On 8/20/12 8:21 PM, Scott Henderson wrote: > On Mon 20 Aug 2012 06:29:01 PM EDT, Jeff Whitaker wrote: >> On 8/20/12 4:41 PM, Scott Henderson wrote: >>> I'm having trouble with transform_scalar() and imshow() with basemap. >>> Essential I have data from satellite tracks that are either smaller >>> or larger than the map extent, so I don't want to use >>> Basemap.imshow() which sets the 'extent' keyword automatically. >>> >>> I tried following the following suggestion, but I can't get things to >>> line up.. >>> http://comments.gmane.org/gmane.comp.python.matplotlib.general/25085 >>> >>> I suspect I've done something wrong in the code below?: >> >> Scott: If you use the pcolormesh or contourf Basemap methods (instead >> of imshow), you can specify the map projection coordinates of your >> data and it will be plotted correctly (whether or not it covers the >> whole map projection region). >> >> -Jeff >>> >>> >>> # ------------------------------- >>> from mpl_toolkits.basemap import Basemap >>> import matplotlib.pyplot as plt >>> >>> LL = (-68, -26) >>> UR = (-66, -21) >>> bmap = Basemap(projection='merc', >>> llcrnrlat=LL[1], >>> urcrnrlat=UR[1], >>> llcrnrlon=LL[0], >>> urcrnrlon=UR[0], >>> resolution='i', >>> suppress_ticks=False, >>> ax=ax) >>> bmap.drawcountries(linewidth=1) >>> >>> # Overlay image with extents that don't match map boundaries >>> nLon, nLat = image.shape >>> LL = (-69.915, -31.161) >>> UR = (-65.075, -17.334) >>> dy = -0.006666664 >>> lats = UR[1] + dy * np.arange(nLat) >>> extent = (LL[0], UR[0], LL[1], UR[1]) >>> nx = nLon; ny = nLat >>> image_xy = bmap.transform_scalar(image, lons, lats[::-1], nx, ny) >>> x, y = bmap(extent[:2],extent[2:]) >>> extent_xy = (x[0], x[1], y[0], y[1]) >>> im = plt.imshow(image_xy, extent=extent_xy) >>> >>> >>> >>> -- >>> --------------- >>> Scott T. Henderson >>> http://www.geo.cornell.edu/eas/gstudent/sth54/contact.html >>> >>> >>> ------------------------------------------------------------------------------ >>> >>> >>> Live Security Virtual Conference >>> Exclusive live event will cover all the ways today's security and >>> threat landscape has changed and how IT managers can respond. >>> Discussions >>> will include endpoint security, mobile security and the latest in >>> malware >>> threats.http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ >>> >>> >>> _______________________________________________ >>> Matplotlib-users mailing list >>> Matplotlib-users@lists.sourceforge.net >>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users >> >> >> -- >> Jeffrey S. Whitaker Phone : (303)497-6313 >> Meteorologist FAX : (303)497-6449 >> NOAA/OAR/PSD R/PSD1 Email :jeffrey.s.whita...@noaa.gov >> 325 Broadway Office : Skaggs Research Cntr 1D-113 >> Boulder, CO, USA 80303-3328 Web :http://tinyurl.com/5telg > > Thanks Jeff, > > pcolormesh seems to get the georeferencing correct. Why is it that > imshow doesn't work? The trouble with pcolormesh is that it's much > slower, the file sizes get bigger and when zooming into detailed > regions the pixels edges show up even when I set edgecolors='None'. > I've attached a few screenshots for comparison.
Scott: That's weird - I don't know why the edges show. The only thing you're getting with imshow is interpolation. To use imshow, you need to have a grid that exactly fits the map projection region. You could do this with transform_scalar using the keyword masked=True, which will assign missing values to grid points outside the range of the input grid. When you plot with imshow, these areas should just show up as transparent. -Jeff > > # New version: > # ------------------- > data_xy, x, y = bmap.transform_scalar(data[::-1], lons, lats[::-1], > nx, ny, returnxy=True) > data_xym = np.ma.array(data_xy, mask=np.isnan(data_xy)) > im = bmap.pcolormesh(x,y,data_xym, > shading='flat', #'gouraud' > edgecolors='None', > alpha=alpha, > vmin=cmin, > vmax=cmax) > plt.colorbar(im) > > > # Different figures attached > > > > -- > --------------- > Scott T. Henderson > http://www.geo.cornell.edu/eas/gstudent/sth54/contact.html > ------------------------------------------------------------------------------ Live Security Virtual Conference Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
