#!/usr/bin/env python

"""N-Gram module.
"""

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

from typing import TypeVar, Tuple, Any
from dataclasses import dataclass, field

from argaze import GazeFeatures, DataFeatures

@dataclass
class AOIScanPathAnalyzer(GazeFeatures.AOIScanPathAnalyzer):
    """Implementation of N-Gram algorithm as proposed in:

        **Lounis C., Peysakhovich V., Causse M. (2021).**  
        *Visual scanning strategies in the cockpit are modulated by pilots’ expertise: A flight simulator study.*  
        PLoS ONE (16(2), 6).  
        [https://doi.org/10.1371/journal.pone.0247061](https://doi.org/10.1371/journal.pone.0247061)
    """

    n_min: int = field(default=2)
    """Minimal grams length to search."""

    n_max: int = field(default=2)
    """Maximal grams length to search."""

    def __post_init__(self):

        super().__init__()

        self.__ngrams_count = {}

    @DataFeatures.PipelineStep
    def analyze(self, aoi_scan_path: GazeFeatures.AOIScanPathType):

        assert(len(aoi_scan_path) > 1)

        sequence = aoi_scan_path.letter_sequence

        self.__ngrams_count = {}

        for n in range(self.n_min, self.n_max + 1):

            ngrams = zip(*[sequence[i:] for i in range(n)])
            ngrams = [ngram for ngram in ngrams]

            self.__ngrams_count[n] = {tuple([aoi_scan_path.get_letter_aoi(l) for l in ngram]) : ngrams.count(ngram) for ngram in ngrams}

    @property
    def ngrams_count(self) -> dict:
        """N-Grams count."""
        
        return self.__ngrams_count