Models for computing good tick locations on different kinds of plots.
AdaptiveTicker
Bases: bokeh.models.tickers.ContinuousTicker
bokeh.models.tickers.ContinuousTicker
Generate “nice” round ticks at any magnitude.
Creates ticks that are “base” multiples of a set of given mantissas. For example, with base=10 and mantissas=[1, 2, 5], the ticker will generate the sequence:
base=10
mantissas=[1, 2, 5]
..., 0.1, 0.2, 0.5, 1, 2, 5, 10, 20, 50, 100, ...
base
Float
10.0
The multiplier to use for scaling mantissas.
desired_num_ticks
Int
6
A desired target number of major tick positions to generate across the plot range.
js_event_callbacks
Dict(String, List(Instance(CustomJS)))
Dict
String
List
Instance
CustomJS
{}
A mapping of event names to lists of CustomJS callbacks.
Typically, rather then modifying this property directly, callbacks should be added using the Model.js_on_event method:
Model.js_on_event
callback = CustomJS(code="console.log('tap event occurred')") plot.js_on_event('tap', callback)
js_property_callbacks
A mapping of attribute names to lists of CustomJS callbacks, to be set up on BokehJS side when the document is created.
Typically, rather then modifying this property directly, callbacks should be added using the Model.js_on_change method:
Model.js_on_change
callback = CustomJS(code="console.log('stuff')") plot.x_range.js_on_change('start', callback)
mantissas
Seq(Float)
Seq
[1, 2, 5]
The acceptable list numbers to generate multiples of.
max_interval
Nullable(Float)
Nullable
None
The largest allowable interval between two adjacent ticks.
Note
To specify an unbounded interval, set to None.
min_interval
0.0
The smallest allowable interval between two adjacent ticks.
name
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', ...)]
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.
num_minor_ticks
5
The number of minor tick positions to generate between adjacent major tick values.
subscribed_events
List(String)
[]
List of events that are subscribed to by Python callbacks. This is the set of events that will be communicated from BokehJS back to Python for this model.
syncable
Bool
True
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.
False
Setting this property to False will prevent any on_change() callbacks on this object from triggering. However, any JS-side callbacks will still work.
on_change()
tags
List(AnyRef)
AnyRef
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.
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.
apply_theme
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).
HasProps
property_values (dict) – theme values to use in place of defaults
dataspecs
Collect the names of all DataSpec properties on this class.
DataSpec
This method always traverses the class hierarchy and includes properties defined on any parent classes.
names of DataSpec properties
set[str]
dataspecs_with_props
Collect a dict mapping the names of all DataSpec properties on this class to the associated properties.
mapping of names and DataSpec properties
dict[str, DataSpec]
equals
Structural equality of models.
other (HasProps) – the other instance to compare to
True, if properties are structurally equal, otherwise False
js_link
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.
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
other
attr_selector (Union[int, str]) – The index to link an item in a subscriptable attr
attr
Added in version 1.1
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
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:
"change:property_name"
"change:"
# 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:
ColumnDataSource
"stream"
source.js_on_change('streaming', callback)
layout
lookup
Find the PropertyDescriptor for a Bokeh property on a class, given the property name.
PropertyDescriptor
name (str) – name of the property to search for
raises (bool) – whether to raise or return None if missing
descriptor for property named name
on_change
Add a callback on this object to trigger when attr changes.
attr (str) – an attribute name on this object
*callbacks (callable) – callback functions to register
Example:
widget.on_change('value', callback1, callback2, ..., callback_n)
on_event
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.
properties
Collect the names of properties on this class.
This method optionally traverses the class hierarchy and includes properties defined on any parent classes.
with_bases (bool, optional) – Whether to include properties defined on parent classes in the results. (default: True)
property names
properties_containers
Collect the names of all container properties on this class.
names of container properties
properties_with_refs
Collect the names of all properties on this class that also have references.
names of properties that have references
properties_with_values
Collect a dict mapping property names to their values.
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.
include_defaults (bool, optional) – Whether to include properties that haven’t been explicitly set since the object was created. (default: True)
mapping from property names to their values
dict
query_properties_with_values
Query the properties values of HasProps instances with a predicate.
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)
mapping of property names and values for matching properties
references
Returns all Models that this object has references to.
Models
remove_on_change
Remove a callback from this object
select
Query this object and all of its references for objects that match the given selector.
selector (JSON-like) –
seq[Model]
select_one
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
Model
set_from_json
Set a property value on this object from JSON.
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.
set_select
Update objects that match a given selector with the specified attribute/value updates.
updates (dict) –
themed_values
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.
dict or None
to_json
Returns a dictionary of the attributes of this object, containing only “JSON types” (string, number, boolean, none, dict, list).
