Hi everybody, I have a problem with LinearSegmentedColormap. In the example below (see PS), I make a colormap, and use it to plot an EllipseCollection. My plot is parameterized by a quantity that I have named "large_value". For large_value equal to 257, a blue point is obtained at (x=0.3, y=0.4). But for large_value equal to 258, it becomes black.
This is because of the way LinearSegmentedColormap is working. It has a parameter N which allows to set the "number of colors": http://matplotlib.org/api/colors_api.html#matplotlib.colors.LinearSegmentedColormap It is 256 by default, so if I increase N to a greater value, the point remains blue for large_value equal to 258. Now, my real plot (not this dummy example) is such that I need N to be very large so as to obtain the right colors on my plot, although very few colors are used at the end. However, when N is too large, the plot becomes very slow, and a lot of memory is used; I think because an array is probably built with this size, although in theory there is no need to construct such a complete array. Is there an easy workaround, or have I to study and modify the matplotlib code myself? Thanks, TP PS: Here is the test code: ################## from pylab import * from matplotlib.colors import LinearSegmentedColormap from matplotlib.collections import CircleCollection ioff() large_value = 257 # blue below this value #large_value = 258 # black above this value N = 1e5 # 256 by default cdict = { 'blue': [(0.0, 0.0, 0.0), (2*1/large_value, 1, 1) , (1.0, 1.0, 1.0)] , 'green': [(0.0, 0.0, 0.0), (2*1/large_value, 0, 0) , (1.0, 1.0, 1.0)] , 'red': [(0.0, 0.0, 0.0), (2*1/large_value, 0, 0), (1.0, 1.0, 1.0)] } measures= array([[ 0.2, 0.3, 1], [ 0.3, 0.4, 2], [ 0.5, 0.6, large_value]]) cmap = LinearSegmentedColormap( "cmap foobar" , cdict # , N= N ) ) fig = figure() axes = fig.add_subplot(111) ec = CircleCollection( [80] , offsets = measures[:,:2] , transOffset = axes.transData ) ec.set_array( measures[:,2] ) ec.set_cmap( cmap ) axes.add_collection( ec ) show() ################## ------------------------------------------------------------------------------ Monitor your physical, virtual and cloud infrastructure from a single web console. Get in-depth insight into apps, servers, databases, vmware, SAP, cloud infrastructure, etc. Download 30-day Free Trial. Pricing starts from $795 for 25 servers or applications! http://p.sf.net/sfu/zoho_dev2dev_nov _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
