esmvaltool/diag_scripts/aerosols/diagnostics_tendency.py
def main(cfg):
    """Compute the global specie emissions for each input dataset."""

    '''
    # Get a description of the preprocessed data that we will use as input.
    input_data = cfg['input_data'].values()

    grouped_input_data = group_metadata(input_data, 'standard_name', sort='dataset')
    logger.info( "Example of how to group and sort input data by standard_name:"
                 "\n%s", pformat(grouped_input_data))

    # Example of how to loop over variables/datasets in alphabetical order
    for standard_name in grouped_input_data:
        logger.info("Processing variable %s", standard_name)
        for attributes in grouped_input_data[standard_name]:
            logger.info("Processing dataset %s", attributes['dataset'])

            filename = attributes['filename']
            logger.info("Loading %s", filename)

            name = os.path.splitext(os.path.basename(filename))[0] + '_mean'
            logger.info("Name %s", name)
    '''

    global_emisions(cfg)

    return
Compute the global specie emissions for each input dataset.
Compute the global specie emissions for each input dataset.
Compute the global specie emissions for each input dataset .
def main(cfg):
    global_emisions(cfg)
    return
def main ( cfg ) : '''
    # Get a description of the preprocessed data that we will use as input.
    input_data = cfg['input_data'].values()

    grouped_input_data = group_metadata(input_data, 'standard_name', sort='dataset')
    logger.info( "Example of how to group and sort input data by standard_name:"
                 "\n%s", pformat(grouped_input_data))

    # Example of how to loop over variables/datasets in alphabetical order
    for standard_name in grouped_input_data:
        logger.info("Processing variable %s", standard_name)
        for attributes in grouped_input_data[standard_name]:
            logger.info("Processing dataset %s", attributes['dataset'])

            filename = attributes['filename']
            logger.info("Loading %s", filename)

            name = os.path.splitext(os.path.basename(filename))[0] + '_mean'
            logger.info("Name %s", name)
    ''' global_emisions ( cfg ) return
Compute the global specie emissions for each input dataset.
Compute the global specie emissions for each input dataset .
"""Compute the global specie emissions for each input dataset.""" '''
    # Get a description of the preprocessed data that we will use as input.
    input_data = cfg['input_data'].values()

    grouped_input_data = group_metadata(input_data, 'standard_name', sort='dataset')
    logger.info( "Example of how to group and sort input data by standard_name:"
                 "\n%s", pformat(grouped_input_data))

    # Example of how to loop over variables/datasets in alphabetical order
    for standard_name in grouped_input_data:
        logger.info("Processing variable %s", standard_name)
        for attributes in grouped_input_data[standard_name]:
            logger.info("Processing dataset %s", attributes['dataset'])

            filename = attributes['filename']
            logger.info("Loading %s", filename)

            name = os.path.splitext(os.path.basename(filename))[0] + '_mean'
            logger.info("Name %s", name)
    '''
cfg