References to other objects are serialized as “refs” (just the object ID and type info), so the deserializer will need to separately have the full attributes of those other objects.
There’s no corresponding from_json() because to deserialize an object is normally done in the context of a Document (since the Document can resolve references).
from_json()
For most purposes it’s best to serialize and deserialize entire documents.
include_defaults (bool) – whether to include attributes that haven’t been changed from the default
to_json_string
Returns a JSON string encoding the attributes of this object.
References to other objects are serialized as references (just the object ID and type info), so the deserializer will need to separately have the full attributes of those other objects.
There’s no corresponding from_json_string() because to deserialize an object is normally done in the context of a Document (since the Document can resolve references).
from_json_string()
trigger
unapply_theme
Remove any themed values and restore defaults.
update
Updates the object’s properties from the given keyword arguments.
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)
update_from_json
Updates the object’s properties from a JSON attributes dictionary.
json_attributes – (JSON-dict) : attributes and values to update
document
The Document this model is attached to (can be None)
Document
struct
A Bokeh protocol “structure” of this model, i.e. a dict of the form:
{ 'type' : << view model name >> 'id' : << unique model id >> }
Additionally there may be a subtype field if this model is a subtype.
{ "base": 10.0, "desired_num_ticks": 6, "id": "18789", "js_event_callbacks": {}, "js_property_callbacks": {}, "mantissas": [ 1, 2, 5 ], "max_interval": null, "min_interval": 0.0, "name": null, "num_minor_ticks": 5, "subscribed_events": [], "syncable": true, "tags": [] }
BasicTicker
Bases: bokeh.models.tickers.AdaptiveTicker
bokeh.models.tickers.AdaptiveTicker
Generate ticks on a linear scale.
This class may be renamed to LinearTicker in the future.
LinearTicker
{ "base": 10.0, "desired_num_ticks": 6, "id": "18802", "js_event_callbacks": {}, "js_property_callbacks": {}, "mantissas": [ 1, 2, 5 ], "max_interval": null, "min_interval": 0.0, "name": null, "num_minor_ticks": 5, "subscribed_events": [], "syncable": true, "tags": [] }
BinnedTicker
Bases: bokeh.models.tickers.Ticker
bokeh.models.tickers.Ticker
Ticker that aligns ticks exactly at bin boundaries of a scanning color mapper.
mapper
Instance(ScanningColorMapper)
ScanningColorMapper
Undefined
A scanning color mapper (e.g. EqHistColorMapper) to use.
EqHistColorMapper
num_major_ticks
Either(Int, Auto)
Either
Auto
8
The number of major tick positions to show or “auto” to use the number of bins provided by the mapper.
{ "id": "18815", "js_event_callbacks": {}, "js_property_callbacks": {}, "name": null, "num_major_ticks": 8, "subscribed_events": [], "syncable": true, "tags": [] }
CategoricalTicker
Generate ticks for categorical ranges.
{ "id": "18824", "js_event_callbacks": {}, "js_property_callbacks": {}, "name": null, "subscribed_events": [], "syncable": true, "tags": [] }
CompositeTicker
Combine different tickers at different scales.
Uses the min_interval and max_interval interval attributes of the tickers to select the appropriate ticker at different scales.
tickers
Seq(Instance(Ticker))
Ticker
A list of Ticker objects to combine at different scales in order to generate tick values. The supplied tickers should be in order. Specifically, if S comes before T, then it should be the case that:
S.get_max_interval() < T.get_min_interval()
{ "desired_num_ticks": 6, "id": "18831", "js_event_callbacks": {}, "js_property_callbacks": {}, "name": null, "num_minor_ticks": 5, "subscribed_events": [], "syncable": true, "tags": [], "tickers": [] }
ContinuousTicker
A base class for non-categorical ticker types.
This is an abstract base class used to help organize the hierarchy of Bokeh model types. It is not useful to instantiate on its own.
{ "desired_num_ticks": 6, "id": "18841", "js_event_callbacks": {}, "js_property_callbacks": {}, "name": null, "num_minor_ticks": 5, "subscribed_events": [], "syncable": true, "tags": [] }
DatetimeTicker
Bases: bokeh.models.tickers.CompositeTicker
bokeh.models.tickers.CompositeTicker
Generate nice ticks across different date and time scales.
