yy_start = 106
yy_end = 116
idx_band = 1
exp = Exposures()
ssp_file = EXP_POP_PTH +'baseYr_total_2000.tif'
exp.set_from_raster(ssp_file, transform=DST_META['transform'], height=DST_META['height'],
width=DST_META['width'], resampling=Resampling.average)
exp.value *= 25 # sum of the grids after upscaling
if np.any(exp.value<0) == True:
raise ValueError
exp.value_unit = 'N people per pixel'
exp.ref_year = 2000
exp[INDICATOR_CENTR+HAZ_TYPE] = np.arange(len(exp), dtype=int)
exp[INDICATOR_IF+HAZ_TYPE] = np.ones(len(exp), dtype=int)
exp.check()
for year in YEAR:
imp_model = [] # initite a list fro all models in one year
imp_save = None
for hydro, gcm in [(hydro, gcm) for hydro in HYDRO_MODEL for gcm in GCM_MODEL]:
haz_file = HAZARD_PTH +'flddph_' +hydro +'_' +gcm +'_' +RCP +'_flopros_gev_picontrol_2006_2300_0.1.nc'
haz_frac = HAZARD_PTH +'fldfrc_' +hydro +'_' +gcm +'_' +RCP +'_flopros_gev_picontrol_2006_2300_0.1.nc'
avg_value_ackerbau = value_ackerbau / exp_hail_agr[exp_hail_agr["region_id"] ==
221].shape[0]
a = exp_hail_agr[exp_hail_agr["region_id"] == 201].assign(value=avg_value_obst)
b = exp_hail_agr[exp_hail_agr["region_id"] == 202].assign(
value=avg_value_rebbau)
c = exp_hail_agr[exp_hail_agr["region_id"] == 221].assign(
value=avg_value_ackerbau)
exp_hail_agr = pd.concat([a, b, c]).sort_index()
exp_hail_agr = Exposures(exp_hail_agr)
exp_hail_agr.loc[exp_hail_agr["region_id"] == 201, "if_"] = int(3)
exp_hail_agr.loc[exp_hail_agr["region_id"] == 202, "if_"] = int(2)
exp_hail_agr.loc[exp_hail_agr["region_id"] == 221, "if_"] = int(4)
exp_hail_agr = exp_hail_agr.rename(columns={'if_': 'if_HL'})
exp_hail_agr.check()
exp_hail_agr.head()
exp_hail_agr.value_unit = "CHF"
exp_hail_agr.write_hdf5(input_folder + "/exp_agr_no_centr.hdf5")
test = exp_hail_agr[exp_hail_agr["value"] > 0]
plt.scatter(test[test["region_id"].isin([221, 222, 223])]["longitude"],
test[test["region_id"].isin([221, 222, 223])]["latitude"])
plt.scatter(test[test["region_id"] == 201]["longitude"],
test[test["region_id"] == 201]["latitude"])
plt.scatter(test[test["region_id"] == 202]["longitude"],
test[test["region_id"] == 202]["latitude"])
plt.legend(labels=["Acker - Futterbau", "Obstbau", "Rebbau"])
