コード例 #1
0
            true_opt_x=symmetric_matrix_to_vector_mandel(true_sigma)[None],
            alpha=0.25,
            n_elems=20,
            n_elems_h=10)
        ax.set_title('Acquisition function', fontsize=50)
        plt.show()

        # Plot the GP
        fig = plt.figure(figsize=(10, 10))
        ax = Axes3D(fig)
        bo_plot_gp_spd(
            ax,
            model,
            r_cone=r_cone,
            xs=bo_optimizer.acquisition.data[0],
            opt_x=Bopt.x,
            true_opt_x=symmetric_matrix_to_vector_mandel(true_sigma)[None],
            true_opt_y=true_opt_val,
            max_colors=max_colors,
            alpha=0.25,
            n_elems=20,
            n_elems_h=10)
        ax.set_title('GP mean', fontsize=50)
        plt.show()

    if display_figures:
        # Plot test function with SPD inputs
        # 3D figure
        fig = plt.figure(figsize=(5, 5))
        ax = Axes3D(fig)
        # Make the panes transparent
        ax.xaxis.set_pane_color((1.0, 1.0, 1.0, 0.0))
コード例 #2
0
            alpha=0.25,
            n_elems=20,
            n_elems_h=10)
        ax.set_title('Acquisition function', fontsize=50)
        plt.show()

        # Plot the GP
        fig = plt.figure(figsize=(10, 10))
        ax = Axes3D(fig)
        bo_plot_gp_spd(
            ax,
            model,
            r_cone=r_cone,
            xs=x_eval_vec,
            opt_x=opt_x_vec,
            true_opt_x=symmetric_matrix_to_vector_mandel(true_sigma)[None],
            true_opt_y=true_opt_val,
            chol=True,
            alpha=0.25,
            max_colors=max_colors,
            n_elems=20,
            n_elems_h=10)
        ax.set_title('GP mean', fontsize=50)
        plt.show()

    if display_figures:
        # Plot test function with SPD inputs
        # 3D figure
        fig = plt.figure(figsize=(5, 5))
        ax = Axes3D(fig)
        # Make the panes transparent
コード例 #3
0
ファイル: bo_cholesky_spd.py プロジェクト: roothyb/GaBOtorch
        best_x[n] = symmetric_matrix_to_vector_mandel(best_x_mat[n])

    if disp_fig:
        # Plot acquisition function
        fig = plt.figure(figsize=(5, 5))
        ax = Axes3D(fig)
        bo_plot_acquisition_spd(ax, acq_fct, r_cone=r_cone, xs=x_eval, opt_x=best_x[-1][None],
                                true_opt_x=true_min_vec, n_elems=20, n_elems_h=10)
        ax.set_title('Acquisition function', fontsize=20)
        plt.show()

        # Plot GP
        fig = plt.figure(figsize=(5, 5))
        ax = Axes3D(fig)
        bo_plot_gp_spd(ax, model, r_cone=r_cone, xs=x_eval, opt_x=best_x[-1][None], true_opt_x=true_min_vec,
                       true_opt_y=true_opt_val, max_colors=25., n_elems=20,
                       n_elems_h=10)
        ax.set_title('GP mean', fontsize=20)
        plt.show()

    if dim == 2:
        # Plot convergence on the sphere
        # 3D figure
        fig = plt.figure(figsize=(5, 5))
        ax = Axes3D(fig)

        # Make the panes transparent
        ax.xaxis.set_pane_color((1.0, 1.0, 1.0, 0.0))
        ax.yaxis.set_pane_color((1.0, 1.0, 1.0, 0.0))
        ax.zaxis.set_pane_color((1.0, 1.0, 1.0, 0.0))