Configuring plot tools

Bokeh comes with a number of interactive tools that you can use to report information, to change plot parameters such as zoom level or range extents, or to add, edit, or delete glyphs. Tools can be grouped into four basic categories:

Gestures

These tools respond to single gestures, such as a pan movement. The types of gesture tools are:

For each type of gesture, only one tool can be active at any given time. The active tool is highlighted on the toolbar next to the tool icon.

Actions

These are immediate or modal operations that are only activated when their button in the toolbar is pressed, such as the ResetTool.

Inspectors

These are passive tools that report information or annotate plots in some way, such as the HoverTool or CrosshairTool.

Edit tools

These are sophisticated multi-gesture tools that can add, delete, or modify glyphs on a plot. Since they may respond to several gestures at once, an edit tool when activated will potentially deactivate multiple single-gesture tools.

This chapter contains information about all the individual tools and describes how the toolbar may be configured.

Positioning the toolbar

By default, Bokeh plots come with a toolbar above the plot. You can change the location of the toolbar or remove it.

You can specify the toolbar location by passing the toolbar_location parameter to the figure() function. Valid values are:

  • "above"

  • "below"

  • "left"

  • "right"

If you would like to hide the toolbar entirely, pass None.

The code below positions the toolbar below the plot. Try running the code and changing the toolbar_location value.

from bokeh.plotting import figure, output_file, show

output_file("toolbar.html")

# create a new plot with the toolbar below
p = figure(width=400, height=400,
           title=None, toolbar_location="below")

p.circle([1, 2, 3, 4, 5], [2, 5, 8, 2, 7], size=10)

show(p)

Note that the toolbar position clashes with the default axes. In this case, setting the toolbar_sticky option to False will move the toolbar outside of the area where the axis is drawn.

from bokeh.plotting import figure, output_file, show

output_file("toolbar.html")

# create a new plot with the toolbar below
p = figure(width=400, height=400,
           title=None, toolbar_location="below",
           toolbar_sticky=False)

p.circle([1, 2, 3, 4, 5], [2, 5, 8, 2, 7], size=10)

show(p)

Specifying tools

At the lowest bokeh.models level, you can add tools to a Plot by passing instances of Tool objects to the add_tools() method:

plot = Plot()
plot.add_tools(LassoSelectTool())
plot.add_tools(WheelZoomTool())

This way of adding tools works with any Bokeh Plot or Plot subclass, such as Figure.

You can specify tools by passing the tools parameter to the figure() function. The tools parameter accepts a list of tool objects, for example:

tools = [BoxZoomTool(), ResetTool()]

You can also add multiple tools with a comma-separated string containing tool shortcut names:

tools = "pan,wheel_zoom,box_zoom,reset"

This method does not allow setting properties of the tools.

Finally, you can add new tools to a plot by passing a tool object to the add_tools() method of a plot. You can combine the add_tools() method with the figure() function’s tools argument:

from bokeh.models import BoxSelectTool

plot = figure(tools="pan,wheel_zoom,box_zoom,reset")
plot.add_tools(BoxSelectTool(dimensions="width"))

Setting the active tools

Bokeh toolbars can have at most one active tool from each kind of gesture (drag, scroll, tap).

However, it is possible to exert control over which tool is active. At the lowest bokeh.models level, you can do this by using the active_drag, active_inspect, active_scroll, and active_tap properties of Toolbar. These properties can take the following values:

  • None — there is no active tool of this kind

  • "auto" — Bokeh chooses a tool of this kind to be active (possibly none)

  • a Tool instance — Bokeh sets the given tool to be the active tool

Additionally, the active_inspect tool may accept: * A sequence of Tool instances to be set as the active tools

As an example:

# configure so that no drag tools are active
plot.toolbar.active_drag = None

# configure so that Bokeh chooses what (if any) scroll tool is active
plot.toolbar.active_scroll = "auto"

# configure so that a specific PolySelect tap tool is active
plot.toolbar.active_tap = poly_select

# configure so that a sequence of specific inspect tools are active
# note: this only works for inspect tools
plot.toolbar.active_inspect = [hover_tool, crosshair_tool]

The default value for all of these properties is "auto".

