-e9UdZddlmZddlZejeZddlmZm Z m Z ddl m Z m Z ddlmZmZddlmZmZmZmZmZmZdd lmZmZerdd lmZdd lmZdd lm Z dd l!m"Z"ddlm#Z#dZ$er3e e e%e e&e%e%fe e&e%e%e%ffZ'de(d<dBdCdZ)dDdEdZ* dFdGd*Z+ dHdId/Z, dJdKd2Z- dJdLd4Z. dMdNd:Z/ dFdGd;Z0 dFdGd<Z1dOd>Z2dPdAZ3dS)Qz Helper functions for applying client-side computations such as transformations to data fields or ``ColumnDataSource`` expressions. ) annotationsN) TYPE_CHECKINGSequenceUnion)ExprField)CumSumStack)CategoricalColorMapperCategoricalMarkerMapperCategoricalPatternMapperEqHistColorMapperLinearColorMapperLogColorMapper)DodgeJitter) TypeAlias) ColorLike)JitterRandomDistributionType)Range) Transform) cumsumdodge eqhist_cmap factor_cmap factor_hatch factor_markjitter linear_cmaplog_cmapstack transformrFactorsF field_namestr include_zeroboolreturnrc>tt||S)a+ Create a ``DataSpec`` dict to generate a ``CumSum`` expression for a ``ColumnDataSource``. Args: field_name (str) : a field name to configure ``CumSum`` with include_zero (bool, optional) : whether to include zero in the sum (default: False) 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 ``end_angle``, no initial zero will be added (i.e. the sums will start with the first angle value, and include the last). )fieldr')rr )r%r's /lib/python3.11/site-packages/bokeh/transform.pyrrIs2 ZlCCC D DDvaluefloatrange Range | Noner c@t|t||S)a Create a ``DataSpec`` dict that applies a client-side ``Dodge`` 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: Field )r.r0)r r)r%r.r0s r,rrds!" Ue<<< = ==r-graypaletteSequence[ColorLike]lowhigh low_colorColorLike | None high_color nan_colorrc Ht|t||||||S)ag Create a ``DataSpec`` dict that applies a client-side ``EqHistColorMapper`` 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") r4r6r7r;r8r:)r rr%r4r6r7r8r:r;s r,rrw>F !       r-factorsstartend float | Nonec Ft|t|||||S)aT Create a ``DataSpec`` dict that applies 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 sequence 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: Field )r4r@rArBr;)r r )r%r4r@rArBr;s r,rrs;B        r-patterns Sequence[str]c Dt|t||||S)a Create a ``DataSpec`` dict that applies a client-side ``CategoricalPatternMapper`` transformation to a ``ColumnDataSource`` column. Args: field_name (str) : a field name to configure ``DataSpec`` with patterns (seq[string]) : a list of hatch patterns to use to 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: Field Added in version 1.1.1 )rEr@rArB)r r)r%rEr@rArBs r,rrs7>        r-markersc Dt|t||||S)aG Create a ``DataSpec`` dict that applies 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 to 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: Field )rHr@rArB)r r )r%rHr@rArBs r,rrs8B       r-uniformwidthmean distributionrc Dt|t||||S)a Create a ``DataSpec`` dict that applies 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: Field )rLrKrMr0)r r)r%rKrLrMr0s r,rr&s78 %      r-c Ht|t||||||S)ag Create a ``DataSpec`` dict that applies 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=)r rr>s r,r r Lr?r-c Ht|t||||||S)ad Create a ``DataSpec`` dict that applies 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 rr>s r,r!r!{s>F !       r-fieldsc<tt|S)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``. rQ)rr rSs r,r"r"s V$$$ % %%r-r#rc"t||S)a. Create a ``DataSpec`` dict that applies an arbitrary client-side ``Transform`` to a ``ColumnDataSource`` column. Args: field_name (str) : A field name to configure ``DataSpec`` with transform (Transform) : A transforms to apply to that field Returns: Field )r )r%r#s r,r#r#s Y ' ''r-)F)r%r&r'r(r)r)N)r%r&r.r/r0r1r)r )NNr3)r%r&r4r5r6r/r7r/r8r9r:r9r;rr)r )rNr3)r%r&r4r5r@r$rAr/rBrCr;rr)r )rN) r%r&rErFr@r$rAr/rBrCr)r ) r%r&rHrFr@r$rAr/rBrCr)r )rrJN) r%r&rKr/rLr/rMrr0r1r)r )rQr&r)r)r%r&r#rr)r )4__doc__ __future__rlogging getLogger__name__logtypingrrrcore.property.vectorizationrr models.expressionsr r models.mappersr r rrrrmodels.transformsrrtyping_extensionsrcolorsr core.enumsr models.rangesrr__all__r&tupler$__annotations__rrrrrrrr r!r"r#r-r,rhs#"""""g!!211111111154444444---------,,,,,,,-++++++!!!!!!888888$$$$$$,,,,,, $ix}huS#X.GRWX[]`beXeRfIgghGhhhhEEEEE6>>>>>0#'#'!-----f! *****` '''''Z )))))\1: $$$$$V#'#'!-----h#'#'!-----^&&&&$ ( ( ( ( ( (r-