#!/usr/bin/env python

"""Implementation of K coefficient and K-modified coefficient.
"""

__author__ = "Théo de la Hogue"
__credits__ = []
__copyright__ = "Copyright 2023, Ecole Nationale de l'Aviation Civile (ENAC)"
__license__ = "BSD"

from dataclasses import dataclass

from argaze import GazeFeatures

import numpy

@dataclass
class ScanPathAnalyzer(GazeFeatures.ScanPathAnalyzer):
    """Implementation of the K coefficient algorithm as described in:

        **Krejtz K., Duchowski A., Krejtz I., Szarkowska A., & Kopacz A. (2016).**  
        *Discerning ambient/focal attention with coefficient K.*  
        ACM Transactions on Applied Perception (TAP, 1–20).  
        [https://doi.org/10.1145/2896452](https://doi.org/10.1145/2896452)
    """

    def __post_init__(self):

        pass

    def analyze(self, scan_path: GazeFeatures.ScanPathType) -> float:
        """Analyze scan path."""

        assert(len(scan_path) > 1)

        durations = []
        amplitudes = []

        for scan_step in scan_path:

            durations.append(scan_step.duration)
            amplitudes.append(scan_step.last_saccade.amplitude)

        durations = numpy.array(durations)
        amplitudes = numpy.array(amplitudes)

        duration_mean = numpy.mean(durations)
        amplitude_mean = numpy.mean(amplitudes)

        duration_std = numpy.std(durations)
        amplitude_std = numpy.std(amplitudes)

        Ks = []
        for scan_step in scan_path:

            Ks.append(((scan_step.duration - duration_mean) / duration_std) - ((scan_step.last_saccade.amplitude - amplitude_mean) / amplitude_std))

        K = numpy.array(Ks).mean()

        return K

@dataclass
class AOIScanPathAnalyzer(GazeFeatures.AOIScanPathAnalyzer):
    """Implementation of the K-modified coefficient algorithm as described in:

        **Lounis, C. A., Hassoumi, A., Lefrancois, O., Peysakhovich, V., & Causse, M. (2020, June).**  
        *Detecting ambient/focal visual attention in professional airline pilots with a modified Coefficient K: a full flight simulator study.*  
        ACM Symposium on Eye Tracking Research and Applications (ETRA'20, 1-6).  
        [https://doi.org/10.1145/3379157.3391412](https://doi.org/10.1145/3379157.3391412)
    """

    def __post_init__(self):

        pass

    def analyze(self, aoi_scan_path: GazeFeatures.AOIScanPathType) -> float:
        """Analyze aoi scan path."""

        assert(len(aoi_scan_path) > 1)

        durations = []
        amplitudes = []

        for aoi_scan_step in aoi_scan_path:

            durations.append(aoi_scan_step.duration)
            amplitudes.append(aoi_scan_step.last_saccade.amplitude)

        durations = numpy.array(durations)
        amplitudes = numpy.array(amplitudes)

        duration_mean = numpy.mean(durations)
        amplitude_mean = numpy.mean(amplitudes)

        duration_std = numpy.std(durations)
        amplitude_std = numpy.std(amplitudes)

        Ks = []
        for aoi_scan_step in aoi_scan_path:

            Ks.append(((aoi_scan_step.duration - duration_mean) / duration_std) - ((aoi_scan_step.last_saccade.amplitude - amplitude_mean) / amplitude_std))

        K = numpy.array(Ks).mean()

        return K