Add Ethiopia to set of countries on which we can train

AnnaXWang · Dec 16, 2018 · 9f7f437 · 9f7f437
1 parent 2778a29
commit 9f7f437
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diff --git a/code/make_yields.py b/code/make_yields.py
@@ -148,6 +148,33 @@ def process_india():
     india_kharif.to_csv('./static_data_files/india_kharif_yields_standardized.csv', index=False)
     india_rabi.to_csv('./static_data_files/india_rabi_yields_standardized.csv', index=False)
 
+def process_ethiopia():
+    HARVEST_YEARS = [2001+i for i in range(16) if i != 2]
+
+    CROP_TRANSLATIONS = {
+        1122: "corn"
+    }
+
+    ethiopia = pd.read_csv('./static_data_files/ethiopia_yields_raw.csv', encoding='utf-8')
+    ethiopia = ethiopia[['Admin 1', 'Admin2_mod', 'Year', 'Season', 'Crop',
+                           'AreaPlanted_ha', 'QuantityProduced_mt', 'Yield_mt_ha']].copy()
+    ethiopia["Admin 1"] = ethiopia["Admin 1"].map(CLEAN_NAME)
+    ethiopia = ethiopia[~ethiopia["Admin2_mod"].isna()].copy()
+    ethiopia["Admin2_mod"] = ethiopia["Admin2_mod"].map(CLEAN_NAME)
+    ethiopia['Crop'] = ethiopia['Crop'].map(lambda s: CROP_TRANSLATIONS[s])
+
+    ethiopia = ethiopia[ethiopia["Season"] == "Meher"].copy()
+    ethiopia = ethiopia.drop("Season", axis=1).copy()
+
+    ethiopia = ethiopia.rename({'QuantityProduced_mt': PRODUCTION,
+                                'AreaPlanted_ha': AREA_PLANTED,
+                                'Yield_mt_ha': YIELD,
+                                'Admin 1': REGION_1,
+                                'Admin2_mod': REGION_2,
+                                'Crop': CROP,
+                                'Year': YEAR}, axis=1)
+    ethiopia.to_csv('./static_data_files/ethiopia_yields_standardized.csv', index=False)
+
 
 if __name__ == '__main__':
     name = sys.argv[1]
@@ -159,3 +186,5 @@ def process_india():
         process_argentina()
     elif (name == 'india'):
         process_india()
+    elif (name == 'ethiopia'):
+        process_ethiopia()
diff --git a/code/pull_modis.py b/code/pull_modis.py
@@ -36,6 +36,7 @@
     'brazil',
     'india',
     'usa',
+    'ethiopia',
 ]
 
 # "Boundary Filters": A rough bounding box for the entire country, to help GEE search for imagery faster
@@ -44,6 +45,7 @@
     [-34, -34, -74, 6],
     [68, 6, 97.5, 37.2],
     [-80, 32, -104.5, 49],
+    [33, 3.5, 48, 15.4],
 ]
 
 # "Feature Collections": The path in Google Earth Engine to a shapefile table specifying a set of subdivisions of the country
@@ -52,6 +54,7 @@
     'users/nikhilarundesai/BRMEE250GC_SIR',
     'users/nikhilarundesai/India_Districts',
     'users/nikhilarundesai/US_Counties',
+    'users/nikhilarundesai/ET_Admin2',
 ]
 
 # "Feature Key Functions": Lambda functions that extract a human-readable name from the metadata for a single feature in the shapefile
@@ -60,6 +63,7 @@
     lambda region: CLEAN_NAME(region, 'NM_MESO') + "-brasil", # BR: "<mesoregion name>-brasil"
     lambda region: CLEAN_NAME(region, 'DISTRICT') + "-" + CLEAN_NAME(region, 'ST_NM'), # IN: "<district name>-<state name>"
     lambda region: CLEAN_NAME(region, 'NAME') + "-" + GET_FIPS(region, 'STATEFP'), # US: "<county name>-<state name>"
+    lambda region: CLEAN_NAME(region, 'ADMIN2') + "-" +  CLEAN_NAME(region,'ADMIN1'), # ET: "<zone name>-<state name>"
 ]
 
 # "Feature Filter Functions": Lambda function that uses metadata to determine whether imagery is worth pulling for a particular region.
@@ -69,6 +73,7 @@
     lambda region: True,
     lambda region: True,
     lambda region: region.get('properties').get('STATEFP') in USA_SOY_FIPS_CODES, # US: only pull imagery from states with soy production
+    lambda region: True,
 ]