Esempio n. 1
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    def test_EU(self):
        """test with demo data containing France and Germany"""
        bbox = [-5, 42, 16, 55]
        haz = RelativeCropyield()
        haz.set_from_single_run(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_single_run(input_dir=INPUT_DIR,
                                filename=FILENAME_LU,
                                hist_mean=FILENAME_MEAN,
                                bbox=bbox,
                                yearrange=(2001, 2005),
                                scenario='flexible',
                                unit='t',
                                crop='whe',
                                irr='firr')

        exp.set_to_usd(INPUT_DIR)
        exp.assign_centroids(haz, threshold=20)

        if_cp = ImpactFuncSet()
        if_def = IFRelativeCropyield()
        if_def.set_relativeyield()
        if_cp.append(if_def)
        if_cp.check()

        impact = Impact()
        impact.calc(exp.loc[exp.region_id == 276],
                    if_cp,
                    haz.select(['2002']),
                    save_mat=True)

        exp_manual = exp.value.loc[exp.region_id == 276].values
        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.value.max(), 53074789.755290434)
        self.assertEqual(exp.latitude.values.size, 1092)
        self.assertAlmostEqual(exp.value[3], 0.0)
        self.assertAlmostEqual(exp.value[1077], 405026.6857207429)
        self.assertAlmostEqual(impact.imp_mat.data[3], -176102.5359452465)
        self.assertEqual(len(dif), 0)
Esempio n. 2
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    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)