You can specify active tools by passing these properties as keyword arguments to the figure() function. It is also possible to pass any one of the string names:

# configures the lasso tool to be active
plot = figure(tools="pan,lasso_select,box_select", active_drag="lasso_select")

Pan/Drag tools

You can use these tools by panning (on touch devices) or left-dragging (on mouse devices). Only one pan/drag tool may be active at a time. Where applicable, Pan/Drag tools will respect any max and min values set on ranges.

BoxSelectTool

  • name: 'box_select'

  • icon: box_select_icon

The box selection tool allows you to define a rectangular selection by left-dragging a mouse, or dragging a finger across the plot area. You can configure the box select tool to select across only one dimension by setting the dimensions property to width or height instead of the default both.

After a selection is made, the indices of the selected points are available from properties on the Selection object for a glyph data source. For example:

source.selected.indices

will hold the selected indices in the common case of a “scatter” type glyph.

Note

To make multiple selections, press the SHIFT key. To clear the selection, press the ESC key.

BoxZoomTool

  • name: 'box_zoom'

  • icon: box_zoom_icon

The box zoom tool allows you to define a rectangular region to zoom the plot bounds to by left-dragging a mouse, or dragging a finger across the plot area.

LassoSelectTool

  • name: 'lasso_select'

  • icon: lasso_select_icon

The lasso selection tool allows you to define an arbitrary region for selection by left-dragging a mouse, or dragging a finger across the plot area.

After a selection is made, the indices of the selected points are available from properties on the Selection object for a glyph data source. For example:

source.selected.indices

will hold the selected indices in the common case of a “scatter” type glyph.

Note

To make a multiple selection, press the SHIFT key. To clear the selection, press the ESC key.

PanTool

  • name: 'pan', 'xpan', 'ypan',

  • icon: pan_icon

The pan tool allows you to pan the plot by left-dragging a mouse or dragging a finger across the plot region.

You can configure the pan tool to act only on either the x-axis or the y-axis by setting the dimensions property to a list containing width or height. Additionally, there are tool names 'xpan' and 'ypan', respectively.

Click/Tap tools

Use these tools by tapping (on touch devices) or left-clicking (on mouse devices). Only one click/tap tool may be active at a time.

PolySelectTool

  • name: 'poly_select'

  • icon: poly_select_icon

The polygon selection tool allows you to define an arbitrary polygonal region for selection by left-clicking a mouse, or tapping a finger at different locations.

After a selection is made, the indices of the selected points are available from properties on the Selection object for a glyph data source. For example:

source.selected.indices

will hold the selected indices in the common case of a “scatter” type glyph.

Note

Complete the selection by making a double left-click or tapping. To make a multiple selection, press the SHIFT key. To clear the selection, press the ESC key.

TapTool

  • name: 'tap'

  • icon: tap_icon

The tap selection tool allows you to select single points by clicking the left mouse button, or tapping with a finger.

After a selection is made, the indices of the selected points are available from properties on the Selection object for a glyph data source. For example:

source.selected.indices

will hold the selected indices in the common case of a “scatter” type glyph.

Note

To make a multiple selection, press the SHIFT key. To clear the selection, press the ESC key.

Scroll/Pinch tools

Use these tools by pinching (on touch devices) or scrolling (on mouse devices). Only one scroll/pinch tool may be active at a time.

WheelZoomTool

  • name: 'wheel_zoom', 'xwheel_zoom', 'ywheel_zoom'

  • icon: wheel_zoom_icon

You can use the wheel zoom tool to zoom the plot in and out, centering on the current mouse location. It will respect any min and max values and ranges, preventing zooming in and out beyond these values.

You can configure the wheel zoom tool to act only on either the x-axis or the y-axis by setting the dimensions property to a list containing width or height. Additionally, there are tool names 'xwheel_zoom' and 'ywheel_zoom', respectively.

WheelPanTool

  • name: 'xwheel_pan', 'ywheel_pan'

  • icon: wheel_pan_icon

The wheel pan tool translates the plot window along a specified dimension without changing the window’s aspect ratio. It will respect any min and max values and ranges, preventing panning beyond these values.

