# coding=utf-8
"""Cmorization classes"""
import glob
import os
import shutil
import uuid
import traceback
import pygrib
from datetime import datetime

import six
from bscearth.utils.date import parse_date, chunk_end_date, previous_day, date2str, add_months
from bscearth.utils.log import Log
from cdo import CDOException
import iris
import iris.coord_categorisation
import iris.analysis
import iris.util
import iris.exceptions
import cf_units

from earthdiagnostics.datafile import NetCDFFile
from earthdiagnostics.frequency import Frequency, Frequencies
from earthdiagnostics.modelingrealm import ModelingRealms
from earthdiagnostics.utils import TempFile, Utils


class Cmorizer(object):
    """
    Class to manage CMORization

    Parameters
    ----------
    data_manager: DataManager
    startdate: str
    member: int

    """

    NON_DATA_VARIABLES = ('lon', 'lat', 'longitude', 'latitude', 'plev', 'time', 'time_bnds', 'leadtime', 'lev',
                          'lev_2', 'icethi',
                          'deptht', 'depthu', 'depthw', 'depthv', 'time_centered', 'time_centered_bounds',
                          'deptht_bounds', 'depthu_bounds', 'depthv_bounds', 'depthw_bounds',
                          'deptht_bnds', 'depthu_bnds', 'depthv_bnds', 'depthw_bnds',
                          'time_counter_bounds', 'ncatice', 'nav_lat_grid_V', 'nav_lat_grid_U',
                          'nav_lat_grid_T', 'nav_lon_grid_V', 'nav_lon_grid_U', 'nav_lon_grid_T',
                          'depth', 'depth_2', 'depth_3', 'depth_4',
                          'depth_bnds', 'depth_2_bnds', 'depth_3_bnds', 'depth_4_bnds',
                          'mlev', 'hyai', 'hybi', 'hyam', 'hybm')

    def __init__(self, data_manager, startdate, member):
        self.data_manager = data_manager
        self.startdate = startdate
        self.member = member
        self.config = data_manager.config
        self.experiment = self.config.experiment
        self.cmor = self.config.cmor
        self.member_str = self.experiment.get_member_str(member)
        self.original_files_path = os.path.join(self.config.data_dir, self.experiment.expid, 'original_files',
                                                self.startdate, self.member_str, 'outputs')
        self.atmos_timestep = None
        self.cmor_scratch = str(os.path.join(self.config.scratch_dir, 'CMOR', self.startdate, self.member_str))

        if self.config.data_convention in ('primavera', 'cmip6'):
            self.lon_name = 'longitude'
            self.lat_name = 'latitude'
        else:
            self.lon_name = 'lon'
            self.lat_name = 'lat'

        self.alt_coord_names = {'time_counter': 'time', 'time_counter_bnds': 'time_bnds',
                                'time_counter_bounds': 'time_bnds',
                                'tbnds': 'bnds', 'nav_lat': self.lat_name, 'nav_lon': self.lon_name, 'x': 'i', 'y': 'j'}

    @property
    def path_icm(self):
        """Path to the ICM file"""
        return os.path.join(self.config.scratch_dir, 'ICM')

    def cmorize_ocean(self):
        """Cmorize ocean files from MMO files"""
        if not self.cmor.ocean:
            Log.info('Skipping ocean cmorization due to configuration')
            return
        Log.info('\nCMORizing ocean\n')
        self._cmorize_ocean_files('MMO', 'PPO', 'diags')

    def _cmorize_ocean_files(self, *args):
        tar_files = ()
        for prefix in args:
            tar_folder = os.path.join(self.original_files_path, '{0}*'.format(prefix))
            tar_files = glob.glob(tar_folder)
            tar_files.sort()
            if len(tar_files) > 0:
                break
        if not len(tar_files):
            Log.error('No {1} files found in {0}'.format(self.original_files_path, args))

        count = 1
        for tarfile in tar_files:
            if not self._cmorization_required(self._get_chunk(os.path.basename(tarfile)), (ModelingRealms.ocean,
                                                                                           ModelingRealms.seaIce,
                                                                                           ModelingRealms.ocnBgchem)):
                Log.info('No need to unpack file {0}/{1}'.format(count, len(tar_files)))
                count += 1
                continue

