bokeh.models.transforms¶
Represent transformations of data to happen on the client (browser) side.
-
class
CustomJSTransform
(**kwargs)[source]¶ Bases:
bokeh.models.transforms.Transform
Apply a custom defined transform to data.
Warning
The explicit purpose of this Bokeh Model is to embed raw JavaScript code for a browser to execute. If any part of the code is derived from untrusted user inputs, then you must take appropriate care to sanitize the user input prior to passing to Bokeh.
-
args
¶ property type:
Dict
(String
,AnyRef
)A mapping of names to Python objects. In particular those can be bokeh’s models. These objects are made available to the transform’ code snippet as the values of named parameters to the callback.
-
func
¶ property type:
String
A snippet of JavaScript code to transform a single value. The variable
x
will contain the untransformed value and can be expected to be present in the function namespace at render time. The snippet will be into the body of a function and therefore requires a return statement.Example:
func = ''' return Math.floor(x) + 0.5 '''
-
use_strict
¶ property type:
Bool
Enables or disables automatic insertion of
"use strict";
intofunc
orv_func
.
-
v_func
¶ property type:
String
A snippet of JavaScript code to transform an array of values. The variable
xs
will contain the untransformed array and can be expected to be present in the function namespace at render time. The snippet will be into the body of a function and therefore requires a return statement.Example:
v_func = ''' var new_xs = new Array(xs.length) for(var i = 0; i < xs.length; i++) { new_xs[i] = xs[i] + 0.5 } return new_xs '''
Warning
The vectorized function,
v_func
, must return an array of the same length as the inputxs
array.
-
classmethod
from_coffeescript
(func, v_func, args={})[source]¶ Create a
CustomJSTransform
instance from a pair of CoffeeScript snippets. The function bodies are translated to JavaScript functions using node and therefore require return statements.The
func
snippet namespace will contain the variablex
(the untransformed value) at render time. Thev_func
snippet namespace will contain the variablexs
(the untransformed vector) at render time.Example:
func = "return Math.cos(x)" v_func = "return [Math.cos(x) for x in xs]" transform = CustomJSTransform.from_coffeescript(func, v_func)
Parameters: Returns: CustomJSTransform
-
classmethod
from_py_func
(func, v_func)[source]¶ Create a
CustomJSTransform
instance from a pair of Python functions. The function is translated to JavaScript using PScript.The python functions must have no positional arguments. It’s possible to pass Bokeh models (e.g. a
ColumnDataSource
) as keyword arguments to the functions.The
func
function namespace will contain the variablex
(the untransformed value) at render time. Thev_func
function namespace will contain the variablexs
(the untransformed vector) at render time.Warning
The vectorized function,
v_func
, must return an array of the same length as the inputxs
array.Example:
def transform(): from pscript.stubs import Math return Math.cos(x) def v_transform(): from pscript.stubs import Math return [Math.cos(x) for x in xs] customjs_transform = CustomJSTransform.from_py_func(transform, v_transform)
Parameters: - func (function) – a scalar function to transform a single
x
value - v_func (function) – a vectorized function to transform a vector
xs
Returns: CustomJSTransform
- func (function) – a scalar function to transform a single
-
-
class
Dodge
(**kwargs)[source]¶ Bases:
bokeh.models.transforms.Transform
Apply either fixed dodge amount to data.
-
class
Interpolator
(**kwargs)[source]¶ Bases:
bokeh.models.transforms.Transform
Base class for interpolator transforms.
Interpolators return the value of a function which has been evaluated between specified (x, y) pairs of data. As an example, if two control point pairs were provided to the interpolator, a linear interpolaction at a specific value of ‘x’ would result in the value of ‘y’ which existed on the line connecting the two control points.
The control point pairs for the interpolators can be specified through either
- A literal sequence of values:
interp = Interpolator(x=[1, 2, 3, 4, 5], y=[2, 5, 10, 12, 16])
- or a pair of columns defined in a
ColumnDataSource
object:
interp = Interpolator(x="year", y="earnings", data=jewlery_prices))
This is the base class and is not intended to end use. Please see the documentation for the final derived classes (
Jitter
,LineraInterpolator
,StepInterpolator
) for more information on their specific methods of interpolation.Note
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.
-
clip
¶ property type:
Bool
Determine if the interpolation should clip the result to include only values inside its predefined range. If this is set to False, it will return the most value of the closest point.
-
data
¶ property type:
Instance
(ColumnarDataSource
)Data which defines the source for the named columns if a string is passed to either the
x
ory
parameters.
-
class
Jitter
(**kwargs)[source]¶ Bases:
bokeh.models.transforms.Transform
Apply either a uniform or normally sampled random jitter to data.
-
distribution
¶ property type:
Enum
(JitterRandomDistribution
)The random distribution upon which to pull the random scatter
-
-
class
LinearInterpolator
(**kwargs)[source]¶ Bases:
bokeh.models.transforms.Interpolator
Compute a linear interpolation between the control points provided through the
x
,y
, anddata
parameters.
-
class
StepInterpolator
(**kwargs)[source]¶ Bases:
bokeh.models.transforms.Interpolator
Compute a step-wise interpolation between the points provided through the
x
,y
, anddata
parameters.-
mode
¶ property type:
Enum
(StepMode
)Adjust the behavior of the returned value in relation to the control points. The parameter can assume one of three values:
after
(default): Assume the y-value associated with the nearest x-value which is less than or equal to the point to transform.before
: Assume the y-value associated with the nearest x-value which is greater than the point to transform.center
: Assume the y-value associated with the nearest x-value to the point to transform.
-
-
class
Transform
(**kwargs)[source]¶ Bases:
bokeh.model.Model
Base class for
Transform
models that represent a computation to be carried out on the client-side.JavaScript implementations should implement the following methods:
compute: (x) -> # compute the transform of a single value v_compute: (xs) -> # compute the transform of an array of values
Note
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.