holoviews.plotly Package

---

plotly Package

---

annotation Module

class holoviews.plotting.plotly.annotation.LabelPlot(element, plot=None, **params)

Bases: ScatterPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

holoviews.plotting.plotly.chart.ScatterPlot: color_index

xoffset = Number(allow_None=True, inclusive_bounds=(True, True), label='Xoffset')

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

yoffset = Number(allow_None=True, inclusive_bounds=(True, True), label='Yoffset')

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

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

---

callbacks Module

class holoviews.plotting.plotly.callbacks.PlotlyCallbackMetaClass(name, bases, attrs)

Bases: type

Metaclass for PlotlyCallback classes.

We want each callback class to keep track of all of the instances of the class. Using a meta class here lets us keep the logic for instance tracking in one place.

mro()

Return a type’s method resolution order.

---

chart Module

class holoviews.plotting.plotly.chart.AreaPlot(element, plot=None, **params)

Bases: AreaMixin, ChartPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

padding = ClassSelector(class_=(<class 'int'>, <class 'float'>, <class 'tuple'>), default=(0, 0.1), label='Padding')

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

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart.BarPlot(element, plot=None, **params)

Bases: BarsMixin, ElementPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

show_legend = Boolean(default=True, label='Show legend')

Whether to show legend for the plot.

multi_level = Boolean(default=True, label='Multi level')

Whether the Bars should be grouped into a second categorical axis level.

stacked = Boolean(default=False, label='Stacked')

Whether the bars should be stacked or grouped.

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)

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_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart.ChartPlot(element, plot=None, **params)

Bases: ElementPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart.CurvePlot(element, plot=None, **params)

Bases: ChartPlot, ColorbarPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

padding = ClassSelector(class_=(<class 'int'>, <class 'float'>, <class 'tuple'>), default=(0, 0.1), label='Padding')

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

interpolation = Selector(default='linear', label='Interpolation', names={}, 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 on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart.ErrorBarsPlot(element, plot=None, **params)

Bases: ChartPlot, ColorbarPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart.HistogramPlot(element, plot=None, **params)

Bases: ElementPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart.ScatterPlot(element, plot=None, **params)

Bases: ChartPlot, ColorbarPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

color_index = ClassSelector(allow_None=True, class_=(<class 'str'>, <class 'int'>), label='Color index')

Index of the dimension from which the color will the drawn

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart.SpreadPlot(element, plot=None, **params)

Bases: ChartPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

padding = ClassSelector(class_=(<class 'int'>, <class 'float'>, <class 'tuple'>), default=(0, 0.1), label='Padding')

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

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

---

chart3d Module

class holoviews.plotting.plotly.chart3d.Chart3DPlot(element, plot=None, **params)

Bases: ElementPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, invert_zaxis, labelled, logz, margins, responsive, zlabel

projection = String(default='3d', label='Projection')

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.

width = Integer(default=500, inclusive_bounds=(True, True), label='Width')

height = Integer(default=500, inclusive_bounds=(True, True), label='Height')

aspect = Parameter(default='cube', label='Aspect')

The aspect ratio mode of the plot. By default, a plot may select its own appropriate aspect ratio but sometimes it may be necessary to force a square aspect ratio (e.g. to display the plot as an element of a grid). The modes ‘auto’ and ‘equal’ correspond to the axis modes of the same name in matplotlib, a numeric value may also be passed.

zticks = Parameter(allow_None=True, label='Zticks')

Ticks along z-axis specified as an integer, explicit list of tick locations, list of tuples containing the locations.

camera_angle = NumericTuple(default=(0.2, 0.5, 0.1, 0.2), label='Camera angle', length=4)

camera_position = NumericTuple(default=(0.1, 0, -0.1), label='Camera position', length=3)

camera_zoom = Integer(default=3, inclusive_bounds=(True, True), label='Camera zoom')

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart3d.Path3DPlot(element, plot=None, **params)

