DKRZ Python example read GRIB file using PyNIOΒΆ

Example script:

#
#  File:
#    read_GRIB_with_PyNIO.py
#
#  Synopsis:
#    Illustrates how to read a GRIB file with PyNIO.
#
#  Description:
#    This example shows how to read a GRIB file using PyNIO.
#
#  Author:
#    Karin Meier-Fleischer
#
#  Date of initial publication:
#    September, 2019
#
'''
  PyEarthScience:   read_GRIB_with_PyNIO.py

  Description:
    Demonstrate the use of PyNIO to open and read the content of
    a GRIB file.

  - PyNIO
  - GRIB

  2019-01-22  kmf
'''

from __future__ import print_function
import Ngl,Nio
import numpy as np

#-----------------------------------------------------------------------
#-- Function: main
#-----------------------------------------------------------------------
def main():

    #-- data directory and file name, we use an example GRIB file from the NCL package
    ncarg  = Ngl.pynglpath("data")
    fname  = ncarg+'/grb/MET9_IR108_cosmode_0909210000.grb2'

    #--  open file
    ds = Nio.open_file(fname, "r")

    print('------------------------------------------------------')
    print()
    print('--> ds:              ', ds)
    print()

    #-- print the size and shape of the variable
    print('------------------------------------------------------')
    print()
    print('--> ds.dimensions            ',ds.dimensions)
    print()

    #-- print file variables
    print('------------------------------------------------------')
    print()
    print('--> file variables:  ', ds.variables)
    print()

    #-- read variable 'SBTMP_P31_GRLL0_I207'
    var  = ds.variables['SBTMP_P31_GRLL0_I207']

    #-- print variable information
    print('------------------------------------------------------')
    print()
    print('--> var')
    print()
    print(var)
    print()

    #-- print the dimension names, size and shape of the variable
    dimnames = var.dimensions

    print('------------------------------------------------------')
    print()
    print('--> var.dimensions           ',var.dimensions)

    #-- print the size and shape of the variable
    print('------------------------------------------------------')
    print()
    print('--> var.size           ',var.size)
    print('--> var.shape          ',var.shape)
    print()

    #-- read variables lat and lon
    lat  = ds.variables['gridlat_0']
    lon  = ds.variables['gridlon_0']

    #-- print the size of the coordinates
    nlat = len(lat[0])
    nlon = len(lat[1])

    print('------------------------------------------------------')
    print()
    print('--> lat:               (%4d,%4d)' % (lat.shape[0],lat.shape[1]))
    print('--> lon:               (%4d,%4d)' % (lon.shape[0],lon.shape[1]))
    print()

    #-- print the minimum and maximum of lat and lon
    print('------------------------------------------------------')
    print()
    print('--> lat min             %12.6f' % np.min(lat))
    print('--> lat max             %12.6f' % np.max(lat))
    print('--> lon min             %12.6f' % np.min(lon))
    print('--> lon max             %12.6f' % np.max(lon))
    print()

    #-- get the attribute content
    lat_spol = lat.attributes['Latitude_of_southern_pole']
    lon_spol = lat.attributes['Longitude_of_southern_pole']

    #-- retrieve the name of the coordinates lat/lon and the values of
    #-- the shape of the coordinates
    dimslat  = dimnames[0]
    shapelat = lat.shape
    dimslon  = dimnames[1]
    shapelon = lon.shape
    nrlat    = shapelat
    nrlon    = shapelon

    print('------------------------------------------------------')
    print()
    print('--> dimslat: ',dimslat, '  dimslon: ',dimslon,'  nrlat: ',nrlat,'  nrlon: ',nrlon)
    print()

    #-- print the variable attributes
    print('------------------------------------------------------')
    print()
    print('--> variable attributes: ',var.attributes)
    print()

    #-- print the variable values
    print('------------------------------------------------------')
    print()
    print('--> values            ')
    print()
    print(var[:])
    print()

    #-- print the type of the variable SBTMP_P31_GRLL0_I207 (DataArray)
    print('------------------------------------------------------')
    print()
    print('--> type(var)         ',type(var))
    print()

    #-- print the type of the variable SBTMP_P31_GRLL0_I207 values (numpy.ndarray)
    print('------------------------------------------------------')
    print()
    print('--> type(var[:])  ',type(var[:]))
    print()

    #-- select variable SBTMP_P31_GRLL0_I207 from dataset
    print('------------------------------------------------------')
    print()
    print('--> dataset variable SBTMP_P31_GRLL0_I207')
    print()
    print(ds.variables['SBTMP_P31_GRLL0_I207'][:])
    print()

    #-- select variable SBTMP_P31_GRLL0_I207 from dataset, lat index 1 and lon index 2
    print('------------------------------------------------------')
    print()
    print('--> dataset variable SBTMP_P31_GRLL0_I207 select data indexing lat=1 and lon=2')
    print()
    print(ds.variables['SBTMP_P31_GRLL0_I207'][1,2])
    print()

    #-- select a sub-region (slice) using lat/lon array indexing
    print('------------------------------------------------------')
    print()
    print('--> select sub-region')
    print()
    print(ds.variables['SBTMP_P31_GRLL0_I207'][0:10,5:25])
    print()

    #-- print median values of variable SBTMP_P31_GRLL0_I207 of dataset
    print('------------------------------------------------------')
    print()
    print('--> variable SBTMP_P31_GRLL0_I207 median')
    print()
    print(np.median(ds.variables['SBTMP_P31_GRLL0_I207']))
    print()

    #-- compute the means of the variable SBTMP_P31_GRLL0_I207 of the dataset
    print('------------------------------------------------------')
    print()
    print('--> variable SBTMP_P31_GRLL0_I207 mean')
    print()
    mean = np.mean(ds.variables['SBTMP_P31_GRLL0_I207'])
    print(mean)
    print()


if __name__ == '__main__':
    main()