for linked brushing and other linked behaviors.

toolbar = param.ObjectSelector(default=’right’, objects=[‘above’, ‘below’, ‘left’, ‘right’, ‘disable’, None])

The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.

width = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

height = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

active_tools = param.List(bounds=(0, None), default=[])

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.

align = param.ObjectSelector(objects=[‘start’, ‘center’, ‘end’])

Alignment (vertical or horizontal) of the plot in a layout.

border = param.Number(default=10, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimum border around plot.

aspect = param.Parameter()

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(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Defines the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.

frame_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

frame_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

min_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

min_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

max_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

max_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

margin = param.Parameter()

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, objects=[False, True, ‘width’, ‘height’])

gridstyle = param.Dict(class_=<class ‘dict’>, default={})

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’])

Whether to plot the ‘x’ and ‘y’ labels.

lod = param.Dict(class_=<class ‘dict’>, default={‘factor’: 10, ‘interval’: 300, ‘threshold’: 2000, ‘timeout’: 500})

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)

Whether or not to show a complete frame around the plot.

shared_axes = param.Boolean(bounds=(0, 1), default=True)

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’])

A list of plugin tools to use on the plot.

tools = param.List(bounds=(0, None), default=[])

A list of plugin tools to use on the plot.

xformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

yformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

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.

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.AreaPlot'>)
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_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.AreaPlot'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.AreaPlot'>)
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.

inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.AreaPlot'>)

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

message(**kwargs)

Inspect .param.message method for the full docstring

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.

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.AreaPlot'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

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.

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.AreaPlot'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.AreaPlot'>)
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.

state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

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.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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.

fontsize = param.Parameter(default={‘title’: ‘12pt’})

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’}

fontscale = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Scales the size of all fonts.

show_title = param.Boolean(bounds=(0, 1), default=True)

Whether to display the plot title.

title = param.String(default=’{label} {group} {dimensions}’)

The formatting string for the title of this plot, allows defining a label group separator and dimension labels.

title_format = param.String()

Alias for title.

normalize = param.Boolean(bounds=(0, 1), default=True)

Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.

projection = param.Parameter()

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

apply_ranges = param.Boolean(bounds=(0, 1), default=True)

Whether to compute the plot bounds from the data itself.

apply_extents = param.Boolean(bounds=(0, 1), default=True)

Whether to apply extent overrides on the Elements

bgcolor = param.ClassSelector(class_=(<class ‘str’>, <class ‘tuple’>))

If set bgcolor overrides the background color of the axis.

default_span = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=2.0)

Defines the span of an axis if the axis range is zero, i.e. if the lower and upper end of an axis are equal or no range is defined at all. For example if there is a single datapoint at 0 a default_span of 2.0 will result in axis ranges spanning from -1 to 1.

hooks = param.HookList(bounds=(0, None), default=[])

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.

invert_axes = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the x- and y-axis

invert_xaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot y-axis.

finalize_hooks = param.HookList(bounds=(0, None), default=[])

Deprecated; use hooks options instead.

logx = param.Boolean(bounds=(0, 1), default=False)

Whether the x-axis of the plot will be a log axis.

logy = param.Boolean(bounds=(0, 1), default=False)

Whether the y-axis of the plot will be a log axis.

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0.1)

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=True)

Whether to show legend for the plot.

show_grid = param.Boolean(bounds=(0, 1), default=False)

Whether to show a Cartesian grid on the plot.

xaxis = param.ObjectSelector(default=’bottom’, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None, True, False])

Whether and where to display the xaxis. The “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=’left’, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None, True, False])

Whether and where to display the yaxis. The “bare” options allow suppressing all axis labels, including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’, ‘left-bare’ and ‘right-bare’.

xlabel = param.String()

An explicit override of the x-axis label, if set takes precedence over the dimension label.

ylabel = param.String()

An explicit override of the y-axis label, if set takes precedence over the dimension label.

xlim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

ylim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

zlim = param.Tuple(default=(nan, nan), length=2)

User-specified z-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

xrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the xticks.

yrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the yticks.

xticks = param.Parameter()

Ticks along x-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

yticks = param.Parameter()

Ticks along y-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

shared_datasource = param.Boolean(bounds=(0, 1), default=True)

Whether Elements drawing the data from the same object should share their Bokeh data source allowing for linked brushing and other linked behaviors.

toolbar = param.ObjectSelector(default=’right’, objects=[‘above’, ‘below’, ‘left’, ‘right’, ‘disable’, None])

The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.

width = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

height = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

active_tools = param.List(bounds=(0, None), default=[])

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.

align = param.ObjectSelector(objects=[‘start’, ‘center’, ‘end’])

Alignment (vertical or horizontal) of the plot in a layout.

border = param.Number(default=10, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimum border around plot.

aspect = param.Parameter()

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(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Defines the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.

frame_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

frame_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

min_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

min_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

max_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

max_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

margin = param.Parameter()

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, objects=[False, True, ‘width’, ‘height’])

gridstyle = param.Dict(class_=<class ‘dict’>, default={})

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’])

Whether to plot the ‘x’ and ‘y’ labels.

lod = param.Dict(class_=<class ‘dict’>, default={‘factor’: 10, ‘interval’: 300, ‘threshold’: 2000, ‘timeout’: 500})

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)

Whether or not to show a complete frame around the plot.

shared_axes = param.Boolean(bounds=(0, 1), default=True)

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’])

A list of plugin tools to use on the plot.

tools = param.List(bounds=(0, None), default=[])

A list of plugin tools to use on the plot.

xformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

yformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

legend_position = param.ObjectSelector(default=’top_right’, 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_muted = param.Boolean(bounds=(0, 1), default=False)

Controls whether the legend entries are muted by default.

legend_offset = param.NumericTuple(default=(0, 0), length=2)

If legend is placed outside the axis, this determines the (width, height) offset in pixels from the original position.

