# -*- coding: utf-8 -*-
# The MIT License (MIT)
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# Copyright (c) 2016, TU Wien
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'''
Module for a command line interface to convert the GLDAS data into a
time series format using the repurpose package
'''

import os
import sys
import argparse
from datetime import datetime

from pygeogrids import BasicGrid

from repurpose.img2ts import Img2Ts
from gldas.interface import GLDAS_Noah_v1_025Ds,GLDAS_Noah_v21_025Ds

def get_filetype(inpath):
    '''
    Tries to find out the file type by searching for
    grib or nc files two subdirectories into the passed input path.
    If function fails, grib is assumed.
    
    Parameters
    ------------
    input_root: string
        input path where era interim data was downloaded
    '''
    
    onedown=os.path.join(inpath,os.listdir(inpath)[0])
    twodown=os.path.join(onedown,os.listdir(onedown)[0])
            
    filelist=[]
    for path, subdirs,files in os.walk(twodown):
        for name in files:
            filename,extension=os.path.splitext(name)
            filelist.append(extension)
            
    if '.nc4' in filelist and '.grb' not in filelist:
        return 'netCDF'
    elif '.grb' in filelist and '.nc4' not in filelist:
        return 'grib'
    else:
        #if file type cannot be detected, guess grib
        return 'grib'
        
        
def mkdate(datestring):
    if len(datestring) == 10:
        return datetime.strptime(datestring, '%Y-%m-%d')
    if len(datestring) == 16:
        return datetime.strptime(datestring, '%Y-%m-%dT%H:%M')


def reshuffle(input_root, outputpath,
              startdate, enddate,
              parameters,
              imgbuffer=50):
    """
    Reshuffle method applied to ERA-Interim data.

    Parameters
    ----------
    input_root: string
        input path where era interim data was downloaded
    outputpath : string
        Output path.
    startdate : datetime
        Start date.
    enddate : datetime
        End date.
    parameters: list
        parameters to read and convert
    imgbuffer: int, optional
        How many images to read at once before writing time series.
    """

    if get_filetype(input_root) == 'grib':
        input_dataset = GLDAS_Noah_v1_025Ds(input_root, parameters,
                                            array_1D=True)
    else:
        input_dataset = GLDAS_Noah_v21_025Ds(input_root, parameters,
                                             array_1D=True)

    if not os.path.exists(outputpath):
        os.makedirs(outputpath)

    global_attr = {'product': 'GLDAS'}

    # get time series attributes from first day of data.
    data = input_dataset.read(startdate)
    ts_attributes = data.metadata
    grid = BasicGrid(data.lon, data.lat)

    reshuffler = Img2Ts(input_dataset=input_dataset, outputpath=outputpath,
                        startdate=startdate, enddate=enddate,
                        input_grid=grid,
                        imgbuffer=imgbuffer, cellsize_lat=5.0, cellsize_lon=5.0,
                        global_attr=global_attr,
                        ts_attributes=ts_attributes)
    reshuffler.calc()


def parse_args(args):
    """
    Parse command line parameters for conversion from image to timeseries

    :param args: command line parameters as list of strings
    :return: command line parameters as :obj:`argparse.Namespace`
    """
    parser = argparse.ArgumentParser(
        description="Convert GLDAS data to time series format.")
    parser.add_argument("dataset_root",
                        help='Root of local filesystem where the data is stored.')
    parser.add_argument("timeseries_root",
                        help='Root of local filesystem where the timeseries should be stored.')
    parser.add_argument("start", type=mkdate,
                        help=("Startdate. Either in format YYYY-MM-DD or YYYY-MM-DDTHH:MM."))
    parser.add_argument("end", type=mkdate,
                        help=("Enddate. Either in format YYYY-MM-DD or YYYY-MM-DDTHH:MM."))
    parser.add_argument("parameters", metavar="parameters",
                        nargs="+",
                        help=("Parameters to download in numerical format. e.g."
                              "086_L1 086_L2 086_L3 086_L4 for Volumetric soil water layers 1 to 4."))

    parser.add_argument("--imgbuffer", type=int, default=50,
                        help=("How many images to read at once. Bigger numbers make the "
                              "conversion faster but consume more memory."))
    args = parser.parse_args(args)
    # set defaults that can not be handled by argparse

    print("Converting data from {} to {} into folder {}.".format(args.start.isoformat(),
                                                                 args.end.isoformat(),
                                                                 args.timeseries_root))
    return args


def main(args):
    args = parse_args(args)

    reshuffle(args.dataset_root,
              args.timeseries_root,
              args.start,
              args.end,
              args.parameters,
              imgbuffer=args.imgbuffer)


def run():
    main(sys.argv[1:])

if __name__ == '__main__':
    run()

@@ -1740,35 +1740,29 @@
  path where 
-era interim
+GLDAS
  data was do

Change era interim to gldas