Actions

Actions are operations that are activated only when their button in the toolbar is tapped or clicked. They are typically modal or immediate-acting.

UndoTool

  • name: 'undo'

  • icon: undo_icon

The undo tool restores the previous state of the plot.

RedoTool

  • name: 'redo'

  • icon: redo_icon

The redo tool reverses the last action performed by the undo tool.

ResetTool

  • name: 'reset'

  • icon: reset_icon

The reset tool restores the plot ranges to their original values.

SaveTool

  • name: 'save'

  • icon: save_icon

The save tool pops up a modal dialog that allows you to save a PNG image of the plot.

ZoomInTool

  • name: 'zoom_in', 'xzoom_in', 'yzoom_in'

  • icon: zoom_in_icon

The zoom-in tool increases the zoom of the plot. It will respect any min and max values and ranges, preventing zooming in and out beyond these.

You can configure the wheel zoom tool to act only on either the x-axis or the y-axis by setting the dimensions property to a list containing width or height. Additionally, there are tool names 'xzoom_in' and 'yzoom_in', respectively.

ZoomOutTool

  • name: 'zoom_out', 'xzoom_out', 'yzoom_out'

  • icon: zoom_out_icon

The zoom-out tool decreases the zoom level of the plot. It will respect any min and max values and ranges, preventing zooming in and out beyond these values.

You can configure the wheel zoom tool to act only on either the x-axis or the y-axis by setting the dimensions property to a list containing width or height. Additionally, there are tool names 'xzoom_in' and 'yzoom_in', respectively.

Inspectors

Inspectors are passive tools that annotate or report information about the plot based on the current cursor position. Multiple inspectors may be active at any given time. You can toggle the active state of an inspector in the inspectors menu in the toolbar.

CrosshairTool

  • name: 'crosshair'

  • menu icon: crosshair_icon

The crosshair tool draws a crosshair annotation over the plot, centered on the current mouse position. You can configure the crosshair tool dimensions by setting the dimensions property to width, height, or both.

HoverTool

  • name: 'hover'

  • menu icon: hover_icon

The hover tool is a passive inspector tool. It defaults to be on at all times, but you can change this in the inspector’s menu in the toolbar.

Basic Tooltips

By default, the hover tool generates a “tabular” tooltip where each row contains a label and its associated value. The labels and values are supplied as a list of (label, value) tuples. For instance, the tooltip below on the left was created with the accompanying tooltips definition on the right.

hover_basic

hover.tooltips = [
    ("index", "$index"),
    ("(x,y)", "($x, $y)"),
    ("radius", "@radius"),
    ("fill color", "$color[hex, swatch]:fill_color"),
    ("fill color", "$color[hex]:fill_color"),
    ("fill color", "$color:fill_color"),
    ("fill color", "$swatch:fill_color"),
    ("foo", "@foo"),
    ("bar", "@bar"),
]

Field names that begin with $ are “special fields”. These often correspond to values that are part of the plot, such as the coordinates of the mouse in data or screen space. These special fields are listed here:

$index

index of selected point in the data source

$name

value of the name property of the hovered glyph renderer

$x

x-coordinate under the cursor in data space

$y

y-coordinate under the cursor in data space

$sx

x-coordinate under the cursor in screen (canvas) space

$sy

y-coordinate under the cursor in screen (canvas) space

$color

colors from a data source, with the syntax: $color[options]:field_name. The available options are: hex (to display the color as a hex value), swatch (color data from data source displayed as a small color box).

$swatch

color data from data source displayed as a small color box.

Field names that begin with @ are associated with columns in a ColumnDataSource. For instance, the field name "@price" will display values from the "price" column whenever a hover is triggered. If the hover is for the 17th glyph instance, then the hover tooltip will display the 17th price value.

Note that if a column name contains spaces, it must be surrounded by curly braces. For example, configuring @{adjusted close} will display values from a column named "adjusted close".

Sometimes, especially with stacked charts, it is desirable to allow the name of the column to be specified indirectly. In this case, use the field name @$name to look up the name field on the hovered glyph renderer, and use that value as the column name. For instance, if you hover with the name "US East", then @$name is equivalent to @{US East}.