            Log.info('Unpacking oceanic file {0}/{1}'.format(count, len(tar_files)))
            try:
                self._unpack_tar_file(tarfile)
                self._cmorize_nc_files()
                Log.result('Oceanic file {0}/{1} finished'.format(count, len(tar_files)))
            except Exception as ex:
                Log.error('Could not CMORize oceanic file {0}: {1}', count, ex)
            count += 1
            if count > self.experiment.num_chunks:
                return

    def _filter_files(self, file_list):
        if not self.cmor.filter_files:
            return file_list
        filtered = list()
        filters = self.cmor.filter_files.split(' ')
        for file_path in file_list:
            filename = os.path.basename(file_path)
            if any(f in filename for f in filters):
                filtered.append(file_path)
            else:
                os.remove(file_path)
        if len(filtered) == 0:
            Log.warning('Filters {0} do not match any of the files', filters)
        return filtered

    def _cmorize_nc_files(self):
        nc_files = glob.glob(os.path.join(self.cmor_scratch, '*.nc'))
        for filename in self._filter_files(nc_files):
            self._cmorize_nc_file(filename)
        self._clean_cmor_scratch()

    def _correct_fluxes(self):
        fluxes_vars = [self.data_manager.variable_list.get_variable(cmor_var, True).short_name
                       for cmor_var in ('prc', "prsn", "rss", "rls", "rsscs", "rsds", "rlds", "hfss", 'hfls')]
        change_sign_vars = [self.data_manager.variable_list.get_variable(cmor_var, True).short_name
                            for cmor_var in ("hfss", 'hfls')]
        total_seconds = (self.experiment.atmos_timestep * 3600)
        for filename in glob.glob(os.path.join(self.cmor_scratch, '*.nc')):
            handler = Utils.open_cdf(filename)
            for varname in handler.variables.keys():
                cmor_var = self.data_manager.variable_list.get_variable(varname, True)

                if cmor_var is None or cmor_var.short_name not in fluxes_vars:
                    continue

                if cmor_var.short_name in change_sign_vars:
                    sign = -1
                else:
                    sign = 1

                var_handler = handler.variables[varname]
                var_handler[:] = sign * var_handler[:] / total_seconds
                var_handler.units = '{0} {1}'.format(var_handler.units, 's-1')
            handler.close()

    def _unpack_tar_file(self, tarfile):
        self._clean_cmor_scratch()
        os.makedirs(self.cmor_scratch)
        Utils.untar((tarfile,), self.cmor_scratch)
        if os.path.isdir(os.path.join(self.cmor_scratch, 'backup')):
            for filepath in glob.glob(os.path.join(self.cmor_scratch, 'backup', '*')):
                Log.debug('Moving file {0}', filepath)
                shutil.move(filepath, filepath.replace('/backup/', '/'))
        zip_files = glob.glob(os.path.join(self.cmor_scratch, '*.gz'))
        if zip_files:
            for zip_file in self._filter_files(zip_files):
                try:
                    Utils.unzip(zip_file)
                except Utils.UnzipException as ex:
                    Log.error('File {0} could not be unzipped: {1}', tarfile, ex)

    def _clean_cmor_scratch(self):
        if os.path.exists(self.cmor_scratch):
            shutil.rmtree(self.cmor_scratch)

