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[SBFRF]

Hey,
read the paper, really interested in using this to track wave breaking across the surfzone. I'm trying to use the detect_breaking_events function from the scripts library, but i don't seem to see a way. Am i missing something? Do i have to redefine function as you have it or is there a way to import the function and start using it?

Thanks,

Spicer

[caiostringari]

Hi Spicer,

You could either redefine the function (see this notebook https://github.com/caiostringari/pywavelearn/blob/master/notebooks/wave-tracking/wave-tracking-omb.ipynb) or import it.

I've just pushed some updates that should make it easier. Try re-installing and then:

from pywavelearn.tracking import detect_breaking_events

If you are getting errors let me know and I will try to fix them. Please notice that I am finishing my PhD project this month and may not have time to work on fixing bugs promptly.

I am also planning a full re-factorization of the code in October.

Cheers,

Caio

[SBFRF]

Hey Caio, yea i had just copied the function and made a little library, locally to solve my problem. I tried your notebook with a timestack of mine and i don't seem to be getting good results, modifying your notebook (changing the colors the method is trained on and the analysis bounds) with my image i got the below image.

while it's not the initial issue, i am happy to open a new one on topic, but any pointers or help are appreciated.

[caiostringari]

Hi,

The residual foam in the surf zone seems to be being picked up by the algorithm.

You can try few different parameters to see if the results improve. For example:

# define which algorithm is used to detect breaking events
brk_alg = 'colour'  # -> change to edges and/or edges_and_colour
# metric used for pixel intensity definition
px_mtrc = 'lightness'
# colour quantization - We will NOT use this for now
qnt_cl = False
n_clrs = None
# peak detection method
pxp_mtd = 'local_maxima'  # -> change to differential
# threshold for peak detection
px_trsh = 0.2 # -> try to increase/reduce this value
# pixel window for denoise_bilateral
px_wndw = 5 # -> try to increase this value
# time window for peak detection
ts_wndw = 11 # -> try to increase this value
# minimum number of samples to be used for the DBSCAN clustering step
dbs_msp = 15 
# minimum distance be used for the DBSCAN clustering step
dbs_eps = 0.0015

and then call

detect_breaking_events(time, crx_dist, rgb, crx_start=None,
                           crx_end=None, px_mtrc="lightness", colours=None,
                           resample_rule="100L", algorithm="peaks",
                           peak_detection="local_maxima", posterize=False,
                           ncolours=0, threshold=0.1, tswindow=11,
                           denoise=True, pxwindow=3, mask_drysand=False)