#!/usr/bin/python
# -*- coding: utf-8 -*-
# \file Normalize.py
# \brief TODO
# \author Florent Guiotte <florent.guiotte@gmail.com>
# \version 0.1
# \date 12 sept. 2018
#
# TODO details

from ld2dap.core import Filter
import numpy as np


class Normalize(Filter):
    """Normalize stream values
    
    This node will normalize values between min and max, unless dtype is
    provided.

    If dtype is not None, min and max will be set to dtype extremum.

    """

    def __init__(self, min=0., max=1., dtype=None):
        super().__init__(self.__class__.__name__)
        
        if dtype is not None:
            self.min = np.iinfo(dtype).min
            self.max = np.iinfo(dtype).max
        else:
            self.min = min
            self.max = max

    def _process(self, data, metadata):
        self.logger.info('Filtering')
        # TODO: see TODO from Treshold _process

        ## Channel independant scale
        for i in range(data.shape[2]):
            data[:,:,i] -= data[:,:,i].min() - self.min
            data[:,:,i] *= (self.max - self.min) / (data[:,:,i].max() - data[:,:,i].min())

        for stack in metadata:
            for d, s in zip(stack.desc, stack.symb):
                d.append('normalize [{}, {}]'.format(self.min, self.max))
                # s.append('T_{{{}}}'.format(self.treshold))

        return data, metadata