def test_normalize_with_fao_cp(self):
""" Test normalizing of two given exposures countrywise (usually firr + norr)
with the mean crop production quantity"""
exp = CropProduction()
exp.set_from_single_run(input_dir=INPUT_DIR,
filename=FILENAME,
hist_mean=FILENAME_MEAN,
bbox=[-5, 42, 16, 55],
yearrange=np.array([2001, 2005]),
scenario='flexible',
crop='mai',
unit='t',
irr='firr')
country_list, ratio, exp_firr_norm, exp_noirr_norm, fao_crop_production, exp_tot_production = \
normalize_with_fao_cp(exp, exp, input_dir=INPUT_DIR,
yearrange=np.array([2009, 2018]), unit='t', return_data=True)
self.assertAlmostEqual(ratio[2], 17.671166854032993)
self.assertAlmostEqual(ratio[11], .86250775)
self.assertAlmostEqual(fao_crop_production[2], 673416.4)
self.assertAlmostEqual(fao_crop_production[11], 160328.7)
self.assertAlmostEqual(np.nanmax(exp_firr_norm.value.values),
220735.69212710857)
self.assertAlmostEqual(np.nanmax(exp_firr_norm.value.values),
np.nanmax(exp_noirr_norm.value.values))
self.assertAlmostEqual(np.nanmax(exp.value.values), 284244.81023404596)
self.assertAlmostEqual(np.nansum(exp_noirr_norm.value.values) +
np.nansum(exp_firr_norm.value.values),
np.nansum(fao_crop_production),
places=1)
self.assertListEqual(list(country_list), [
0, 40, 56, 70, 191, 203, 208, 250, 276, 380, 442, 528, 616, 705,
724, 756, 826
])
def test_EU(self):
"""test with demo data containing France and Germany"""
bbox = [-5, 42, 16, 55]
haz = RelativeCropyield()
haz.set_from_isimip_netcdf(input_dir=INPUT_DIR,
yearrange=(2001, 2005),
bbox=bbox,
ag_model='lpjml',
cl_model='ipsl-cm5a-lr',
scenario='historical',
soc='2005soc',
co2='co2',
crop='whe',
irr='noirr',
fn_str_var=FN_STR_DEMO)
hist_mean = haz.calc_mean(yearrange_mean=(2001, 2005))
haz.set_rel_yield_to_int(hist_mean)
haz.centroids.set_region_id()
exp = CropProduction()
exp.set_from_isimip_netcdf(input_dir=INPUT_DIR,
filename=FILENAME_LU,
hist_mean=FILENAME_MEAN,
bbox=bbox,
yearrange=(2001, 2005),
scenario='flexible',
unit='t/y',
crop='whe',
irr='firr')
exp.set_value_to_usd(INPUT_DIR, yearrange=(2000, 2018))
exp.assign_centroids(haz, threshold=20)
impf_cp = ImpactFuncSet()
impf_def = ImpfRelativeCropyield()
impf_def.set_relativeyield()
impf_cp.append(impf_def)
impf_cp.check()
impact = Impact()
reg_sel = exp.copy()
reg_sel.gdf = reg_sel.gdf[reg_sel.gdf.region_id == 276]
impact.calc(reg_sel, impf_cp, haz.select(['2002']), save_mat=True)
exp_manual = reg_sel.gdf.value
impact_manual = haz.select(event_names=['2002'],
reg_id=276).intensity.multiply(exp_manual)
dif = (impact_manual - impact.imp_mat).data
self.assertEqual(haz.tag.haz_type, 'RC')
self.assertEqual(haz.size, 5)
self.assertEqual(haz.centroids.size, 1092)
self.assertAlmostEqual(haz.intensity.mean(), -2.0489097e-08)
self.assertAlmostEqual(exp.gdf.value.max(), 53074789.755290434)
self.assertEqual(exp.gdf.latitude.values.size, 1092)
self.assertAlmostEqual(exp.gdf.value[3], 0.0)
self.assertAlmostEqual(exp.gdf.value[1077], 405026.6857207429)
self.assertAlmostEqual(impact.imp_mat.data[3], -176102.5359452465)
self.assertEqual(len(dif), 0)
def set_value_to_usd(self):
"""Test calculating cropyield_isimip Exposure in [USD/y]"""
exp = CropProduction()
exp.set_from_isimip_netcdf(input_dir=INPUT_DIR, filename=FILENAME, hist_mean=FILENAME_MEAN,