Bases: Chart3DPlot, CurvePlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, invert_zaxis, labelled, logz, margins, responsive, zlabel

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

holoviews.plotting.plotly.chart.CurvePlot: padding, interpolation

holoviews.plotting.plotly.chart3d.Chart3DPlot: projection, width, height, aspect, zticks, camera_angle, camera_position, camera_zoom

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart3d.Scatter3DPlot(element, plot=None, **params)

Bases: Chart3DPlot, ScatterPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, invert_zaxis, labelled, logz, margins, responsive, zlabel

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

holoviews.plotting.plotly.chart.ScatterPlot: color_index

holoviews.plotting.plotly.chart3d.Chart3DPlot: projection, width, height, aspect, zticks, camera_angle, camera_position, camera_zoom

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart3d.SurfacePlot(element, plot=None, **params)

Bases: Chart3DPlot, ColorbarPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, invert_zaxis, labelled, logz, margins, responsive, zlabel

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

holoviews.plotting.plotly.chart3d.Chart3DPlot: projection, width, height, aspect, zticks, camera_angle, camera_position, camera_zoom

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.chart3d.TriSurfacePlot(element, plot=None, **params)

Bases: Chart3DPlot, ColorbarPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, invert_zaxis, labelled, logz, margins, responsive, zlabel

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

holoviews.plotting.plotly.chart3d.Chart3DPlot: projection, width, height, aspect, zticks, camera_angle, camera_position, camera_zoom

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

---

dash Module

---

element Module

class holoviews.plotting.plotly.element.ColorbarPlot(element, plot=None, **params)

Bases: ElementPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

clim = NumericTuple(default=(nan, nan), label='Clim', length=2)

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

clim_percentile = ClassSelector(class_=(<class 'int'>, <class 'float'>, <class 'bool'>), default=False, label='Clim percentile')

Percentile value to compute colorscale robust to outliers. If True, uses 2nd and 98th percentile; otherwise uses the specified numerical percentile value.

colorbar = Boolean(default=False, label='Colorbar')

Whether to display a colorbar.

color_levels = ClassSelector(allow_None=True, class_=(<class 'int'>, <class 'list'>), label='Color levels')

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

colorbar_opts = Dict(class_=<class 'dict'>, default={}, label='Colorbar opts')

Allows setting including borderwidth, showexponent, nticks, outlinecolor, thickness, bgcolor, outlinewidth, bordercolor, ticklen, xpad, ypad, tickangle…

symmetric = Boolean(default=False, label='Symmetric')

Whether to make the colormap symmetric around zero.

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.element.ElementPlot(element, plot=None, **params)

Bases: PlotlyPlot, GenericElementPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

bgcolor = ClassSelector(allow_None=True, class_=(<class 'str'>, <class 'tuple'>), label='Bgcolor')

If set bgcolor overrides the background color of the axis.

invert_axes = Selector(default=False, label='Invert axes', names={}, objects=[False])

Inverts the axes of the plot. Note that this parameter may not always be respected by all plots but should be respected by adjoined plots when appropriate.

invert_xaxis = Boolean(default=False, label='Invert xaxis')

Whether to invert the plot x-axis.

invert_yaxis = Boolean(default=False, label='Invert yaxis')

Whether to invert the plot y-axis.

logx = Boolean(default=False, label='Logx')

Whether to apply log scaling to the x-axis of the Chart.

logy = Boolean(default=False, label='Logy')

Whether to apply log scaling to the y-axis of the Chart.

show_legend = Boolean(default=False, label='Show legend')

Whether to show legend for the plot.

xaxis = Selector(default='bottom', label='Xaxis', names={}, 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 = Selector(default='left', label='Yaxis', names={}, 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’.

xticks = Parameter(allow_None=True, label='Xticks')

Ticks along x-axis specified as an integer, explicit list of tick locations, list of tuples containing the locations.

yticks = Parameter(allow_None=True, label='Yticks')

