# -*- coding: utf-8 -*-
#!/usr/local/bin/python

"""
Description :
-------------
    BUT REALISER UNE MOYENNE D'IMAGE SUR JEU DE DONNEEES A LA FOIS TEMPORELLE (fichier(s) en entrée) ET SPATIALE (subsetting)
Usage :
-------

                                                                                                      
    EN COMMANDES UNIX : exemple : python MEAN_IMAGE.py  -s [valeurs_du_subsetting] -d nom_du_sds -f filename (pour l'enregistrment en .png ou hdf) chemin_de_lecture_du_ou_des_fichiers.hdf + autres options               
                                      

Example :
---------

Prerequisites :
---------------
   python >= 2.5 ; not tested but probably all versions

Author :
--------
   CGTD-ICARE/UDEV Nicolas THOMAS ( nicolas.thomas-at-icare.univ-lille1.fr  )

License :
---------
   This file must be used under the terms of the CeCILL.
   This source file is licensed as described in the file COPYING, which
   you should have received as part of this distribution.  The terms
   are also available at
   http://www.cecill.info/licences/Licence_CeCILL_V2-en.txt

History :
---------
v0.0.0 : 2009/12/01
- creation
""" 
import sys,re
from Average_management import prog_options,get_name_sds,image_size,subsetting
from pyhdf.SD import*
from hdf2img.data2img import *

def get_display_save_image(options,args,row_min,row_max,col_min,col_max) :

    
    if options.sensor is None :
        msg="Error : the sensor's name must be indicated. Example : -r SEVIRI, -r PARASOL, -r MODIS, ..."
	raise ValueError(msg)
    hdf_name=args[0]
    
    if re.search('/',args[0]) :
        f=hdf_name.split('/')[-1]
        hdf_name_im=str(f[:-4])
        
    else :
        hdf_name_im=str(args[0][:-4])+'_'
        
    hdf_file = SD(hdf_name)
    datasets=hdf_file.datasets().keys()
    
    
    for name in datasets :
        
        if re.search('nb_data',name):
            sds=hdf_file.select(name).get()
            sds=sds[row_min:row_max,col_min:col_max]
            sds_numpy_obj=data2img(sds,colormap="blue_red")
            filename=options.output_directory+'/'+hdf_name_im+'_'+name+'.png'
            sds_numpy_obj.save(filename)
            
        elif re.search('mean',name):
            if re.search('SEVIRI',options.sensor):  
                options.valmin=0.
                options.valmax=256.                                          
                sds=hdf_file.select(name).get()
                sds=sds[row_min:row_max,col_min:col_max]
                sds_numpy_obj=data2img(sds,colormap="met",val_min=options.valmin,val_max=options.valmax)
                filename=options.output_directory+'/'+hdf_name_im+'_'+name+'.png'
                sds_numpy_obj.save(filename)
            else :
                sds=hdf_file.select(name).get()
                sds=sds[row_min:row_max,col_min:col_max]
                if options.valmax is None : options.valmax=sds.max()
                if options.valmin is None : options.valmin=sds.min()
                _fill_value=hdf_file.select(name).getfillvalue()
                sds_numpy_obj=data2img(sds,colormap="blue_red",val_min=options.valmin,val_max=options.valmax,invalid_val=_fill_value)
                filename=options.output_directory+'/'+hdf_name_im+'_'+name+'.png'
                sds_numpy_obj.save(filename)
        else : 
            if re.search('SEVIRI',options.sensor):  
               options.valmin=0.
               options.valmax=256.
               sds=hdf_file.select(name).get() 
               sds=sds[row_min:row_max,col_min:col_max]                               
               sds_numpy_obj=data2img(sds,colormap="met",val_min=options.valmin,val_max=options.valmax)
               filename=options.output_directory+'/'+hdf_name_im+'_'+name+'.png'
               sds_numpy_obj.save(filename)
            else :
               sds=hdf_file.select(name).get()
               sds=sds[row_min:row_max,col_min:col_max]
               _fill_value=hdf_file.select(name).getfillvalue()
               valmin=sds.min()
               valmax=sds.max()
               sds_numpy_obj=data2img(sds,colormap="blue_red",val_max=valmax,val_min=valmin) 
               filename=options.output_directory+'/'+hdf_name_im+'_'+name+'.png'
               sds_numpy_obj.save(filename)
#
#_____________________________________________________
#            
def main() :

    print "  ----------------------------- Save hdf's datasets to .png ---------------------------"
    print "\n"
    
    list_parameters=sys.argv
  
    options,args=prog_options ( list_parameters )

    sds_name=options.dataset
    
    sds_name=get_name_sds(options,args)
    
    lin,col=image_size(args,sds_name,options)
    
    row_min,row_max,col_min,col_max=subsetting(options,lin,col)

    im=get_display_save_image(options,args,row_min,row_max,col_min,col_max)
     
    print "  ---------------------- Fin du programme Average_display_image.py --------------------"
    
#
#_____________________________________________________
#

if __name__== "__main__":

    import time
    
    start_time=time.time()
    
    main()
    
    end_time=time.time()
    
    print "elapsed time :"+time.strftime("%H:%M:%S",time.gmtime(end_time-start_time))+"######\n"