ValueError: assignment destination is read-only
self = <climada.entity.exposures.test.test_base.TestChecker testMethod=test_error_geometry_fail>

    def test_error_geometry_fail(self):
        """Wrong exposures definition"""
        expo = good_exposures()
        expo.set_geometry_points()
>       expo.gdf.latitude.values[0] = 5
E       ValueError: assignment destination is read-only

climada/entity/exposures/test/test_base.py:282: ValueError

UnboundLocalError: cannot access local variable 'close_year' where it is not associated with a value
cntry_iso = 'CHE', ref_year = 2222, shp_file = None

    def income_group(cntry_iso, ref_year, shp_file=None):
        """Get country's income group from World Bank's data at a given year,
        or closest year value. If no data, get the natural earth's approximation.
    
        Parameters
        ----------
        cntry_iso : str
            key = ISO alpha_3 country
        ref_year : int
            reference year
        shp_file : cartopy.io.shapereader.Reader, optional
            shape file with
            INCOME_GRP attribute for every country. Load Natural Earth admin0
            if not provided.
        """
        try:
>           close_year, close_val = world_bank(cntry_iso, ref_year, 'INC_GRP')

climada/util/finance.py:121: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
climada/util/finance.py:210: in world_bank
    dfr_wb = dfr_wb.replace(INCOME_GRP_WB_TABLE.keys(),
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/generic.py:7867: in replace
    new_data = self._mgr.replace_list(
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/internals/base.py:253: in replace_list
    bm = self.apply_with_block(
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/internals/managers.py:354: in apply
    applied = getattr(b, f)(**kwargs)
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/internals/blocks.py:908: in replace_list
    b.refs.referenced_blocks.index(ref)
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/ops/common.py:76: in new_method
    return method(self, other)
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/arraylike.py:40: in __eq__
    return self._cmp_method(other, operator.eq)
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/indexes/base.py:7129: in _cmp_method
    result = ops.comp_method_OBJECT_ARRAY(op, self._values, other)
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/ops/array_ops.py:131: in comp_method_OBJECT_ARRAY
    result = libops.scalar_compare(x.ravel(), y, op)
ops.pyx:32: in pandas._libs.ops.scalar_compare
    ???
stringsource:660: in View.MemoryView.memoryview_cwrapper
    ???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: buffer source array is read-only

stringsource:350: ValueError

During handling of the above exception, another exception occurred:

self = <climada.entity.exposures.test.test_litpop.TestLitPop testMethod=test_get_total_value_per_country_gdp>

    def test_get_total_value_per_country_gdp(self):
        "test _get_total_value_per_country get number for gdp"
        gdp_togo = lp._get_total_value_per_country('TGO', 'gdp', 2010)
        gdp_switzerland = lp._get_total_value_per_country('CHE', 'gdp', 2222)
>       value_switzerland = lp._get_total_value_per_country('CHE', 'income_group', 2222)

climada/entity/exposures/test/test_litpop.py:349: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
climada/entity/exposures/litpop/litpop.py:864: in _get_total_value_per_country
    return gdp_value*(u_fin.income_group(cntry_iso3a, reference_year)[1]+1)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

cntry_iso = 'CHE', ref_year = 2222, shp_file = None

    def income_group(cntry_iso, ref_year, shp_file=None):
        """Get country's income group from World Bank's data at a given year,
        or closest year value. If no data, get the natural earth's approximation.
    
        Parameters
        ----------
        cntry_iso : str
            key = ISO alpha_3 country
        ref_year : int
            reference year
        shp_file : cartopy.io.shapereader.Reader, optional
            shape file with
            INCOME_GRP attribute for every country. Load Natural Earth admin0
            if not provided.
        """
        try:
            close_year, close_val = world_bank(cntry_iso, ref_year, 'INC_GRP')
        except (KeyError, IndexError):
            # take value from natural earth repository
            close_year, close_val = nat_earth_adm0(cntry_iso, 'INCOME_GRP',
                                                   shp_file=shp_file)
        finally:
>           LOGGER.info('Income group %s %s: %s.', cntry_iso, close_year, close_val)
E           UnboundLocalError: cannot access local variable 'close_year' where it is not associated with a value

climada/util/finance.py:127: UnboundLocalError

ValueError: assignment destination is read-only
self = <climada.entity.measures.test.test_base.TestApply testMethod=test_change_exposures_impf_pass>

    def test_change_exposures_impf_pass(self):
        """Test _change_exposures_impf"""
        meas = Measure(
            imp_fun_map='1to3',
            haz_type='TC',
        )
    
        imp_set = ImpactFuncSet()
    