Ticks along y-axis specified as an integer, explicit list of tick locations, list of tuples containing the locations.

aspect = Parameter(default='cube', label='Aspect')

The aspect ratio mode of the plot. By default, a plot may select its own appropriate aspect ratio but sometimes it may be necessary to force a square aspect ratio (e.g. to display the plot as an element of a grid). The modes ‘auto’ and ‘equal’ correspond to the axis modes of the same name in matplotlib, a numeric value may also be passed.

invert_zaxis = Boolean(default=False, label='Invert zaxis')

Whether to invert the plot z-axis.

labelled = List(bounds=(0, None), default=['x', 'y', 'z'], label='Labelled')

Whether to label the ‘x’ and ‘y’ axes.

logz = Boolean(default=False, label='Logz')

Whether to apply log scaling to the y-axis of the Chart.

margins = NumericTuple(default=(50, 50, 50, 50), label='Margins', length=4)

Margins in pixel values specified as a tuple of the form (left, bottom, right, top).

responsive = Boolean(default=False, label='Responsive')

Whether the plot should stretch to fill the available space.

zlabel = String(allow_None=True, label='Zlabel')

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

zticks = Parameter(allow_None=True, label='Zticks')

Ticks along z-axis specified as an integer, explicit list of tick locations, list of tuples containing the locations.

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.element.OverlayPlot(overlay, ranges=None, batched=True, keys=None, group_counter=None, **params)

Bases: GenericOverlayPlot, ElementPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plot.GenericOverlayPlot: show_legend, batched, legend_limit, style_grouping

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(overlay, ranges, range_type='combined', dimension=None, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Set the plot(s) to the given frame number. Operates by manipulating the matplotlib objects held in the self._handles dictionary.

If n is greater than the number of available frames, update using the last available frame.

---

images Module

class holoviews.plotting.plotly.images.RGBPlot(element, plot=None, **params)

Bases: ElementPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, is_geo=False, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

---

plot Module

class holoviews.plotting.plotly.plot.AdjointLayoutPlot(layout, layout_type, subplots, **params)

Bases: PlotlyPlot, GenericAdjointLayoutPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

cleanup()

Cleans up references to the plot on the attached 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.

initialize_plot(ranges=None, is_geo=False)

Plot all the views contained in the AdjointLayout Object using axes appropriate to the layout configuration. All the axes are supplied by LayoutPlot - the purpose of the call is to invoke subplots with correct options and styles and hide any empty axes as necessary.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

set_root(root)

Sets the root model on all subplots.

property state

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

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.

class holoviews.plotting.plotly.plot.GridPlot(layout, ranges=None, layout_num=1, **params)

Bases: PlotlyPlot, GenericCompositePlot

Plot a group of elements in a grid layout based on a GridSpace element object.

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

hspacing = Number(bounds=(0, None), default=15, inclusive_bounds=(True, True), label='Hspacing')

vspacing = Number(bounds=(0, None), default=15, inclusive_bounds=(True, True), label='Vspacing')

shared_axes = Boolean(default=True, label='Shared axes')

Whether axes ranges should be shared across the layout, if disabled switches axiswise normalization option on globally.

cleanup()

Cleans up references to the plot on the attached 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.

initialize_plot(ranges=None, is_geo=False)

Initialize the matplotlib figure.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

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.

class holoviews.plotting.plotly.plot.LayoutPlot(layout, **params)

Bases: PlotlyPlot, GenericLayoutPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericLayoutPlot: transpose

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

hspacing = Number(bounds=(0, None), default=120, inclusive_bounds=(True, True), label='Hspacing')

vspacing = Number(bounds=(0, None), default=100, inclusive_bounds=(True, True), label='Vspacing')

adjoint_spacing = Number(bounds=(0, None), default=20, inclusive_bounds=(True, True), label='Adjoint spacing')

shared_axes = Boolean(default=True, label='Shared axes')

Whether axes ranges should be shared across the layout, if disabled switches axiswise normalization option on globally.