legend_cols = param.Integer(default=False, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Whether to lay out the legend as columns.

color_levels = param.ClassSelector(class_=(<class ‘int’>, <class ‘list’>))

Number of discrete colors to use when colormapping or a set of color intervals defining the range of values to map each color to.

clabel = param.String()

An explicit override of the color bar label, if set takes precedence over the title key in colorbar_opts.

clim = param.NumericTuple(default=(nan, nan), 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.

cformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the colorbar axis.

colorbar = param.Boolean(bounds=(0, 1), default=False)

Whether to display a colorbar.

colorbar_position = param.ObjectSelector(default=’right’, 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={})

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={})

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)

Whether to apply log scaling to the z-axis.

symmetric = param.Boolean(bounds=(0, 1), default=False)

Whether to make the colormap symmetric around zero.

multi_level = param.Boolean(bounds=(0, 1), default=True)

Whether the Bars should be grouped into a second categorical axis level.

stacked = param.Boolean(bounds=(0, 1), default=False)

Whether the bars should be stacked or grouped.

color_index = param.ClassSelector(class_=(<class ‘str’>, <class ‘int’>))

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.

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.BarPlot'>)
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_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.BarPlot'>)
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_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.BarPlot'>)
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.

inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.BarPlot'>)

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

message(**kwargs)

Inspect .param.message method for the full docstring

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.

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.BarPlot'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

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.

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.BarPlot'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.BarPlot'>)
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.

state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

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.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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

Bases: holoviews.plotting.bokeh.element.ElementPlot

fontsize = param.Parameter(default={‘title’: ‘12pt’})

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’}

fontscale = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Scales the size of all fonts.

show_title = param.Boolean(bounds=(0, 1), default=True)

Whether to display the plot title.

title = param.String(default=’{label} {group} {dimensions}’)

The formatting string for the title of this plot, allows defining a label group separator and dimension labels.

title_format = param.String()

Alias for title.

normalize = param.Boolean(bounds=(0, 1), default=True)

Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.

projection = param.Parameter()

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

apply_ranges = param.Boolean(bounds=(0, 1), default=True)

Whether to compute the plot bounds from the data itself.

apply_extents = param.Boolean(bounds=(0, 1), default=True)

Whether to apply extent overrides on the Elements

bgcolor = param.ClassSelector(class_=(<class ‘str’>, <class ‘tuple’>))

If set bgcolor overrides the background color of the axis.

default_span = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=2.0)

Defines the span of an axis if the axis range is zero, i.e. if the lower and upper end of an axis are equal or no range is defined at all. For example if there is a single datapoint at 0 a default_span of 2.0 will result in axis ranges spanning from -1 to 1.

hooks = param.HookList(bounds=(0, None), default=[])

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.

invert_axes = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the x- and y-axis

invert_xaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot y-axis.

finalize_hooks = param.HookList(bounds=(0, None), default=[])

Deprecated; use hooks options instead.

logx = param.Boolean(bounds=(0, 1), default=False)

Whether the x-axis of the plot will be a log axis.

logy = param.Boolean(bounds=(0, 1), default=False)

Whether the y-axis of the plot will be a log axis.

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=(0, 0.1))

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=True)

Whether to show legend for the plot.

show_grid = param.Boolean(bounds=(0, 1), default=False)

Whether to show a Cartesian grid on the plot.

xaxis = param.ObjectSelector(default=’bottom’, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None, True, False])

Whether and where to display the xaxis. The “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=’left’, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None, True, False])

Whether and where to display the yaxis. The “bare” options allow suppressing all axis labels, including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’, ‘left-bare’ and ‘right-bare’.

xlabel = param.String()

An explicit override of the x-axis label, if set takes precedence over the dimension label.

ylabel = param.String()

An explicit override of the y-axis label, if set takes precedence over the dimension label.

xlim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

ylim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

zlim = param.Tuple(default=(nan, nan), length=2)

User-specified z-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

xrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the xticks.

yrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the yticks.

xticks = param.Parameter()

Ticks along x-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

yticks = param.Parameter()

Ticks along y-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

shared_datasource = param.Boolean(bounds=(0, 1), default=True)

Whether Elements drawing the data from the same object should share their Bokeh data source allowing for linked brushing and other linked behaviors.

toolbar = param.ObjectSelector(default=’right’, objects=[‘above’, ‘below’, ‘left’, ‘right’, ‘disable’, None])

The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.

width = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

height = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

active_tools = param.List(bounds=(0, None), default=[])

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.

align = param.ObjectSelector(objects=[‘start’, ‘center’, ‘end’])

Alignment (vertical or horizontal) of the plot in a layout.

border = param.Number(default=10, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimum border around plot.

aspect = param.Parameter()

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(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Defines the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.

frame_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

frame_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

min_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

min_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

max_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

max_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

margin = param.Parameter()

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, objects=[False, True, ‘width’, ‘height’])

gridstyle = param.Dict(class_=<class ‘dict’>, default={})

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’])

Whether to plot the ‘x’ and ‘y’ labels.

lod = param.Dict(class_=<class ‘dict’>, default={‘factor’: 10, ‘interval’: 300, ‘threshold’: 2000, ‘timeout’: 500})

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)

Whether or not to show a complete frame around the plot.

shared_axes = param.Boolean(bounds=(0, 1), default=True)

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’])

A list of plugin tools to use on the plot.

tools = param.List(bounds=(0, None), default=[])

A list of plugin tools to use on the plot.

xformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

yformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

interpolation = param.ObjectSelector(default=’linear’, 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.

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.CurvePlot'>)
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_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.CurvePlot'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.CurvePlot'>)
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.

inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.CurvePlot'>)

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

message(**kwargs)

Inspect .param.message method for the full docstring

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.

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.CurvePlot'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

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.

