Hi,
I would like to plot a density slice scatter plot (when you have lots of points superimposed, it’s very useful). An example from IDL/envi is here: <http://www2.geog.ucl.ac.uk/%7Eplewis/geog2021/practical1/scatter3.gif>
My rustic approach to solving this problem has been to bin all my data points into a 2D array (each point that falls in a given cell adds one to that cell), and then use the c argument in scatterplot to map the color to the number of samples in the corresponding bin. Is there a better way of achieving this, as I need a fair bit of tweaking to get the color scales right?
Thanks!
J
You might try looking at pyplot.hexbin:
http://matplotlib.sourceforge.net/examples/pylab_examples/hexbin_demo.html
Ryan
···
On Tue, May 5, 2009 at 11:47 AM, Jose Gomez-Dans <jgomezdans@…120…287…> wrote:
Hi,
I would like to plot a density slice scatter plot (when you have lots of points superimposed, it’s very useful). An example from IDL/envi is here: <http://www2.geog.ucl.ac.uk/%7Eplewis/geog2021/practical1/scatter3.gif>
My rustic approach to solving this problem has been to bin all my data points into a 2D array (each point that falls in a given cell adds one to that cell), and then use the c argument in scatterplot to map the color to the number of samples in the corresponding bin. Is there a better way of achieving this, as I need a fair bit of tweaking to get the color scales right?
–
Ryan May
Graduate Research Assistant
School of Meteorology
University of Oklahoma
I've also had some luck with scipy.histogramdd and pylab.imshow (you
have to work with the extent and aspect parameters to get the plot you
want). I don't have a standalone demo of this, but if you try it and
have trouble let me know and I'll try to make one.
···
On Tue, May 5, 2009 at 1:04 PM, Ryan May <rmay31@...287...> wrote:
On Tue, May 5, 2009 at 11:47 AM, Jose Gomez-Dans <jgomezdans@...287...> > wrote:
Hi,
I would like to plot a density slice scatter plot (when you have lots of
points superimposed, it's very useful). An example from IDL/envi is here:
<http://www2.geog.ucl.ac.uk/~plewis/geog2021/practical1/scatter3.gif>
My rustic approach to solving this problem has been to bin all my data
points into a 2D array (each point that falls in a given cell adds one to
that cell), and then use the c argument in scatterplot to map the color to
the number of samples in the corresponding bin. Is there a better way of
achieving this, as I need a fair bit of tweaking to get the color scales
right?
You might try looking at pyplot.hexbin:
http://matplotlib.sourceforge.net/examples/pylab_examples/hexbin_demo.html
Ryan