    def _merge_mma_files(self, tarfile):
        temp = TempFile.get()
        for grid in ['SH', 'GG']:
            files = glob.glob(os.path.join(self.cmor_scratch, 'MMA_*_{}_*.nc'.format(grid)))
            if not files:
                continue
            merged = TempFile.get()
            if grid == 'SH':
                for filename in files:
                    Utils.cdo.sp2gpl(options='-O', input=filename, output=temp)
                    shutil.move(temp, filename)
            Utils.cdo.mergetime(input=files, output=merged)
            for filename in files:
                os.remove(filename)
            tar_startdate = os.path.basename(tarfile[0:-4]).split('_')[4].split('-')
            filename = 'MMA{0}_1m_{1[0]}_{1[1]}.nc'.format(grid, tar_startdate)
            shutil.move(merged, os.path.join(self.cmor_scratch, filename))

    def cmorize_atmos(self):
        """Cmorize atmospheric data, from grib or MMA files"""
        if not self.cmor.atmosphere:
            Log.info('Skipping atmosphere cmorization due to configuration')
            return

        Log.info('\nCMORizing atmosphere\n')
        if self.cmor.use_grib and self._gribfiles_available():
            self._cmorize_grib_files()
        else:
            self._cmorize_mma_files()

    def _cmorize_mma_files(self):
        tar_files = glob.glob(os.path.join(self.original_files_path, 'MMA*'))
        tar_files.sort()
        count = 1
        if len(tar_files) == 0:
            Log.error('MMA files not found in {0}'.format(self.original_files_path))
        for tarfile in tar_files:
            if not self._cmorization_required(self._get_chunk(os.path.basename(tarfile)), (ModelingRealms.atmos,)):
                Log.info('No need to unpack file {0}/{1}'.format(count, len(tar_files)))
                count += 1
                continue
            Log.info('Unpacking atmospheric file {0}/{1}'.format(count, len(tar_files)))
            try:
                self._unpack_tar_file(tarfile)
                self._merge_mma_files(tarfile)
                self._correct_fluxes()
                self._cmorize_nc_files()
                Log.result('Atmospheric file {0}/{1} finished'.format(count, len(tar_files)))
            except Exception as ex:
                Log.error('Could not cmorize atmospheric file {0}: {1}\n {2}', count, ex, traceback.format_exc())

            count += 1

    def _cmorize_grib_files(self):
        chunk = 1
        chunk_start = parse_date(self.startdate)

        while os.path.exists(self._get_original_grib_path(chunk_start, 'GG')) or \
                os.path.exists(self._get_original_grib_path(chunk_start, 'SH')):

            if self._cmorization_required(chunk, (ModelingRealms.atmos,)):
                chunk_end = chunk_end_date(chunk_start, self.experiment.chunk_size, 'month', self.experiment.calendar)
                chunk_end = previous_day(chunk_end, self.experiment.calendar)
                Log.info('CMORizing chunk {0}-{1}', date2str(chunk_start), date2str(chunk_end))
                try:
                    for grid in ('SH', 'GG'):
                        Log.info('Processing {0} variables', grid)

                        first_grib = self._get_original_grib_path(chunk_start, grid)
                        if not os.path.exists(first_grib):
                            continue
                        var_list = Utils.cdo.showvar(input=first_grib)[0]
                        codes = {int(var.replace('var', '')) for var in var_list.split()}
                        if not codes.intersection(self.config.cmor.get_requested_codes()):
                            Log.info('No requested variables found in {0}. Skipping...', grid)
                            continue
                        self._cmorize_grib_file(chunk_end, chunk_start, grid)
                except Exception as ex:
                    Log.error('Can not cmorize GRIB file for chunk {0}-{1}: {2}',
                              date2str(chunk_start), date2str(chunk_end), ex)
            chunk_start = chunk_end_date(chunk_start, self.experiment.chunk_size, 'month', self.experiment.calendar)
            chunk += 1

