σ mάJ]c @`sGdZddlmZmZmZmZddlZejeƒZ ddl m Z m Z ddl mZmZddlmZmZmZmZmZddlmZmZdZed„Zdd„Zdddd„Zddd„Zddd„Z dddd„Z!dddd„Z"dddd„Z#d„Z$d„Z%dS( u… Helper functions for applying client-side computations such as transformations to data fields or ``ColumnDataSource`` expressions. i(tabsolute_importtdivisiontprint_functiontunicode_literalsNi(texprtfield(tCumSumtStack(tCategoricalColorMappertCategoricalMarkerMappertCategoricalPatternMappertLinearColorMappertLogColorMapper(tDodgetJitterucumsumudodgeu factor_cmapu factor_hatchu factor_markujitteru linear_cmapulog_cmapustacku transformcC`sttd|d|ƒƒS(u} 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). Rt include_zero(RR(RR((s.lib/python2.7/site-packages/bokeh/transform.pytcumsum7scC`st|td|d|ƒƒS(uς 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 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 tvaluetrange(RR (t field_nameRR((s.lib/python2.7/site-packages/bokeh/transform.pytdodgeLsugrayc C`s.t|td|d|d|d|d|ƒƒS(uT 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 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 tpalettetfactorststarttendt nan_color(RR(RRRRRR((s.lib/python2.7/site-packages/bokeh/transform.pyt factor_cmap_s c C`s(t|td|d|d|d|ƒƒS(uθ 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: dict Added in version 1.1.1 tpatternsRRR(RR (RRRRR((s.lib/python2.7/site-packages/bokeh/transform.pyt factor_hatchsc C`s(t|td|d|d|d|ƒƒS(uF 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: dict tmarkersRRR(RR (RRRRR((s.lib/python2.7/site-packages/bokeh/transform.pyt factor_marksuuniformc C`s(t|td|d|d|d|ƒƒS(u¦ 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: dict tmeantwidtht distributionR(RR(RR RR!R((s.lib/python2.7/site-packages/bokeh/transform.pytjitter½scC`s4t|td|d|d|d|d|d|ƒƒS(uh Create a ``DataSpec`` dict that applyies 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") RtlowthighRt low_colort high_color(RR (RRR#R$R%R&R((s.lib/python2.7/site-packages/bokeh/transform.pyt linear_cmapΨs cC`s4t|td|d|d|d|d|d|ƒƒS(ud 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") RR#R$RR%R&(RR (RRR#R$R%R&R((s.lib/python2.7/site-packages/bokeh/transform.pytlog_cmapϊs cG`sttd|ƒƒS(u’ 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``. tfields(RR(R)((s.lib/python2.7/site-packages/bokeh/transform.pytstackscC`s t||ƒS(u- 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: dict (R(Rt transform((s.lib/python2.7/site-packages/bokeh/transform.pyR+.s ( ucumsumudodgeu factor_cmapu factor_hatchu factor_markujitteru linear_cmapulog_cmapustacku transform(&t__doc__t __future__RRRRtloggingt getLoggert__name__tlogtcore.propertiesRRtmodels.expressionsRRtmodels.mappersRR R R R tmodels.transformsR Rt__all__tFalseRtNoneRRRRR"R'R(R*R+(((s.lib/python2.7/site-packages/bokeh/transform.pyt s6"  (    ""