0
[AdaptiveTicker(id='18872', ...), AdaptiveTicker(id='18873', ...), AdaptiveTicker(id='18874', ...), DaysTicker(id='18875', ...), DaysTicker(id='18876', ...), DaysTicker(id='18877', ...), DaysTicker(id='18878', ...), MonthsTicker(id='18879', ...), MonthsTicker(id='18880', ...), MonthsTicker(id='18881', ...), MonthsTicker(id='18882', ...), YearsTicker(id='18883', ...)]
{ "desired_num_ticks": 6, "id": "18850", "js_event_callbacks": {}, "js_property_callbacks": {}, "name": null, "num_minor_ticks": 0, "subscribed_events": [], "syncable": true, "tags": [], "tickers": [ { "id": "18851" }, { "id": "18852" }, { "id": "18853" }, { "id": "18854" }, { "id": "18855" }, { "id": "18856" }, { "id": "18857" }, { "id": "18858" }, { "id": "18859" }, { "id": "18860" }, { "id": "18861" }, { "id": "18862" } ] }
DaysTicker
Bases: bokeh.models.tickers.SingleIntervalTicker
bokeh.models.tickers.SingleIntervalTicker
Generate ticks spaced apart by specific, even multiples of days.
days
Seq(Int)
The intervals of days to use.
interval
NonNullable(Float)
NonNullable
The interval between adjacent ticks.
{ "days": [], "desired_num_ticks": 6, "id": "18884", "js_event_callbacks": {}, "js_property_callbacks": {}, "name": null, "num_minor_ticks": 0, "subscribed_events": [], "syncable": true, "tags": [] }
FixedTicker
Generate ticks at fixed, explicitly supplied locations.
The desired_num_ticks property is ignored by this Ticker.
minor_ticks
List of minor tick locations.
ticks
List of major tick locations.
{ "desired_num_ticks": 6, "id": "18895", "js_event_callbacks": {}, "js_property_callbacks": {}, "minor_ticks": [], "name": null, "num_minor_ticks": 5, "subscribed_events": [], "syncable": true, "tags": [], "ticks": [] }
LogTicker
Generate ticks on a log scale.
[1, 5]
{ "base": 10.0, "desired_num_ticks": 6, "id": "18906", "js_event_callbacks": {}, "js_property_callbacks": {}, "mantissas": [ 1, 5 ], "max_interval": null, "min_interval": 0.0, "name": null, "num_minor_ticks": 5, "subscribed_events": [], "syncable": true, "tags": [] }
MercatorTicker
Bases: bokeh.models.tickers.BasicTicker
bokeh.models.tickers.BasicTicker
Generate nice lat/lon ticks form underlying WebMercator coordinates.
dimension
Nullable(Enum(LatLon))
Enum
LatLon
Specify whether to generate ticks for Latitude or Longitude.
Projected coordinates are not separable, computing Latitude and Longitude tick locations from Web Mercator requires considering coordinates from both dimensions together. Use this property to specify which result should be returned.
Typically, if the ticker is for an x-axis, then dimension should be "lon" and if the ticker is for a y-axis, then the dimension should be “lat”`.
"lon"
In order to prevent hard to debug errors, there is no default value for dimension. Using an un-configured MercatorTicker will result in a validation error and a JavaScript console error.
{ "base": 10.0, "desired_num_ticks": 6, "dimension": null, "id": "18919", "js_event_callbacks": {}, "js_property_callbacks": {}, "mantissas": [ 1, 2, 5 ], "max_interval": null, "min_interval": 0.0, "name": null, "num_minor_ticks": 5, "subscribed_events": [], "syncable": true, "tags": [] }
MonthsTicker
Generate ticks spaced apart by specific, even multiples of months.
months
The intervals of months to use.
{ "desired_num_ticks": 6, "id": "18933", "js_event_callbacks": {}, "js_property_callbacks": {}, "months": [], "name": null, "num_minor_ticks": 5, "subscribed_events": [], "syncable": true, "tags": [] }
SingleIntervalTicker
Generate evenly spaced ticks at a fixed interval regardless of scale.
{ "desired_num_ticks": 6, "id": "18944", "js_event_callbacks": {}, "js_property_callbacks": {}, "name": null, "num_minor_ticks": 5, "subscribed_events": [], "syncable": true, "tags": [] }
Bases: bokeh.model.Model
bokeh.model.Model
A base class for all ticker types.
{ "id": "18954", "js_event_callbacks": {}, "js_property_callbacks": {}, "name": null, "subscribed_events": [], "syncable": true, "tags": [] }
YearsTicker
Generate ticks spaced apart even numbers of years.
{ "desired_num_ticks": 6, "id": "18961", "js_event_callbacks": {}, "js_property_callbacks": {}, "name": null, "num_minor_ticks": 5, "subscribed_events": [], "syncable": true, "tags": [] }