    def _cmorize_grib_file(self, chunk_end, chunk_start, grid):
        for month in range(0, self.experiment.chunk_size):
            current_date = add_months(chunk_start, month, self.experiment.calendar)
            original_gribfile = self._get_original_grib_path(current_date, grid)
            Log.info('Processing month {1}', grid, date2str(current_date))
            gribfile = self._get_scratch_grib_path(current_date, grid)
            if not os.path.isfile(gribfile):
                Log.info('Copying file...', grid, date2str(current_date))
                Utils.copy_file(original_gribfile, gribfile)

            self._obtain_atmos_timestep(gribfile)
            full_file = self._get_monthly_grib(current_date, gribfile, grid)
            if not self._unpack_grib(full_file, gribfile, grid, current_date.month):
                os.remove(gribfile)
                return

            next_gribfile = self._get_original_grib_path(add_months(current_date, 1, self.experiment.calendar), grid)
            if not os.path.exists(next_gribfile):
                os.remove(gribfile)

            self._ungrib_vars(gribfile, current_date.month)

            for splited_file in glob.glob('{0}_*.128.nc'.format(gribfile)):
                os.remove(splited_file)

            Log.result('Month {0}, {1} variables finished', date2str(current_date), grid)

        self._merge_and_cmorize_atmos(chunk_start, chunk_end, grid, Frequencies.monthly)
        self._merge_and_cmorize_atmos(chunk_start, chunk_end, grid, Frequencies.daily)
        self._merge_and_cmorize_atmos(chunk_start, chunk_end, grid,
                                      '{0}hr'.format(self.atmos_timestep))

    def _unpack_grib(self, full_file, gribfile, grid, month):
        Log.info('Unpacking... ')
        # remap on regular Gauss grid

        codes = self.cmor.get_requested_codes()
        if 228 in codes:
            codes.update((142, 143))
        codes_str = ','.join([str(code) for code in codes])
        try:
            if grid == 'SH':
                Utils.cdo.splitparam(input='-sp2gpl -selcode,{0} {1} '.format(codes_str, full_file),
                                     output=gribfile + '_',
                                     options='-f nc4 -t ecmwf')

            else:
                Utils.cdo.splitparam(input='-selcode,{0} {1}'.format(codes_str, full_file),
                                     output=gribfile + '_',
                                     options='-R -f nc4 -t ecmwf')
                # total precipitation (remove negative values)
                if 228 in codes:
                    Utils.cdo.setcode(228,
                                      input='-chname,LSP,TP -setmisstoc,0 -setvrange,0,Inf '
                                            '-add {0}_142.128.nc {0}_143.128.nc'.format(gribfile),
                                      output='{0}_228.128.nc'.format(gribfile),
                                      options='-f nc4')
            return True
        except CDOException:
            Log.info('No requested codes found in {0} file'.format(grid))
            return False
        finally:
            Utils.remove_file(self.path_icm)

    def _get_monthly_grib(self, current_date, gribfile, grid):
        prev_gribfile = self._get_scratch_grib_path(add_months(current_date, -1, self.experiment.calendar), grid)
        if os.path.exists(prev_gribfile):
            self._merge_grib_files(current_date, prev_gribfile, gribfile)

            full_file = self.path_icm
        else:
            full_file = gribfile
        return full_file

    def _get_scratch_grib_path(self, current_date, grid):
        return os.path.join(self.config.scratch_dir, self._get_grib_filename(grid, current_date))

    def _obtain_atmos_timestep(self, gribfile):
        if self.atmos_timestep is None:
            self.atmos_timestep = self._get_atmos_timestep(gribfile)

    def _get_original_grib_path(self, current_date, grid):
        return os.path.join(self.original_files_path,
                            self._get_grib_filename(grid, current_date))

    def _get_grib_filename(self, grid, month):
        return 'ICM{0}{1}+{2}.grb'.format(grid, self.experiment.expid, date2str(month)[:-2])

    def _get_atmos_timestep(self, gribfile):
        Log.info('Getting timestep...')
        grib_handler = pygrib.open(gribfile)
        dates = set()
        for mes in grib_handler:
            dates.add(mes.validDate)
        dates = list(dates)
        dates.sort()
        atmos_timestep = dates[1] - dates[0]
        atmos_timestep = int(atmos_timestep.total_seconds() / 3600)
        self.experiment.atmos_timestep = atmos_timestep
        grib_handler.close()
        return atmos_timestep

    def _cmorize_nc_file(self, filename):
        Log.info('Processing file {0}', filename)

        if not self._contains_requested_variables(filename):
            os.remove(filename)
            return

