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@joshreini1
Created October 7, 2022 20:08
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import h5py
def load_data_for_year(year) -> pd.DataFrame:
if year > 2016:
filename = f'GFED4.1s_{year}_beta.hdf5'
else:
filename = f'GFED4.1s_{year}.hdf5'
filepath = os.path.join(data_dir, filename)
data = h5py.File(filepath, 'r')
df = pd.DataFrame({
'lat': data['lat'][:].flatten(),
'lon': data['lon'][:].flatten(),
})
keys = ['burned_area/{:02}/burned_fraction',
'emissions/{:02}/DM',
'emissions/{:02}/C',
'emissions/{:02}/small_fire_fraction',
'biosphere/{:02}/NPP',
'biosphere/{:02}/Rh',
'biosphere/{:02}/BB']
for month in range(1,13):
for key in keys:
key_str = key.format(month)
df[key_str] = data[key_str][:].flatten()
df = filter_to_west_us_region(df)
return df
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