The maximum response, the top 25% response, and the top 50% (median) response, calculated on all experiments designed until a given generation, are plotted in sequence.

The responses for each generation are sorted, and presented in sequence. Standard-deviation bars are given at the top of each colored bar. Initial/extra experiments are displayed in grey color.

Detail of the previous graph, giving a separate graph of sorted responses for each generation.

A summary of the data in the previous two graphs, with sorted response barplots for each generation overlapping each other.

A boxplot representation of the distributions of response values for each generation, presented in sequence.

A summary histogram showing the distribution of the responses of all experiments in all generations.

Response histograms, generation by generation.

For each experimental parameter, the relative representation of that parameter for each generation is presented in sequence for the daptics experiments only (no initial or extra experiments). Relative representation is measured by a percentage, namely the percentage of experiments for a given generation having a particular parameter at a particular value.

In the course of evolution, parameter values that rise to high representation tend to be those that are more beneficial to the response, and therefore to the success of the experiment.

This plot represents a regression tree trained on the experimental data. Each box plot at the bottom of the tree represents the distribution of response values for a different subset of experiments. Each subset of experiments is characterized by a different "rule", that is a different combination of values of the experimental parameters. These rules can be obtained reading node and arc labels from top to bottom. Experimental parameters and values appearing in the rules of the tree can be considered important for explaining statistically significant differences in the response values.

This collection of plots shows how the response, as predicted by the daptics model trained in the previous generation, varies as a function of each experimental parameter, and of each pair of parameters. Each plot represents a 1-dimensional projection of the predicted response surface, which is defined on the n-dimensional set of all parameters.

The 1-dimensional plots are obtained based on a "pivot" experiment, which corresponds to the best experiment found in all previous generations. Each plot refers to a different parameter p (x-axis), which is varied over the range of values specified in the ESD, plus some extra intermediate values within that range if p is numerical. The pivot's value of p is shown in green on the x-axis labels. A prediction (y-axis) is calculated for each of those values of p, while keeping all of the other parameters fixed to the pivot's values. A continuous prediction curve is also shown if p is numerical. The (jittered) value of p of all experiments run up to the previous generation is finally shown with red bars.

The 2-dimensional plots use the pivot in the same way as the 1-dimensional plots, except they vary the values of a pair of parameters p_i (x-axis), p_j (y-axis), and represent 2-dimensional projections of the predicted response surface. The response prediction for any given combination of p_i, p_j values is visualized with the corresponding color from the palette on the right hand side of the plot. Contour lines (each representing a different set of p_i, p_j values sharing the same prediction) are also shown if both p_i and p_j are numerical. The (jittered) p_i, p_j values of all experiments run up to the previous generation is finally shown with red crosses.