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.CurvePlot'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.CurvePlot'>)
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.

state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

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.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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

Bases: holoviews.plotting.bokeh.element.ColorbarPlot

fontsize = param.Parameter(default={‘title’: ‘12pt’})

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’}

fontscale = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Scales the size of all fonts.

show_title = param.Boolean(bounds=(0, 1), default=True)

Whether to display the plot title.

title = param.String(default=’{label} {group} {dimensions}’)

The formatting string for the title of this plot, allows defining a label group separator and dimension labels.

title_format = param.String()

Alias for title.

normalize = param.Boolean(bounds=(0, 1), default=True)

Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.

projection = param.Parameter()

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

apply_ranges = param.Boolean(bounds=(0, 1), default=True)

Whether to compute the plot bounds from the data itself.

apply_extents = param.Boolean(bounds=(0, 1), default=True)

Whether to apply extent overrides on the Elements

bgcolor = param.ClassSelector(class_=(<class ‘str’>, <class ‘tuple’>))

If set bgcolor overrides the background color of the axis.

default_span = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=2.0)

Defines the span of an axis if the axis range is zero, i.e. if the lower and upper end of an axis are equal or no range is defined at all. For example if there is a single datapoint at 0 a default_span of 2.0 will result in axis ranges spanning from -1 to 1.

hooks = param.HookList(bounds=(0, None), default=[])

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.

invert_axes = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the x- and y-axis

invert_xaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot y-axis.

finalize_hooks = param.HookList(bounds=(0, None), default=[])

Deprecated; use hooks options instead.

logx = param.Boolean(bounds=(0, 1), default=False)

Whether the x-axis of the plot will be a log axis.

logy = param.Boolean(bounds=(0, 1), default=False)

Whether the y-axis of the plot will be a log axis.

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0.1)

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=True)

Whether to show legend for the plot.

show_grid = param.Boolean(bounds=(0, 1), default=False)

Whether to show a Cartesian grid on the plot.

xaxis = param.ObjectSelector(default=’bottom’, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None, True, False])

Whether and where to display the xaxis. The “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=’left’, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None, True, False])

Whether and where to display the yaxis. The “bare” options allow suppressing all axis labels, including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’, ‘left-bare’ and ‘right-bare’.

xlabel = param.String()

An explicit override of the x-axis label, if set takes precedence over the dimension label.

ylabel = param.String()

An explicit override of the y-axis label, if set takes precedence over the dimension label.

xlim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

ylim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

zlim = param.Tuple(default=(nan, nan), length=2)

User-specified z-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

xrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the xticks.

yrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the yticks.

xticks = param.Parameter()

Ticks along x-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

yticks = param.Parameter()

Ticks along y-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

shared_datasource = param.Boolean(bounds=(0, 1), default=True)

Whether Elements drawing the data from the same object should share their Bokeh data source allowing for linked brushing and other linked behaviors.

toolbar = param.ObjectSelector(default=’right’, objects=[‘above’, ‘below’, ‘left’, ‘right’, ‘disable’, None])

The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.

width = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

height = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

active_tools = param.List(bounds=(0, None), default=[])

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.

align = param.ObjectSelector(objects=[‘start’, ‘center’, ‘end’])

Alignment (vertical or horizontal) of the plot in a layout.

border = param.Number(default=10, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimum border around plot.

aspect = param.Parameter()

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(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Defines the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.

frame_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

frame_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

min_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

min_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

max_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

max_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

margin = param.Parameter()

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, objects=[False, True, ‘width’, ‘height’])

gridstyle = param.Dict(class_=<class ‘dict’>, default={})

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’])

Whether to plot the ‘x’ and ‘y’ labels.

lod = param.Dict(class_=<class ‘dict’>, default={‘factor’: 10, ‘interval’: 300, ‘threshold’: 2000, ‘timeout’: 500})

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)

Whether or not to show a complete frame around the plot.

shared_axes = param.Boolean(bounds=(0, 1), default=True)

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’])

A list of plugin tools to use on the plot.

tools = param.List(bounds=(0, None), default=[])

A list of plugin tools to use on the plot.

xformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

yformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

color_levels = param.ClassSelector(class_=(<class ‘int’>, <class ‘list’>))

Number of discrete colors to use when colormapping or a set of color intervals defining the range of values to map each color to.

clabel = param.String()

An explicit override of the color bar label, if set takes precedence over the title key in colorbar_opts.

clim = param.NumericTuple(default=(nan, nan), 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.

cformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the colorbar axis.

colorbar = param.Boolean(bounds=(0, 1), default=False)

Whether to display a colorbar.

colorbar_position = param.ObjectSelector(default=’right’, 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={})

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={})

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)

Whether to apply log scaling to the z-axis.

symmetric = param.Boolean(bounds=(0, 1), default=False)

Whether to make the colormap symmetric around zero.

selected = param.List(bounds=(0, None))

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.

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.ErrorPlot'>)
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_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.ErrorPlot'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.ErrorPlot'>)
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.

inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.ErrorPlot'>)

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

message(**kwargs)

Inspect .param.message method for the full docstring

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.

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.ErrorPlot'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

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.

