Surrogate Modeling

... is an umbrella term for approximations of building energy models using Machine Learning (ML) or algorithmic approach, as compared to (slower) simulations. This repository contains utilities and models to replicate ResStock dataset using Surrogate Modeling.

This code was developed in and depends on Databricks.

More technical documentation will be added in the future, but for now see Architechture and Features & Upgrades.

Note that there are two other version of this model that are stored in deprecated/ that are not being maintained.

Install

This repo is designed to be run on Databricks. But it is also designed to use shared library code from the RA private repo to avoid duplication of utility code from one project to another. It follows the conventions described in dml-sample-transmission-line so you should read an understand the conventions and usage patterns described in the README.md found there. We currently run this project on clusters with DB 14.3 LTS runtime (Python 3.10, R 4.2).

You should add install-db-requirements.sh as your cluster init script by uploading it in Advanced Options > Init Script in your cluster menu. The cluster will need to be restarted for changes to take effect.

Updating Requirements

Whenever you add a requirement to pyproject.toml you need to

1. poetry update as normal
2. generate requirements files with dml-gen-requirements as described in the dml-sample-transmission-line README.md