Hello, I have a 2D numpy masked array of geo-located data -- with some data missing -- that I wish to plot on a map. Basemap provides a nice tool to do this, but I am stumped trying to get the colorscheme I want.
My data are only physically meaningful on land, so I am using Basemap.maskoceans() to mask out "wet" locations (oceans, lakes, etc.) Trouble is, now both water as well as actual missing data show up in the missing data color. I want to have blue water, some other (bright) color for missing data, and a nice-looking color transition (matplotlib.cm.Blues or something similar) for the valid data over land (values from 0 to 50). The Cookbook example at <http://www.scipy.org/Cookbook/Matplotlib/Plotting_Images_with_Special_Values> addresses my problem, but I cannot get it to work. After changing instances of matplotlib.numerix to numpy, I get a long list of exceptions, the last of which is TypeError: __call__() got an unexpected keyword argument 'bytes'. This has to do with sentinelNorm, I think, but I'm not sure how to fix it. Eventually I would like to sub-classify missing data by the type of missing input that caused a missing value, but for now a single missing data color is enough. The code below does almost what I want- I just need to figure out how to make the water blue. I have also messed around with matplotlib.cm.BoundaryNorm to create a colormap/normalization to handle my data, but I am getting hung up initializing the cmap, counting bin edges, etc. I also tacked my test code for that... Any help greatly appreciated! Thanks, Tim -- Timothy W. Hilton PhD Candidate, Department of Meteorology The Pennsylvania State University 503 Walker Building, University Park, PA 16802 hil...@meteo.psu.edu #-------------------------------------------------- # amost right... import numpy as np import numpy.ma as ma from mpl_toolkits.basemap import Basemap, maskoceans import matplotlib.pyplot as plt import matplotlib.colors if __name__=="__main__": # setup a basemap instance & draw a map m_aeqd = Basemap(width=9e5,height=9e5,projection='aeqd', lat_0=28.46,lon_0=360-80.67, resolution='i', area_thresh=1000, rsphere=6371007.181000) col_water='#B9D3EE' #SlateGray2 col_land ='#1C1C1C' m_aeqd.drawmapboundary(fill_color=col_water) # draw coasts and fill continents. m_aeqd.drawcoastlines(linewidth=0.5) m_aeqd.fillcontinents(color=col_land,lake_color=col_water, zorder=0) # create a 100 x 100 pseudodata array with valid data between 0 and 50 and some "missing" data (less than zero) n=100 X = ma.masked_less(np.random.random_integers(-1, 50, (n,n)), 0) plot_mid = np.mean((m_aeqd.llcrnrx, m_aeqd.urcrnrx)) Xu, Xv = np.meshgrid(np.arange(stop=plot_mid + 500*n, start=plot_mid - 500*n, step=1000), np.arange(stop=m_aeqd.urcrnry, start=m_aeqd.urcrnry - 1000*n, step=1000)) Xlon, Xlat = m_aeqd(Xu, Xv, inverse=True) #setup a colormap and plot the data cmap = matplotlib.cm.get_cmap("Blues", 25) #mask oceans ocean_mask = maskoceans(Xlon, Xlat, X) #now I'm stumped how to incorporate oceans_mask into the color map oceans_cmap = matplotlib.colors.ListedColormap((col_land, "#000000"), name="oceans", N=2) cmap.set_bad(color="#FF0000") #show missing vals in bright red m_aeqd.pcolormesh(Xu, Xv, ocean_mask, cmap=cmap) plt.colorbar() #it seems like I could do another pcolormesh call with #ocean_mask.mask and oceans_cmap; I'd need to set the #transparency. It seems like the more elegant solution is to #devise cmap to account for ocean_mask.mask (water) separately #from X.mask (data that are actually missing). I'm not sure how #do that though. ------------------------------------------------------------------------------ Nokia and AT&T present the 2010 Calling All Innovators-North America contest Create new apps & games for the Nokia N8 for consumers in U.S. and Canada $10 million total in prizes - $4M cash, 500 devices, nearly $6M in marketing Develop with Nokia Qt SDK, Web Runtime, or Java and Publish to Ovi Store http://p.sf.net/sfu/nokia-dev2dev _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
