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Viewing changes to examples/demo/multi_line_plot.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/multi_line_plot.py
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import numpy as np
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from chaco.api import LinearMapper, Plot, ArrayDataSource, DataRange1D
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from chaco.multi_array_data_source import MultiArrayDataSource
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from chaco.multi_line_plot import MultiLinePlot
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from enable.api import ComponentEditor
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from traits.api import Instance, HasTraits
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from traitsui.api import View, Item
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class MyPlot(HasTraits):
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    """ Displays a plot with a few buttons to control which overlay
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        to display
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    """
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    plot = Instance(Plot)
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    traits_view = View(Item('plot', editor=ComponentEditor(), show_label=False),
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                        resizable=True)
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    def __init__(self, x_index, y_index, data, **kw):
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        super(MyPlot, self).__init__(**kw)
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        # Create the data source for the MultiLinePlot.
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        ds = MultiArrayDataSource(data=data)
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        xs = ArrayDataSource(x_index, sort_order='ascending')
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        xrange = DataRange1D()
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        xrange.add(xs)
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        ys = ArrayDataSource(y_index, sort_order='ascending')
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        yrange = DataRange1D()
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        yrange.add(ys)
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        mlp = MultiLinePlot(
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                        index = xs,
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                        yindex = ys,
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                        index_mapper = LinearMapper(range=xrange),
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                        value_mapper = LinearMapper(range=yrange),
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                        value=ds,
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                        global_max = np.nanmax(data),
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                        global_min = np.nanmin(data),
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                        **kw)
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        self.plot = Plot()
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        self.plot.add(mlp)
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x_index = np.arange(0,100, 1)
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y_index = np.arange(0,1000, 10)
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data = np.sin(np.arange(0,x_index.size*y_index.size))
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# add a random chunk of nan values
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data[1532:1588] = np.nan
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data = data.reshape(x_index.size, y_index.size)
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my_plot = MyPlot(x_index, y_index, data)
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my_plot.configure_traits()