epidemioptim/analysis/plots.py
def pareto_plot(central, error):
    """
    Plots a Pareto front for a given algorithm. (Ellipses show errors in two dimensions).
    Parameters
    ----------
    central: 2D nd.array
        Coordinates of solutions from the Pareto front.
    error: 2D nd.array
        Error measures of solutions from the Pareto front.

    """
    n_points = central.shape[0]
    artists, ax = setup_figure()
    if PLOT_STD:
        ellipses = []
        for i in range(n_points):
            ellipses.append(Ellipse(xy=central[i],
                                    width=error[i][0],
                                    height=error[i][1],
                                    alpha=0.1))
        for e in ellipses:
            ax.add_artist(e)
            e.set_clip_box(ax.bbox)
            e.set_facecolor('r')

    plt.scatter(central[:, 0], central[:, 1], s=SCATTER_WIDTH, color='r')
    return artists

    Plots a Pareto front for a given algorithm. (Ellipses show errors in two dimensions).
    Parameters
    ----------
    central: 2D nd.array
        Coordinates of solutions from the Pareto front.
    error: 2D nd.array
        Error measures of solutions from the Pareto front.

    
Plots a Pareto front for a given algorithm. (Ellipses show errors in two dimensions).
Parameters

2D nd.array
Coordinates of solutions from the Pareto front.
error: 2D nd.array
Error measures of solutions from the Pareto front.
Plots a Pareto front for a given algorithm . ( Ellipses show errors in two dimensions ) . Parameters 2D nd . array Coordinates of solutions from the Pareto front . error : 2D nd . array Error measures of solutions from the Pareto front .
def pareto_plot(central, error):
    n_points = central.shape[0]
    artists, ax = setup_figure()
    if PLOT_STD:
        ellipses = []
        for i in range(n_points):
            ellipses.append(Ellipse(xy=central[i],
                                    width=error[i][0],
                                    height=error[i][1],
                                    alpha=0.1))
        for e in ellipses:
            ax.add_artist(e)
            e.set_clip_box(ax.bbox)
            e.set_facecolor('r')
    plt.scatter(central[:, 0], central[:, 1], s=SCATTER_WIDTH, color='r')
    return artists
def pareto_plot ( central , error ) : n_points = central . shape [ 0 ] artists , ax = setup_figure ( ) if PLOT_STD : ellipses = [ ] for i in range ( n_points ) : ellipses . append ( Ellipse ( xy = central [ i ] , width = error [ i ] [ 0 ] , height = error [ i ] [ 1 ] , alpha = 0.1 ) ) for e in ellipses : ax . add_artist ( e ) e . set_clip_box ( ax . bbox ) e . set_facecolor ( 'r' ) plt . scatter ( central [ : , 0 ] , central [ : , 1 ] , s = SCATTER_WIDTH , color = 'r' ) return artists
Plots a Pareto front for a given algorithm.
Plots a Pareto front for a given algorithm .
"""
    Plots a Pareto front for a given algorithm. (Ellipses show errors in two dimensions).
    Parameters
    ----------
    central: 2D nd.array
        Coordinates of solutions from the Pareto front.
    error: 2D nd.array
        Error measures of solutions from the Pareto front.

    """
central
error