        # Utils.convert2netcdf4(filename)
        frequency = self._get_nc_file_frequency(filename)
        Utils.rename_variables(filename, self.alt_coord_names, False)
        handler = Utils.open_cdf(filename)
        Cmorizer._remove_valid_limits(handler)
        self._add_common_attributes(handler, frequency)
        self._update_time_variables(handler)

        variables = handler.variables.keys()
        handler.close()

        Log.info('Splitting file {0}', filename)
        for variable in variables:
            if variable in Cmorizer.NON_DATA_VARIABLES:
                continue
            try:
                self.extract_variable(filename, frequency, variable)
            except Exception as ex:
                Log.error('Variable {0} can not be cmorized: {1}', variable, ex)
        Log.result('File {0} cmorized!', filename)
        os.remove(filename)

    @staticmethod
    def _remove_valid_limits(handler):
        for variable in handler.variables.keys():
            var = handler.variables[variable]
            if 'valid_min' in var.ncattrs():
                del var.valid_min
            if 'valid_max' in var.ncattrs():
                del var.valid_max
        handler.sync()

    def _get_nc_file_frequency(self, filename):
        file_parts = os.path.basename(filename).split('_')
        if self.experiment.expid in [file_parts[1], file_parts[2]]:
            frequency = Frequency('m')
        elif self.experiment.expid == file_parts[0]:
            try:
                parse_date(file_parts[1])
                frequency = Frequency('m')
            except ValueError:
                frequency = Frequency(file_parts[1])
        else:
            frequency = Frequency(file_parts[1])
        return frequency

    def _contains_requested_variables(self, filename):
        variables = Utils.get_file_variables(filename)
        return self.cmor.any_required(variables)

    def extract_variable(self, file_path, frequency, variable):
        """
        Extract a variable from a file and creates the CMOR file

        Parameters
        ----------
        file_path:str
        frequency: Frequency
        variable: str

        Raises
        ------
        CMORException
            If the filename does not match any of the recognized patterns

        """
        alias, var_cmor = self.config.var_manager.get_variable_and_alias(variable)
        if var_cmor is None:
            return

        if not self.cmor.cmorize(var_cmor):
            return

        temp = TempFile.get()
        handler = Utils.open_cdf(file_path)
        coords = [self.lon_name, self.lat_name, 'time']
        if 'leadtime' in handler.variables.keys():
            coords.append('leadtime')

        if var_cmor.domain == ModelingRealms.ocean:
            lev_dimensions = {'deptht': 'lev', 'depthu': 'lev', 'depthw': 'lev', 'depthv': 'lev',
                              'depth': 'lev'}
        elif var_cmor.domain in [ModelingRealms.landIce, ModelingRealms.land]:
            lev_dimensions = {'depth': 'sdepth', 'depth_2': 'sdepth', 'depth_3': 'sdepth',
                              'depth_4': 'sdepth'}
        elif var_cmor.domain == ModelingRealms.atmos:
            lev_dimensions = {'depth': 'plev'}
        else:
            lev_dimensions = {}

        for lev_dim in lev_dimensions.keys():
            if lev_dim in handler.variables[variable].dimensions:
                coords.append(lev_dim)

        handler.variables[variable].coordinates = ' '.join(set(coords))
        handler.close()

