"""
Created on Mon Apr 17 2023
@name:   data_extraction.py
@desc:   This module contains some utility functions for math operations.
@auth:   Djalim Simaila
@e-mail: djalim.simaila@inrae.fr
"""
import numpy as np
import math

def get_mean(values:list):
    """
    Get the mean of the values.

    :param values: values
    :return: mean of the values

    :Example:
    >>> get_mean([1,2,3,4,5])
    3.0
    """
    return np.mean(values)

def get_standard_deviation(values:list):
    """
    Get the standard deviation of the values.

    :param values: values
    :return: standard deviation of the values

    :Example:
    >>> get_standard_deviation([1,2,3,4,5])
    1.4142135623730951
    """
    return np.std(values)

def get_x_y_z_mean(discrete_values:list):
    """
    Get the mean of the x and y coordinates in the discrete range.

    :param x: x coordinates
    :param y: y coordinates
    :return: mean of x and y coordinates in the discrete range

    :Example:
    >>> get_x_y_z_mean([(1,2,3),(4,5,6),(7,8,9)])
    (4.0, 5.0, 6.0)
    """
    x = [vertex[0] for vertex in discrete_values]
    y = [vertex[1] for vertex in discrete_values]
    z = [vertex[2] for vertex in discrete_values]
    return get_mean(x), get_mean(y), get_mean(z)

def get_radius_from_x_y(xi:float, yi:float, x_mean:float, y_mean:float):
    """
    Get the radius from the x and y coordinates.

    :param xi: x coordinate
    :param yi: y coordinate
    :param x_mean: mean of x coordinates in the discrete range
    :param y_mean: mean of y coordinates in the discrete range
    :return: radius for this point

    :Example:
    >>> get_radius_from_x_y(1,2,3,4)
    2.8284271247461903
    """
    return np.sqrt(np.power((xi - x_mean), 2) + np.power((yi - y_mean), 2))

def get_mean_radius(discrete_values:list):
    """
    Get the mean of the radius in the discrete range.

    :param discrete_values: discrete values
    :return: mean of the radius in the discrete range

    :Example:
    >>> get_mean_radius([(1,2,3),(4,5,6),(7,8,9)])
    2.82842712474619
    """
    x_mean, y_mean, z_mean = get_x_y_z_mean(discrete_values)
    radius = []
    for x,y,z in discrete_values:
        radius.append(get_radius_from_x_y(x,y,x_mean,y_mean))
    return get_mean(radius)

def get_radius_std(discrete_values:list):
    """
    Get the standard deviation of the radius in the discrete range.

    :param discrete_values: discrete values
    :return: standard deviation of the radius in the discrete range

    :Example:
    >>> get_radius_std([(1,2,3),(4,5,6),(7,8,9)])
    2.8284271247461903
    """
    x_mean, y_mean, z_mean = get_x_y_z_mean(discrete_values)
    radius = []
    for x,y,z in discrete_values:
        radius.append(get_radius_from_x_y(x,y,x_mean,y_mean))
    return get_standard_deviation(radius)

def get_mean_teta(discrete_values:list):
    """
    Get the mean of the teta in the discrete range.

    :param discrete_values: discrete values
    :return: mean of the teta in the discrete range

    :Example:
    >>> get_mean_teta([(1,2,3),(4,5,6),(7,8,9)])
    0.7853981633974483
    """
    x_mean, y_mean, z_mean = get_x_y_z_mean(discrete_values)
    teta = []
    for x,y,z in discrete_values:
        teta.append(get_teta_from_x_y(x,y,x_mean,y_mean))
    return get_mean(teta)

def get_teta_from_x_y(xi:float, yi:float, x_mean:float, y_mean:float):
    """
    Get the teta from the x and y coordinates.

    :param xi: x coordinate
    :param yi: y coordinate
    :param x_mean: mean of x coordinates in the discrete range
    :param y_mean: mean of y coordinates in the discrete range
    :return: teta for this point
    
    :Example:
    >>> get_teta_from_x_y(1,2,3,4)
    0.7853981633974483
    """
    return math.atan((xi - x_mean)/(yi - y_mean))

#todo fix examples
if __name__ == "__main__":
    import doctest
    doctest.testmod()