Here is a complete example of how to configure and use the hover tool by setting the tooltips argument to figure:

from bokeh.plotting import ColumnDataSource, figure, output_file, show

output_file("toolbar.html")

source = ColumnDataSource(data=dict(
    x=[1, 2, 3, 4, 5],
    y=[2, 5, 8, 2, 7],
    desc=['A', 'b', 'C', 'd', 'E'],
))

TOOLTIPS = [
    ("index", "$index"),
    ("(x,y)", "($x, $y)"),
    ("desc", "@desc"),
]

p = figure(width=400, height=400, tooltips=TOOLTIPS,
           title="Mouse over the dots")

p.circle('x', 'y', size=20, source=source)

show(p)

Hit-Testing behavior

The hover tool displays tooltips associated with individual glyphs. You can configure these tooltips to activate in different ways with a mode property:

"mouse"

only when the mouse is directly over a glyph

"vline"

whenever a vertical line from the mouse position intersects a glyph

"hline"

whenever a horizontal line from the mouse position intersects a glyph

The default configuration is mode = "mouse". See this in the Basic Tooltips example above. The example below in Formatting tooltip fields demonstrates mode = "vline".

Formatting tooltip fields

By default, values for fields (@foo, for example) are displayed in a basic numeric format. To control the formatting of values, you can modify fields by appending a specified format to the end in curly braces. Some examples are below.

"@foo{0,0.000}"    # formats 10000.1234 as: 10,000.123

"@foo{(.00)}"      # formats -10000.1234 as: (10000.123)

"@foo{($ 0.00 a)}" # formats 1230974 as: $ 1.23 m

The examples above all use the default formatting scheme. There are other formatting schemes you can specify:

"numeral"

Provides a wide variety of formats for numbers, currency, bytes, times, and percentages. The full set of formats can be found in the NumeralTickFormatter reference documentation.

"datetime"

Provides formats for date and time values. The full set of formats is listed in the DatetimeTickFormatter reference documentation.

"printf"

Provides formats similar to C-style “printf” type specifiers. See the PrintfTickFormatter reference documentation for complete details.

You can add these by configuring the formatters property of a hover tool. This property maps tooltip variables to format schemes. For example, to use the "datetime" scheme for formatting a column "@{close date}", set the value:

hover_tool.formatters = { "@{close date}": "datetime"}

You can also supply formatters for “special variables” such as "$x":

hover_tool.formatters = { "$x": "datetime"}

If a formatter is not specified for a column name, the default "numeral" formatter is assumed.

Note that format specifications are also compatible with column names that have spaces. For example, @{adjusted close}{($ 0.00 a)} applies a format to a column named “adjusted close”.

The example code below configures a HoverTool with different formatters for different fields:

HoverTool(
    tooltips=[
        ( 'date',   '@date{%F}'            ),
        ( 'close',  '$@{adj close}{%0.2f}' ), # use @{ } for field names with spaces
        ( 'volume', '@volume{0.00 a}'      ),
    ],

    formatters={
        '@date'        : 'datetime', # use 'datetime' formatter for '@date' field
        '@{adj close}' : 'printf',   # use 'printf' formatter for '@{adj close}' field
                                     # use default 'numeral' formatter for other fields
    },

    # display a tooltip whenever the cursor is vertically in line with a glyph
    mode='vline'
)

You can see the output generated from this configuration by hovering the mouse over the plot below:

The CustomJSHover model allows you to use JavaScript to specify a custom formatter that can display derived quantities in the tooltip.

