Scatter#

class Scatter(*args: Any, id: ID | None = None, **kwargs: Any)[source]#

Bases: Marker

Render scatter markers selected from a predefined list of designs.

Use Scatter to draw any of Bokeh’s built-in marker types: asterisk, circle, circle_cross, circle_dot, circle_x, circle_y, cross, dash, diamond, diamond_cross, diamond_dot, dot, hex, hex_dot, inverted_triangle, plus, square, square_cross, square_dot, square_pin, square_x, star, star_dot, triangle, triangle_dot, triangle_pin, x, or y. This collection is available in MarkerType.

Bokeh’s built-in markers consist of a set of base markers, most of which can be combined with different kinds of additional visual features:

You can select marker types in two ways:

To draw the same marker for all values, use the marker attribute to specify the name of a specific marker. For example:
```
glyph = Scatter(x="x", y="y", size="sizes", marker="square")
plot.add_glyph(source, glyph)
```
This will render square markers for all points.

Alternatively, to use marker types specified in a data source column, assign the column name to the marker attribute. For example:

# source.data['markers'] = ["circle", "square", "circle", ... ]

glyph = Scatter(x="x", y="y", size="sizes", marker="markers")
plot.add_glyph(source, glyph)

Note

When you draw circle markers with Scatter, you can only assign a size in screen units (by passing a number of pixels to the size property). In case you want to define the radius of circles in data units, use the Circle glyph instead of the Scatter glyph.

Note

Scatter markers with multiple marker types may be drawn in a different order when using the WebGL output backend. This is an explicit trade-off made in the interests of performance.

Example

import numpy as np

from bokeh.core.enums import MarkerType
from bokeh.io import curdoc, show
from bokeh.models import ColumnDataSource, Grid, LinearAxis, Plot, Scatter

N = len(MarkerType)
x = np.linspace(-2, 2, N)
y = x**2
markers = list(MarkerType)

source = ColumnDataSource(dict(x=x, y=y, markers=markers))

plot = Plot(
    title=None, width=300, height=300,
    min_border=0, toolbar_location=None)

glyph = Scatter(x="x", y="y", size=20, fill_color="#74add1", marker="markers")
plot.add_glyph(source, glyph)

xaxis = LinearAxis()
plot.add_layout(xaxis, 'below')

yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')

plot.add_layout(Grid(dimension=0, ticker=xaxis.ticker))
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))

curdoc().add_root(plot)

show(plot)

angle = 0.0#

Type:: AngleSpec

The angles to rotate the markers.

angle_units = 'rad'#

Type:: NotSerialized(Enum(AngleUnits))

Units to use for the associated property: deg, rad, grad or turn

decorations = []#

Type:: List

A collection of glyph decorations, e.g. arrow heads.

Use GlyphRenderer.add_decoration() for easy setup for all glyphs of a glyph renderer. Use this property when finer control is needed.

Note

Decorations are only for aiding visual appearance of a glyph, but they don’t participate in hit testing, etc.

fill_alpha = 1.0#

Type:: AlphaSpec

The fill alpha values for the markers.

fill_color = 'gray'#

Type:: ColorSpec

The fill color values for the markers.

hatch_alpha = 1.0#

Type:: AlphaSpec

The hatch alpha values for the markers.

hatch_color = 'black'#

Type:: ColorSpec

The hatch color values for the markers.

hatch_extra = {}#

Type:: Dict(String, Instance(Texture))

The hatch extra values for the markers.

hatch_pattern = None#

Type:: HatchPatternSpec

The hatch pattern values for the markers.

hatch_scale = 12.0#

Type:: NumberSpec

The hatch scale values for the markers.

hatch_weight = 1.0#

Type:: NumberSpec

The hatch weight values for the markers.

hit_dilation = 1.0#

Type:: Size

The factor by which to dilate the hit radius which is responsible for defining the range in which a marker responds to interactions with the Hover and Tap tools.

line_alpha = 1.0#

Type:: AlphaSpec

The line alpha values for the markers.

line_cap = 'butt'#

Type:: LineCapSpec

The line cap values for the markers.

line_color = 'black'#

Type:: ColorSpec

The line color values for the markers.

line_dash = []#

Type:: DashPatternSpec

The line dash values for the markers.

line_dash_offset = 0#

Type:: IntSpec

The line dash offset values for the markers.

line_join = 'bevel'#

Type:: LineJoinSpec

The line join values for the markers.

line_width = 1#

Type:: NumberSpec

The line width values for the markers.

marker = 'circle'#

Type:: MarkerSpec

Which marker to render. This can be the name of any built in marker, e.g. “circle”, or a reference to a data column containing such names.

name = None#

Type:: Nullable(String)

An arbitrary, user-supplied name for this model.

This name can be useful when querying the document to retrieve specific Bokeh models.

