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Fill Feature Lookup Tables

Use the Feature Fill Wizard to fill and optimize the values in tables by reference to the model or data. You can fill multiple tables at once using the wizard, and you can Fill from the top feature node or from any table node in a feature. Use Fill at the top feature node to calibrate the entire feature, that is, fill all the table values by referring to a model.

Before using the Feature Fill wizard:

  • Your project must contain a feature and a model or a data set.

  • Initialize your tables, unless you imported your strategy with tables already initialized.

Filling and Optimizing Lookup Table Values

When filling a feature table, the Feature Fill Wizard optimizes the table values to minimize the total square error between the feature values and the model. This routine optimizes the fit between your strategy and your model. Using Fill places values into your table. The optimization process shifts the cell values up and down to minimize the overall error between the interpolation between the model and the strategy.

To fill feature tables:

  1. Select Feature > Fill Feature to open the Feature Fill Wizard.

    Feature Fill Wizard dialog showing lookup tables and calibration scalars with options for table bounds, gradients, and calibration file import.

    Select tables to fill. Select the check boxes of the tables you want to fill. For each table, you can set these options.

    OptionDescription

    Clear Mask

    Select to clear any table mask. Model-Based Calibration Toolbox™ adds filled table cells to the table mask and uses the entire mask for extrapolation.

    Extrapolate

    Select to extrapolate across the whole table after filling cells. The extrapolation is based on the filled cells in the mask and any locked cells.

    Table Bounds

    Set bounds on the table values.

    Row Gradient Bounds

    Column Gradient Bounds

    Set bounds on the gradient (slope) between rows and columns. For example, entering 0 Inf in the left edit box imposes the constraint that the gradient must be positive (increasing) between successive rows.

  2. Set up the feature fill.

    Feature Fill Wizard dialog showing input data source, reference feature, fill method, and smoothing options for normalizers.

    ParameterDescription

    Reference

    Specify the model or data set column to use to fill the feature.

    By default, the feature fill uses the absolute error. To use the percentage error, select Use percentage error.

    Input data source

    For Input data, specify either Grid or Data Set. The data set option is available only if there is a data set containing some of the inputs to the feature.

    For Constraint, you can click Setup to create a constraint. Constraints restrict the input grid or data set values that CAGE uses to fill the feature. By default, the toolbox sets the constraint to the boundary model associated with the main model.

    Smoothing

    Specify a Smoothing factor on table axes.

    If you are filling the feature with a data set, specify a smoothing factor.

    The smoothing factor applies to all the tables CAGE fill.

    The smoothing factor applies a smoothing penalty to the optimization. The smoothness penalty uses the second derivative to avoid steep jumps between adjacent table values.

  3. Connect the model and feature inputs to define the feature fill.

    Feature Fill Wizard dialog showing input connections on the left and available connections on the right with options to connect or disconnect.

    Click Next.

  4. Set the grid values that you want to use for the feature fill.

    Feature Fill Wizard dialog showing input grid values for N, L, A, and delta_S with grid size displayed.

    Optionally, you can click Initialize From Normalizer to use the normalizer breakpoints as a variable value. In the Select Normalizer dialog box, you can also choose to interleave values between breakpoints. Interleaving values can minimize interpolation error by adding values between each normalizer value. In this way, you can create a grid of more points than table cells to optimize over. Select normalizers in the dialog box to use those breakpoints as the value.

  5. Click Finish to fill the tables.

    CAGE evaluates the model over the number of grid points specified, then calculates the total square error between this mesh model and the feature values. If no gradient constraints exist, CAGE uses lsqnonlin to adjust the table values until the error is minimized. If there are gradient constraints, to specify the gradient of the table at each cell, CAGE uses fmincon.

Saving and Reusing Feature Fill Settings

After feature filling, the Feature Fill Wizard saves your settings. You can run and manage your saved fill settings from the Feature Fill Settings pane. If you import new models, CAGE reuses the saved settings for the feature fill.

ToSelect

Define new fill settings starting from the defaults

Select Feature > New Fill Setting.

Rerun all saved fill settings in your feature

Select Feature > Run All Fill Settings.

Copy and modify some saved settings

Select Feature > Duplicate Selected Fill Setting.

Delete all saved fill settings for the selected feature

Select Feature > Clear All Fill Settings.

See Also

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