Options to save RunningMetric plots

[rabiu42000]

I am running optimization in a loop. At each iteration I want to to save RunningMetric plots with command such as plt.savefig(filename) instead of output into the IDE display. Is there an option to save each plot after each iteration in the loop?

[blankjul]

This is possible but with a more hacky solution. Simply define your own running metric based on ours and store the files.
You can also define it more generic in the class itself.

import matplotlib.pyplot as plt
import numpy as np

from pymoo.util.termination.f_tol import MultiObjectiveSpaceToleranceTerminationWithRenormalization
from pymoo.visualization.video.callback_video import AnimationCallback


class RunningMetric(AnimationCallback):

    def __init__(self,
                 delta_gen,
                 n_plots=4,
                 only_if_n_plots=False,
                 key_press=True,
                 **kwargs) -> None:

        super().__init__(**kwargs)
        self.delta_gen = delta_gen
        self.key_press = key_press
        self.only_if_n_plots = only_if_n_plots
        self.term = MultiObjectiveSpaceToleranceTerminationWithRenormalization(n_last=100000,
                                                                               all_to_current=True,
                                                                               sliding_window=False)
        self.hist = []
        self.n_plots = n_plots

    def do(self, _, algorithm, force_plot=False, **kwargs):
        self.term.do_continue(algorithm)

        metric = self.term.get_metric()
        metrics = self.term.metrics
        tau = len(metrics)

        if metric is not None and (tau + 1) % self.delta_gen == 0 or force_plot:

            _delta_f = metric["delta_f"]
            _delta_ideal = [m['delta_ideal'] > 0.005 for m in metrics]
            _delta_nadir = [m['delta_nadir'] > 0.005 for m in metrics]

            if force_plot or not self.only_if_n_plots or (self.only_if_n_plots and len(self.hist) == self.n_plots - 1):

                fig, ax = plt.subplots()

                if self.key_press:
                    def press(event):
                        if event.key == 'q':
                            algorithm.termination.force_termination = True

                    fig.canvas.mpl_connect('key_press_event', press)

                for k, f in self.hist:
                    ax.plot(np.arange(len(f)) + 1, f, label="t=%s" % (k+1), alpha=0.6, linewidth=3)
                ax.plot(np.arange(len(_delta_f)) + 1, _delta_f, label="t=%s (*)" % (tau+1), alpha=0.9, linewidth=3)

                for k in range(len(_delta_ideal)):
                    if _delta_ideal[k] or _delta_nadir[k]:
                        ax.plot([k+1, k+1], [0, _delta_f[k]], color="black", linewidth=0.5, alpha=0.5)
                        ax.plot([k+1], [_delta_f[k]], "o", color="black", alpha=0.5, markersize=2)

                ax.set_yscale("symlog")
                ax.legend()

                ax.set_xlabel("Generation")
                ax.set_ylabel("$\Delta \, f$", rotation=0)

                if self.key_press:
                    plt.draw()
                    plt.waitforbuttonpress()
                    plt.close('all')

            self.hist.append((tau, _delta_f))
            self.hist = self.hist[-(self.n_plots - 1):]

[rabiu42000]

Thank you very much. This worked