>>> plot.circle([1,2,3], [4,5,6], name="temp")
>>> plot.select(name="temp")
[GlyphRenderer(id='399d53f5-73e9-44d9-9527-544b761c7705', ...)]

Note

No uniqueness guarantees or other conditions are enforced on any names that are provided, nor is the name used directly by Bokeh for any reason.

size = 4#

Type:: SizeSpec

The size (diameter) values for the markers in screen space units.

syncable = True#

Type:: Bool

Indicates whether this model should be synchronized back to a Bokeh server when updated in a web browser. Setting to False may be useful to reduce network traffic when dealing with frequently updated objects whose updated values we don’t need.

Note

Setting this property to False will prevent any on_change() callbacks on this object from triggering. However, any JS-side callbacks will still work.

tags = []#

Type:: List

An optional list of arbitrary, user-supplied values to attach to this model.

This data can be useful when querying the document to retrieve specific Bokeh models:

>>> r = plot.circle([1,2,3], [4,5,6])
>>> r.tags = ["foo", 10]
>>> plot.select(tags=['foo', 10])
[GlyphRenderer(id='1de4c3df-a83d-480a-899b-fb263d3d5dd9', ...)]

Or simply a convenient way to attach any necessary metadata to a model that can be accessed by CustomJS callbacks, etc.

Note

No uniqueness guarantees or other conditions are enforced on any tags that are provided, nor are the tags used directly by Bokeh for any reason.

x = Field(field='x', transform=Unspecified, units=Unspecified)#

Type:: NumberSpec

The x-axis coordinates for the center of the markers.

y = Field(field='y', transform=Unspecified, units=Unspecified)#

Type:: NumberSpec

The y-axis coordinates for the center of the markers.

apply_theme(property_values: dict[str, Any]) → None#

Apply a set of theme values which will be used rather than defaults, but will not override application-set values.

The passed-in dictionary may be kept around as-is and shared with other instances to save memory (so neither the caller nor the HasProps instance should modify it).

Parameters:: property_values (dict) – theme values to use in place of defaults
Returns:: None

clone(**overrides: Any) → Self#

Duplicate a HasProps object.

This creates a shallow clone of the original model, i.e. any mutable containers or child models will not be duplicated. Allows to override particular properties while cloning.

classmethod dataspecs() → dict[str, DataSpec]#

Collect the names of all DataSpec properties on this class.

This method always traverses the class hierarchy and includes properties defined on any parent classes.

Returns:: names of DataSpec properties
Return type:: set[str]

classmethod descriptors() → list[PropertyDescriptor[Any]]#: List of property descriptors in the order of definition.

destroy() → None#: Clean up references to the document and property

equals(other: HasProps) → bool#

Structural equality of models.

Parameters:: other (HasProps) – the other instance to compare to
Returns:: True, if properties are structurally equal, otherwise False

js_link(attr: str, other: Model, other_attr: str, attr_selector: int | str | None = None) → None#

Link two Bokeh model properties using JavaScript.

This is a convenience method that simplifies adding a CustomJS callback to update one Bokeh model property whenever another changes value.

Parameters:

attr (str) – The name of a Bokeh property on this model
other (Model) – A Bokeh model to link to self.attr
other_attr (str) – The property on other to link together
attr_selector (int | str) – The index to link an item in a subscriptable attr

Added in version 1.1

Raises:: ValueError –

Examples

This code with js_link:

select.js_link('value', plot, 'sizing_mode')

is equivalent to the following:

from bokeh.models import CustomJS
select.js_on_change('value',
    CustomJS(args=dict(other=plot),
             code="other.sizing_mode = this.value"
    )
)

Additionally, to use attr_selector to attach the left side of a range slider to a plot’s x_range:

range_slider.js_link('value', plot.x_range, 'start', attr_selector=0)

which is equivalent to:

from bokeh.models import CustomJS
range_slider.js_on_change('value',
    CustomJS(args=dict(other=plot.x_range),
             code="other.start = this.value[0]"
    )
)

js_on_change(event: str, *callbacks: JSChangeCallback) → None#

Attach a CustomJS callback to an arbitrary BokehJS model event.

On the BokehJS side, change events for model properties have the form "change:property_name". As a convenience, if the event name passed to this method is also the name of a property on the model, then it will be prefixed with "change:" automatically:

# these two are equivalent
source.js_on_change('data', callback)
source.js_on_change('change:data', callback)

However, there are other kinds of events that can be useful to respond to, in addition to property change events. For example to run a callback whenever data is streamed to a ColumnDataSource, use the "stream" event on the source:

source.js_on_change('streaming', callback)

classmethod lookup(name: str, *, raises: bool = True) → PropertyDescriptor[Any] | None#

Find the PropertyDescriptor for a Bokeh property on a class, given the property name.

