1. XYTable

The XYTable is useful to display data generated from multiple runs based on variations of variables. Such data can be generated using Condition Sets, Condition Spaces, or Workflow Sets.

Based on the values of the two selected variables, the XYTable displays a two dimensional grid. Each cell shows the value of the selected signal for the according combination of variable values.

When filtering the signals before the XYTable, keep both variables folder and the signal you are interested in. Otherwise you will not be able to select the signal, as there are no variables available to be used for the columns and rows.
Also keep in mind, that the signal must be a single value for each variation and that it must only be varied in exactly two variables.

Limitations: 50 signals, 600 variable combinations (columns * rows)

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1.1. How to Use XYTable

1. Open the example RIFLEX/Simple flexible riser.
2. Edit its environment and change the wave type to Jonswap Double Peaked.
3. Enter 2.5 and 3.3 for Significant Wave Height and Peak Period.
4. Right click each field, select Set as variable, and keep the proposed default variable name.
5. Under Conditions create a new Condition Space.
6. Add two more columns to the significantWaveHeight (3.5, 4.5) and one more column to peakPeriod (4.3).
7. Run the dynamic analysis.
8. Create a new Post Processor Task.
9. Open the Post Processor spec.
10. Drag the conditionSpace into the diagram area of the Post Processor.
11. Drag in a Statistics filter.
12. Drag in an XYTable from the palette.
13. Link the conditionSpace.out → Statistics.in and Statistics.max → XYTable.in.
14. Double click the connection between the condition space and the statistics filter. Add two signal requirements on the attribute path: *.Dynamic.RiserLine.Displacement envelope curves’ and ’\*.Variables. This will reduce the amount of data to be processed.
14. Open the XYTable by double clicking it in the diagram.
15. Select \*.Dynamic.RiserLine.Displacement envelope curves.X-MAX.max as signal, significantWaveHeight as column variable, and peakPeriod as row variable.

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The table of selected data will look similar to the one below.

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