On Tue, Aug 4, 2009 at 11:50 AM, John Hunter <jdh2...@gmail.com> wrote:
> On Mon, Aug 3, 2009 at 11:38 PM, Gökhan Sever<gokhanse...@gmail.com>
> wrote:
> > Hello,
> >
> > I was wondering if it is possible to hide some data on figures using a
> say
> > right click option to any of the legend entry and make it temporarily
> > hidden/visible to better analyse the rest of the data?
> >
> > Check this screenshot for example:
> >
> > http://img25.imageshack.us/img25/9427/datahiding.png
> >
> > The red data clutters the rest of the figure, and I would like to be able
> to
> > hide it temporarily so that I can investigate the other two relations
> more
> > easily.
> >
> > Any ideas? or alternative solutions?
>
> It's a nice idea, and should be doable with the pick interface we have
> for all mpl artists. Unfortunately, there were a few problems in the
> legend implementation which blocked the pick events from hitting the
> proxy lines they contained. I just made a few changes to mpl svn HEAD
> to support this, and added a new example.
>
> examples/event_handling/legend_picking.py
>
> which I'll include below. JJ could you review the changes to legend.py?
>
> Instructions for checking out svn are at::
>
>
> http://matplotlib.sourceforge.net/faq/installing_faq.html#install-from-svn
>
> Here is the example:
>
> """
> Enable picking on the legend to toggle the legended line on and off
> """
> import numpy as np
> import matplotlib.pyplot as plt
>
> t = np.arange(0.0, 0.2, 0.1)
> y1 = 2*np.sin(2*np.pi*t)
> y2 = 4*np.sin(2*np.pi*2*t)
>
> fig = plt.figure()
> ax = fig.add_subplot(111)
>
> line1, = ax.plot(t, y1, lw=2, color='red', label='1 hz')
> line2, = ax.plot(t, y2, lw=2, color='blue', label='2 hz')
>
> leg = ax.legend(loc='upper left', fancybox=True, shadow=True)
> leg.get_frame().set_alpha(0.4)
>
>
> lines = [line1, line2]
> lined = dict()
> for legline, realine in zip(leg.get_lines(), lines):
> legline.set_picker(5) # 5 pts tolerance
> lined[legline] = realine
>
> def onpick(event):
> legline = event.artist
> realline = lined[legline]
> vis = realline.get_visible()
> realline.set_visible(not vis)
> fig.canvas.draw()
>
> fig.canvas.mpl_connect('pick_event', onpick)
>
> plt.show()
>
Excellent John. Right what I was seeking for. This will help me a lot to
view and analyze my crowded plots.
Thanks also Ryan for the additional correction.
I have a little question on the code:
What is the purpose of using "commas" after line1 and line2 names?
I see a little change when I typed them in Ipython, however not exactly sure
the real reasoning behind this.
In [4]: lines = ax.plot(t, y1, lw=2, color='red', label='1 hz')
In [5]: lines
Out[5]: [<matplotlib.lines.Line2D object at 0xabce76c>]
In [6]: lines, = ax.plot(t, y1, lw=2, color='red', label='1 hz')
In [7]: lines
Out[7]: <matplotlib.lines.Line2D object at 0xabceaec>
Thanks.
--
Gökhan
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