On 4/5/10 7:25 AM, Will Hewson wrote:
I should perhaps of explained my code (included in top post) a little better, the values in my attached file aren't on a regular grid to start with, I do a little bit of juggling as follows to get them into a regular grid:I'm firstly setting up my 2D grid of 0.5 degree lat lons, followed by identically sized grids of zeros for the data bin, and mean divisors: x = np.arange(-180, 180, 0.5); y = np.arange(-90, 90, 0.5) grid_lon, grid_lat = np.meshgrid(x,y) #regularly spaced 2D grid n_vals = np.zeros((360,720)) #mean divisor dat = np.zeros((360,720)) #2D grid of zeros I'm then taking my input data (e.g. the .plt file attached), and rounding the lat lons to the nearest 0 or 0.5: lon = (np.around(lon*2))/2 #round to nearest .0 or 0.5 lat = (np.around(lat*2))/2 #round to nearest .0 or 0.5 Then for each row in my input file where Z is greater than 0, I'm adding the n'th Z value to its corresponding position in the dat zeros array, and keeping a count of how many values are going into each cell in the mean divisor array: j=0 for i in slcol: if lon[j]< 0: grid_lon_ind = 360+(lon[j]*2) grid_lat_ind = 180+(lat[j]*2) else: grid_lon_ind = 360-(lon[j]*2) grid_lat_ind = 180+(lat[j]*2) if i> 0: dat[grid_lat_ind, grid_lon_ind] += i #add i'th value n_vals[grid_lat_ind, grid_lon_ind] += 1 #increase cell counter by 1 for each extra value j+=1 Finally the new dat array is divided by the mean divisor array to give me my mean Z values: dat = np.nan_to_num(dat/n_vals) I've done it this way as opposed to interpolating *properly* in order to (for instance) stop the values bleeding away from the edges of the satellite swath. Cheers, Will.
Will: I made some slight modifications to your original script and it works fine with the ortho projection using either contourf on the original lat/lon grid or pcolormesh on the interpolated map projection grid.
-Jeff
Jeff Whitaker wrote:On 4/5/10 4:16 AM, Will Hewson wrote:Hey Jeff, It's somewhere between the two - the original satellite swath is converted to a regular 0.5 degree grid by truncating, binning, and averaging each point's lons and lats over the top of a 720 x 360 np.zeros array. the plotting still works fine for non ortho/ hemispherical projections, and I've no big problem with using global projections for the time being. Thanks for your help in the meantime anyway. Cheers, Will.Will: If it's a regular 0.5 degree lat/lon grid, it should work in transform_scalar. However, I don't see how to read the data in your test.plt file into a regular 360x720 grid. It seems to only contain the points in the swath with nonzero values. -JeffJeff Whitaker wrote:On 4/4/10 11:06 AM, Will Hewson wrote:Hi again Jeff et al... I've had a play around with the extra few lines of code - on paper this seems like it should solve the problems I'm experiencing. However, an error's being thrown up by the transform scalar function, as my lons and lats won't necessarily be increasing. The data I'm plotting is satellite data and so at the beginning and end of the orbit file lats go over the pole from 90 to -90, with a similar problem for the lons - whereby the data is taken across the satellite track. I've thought about sorting the data before passing it to transform_scalar but I'm always going to be left with the problem in either lats or lons. I've uploaded the file I'm currently working with this time. It's three columns of lons, lats and z values. Once again, many thanks for your help. Will. http://old.nabble.com/file/p28133659/test.plt test.pltWill: Is it a regular lat/lon grid or a satellite swath? If it's the latter, you can't use my solution. -Jeff ------------------------------------------------------------------------------ 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------------------------------------------------------------------------------ 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
-- 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
hewson.py
Description: application/python
------------------------------------------------------------------------------ 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