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.ErrorPlot'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.ErrorPlot'>)
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.

state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

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.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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

Bases: holoviews.plotting.bokeh.element.ColorbarPlot

fontsize = param.Parameter(default={‘title’: ‘12pt’})

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’}

fontscale = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Scales the size of all fonts.

show_title = param.Boolean(bounds=(0, 1), default=True)

Whether to display the plot title.

title = param.String(default=’{label} {group} {dimensions}’)

The formatting string for the title of this plot, allows defining a label group separator and dimension labels.

title_format = param.String()

Alias for title.

normalize = param.Boolean(bounds=(0, 1), default=True)

Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.

projection = param.Parameter()

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

apply_ranges = param.Boolean(bounds=(0, 1), default=True)

Whether to compute the plot bounds from the data itself.

apply_extents = param.Boolean(bounds=(0, 1), default=True)

Whether to apply extent overrides on the Elements

bgcolor = param.ClassSelector(class_=(<class ‘str’>, <class ‘tuple’>))

If set bgcolor overrides the background color of the axis.

default_span = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=2.0)

Defines the span of an axis if the axis range is zero, i.e. if the lower and upper end of an axis are equal or no range is defined at all. For example if there is a single datapoint at 0 a default_span of 2.0 will result in axis ranges spanning from -1 to 1.

hooks = param.HookList(bounds=(0, None), default=[])

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.

invert_axes = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the x- and y-axis

invert_xaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot y-axis.

finalize_hooks = param.HookList(bounds=(0, None), default=[])

Deprecated; use hooks options instead.

logx = param.Boolean(bounds=(0, 1), default=False)

Whether the x-axis of the plot will be a log axis.

logy = param.Boolean(bounds=(0, 1), default=False)

Whether the y-axis of the plot will be a log axis.

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0.1)

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=True)

Whether to show legend for the plot.

show_grid = param.Boolean(bounds=(0, 1), default=False)

Whether to show a Cartesian grid on the plot.

xaxis = param.ObjectSelector(default=’bottom’, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None, True, False])

Whether and where to display the xaxis. The “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=’left’, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None, True, False])

Whether and where to display the yaxis. The “bare” options allow suppressing all axis labels, including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’, ‘left-bare’ and ‘right-bare’.

xlabel = param.String()

An explicit override of the x-axis label, if set takes precedence over the dimension label.

ylabel = param.String()

An explicit override of the y-axis label, if set takes precedence over the dimension label.

xlim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

ylim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

zlim = param.Tuple(default=(nan, nan), length=2)

User-specified z-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

xrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the xticks.

yrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the yticks.

xticks = param.Parameter()

Ticks along x-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

yticks = param.Parameter()

Ticks along y-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

shared_datasource = param.Boolean(bounds=(0, 1), default=True)

Whether Elements drawing the data from the same object should share their Bokeh data source allowing for linked brushing and other linked behaviors.

toolbar = param.ObjectSelector(default=’right’, objects=[‘above’, ‘below’, ‘left’, ‘right’, ‘disable’, None])

The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.

width = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

height = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

active_tools = param.List(bounds=(0, None), default=[])

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.

align = param.ObjectSelector(objects=[‘start’, ‘center’, ‘end’])

Alignment (vertical or horizontal) of the plot in a layout.

border = param.Number(default=10, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimum border around plot.

aspect = param.Parameter()

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(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Defines the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.

frame_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

frame_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

min_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

min_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

max_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

max_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

margin = param.Parameter()

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, objects=[False, True, ‘width’, ‘height’])

gridstyle = param.Dict(class_=<class ‘dict’>, default={})

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’])

Whether to plot the ‘x’ and ‘y’ labels.

lod = param.Dict(class_=<class ‘dict’>, default={‘factor’: 10, ‘interval’: 300, ‘threshold’: 2000, ‘timeout’: 500})

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)

Whether or not to show a complete frame around the plot.

shared_axes = param.Boolean(bounds=(0, 1), default=True)

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’])

A list of plugin tools to use on the plot.

tools = param.List(bounds=(0, None), default=[])

A list of plugin tools to use on the plot.

xformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

yformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

color_levels = param.ClassSelector(class_=(<class ‘int’>, <class ‘list’>))

Number of discrete colors to use when colormapping or a set of color intervals defining the range of values to map each color to.

clabel = param.String()

An explicit override of the color bar label, if set takes precedence over the title key in colorbar_opts.

clim = param.NumericTuple(default=(nan, nan), 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.

cformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the colorbar axis.

colorbar = param.Boolean(bounds=(0, 1), default=False)

Whether to display a colorbar.

colorbar_position = param.ObjectSelector(default=’right’, 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={})

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={})

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)

Whether to apply log scaling to the z-axis.

symmetric = param.Boolean(bounds=(0, 1), default=False)

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.

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.HistogramPlot'>)
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_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.HistogramPlot'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.HistogramPlot'>)
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.

inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.HistogramPlot'>)

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

message(**kwargs)

Inspect .param.message method for the full docstring

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.

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.HistogramPlot'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

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.

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.HistogramPlot'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.HistogramPlot'>)
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.

state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

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.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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

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

fontsize = param.Parameter(default={‘title’: ‘12pt’})

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’}

fontscale = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Scales the size of all fonts.

show_title = param.Boolean(bounds=(0, 1), default=True)

Whether to display the plot title.

title = param.String(default=’{label} {group} {dimensions}’)

The formatting string for the title of this plot, allows defining a label group separator and dimension labels.

title_format = param.String()

Alias for title.

normalize = param.Boolean(bounds=(0, 1), default=True)

Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.

projection = param.Parameter()

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

apply_ranges = param.Boolean(bounds=(0, 1), default=True)

Whether to compute the plot bounds from the data itself.

apply_extents = param.Boolean(bounds=(0, 1), default=True)

Whether to apply extent overrides on the Elements

bgcolor = param.ClassSelector(class_=(<class ‘str’>, <class ‘tuple’>))

If set bgcolor overrides the background color of the axis.

default_span = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=2.0)

Defines the span of an axis if the axis range is zero, i.e. if the lower and upper end of an axis are equal or no range is defined at all. For example if there is a single datapoint at 0 a default_span of 2.0 will result in axis ranges spanning from -1 to 1.

hooks = param.HookList(bounds=(0, None), default=[])

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.

invert_axes = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the x- and y-axis

invert_xaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot y-axis.

finalize_hooks = param.HookList(bounds=(0, None), default=[])

Deprecated; use hooks options instead.

logx = param.Boolean(bounds=(0, 1), default=False)

Whether the x-axis of the plot will be a log axis.

logy = param.Boolean(bounds=(0, 1), default=False)

Whether the y-axis of the plot will be a log axis.

