research-rainfallradar/rainfallwrangler/src/index.mjs

#!/usr/bin/env node
"use strict";

import cli from './cli.mjs';


(async () => {
    "use strict";
    
    await cli();
})();
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 18:06:15 +00:00			`#!/usr/bin/env node`
			`"use strict";`

			`import cli from './cli.mjs';`


			`(async () => {`
			`"use strict";`

			`await cli();`
			`})();`