Predicting TWL using time-varying foreshore slope is pretty slow, so let's remove it from our data analysis pipeline. The code is still there if we want to call it, but for the time being, let's remove this model when we're looking at comparisons.
If pre and post storm profiles returned to similar elevations within the sampled profile length, the change point detection would select the most seaward point and incorrectly calculate the swash zone volumes. This change looks at the slope of the difference between the two profiles and assumes that the difference between the two profiles should be increasing at the location of the change point.
This is useful where we have a structure or rock wall and want to specify that we don't know what the observed storm regime is. In this case, we'll put a 'unknown' string in the ./data/raw/profile_features observed storm impact csv field and overwrite it with a NaN in our pandas dataframe.
If the x-coordinate specified for the toe/crest does not exist for the profile type, this fixes an issue where the z-elevation of the other profile type was not being correctly calculated. Also, some commented out code is removed.
Dune toe TWL exceedence hours were being left as zero if the profile didn't have a dune toe (technically correct). In these cases it's more useful to calculate the exceedence hours of the dune crest level.
Without this change, interim .csv files were being recorded with 9 decimal places, greatly increasing the file size. This keeps the number of decimals limited to a practical amount.
Christopher Leaman
Chris Leaman