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Updates argument in load_regions utility from bool to region name #7

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Updates argument in load_regions utility from bool to region name #7

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2 changes: 1 addition & 1 deletion notebooks/05_aggregate.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -211,7 +211,7 @@
},
"outputs": [],
"source": [
"regions_df = load_regions(extension=True)\n",
"regions_df = load_regions(extension='se-europe')\n",
"# use an area-preserving projection\n",
"buffer = (\n",
" 0.5 # padding to expand bounds to ensure you grab the data covering each region\n",
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2 changes: 1 addition & 1 deletion notebooks/06_bias_correction.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -113,7 +113,7 @@
},
"outputs": [],
"source": [
"regions_df = load_regions(extension=True)"
"regions_df = load_regions(extension='se-europe')"
]
},
{
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2 changes: 1 addition & 1 deletion notebooks/07_solar_radiation_wind.ipynb
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Expand Up @@ -76,7 +76,7 @@
"metadata": {},
"outputs": [],
"source": [
"regions_df = load_regions(extension=True)\n",
"regions_df = load_regions(extension='se-europe')\n",
"buffer = (\n",
" 0.5 # padding to expand bounds to ensure you grab the data covering each region\n",
")\n",
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25 changes: 22 additions & 3 deletions notebooks/utils.py
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Expand Up @@ -280,8 +280,9 @@ def calc_sparse_weights(
weights_sparse = ds_weights.unstack(sparse=True, fill_value=0.0).weights
return weights_sparse

from typing import Optional, Literal

def load_regions(extension=False):
def load_regions(extension: Literal['all', 'se-europe', 'central-asia'] = 'all'):
"""
Load in the city and regions that to use for aggregation.
"""
Expand All @@ -293,14 +294,32 @@ def load_regions(extension=False):
# use an area-preserving projection
crs_area = "ESRI:53034"
regions_df = regions_df.to_crs(crs_area)
if extension:

if extension == 'all': # should this be 'in'
return regions_df
elif extension == 'central-asia':
extension_cities = pd.read_csv(
"s3://carbonplan-climate-impacts/extreme-heat-extension/v1.0/inputs/<_______TODO_____ADD_PATH_TO_CENTRAL_ASIAN_CITIES_______>.csv"
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@orianac once we get the list of cities for central Asia, we can update this line.

)
regions_df = regions_df[
regions_df["ID_HDC_G0"].isin(extension_cities["ID_HDC_G0"].values)
]
return regions_df
elif extension == 'se-europe':
extension_cities = pd.read_csv(
"s3://carbonplan-climate-impacts/extreme-heat-extension/v1.0/inputs/SE_Europe_city_selection.csv"
)
regions_df = regions_df[
regions_df["ID_HDC_G0"].isin(extension_cities["ID_HDC_G0"].values)
]
return regions_df

return regions_df
else:
raise ValueError(f"extension: {extension} not in ['all', 'se-europe', 'central-asia']")






def remove_360_longitudes(ds):
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