        cube = iris.load_cube(file_path, iris.Constraint(cube_func=lambda c: c.var_name == variable))
        for lev_original, lev_target in six.iteritems(lev_dimensions):
            try:
                cube.coord(lev_original).var_name = lev_target
            except iris.exceptions.CoordinateNotFoundError:
                pass

        iris.save(cube, temp, zlib=True)

        if alias.basin is None:
            region = None
        else:
            region = alias.basin.name

        date_str = self._get_date_str(file_path)
        if date_str is None:
            Log.error('Variable {0} can not be cmorized. Original filename does not match a recognized pattern',
                      var_cmor.short_name)
            raise CMORException('Variable {0}:{1} can not be cmorized. Original filename does not match a recognized '
                                'pattern'.format(var_cmor.domain, var_cmor.short_name))

        netcdf_file = NetCDFFile()
        netcdf_file.data_manager = self.data_manager
        netcdf_file.local_file = temp
        netcdf_file.remote_file = self.data_manager.get_file_path(self.startdate, self.member,
                                                                  var_cmor.domain, var_cmor.short_name, var_cmor,
                                                                  None, frequency,
                                                                  grid=alias.grid, year=None, date_str=date_str)

        netcdf_file.data_convention = self.config.data_convention
        netcdf_file.region = region
        netcdf_file.frequency = frequency
        netcdf_file.domain = var_cmor.domain
        netcdf_file.var = var_cmor.short_name
        netcdf_file.final_name = var_cmor.short_name

        netcdf_file.prepare_to_upload(rename_var=variable)
        netcdf_file.add_cmorization_history()
        netcdf_file.upload()

        if region:
            region_str = ' (Region {})'.format(region)
        else:
            region_str = ''
        Log.info('Variable {0.domain}:{0.short_name} processed{1}', var_cmor, region_str)

    def _get_date_str(self, file_path):
        file_parts = os.path.basename(file_path).split('_')
        valid_starts = (self.experiment.expid, 'MMA', 'MMASH', 'MMAGG', 'MMO')
        if file_parts[0] in valid_starts or file_parts[0].startswith('ORCA'):
            # Model output
            if file_parts[-1].endswith('.tar'):
                file_parts = file_parts[-1][0:-4].split('-')
                return '{0}-{1}'.format(file_parts[0][0:6], file_parts[1][0:6])
            else:
                return '{0}-{1}'.format(file_parts[2][0:6], file_parts[3][0:6])
        elif file_parts[1] == self.experiment.expid:
            # Files generated by the old version of the diagnostics
            return '{0}-{1}'.format(file_parts[4][0:6], file_parts[5][0:6])
        else:
            return None

    def _get_chunk(self, file_path):
        chunk_start = parse_date(self._get_date_str(file_path).split('-')[0])
        current_date = parse_date(self.startdate)
        chunk = 1
        while current_date < chunk_start:
            current_date = chunk_end_date(current_date, self.experiment.chunk_size, 'month', self.experiment.calendar)
            chunk += 1

        if current_date != chunk_start:
            raise Exception('File {0} start date is not a valid chunk start date'.format(file_path))
        return chunk

    def _merge_grib_files(self, current_month, prev_gribfile, gribfile):
        Log.info('Merging data from different files...')
        temp = TempFile.get(suffix='.grb')
        Utils.cdo.selmon(current_month.month, input=prev_gribfile, output=temp)
        Utils.cdo.mergetime(input=[temp, gribfile],
                            output=self.path_icm)
        os.remove(prev_gribfile)
        os.remove(temp)

    def _ungrib_vars(self, gribfile, month):
        for var_code in self.cmor.get_requested_codes():
            file_path = '{0}_{1}.128.nc'.format(gribfile, var_code)
            if not os.path.exists(file_path):
                continue
            cube = iris.load_cube(file_path)

            cube = self._fix_time_coord(cube, var_code)
            cube = cube.extract(iris.Constraint(month_number=month))
            cube = self._change_units(cube, var_code)

