Greetings all, I rotate a vector field and than I tried to interpolate it to a new grid using griddata.
CODE: x_grid_unique = unique(x_grid) y_grid_unique = unique(y_grid) x_meshgrid, y_meshgrid = meshgrid(x_grid_unique, y_grid_unique) x_rot_meshgrid = reshape(x_rot, [ len(x_meshgrid[:, 0]), len(x_meshgrid[0, :])] ) y_rot_meshgrid = reshape(y_rot, [ len(x_meshgrid[:, 0]), len(x_meshgrid[0, :])] ) u_rot_meshgrid = reshape(u_rot, [ len(x_meshgrid[:, 0]), len(x_meshgrid[0, :])] ) v_rot_meshgrid = reshape(v_rot, [ len(x_meshgrid[:, 0]), len(x_meshgrid[0, :])] ) u_interpolate = griddata(x_rot, y_rot, u_rot, x_rot_meshgrid, y_rot_meshgrid) v_interpolate = griddata(x_rot, y_rot, v_rot, x_rot_meshgrid, y_rot_meshgrid) I unfortunately griddata returns some nan (It seems that there are multiple occurrences of the same [X,Y] pair in the data). In matlab you can use griddata with additional options e.g. ru = griddata(nx,ny,nu,rx,ry,'linear', {'QJ'}) to fix this, but this seems to be not possible using the griddata function in matplotlib. Is there any other way to avoid a return of nan? For any help many thanks in advance Andreas -- View this message in context: http://www.nabble.com/griddata-returns-nan-tp24537481p24537481.html Sent from the matplotlib - users mailing list archive at Nabble.com. ------------------------------------------------------------------------------ Enter the BlackBerry Developer Challenge This is your chance to win up to $100,000 in prizes! For a limited time, vendors submitting new applications to BlackBerry App World(TM) will have the opportunity to enter the BlackBerry Developer Challenge. See full prize details at: http://p.sf.net/sfu/Challenge _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users