"""
Ce module contient des fonctions utilitaires
"""
from HMM import HMM


def normalize_probabilities(prob_fr: float, prob_en: float, prob_it: float, searched: float) -> float:
    sum = prob_fr + prob_en + prob_it

    # si on utilise une matrice identité en tant que matrice d'émission il y a de forte change d'avoir une somme à 0.
    if sum != 0:
        return searched / sum
    else:
        return searched # retourne 0


def forward_detection(hmm_fr: HMM, hmm_en: HMM, hmm_it: HMM, O: list[int]) -> tuple[str, float, list[float]]:
    """
    Prints the language detected with forward method
    :param hmm_fr: lambda_fr
    :param hmm_en: lambda_en
    :param hmm_it: lambda_it
    :param O: mot à détecter
    :return: Le langage détecté et la probabilité
    """
    res_fr, _ = hmm_fr.forward(O)
    res_en, _ = hmm_en.forward(O)
    res_it, _ = hmm_it.forward(O)

    proba_fr = normalize_probabilities(res_fr, res_en, res_it, res_fr)
    proba_en = normalize_probabilities(res_fr, res_en, res_it, res_en)
    proba_it = normalize_probabilities(res_fr, res_en, res_it, res_it)

    #print(f'FR={proba_fr}, EN={proba_en}, IT={proba_it}')

    probas: list[float] = [proba_fr, proba_en, proba_it]

    max_prob = proba_fr
    language_index = 0
    for index in range(1, len(probas)):
        if max_prob < probas[index]:
            max_prob = probas[index]
            language_index = index

    if language_index == 0:
        return 'Français', max_prob, [proba_fr, proba_en, proba_it]
    elif language_index == 1:
        return 'Anglais', max_prob, [proba_fr, proba_en, proba_it]
    else:
        return 'Italien', max_prob, [proba_fr, proba_en, proba_it]


def backward_detection(hmm_fr: HMM, hmm_en: HMM, hmm_it: HMM, O: str) -> tuple[str, float]:
    """
    Prints the language detected with backward method
    :param hmm_fr: lambda_fr
    :param hmm_en: lambda_en
    :param hmm_it: lambda_it
    :param O: mot à détecter
    :return: Langage détecté et probabilité
    """
    res_fr = hmm_fr.backward(O)
    res_en = hmm_en.backward(O)
    res_it = hmm_it.backward(O)

    proba_fr = normalize_probabilities(res_fr, res_en, res_it, res_fr)
    proba_en = normalize_probabilities(res_fr, res_en, res_it, res_en)
    proba_it = normalize_probabilities(res_fr, res_en, res_it, res_it)

    print(f'FR={proba_fr}, EN={proba_en}, IT={proba_it}')

    probas = [proba_fr, proba_en, proba_it]

    max_prob = proba_fr
    language_index = 0
    for index in range(1,len(probas)):
        if max_prob < probas[index]:
            max_prob = probas[index]
            language_index = index

    if language_index == 0:
        return 'Français', max_prob
    elif language_index == 1:
        return 'Anglais', max_prob
    else:
        return 'Italien', max_prob


def forward_detection_with_text(hmm_fr: HMM, hmm_en: HMM, hmm_it: HMM, O: list[list[int]]) -> dict:
    """

    :param hmm_fr: lambda fr
    :param hmm_en: lambda en
    :param hmm_it: lambda it
    :param O: Le texte en version index de l'alphabet
    :return: Le langage détecté
    """

    # Count the language détection occurrences
    french_prob_count = english_prob_count = italian_prob_count = 0

    for word in O:
        lang, _, _ = forward_detection(hmm_fr, hmm_en, hmm_it, word)
        match lang:
            case 'Français':
                french_prob_count += 1
            case 'Anglais':
                english_prob_count += 1
            case 'Italien':
                italian_prob_count += 1

    total_sum = french_prob_count + english_prob_count + italian_prob_count

    return {'french': french_prob_count / total_sum, 'english': english_prob_count / total_sum, 'italian': italian_prob_count / total_sum}