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Bernhard,

Are you sure you want a colorbar with lines and not a legend?

A colorbar with lines only, matching a LineCollection, can be done with 
  the facilities in mpl's colorbar.py module; you might take a look at 
the code in that module to see how it is being done in the line contour 
case. Note that ColorbarBase has a method, add_lines, for this. I'm 
sorry I don't have time to be more specific now, though.

Eric

Bernhard Voigt wrote:
> Dear all!
> 
> I'm folowing the line_collection2.py example to create a LineCollection 
> plot with a colorbar.
> How can I force the colorbar to show distinct lines like it does in 
> contour plots for a LineCollection plot?
> 
> Thanks! Bernhard

Dear all!

I'm folowing the line_collection2.py example to create a LineCollection plot
with a colorbar.
How can I force the colorbar to show distinct lines like it does in contour
plots for a LineCollection plot?

Thanks! Bernhard

Hi!

You could also use the bar method and do the histogram with numpy:

import numpy as n
import pylab as p

foo = n.random.normal(size=100)
p.hist(foo, 20)
p.twinx()
counts, bins = n.histogram(foo, 20)
counts = counts.astype(float)/len(foo)
width = (bins[1]-bins[0]) * .9
p.bar(bins ,counts, width=width, fc='r')

Cheers! Bernhard

On Fri, Feb 22, 2008 at 4:08 PM, Auré Gourrier <aur...@ya...>
wrote:

> Hi all,
>
> In my latest post, I wanted to use the mpl.hist() function in a different
> way, i.e.:
>
> x = datalist
> bins= 100
> hist(x,bins,normed=0)    #returns a tupple (n,bins,patches)
>
> Instead of ploting the number of counts n, I wanted to plot the relative
> percentage of counts, i.e. n/len(x). I can't really use the option
> normed=1 which returns n/(len(x)*dbin). In the axes.py module, this would
> simply mean adding an argument e.g. relpercent = 1. I added the code line
> to show how this could be done (in major cap). If this is useful, how could
> it be modified in the distribution ?
>
>
>     def hist(self, x, bins=10, RELPERCENT = 1, normed=0, bottom=None,
>              align='edge', orientation='vertical', width=None,
>              log=False, **kwargs):
>         """
>
>         if not self._hold: self.cla()
>         n, bins = npy.histogram(x, bins, range=None, normed=normed)
>         IF NOT NORMED AND RELPERCENT: N = N/FLOAT(LEN(X))
>         if width is None: width = 0.9*(bins[1]-bins[0])
>         if orientation == 'horizontal':
>             patches = self.barh(bins, n, height=width, left=bottom,
>                                 align=align, log=log)
>         elif orientation == 'vertical':
>             patches = self.bar(bins, n, width=width, bottom=bottom,
>                                 align=align, log=log)
>         else:
>             raise ValueError, 'invalid orientation: %s' % orientation
>         for p in patches:
>             p.update(kwargs)
>         return n, bins, cbook.silent_list('Patch', patches)
>
>
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