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0.1)

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=True)

Whether to show legend for the plot.

show_grid = param.Boolean(bounds=(0, 1), default=False)

Whether to show a Cartesian grid on the plot.

xaxis = param.ObjectSelector(default=’bottom’, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None, True, False])

Whether and where to display the xaxis. The “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=’left’, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None, True, False])

Whether and where to display the yaxis. The “bare” options allow suppressing all axis labels, including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’, ‘left-bare’ and ‘right-bare’.

xlabel = param.String()

An explicit override of the x-axis label, if set takes precedence over the dimension label.

ylabel = param.String()

An explicit override of the y-axis label, if set takes precedence over the dimension label.

xlim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

ylim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

zlim = param.Tuple(default=(nan, nan), length=2)

User-specified z-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

xrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the xticks.

yrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the yticks.

xticks = param.Parameter()

Ticks along x-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

yticks = param.Parameter()

Ticks along y-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

shared_datasource = param.Boolean(bounds=(0, 1), default=True)

Whether Elements drawing the data from the same object should share their Bokeh data source allowing for linked brushing and other linked behaviors.

toolbar = param.ObjectSelector(default=’right’, objects=[‘above’, ‘below’, ‘left’, ‘right’, ‘disable’, None])

The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.

width = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

height = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

active_tools = param.List(bounds=(0, None), default=[])

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.

align = param.ObjectSelector(objects=[‘start’, ‘center’, ‘end’])

Alignment (vertical or horizontal) of the plot in a layout.

border = param.Number(default=10, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimum border around plot.

aspect = param.Parameter()

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(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Defines the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.

frame_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

frame_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

min_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

min_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

max_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

max_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

margin = param.Parameter()

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, objects=[False, True, ‘width’, ‘height’])

gridstyle = param.Dict(class_=<class ‘dict’>, default={})

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’])

Whether to plot the ‘x’ and ‘y’ labels.

lod = param.Dict(class_=<class ‘dict’>, default={‘factor’: 10, ‘interval’: 300, ‘threshold’: 2000, ‘timeout’: 500})

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)

Whether or not to show a complete frame around the plot.

shared_axes = param.Boolean(bounds=(0, 1), default=True)

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’])

A list of plugin tools to use on the plot.

tools = param.List(bounds=(0, None), default=[])

A list of plugin tools to use on the plot.

xformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

yformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

color_levels = param.ClassSelector(class_=(<class ‘int’>, <class ‘list’>))

Number of discrete colors to use when colormapping or a set of color intervals defining the range of values to map each color to.

clabel = param.String()

An explicit override of the color bar label, if set takes precedence over the title key in colorbar_opts.

clim = param.NumericTuple(default=(nan, nan), 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.

cformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the colorbar axis.

colorbar = param.Boolean(bounds=(0, 1), default=False)

Whether to display a colorbar.

colorbar_position = param.ObjectSelector(default=’right’, 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={})

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={})

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)

Whether to apply log scaling to the z-axis.

symmetric = param.Boolean(bounds=(0, 1), default=False)

Whether to make the colormap symmetric around zero.

legend_position = param.ObjectSelector(default=’top_right’, 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_muted = param.Boolean(bounds=(0, 1), default=False)

Controls whether the legend entries are muted by default.

legend_offset = param.NumericTuple(default=(0, 0), length=2)

If legend is placed outside the axis, this determines the (width, height) offset in pixels from the original position.

legend_cols = param.Integer(default=False, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Whether to lay out the legend as columns.

jitter = param.Number(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The amount of jitter to apply to offset the points along the x-axis.

selected = param.List(bounds=(0, None))

The current selection as a list of integers corresponding to the selected items.

color_index = param.ClassSelector(class_=(<class ‘str’>, <class ‘int’>))

Deprecated in favor of color style mapping, e.g. color=dim(‘color’)

size_index = param.ClassSelector(class_=(<class ‘str’>, <class ‘int’>))

Deprecated in favor of size style mapping, e.g. size=dim(‘size’)

scaling_method = param.ObjectSelector(default=’area’, 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), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

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’>)

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.

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.PointPlot'>)
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_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.PointPlot'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.PointPlot'>)
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.

inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.PointPlot'>)

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

message(**kwargs)

Inspect .param.message method for the full docstring

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.

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.PointPlot'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

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.

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.PointPlot'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.PointPlot'>)
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.

state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

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.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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

Bases: holoviews.plotting.bokeh.chart.HistogramPlot

fontsize = param.Parameter(default={‘title’: ‘12pt’})

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’}

fontscale = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Scales the size of all fonts.

show_title = param.Boolean(bounds=(0, 1), default=False)

Whether to display the plot title.

title = param.String(default=’{label} {group} {dimensions}’)

The formatting string for the title of this plot, allows defining a label group separator and dimension labels.

title_format = param.String()

Alias for title.

normalize = param.Boolean(bounds=(0, 1), default=True)

Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.

projection = param.Parameter()

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

apply_ranges = param.Boolean(bounds=(0, 1), default=True)

Whether to compute the plot bounds from the data itself.

apply_extents = param.Boolean(bounds=(0, 1), default=True)

Whether to apply extent overrides on the Elements

bgcolor = param.ClassSelector(class_=(<class ‘str’>, <class ‘tuple’>))

If set bgcolor overrides the background color of the axis.

default_span = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=2.0)

Defines the span of an axis if the axis range is zero, i.e. if the lower and upper end of an axis are equal or no range is defined at all. For example if there is a single datapoint at 0 a default_span of 2.0 will result in axis ranges spanning from -1 to 1.

hooks = param.HookList(bounds=(0, None), default=[])

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.

invert_axes = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the x- and y-axis

invert_xaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot y-axis.

finalize_hooks = param.HookList(bounds=(0, None), default=[])

Deprecated; use hooks options instead.

logx = param.Boolean(bounds=(0, 1), default=False)

Whether the x-axis of the plot will be a log axis.

logy = param.Boolean(bounds=(0, 1), default=False)

Whether the y-axis of the plot will be a log axis.

