#!/usr/bin/env python

from __future__ import print_function

# @category Control Points
# @name     keep 5 CPs per image pair
# @api-min  2011.1
# @api-max  2016.2

#    top_five.py - keep the five best CPs for each image pair

#    Copyright (C) 2011  Kay F. Jahnke

#    This program is free software: you can redistribute it and/or modify
#    it under the terms of the GNU General Public License as published by
#    the Free Software Foundation, either version 3 of the License, or
#    (at your option) any later version.

#    This program is distributed in the hope that it will be useful,
#    but WITHOUT ANY WARRANTY; without even the implied warranty of
#    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
#    GNU General Public License for more details.

#    You should have received a copy of the GNU General Public License
#    along with this program.  If not, see <http://www.gnu.org/licenses/>.

# another demo plugin: this one will keep at most five control
# points per image pair. Selection is by CP error, the points
# with the smallest error are kept.

def entry ( pano ) :

    import hsi

    # on loading the CP errors are unknown - we have to have them
    # calculated before we can start:
    
    hsi.calcCtrlPointErrors(pano)

    # First we find out what pairs there are. We make a set
    # of these pairs and use them as index in a dictionary
    # with an empty list as value
    
    cpv = pano.getCtrlPoints()

    print ( 'found %d control points' % len ( cpv ) )
    
    pairs = set ( ( cp.image1Nr , cp.image2Nr ) for cp in cpv )
    cpdict = dict ( ( pair , [] ) for pair in pairs )

    # now each CP goes into the list indexed by the pair of
    # images it connects - but in a tuple with the error in front
    # se we can easily sort by error
    
    for cp in cpv :
        cpdict[(cp.image1Nr, cp.image2Nr)].append((cp.error, cp))

    # we extract the five values with the smallest error
    # from every list. The CPs in there are our top five,
    # so we put them into cpv
    
    cpv = []
    for pair in pairs :
        top_five = [ t[1] for t in sorted(cpdict[pair])[:5] ]
        cpv.extend ( top_five )

    # finally we attach the new CP vector to the panorama
    
    print ( 'keeping %d control points' % len ( cpv ) )
    pano.setCtrlPoints ( cpv )
    
    return 0

if __name__ == "__main__":

    print ( 'this script only runs as a hugin plugin.' )
