Pass through predictor data #27
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There was an issue related to normalizing the predictor data based on the training data Most steps in that normalization step use pre-calculated values, so it wasn’t a problem but there is a last step where the minimum value in the dataset is subtracted (to get rid of negative values in case one wanted to take a sqrt) That step uses the minimum value of the normalization data. Now a minval field is added to the variable datatype, allocated and initialized in the IO code, and updated in the normalization code after removing mean and stddev but before removing the minval itself.
Both training and predictor data now have the option to be normalized or not.
Permits the user to select a predictor variable to simply pass through as the output Also added the option to the included namelist. Probably need to update the documentation though.
also modified docs for new normalization options
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Added an option to pass a predictor data through as the output variable.