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0.1)

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=True)

Whether to show legend for the plot.

show_grid = param.Boolean(bounds=(0, 1), default=False)

Whether to show a Cartesian grid on the plot.

xaxis = param.ObjectSelector(default=’bottom’, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None, True, False])

Whether and where to display the xaxis. The “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=’left’, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None, True, False])

Whether and where to display the yaxis. The “bare” options allow suppressing all axis labels, including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’, ‘left-bare’ and ‘right-bare’.

xlabel = param.String()

An explicit override of the x-axis label, if set takes precedence over the dimension label.

ylabel = param.String()

An explicit override of the y-axis label, if set takes precedence over the dimension label.

xlim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

ylim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

zlim = param.Tuple(default=(nan, nan), length=2)

User-specified z-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

xrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the xticks.

yrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the yticks.

xticks = param.Parameter()

Ticks along x-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

yticks = param.Parameter()

Ticks along y-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

shared_datasource = param.Boolean(bounds=(0, 1), default=True)

Whether Elements drawing the data from the same object should share their Bokeh data source allowing for linked brushing and other linked behaviors.

toolbar = param.ObjectSelector(default=’right’, objects=[‘above’, ‘below’, ‘left’, ‘right’, ‘disable’, None])

The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.

width = param.Integer(bounds=(0, None), default=125, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the plot

height = param.Integer(bounds=(0, None), default=125, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the plot

active_tools = param.List(bounds=(0, None), default=[])

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.

align = param.ObjectSelector(objects=[‘start’, ‘center’, ‘end’])

Alignment (vertical or horizontal) of the plot in a layout.

border = param.Number(default=10, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimum border around plot.

aspect = param.Parameter()

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(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Defines the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.

frame_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

frame_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

min_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

min_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

max_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

max_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

margin = param.Parameter()

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, objects=[False, True, ‘width’, ‘height’])

gridstyle = param.Dict(class_=<class ‘dict’>, default={})

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’])

Whether to plot the ‘x’ and ‘y’ labels.

lod = param.Dict(class_=<class ‘dict’>, default={‘factor’: 10, ‘interval’: 300, ‘threshold’: 2000, ‘timeout’: 500})

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)

Whether or not to show a complete frame around the plot.

shared_axes = param.Boolean(bounds=(0, 1), default=True)

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’])

A list of plugin tools to use on the plot.

tools = param.List(bounds=(0, None), default=[])

A list of plugin tools to use on the plot.

xformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

yformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

color_levels = param.ClassSelector(class_=(<class ‘int’>, <class ‘list’>))

Number of discrete colors to use when colormapping or a set of color intervals defining the range of values to map each color to.

clabel = param.String()

An explicit override of the color bar label, if set takes precedence over the title key in colorbar_opts.

clim = param.NumericTuple(default=(nan, nan), 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.

cformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the colorbar axis.

colorbar = param.Boolean(bounds=(0, 1), default=False)

Whether to display a colorbar.

colorbar_position = param.ObjectSelector(default=’right’, 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={})

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={})

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)

Whether to apply log scaling to the z-axis.

symmetric = param.Boolean(bounds=(0, 1), default=False)

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.

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SideHistogramPlot'>)
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_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SideHistogramPlot'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SideHistogramPlot'>)
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.

inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SideHistogramPlot'>)

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

message(**kwargs)

Inspect .param.message method for the full docstring

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.

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SideHistogramPlot'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

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.

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SideHistogramPlot'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SideHistogramPlot'>)
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.

state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

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.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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.

fontsize = param.Parameter(default={‘title’: ‘12pt’})

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’}

fontscale = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Scales the size of all fonts.

show_title = param.Boolean(bounds=(0, 1), default=True)

Whether to display the plot title.

title = param.String(default=’{label} {group} {dimensions}’)

The formatting string for the title of this plot, allows defining a label group separator and dimension labels.

title_format = param.String()

Alias for title.

normalize = param.Boolean(bounds=(0, 1), default=True)

Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.

projection = param.Parameter()

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

apply_ranges = param.Boolean(bounds=(0, 1), default=True)

Whether to compute the plot bounds from the data itself.

apply_extents = param.Boolean(bounds=(0, 1), default=True)

Whether to apply extent overrides on the Elements

bgcolor = param.ClassSelector(class_=(<class ‘str’>, <class ‘tuple’>))

If set bgcolor overrides the background color of the axis.

default_span = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=2.0)

Defines the span of an axis if the axis range is zero, i.e. if the lower and upper end of an axis are equal or no range is defined at all. For example if there is a single datapoint at 0 a default_span of 2.0 will result in axis ranges spanning from -1 to 1.

hooks = param.HookList(bounds=(0, None), default=[])

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.

invert_axes = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the x- and y-axis

invert_xaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot y-axis.

finalize_hooks = param.HookList(bounds=(0, None), default=[])

Deprecated; use hooks options instead.

logx = param.Boolean(bounds=(0, 1), default=False)

Whether the x-axis of the plot will be a log axis.

logy = param.Boolean(bounds=(0, 1), default=False)

Whether the y-axis of the plot will be a log axis.

