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# Copyright (c) 2012 - 2021, Anaconda, Inc., and Bokeh Contributors.
# All rights reserved.
#
# The full license is in the file LICENSE.txt, distributed with this software.
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''' Represent transformations of data to happen on the client (browser) side.
'''
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# Boilerplate
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from __future__ import annotations
import logging # isort:skip
log = logging.getLogger(__name__)
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# Imports
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# Bokeh imports
from ..core.enums import JitterRandomDistribution, StepMode
from ..core.has_props import abstract
from ..core.properties import (
AnyRef,
Bool,
Dict,
Either,
Enum,
Float,
Instance,
NonNullable,
Nullable,
Seq,
String,
)
from ..model import Model
from .sources import ColumnarDataSource
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# Globals and constants
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__all__ = (
'CustomJSTransform',
'Dodge',
'Interpolator',
'Jitter',
'LinearInterpolator',
'StepInterpolator',
'Transform',
)
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# General API
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[docs]class Dodge(Transform):
''' Apply either fixed dodge amount to data.
'''
value = Float(default=0, help="""
The amount to dodge the input data.
""")
range = Nullable(Instance("bokeh.models.ranges.Range"), help="""
When applying ``Dodge`` to categorical data values, the corresponding
``FactorRange`` must be supplied as the ``range`` property.
""")
[docs]class Jitter(Transform):
''' Apply either a uniform or normally sampled random jitter to data.
'''
mean = Float(default=0, help="""
The central value for the random sample
""")
width = Float(default=1, help="""
The width (absolute for uniform distribution and sigma for the normal
distribution) of the random sample.
""")
distribution = Enum(JitterRandomDistribution, default='uniform', help="""
The random distribution upon which to pull the random scatter
""")
range = Nullable(Instance("bokeh.models.ranges.Range"), help="""
When applying Jitter to Categorical data values, the corresponding
``FactorRange`` must be supplied as the ``range`` property.
""")
[docs]@abstract
class Interpolator(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:
.. code-block:: python
interp = Interpolator(x=[1, 2, 3, 4, 5], y=[2, 5, 10, 12, 16])
* or a pair of columns defined in a ``ColumnDataSource`` object:
.. code-block:: python
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.
'''
x = NonNullable(Either(String, Seq(Float)), help="""
Independent coordinate denoting the location of a point.
""")
y = NonNullable(Either(String, Seq(Float)), help="""
Dependant coordinate denoting the value of a point at a location.
""")
data = Nullable(Instance(ColumnarDataSource), help="""
Data which defines the source for the named columns if a string is passed to either the ``x`` or ``y`` parameters.
""")
clip = Bool(True, help="""
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.
""")
# Define an initialization routine to do some cross checking of input values
def __init__(self, **kwargs) -> None:
super().__init__(**kwargs)
[docs]class LinearInterpolator(Interpolator):
''' Compute a linear interpolation between the control points provided through
the ``x``, ``y``, and ``data`` parameters.
'''
pass
[docs]class StepInterpolator(Interpolator):
''' Compute a step-wise interpolation between the points provided through
the ``x``, ``y``, and ``data`` parameters.
'''
mode = Enum(StepMode, default="after", help="""
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.
""")
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# Dev API
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# Private API
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# Code
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