Use closest year available for each map #374
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src/compare_covermaps.py
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| "Tigray2021": 2021, | ||
| "Tigray2020": 2020, | ||
| "Zambia2019": 2019, | ||
| } |
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I don't really love that every time an intercomparison is made this file needs to be updated. I think it would be cleaner to minimize (or eliminate) changes to this file, and set the configuration (dataset name, admin code, year) in each respective notebook. In my view it'll be a bit more modular and pleasant to use that way.
Of course that script that generates all the intercomparisons would need to be updated or deleted, but since this is the primary way we are doing intercomparisons, I would be alright with that.
What do you think? @hannah-rae
| @@ -174,13 +200,23 @@ def ee_script(self, country: str, include_export: bool = True, include_prefix: b | |||
| }});""" | |||
| return script | |||
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| def extract_test(self, test: gpd.GeoDataFrame) -> gpd.GeoDataFrame: | |||
| def extract_test(self, test: gpd.GeoDataFrame, year: int) -> gpd.GeoDataFrame: | |||
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Should this parameter be a list to allow sampling from a range of years?
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Might be a more explicit way of specifying which maps should or should not be sampled
src/compare_covermaps.py
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| ), | ||
| "glad": Covermap( | ||
| "glad", | ||
| 'ee.ImageCollection("users/potapovpeter/Global_cropland_2019")', | ||
| resolution=30, | ||
| probability=0.5, | ||
| years_covered=[2003, 2007, 2011, 2015, 2019], |
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This collection only includes images for 2019
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Oh yeah, this one is weird. I'll make it so that it changes the collection.
| ), | ||
| "dynamicworld": Covermap( | ||
| "dynamicworld", | ||
| """ee.ImageCollection( | ||
| ee.ImageCollection("GOOGLE/DYNAMICWORLD/V1") | ||
| .filter(ee.Filter.date("2019-01-01", "2020-01-01")) | ||
| .filter(ee.Filter.date("2019-01-01", "2019-12-31")) |
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Ah this filter date thing is a bit messy now with the years. What do you think about making it a regex style in all instances.
.filterDate("YYYY-01-01", "YYYY-12-31") and that YYYY is replaces with the year selected?
Also filterDate is the same as .filter(ee.Filter.date so it can be replaced everywhere
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I think that may work... the issue I had when thinking about this is that the Covermap objects get created before they are sampled. But as long as every dataset has a year specified then it should be fine.
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Evaluating the ee_asset from a string can just be moved into extract_test to fix this:
ee_asset = eval(ee_asset_str.replace("\n", "").replace(" ", ""))
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Updates:
These changes were made to ensure the
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For maps that have more than one year available, we use the closest year to the test set year.
TODO: update results for all map notebooks