Example #1
0
    def test_local_mustar(self):

        hef_file = get_demo_file('Hintereisferner.shp')
        rgidf = gpd.GeoDataFrame.from_file(hef_file)

        # loop because for some reason indexing wont work
        for index, entity in rgidf.iterrows():
            gdir = cfg.GlacierDir(entity, base_dir=self.testdir)
        gis.define_glacier_region(gdir, entity)
        gis.glacier_masks(gdir)
        centerlines.compute_centerlines(gdir)
        geometry.initialize_flowlines(gdir)
        geometry.catchment_area(gdir)
        geometry.catchment_width_geom(gdir)
        geometry.catchment_width_correction(gdir)
        climate.distribute_climate_data([gdir])
        climate.mu_candidates(gdir, div_id=0)

        hef_file = get_demo_file('mbdata_RGI40-11.00897.csv')
        mbdf = pd.read_csv(hef_file).set_index('YEAR')
        t_star, bias = climate.t_star_from_refmb(gdir, mbdf['ANNUAL_BALANCE'])

        t_star = t_star[-1]
        bias = bias[-1]

        climate.local_mustar_apparent_mb(gdir, t_star, bias)

        df = pd.read_csv(gdir.get_filepath('local_mustar', div_id=0))
        mu_ref = gdir.read_pickle('mu_candidates', div_id=0).loc[t_star]
        np.testing.assert_allclose(mu_ref, df['mu_star'][0], atol=1e-3)

        # Check for apparent mb to be zeros
        for i in [0] + list(gdir.divide_ids):
             fls = gdir.read_pickle('inversion_flowlines', div_id=i)
             tmb = 0.
             for fl in fls:
                 self.assertTrue(fl.apparent_mb.shape == fl.widths.shape)
                 tmb += np.sum(fl.apparent_mb * fl.widths)
             np.testing.assert_allclose(tmb, 0., atol=0.01)
             if i == 0: continue
             np.testing.assert_allclose(fls[-1].flux[-1], 0., atol=0.01)

        # ------ Look for gradient
        # which years to look at
        fls = gdir.read_pickle('inversion_flowlines', div_id=0)
        mb_on_h = np.array([])
        h = np.array([])
        for fl in fls:
            y, t, p = climate.mb_yearly_climate_on_height(gdir, fl.surface_h)
            selind = np.searchsorted(y, mbdf.index)
            t = np.mean(t[:, selind], axis=1)
            p = np.mean(p[:, selind], axis=1)
            mb_on_h = np.append(mb_on_h, p - mu_ref * t)
            h = np.append(h, fl.surface_h)
        dfg = pd.read_csv(get_demo_file('mbgrads_RGI40-11.00897.csv'),
                          index_col='ALTITUDE').mean(axis=1)
        # Take the altitudes below 3100 and fit a line
        dfg = dfg[dfg.index < 3100]
        pok = np.where(h < 3100)
        from scipy.stats import linregress
        slope_obs, _, _, _, _ = linregress(dfg.index, dfg.values)
        slope_our, _, _, _, _ = linregress(h[pok], mb_on_h[pok])
        np.testing.assert_allclose(slope_obs, slope_our, rtol=0.1)
Example #2
0
    def test_yearly_mb_climate(self):

        hef_file = get_demo_file('Hintereisferner.shp')
        rgidf = gpd.GeoDataFrame.from_file(hef_file)

        # loop because for some reason indexing wont work
        gdirs = []
        for index, entity in rgidf.iterrows():
            gdir = cfg.GlacierDir(entity, base_dir=self.testdir)
            gis.define_glacier_region(gdir, entity)
            gdirs.append(gdir)
        climate.distribute_climate_data(gdirs)

        nc_r = netCDF4.Dataset(get_demo_file('histalp_merged_hef.nc'))
        ref_h = nc_r.variables['hgt'][1, 1]
        ref_p = nc_r.variables['prcp'][:, 1, 1]
        ref_p *= cfg.params['prcp_scaling_factor']
        ref_t = nc_r.variables['temp'][:, 1, 1]
        ref_t = np.where(ref_t < 0, 0, ref_t)
        nc_r.close()

        # NORMAL --------------------------------------------------------------
        hgts = np.array([ref_h, ref_h, -8000, 8000])
        years, temp, prcp = climate.mb_yearly_climate_on_height(gdir, hgts)

        ref_nt = 202
        self.assertTrue(len(years) == ref_nt)
        self.assertTrue(temp.shape == (4, ref_nt))
        self.assertTrue(prcp.shape == (4, ref_nt))

        yr = [1802, 1802]
        years, temp, prcp = climate.mb_yearly_climate_on_height(gdir, hgts,
                                                                year_range=yr)
        ref_nt = 1
        self.assertTrue(len(years) == ref_nt)
        self.assertTrue(years == 1802)
        self.assertTrue(temp.shape == (4, ref_nt))
        self.assertTrue(prcp.shape == (4, ref_nt))
        np.testing.assert_allclose(temp[0, :], np.sum(ref_t[0:12]))
        np.testing.assert_allclose(temp[0, :], temp[1, :])
        np.testing.assert_allclose(prcp[0, :], prcp[1, :])
        np.testing.assert_allclose(prcp[3, :], np.sum(ref_p[0:12]))
        np.testing.assert_allclose(prcp[2, :], np.sum(ref_p[0:12])*0)
        np.testing.assert_allclose(temp[3, :], np.sum(ref_p[0:12])*0)

        yr = [1803, 1804]
        years, temp, prcp = climate.mb_yearly_climate_on_height(gdir, hgts,
                                                                year_range=yr)
        ref_nt = 2
        self.assertTrue(len(years) == ref_nt)
        np.testing.assert_allclose(years, yr)
        self.assertTrue(temp.shape == (4, ref_nt))
        self.assertTrue(prcp.shape == (4, ref_nt))
        np.testing.assert_allclose(prcp[2, :], [0, 0])
        np.testing.assert_allclose(temp[3, :], [0, 0])

        # FLATTEN -------------------------------------------------------------
        hgts = np.array([ref_h, ref_h, -8000, 8000])
        years, temp, prcp = climate.mb_yearly_climate_on_height(gdir, hgts,
                                                                flatten=True)

        ref_nt = 202
        self.assertTrue(len(years) == ref_nt)
        self.assertTrue(temp.shape == (ref_nt,))
        self.assertTrue(prcp.shape == (ref_nt,))

        yr = [1802, 1802]
        hgts = np.array([ref_h])
        years, temp, prcp = climate.mb_yearly_climate_on_height(gdir, hgts,
                                                                year_range=yr,
                                                                flatten=True)
        ref_nt = 1
        self.assertTrue(len(years) == ref_nt)
        self.assertTrue(years == 1802)
        self.assertTrue(temp.shape == (ref_nt,))
        self.assertTrue(prcp.shape == (ref_nt,))
        np.testing.assert_allclose(temp[:], np.sum(ref_t[0:12]))

        yr = [1802, 1802]
        hgts = np.array([8000])
        years, temp, prcp = climate.mb_yearly_climate_on_height(gdir, hgts,
                                                                year_range=yr,
                                                                flatten=True)
        np.testing.assert_allclose(prcp[:], np.sum(ref_p[0:12]))