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Viewing changes to examples/demo/tornado.py

  • Committer: Package Import Robot
  • Author(s): Andrew Starr-Bochicchio
  • Date: 2014-06-01 17:04:08 UTC
  • mfrom: (7.2.5 sid)
  • Revision ID: package-import@ubuntu.com-20140601170408-m86xvdjd83a4qon0
Tags: 4.4.1-1ubuntu1
* Merge from Debian unstable. Remaining Ubuntu changes:
 - Let the binary-predeb target work on the usr/lib/python* directory
   as we don't have usr/share/pyshared anymore.

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examples/demo/tornado.py
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""" Tornado plot example from Brennan Williams """
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# Major library imports
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from numpy import linspace, pi, sin, ones
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# Enthought library imports
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from enable.api import Component, ComponentEditor
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from traits.api import HasTraits, Instance
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from traitsui.api import Item, View
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# Chaco imports
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from chaco.api import ArrayDataSource, BarPlot, DataRange1D, LabelAxis, \
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                      LinearMapper, OverlayPlotContainer, PlotAxis
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from chaco.example_support import COLOR_PALETTE
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class PlotExample(HasTraits):
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    plot = Instance(Component)
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    traits_view = View(Item('plot', editor=ComponentEditor(), show_label=False),
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                    resizable=True, title="Tornado Plot",
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                    width=800, height=600
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                    )
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    def _plot_default(self):
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        container = OverlayPlotContainer(bgcolor = "white")
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        plots = self._make_curves()
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        for plot in plots:
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            plot.padding = 60
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            container.add(plot)
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        bottom_axis = PlotAxis(plot, orientation='bottom')
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        label_list=['var a', 'var b', 'var c', 'var d', 'var e', 'var f',
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                    'var g', 'var h', 'var i']
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        vertical_axis = LabelAxis(plot, orientation='left',
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                                title='Categories',
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                                positions = range(1, 10),
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                                labels=label_list)
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        vertical2_axis = LabelAxis(plot, orientation='right',
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                                   positions = range(1, 10),
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                                   labels=label_list)
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        plot.underlays.append(vertical_axis)
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        plot.underlays.append(vertical2_axis)
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        plot.underlays.append(bottom_axis)
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        return container
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    def _get_points(self):
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        index = linspace(pi/4, 3*pi/2, 9)
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        data = sin(index) + 2
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        return (range(1, 10), data)
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    def _make_curves(self):
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        (index_points, value_points) = self._get_points()
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        size = len(index_points)
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        middle_value=2500000.0
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        mid_values=middle_value*ones(size)
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        low_values=mid_values-10000.0*value_points
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        high_values=mid_values+20000.0*value_points
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        idx = ArrayDataSource(index_points)
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        vals = ArrayDataSource(low_values, sort_order="none")
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        idx2 = ArrayDataSource(index_points)
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        vals2 = ArrayDataSource(high_values, sort_order="none")
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        starting_vals = ArrayDataSource(mid_values, sort_order="none")
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        # Create the index range
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        index_range = DataRange1D(idx, low=0.5, high=9.5)
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        index_mapper = LinearMapper(range=index_range)
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        # Create the value range
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        value_range = DataRange1D(vals, vals2, low_setting='auto',
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                                  high_setting='auto', tight_bounds=False)
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        value_mapper = LinearMapper(range=value_range,tight_bounds=False)
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        # Create the plot
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        plot1 = BarPlot(index=idx, value=vals,
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                        value_mapper=value_mapper,
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                        index_mapper=index_mapper,
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                        starting_value=starting_vals,
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                        line_color='black',
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                        orientation='v',
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                        fill_color=tuple(COLOR_PALETTE[6]),
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                        bar_width=0.8, antialias=False)
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        plot2 = BarPlot(index=idx2, value=vals2,
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                        value_mapper=value_mapper,
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                        index_mapper=index_mapper,
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                        starting_value=starting_vals,
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                        line_color='black',
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                        orientation='v',
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                        fill_color=tuple(COLOR_PALETTE[1]),
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                        bar_width=0.8, antialias=False)
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        return [plot1, plot2]
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demo = PlotExample()
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if __name__ == "__main__":
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    demo.configure_traits()