surface_plot.py

import scipy.linalg
from mpl_toolkits.mplot3d import axes3d
from matplotlib.ticker import MaxNLocator
import itertools
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import cm
import matplotlib
plt.rcParams['svg.fonttype'] = 'none'


def polyfit2d(x, y, z, order=3):
    z = np.array(list(map(int, z)))
    ncols = (order + 1)**2
    G = np.zeros((x.size, ncols))
    ij = itertools.product(range(order+1), range(order+1))
    for k, (i, j) in enumerate(ij):
        G[:, k] = x**i * y**j
    m, _, _, _ = np.linalg.lstsq(G, z, rcond=None)
    return m


def polyval2d(x, y, m):
    order = int(np.sqrt(len(m))) - 1
    ij = itertools.product(range(order+1), range(order+1))
    z = np.zeros_like(x, dtype='float64')
    for a, (i, j) in zip(m, ij):
        z += a * x**i * y**j
    return z


if __name__ == "__main__":

    # wykres powierzchniowy
    with open('./output_data/acc/filter_size_2.csv') as f:
        X, Y, data_3 = [], [], []
        set_y, size = set(), 0

        for line in f:
            x, y, z = [float(s) for s in line.split(';')]
            set_y.add(y)
            X.append(x)
            Y.append(y)
            data_3.append(z)
        size = len(set_y)

        X = np.array(X)
        Y = np.array(Y)
        # data_3 = np.array(data_3).reshape((size,-1))
        data_3 = np.array(data_3)

        data_1 = X.reshape((-1, size))
        data_2 = Y.reshape((-1, size))

    data = np.c_[X, Y, data_3]
    mn = np.min(data, axis=0)
    mx = np.max(data, axis=0)

    Z = polyval2d(data_1, data_2, polyfit2d(data_1.flatten(), data_2.flatten(), data_3))

    fig = plt.figure()
    ax = plt.axes(projection='3d')
    plt.xlabel('ilość filtrów warstwa 1.')
    plt.ylabel('ilość filtrów warstwa 2.')
    ax.set_zlabel('ACC[%]')

    # plt.xticks(np.arange(1, 101, step=10))
    # plt.yticks(np.arange(1, 41, step=10))
    ax.plot_surface(data_2, data_1,  Z, cmap=cm.coolwarm,
                    rstride=1, cstride=1, linewidth=2, antialiased=True)
    # ax.scatter(X, Y, data_3, c='r', s=50)
    plt.show()