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  • Committer: Bazaar Package Importer
  • Author(s): Varun Hiremath
  • Date: 2008-12-29 02:34:05 UTC
  • Revision ID: james.westby@ubuntu.com-20081229023405-x7i4kp9mdxzmdnvu
Tags: upstream-3.0.1
Import upstream version 3.0.1

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examples/scales_test.py
 
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#!/usr/bin/env python
 
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"""
 
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Draws several overlapping line plots.
 
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Left-drag pans the plot.
 
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Mousewheel up and down zooms the plot in and out.
 
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Pressing "z" brings up the Zoom Box, and you can click-drag a rectangular region to
 
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zoom.  If you use a sequence of zoom boxes, pressing alt-left-arrow and
 
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alt-right-arrow moves you forwards and backwards through the "zoom history".
 
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Right-click and dragging on the legend allows you to reposition the legend.
 
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Double-clicking on line or scatter plots brings up a traits editor for the plot.
 
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"""
 
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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 time import time
 
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from enthought.chaco.example_support import COLOR_PALETTE
 
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from enthought.enable.example_support import DemoFrame, demo_main
 
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# Enthought library imports
 
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from enthought.enable.api import Window
 
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# Chaco imports
 
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from enthought.chaco.api import create_line_plot, OverlayPlotContainer, PlotLabel, \
 
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                                 create_scatter_plot, Legend, PlotGrid
 
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from enthought.chaco.tools.api import PanTool, ZoomTool, \
 
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                                       LegendTool, TraitsTool
 
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from enthought.chaco.scales.api import CalendarScaleSystem
 
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from enthought.chaco.scales_tick_generator import ScalesTickGenerator
 
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from enthought.chaco.scales_axis import PlotAxis
 
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def add_default_axes(plot, orientation="normal", vtitle="",htitle=""):
 
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    """
 
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    Creates left and bottom axes for a plot.  Assumes that the index is
 
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    horizontal and value is vertical by default; set orientation to
 
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    something other than "normal" if they are flipped.
 
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    """
 
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    if orientation in ("normal", "h"):
 
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        v_mapper = plot.value_mapper
 
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        h_mapper = plot.index_mapper
 
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    else:
 
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        v_mapper = plot.index_mapper
 
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        h_mapper = plot.value_mapper
 
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    left = PlotAxis(orientation='left',
 
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                    title= vtitle,
 
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                    mapper=v_mapper,
 
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                    component=plot)
 
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    bottom = PlotAxis(orientation='bottom',
 
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                      title= htitle,
 
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                      mapper=h_mapper,
 
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                      component=plot)
 
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    plot.underlays.append(left)
 
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    plot.underlays.append(bottom)
 
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    return left, bottom
 
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def add_default_grids(plot, orientation="normal", tick_gen=None):
 
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    """
 
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    Creates horizontal and vertical gridlines for a plot.  Assumes that the
 
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    index is horizontal and value is vertical by default; set orientation to
 
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    something other than "normal" if they are flipped.
 
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    """
 
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    if orientation in ("normal", "h"):
 
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        v_mapper = plot.index_mapper
 
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        h_mapper = plot.value_mapper
 
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    else:
 
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        v_mapper = plot.value_mapper
 
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        h_mapper = plot.index_mapper
 
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    vgrid = PlotGrid(mapper=v_mapper, orientation='vertical',
 
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                     component=plot,
 
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                     line_color="lightgray", line_style="dot",
 
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                     tick_generator = tick_gen)
 
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    hgrid = PlotGrid(mapper=h_mapper, orientation='horizontal',
 
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                     component=plot,
 
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                     line_color="lightgray", line_style="dot",
 
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                     tick_generator = ScalesTickGenerator())
 
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    plot.underlays.append(vgrid)
 
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    plot.underlays.append(hgrid)
 
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    return hgrid, vgrid
 
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class PlotFrame(DemoFrame):
 
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    def _create_window(self):
 
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        container = OverlayPlotContainer(padding = 50, fill_padding = True,
 
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                                         bgcolor = "lightgray", use_backbuffer=True)
 
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        self.container = container
 
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        # Create the initial X-series of data
 
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        numpoints = 100
 
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        low = -5
 
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        high = 15.0
 
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        x = linspace(low, high, numpoints)
 
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        now = time()
 
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        timex = linspace(now, now+7*24*3600, numpoints)
 
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        # Plot some bessel functions
 
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        value_mapper = None
 
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        index_mapper = None
 
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        plots = {}
 
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        for i in range(10):
 
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            y = jn(i, x)
 
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            if i%2 == 1:
 
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                plot = create_line_plot((timex,y), color=tuple(COLOR_PALETTE[i]), width=2.0)
 
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                plot.index.sort_order = "ascending"
 
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            else:
 
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                plot = create_scatter_plot((timex,y), color=tuple(COLOR_PALETTE[i]))
 
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            plot.bgcolor = "white"
 
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            plot.border_visible = True
 
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            if i == 0:
 
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                value_mapper = plot.value_mapper
 
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                index_mapper = plot.index_mapper
 
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                left, bottom = add_default_axes(plot)
 
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                left.tick_generator = ScalesTickGenerator()
 
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                bottom.tick_generator = ScalesTickGenerator(scale=CalendarScaleSystem())
 
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                add_default_grids(plot, tick_gen=bottom.tick_generator)
 
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            else:
 
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                plot.value_mapper = value_mapper
 
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                value_mapper.range.add(plot.value)
 
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                plot.index_mapper = index_mapper
 
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                index_mapper.range.add(plot.index)
 
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            if i==0:
 
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                plot.tools.append(PanTool(plot))
 
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                zoom = ZoomTool(plot, tool_mode="box", always_on=False)
 
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                plot.overlays.append(zoom)
 
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                # Add a legend in the upper right corner, and make it relocatable
 
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                legend = Legend(component=plot, padding=10, align="ur")
 
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                legend.tools.append(LegendTool(legend, drag_button="right"))
 
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                plot.overlays.append(legend)
 
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            container.add(plot)
 
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            plots["Bessel j_%d"%i] = plot
 
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        # Set the list of plots on the legend
 
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        legend.plots = plots
 
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        # Add the title at the top
 
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        container.overlays.append(PlotLabel("Bessel functions",
 
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                                  component=container,
 
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                                  font = "swiss 16",
 
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                                  overlay_position="top"))
 
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        # Add the traits inspector tool to the container
 
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        container.tools.append(TraitsTool(container))
 
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        return Window(self, -1, component=container)
 
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if __name__ == "__main__":
 
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    demo_main(PlotFrame, size=(800,700), title="Simple line plot")
 
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# EOF