def simulate()

in simulation/decai/simulation/simulate.py [0:0]

• 70 lines of code
• 5 McCabe index (conditional complexity)

    def simulate(self,
                 agents: List[Agent],
                 baseline_accuracy: float = None,
                 init_train_data_portion: float = 0.1,
                 pm_test_sets: list = None,
                 accuracy_plot_wait_s=2E5,
                 train_size: int = None, test_size: int = None,
                 filename_indicator: str = None
                 ):
        """
        Run a simulation.

        :param agents: The agents that will interact with the data.
        :param baseline_accuracy: The baseline accuracy of the model.
            Usually the accuracy on a hidden test set when the model is trained with all data.
        :param init_train_data_portion: The portion of the data to initially use for training. Must be [0,1].
        :param pm_test_sets: The test sets for the prediction market incentive mechanism.
        :param accuracy_plot_wait_s: The amount of time to wait in seconds between plotting the accuracy.
        :param train_size: The amount of training data to use.
        :param test_size: The amount of test data to use.
        :param filename_indicator: Path of the filename to create for the run.
        """

        assert 0 <= init_train_data_portion <= 1

        # Data to save.
        save_data = dict(agents=[asdict(a) for a in agents],
                         baselineAccuracy=baseline_accuracy,
                         initTrainDataPortion=init_train_data_portion,
                         accuracies=[],
                         balances=[],
                         )
        time_for_filenames = int(time.time())
        save_path = f'saved_runs/{time_for_filenames}-{filename_indicator}-simulation_data.json'
        model_save_path = f'saved_runs/{time_for_filenames}-{filename_indicator}-model.json'
        plot_save_path = f'saved_runs/{time_for_filenames}-{filename_indicator}.png'
        self._logger.info("Saving run info to \"%s\".", save_path)
        os.makedirs(os.path.dirname(save_path), exist_ok=True)

        # Set up plots.
        doc: Document = curdoc()
        doc.title = "DeCAI Simulation"

        plot = figure(title="Balances & Accuracy on Hidden Test Set",
                      )
        plot.width = 800
        plot.height = 600

        plot.xaxis.axis_label = "Time (days)"
        plot.yaxis.axis_label = "Percent"
        plot.title.text_font_size = '20pt'
        plot.xaxis.major_label_text_font_size = '20pt'
        plot.xaxis.axis_label_text_font_size = '20pt'
        plot.yaxis.major_label_text_font_size = '20pt'
        plot.yaxis.axis_label_text_font_size = '20pt'

        plot.xaxis[0].ticker = AdaptiveTicker(base=5 * 24 * 60 * 60)
        plot.xgrid[0].ticker = AdaptiveTicker(base=24 * 60 * 60)

        balance_plot_sources_per_agent = dict()
        good_colors = cycle([
            colors.named.green,
            colors.named.lawngreen,
            colors.named.darkgreen,
            colors.named.limegreen,
        ])
        bad_colors = cycle([
            colors.named.red,
            colors.named.darkred,
        ])
        for agent in agents:
            source = ColumnDataSource(dict(t=[], b=[]))
            assert agent.address not in balance_plot_sources_per_agent
            balance_plot_sources_per_agent[agent.address] = source
            if agent.calls_model:
                color = 'blue'
                line_dash = 'dashdot'
            elif agent.good:
                color = next(good_colors)
                line_dash = 'dotted'
            else:
                color = next(bad_colors)
                line_dash = 'dashed'
            plot.line(x='t', y='b',
                      line_dash=line_dash,
                      line_width=2,
                      source=source,
                      color=color,
                      legend=f"{agent.address} Balance")

        plot.legend.location = 'top_left'
        plot.legend.label_text_font_size = '12pt'

        # JavaScript code.
        plot.xaxis[0].formatter = FuncTickFormatter(code="""