from utils.math import data_extraction
from utils.files.input import ScannedObject
from utils.settings.SettingManager import SettingManager

def progressbar_placeholder(percent:int):
    """
    This function is a placeholder for a progressbar function
    """

def get_raw_data(obj:ScannedObject, ndigits:int,delta_z:float=1,update_progress_bar = progressbar_placeholder)->dict:
    """
    Calculates data from the given object

    :param obj: Object to analyse
    :param ndigits: Number of digits to keep after the comma
    :return: dict(str:list) with the following keys:
        - X (en mm)     : list of x values
        - Y (en mm)     : list of y values
        - Z (en mm)     : list of z values
        - teta (en rad) : list of teta values
        - rayon (en mm) : list of radius values
        - Xi-Xmoy       : list of Xi-Xmoy values
        - Yi-Ymoy       : list of Yi-Ymoy values
    """
    colones = ["X (en mm)", "Y (en mm)", "Z (en mm)", "teta (en rad)", "rayon (en mm)","Xi-Xmoy","Yi-Ymoy"]
    data = {}
    for colone in colones:
        data[colone] = []
    discrete_vertices = obj.get_discrete_vertices(delta_z)
    progress = 0
    for discrete_values in discrete_vertices:
        mean_x ,mean_y, mean_z = data_extraction.get_x_y_z_mean(discrete_values)
        for x,y,z in discrete_values:
            data["X (en mm)"].append(round(x, ndigits))
            data["Y (en mm)"].append(round(y, ndigits))
            data["Z (en mm)"].append(round(z, ndigits))
            data["teta (en rad)"].append(round(data_extraction.get_teta_from_x_y(x,y,mean_x,mean_y), ndigits))
            data["rayon (en mm)"].append(round(data_extraction.get_radius_from_x_y(x,y,mean_x,mean_y), ndigits))
            data["Xi-Xmoy"].append(round(x-mean_x, ndigits))
            data["Yi-Ymoy"].append(round(y-mean_y, ndigits))
        update_progress_bar(int(progress/len(discrete_vertices)*100))
        progress += 1
    return data

def get_discrete_data(obj:ScannedObject, ndigits:int, delta_z:float=1, update_progress_bar= progressbar_placeholder)->dict:
    """
    Calculates data from the given object

    :param obj: Object to analyse
    :param ndigits: Number of digits to keep after the comma
    :return: dict(str:list) with the following keys:
        - X moy (en mm)             : list of x mean values
        - Y moy (en mm)             : list of y mean values
        - Z moy (en mm)             : list of z mean values
        - Rayon moyen (en mm)       : list of mean radius values
        - Rayon ecart type (en mm)  : list of radius standard deviation values
    """
    colones = ["X moy (en mm)", "Y moy (en mm)", "Z moy (en mm)","Discretisation(en mm)","Rayon moyen (en mm)","Rayon ecart type (en mm)"]
    data = {}
    for colone in colones:
        data[colone] = []
    if SettingManager.get_instance().get_setting("discretisation_method") == "Z0-Zi < DeltaZ":
        get_discrete_vertices = obj.get_discrete_vertices
    else:
        get_discrete_vertices = obj.get_discrete_vertices2 

    discrete_vertices = get_discrete_vertices(delta_z)
    progress = 0
    for discrete_values in discrete_vertices:
        x,y,z = data_extraction.get_x_y_z_mean(discrete_values)
        data["X moy (en mm)"].append(round(x, ndigits))
        data["Y moy (en mm)"].append(round(y, ndigits))
        data["Z moy (en mm)"].append(round(z, ndigits))
        first = discrete_values[0]
        last = discrete_values[-1]
        data["Discretisation(en mm)"].append(round(last[2]-first[2],ndigits))
        data["Rayon moyen (en mm)"].append(round(data_extraction.get_mean_radius(discrete_values), ndigits))
        data["Rayon ecart type (en mm)"].append(round(data_extraction.get_radius_std(discrete_values), ndigits))
        update_progress_bar(int(progress/len(discrete_vertices)*100))
        progress += 1
    return data