4 hot vector with dataset

[CraftMiner1]

Dear @dnguyengithub,

Could you please clarify as to how to change the 4 hot vectors so that the pre-processing works for another dataset?
For example if I were to use a dataset with:
LAT_MIN = 25.00, LAT_MAX = 30.00 ,LON_MIN = -89.00, LON_MAX = -84.00

From what I understood the values for the LAT_BINS and LON_BINS would be as follows:
LAT_BINS = 500; LON_BINS = 500;

What about the SOG_BINS and the COG_BINS? Do they stay 30 and 72?
SOG_BINS = 30; COG_BINS = 72

I ran the codes in that order:
csv2pkl.py -> dataset_preprocessing.py ->calculate_AIS_mean.py

calculate_AIS_mean is yeilding the following error:
Traceback (most recent call last):
File "c:/Users/User/Desktop/geotracknet/data/calculate_AIS_mean.py", line 102, in
current_sparse_matrix,, = sparse_AIS_to_dense(tmp,0,0)
File "c:/Users/User/Desktop/geotracknet/data/calculate_AIS_mean.py", line 68, in sparse_AIS_to_dense
dense_msgs.append(create_dense_vect(msg,
File "c:/Users/User/Desktop/geotracknet/data/calculate_AIS_mean.py", line 58, in create_dense_vect
dense_vect[int(lat*lat_bins)] = 1.0
IndexError: index 14709 is out of bounds for axis 0 with size 1102

Looking forward to hearing from you
Thank you.

[yche-sflscientific]

Probably too late, but I ran into the same issue. I figure it's because the LAT/LON are not properly normalized in this case. So current code in dataset_preprocessing.py the normalizing part is not doing much as it did not modify what's inside the Data dictionary, and lat*lat_bins assume a lat normalized lat value. I made the change and got passed the calculate_AIS_mean.py, but still struggling with the mismatched 4-hot dimensions...