Source code for bokeh.models.scales
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# Copyright (c) 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 ..core.properties import Instance, Required
from .transforms import Transform
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# Globals and constants
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__all__ = (
    'CategoricalScale',
    'CompositeScale',
    '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) 
[docs]
class CompositeScale(Scale):
    ''' Represent a composition of two scales, which useful for defining
    sub-coordinate systems.
    '''
    # explicit __init__ to support Init signatures
    def __init__(self, *args, **kwargs) -> None:
        super().__init__(*args, **kwargs)
    source_scale = Required(Instance(Scale), help="""
    The source scale.
    """)
    target_scale = Required(Instance(Scale), help="""
    The target scale.
    """) 
    # TODO assert source_scale != target_scale
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# Dev API
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# Private API
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# Code
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