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Thanks again @attila, I'm really looking forward to testing this feature out with some upcoming measurements. Excellent work!

Thank you @attila, your additions to the table editor are very useful. There is another feature that is built into a SRS SR785 spectrum analyzer that we also use for some measurements, which I think could really have a positive impact on the measurement capabilities of Waveforms. The feature is called Auto Leveling and it adjusts the amplitude of the source signal in order to keep one of the input channel signals at some reference level that is set by the user. This would be a giant leap forward in source level dynamic scaling, as it would not require having to construct a table to shape the source levels and it would automatically adjust to different DUT responses. I'm not quite familiar with scripting to do this, but I suspect this might be handled this way (specify reference channel and reference level, then at each frequency in the sweep check the reference channel level and adjust the input level before taking a measurement).

That's great @attila, thanks! I should have read the documentation more thoroughly. When entering points in the table, I could see a use for buttons to import a table, add or delete a frequency point, sort the table by frequency, and scale the amplitude of the whole table by a constant. Keep up the great work on WaveForms.

For many sensor calibration measurement scenarios, it would be useful to be able to vary the wavegen output level in a custom way. In particular, measurements taken over a broad range of swept frequencies on dynamic systems that have a high Q can result in very large dynamic ranges. One way to achieve somewhat clean results is to separate the full measurement band into smaller frequency sweep ranges at a different sweep levels and recombine the frequency responses. If there's an easy way to take a baseline measurement, and use the inverse frequency response to excite the system, then the output should be much more stable (ideally flat spectrum level) for more optimum acquisition. Then just subtract the custom generator levels from the output data to get the true response. For example, a peak level in the baseline output response will result in a low generator level at that frequency. What's the best way to implement such an inverse compensation [filter]? When I tried to import a Custom file of frequency response data, the GUI interprets the frequency points as a time series. Thanks.