active_inference_basic.py 文件源码

def rh_model_plot(self):
        """prepare and plot model outputs over input variations from sweep"""
        assert hasattr(self, "X_model_sweep")
        assert hasattr(self, "Y_model_sweep")

        print "%s.rh_plot_model sweepsteps = %d" % (self.__class__.__name__, self.X_model_sweep.shape[0])
        print "%s.rh_plot_model environment = %s" % (self.__class__.__name__, self.environment)
        print "%s.rh_plot_model environment proprio dims = %d" % (self.__class__.__name__, self.environment.conf.m_ndims)

        # scatter_data_raw   = np.hstack((self.X_model_sweep[:,1:], self.Y_model_sweep))
        # scatter_data_cols  = ["X%d" % i for i in range(1, self.X_model_sweep.shape[1])]
        # scatter_data_cols += ["Y%d" % i for i in range(self.Y_model_sweep.shape[1])]
        # print "scatter_data_raw", scatter_data_raw.shape
        # # df = pd.DataFrame(scatter_data_raw, columns=["x_%d" % i for i in range(scatter_data_raw.shape[1])])
        # df = pd.DataFrame(scatter_data_raw, columns=scatter_data_cols)

        title = "%s, input/output sweep of model %s at time %d" % (self.mode, self.model, -1)

        # plot_scattermatrix(df)
        # plot_scattermatrix_reduced(df)
        plot_colormeshmatrix_reduced(self.X_model_sweep, self.Y_model_sweep, ymin = -1.0, ymax = 1.0, title = title)

    ################################################################################