Image hover

You can use the hover tool to inspect image glyphs which may contain layers of data in the corresponding ColumnDataSource:

import numpy as np

from bokeh.plotting import figure, output_file, show

output_file("tools_hover_tooltip_image.html")

ramp = np.array([np.linspace(0, 10, 200)]*20)
steps = np.array([np.linspace(0, 10, 10)]*20)
bitmask = np.random.rand(25, 10) > 0.5

data = dict(image=[ramp, steps, bitmask],
            squared=[ramp**2, steps**2, bitmask**2],
            pattern=['smooth ramp', 'steps', 'bitmask'],
            x=[0, 0, 25],
            y=[5, 20, 5],
            dw=[20,  20, 10],
            dh=[10,  10, 25])

TOOLTIPS = [
    ('name', "$name"),
    ('index', "$index"),
    ('pattern', '@pattern'),
    ("x", "$x"),
    ("y", "$y"),
    ("value", "@image"),
    ('squared', '@squared')
]

p = figure(x_range=(0, 35), y_range=(0, 35), tools='hover,wheel_zoom', tooltips=TOOLTIPS)
p.image(source=data, image='image', x='x', y='y', dw='dw', dh='dh', palette="Inferno256", name="Image Glyph")

show(p)

In this example, three image patterns are defined, ramp, steps, and bitmask. The hover tooltip shows the index of the image, the name of the pattern, the x and y position of the cursor, as well as the corresponding value and value squared.

Custom tooltip

You can supply a custom HTML template for a tooltip. To do this, pass an HTML string with the Bokeh tooltip field name symbols wherever substitutions are desired. All of the information above regarding formats still applies. Note that you can also use the {safe} format after the column name to disable the escaping of HTML in the data source. See the example below:

from bokeh.plotting import ColumnDataSource, figure, output_file, show

output_file("toolbar.html")

source = ColumnDataSource(data=dict(
    x=[1, 2, 3, 4, 5],
    y=[2, 5, 8, 2, 7],
    desc=['A', 'b', 'C', 'd', 'E'],
    imgs=[
        'https://docs.bokeh.org/static/snake.jpg',
        'https://docs.bokeh.org/static/snake2.png',
        'https://docs.bokeh.org/static/snake3D.png',
        'https://docs.bokeh.org/static/snake4_TheRevenge.png',
        'https://docs.bokeh.org/static/snakebite.jpg'
    ],
    fonts=[
        '<i>italics</i>',
        '<pre>pre</pre>',
        '<b>bold</b>',
        '<small>small</small>',
        '<del>del</del>'
    ]
))

TOOLTIPS = """
    <div>
        <div>
            <img
                src="@imgs" height="42" alt="@imgs" width="42"
                style="float: left; margin: 0px 15px 15px 0px;"
                border="2"
            ></img>
        </div>
        <div>
            <span style="font-size: 17px; font-weight: bold;">@desc</span>
            <span style="font-size: 15px; color: #966;">[$index]</span>
        </div>
        <div>
            <span>@fonts{safe}</span>
        </div>
        <div>
            <span style="font-size: 15px;">Location</span>
            <span style="font-size: 10px; color: #696;">($x, $y)</span>
        </div>
    </div>
"""

p = figure(width=400, height=400, tooltips=TOOLTIPS,
           title="Mouse over the dots")

p.circle('x', 'y', size=20, source=source)

show(p)

Edit tools

The edit tools provide functionality for drawing and editing glyphs client-side by adding, modifying, and deleting ColumnDataSource data.

All the edit tools share a small number of key bindings:

SHIFT

Modifier key to add to selection or start drawing

BACKSPACE

Deletes the selected glyphs

ESC

Clears the selection

Note

On MacBooks and some other keyboards, the BACKSPACE key is labeled “delete”.

BoxEditTool

  • name: 'box_edit'

  • menu icon: box_edit_icon

The BoxEditTool() allows you to draw, drag, and delete Rect glyphs on one or more renderers by editing the underlying ColumnDataSource data. Like other drawing tools, you must pass the renderers to be edited as a list:

r1 = p.rect('x', 'y', 'width', 'height', source=source)
r2 = p.rect('x', 'y', 'width', 'height', source=source2)
tool = BoxEditTool(renderers=[r1, r2])

The tool automatically modifies the columns of the data source corresponding to the x, y, width, and height values of the glyph. Any additional columns in the data source will be padded with the declared empty_value when adding a new point. Any newly added points will be inserted in the ColumnDataSource of the first supplied renderer.

It is often useful to limit the number of elements that can be drawn. For example, when specifying a certain number of regions of interest. Using the num_objects property, you can ensure that once the limit has been reached, the oldest box will be popped off the queue to make space for the newest box being added.

