reprojecting a Gaussian Grid to a regular grid [SOLVED]

I guess sometimes its best to dig into ipython. I apparently
misunderstood interp, but it seems it doesn't need to be used only
with grids created from a Basemap instance. I created the following
function which accomplishes my goals (I know this shouldn't all be in
one function, I'll look into making it more 'general' as a next step).
If I get around to cleaning it up, I'll repost. --john

def create_land_veg_mask():
    """ Process to convert Gaussian grid data to lat lon (0.5 deg)
         for gridded data inside the grib2 ncep files available here:


    from mpl_toolkits.basemap import interp, shiftgrid
    import pygrib

    def interp_shift(data,lslons,lslats,lonsg,latsg,lons):
        dataout = interp(data.values,lslons[0,:],lslats[:,0],lonsg,latsg)
        data_shft,lon_shft = shiftgrid(-180,dataout.T,lons)
        return lon_shft, lats, data_shft

    grbs ='gfs.t00z.sfluxgrbf03.grib2')
    lsmask ='Land-sea mask')[0]
    vegtypes ='Vegetation Type')[0]
    lslats,lslons = lsmask.latlons() #same for vegtypes
    reg_lons = np.arange(-360,0,0.5)
    reg_lats = np.arange(-90,90,0.5)
    latsg,lonsg = np.meshgrid(reg_lats,reg_lons)

    lonsout, lats, vegout =
    lonsout, lats, lsmaskout =

    return lonsout,lats,vegout,lsmaskout