            for frequency in (Frequencies.monthly, Frequencies.daily, Frequency('{0}hr'.format(self.atmos_timestep))):
                if var_code not in self.cmor.get_variables(frequency):
                    continue
                time_cube = self._get_time_average(cube, frequency, var_code)

                levels = self.config.cmor.get_levels(frequency, var_code)
                if levels:
                    time_cube = time_cube.extract(level=levels)

                if cube.var_name.endswith('_2'):
                    time_cube.var_name = cube.var_name[:-2]

                out_file = '{0}_{1}_{2}.nc'.format(gribfile, var_code, frequency)
                time_cube.remove_coord('month_number')
                time_cube.remove_coord('day_of_month')
                iris.save(time_cube, out_file, zlib=True)

    def _fix_time_coord(self, cube, var_code):
        time = cube.coord('time')
        target_units = 'days since 1950-01-01 00:00:00'
        time.convert_units(cf_units.Unit(target_units, calendar=time.units.calendar))
        time.units = target_units

        if var_code in (144, 146, 147, 169, 175, 176, 177, 179, 180, 181, 182, 201, 202, 205, 212, 228):
            time.points = time.points - (self.experiment.atmos_timestep / 24.0)
        iris.coord_categorisation.add_day_of_month(cube, 'time')
        iris.coord_categorisation.add_month_number(cube, 'time')
        return cube

    @staticmethod
    def _get_time_average(cube, frequency, var_code):
        if frequency == Frequencies.monthly:
            if var_code == 201:
                cube = cube.aggregated_by(['month_number', 'day_of_month'], iris.analysis.MAX)
            elif var_code == 202:
                cube = cube.aggregated_by(['month_number', 'day_of_month'], iris.analysis.MIN)
            cube = cube.aggregated_by(['month_number'], iris.analysis.MEAN)
        elif frequency == Frequencies.daily:
            if var_code == 201:
                cube = cube.aggregated_by(['month_number', 'day_of_month'], iris.analysis.MAX)
            elif var_code == 202:
                cube = cube.aggregated_by(['month_number', 'day_of_month'], iris.analysis.MIN)
            else:
                cube = cube.aggregated_by(['month_number', 'day_of_month'], iris.analysis.MEAN)
        return cube

    def _change_units(self, cube, var_code):
        var_name = cube.var_name
        if var_code == 129:
            # geopotential
            cube = cube / 9.81
            cube.units = 'm'
        elif var_code in (146, 147, 169, 175, 176, 177, 179, 212):
            # radiation
            cube = cube / (self.experiment.atmos_timestep * 3600)
            cube.units = 'W m-2'
        elif var_code in (180, 181):
            # momentum flux
            cube = cube / (self.experiment.atmos_timestep * 3600)
            cube.units = 'N m-2'
        elif var_code in (144, 182, 205, 228):
            # precipitation/evaporation/runoff
            cube = cube * 1000 / (self.experiment.atmos_timestep * 3600)
            cube.units = 'kg m-2 s-1'
        cube.var_name = var_name
        return cube

    def _merge_and_cmorize_atmos(self, chunk_start, chunk_end, grid, frequency):
        merged_file = 'MMA_{0}_{1}_{2}_{3}.nc'.format(frequency, date2str(chunk_start), date2str(chunk_end), grid)
        files = glob.glob(os.path.join(self.config.scratch_dir,
                                       '{0}_*_{1}.nc'.format(self._get_grib_filename(grid, chunk_start), frequency)))

        def _load_cube(cube, field, filename):
            if 'history' in cube.attributes:
                del cube.attributes['history']

        for first_file in files:
            var_files = []
            current_month = chunk_start
            while current_month < chunk_end:
                var_files.append(first_file.replace('+{0}.grb'.format(date2str(chunk_start)[:-2]),
                                                    '+{0}.grb'.format(date2str(current_month)[:-2])))
                current_month = add_months(current_month, 1, self.experiment.calendar)
            var_cubes = iris.load(var_files, callback=_load_cube)
            iris.util.unify_time_units(var_cubes)
            var_cube = var_cubes.concatenate_cube()
            iris.save(var_cube, merged_file, zlib=True)
            for var_file in var_files:
                os.remove(var_file)
            self._cmorize_nc_file(merged_file)

