import random as rn
import time
import numpy as np
import helpers as hp
import functions as f


def get_G(x):
    return (np.sum(np.array(x), axis=0)/len(x)).tolist()


def get_P(centroid, w):
    doubled_G = [2*x for x in centroid]
    return [doubled_G[i] - w[i] for i in range(len(centroid))]


def get_Q(centroid, w):
    added = [centroid[i] + w[i] for i in range(len(centroid))]
    return [0.5*x for x in added]


def get_R(centroid, w):
    return [4*centroid[i] - 3*w[i] for i in range(len(centroid))]


def CRS3(FUNCTION_NUMBER, vec_len):
    final_result = list()
    rn.seed(1)
    N = 800
    iterations = 20000
    start_rand = time.time()
    A = eval('f.generate_points_func_' + str(FUNCTION_NUMBER) + '(N, vec_len)')
    start_iter = time.time()
    for iteration in range(iterations):

        i_W = np.argmax(np.array(A).T[-1])
        W = A[i_W]

        A_exclude_W = A.copy()
        A_exclude_W.remove(W)

        R_chosen = rn.sample(A_exclude_W, vec_len)

        i_S = np.argmax(np.array(A_exclude_W).T[-1])
        S = A_exclude_W[i_S]

        centroid = get_G(R_chosen)

        P = get_P(centroid, W)
        Q = get_Q(centroid, W)
        R = get_R(centroid, W)

        if f.is_point_in_domain(P):

            P[-1] = eval('f.function_' + str(FUNCTION_NUMBER) + '(P[:-1])')

            if P[-1] < S[-1]:
                if not f.is_point_in_domain(R):
                    W = P
                    A[i_W] = P
                    final_result.append(P[-1])
                else:
                    R[-1] = eval('f.function_' + str(FUNCTION_NUMBER) + '(R[:-1])')
                    if R[-1] < S[-1]:
                        W = R
                        A[i_W] = R
                        final_result.append(R[-1])
                    else:
                        W = P
                        A[i_W] = P
                        final_result.append(P[-1])
        else:
            if not f.is_point_in_domain(Q):
                continue
            else:
                Q[-1] = eval('f.function_' + str(FUNCTION_NUMBER) + '(Q[:-1])')
                if Q[-1] < S[-1]:
                    W = Q
                    A[i_W] = Q
                    final_result.append(Q[-1])
                else:
                    continue
        if iteration % 100 == 0:
            print(str(iteration) + ' Kolejna wartość P' + str(P))

            if iteration // 100 < 10:
                f_name = 'results/CRS3_00{}'.format(iteration // 100)
            elif iteration // 100 < 100:
                f_name = 'results/CRS3_0{}'.format(iteration // 100)
            else:
                f_name = 'results/CRS3_{}'.format(iteration // 100)

            hp.plot_3d_scatter(whole_set=A,
                               centroid=centroid,
                               r_last=W,
                               optimum=P,
                               f_name=f_name,
                               func_number=FUNCTION_NUMBER)

    hp.plot_convergence(final_result)
    end = time.time()
    iter_time = end - start_iter
    rand_time = start_iter - start_rand
    full_time = end - start_rand

    return (iter_time, rand_time, full_time, final_result[-1])


if __name__ == '__main__':
    CRS3(1, 2)



import random as rn
import time
import numpy as np
import helpers as hp
import functions as f


def get_G(x):
    return (np.sum(np.array(x), axis=0)/len(x)).tolist()


def get_P(centroid, w):
    doubled_G = [2*x for x in centroid]
    return [doubled_G[i] - w[i] for i in range(len(centroid))]


def get_Q(centroid, w):
    added = [centroid[i] + w[i] for i in range(len(centroid))]
    return [0.5*x for x in added]


def get_R(centroid, w):
    return [4*centroid[i] - 3*w[i] for i in range(len(centroid))]


def CRS3(FUNCTION_NUMBER, vec_len):
    final_result = list()
    rn.seed(1)
    N = 800
    iterations = 20000
    start_rand = time.time()
    A = eval('f.generate_points_func_' + str(FUNCTION_NUMBER) + '(N, vec_len)')
    start_iter = time.time()
    for iteration in range(iterations):

        i_W = np.argmax(np.array(A).T[-1])
        W = A[i_W]

        A_exclude_W = A.copy()
        A_exclude_W.remove(W)

        R_chosen = rn.sample(A_exclude_W, vec_len)

        i_S = np.argmax(np.array(A_exclude_W).T[-1])
        S = A_exclude_W[i_S]

        centroid = get_G(R_chosen)

        P = get_P(centroid, W)
        Q = get_Q(centroid, W)
        R = get_R(centroid, W)

        if f.is_point_in_domain(P):

            P[-1] = eval('f.function_' + str(FUNCTION_NUMBER) + '(P[:-1])')

            if P[-1] < S[-1]:
                if not f.is_point_in_domain(R):
                    W = P
                    A[i_W] = P
                    final_result.append(P[-1])
                else:
                    R[-1] = eval('f.function_' + str(FUNCTION_NUMBER) + '(R[:-1])')
                    if R[-1] < S[-1]:
                        W = R
                        A[i_W] = R
                        final_result.append(R[-1])
                    else:
                        W = P
                        A[i_W] = P
                        final_result.append(P[-1])
        else:
            if not f.is_point_in_domain(Q):
                continue
            else:
                Q[-1] = eval('f.function_' + str(FUNCTION_NUMBER) + '(Q[:-1])')
                if Q[-1] < S[-1]:
                    W = Q
                    A[i_W] = Q
                    final_result.append(Q[-1])
                else:
                    continue
        if iteration % 100 == 0:
            print(str(iteration) + ' Kolejna wartość P' + str(P))

            if iteration // 100 < 10:
                f_name = 'results/CRS3_00{}'.format(iteration // 100)
            elif iteration // 100 < 100:
                f_name = 'results/CRS3_0{}'.format(iteration // 100)
            else:
                f_name = 'results/CRS3_{}'.format(iteration // 100)

            hp.plot_3d_scatter(whole_set=A,
                               centroid=centroid,
                               r_last=W,
                               optimum=P,
                               f_name=f_name,
                               func_number=FUNCTION_NUMBER)

    hp.plot_convergence(final_result)
    end = time.time()
    iter_time = end - start_iter
    rand_time = start_iter - start_rand
    full_time = end - start_rand

    return (iter_time, rand_time, full_time, final_result[-1])


if __name__ == '__main__':
    CRS3(1, 2)


