Howdy All, I'm hoping someone can give me a quick solution to a couple of problems. I think I'm just missing an idea or two.
Problem 1: I'm creating a map using the 'llc' lambert conformal projection and pcolormesh. Here is a sampling of the source. self.m = Basemap(lat_0=self.lat_0,lon_0=self.lon_0,projection='lcc', width=store_comp.base_width,height=store_comp.base_height, resolution='i',area_thresh=100000) self.fig = plt.figure(figsize=(width,hieght),frameon=True) self.ax = self.fig.add_subplot(111) self.xx, self.yy = self.m(*numpy.meshgrid(self.x,self.y)) self.the_image = self.m.pcolormesh(self.xx,self.yy,z,edgecolors='None',cmap=self.color_scheme) The problem I have is two fold: 1) the map segment isn't fully shown unless I drive up the width and size in basemap so that the map floats in a lot of whitespace. 2) when I use drawparallels etc. the lines extend beyond the map in a way that I wish they wouldn't. See map1 in http://gallery.me.com/ohtinsel#100149 Problem 2: This problem comes up when I use contourf on the same data, which occupies only a limited domain (i.e., there is no data outside the lat/lon bounds shown in map1). Here the contours spill out onto the plot in a way that I wish they wound't (some of the source is below). See map2 in http://gallery.me.com/ohtinsel#100149 self.x = numpy.where(self.x < 180.0,self.x,self.x-360.0) scale = 1 dx = self.width/((len(self.x)-1)*scale) dy = self.height/((len(self.y)-1)*scale) nx = int((self.m.xmax-self.m.xmin)/dx)+1 ny = int((self.m.ymax-self.m.ymin)/dy)+1 self.z,self.xx,self.yy = self.m.transform_scalar( self.z,self.x,self.y,nx,ny,returnxy=True) self.the_image = self.m.contour(self.xx,self.yy,self.z,colors='k') self.the_image = self.m.contourf(self.xx,self.yy,self.z, cmap=self.color_scheme,extend=self.extend) No doubt I'm doing something wrong and probably obvious, but I can't figure it out. Suggestions are much appreciated. Mike ------------------------------------------------------------------------------ Download Intel® Parallel Studio Eval Try the new software tools for yourself. Speed compiling, find bugs proactively, and fine-tune applications for parallel performance. See why Intel Parallel Studio got high marks during beta. http://p.sf.net/sfu/intel-sw-dev _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users