bbox=[-5, 42, 16, 55], yearrange=np.array([2001, 2005]),
scenario='flexible', crop = 'mai', irr='firr', unit='USD/y')
self.assertEqual(exp.gdf.longitude.min(), -4.75)
self.assertEqual(exp.gdf.longitude.max(), 15.75)
self.assertEqual(exp.gdf.latitude.min(), 42.25)
self.assertEqual(exp.gdf.latitude.max(), 54.75)
self.assertEqual(exp.gdf.value.shape, (1092,))
self.assertEqual(exp.value_unit, 'USD/y')
self.assertEqual(exp.crop, 'mai')
self.assertAlmostEqual(exp.gdf.value.max(), 51603897.28533253, places=6)
def test_load_central_EU(self):
"""Test defining crop_production Exposure from complete demo file (Central Europe)"""
exp = CropProduction()
exp.set_from_isimip_netcdf(input_dir=INPUT_DIR, filename=FILENAME, hist_mean=FILENAME_MEAN,
bbox=[-5, 42, 16, 55], yearrange=np.array([2001, 2005]),
scenario='flexible', unit='t/y', crop = 'mai', irr='firr')
self.assertEqual(exp.gdf.longitude.min(), -4.75)
self.assertEqual(exp.gdf.longitude.max(), 15.75)
self.assertEqual(exp.gdf.latitude.min(), 42.25)
self.assertEqual(exp.gdf.latitude.max(), 54.75)
self.assertEqual(exp.gdf.value.shape, (1092,))
self.assertEqual(exp.value_unit, 't/y')
self.assertEqual(exp.crop, 'mai')
self.assertAlmostEqual(exp.gdf.value.max(), 284244.81023404596, places=5)
def test_set_from_area_and_yield_nc4(self):
"""Test defining crop_production Exposure from area and yield
data extracted from netcdf test data for Switzerland"""
exp = CropProduction()
exp.set_from_area_and_yield_nc4('whe',
2,
2,
FILENAME_YIELD,
FILENAME_AREA,
'yield.tot',
'cultivated area all',
input_dir=INPUT_DIR)
self.assertEqual(exp.crop, 'whe')
self.assertEqual(exp.gdf.shape[0], 55)
self.assertEqual(exp.meta['width'] * exp.meta['height'], 55)
self.assertIn(756, exp.gdf.region_id.values)
self.assertIn(380, exp.gdf.region_id.values)
self.assertAlmostEqual(exp.gdf['value'].max(), 253225.66611428373)
def test_set_value_to_usd(self):
"""Test calculating crop_production Exposure in [USD/y]"""
exp = CropProduction()
exp.set_from_isimip_netcdf(input_dir=INPUT_DIR,
filename=FILENAME,
hist_mean=FILENAME_MEAN,
bbox=[-5, 42, 16, 55],
yearrange=np.array([2001, 2005]),
scenario='flexible',
unit='t/y',
crop='mai',
irr='firr')
exp.set_value_to_usd(INPUT_DIR, yearrange=(2000, 2018))
self.assertEqual(exp.gdf.longitude.min(), -4.75)
self.assertEqual(exp.gdf.longitude.max(), 15.75)
self.assertEqual(exp.gdf.latitude.min(), 42.25)
self.assertEqual(exp.gdf.latitude.max(), 54.75)
self.assertEqual(exp.gdf.value.shape, (1092, ))
self.assertEqual(exp.value_unit, 'USD/y')
self.assertEqual(exp.crop, 'mai')
self.assertAlmostEqual(exp.gdf.tonnes_per_year[28], 1998.3634803238633)
self.assertAlmostEqual(exp.gdf.value.max(),
51603897.28533253,
places=5)
self.assertAlmostEqual(exp.gdf.value.mean(),
907401.9933073953,
places=5)
self.assertEqual(exp.gdf.value.min(), 0.0)
def test_set_value_to_kcal(self):
"""Test calculating crop_production Exposure in [kcal/y]"""
exp = CropProduction()
exp.set_from_isimip_netcdf(input_dir=INPUT_DIR,
filename=FILENAME,
hist_mean=FILENAME_MEAN,
bbox=[-5, 45, 10, 50],
yearrange=np.array([2001, 2005]),
scenario='flexible',
unit='t/y',
crop='mai',
irr='firr')
max_tonnes = exp.gdf.value.max()
exp.set_value_to_kcal()
self.assertEqual(exp.gdf.latitude.min(), 45.25)