        intensity = np.arange(10, 100, 10)
        mdd = np.arange(10, 100, 10)
        paa = np.arange(10, 100, 10)
        imp_tc = ImpactFunc("TC", 1, intensity, mdd, paa)
        imp_set.append(imp_tc)
    
        mdd = np.arange(10, 100, 10) * 2
        paa = np.arange(10, 100, 10) * 2
        imp_tc = ImpactFunc("TC", 3, intensity, mdd, paa)
    
        exp = Exposures.from_hdf5(EXP_DEMO_H5)
>       new_exp = meas._change_exposures_impf(exp)

climada/entity/measures/test/test_base.py:164: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <climada.entity.measures.base.Measure object at 0x78e389151890>
exposures = <climada.entity.exposures.base.Exposures object at 0x78e388d96c50>

    def _change_exposures_impf(self, exposures):
        """Change exposures impact functions ids according to imp_fun_map.
    
        Parameters
        ----------
        exposures : climada.entity.Exposures
            exposures instance
    
        Returns
        -------
        new_exp : climada.entity.Exposure
            Exposure with updated impact functions ids accordgin to
            impf_fun_map
        """
        if self.imp_fun_map == NULL_STR:
            return exposures
    
        LOGGER.debug('Setting new exposures impact functions%s', self.imp_fun_map)
        new_exp = exposures.copy(deep=True)
        from_id = int(self.imp_fun_map[0:self.imp_fun_map.find('to')])
        to_id = int(self.imp_fun_map[self.imp_fun_map.find('to') + 2:])
        try:
            exp_change = np.argwhere(
                new_exp.gdf[INDICATOR_IMPF + self.haz_type].values == from_id
            ).reshape(-1)
>           new_exp.gdf[INDICATOR_IMPF + self.haz_type].values[exp_change] = to_id
E           ValueError: assignment destination is read-only

climada/entity/measures/base.py:351: ValueError

ValueError: assignment destination is read-only
self = <climada.entity.measures.test.test_base.TestApply testMethod=test_cutoff_hazard_region_pass>

    def test_cutoff_hazard_region_pass(self):
        """Test _cutoff_hazard_damage in specific region"""
        meas = MeasureSet.from_mat(ENT_TEST_MAT)
        act_1 = meas.get_measure(name='Seawall')[0]
        act_1.exp_region_id = [1]
    
        haz = Hazard.from_mat(HAZ_TEST_MAT)
        exp = Exposures.from_mat(ENT_TEST_MAT)
        exp.gdf['region_id'] = np.zeros(exp.gdf.shape[0])
>       exp.gdf.region_id.values[10:] = 1
E       ValueError: assignment destination is read-only

climada/entity/measures/test/test_base.py:118: ValueError

ValueError: assignment destination is read-only
self = <climada.entity.measures.test.test_base.TestApply testMethod=test_filter_exposures_pass>

    def test_filter_exposures_pass(self):
        """Test _filter_exposures method with two values"""
        meas = Measure(
            exp_region_id=[3, 4],
            haz_type='TC',
        )
    
        exp = Exposures.from_mat(ENT_TEST_MAT)
        exp.gdf.rename(columns={'impf_': 'impf_TC', 'centr_': 'centr_TC'}, inplace=True)
        exp.gdf['region_id'] = np.ones(exp.gdf.shape[0])
>       exp.gdf.region_id.values[:exp.gdf.shape[0] // 2] = 3
E       ValueError: assignment destination is read-only

climada/entity/measures/test/test_base.py:243: ValueError

AssertionError: 45 != 44
self = <climada.hazard.centroids.test.test_centr.TestCentroidsReader testMethod=test_geodataframe>

    def test_geodataframe(self):
        """Test that constructing a valid Centroids instance from gdf works."""
        gdf = gpd.GeoDataFrame(pd.read_excel(HAZ_TEMPLATE_XLS))
        gdf.geometry = gpd.points_from_xy(
                gdf['longitude'], gdf['latitude']
        )
        gdf['elevation'] = np.random.rand(gdf.geometry.size)
        gdf['region_id'] = np.zeros(gdf.geometry.size)
        gdf['region_id'][0] = np.NaN
        gdf['geom'] = gdf.geometry  # this should have no effect on centroids
    
        centroids = Centroids.from_geodataframe(gdf)
        centroids.check()
    
        self.assertEqual(centroids.geometry.size, 45)
        self.assertEqual(centroids.lon[0], 32.57)
        self.assertEqual(centroids.lat[0], -25.95)
        self.assertEqual(centroids.elevation.size, 45)
>       self.assertEqual(centroids.on_land.sum(), 44)
E       AssertionError: 45 != 44

