B @\+@sdZddlmZmZmZmZddlZeeZ ddl m Z m Z ddl mZmZddlmZmZmZmZddlmZmZd Zdd d Zd d dZd!ddZd"ddZd#ddZd$ddZd%ddZddZ ddZ!dS)&z Helper functions for applying client-side computations such as transformations to data fields or ``ColumnDataSource`` expressions. )absolute_importdivisionprint_functionunicode_literalsN)exprfield)CumSumStack)CategoricalColorMapperCategoricalMarkerMapperLinearColorMapperLogColorMapper)DodgeJitter) cumsumdodge factor_cmap factor_markjitter linear_cmaplog_cmapstack transformFcCstt||dS)a} Create a Create a ``DataSpec`` dict to generate a ``CumSum`` expression for a ``ColumnDataSource``. Examples: .. code-block:: python p.wedge(start_angle=cumsum('angle', include_zero=True), end_angle=cumsum('angle'), ...) will generate a ``CumSum`` expressions that sum the ``"angle"`` column of a data source. For the ``start_angle`` value, the cumulative sums will start with a zero value. For ``start_angle``, no initial zero will be added (i.e. the sums will start with the first angle value, and include the last). )r include_zero)rr )rrr.lib/python3.7/site-packages/bokeh/transform.pyr6srcCst|t||dS)a Create a ``DataSpec`` dict to apply a client-side ``Jitter`` transformation to a ``ColumnDataSource`` column. Args: field_name (str) : a field name to configure ``DataSpec`` with value (float) : the fixed offset to add to column data range (Range, optional) : a range to use for computing synthetic coordinates when necessary, e.g. a ``FactorRange`` when the column data is categorical (default: None) Returns: dict )valuerange)rr) field_namerrrrrrKsrgrayc Cst|t|||||dS)aP Create a ``DataSpec`` dict to apply a client-side ``CategoricalColorMapper`` transformation to a ``ColumnDataSource`` column. Args: field_name (str) : a field name to configure ``DataSpec`` with palette (seq[color]) : a list of colors to use for colormapping factors (seq) : a sequences of categorical factors corresponding to the palette start (int, optional) : a start slice index to apply when the column data has factors with multiple levels. (default: 0) end (int, optional) : an end slice index to apply when the column data has factors with multiple levels. (default: None) nan_color (color, optional) : a default color to use when mapping data from a column does not succeed (default: "gray") Returns: dict )palettefactorsstartend nan_color)rr )rr!r"r#r$r%rrrr^s rcCst|t||||dS)a? Create a ``DataSpec`` dict to apply a client-side ``CategoricalMarkerMapper`` transformation to a ``ColumnDataSource`` column. .. note:: This transform is primarily only useful with ``scatter``, which can be parameterized by glyph type. Args: field_name (str) : a field name to configure ``DataSpec`` with markers (seq[string]) : a list of markers to use map to factors (seq) : a sequences of categorical factors corresponding to the palette start (int, optional) : a start slice index to apply when the column data has factors with multiple levels. (default: 0) end (int, optional) : an end slice index to apply when the column data has factors with multiple levels. (default: None) Returns: dict )markersr"r#r$)rr )rr&r"r#r$rrrr~sruniformcCst|t||||dS)a Create a ``DataSpec`` dict to apply a client-side ``Jitter`` transformation to a ``ColumnDataSource`` column. Args: field_name (str) : a field name to configure ``DataSpec`` with width (float) : the width of the random distribution to apply mean (float, optional) : an offset to apply (default: 0) distribution (str, optional) : ``"uniform"`` or ``"normal"`` (default: ``"uniform"``) range (Range, optional) : a range to use for computing synthetic coordinates when necessary, e.g. a ``FactorRange`` when the column data is categorical (default: None) Returns: dict )meanwidth distributionr)rr)rr)r(r*rrrrrsrc Cst|t||||||dS)ac Create a ``DataSpec`` dict to apply a client-side ``LinearColorMapper`` transformation to a ``ColumnDataSource`` column. Args: field_name (str) : a field name to configure ``DataSpec`` with palette (seq[color]) : a list of colors to use for colormapping low (float) : a minimum value of the range to map into the palette. Values below this are clamped to ``low``. high (float) : a maximum value of the range to map into the palette. Values above this are clamped to ``high``. low_color (color, optional) : color to be used if data is lower than ``low`` value. If None, values lower than ``low`` are mapped to the first color in the palette. (default: None) high_color (color, optional) : color to be used if data is higher than ``high`` value. If None, values higher than ``high`` are mapped to the last color in the palette. (default: None) nan_color (color, optional) : a default color to use when mapping data from a column does not succeed (default: "gray") )r!lowhighr% low_color high_color)rr )rr!r+r,r-r.r%rrrrs rc Cst|t||||||dS)a` Create a ``DataSpec`` dict to apply a client-side ``LogColorMapper`` transformation to a ``ColumnDataSource`` column. Args: field_name (str) : a field name to configure ``DataSpec`` with palette (seq[color]) : a list of colors to use for colormapping low (float) : a minimum value of the range to map into the palette. Values below this are clamped to ``low``. high (float) : a maximum value of the range to map into the palette. Values above this are clamped to ``high``. low_color (color, optional) : color to be used if data is lower than ``low`` value. If None, values lower than ``low`` are mapped to the first color in the palette. (default: None) high_color (color, optional) : color to be used if data is higher than ``high`` value. If None, values higher than ``high`` are mapped to the last color in the palette. (default: None) nan_color (color, optional) : a default color to use when mapping data from a column does not succeed (default: "gray") )r!r+r,r%r-r.)rr)rr!r+r,r-r.r%rrrrs rcGstt|dS)a Create a Create a ``DataSpec`` dict to generate a ``Stack`` expression for a ``ColumnDataSource``. Examples: .. code-block:: python p.vbar(bottom=stack("sales", "marketing"), ... will generate a ``Stack`` that sums the ``"sales"`` and ``"marketing"`` columns of a data source, and use those values as the ``top`` coordinate for a ``VBar``. )fields)rr )r/rrrrsrcCs t||S)a) Create a ``DataSpec`` dict to apply an arbitrary client-side ``Transform`` to a ``ColumnDataSource`` column. Args: field_name (str) : A field name to configure ``DataSpec`` with transform (Transform) : A transforms to apply to that field Returns: dict )r)rrrrrrs r)F)N)rNr )rN)rr'N)NNr )NNr )"__doc__Z __future__rrrrZloggingZ getLogger__name__logZcore.propertiesrrZmodels.expressionsr r Zmodels.mappersr r r rZmodels.transformsrr__all__rrrrrrrrrrrrr s"     " "