cleanup()

Cleans up references to the plot on the attached 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.

initialize_plot(ranges=None, is_geo=False)

Initialize the matplotlib figure.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

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.

class holoviews.plotting.plotly.plot.PlotlyPlot(keys=None, dimensions=None, layout_dimensions=None, uniform=True, subplot=False, adjoined=None, layout_num=0, style=None, subplots=None, dynamic=False, **params)

Bases: DimensionedPlot, CallbackPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

width = Integer(default=400, inclusive_bounds=(True, True), label='Width')

height = Integer(default=400, inclusive_bounds=(True, True), label='Height')

cleanup()

Cleans up references to the plot on the attached 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.

initialize_plot(ranges=None, is_geo=False)

Initialize the matplotlib figure.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

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.

---

raster Module

class holoviews.plotting.plotly.raster.HeatMapPlot(element, plot=None, **params)

Bases: HeatMapMixin, RasterPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

holoviews.plotting.plotly.raster.RasterPlot: padding, nodata

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.raster.QuadMeshPlot(element, plot=None, **params)

Bases: RasterPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

holoviews.plotting.plotly.raster.RasterPlot: padding

nodata = Integer(allow_None=True, inclusive_bounds=(True, True), label='Nodata')

Optional missing-data value for integer data. If non-None, data with this value will be replaced with NaN so that it is transparent (by default) when plotted.

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.raster.RasterPlot(element, plot=None, **params)

Bases: ColorbarPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

padding = ClassSelector(class_=(<class 'int'>, <class 'float'>, <class 'tuple'>), default=0, label='Padding')

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

nodata = Integer(allow_None=True, inclusive_bounds=(True, True), label='Nodata')

Optional missing-data value for integer data. If non-None, data with this value will be replaced with NaN so that it is transparent (by default) when plotted.

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

---

renderer Module

class holoviews.plotting.plotly.renderer.PlotlyRenderer(*, backend, center, css, dpi, fig, fps, holomap, mode, post_render_hooks, size, widget_location, widget_mode, info_fn, key_fn, name)

Bases: Renderer

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.renderer.Renderer: key_fn, info_fn, center, dpi, fps, mode, size, widget_location, widget_mode, css, post_render_hooks

backend = String(default='plotly', label='Backend')

The backend name.

fig = Selector(default='auto', label='Fig', names={}, objects=['html', 'png', 'svg', 'auto'])

Output render format for static figures. If None, no figure rendering will occur.

holomap = Selector(default='auto', label='Holomap', names={}, objects=['scrubber', 'widgets', 'gif', None, 'auto'])

Output render multi-frame (typically animated) format. If None, no multi-frame rendering will occur.

classmethod app(plot, show=False, new_window=False, websocket_origin=None, port=0)

Creates a bokeh app from a HoloViews object or plot. By default simply attaches the plot to bokeh’s curdoc and returns the Document, if show option is supplied creates an Application instance and displays it either in a browser window or inline if notebook extension has been loaded. Using the new_window option the app may be displayed in a new browser tab once the notebook extension has been loaded. A websocket origin is required when launching from an existing tornado server (such as the notebook) and it is not on the default port (‘localhost:8888’).

comm_manager

alias of CommManager

components(obj, fmt=None, comm=True, **kwargs)

Returns data and metadata dictionaries containing HTML and JS components to include render in app, notebook, or standalone document.

classmethod encode(entry)

Classmethod that applies conditional encoding based on mime-type. Given an entry as returned by __call__ return the data in the appropriate encoding.

classmethod export_widgets(obj, filename, fmt=None, template=None, json=False, json_path='', **kwargs)

Render and export object as a widget to a static HTML file. Allows supplying a custom template formatting string with fields to interpolate ‘js’, ‘css’ and the main ‘html’ containing the widget. Also provides options to export widget data to a json file in the supplied json_path (defaults to current path).

classmethod get_plot(obj, doc=None, renderer=None, comm=None, **kwargs)

Given a HoloViews Viewable return a corresponding plot instance.

get_plot_state(obj, doc=None, renderer=None, numpy_convert=False, **kwargs)

Given a HoloViews Viewable return a corresponding figure dictionary. Allows cleaning the dictionary of any internal properties that were added

classmethod get_size(plot)

Return the display size associated with a plot before rendering to any particular format. Used to generate appropriate HTML display.