Animation showing box draw, select, and delete actions

The animation above shows the supported tool actions, highlighting mouse actions with a circle around the cursor, and key strokes by showing the pressed keys. The BoxEditTool can Add, Move and Delete boxes on plots:

Add box

Hold shift, then click and drag anywhere on the plot or double tap once to start drawing. Move the mouse and double tap again to finish drawing.

Move box

Click and drag an existing box. The box will be dropped once you let go of the mouse button.

Delete box

Tap a box to select it, then press the BACKSPACE key while the mouse is within the plot area.

To Move or Delete multiple boxes at once:

Move selection

Select box(es) with SHIFT+tap (or another selection tool) then drag anywhere on the plot. Selecting and then dragging on a specific box will move both.

Delete selection

Select box(es) with SHIFT+tap (or another selection tool) then press BACKSPACE while the mouse is within the plot area.

FreehandDrawTool

  • name: 'freehand_draw'

  • menu icon: freehand_draw_icon

The FreehandDrawTool() allows freehand drawing of lines and polygons using the Patches and MultiLine glyphs, by editing the underlying ColumnDataSource data. Like other drawing tools, you must pass the renderers to be edited as a list:

r = p.multi_line('xs', 'ys' source=source)
tool = FreehandDrawTool(renderers=[r])

The tool automatically modifies the columns on the data source corresponding to the xs and ys values of the glyph. Any additional columns in the data source will be padded with the declared empty_value when adding a new point. Any newly added points will be inserted in the ColumnDataSource of the first supplied renderer.

It is also often useful to limit the number of elements that can be drawn. For example, when specifying a specific number of regions of interest. Using the num_objects property, you can ensure that once the limit has been reached, the oldest patch/multi-line will be popped off the queue to make space for the new patch/multi-line being added.

Animation showing freehand drawing and delete actions

The animation above shows the supported tool actions, highlighting mouse actions with a circle around the cursor, and key strokes by showing the pressed keys. The PolyDrawTool can Draw and Delete patches and multi-lines:

Draw patch/multi-line

Click and drag to start drawing and release the mouse button to finish drawing.

Delete patch/multi-line

Tap a line or patch to select it then press the BACKSPACE key while the mouse is within the plot area.

To Delete multiple patches/lines at once:

Delete selection

Select patches/lines with SHIFT+tap (or another selection tool), then press BACKSPACE while the mouse is within the plot area.

PointDrawTool

  • name: 'point_draw'

  • menu icon: point_draw_icon

The PointDrawTool() allows you to add, drag, and delete point-like glyphs (of XYGlyph type) on one or more renderers by editing the underlying ColumnDataSource data. Like other drawing tools, you must pass the renderers to be edited as a list:

c1 = p.circle('x', 'y', 'width', 'height', source=source)
r1 = p.rect('x', 'y', 0.1, 0.1, source=source2)
tool = PointDrawTool(renderers=[c1, r1])

The tool automatically modifies the columns on the data source corresponding to the x and y values of the glyph. Any additional columns in the data source will be padded with the declared empty_value when adding a new point. Any newly added points will be inserted in the ColumnDataSource of the first supplied renderer.

It is also often useful to limit the number of elements that can be drawn. Using the num_objects property, you can ensure that once the limit has been reached, the oldest point will be popped off the queue to make space for the new point being added.

Animation showing point draw, drag, select, and delete actions

The animation above shows the supported tool actions, highlighting mouse actions with a circle around the cursor, and key strokes by showing the pressed keys. The PointDrawTool can Add, Move, and Delete point-like glyphs on plots:

Add point

Tap anywhere on the plot.

Move point

Tap and drag an existing point. The point will be dropped once you let go of the mouse button.

Delete point

Tap a point to select it then press BACKSPACE key while the mouse is within the plot area.

To Move or Delete multiple points at once:

Move selection

Select point(s) with SHIFT+tap (or another selection tool), then drag anywhere on the plot. Selecting and then dragging a specific point will move both.

Delete selection

Select point(s) with SHIFT+tap (or another selection tool), then press BACKSPACE while the mouse is within the plot area.

