On Fri, 2011-03-11 at 17:08 -1000, Eric Firing wrote: > On 03/11/2011 02:54 PM, onet wrote: > > Using matplotlib I try to plot satellite observations, which consists of > > roughly one million patches that are not gridded regularly. > > I first collect the vertices (corner points of the observations) and > > colors and then use PolyCollection and ax.add_collection to add these > > patches to the figure. > > > > On my 64bit Linux machine: > > # 1M patches will use> 4Gb of memory > > > > My question: how can I plot more efficiently and use less memory? > > If your data are on a quadrilateral mesh, as in your example, (or can be > approximately mapped onto such a mesh) then pcolormesh should be very > much more efficient both in time and in memory than making a PolyCollection.
The data I want to plot is not as regular as in the example (this was just to generate lots of non-overlaping patches) but it has different shapes along the orbit of the satellite when projected on the map. Almost square at the equator and rotated near the poles. See example link below from a plot in IDL. http://temis.nl/o3msaf/vaac/gome2/vaac/daily/images/2011/S-O3M_GOME_NAR_02_M02_20110312000254Z_20110313000254Z_N_O_20110313024518Z.AAI_Global.Unfiltered.png But I think my satellite data along an orbit is probably piecewise regular enough try the pcolormesh approach. So thanks for the suggestion! Best regards, Olaf. ------------------------------------------------------------------------------ Colocation vs. Managed Hosting A question and answer guide to determining the best fit for your organization - today and in the future. http://p.sf.net/sfu/internap-sfd2d _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