Returns a tuple of (width, height) in pixels.

html(obj, fmt=None, css=None, resources='CDN', **kwargs)

Renders plot or data structure and wraps the output in HTML. The comm argument defines whether the HTML output includes code to initialize a Comm, if the plot supplies one.

classmethod instance(**params)

Return an instance of this class, copying parameters from any existing instance provided.

classmethod load_nb(inline=True)

Loads the plotly notebook resources.

classmethod plot_options(obj, percent_size)

Given an object and a percentage size (as supplied by the %output magic) return all the appropriate plot options that would be used to instantiate a plot class for that element.

Default plot sizes at the plotting class level should be taken into account.

classmethod plotting_class(obj)

Given an object or Element class, return the suitable plotting class needed to render it with the current renderer.

classmethod save(obj, basename, fmt='auto', key=None, info=None, options=None, resources='inline', title=None, **kwargs)

Save a HoloViews object to file, either using an explicitly supplied format or to the appropriate default.

classmethod server_doc(obj, doc=None)

Get a bokeh Document with the plot attached. May supply an existing doc, otherwise bokeh.io.curdoc() is used to attach the plot to the global document instance.

classmethod state()

Context manager to handle global state for a backend, allowing Plot classes to temporarily override that state.

static_html(obj, fmt=None, template=None)

Generates a static HTML with the rendered object in the supplied format. Allows supplying a template formatting string with fields to interpolate ‘js’, ‘css’ and the main ‘html’.

classmethod validate(options)

Validate an options dictionary for the renderer.

---

selection Module

class holoviews.plotting.plotly.selection.PlotlyOverlaySelectionDisplay(color_prop='color', is_cmap=False, supports_region=True)

Bases: OverlaySelectionDisplay

Overlay selection display subclass for use with plotly backend

---

shapes Module

class holoviews.plotting.plotly.shapes.BoxShapePlot(element, plot=None, **params)

Bases: GeomMixin, ShapePlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)

Use first two key dimensions to set names, and all four to set the data range.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, is_geo=False, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.shapes.HVLinePlot(element, plot=None, **params)

Bases: ShapePlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

apply_ranges = Boolean(default=False, label='Apply ranges')

Whether to include the annotation in axis range calculations.

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, is_geo=False, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.shapes.HVSpanPlot(element, plot=None, **params)

Bases: ShapePlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

apply_ranges = Boolean(default=False, label='Apply ranges')

Whether to include the annotation in axis range calculations.

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, is_geo=False, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.shapes.PathShapePlot(element, plot=None, **params)

Bases: ShapePlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, is_geo=False, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.shapes.PathsPlot(element, plot=None, **params)

Bases: ShapePlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, is_geo=False, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.shapes.SegmentShapePlot(element, plot=None, **params)

Bases: GeomMixin, ShapePlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)

Use first two key dimensions to set names, and all four to set the data range.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, is_geo=False, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.shapes.ShapePlot(element, plot=None, **params)

Bases: ElementPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, is_geo=False, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

---

stats Module

class holoviews.plotting.plotly.stats.BivariatePlot(element, plot=None, **params)

Bases: ChartPlot, ColorbarPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

holoviews.plotting.plotly.element.ColorbarPlot: clim, clim_percentile, colorbar, color_levels, colorbar_opts, symmetric

filled = Boolean(default=False, label='Filled')

ncontours = Integer(allow_None=True, inclusive_bounds=(True, True), label='Ncontours')

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.stats.BoxWhiskerPlot(element, plot=None, **params)

