thinkingmachines / unicef-ai4d-poverty-mapping

UNICEF AI4D Relative Wealth Mapping Project - datasets, models, and scripts for building relative wealth estimation models across Southeast Asia (SEA)
https://thinkingmachines.github.io/unicef-ai4d-poverty-mapping
MIT License
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Cross-country rollouts #161

Closed tm-jace-peralta closed 1 year ago

tm-jace-peralta commented 1 year ago

What does this PR contain?

Output for https://github.com/thinkingmachines/unicef-ai4d-poverty-mapping/issues/130, https://github.com/thinkingmachines/unicef-ai4d-poverty-mapping/issues/131, https://github.com/thinkingmachines/unicef-ai4d-poverty-mapping/issues/132, https://github.com/thinkingmachines/unicef-ai4d-poverty-mapping/issues/133

The final output of these notebooks contain (1) the predicted relative wealth index and (2) binned wealth category from A-E

Notes on rollout runs

~~ Country Region variable value
Vietnam “viet nam”
Thailand “thailand”
Malaysia “malaysia”
Laos "lao people's democratic republic" ~~
Country N grids Grid generation Feature generation
Vietnam 50880 10 mins 110 mins
Thailand 78254 15 mins 89 mins
Malaysia 30202 27 mins 20 mins
Laos 50880 8 mins 24 mins
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tm-jace-peralta commented 1 year ago

Added standard country name lookup dicts for iso3.py and hdx.py. All *_generate grids.ipynb can now take in the common country name, e.g. "vietnam","laos"