    def _update_time_variables(self, handler):
        time_var = handler.variables['time']
        if hasattr(time_var, 'calendar'):
            calendar = time_var.calendar
        else:
            calendar = 'standard'
        if "time_bnds" in handler.variables:
            time_var.bounds = "time_bnds"
            handler.variables['time_bnds'].units = time_var.units
            Utils.convert_units(handler.variables['time_bnds'], 'days since 1850-01-01 00:00:00', calendar, calendar)
        Utils.convert_units(time_var, 'days since 1850-1-1 00:00:00', calendar)
        self._set_leadtime_var(handler)

    def _set_leadtime_var(self, handler):
        if 'leadtime' in handler.variables:
            var = handler.variables['leadtime']
        else:
            var = handler.createVariable('leadtime', float, 'time')
        var.units = "days"
        var.long_name = "Time elapsed since the start of the forecast"
        var.standard_name = "forecast_period"
        leadtime = Utils.get_datetime_from_netcdf(handler)
        startdate = parse_date(self.startdate)
        leadtime = [datetime(time.year, time.month, time.day, time.hour, time.minute, time.second) - startdate
                    for time in leadtime]
        for lt, lead in enumerate(leadtime):
            var[lt] = lead.days

    def _add_common_attributes(self, handler, frequency):
        cmor = self.config.cmor
        experiment = self.config.experiment
        handler.associated_experiment = cmor.associated_experiment
        handler.batch = '{0}{1}'.format(experiment.institute, datetime.now().strftime('%Y-%m-%d(T%H:%M:%SZ)'))
        handler.contact = 'Pierre-Antoine Bretonniere, pierre-antoine.bretonniere@bsc.es , ' \
                          'Javier Vegas-Regidor, javier.vegas@bsc.es '
        handler.Conventions = 'CF-1.6'
        handler.creation_date = datetime.now().strftime('%Y-%m-%d(T%H:%M:%SZ)')
        handler.experiment_id = experiment.experiment_name
        startdate = parse_date(self.startdate)
        handler.forecast_reference_time = '{0.year}-{0.month:02}-{0.day:02}' \
                                          '(T{0.hour:02}:{0.minute:02}:{0.second:02}Z)'.format(startdate)
        handler.frequency = frequency.frequency
        handler.institute_id = experiment.institute
        handler.institution = experiment.institute
        handler.initialization_method = cmor.initialization_method
        handler.initialization_description = cmor.initialization_description
        handler.physics_version = cmor.physics_version
        handler.physics_description = cmor.physics_description
        handler.model_id = experiment.model
        handler.associated_model = cmor.associated_model
        handler.project_id = self.config.data_convention.upper()
        handler.realization = str(self.member + 1)
        handler.source = cmor.source
        handler.startdate = 'S{0}'.format(self.startdate)
        handler.tracking_id = str(uuid.uuid1())
        handler.title = "{0} model output prepared for {2} {1}".format(experiment.model, experiment.experiment_name,
                                                                       self.config.data_convention.upper())

    def _gribfiles_available(self):
        grb_path = os.path.join(self.original_files_path, '*.grb')
        gribfiles = glob.glob(grb_path)
        return len(gribfiles) > 0

    def _cmorization_required(self, chunk, domains):
        if not self.config.cmor.chunk_cmorization_requested(chunk):
            return False
        if self.config.cmor.force:
            return True
        for domain in domains:
            if self.data_manager.is_cmorized(self.startdate, self.member, chunk, domain):
                return False
        return True


class CMORException(Exception):
    """Exception to be launched when an error is encountered during cmorization"""

    pass