self.assertEqual(exp.gdf.latitude.max(), 49.75)
self.assertEqual(exp.gdf.value.shape, (300, ))
self.assertAlmostEqual(exp.gdf.value.max(),
365 * 10 * 1000 * max_tonnes,
places=3)
self.assertAlmostEqual(exp.gdf.value.max(),
874488976392.9623,
places=3)
self.assertAlmostEqual(exp.gdf.value.mean(),
19910311383.52674,
places=4)
self.assertEqual(exp.gdf.value.min(), 0.0)
def test_set_value_to_kcal(self):
"""Test calculating crop_production Exposure in [kcal/y]"""
# (1) biomass = True
exp = CropProduction()
exp.set_from_isimip_netcdf(input_dir=INPUT_DIR,
filename=FILENAME,
hist_mean=FILENAME_MEAN,
bbox=[-5, 45, 10, 50],
yearrange=np.array([2001, 2005]),
scenario='flexible',
unit='t/y',
crop='mai',
irr='firr')
max_tonnes = exp.gdf.value.max()
exp.set_value_to_kcal()
self.assertEqual(exp.gdf.latitude.min(), 45.25)
self.assertEqual(exp.gdf.latitude.max(), 49.75)
self.assertEqual(exp.gdf.value.shape, (300, ))
self.assertAlmostEqual(exp.gdf.value.max(),
3.56e6 * max_tonnes,
places=3)
self.assertAlmostEqual(exp.gdf.value.max(),
852926234509.3002,
places=3)
self.assertAlmostEqual(exp.gdf.value.mean(),
19419372198.727455,
places=4)
self.assertEqual(exp.gdf.value.min(), 0.0)
# (2) biomass = False
exp = CropProduction()
exp.set_from_isimip_netcdf(input_dir=INPUT_DIR,
filename=FILENAME,
hist_mean=FILENAME_MEAN,
bbox=[-5, 45, 10, 50],
yearrange=np.array([2001, 2005]),
scenario='flexible',
unit='t/y',
crop='mai',
irr='firr')
max_tonnes = exp.gdf.value.max()
exp.set_value_to_kcal(biomass=False)
self.assertEqual(exp.gdf.latitude.min(), 45.25)
self.assertEqual(exp.gdf.value.shape, (300, ))
self.assertAlmostEqual(exp.gdf.value.max(),
3.56e6 * max_tonnes / (1 - .12),
places=3)
self.assertAlmostEqual(exp.gdf.value.mean(),
22067468407.644833,
places=4)
def test_EU_nan(self):
"""Test whether setting the zeros in exp.value to NaN changes the impact"""
bbox = [0, 42, 10, 52]
haz = RelativeCropyield()
haz.set_from_isimip_netcdf(input_dir=INPUT_DIR,
yearrange=(2001, 2005),
bbox=bbox,
ag_model='lpjml',
cl_model='ipsl-cm5a-lr',
scenario='historical',
soc='2005soc',
co2='co2',
crop='whe',
irr='noirr',
fn_str_var=FN_STR_DEMO)
hist_mean = haz.calc_mean(yearrange_mean=(2001, 2005))
haz.set_rel_yield_to_int(hist_mean)
haz.centroids.set_region_id()
exp = CropProduction()
exp.set_from_isimip_netcdf(input_dir=INPUT_DIR,
filename=FILENAME_LU,
hist_mean=FILENAME_MEAN,
bbox=bbox,
yearrange=(2001, 2005),
scenario='flexible',
unit='t/y',
crop='whe',
irr='firr')
exp.assign_centroids(haz, threshold=20)
impf_cp = ImpactFuncSet()
impf_def = ImpfRelativeCropyield()
impf_def.set_relativeyield()
impf_cp.append(impf_def)
impf_cp.check()
impact = Impact()
impact.calc(exp, impf_cp, haz, save_mat=True)
exp_nan = CropProduction()
exp_nan.set_from_isimip_netcdf(input_dir=INPUT_DIR,
filename=FILENAME_LU,
hist_mean=FILENAME_MEAN,
bbox=[0, 42, 10, 52],
yearrange=(2001, 2005),
scenario='flexible',
unit='t/y',
crop='whe',
irr='firr')
exp_nan.gdf.value[exp_nan.gdf.value == 0] = np.nan
exp_nan.assign_centroids(haz, threshold=20)
impact_nan = Impact()
impact_nan.calc(exp_nan, impf_cp, haz, save_mat=True)
self.assertListEqual(list(impact.at_event), list(impact_nan.at_event))
self.assertAlmostEqual(12.056545220060798, impact_nan.aai_agg)
self.assertAlmostEqual(12.056545220060798, impact.aai_agg)