mapper_globcolour_l3m.py

# Name:         mapper_globcolour_l3m
# Purpose:      Mapping for L3 mapped GLOBCOLOUR data
# Authors:      Anton Korosov
# Licence:      This file is part of NANSAT. You can redistribute it or modify
#               under the terms of GNU General Public License, v.3
#               http://www.gnu.org/licenses/gpl-3.0.html

from __future__ import unicode_literals, print_function, division
import datetime
import os.path
import glob

import numpy as np

from nansat.vrt import VRT
from nansat.mappers.globcolour import Globcolour
from nansat.tools import gdal, ogr
from nansat.exceptions import WrongMapperError


class Mapper(VRT, Globcolour):
    """Mapper for GLOBCOLOR L3M products"""

    def __init__(self, filename, gdalDataset, gdalMetadata, **kwargs):
        ''' GLOBCOLOR L3M VRT '''

        try:
            print("=>%s<=" % gdalMetadata['NC_GLOBAL#title'])
        except (TypeError, KeyError):
            raise WrongMapperError

        if 'GlobColour' not in gdalMetadata['NC_GLOBAL#title']:
            raise WrongMapperError

        # get list of similar (same date) files in the directory
        iDir, iFile = os.path.split(filename)
        iFileName, iFileExt = os.path.splitext(iFile)
        print('idir:', iDir, iFile, iFileName[0:30], iFileExt[0:8])

        simFilesMask = os.path.join(iDir, iFileName[0:30] + '*.nc')
        simFiles = glob.glob(simFilesMask)
        print('simFilesMask, simFiles', simFilesMask, simFiles)

        metaDict = []
        for simFile in simFiles:
            print('simFile', simFile)
            # open file, get metadata and get parameter name
            simSupDataset = gdal.Open(simFile)
            simSubDatasets = simSupDataset.GetSubDatasets()
            simWKV = None
            for simSubDataset in simSubDatasets:
                if '_mean' in simSubDataset[0]:
                    simValidSupDataset = simSupDataset
                    simGdalDataset = gdal.Open(simSubDataset[0])
                    simBand = simGdalDataset.GetRasterBand(1)
                    simBandMetadata = simBand.GetMetadata()
                    simVarname = simBandMetadata['NETCDF_VARNAME']
                    # get WKV
                    print('    simVarname', simVarname)
                    if simVarname in self.varname2wkv:
                        simWKV = self.varname2wkv[simVarname]
                        break

            # skipp adding this similar file if it is not valid
            if simWKV is None:
                continue

            metaEntry = {
                'src': {'SourceFilename': simSubDataset[0],
                        'SourceBand':  1},
                'dst': {'wkv': simWKV, 'original_name': simVarname}}

            # add wavelength and name
            longName = simBandMetadata['long_name']
            if 'Fully normalised water leaving radiance' in longName:
                simWavelength = simVarname.split('L')[1].split('_mean')[0]
                metaEntry['dst']['suffix'] = simWavelength
                metaEntry['dst']['wavelength'] = simWavelength

            # add band with rrsw
            metaEntry2 = None
            if simWKV == 'surface_upwelling_spectral_radiance_in_air_emerging_from_sea_water':
                solarIrradiance = simBandMetadata['solar_irradiance']
                metaEntry2 = {'src': metaEntry['src']}
                metaEntry2['dst'] = {'wkv': 'surface_ratio_of_upwelling_radiance_emerging_from_sea'
                                            '_water_to_downwelling_radiative_flux_in_water',
                                     'suffix': simWavelength,
                                     'wavelength': simWavelength,
                                     # 'expression': 'self["nLw_%s"] / %s / (0.52 + 1.7 * self["nLw
                                     # _%s"] / %s)' % (simWavelength, solarIrradiance,
                                     # simWavelength, solarIrradiance),
                                     'expression': 'self["nLw_%s"] / %s' %
                                     (simWavelength, solarIrradiance)
                                     }

            print('        metaEntry', metaEntry)
            metaDict.append(metaEntry)
            if metaEntry2 is not None:
                print('        metaEntry2', metaEntry2)
                metaDict.append(metaEntry2)

        print('simSubDatasets', simValidSupDataset.GetSubDatasets())
        for simSubDataset in simValidSupDataset.GetSubDatasets():
            print('simSubDataset', simSubDataset)
            if '_flags ' in simSubDataset[1]:
                print('    mask simSubDataset', simSubDataset[1])
                flags = gdal.Open(simSubDataset[0]).ReadAsArray()
                mask = np.ones(flags.shape) * 64
                mask[np.bitwise_and(flags, np.power(2, 0)) > 0] = 1
                mask[np.bitwise_and(flags, np.power(2, 3)) > 0] = 2

        self.band_vrts = {'maskVRT': VRT(array=mask)}

        metaDict.append(
            {'src': {'SourceFilename': self.band_vrts['maskVRT'].filename,
                     'SourceBand': 1},
             'dst': {'name': 'mask'}})

        # create empty VRT dataset with geolocation only
        simGdalDataset.SetProjection('GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,'
                                     '298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG",'
                                     '"6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],'
                                     'UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],'
                                     'AUTHORITY["EPSG","4326"]]')
        self._init_from_gdal_dataset(simGdalDataset)

        # add bands with metadata and corresponding values to the empty VRT
        self.create_bands(metaDict)

        # Add valid time
        startYear = int(gdalMetadata['Start Year'])
        startDay = int(gdalMetadata['Start Day'])
        # Adding valid time to dataset
        self.dataset.SetMetadataItem('time_coverage_start',
            (datetime.datetime(startYear, 1, 1) + datetime.timedelta(startDay)).isoformat())
        self.dataset.SetMetadataItem('time_coverage_end',
            (datetime.datetime(startYear, 1, 1) + datetime.timedelta(startDay)).isoformat())