Creating Approximations Using a Coefficient File

You can create an approximation using a previously saved file with coefficient data.

If you want to create a coefficient data file based on an existing approximation, see Initializing Approximations and Viewing the Data.

Important: If you are selecting a component that is in a Task Plan, you must select the component using the model explorer.

  1. Do one of the following:

    • From the Design Gateway,

      1. Select the component for which you want to create an approximation:
        • Select a component on the Sim-flow tab or in the model explorer, and click the Approximations button on the component title bar.
        • Right-click the component on the Sim-flow tab or in the model explorer, and select Approximations.

        The Approximations dialog box appears.

      2. On the right side of the dialog box, click New.

        The Approximation Wizard appears.

    • From the Runtime Gateway,

      1. Select a component on the Sim-flow tab or in the model explorer.
      2. Click the Visual Design tab, and click the button on the component title bar.

        The Approximation Wizard appears.

  2. In the Name of approximation text box, enter a name for the approximation.

  3. Click Previously Saved, and click Browse to locate the file you want to use.

  4. Locate the file, and click Select.

    The Approximation Wizard appears, and the file name appears in the text box.

  5. Click Next.

    The Approximation Technique screen appears.

    The technique that was used in the original approximation appears in the RBF model.

    Note: You cannot change the technique. If you change the technique, the coefficient data file is not used. Instead, a user-defined approximation is created.

  6. Click Next.

    The Input and Output Parameters screen appears.

    This screen shows the input and output parameters that were used in the original approximation.

    Note: You cannot change the input and output parameters. If you change the parameters, the coefficient file is not used. Instead, a user defined approximation is created.

  7. Click Next.

    The Error Analysis Method screen appears.

  8. Select the desired error analysis method for the approximation:

    • Separate data set. This method compares exact and approximate output values for each data point.

      1. Click Next.
      2. Select the desired sampling method (Random Points, Data File, or DOE Matrix), and configure the corresponding options as described in Configuring the Random Points Sampling Method, Configuring the Data File Sampling Method, or Configuring the DOE Matrix Sampling Method.

    • Cross-validation. This method selects a subset of points from the main data set, removes each point one at a time, recalculates coefficients, and compares exact and approximate output values at each removed point.

      1. In the first text box, type the number of points from the total number of sampling points that you want to use for cross-validation error analysis.
      2. Click Use a fixed random seed for selecting points and specify a seed value to use for the random number generator when determining the set of sample points selected for cross-validation. This option allows you to reproduce the approximation with the same set of points later, if desired.

    • No error analysis.

    If you are performing an error analysis (on any approximation other than a Orthogonal polynomial approximation), the Approximation Improvement Options screen appears; if you choose to skip the error analysis, the Runtime Options screen appears.

  9. If you are performing an error analysis, you can configure the approximation improvement options.

    For more information, see Improving Approximations using Sequential Sampling.

    You can choose to improve the approximation by allowing Isight to add sample points. Isight will use a sequential sampling technique that is appropriate for the approximation technique selected.

    1. Enter a target for the average prediction error of the approximation. Isight will add sample points sequentially until the average error falls below the value that you enter. Valid values are 0.0–1.0.
    2. Enter the maximum number of additional points that you want to use for improving the approximation.
    3. Enter the maximum number of iterations to improve the approximation. Dividing the maximum number of additional points by the maximum number of iterations results in the number of points that are added during each iteration of sequential sampling. Although it is desirable to add one point during each iteration, choosing fewer iterations reduces the time taken to fit the approximation model.

  10. Click Next.

    The Runtime Options screen appears.

  11. Set the Store coefficient data in file parameter named option. When activated, this option creates a file parameter that stores the approximation’s coefficient data. This option is useful if the approximation is initialized or updated (re-initialized) during execution and the coefficient data are needed for custom postprocessing. It is also useful if you want the coefficient data preserved in your database. For more information on file parameters, see Using File Parameters.

  12. Click Finish.

    A message appears prompting you to initialize the approximation.

  13. Perform one of the following actions: