Trade Off Post Processing

Perform "What If" scenarios with interactive response surface tools in the Trade-Off post process tab.

1. From the Post Processing step, click the Trade-Off tab.
2. From the Channel selector, select the output response(s) to analyze in the Output Table.
3. Analyze the effect on inputs vs. outputs.

   Option	Description
   Modify the values of input variables to see their effect on output response approximations	In the Inputs pane, change each input variable by moving the slider in the first Value column, or by entering a value into the second Value column. Set input variables to their initial, minimum, or maximum values by moving the slider in the upper right-hand corner of the Inputs frame. Figure 1.
   Plot the effect of input variables on output response approximations	In the Inputs pane, select an input variable to plot by selecting its corresponding X Axis and/or Y Axis checkbox. Create a 2D trade-off by enabling the X Axis checkbox. Figure 2. Create a 3D trade off by enabling X Axis and Y Axis checkboxes. Figure 3. The output responses selected with the Channel selector are plotted. The values for the input variables which are not plotted can be modified by moving the sliders in the Value column to modify the other input variables, while studying the output response throughout the design space.

For the given values of the input variables, the output responses’ predictions are calculated by the Fit, and displayed in the Output Plot pane. Table shading is used to indicate the output response’s value between the minimum and maximum values contained in the input design matrix. When shading extends into either the Sample Min or Sample Max column, this indicates that the predicted value is beyond the bounds contained in the input matrix. If the shading extends significantly into these regions, it is suggested that you asses the validity of this value based on experience and knowledge of the modeled problem.

The Quality column is provided as a measure to assess both the accuracy and trust in the Fit at a specific point in the design space. Both global and local metrics are combined to create a metric that runs between 0 and an Upper Bound limited by the Fit’s R^2 value. The quality will be highest at points inside the convex hull formed around the Fit’s input points, where the predictive model has been trained to explain variance in the data. The quality metric decreases proportional to the distance outside the convex hull as the predictions at these points becomes less reliable, partially due to the values increasing based on an extrapolation of the data.

Tip: In a 2D trade-off the metrics shown in the Quality column can be plotted alongside the output response curve by selecting Fit Quality from the menu that displays when you click (located in the Output Plot pane).

Configure the Trade Off tab's display settings by clicking (located in the top, right corner of the work area). For more information about these settings, refer to Trade-Off Tab Settings.