Bases: MultiDistributionPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

boxpoints = Selector(default='outliers', label='Boxpoints', names={}, objects=['all', 'outliers', 'suspectedoutliers', False])

Which points to show, valid options are ‘all’, ‘outliers’, ‘suspectedoutliers’ and False

jitter = Number(default=0, inclusive_bounds=(True, True), label='Jitter')

Sets the amount of jitter in the sample points drawn. If “0”, the sample points align along the distribution axis. If “1”, the sample points are drawn in a random jitter of width equal to the width of the box(es).

mean = Selector(default=False, label='Mean', names={}, objects=[True, False, 'sd'])

If “True”, the mean of the box(es)’ underlying distribution is drawn as a dashed line inside the box(es). If “sd” the standard deviation is also drawn.

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.stats.DistributionPlot(element, plot=None, **params)

Bases: ElementPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

bandwidth = Number(allow_None=True, inclusive_bounds=(True, True), label='Bandwidth')

The bandwidth of the kernel for the density estimate.

cut = Number(default=3, inclusive_bounds=(True, True), label='Cut')

Draw the estimate to cut * bw from the extreme data points.

filled = Boolean(default=True, label='Filled')

Whether the bivariate contours should be filled.

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.stats.MultiDistributionPlot(element, plot=None, **params)

Bases: MultiDistributionMixin, ElementPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

class holoviews.plotting.plotly.stats.ViolinPlot(element, plot=None, **params)

Bases: MultiDistributionPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

box = Boolean(default=True, label='Box')

Whether to draw a boxplot inside the violin

meanline = Boolean(default=False, label='Meanline')

If “True”, the mean of the box(es)’ underlying distribution is drawn as a dashed line inside the box(es). If “sd” the standard deviation is also drawn.

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

---

tabular Module

class holoviews.plotting.plotly.tabular.TablePlot(element, plot=None, **params)

Bases: ElementPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

width = Number(default=400, inclusive_bounds=(True, True), label='Width')

height = Number(default=400, inclusive_bounds=(True, True), label='Height')

cleanup()

Cleans up references to the plot on the attached 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.

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', dimension=None, xdim=None, ydim=None, zdim=None, lims_as_soft_ranges=False, **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

---

tiles Module

class holoviews.plotting.plotly.tiles.TilePlot(element, plot=None, **params)

Bases: ElementPlot

Parameter Definitions

---

Parameters inherited from:

holoviews.plotting.plot.DimensionedPlot: fontsize, fontscale, show_title, title, normalize, projection

holoviews.plotting.plot.GenericElementPlot: apply_ranges, apply_extents, default_span, hooks, padding, show_grid, xlabel, ylabel, xlim, ylim, zlim, xrotation, yrotation

holoviews.plotting.plotly.plot.PlotlyPlot: width, height

holoviews.plotting.plotly.element.ElementPlot: bgcolor, invert_axes, invert_xaxis, invert_yaxis, logx, logy, show_legend, xaxis, yaxis, xticks, yticks, aspect, invert_zaxis, labelled, logz, margins, responsive, zlabel, zticks

cleanup()

Cleans up references to the plot on the attached 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.

generate_plot(key, ranges, element=None, is_geo=False)

Override to force is_geo to True

get_aspect(xspan, yspan)

Computes the aspect ratio of the plot

get_extents(element, ranges, range_type='combined', **kwargs)

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.

