Commit graph

5 commits

Author SHA1 Message Date
Starbeamrainbowlabs 0c11ddca4b
rainfallwrangler does NOT mess up the ordering of the data 2022-10-18 19:07:14 +01:00
Starbeamrainbowlabs f2312c1184
fix crash 2022-08-31 16:25:27 +01:00
Starbeamrainbowlabs fe7a8b3fc0
Add 9 simple steps to use the rainfall radar model..... oh boy. 2022-08-31 16:18:28 +01:00
Starbeamrainbowlabs d9b9a4f9fc
note tos elf 2022-07-22 19:04:41 +01:00
Starbeamrainbowlabs 8a9cd6c1c0
Lay out some basic scaffolding
I *really* hope this works. This is the 3rd major revision of this
model. I've learnt a ton of stuff between now and my last attempt, so
here's hoping that all goes well :D

The basic idea behind this attempt is *Contrastive Learning*. If we
don't get anything useful with this approach, then we can assume that
it's not really possible / feasible.

Something we need to watch out for is the variance (or rather lack
thereof) in the dataset. We have 1.5M timesteps, but not a whole lot
will be happening in most of those....

We may need to analyse the variance of the water depth data and extract
a subsample that's more balanced.
2022-05-13 19:06:15 +01:00