ó ÎYc @@sĚdZddlmZddlmZmZddlmZddlm Z ddl m Z dd l m Z dd lmZmZmZdddddd d d eedd„ Zde fd„ƒYZdS(sThis is the Bokeh charts interface. It gives you a high level API to build complex plot is a simple way. This is the Dot class which lets you build your Dot plots just passing the arguments to the Chart class and calling the proper functions. It also add a new chained stacked method. i(tabsolute_import(tBooltFloat(tRange1di(tcreate_and_buildi(t BarBuilder(tDotGlyph(t ColorAttrtCatAttrt MarkerAttrtsumt categoricaltlinearc K@ső| r%t| tƒ r%tdƒ‚n|dk rq|dkrqt| d<|dks_|dkrqd}|}qqn| } || d<|| d<|| d<|| d <|| d <|| d <|| d <|| d <| | d<| | d<| | d` to render the geometry from the inputs. Args: data (:ref:`userguide_charts_data_types`): the data source for the chart. label (list(str) or str, optional): list of string representing the categories. (Defaults to None) values (str, optional): iterable 2d representing the data series values matrix. color (str or list(str) or `~bkcharts._attributes.ColorAttr`): string color, string column name, list of string columns or a custom `ColorAttr`, which replaces the default `ColorAttr` for the builder. stack (list(str) or str, optional): columns to use for stacking. (Defaults to False, so grouping is assumed) group (list(str) or str, optional): columns to use for grouping. agg (str): how to aggregate the `values`. (Defaults to 'sum', or only label is provided, then performs a `count`) continuous_range(Range1d, optional): Custom continuous_range to be used. (Defaults to None) In addition to the parameters specific to this chart, :ref:`userguide_charts_defaults` are also accepted as keyword parameters. Returns: :class:`Chart`: includes glyph renderers that generate dots Examples: .. bokeh-plot:: :source-position: above from bkcharts import Dot, output_file, show from bokeh.layouts import row # best support is with data in a format that is table-like data = { 'sample': ['1st', '2nd', '1st', '2nd', '1st', '2nd'], 'interpreter': ['python', 'python', 'pypy', 'pypy', 'jython', 'jython'], 'timing': [-2, 5, 12, 40, 22, 30] } # x-axis labels pulled from the interpreter column, stacking labels from sample column dot = Dot(data, values='timing', label='interpreter', stack='sample', agg='mean', title="Python Interpreter Sampling", legend='top_right', plot_width=400) # table-like data results in reconfiguration of the chart with no data manipulation dot2 = Dot(data, values='timing', label=['interpreter', 'sample'], agg='mean', title="Python Interpreters", plot_width=400) output_file("Dot.html") show(row(dot, dot2)) sCcontinuous_range must be an instance of bokeh.models.ranges.Range1dt label_onlyR tmeantcounttlabeltvaluestcolortstacktgrouptaggtxscaletyscaletxgridtygridty_rangeN(t isinstanceRt ValueErrortNonetTrueRt DotBuilder(tdataRRRRRRRRRRtcontinuous_rangetkwR((s<lib/python2.7/site-packages/bkcharts/builders/dot_builder.pytDot#s*:              RcB@sweZdZeddƒZieƒd6eƒd6eƒd6eƒd6eƒd6eƒd6Ze e d d ƒZ e Z RS( s°Produces Dot Glyphs for groups of data. Handles dot plot options to produce one to many dots, which are used to describe the values of aggregated groups of data. tdefaultgđ?RRt line_colorRRtmarkerthelps: Whether to draw a stem from each do to the axis. (t__name__t __module__t__doc__Rt line_alphaRRR tdefault_attributesRtFalsetstemRtglyph(((s<lib/python2.7/site-packages/bkcharts/builders/dot_builder.pyRys        N(R*t __future__Rtbokeh.core.propertiesRRt bokeh.modelsRtbuilderRt bar_builderRtglyphsRt attributesRRR RR-RR#R(((s<lib/python2.7/site-packages/bkcharts/builders/dot_builder.pyts  T