Feature/smart cities lulc #20
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…/smart_cities_lulc
…/smart_cities_lulc
…ities-cif into feature/smart_cities_lulc
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To Test:
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jterry64
requested changes
Jan 3, 2024
| # ESA reclass and upsample | ||
| esa_world_cover = EsaWorldCover().get_data(bbox) | ||
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| reclass_map = { |
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you define this in a couple places, could you define it all in one layer?
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| clf.fit(buildings_sample[['ULU', 'ANBH', 'Area_m']], buildings_sample['Slope_encoded']) | ||
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| # plt.figure(figsize=(20, 10)) |
…/smart_cities_lulc
…ties-cif into feature/smart_cities_lulc
…i/cities-cif into feature/smart_cities_lulc
…i/cities-cif into feature/smart_cities_lulc
…/smart_cities_lulc
…s-cif into feature/smart_cities_lulc
…/smart_cities_lulc
…/smart_cities_lulc
…/smart_cities_lulc
jterry64
requested changes
Jun 7, 2024
| @@ -0,0 +1,303 @@ | |||
| { | |||
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You typically don't want to check in large data files like this, it will blow up the size of the git history. Could this be stored in S3 and downloaded?
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It is only 184 KB so not very large. I like having it here since it is the basis for the model. If we start needing to use more training data in the future, we should find a better solution probably.
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| import xarray as xr | |||
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is this file just a duplicate of the .py file?
…/smart_cities_lulc
…/smart_cities_lulc
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Create models folder and move building_classifier files into it. |
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Description: Add python version of layer for https://github.com/wri/cities-heat/blob/main/LULC_grid_V2.R
JIRA ticket is https://gfw.atlassian.net/browse/CIF-124
Test by running
pytest layers.py::test_smart_surface_lulc