from jasmin_cis.data_io.products.AProduct import AProduct
from jasmin_cis.data_io.Coord import Coord, CoordList
from jasmin_cis.data_io.ungridded_data import UngriddedData
from jasmin_cis.data_io.ungridded_data import Metadata
import jasmin_cis.data_io.hdf as hdf
import logging
from pyhdf import SD
import numpy as np

class SEVIRI_L2_Apollo(AProduct):
    """
    Reads cloud top temperature variable from a CMSAF (CTX version 001) HDF file containing non CF compliant metadata.
    Applies scale and offset to data.
    Masks fill values.
    Creates variable metadata.
    Reads latitude and longitude values from a separate HDF file.
    Returns data, metadata and coordinates.
    """

    def get_file_signature(self):
        "Returns a list of regular expressions, which are used to decided which files require this plugin."
        
        return [r'clouds_MET08*']
    
    def create_data_object(self, filenames, variable):
        "Read in and return the relevant data, metadata and coords for the specified filename."
        logging.debug("Creating data object for variable " + variable)
        # reading coordinates
        coords = self.create_coords(filenames, variable)
        # reading variables
        variables=[variable,'mask']
        sdata, vdata = hdf.read(filenames, variables)

        # retrieve variable
        var = sdata[variable]
        var_data = hdf.read_data(var,"SD")
        
	    # apply offset to variable
        var_data = var_data * 0.01
        
        # mask variable fill values
        var_data = np.ma.masked_less_equal(var_data ,0.0)	    
        
        # read mask
        cloud_mask = sdata['mask']
        cloud_mask = hdf.read_data(cloud_mask,"SD")
        
        # apply mask to variable
        var_data = np.ma.array(var_data, mask = (cloud_mask != 100))
        
        # create variable metadata
        metadata = Metadata(name='Cloud_Top_Temperature',units='K')
       
        logging.info(type(var_data))
        logging.info(type(metadata))
        logging.info(type(coords))
    
        return UngriddedData(var_data,metadata,coords)

    def create_coords(self, filenames, variable=None):
	"Read in the relevant coordinates for the specified file and return them as a list."

        # list of coordinates to be read in
        coordinates = ['latitude','longitude']
        logging.info("Listing coordinates: " + str(coordinates))	    
        
        # in this case, the coord information is in a separate file
        filenames=['seviri-geolocation.hdf']
        
        # get coord data
        sdata,vdata = hdf.read(filenames,coordinates)
        lat = sdata['latitude']
        lon = sdata['longitude']
        
        # mask out fill values
        lat_data = hdf.read_data(lat,"SD",[999.9])
        lon_data = hdf.read_data(lon,"SD",[999.9])

	    # create metedata
        logging.info("gathering coordinates metadata")
        lat_metadata = Metadata(name='latitude',units='degrees', missing_value=999.9)
        lon_metadata = Metadata(name='longitude',units='degrees',missing_value=999.9)

	    # create x and y coord objects to be passed back to CIS
        lon_coord = Coord(lon_data, lon_metadata,'X')
        lat_coord = Coord(lat_data, lat_metadata,'Y')

        return CoordList([lat_coord,lon_coord])