Attached is a very simple example that shows how to do something similar
to scatterhist in matplotlib
Manuel
per freem wrote:
> hello,
>
> is there a way to make a 2d scatter plot that includes (outside the axes)
> histograms of the marginals of the two variables? like the matlab function
> 'scatterhist'. see this for an example:
>
> http://www.mathworks.com/access/helpdesk/help/toolbox/stats/index.html?/access/helpdesk/help/toolbox/stats/scatterhist.html
>
> ideally i'd like the histograms outside the scatter plot to also have axes
> so that the height of each histogram bar will be interpretable.
> i understand that there's no command for this - but how can i construct it?
> i would not mind writing code to do this... if it's possible. right now
> this is the only thing keeping me from switching from matlab to matplotlib
> exclusively since i use these graphs a lot
>
> thank you
>
>
>
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import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import NullFormatter
x = np.random.randn(1000)
y = np.random.randn(1000)
nullfmt = NullFormatter() # no labels
left, width = 0.1, 0.65
bottom, height = 0.1, 0.65
bottom_h = left_h = left+width+0.02
rect1 = [left, bottom, width, height]
rect2 = [left, bottom_h, width, 0.2]
rect3 = [left_h, bottom, 0.2, height]
# start with a rectangular figure
#fig = plt.Figure( (8,8) )
axScatter = plt.axes(rect1)
axHistx = plt.axes(rect2)#, sharex=axScatter)
axHisty = plt.axes(rect3)#, sharey=axScatter)
axHistx.xaxis.set_major_formatter(nullfmt)
axHisty.yaxis.set_major_formatter(nullfmt)
axScatter.scatter(x,y)
bins = np.linspace(-4,4,21)
axHistx.hist(x, bins=bins)
axHisty.hist(x, bins=bins, orientation='horizontal')
axHistx.set_xlim( axScatter.get_xlim() )
axHisty.set_ylim( axScatter.get_ylim() )
plt.show()
------------------------------------------------------------------------------
Open Source Business Conference (OSBC), March 24-25, 2009, San Francisco, CA
-OSBC tackles the biggest issue in open source: Open Sourcing the Enterprise
-Strategies to boost innovation and cut costs with open source participation
-Receive a $600 discount off the registration fee with the source code: SFAD
http://p.sf.net/sfu/XcvMzF8H
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