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0.1)

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=True)

Whether to show legend for the plot.

show_grid = param.Boolean(bounds=(0, 1), default=False)

Whether to show a Cartesian grid on the plot.

xaxis = param.ObjectSelector(default=’top-bare’, 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’, 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’.

xlabel = param.String()

An explicit override of the x-axis label, if set takes precedence over the dimension label.

ylabel = param.String()

An explicit override of the y-axis label, if set takes precedence over the dimension label.

xlim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

ylim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

zlim = param.Tuple(default=(nan, nan), length=2)

User-specified z-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

xrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the xticks.

yrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the yticks.

xticks = param.Parameter()

Ticks along x-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

yticks = param.Parameter()

Ticks along y-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

shared_datasource = param.Boolean(bounds=(0, 1), default=True)

Whether Elements drawing the data from the same object should share their Bokeh data source allowing for linked brushing and other linked behaviors.

toolbar = param.ObjectSelector(default=’right’, objects=[‘above’, ‘below’, ‘left’, ‘right’, ‘disable’, None])

The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.

width = param.Integer(bounds=(0, None), default=50, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Width of plot

height = param.Integer(bounds=(0, None), default=50, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Height of plot

active_tools = param.List(bounds=(0, None), default=[])

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.

align = param.ObjectSelector(objects=[‘start’, ‘center’, ‘end’])

Alignment (vertical or horizontal) of the plot in a layout.

border = param.Integer(default=5, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Default borders on plot

aspect = param.Parameter()

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(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Defines the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.

frame_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

frame_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

min_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

min_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

max_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

max_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

margin = param.Parameter()

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, objects=[False, True, ‘width’, ‘height’])

gridstyle = param.Dict(class_=<class ‘dict’>, default={})

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’])

Whether to plot the ‘x’ and ‘y’ labels.

lod = param.Dict(class_=<class ‘dict’>, default={‘factor’: 10, ‘interval’: 300, ‘threshold’: 2000, ‘timeout’: 500})

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)

Whether or not to show a complete frame around the plot.

shared_axes = param.Boolean(bounds=(0, 1), default=True)

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’])

A list of plugin tools to use on the plot.

tools = param.List(bounds=(0, None), default=[])

A list of plugin tools to use on the plot.

xformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

yformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

color_levels = param.ClassSelector(class_=(<class ‘int’>, <class ‘list’>))

Number of discrete colors to use when colormapping or a set of color intervals defining the range of values to map each color to.

clabel = param.String()

An explicit override of the color bar label, if set takes precedence over the title key in colorbar_opts.

clim = param.NumericTuple(default=(nan, nan), 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.

cformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the colorbar axis.

colorbar = param.Boolean(bounds=(0, 1), default=False)

Whether to display a colorbar.

colorbar_position = param.ObjectSelector(default=’right’, 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={})

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={})

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)

Whether to apply log scaling to the z-axis.

symmetric = param.Boolean(bounds=(0, 1), default=False)

Whether to make the colormap symmetric around zero.

spike_length = param.Number(default=0.5, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The length of each spike if Spikes object is one dimensional.

position = param.Number(default=0.0, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The position of the lower end of each spike.

color_index = param.ClassSelector(class_=(<class ‘str’>, <class ‘int’>))

Deprecated in favor of color style mapping, e.g. color=dim(‘color’)

selected = param.List(bounds=(0, None))

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.

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SideSpikesPlot'>)
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_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SideSpikesPlot'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SideSpikesPlot'>)
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.

inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SideSpikesPlot'>)

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

message(**kwargs)

Inspect .param.message method for the full docstring

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.

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SideSpikesPlot'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

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.

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default(*args, **kwargs)

Inspect .param.set_default method for the full docstring

set_dynamic_time_fn = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SideSpikesPlot'>)
set_param = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SideSpikesPlot'>)
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.

state_pop()

Restore the most recently saved state.

See state_push() for more details.

state_push()

Save this instance’s state.

For Parameterized instances, this includes the state of dynamically generated values.

Subclasses that maintain short-term state should additionally save and restore that state using state_push() and state_pop().

Generally, this method is used by operations that need to test something without permanently altering the objects’ state.

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.

verbose(**kwargs)

Inspect .param.verbose method for the full docstring

warning(**kwargs)

Inspect .param.warning method for the full docstring

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

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

fontsize = param.Parameter(default={‘title’: ‘12pt’})

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’}

fontscale = param.Number(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Scales the size of all fonts.

show_title = param.Boolean(bounds=(0, 1), default=True)

Whether to display the plot title.

title = param.String(default=’{label} {group} {dimensions}’)

The formatting string for the title of this plot, allows defining a label group separator and dimension labels.

title_format = param.String()

Alias for title.

normalize = param.Boolean(bounds=(0, 1), default=True)

Whether to compute ranges across all Elements at this level of plotting. Allows selecting normalization at different levels for nested data containers.

projection = param.Parameter()

Allows supplying a custom projection to transform the axis coordinates during display. Example projections include ‘3d’ and ‘polar’ projections supported by some backends. Depending on the backend custom, projection objects may be supplied.

apply_ranges = param.Boolean(bounds=(0, 1), default=True)

Whether to compute the plot bounds from the data itself.

apply_extents = param.Boolean(bounds=(0, 1), default=True)

Whether to apply extent overrides on the Elements

bgcolor = param.ClassSelector(class_=(<class ‘str’>, <class ‘tuple’>))

If set bgcolor overrides the background color of the axis.

default_span = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=2.0)

Defines the span of an axis if the axis range is zero, i.e. if the lower and upper end of an axis are equal or no range is defined at all. For example if there is a single datapoint at 0 a default_span of 2.0 will result in axis ranges spanning from -1 to 1.

hooks = param.HookList(bounds=(0, None), default=[])

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.

invert_axes = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the x- and y-axis

invert_xaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot x-axis.

invert_yaxis = param.Boolean(bounds=(0, 1), default=False)

Whether to invert the plot y-axis.

finalize_hooks = param.HookList(bounds=(0, None), default=[])

Deprecated; use hooks options instead.

logx = param.Boolean(bounds=(0, 1), default=False)

Whether the x-axis of the plot will be a log axis.

logy = param.Boolean(bounds=(0, 1), default=False)

Whether the y-axis of the plot will be a log axis.

padding = param.ClassSelector(class_=(<class ‘int’>, <class ‘float’>, <class ‘tuple’>), default=0.1)