If lims_as_soft_ranges is set to True, the xlim and ylim will be treated as soft ranges instead of the default case as hard ranges while computing the extents. This is used e.g. when apply_hard_bounds is True and xlim/ylim is set, in which case we limit the initial viewable range to xlim/ylim, but allow navigation up to the abs max between the data range and xlim/ylim.

get_padding(obj, extents)

Computes padding along the axes taking into account the plot aspect.

get_zorder(overlay, key, el)

Computes the z-order of element in the NdOverlay taking into account possible batching of elements.

init_graph(datum, options, index=0, **kwargs)

Initialize the plotly components that will represent the element

Parameters

datum: dict

An element of the data list returned by the get_data method

options: dict

Graph options that were returned by the graph_options method

index: int

Index of datum in the original list returned by the get_data method

Returns

dict

Dictionary of the plotly components that represent the element. Keys may include:

• ‘traces’: List of trace dicts

• ‘annotations’: List of annotations dicts

• ‘images’: List of image dicts

• ‘shapes’: List of shape dicts

initialize_plot(ranges=None, is_geo=False)

Initializes a new plot object with the last available frame.

property link_sources

Returns potential Link or Stream sources.

matches(spec)

Matches a specification against the current Plot.

push()

Pushes plot updates to the frontend.

refresh(**kwargs)

Refreshes the plot by rerendering it and then pushing the updated data if the plot has an associated Comm.

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.

traverse(fn=None, specs=None, full_breadth=True)

Traverses any nested DimensionedPlot returning a list of all plots that match the specs. The specs should be supplied as a list of either Plot types or callables, which should return a boolean given the plot class.

update(key)

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

update_frame(key, ranges=None, element=None, is_geo=False)

Updates an existing plot with data corresponding to the key.

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util Module

holoviews.plotting.plotly.util.clean_internal_figure_properties(fig)

Remove all HoloViews internal properties (those with leading underscores) from the input figure.

Note: This function mutates the input figure

Parameters

fig: dict

The figure dictionary to process.

holoviews.plotting.plotly.util.configure_matching_axes_from_dims(fig, matching_prop='_dim')

Configure matching axes for a figure

Note: This function mutates the input figure

Parameters

fig: dict

The figure dictionary to process.

matching_prop: str

The name of the axis property that should be used to determine that two axes should be matched together. If the property is missing or None, axes will not be matched

holoviews.plotting.plotly.util.figure_grid(figures_grid, row_spacing=50, column_spacing=50, share_xaxis=False, share_yaxis=False, width=None, height=None)

Construct a figure from a 2D grid of sub-figures

Parameters

figures_grid: list of list of (dict or None)

2D list of plotly figure dicts that will be combined in a grid to produce the resulting figure. None values maybe used to leave empty grid cells

row_spacing: float (default 50)

Vertical spacing between rows in the grid in pixels

column_spacing: float (default 50)

Horizontal spacing between columns in the grid in pixels coordinates

share_xaxis: bool (default False)

Share x-axis between sub-figures in the same column. Also link all x-axes in the figure. This will only work if each sub-figure has a single x-axis

share_yaxis: bool (default False)

Share y-axis between sub-figures in the same row. Also link all y-axes in the figure. This will only work if each subfigure has a single y-axis

width: int (default None)

Final figure width. If not specified, width is the sum of the max width of the figures in each column

height: int (default None)

Final figure width. If not specified, height is the sum of the max height of the figures in each row

Returns

dict

A plotly figure dict

holoviews.plotting.plotly.util.get_colorscale(cmap, levels=None, cmin=None, cmax=None)

Converts a cmap spec to a plotly colorscale

Args:

cmap: A recognized colormap by name or list of colors levels: A list or integer declaring the color-levels cmin: The lower bound of the color range cmax: The upper bound of the color range

Returns:

A valid plotly colorscale

holoviews.plotting.plotly.util.merge_figure(fig, subfig)

Merge a sub-figure into a parent figure

Note: This function mutates the input fig dict, but it does not mutate the subfig dict

Parameters

fig: dict

The plotly figure dict into which the sub figure will be merged

subfig: dict

The plotly figure dict that will be copied and then merged into fig

holoviews.plotting.plotly.util.merge_layout(obj, subobj)

Merge layout objects recursively

Note: This function mutates the input obj dict, but it does not mutate the subobj dict

Parameters

obj: dict

dict into which the sub-figure dict will be merged

subobj: dict

dict that sill be copied and merged into obj

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