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Displays multiple data sets with different scales in the same plot area,
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and shows a separate, distinct, axis for each plot.
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Interactions are the same as in multiaxis.py
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# Major library imports
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from numpy import linspace
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from scipy.special import jn
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from chaco.example_support import COLOR_PALETTE
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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, Group, View
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from chaco.api import HPlotContainer, \
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OverlayPlotContainer, PlotAxis, PlotGrid
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from chaco.tools.api import BroadcasterTool, PanTool
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from chaco.api import create_line_plot
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#===============================================================================
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# # Create the Chaco plot.
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#===============================================================================
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def _create_plot_component():
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# Create some x-y data series to plot
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plot_area = OverlayPlotContainer(border_visible=True)
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container = HPlotContainer(padding=50, bgcolor="transparent")
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#container.spacing = 15
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x = linspace(-2.0, 10.0, 100)
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color = tuple(COLOR_PALETTE[i])
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renderer = create_line_plot((x, y), color=color)
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plot_area.add(renderer)
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#plot_area.padding_left = 20
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axis = PlotAxis(orientation="left", resizable="v",
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mapper = renderer.y_mapper,
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axis_line_color=color,
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tick_label_color=color,
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bgcolor="transparent",
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border_visible = True,)
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axis.padding_left = 10
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axis.padding_right = 10
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# Use the last plot's X mapper to create an X axis and a
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x_axis = PlotAxis(orientation="bottom", component=renderer,
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mapper=renderer.x_mapper)
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renderer.overlays.append(x_axis)
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grid = PlotGrid(mapper=renderer.x_mapper, orientation="vertical",
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line_color="lightgray", line_style="dot")
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renderer.underlays.append(grid)
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# Add the plot_area to the horizontal container
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container.add(plot_area)
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# Attach some tools to the plot
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broadcaster = BroadcasterTool()
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for plot in plot_area.components:
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broadcaster.tools.append(PanTool(plot))
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# Attach the broadcaster to one of the plots. The choice of which
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# plot doesn't really matter, as long as one of them has a reference
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# to the tool and will hand events to it.
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plot.tools.append(broadcaster)
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#===============================================================================
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# Attributes to use for the plot view.
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#===============================================================================
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# # Demo class that is used by the demo.py application.
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#===============================================================================
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class Demo(HasTraits):
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plot = Instance(Component)
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Item('plot', editor=ComponentEditor(size=size),
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orientation = "vertical"),
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resizable=True, title=title,
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width=size[0], height=size[1]
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def _plot_default(self):
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return _create_plot_component()
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if __name__ == "__main__":
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demo.configure_traits()
added
removed
examples/demo/stacked_axis.py