Parameters:

name (str) – name of the property to search for
raises (bool) – whether to raise or return None if missing

Returns:

descriptor for property named name

Return type:

PropertyDescriptor

on_change(attr: str, *callbacks: PropertyCallback) → None#

Add a callback on this object to trigger when attr changes.

Parameters:

attr (str) – an attribute name on this object
*callbacks (callable) – callback functions to register

Returns:

None

Examples

widget.on_change('value', callback1, callback2, ..., callback_n)

on_event(event: str | type[Event], *callbacks: Callable[[Event], None] | Callable[[], None]) → None#

Run callbacks when the specified event occurs on this Model

Not all Events are supported for all Models. See specific Events in bokeh.events for more information on which Models are able to trigger them.

classmethod parameters() → list[Parameter]#

Generate Python Parameter values suitable for functions that are derived from the glyph.

Returns:: list(Parameter)

classmethod properties(*, _with_props: bool = False) → set[str] | dict[str, Property[Any]]#

Collect the names of properties on this class.

Warning

In a future version of Bokeh, this method will return a dictionary mapping property names to property objects. To future-proof this current usage of this method, wrap the return value in list.

Returns:: property names

classmethod properties_with_refs() → dict[str, Property[Any]]#

Collect the names of all properties on this class that also have references.

This method always traverses the class hierarchy and includes properties defined on any parent classes.

Returns:: names of properties that have references
Return type:: set[str]

properties_with_values(*, include_defaults: bool = True, include_undefined: bool = False) → dict[str, Any]#

Collect a dict mapping property names to their values.

This method always traverses the class hierarchy and includes properties defined on any parent classes.

Non-serializable properties are skipped and property values are in “serialized” format which may be slightly different from the values you would normally read from the properties; the intent of this method is to return the information needed to losslessly reconstitute the object instance.

Parameters:: include_defaults (bool, optional) – Whether to include properties that haven’t been explicitly set since the object was created. (default: True)
Returns:: mapping from property names to their values
Return type:: dict

query_properties_with_values(query: Callable[[PropertyDescriptor[Any]], bool], *, include_defaults: bool = True, include_undefined: bool = False) → dict[str, Any]#

Query the properties values of HasProps instances with a predicate.

Parameters:

query (callable) – A callable that accepts property descriptors and returns True or False
include_defaults (bool, optional) – Whether to include properties that have not been explicitly set by a user (default: True)

Returns:

mapping of property names and values for matching properties

Return type:

dict

references() → set[Model]#: Returns all Models that this object has references to.

remove_on_change(attr: str, *callbacks: Callable[[str, Any, Any], None]) → None#: Remove a callback from this object

select(selector: SelectorType) → Iterable[Model]#

Query this object and all of its references for objects that match the given selector.

Parameters:: selector (JSON-like)
Returns:: seq[Model]

select_one(selector: SelectorType) → Model | None#

Query this object and all of its references for objects that match the given selector. Raises an error if more than one object is found. Returns single matching object, or None if nothing is found :param selector: :type selector: JSON-like

Returns:: Model

set_from_json(name: str, value: Any, *, setter: Setter | None = None) → None#

Set a property value on this object from JSON.

Parameters:

name – (str) : name of the attribute to set
json – (JSON-value) : value to set to the attribute to
models (dict or None, optional) –
Mapping of model ids to models (default: None)

This is needed in cases where the attributes to update also have values that have references.
setter (ClientSession or ServerSession or None, optional) –
This is used to prevent “boomerang” updates to Bokeh apps.

In the context of a Bokeh server application, incoming updates to properties will be annotated with the session that is doing the updating. This value is propagated through any subsequent change notifications that the update triggers. The session can compare the event setter to itself, and suppress any updates that originate from itself.

Returns:

None

set_select(selector: type[Model] | SelectorType, updates: dict[str, Any]) → None#

Update objects that match a given selector with the specified attribute/value updates.

Parameters:

selector (JSON-like)
updates (dict)

Returns:

None

themed_values() → dict[str, Any] | None#

Get any theme-provided overrides.

Results are returned as a dict from property name to value, or None if no theme overrides any values for this instance.

Returns:: dict or None

to_serializable(serializer: Serializer) → ObjectRefRep#: Converts this object to a serializable representation.

trigger(attr: str, old: Any, new: Any, hint: DocumentPatchedEvent | None = None, setter: Setter | None = None) → None#

unapply_theme() → None#

Remove any themed values and restore defaults.

Returns:: None

update(**kwargs: Any) → None#

Updates the object’s properties from the given keyword arguments.

Returns:: None

Examples

The following are equivalent:

from bokeh.models import Range1d

r = Range1d

# set properties individually:
r.start = 10
r.end = 20

# update properties together:
r.update(start=10, end=20)

property document: Document | None#: The Document this model is attached to (can be None)