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=True)

Whether to show legend for the plot.

show_grid = param.Boolean(bounds=(0, 1), default=False)

Whether to show a Cartesian grid on the plot.

xaxis = param.ObjectSelector(default=’bottom’, objects=[‘top’, ‘bottom’, ‘bare’, ‘top-bare’, ‘bottom-bare’, None, True, False])

Whether and where to display the xaxis. The “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=’left’, objects=[‘left’, ‘right’, ‘bare’, ‘left-bare’, ‘right-bare’, None, True, False])

Whether and where to display the yaxis. The “bare” options allow suppressing all axis labels, including ticks and ylabel. Valid options are ‘left’, ‘right’, ‘bare’, ‘left-bare’ and ‘right-bare’.

xlabel = param.String()

An explicit override of the x-axis label, if set takes precedence over the dimension label.

ylabel = param.String()

An explicit override of the y-axis label, if set takes precedence over the dimension label.

xlim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

ylim = param.Tuple(default=(nan, nan), length=2)

User-specified x-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

zlim = param.Tuple(default=(nan, nan), length=2)

User-specified z-axis range limits for the plot, as a tuple (low,high). If specified, takes precedence over data and dimension ranges.

xrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the xticks.

yrotation = param.Integer(bounds=(0, 360), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Rotation angle of the yticks.

xticks = param.Parameter()

Ticks along x-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

yticks = param.Parameter()

Ticks along y-axis specified as an integer, explicit list of tick locations, or bokeh Ticker object. If set to None default bokeh ticking behavior is applied.

shared_datasource = param.Boolean(bounds=(0, 1), default=True)

Whether Elements drawing the data from the same object should share their Bokeh data source allowing for linked brushing and other linked behaviors.

toolbar = param.ObjectSelector(default=’right’, objects=[‘above’, ‘below’, ‘left’, ‘right’, ‘disable’, None])

The toolbar location, must be one of ‘above’, ‘below’, ‘left’, ‘right’, None.

width = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

height = param.Integer(bounds=(0, None), default=300, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

active_tools = param.List(bounds=(0, None), default=[])

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.

align = param.ObjectSelector(objects=[‘start’, ‘center’, ‘end’])

Alignment (vertical or horizontal) of the plot in a layout.

border = param.Number(default=10, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimum border around plot.

aspect = param.Parameter()

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(inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Defines the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.

frame_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The width of the component (in pixels). This can be either fixed or preferred width, depending on width sizing policy.

frame_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The height of the component (in pixels). This can be either fixed or preferred height, depending on height sizing policy.

min_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

min_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

max_width = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal width of the component (in pixels) if width is adjustable.

max_height = param.Integer(bounds=(0, None), inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

Minimal height of the component (in pixels) if height is adjustable.

margin = param.Parameter()

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, objects=[False, True, ‘width’, ‘height’])

gridstyle = param.Dict(class_=<class ‘dict’>, default={})

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’])

Whether to plot the ‘x’ and ‘y’ labels.

lod = param.Dict(class_=<class ‘dict’>, default={‘factor’: 10, ‘interval’: 300, ‘threshold’: 2000, ‘timeout’: 500})

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)

Whether or not to show a complete frame around the plot.

shared_axes = param.Boolean(bounds=(0, 1), default=True)

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’])

A list of plugin tools to use on the plot.

tools = param.List(bounds=(0, None), default=[])

A list of plugin tools to use on the plot.

xformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

yformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the x-axis.

color_levels = param.ClassSelector(class_=(<class ‘int’>, <class ‘list’>))

Number of discrete colors to use when colormapping or a set of color intervals defining the range of values to map each color to.

clabel = param.String()

An explicit override of the color bar label, if set takes precedence over the title key in colorbar_opts.

clim = param.NumericTuple(default=(nan, nan), 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.

cformatter = param.ClassSelector(class_=(<class ‘str’>, <class ‘bokeh.models.formatters.TickFormatter’>, <class ‘function’>))

Formatter for ticks along the colorbar axis.

colorbar = param.Boolean(bounds=(0, 1), default=False)

Whether to display a colorbar.

colorbar_position = param.ObjectSelector(default=’right’, 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={})

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={})

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)

Whether to apply log scaling to the z-axis.

symmetric = param.Boolean(bounds=(0, 1), default=False)

Whether to make the colormap symmetric around zero.

spike_length = param.Number(default=0.5, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The length of each spike if Spikes object is one dimensional.

position = param.Number(default=0.0, inclusive_bounds=(True, True), time_dependent=False, time_fn=Time(label=’Time’, name=’Time00001’, time_type=<class ‘int’>, timestep=1.0, unit=None, until=Infinity()))

The position of the lower end of each spike.

color_index = param.ClassSelector(class_=(<class ‘str’>, <class ‘int’>))

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.

debug(**kwargs)

Inspect .param.debug method for the full docstring

defaults(**kwargs)

Inspect .param.defaults method for the full docstring

force_new_dynamic_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SpikesPlot'>)
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_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_param_values = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SpikesPlot'>)
get_value_generator = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SpikesPlot'>)
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.

inspect_value = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SpikesPlot'>)

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

message(**kwargs)

Inspect .param.message method for the full docstring

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.

params = functools.partial(<function Parameters.deprecate.<locals>.inner>, <class 'holoviews.plotting.bokeh.chart.SpikesPlot'>)
pprint(imports=None, prefix=' ', unknown_value='<?>', qualify=False, separator='')

(Experimental) Pretty printed representation that may be evaluated with eval. See pprint() function for more details.

classmethod print_param_defaults(*args, **kwargs)

Inspect .param.print_param_defaults method for the full docstring

print_param_values(**kwargs)

Inspect .param.print_param_values method for the full docstring

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.

script_repr(imports=[], prefix=' ')

Variant of __repr__ designed for generating a runnable script.

classmethod set_default