#!/usr/bin/env python3
# -*- coding: utf-8 -*-

from __future__ import print_function, division, unicode_literals, absolute_import

__doc__ = """
Example for CliMAF access to data organized according to CMIP5 DRS such as :
...../CMIP5/output1/CNRM-CERFACS/CNRM-CM5/1pctCO2/mon/atmos/Amon/r1i1p1/v20110701/clivi/clivi_Amon_CNRM-CM5_1pctCO2_r1i1p1_185001-189912.nc

This example will work as is on CNRM's Lustre and on Ciclad, and 
can be easily tuned to other local CMIP5 datasets

NOTE : Both the CMIP5 project definition and the CMIP5 data locations 
indicated here are actually already declared in standard CliMAF API 
setup (by ``import site_settings`` and ``import standard_projects``)
"""

# S.Senesi - feb 2015

import os

from climaf.api import *

# CMIP5 data are standard in CliMAF and defined that way :
# cproject("CMIP5" ,"model","experiment", ("frequency","monthly"), ("table","*"),
#         ("realm","*"),("version","last"), ("simulation,"r1i1p1"),
#         ensemble=["model","simulation"])

# Define default value for some dataset facets
cdef("frequency", "monthly")
cdef("project", "CMIP5")

# Define your dataset (a number of facets take default values)
tas1pc = ds(project='CMIP5', model="CNRM-CM5", experiment="1pctCO2", variable="tas", period="1860-1861", table="Amon")

# Display the basic filenames involved in the dataset (all filenames
# in one single string). CliMAF will search them at the data location
# which is the most specific among all declared data locations
files = tas1pc.baseFiles()
print(files)

# Let CliMAF generate a file with the exact dataset in its disk cache
# (select period and/or variables, aggregate files...)
my_file = cfile(tas1pc)
print(my_file)

# Check file size and content
os.system("ls -al " + my_file)
# os.system("type ncdump && ncdump -h "+my_file)

if my_file is None:
    exit(1)