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This repository has been archived by the owner on Dec 7, 2018. It is now read-only.
There should be a condition strain node in the workflow. The condition strain will do all of the data loading, then write out a (hdf?) file of the Fourier domain data. All subsequent nodes will then simply load the FD data, instead of trying to repeat data conditioning. This will ensure that the ROQ weights, Bayeswave (when it's added) and gwin are all using exactly the same data.
The text was updated successfully, but these errors were encountered:
@cdcapano This is a good idea. I think it almost does what is needed, but probably we need to add a flag to the fourier domain output. I guess some logic will need to be added to the workflow then to take over keeping track of segment lengths.
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There should be a condition strain node in the workflow. The condition strain will do all of the data loading, then write out a (hdf?) file of the Fourier domain data. All subsequent nodes will then simply load the FD data, instead of trying to repeat data conditioning. This will ensure that the ROQ weights, Bayeswave (when it's added) and gwin are all using exactly the same data.
The text was updated successfully, but these errors were encountered: