Source code for bokeh.models.scales
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# Copyright (c) 2012 - 2023, 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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'''
'''
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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.has_props import abstract
from .transforms import Transform
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# Globals and constants
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__all__ = (
'CategoricalScale',
'LinearScale',
'LogScale',
'Scale',
)
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# General API
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[docs]@abstract
class Scale(Transform):
''' Base class for ``Scale`` models that represent an invertible
computation to be carried out on the client-side.
JavaScript implementations should implement the following methods:
.. code-block
compute(x: number): number {
# compute and return the transform of a single value
}
v_compute(xs: Arrayable<number>): Arrayable<number> {
# compute and return the transform of an array of values
}
invert(sx: number): number {
# compute and return the inverse transform of a single value
}
v_invert(sxs: Arrayable<number>): Arrayable<number> {
# compute and return the inverse transform of an array of values
}
'''
# explicit __init__ to support Init signatures
def __init__(self, *args, **kwargs) -> None:
super().__init__(*args, **kwargs)
class ContinuousScale(Scale):
''' Represent a scale transformation between continuous ranges.
'''
# explicit __init__ to support Init signatures
def __init__(self, *args, **kwargs) -> None:
super().__init__(*args, **kwargs)
[docs]class LinearScale(ContinuousScale):
''' Represent a linear scale transformation between continuous ranges.
'''
# explicit __init__ to support Init signatures
def __init__(self, *args, **kwargs) -> None:
super().__init__(*args, **kwargs)
[docs]class LogScale(ContinuousScale):
''' Represent a log scale transformation between continuous ranges.
'''
# explicit __init__ to support Init signatures
def __init__(self, *args, **kwargs) -> None:
super().__init__(*args, **kwargs)
[docs]class CategoricalScale(Scale):
''' Represent a scale transformation between a categorical source range and
continuous target range.
'''
# explicit __init__ to support Init signatures
def __init__(self, *args, **kwargs) -> None:
super().__init__(*args, **kwargs)
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# Dev API
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# Private API
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# Code
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