VArea#
- class VArea(*args: Any, id: ID | None = None, **kwargs: Any)[source]#
Bases:
FillGlyph
,HatchGlyph
Render a vertically directed area between two equal length sequences of y-coordinates with the same x-coordinates.
Example
import numpy as np from bokeh.io import curdoc, show from bokeh.models import ColumnDataSource, Grid, LinearAxis, Plot, VArea N = 30 x = np.linspace(-2, 3, N) y1 = np.zeros(N) y2 = 10 - x**2 source = ColumnDataSource(dict(x=x, y1=y1, y2=y2)) plot = Plot( title=None, width=300, height=300, min_border=0, toolbar_location=None) glyph = VArea(x="x", y1="y1", y2="y2", fill_color="#f46d43") 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)
JSON Prototype
{ "decorations": [], "fill_alpha": 1.0, "fill_color": "gray", "hatch_alpha": { "type": "value", "value": 1.0 }, "hatch_color": { "type": "value", "value": "black" }, "hatch_extra": { "type": "map" }, "hatch_pattern": { "type": "value", "value": null }, "hatch_scale": { "type": "value", "value": 12.0 }, "hatch_weight": { "type": "value", "value": 1.0 }, "id": "p52915", "js_event_callbacks": { "type": "map" }, "js_property_callbacks": { "type": "map" }, "name": null, "subscribed_events": { "type": "set" }, "syncable": true, "tags": [], "x": { "field": "x", "type": "field" }, "y1": { "field": "y1", "type": "field" }, "y2": { "field": "y2", "type": "field" } }
- decorations = []#
- Type:
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.
- hatch_extra = {}#
-
The hatch extra values for the vertical directed area.
- hatch_pattern = None#
- Type:
HatchPatternSpec
The hatch pattern values for the vertical directed area.
- hatch_scale = 12.0#
- Type:
The hatch scale values for the vertical directed area.
- hatch_weight = 1.0#
- Type:
The hatch weight values for the vertical directed area.
- name = None#
-
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.
- syncable = True#
- Type:
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 anyon_change()
callbacks on this object from triggering. However, any JS-side callbacks will still work.
- tags = []#
- Type:
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:
The x-coordinates for the points of the area.
- y1 = Field(field='y1', transform=Unspecified, units=Unspecified)#
- Type:
The y-coordinates for the points of one side of the area.
- y2 = Field(field='y2', transform=Unspecified, units=Unspecified)#
- Type:
The y-coordinates for the points of the other side of the area.
- 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() HasProps #
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.
- 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.
- classmethod descriptors() list[bokeh.core.property.descriptors.PropertyDescriptor[Any]] #
List of property descriptors in the order of definition.
- 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:
Added in version 1.1
- Raises:
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:
- Returns:
descriptor for property named
name
- Return type:
- 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: EventCallback) 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[inspect.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.
- 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.
- 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:
- references() set[bokeh.model.model.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 #
- 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)