a =Df9 @sUdZddlmZddlZeeZddlmZm Z m Z ddl m Z m Z ddlmZmZddlmZmZmZmZmZmZdd lmZmZerdd lmZdd lmZdd lm Z dd l!m"Z"ddlm#Z#dZ$ere e e%e e&e%e%fe e&e%e%e%ffZ'de(d<dAddddddZ)dBdddddddZ*dCdd ddd!d!d"dd#d$d%Z+dDdd ddd&d"dd'd(d)Z,dEdd*ddd&dd+d,d-Z-dFdd*ddd&dd.d/d0Z.dGdddd2ddd3d4d5Z/dHdd ddd!d!d"dd#d6d7Z0dIdd ddd!d!d"dd#d8d9Z1ddd:d;d<Z2dd=dd>d?d@Z3dS)Jz 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 transformrFactorsFstrboolr) field_name include_zeroreturncCstt||dS)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'r*\/nfs/NAS7/SABIOD/METHODE/ermites/ermites_venv/lib/python3.9/site-packages/bokeh/transform.pyrIsrfloatz Range | Noner)r&valueranger(cCst|t||dS)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-r.)rr)r&r-r.r*r*r+rdsrgrayzSequence[ColorLike]zColorLike | Noner)r&palettelowhigh low_color high_color nan_colorr(c Cst|t||||||dS)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") r0r1r2r5r3r4)rrr&r0r1r2r3r4r5r*r*r+rws#rz float | None)r&r0factorsstartendr5r(c Cst|t|||||dS)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 )r0r8r9r:r5)rr )r&r0r8r9r:r5r*r*r+rs!rz Sequence[str])r&patternsr8r9r:r(cCst|t||||dS)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 )r;r8r9r:)rr )r&r;r8r9r:r*r*r+rsr)r&markersr8r9r:r(cCst|t||||dS)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 )r<r8r9r:)rr )r&r<r8r9r:r*r*r+rs!runiformr)r&widthmean distributionr.r(cCst|t||||dS)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 )r?r>r@r.)rr)r&r>r?r@r.r*r*r+r&src Cst|t||||||dS)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") r6)rrr7r*r*r+rLs#rc Cst|t||||||dS)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") r6)rrr7r*r*r+r {s#r )fieldsr(cGstt|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``. rA)rr rBr*r*r+r!sr!r)r&r"r(cCs 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"r*r*r+r"s r")F)N)NNr/)rNr/)rN)rN)rr=N)NNr/)NNr/)4__doc__ __future__rlogging getLogger__name__logtypingrrrZcore.property.vectorizationrrZmodels.expressionsr r Zmodels.mappersr r r rrrZmodels.transformsrrZtyping_extensionsrcolorsrZ core.enumsrZ models.rangesrr__all__r$tupler#__annotations__rrrrrrrrr r!r"r*r*r*r+s^        430-.+4/