PolyDrawTool

  • name: 'poly_draw'

  • menu icon: poly_draw_icon

The PolyDrawTool() allows you to draw, select, and delete Patches and MultiLine glyphs on one or more renderers by editing the underlying ColumnDataSource data. Like other drawing tools, you must pass the renderers to be edited as a list.

The tool automatically modifies the columns on the data source corresponding to the xs and ys values of the glyph. Any additional columns in the data source will be padded with the declared empty_value, when adding a new point. Any newly added patch or multi-line will be inserted on the ColumnDataSource of the first supplied renderer.

It is also often useful to limit the number of elements that can be drawn. For example, when specifying a specific number of regions of interest. Using the num_objects property, you can ensure that once the limit has been reached the oldest patch/multi-line will be popped off the queue to make space for the new patch/multi-line being added.

If a vertex_renderer with a point-like glyph is supplied, the PolyDrawTool will use it to display the vertices of the multi-lines/patches on all supplied renderers. This also enables the ability to snap to existing vertices while drawing.

Animation showing polygon draw, select, and delete actions

The animation above shows the supported tool actions, highlighting mouse actions with a circle around the cursor, and key strokes by showing the pressed keys. The PolyDrawTool can Add, Move, and Delete patches and multi-lines:

Add patch/multi-line

Double tap to add the first vertex, then use tap to add each subsequent vertex. To finalize the draw action, double tap to insert the final vertex or press the ESC key.

Move patch/multi-line

Tap and drag an existing patch/multi-line. The point will be dropped once you let go of the mouse button.

Delete patch/multi-line

Tap a patch/multi-line to select it, then press the BACKSPACE key while the mouse is within the plot area.

PolyEditTool

  • name: 'poly_edit'

  • menu icon: poly_edit_icon

The PolyEditTool() allows you to edit the vertices of one or more Patches or MultiLine glyphs. You can define the glyphs to be edited with the renderers property. You can define the renderer for the vertices with the vertex_renderer. It must render a point-like Glyph (of XYGlyph type).

The tool automatically modifies the columns on the data source corresponding to the xs and ys values of the glyph. Any additional columns in the data source will be padded with the declared empty_value, when adding a new point.

Animation showing polygon and vertex drag, select, and delete actions

The animation above shows the supported tool actions, highlighting mouse actions with a circle around the cursor, and key strokes by showing the pressed keys. The PolyEditTool can Add, Move, and Delete vertices on existing patches and multi-lines:

Show vertices

Double tap an existing patch or multi-line.

Add vertex

Double tap an existing vertex to select it. The tool will draw the next point. To add it, tap in a new location. To finish editing and add a point, double tap. Otherwise press the ESC key to cancel.

Move vertex

Drag an existing vertex and let go of the mouse button to release it.

Delete vertex

After selecting one or more vertices, press BACKSPACE while the mouse cursor is within the plot area.

Controlling level of detail

Although the HTML canvas can comfortably display tens or even hundreds of thousands of glyphs, doing so can have adverse effects on interactive performance. In order to accommodate large data sizes, Bokeh plots offer “Level of Detail” (LOD) capability in the client.

Note

Another option when dealing with very large data volumes is to use the Bokeh Server to perform downsampling on data before it is sent to the browser. Such an approach is unavoidable past a certain data size. See Running a Bokeh server for more information.

To maintain performance while handling large data sizes, the plot only draws a small fraction of data points during interactive operations (panning or zooming, for example). There are four properties on Plot objects that control LOD behavior:

lod_factor = 10
Type

Int

Decimation factor to use when applying level-of-detail decimation.

lod_interval = 300
Type

Int

Interval (in ms) during which an interactive tool event will enable level-of-detail downsampling.

lod_threshold = 2000
Type

Nullable(Int)

A number of data points, above which level-of-detail downsampling may be performed by glyph renderers. Set to None to disable any level-of-detail downsampling.

lod_timeout = 500
Type

Int

Timeout (in ms) for checking whether interactive tool events are still occurring. Once level-of-detail mode is enabled, a check is made every lod_timeout ms. If no interactive tool events have happened, level-of-detail mode is disabled.