#!/usr/bin/python
# -*- coding: utf-8 -*-
# \file AttributeProfiles.py
# \brief TODO
# \author Florent Guiotte <florent.guiotte@gmail.com>
# \version 0.1
# \date 04 avril 2018
#
# TODO details

from .core import Filter, Stack

## TODO: dep
import sys
import numpy as np
sys.path.append('../triskele/python')
import triskele

class AttributeProfiles(Filter):
    def __init__(self, area=None, sd=None, moi=None):
        super().__init__(self.__class__.__name__)
        self.area = np.sort(area) if area is not None else None
        self.sd   = np.sort(sd) if sd is not None else None
        self.moi  = np.sort(moi) if moi is not None else None

    def _process_desc(self):
        att_desc = dict()
        for att in ['area', 'sd', 'moi']:
            att_desc[att] = list()
            if self.__getattribute__(att) is not None:
                att_desc[att].extend(
                  ['Thickening {} {}'.format(att, x) for x in self.__getattribute__(att)[::-1]])
                att_desc[att].append(None)
                att_desc[att].extend(
                  ['Thinning {} {}'.format(att, x) for x in self.__getattribute__(att)])

        return att_desc

    def _process_offset(self):
        att_offset = dict()
        for att in ['area', 'sd', 'moi']:
            values = self.__getattribute__(att)
            att_offset[att] = len(values) * 2 + 1 if values is not None else 0
        return att_offset

    def _process(self, data, metadata):
        t       = triskele.Triskele(data, verbose=False)
        att_min = t.filter(tree='min-tree', area=self.area,
                              standard_deviation=self.sd,
                              moment_of_inertia=self.moi)
        att_max = t.filter(tree='max-tree', area=self.area,
                              standard_deviation=self.sd,
                              moment_of_inertia=self.moi)

        ## Merge filtering as APs

        ## Create new metadata
        ### Pre-process descriptions
        att_desc = self._process_desc()

        ### Compute stack offsets
        att_offset = self._process_offset()
        stack_offset = sum(att_offset.values())

        ### Merge old and new descriptions
        metadata_new = list()
        for stack in metadata:
            if stack.end - stack.begin > 1:
                raise NotImplementedError('Nested filtering not implemented yet')

            for att in ['area', 'sd', 'moi']:
                stack_new = Stack(stack_offset * stack.begin, att_offset[att], 
                        stack.desc[0], stack.symb[0])

                for old_desc, new_desc in zip(stack_new.desc, att_desc[att]):
                    print('DESCRIPTION: {} > {}'.format(old_desc, new_desc))
                    old_desc.append(new_desc)

                metadata_new.append(stack_new)


        att = np.dstack((att_min, att_max))

        return att, metadata_new

if __name__ == '__main__':
    area = [10, 100, 1000]
    sd   = [.1, .9]

    ap = AttributeProfiles(area, sd)

    print(ap._process_desc())
    print(ap._process_offset())