climada/hazard/centroids/test/test_centr.py:107: AssertionError

ValueError: output array is read-only
self = <climada.hazard.test.test_tc_tracks.TestFuncs testMethod=test_interp_track_pass>

    def test_interp_track_pass(self):
        """Interpolate track to min_time_step. Compare to MATLAB reference."""
        tc_track = tc.TCTracks.from_processed_ibtracs_csv(TEST_TRACK)
        tc_track.equal_timestep(time_step_h=1)
    
        self.assertEqual(tc_track.data[0].time.size, 223)
        self.assertAlmostEqual(tc_track.data[0].lon.values[11], -27.426151640151684)
        self.assertAlmostEqual(float(tc_track.data[0].lat[23]), 12.300006169591480)
        self.assertEqual(tc_track.data[0].time_step[7], 1)
        self.assertEqual(np.max(tc_track.data[0].radius_max_wind), 0)
        self.assertEqual(np.min(tc_track.data[0].radius_max_wind), 0)
        self.assertEqual(tc_track.data[0].max_sustained_wind[21], 25)
        self.assertTrue(np.isfinite(tc_track.data[0].central_pressure.values).all())
        self.assertAlmostEqual(tc_track.data[0].central_pressure.values[29], 1008, places=0)
        self.assertEqual(np.max(tc_track.data[0].environmental_pressure), 1010)
        self.assertEqual(np.min(tc_track.data[0].environmental_pressure), 1010)
        self.assertEqual(tc_track.data[0]['time.year'][13], 1951)
        self.assertEqual(tc_track.data[0]['time.month'][26], 8)
        self.assertEqual(tc_track.data[0]['time.day'][7], 27)
        self.assertEqual(tc_track.data[0].max_sustained_wind_unit, 'kn')
        self.assertEqual(tc_track.data[0].central_pressure_unit, 'mb')
        self.assertEqual(tc_track.data[0].orig_event_flag, 1)
        self.assertEqual(tc_track.data[0].name, '1951239N12334')
        self.assertEqual(tc_track.data[0].data_provider, 'hurdat_atl')
        np.testing.assert_array_equal(tc_track.data[0].basin, 'NA')
        self.assertEqual(tc_track.data[0].id_no, 1951239012334)
        self.assertEqual(tc_track.data[0].category, 1)
    
        # test some "generic floats"
        for time_step_h in [0.6663545049172093, 2.509374054925788, 8.175754471661111]:
            # artifically create data that doesn't start at full hour
            for loffset in [0, 22, 30]:
                tc_track = tc.TCTracks.from_processed_ibtracs_csv(TEST_TRACK)
>               tc_track.data[0].time.values[:] += np.timedelta64(loffset, "m")
E               ValueError: output array is read-only

climada/hazard/test/test_tc_tracks.py:632: ValueError

UnboundLocalError: cannot access local variable 'close_year' where it is not associated with a value
cntry_iso = 'SXM', ref_year = 1999
shp_file = <cartopy.io.shapereader.FionaReader object at 0x78e38acc9650>

    def income_group(cntry_iso, ref_year, shp_file=None):
        """Get country's income group from World Bank's data at a given year,
        or closest year value. If no data, get the natural earth's approximation.
    
        Parameters
        ----------
        cntry_iso : str
            key = ISO alpha_3 country
        ref_year : int
            reference year
        shp_file : cartopy.io.shapereader.Reader, optional
            shape file with
            INCOME_GRP attribute for every country. Load Natural Earth admin0
            if not provided.
        """
        try:
>           close_year, close_val = world_bank(cntry_iso, ref_year, 'INC_GRP')

climada/util/finance.py:121: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
climada/util/finance.py:210: in world_bank
    dfr_wb = dfr_wb.replace(INCOME_GRP_WB_TABLE.keys(),
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/generic.py:7867: in replace
    new_data = self._mgr.replace_list(
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/internals/base.py:253: in replace_list
    bm = self.apply_with_block(
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/internals/managers.py:354: in apply
    applied = getattr(b, f)(**kwargs)
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/internals/blocks.py:908: in replace_list
    b.refs.referenced_blocks.index(ref)
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/ops/common.py:76: in new_method
    return method(self, other)
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/arraylike.py:40: in __eq__
    return self._cmp_method(other, operator.eq)
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/indexes/base.py:7129: in _cmp_method
    result = ops.comp_method_OBJECT_ARRAY(op, self._values, other)
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/ops/array_ops.py:131: in comp_method_OBJECT_ARRAY
    result = libops.scalar_compare(x.ravel(), y, op)
ops.pyx:32: in pandas._libs.ops.scalar_compare
    ???
stringsource:660: in View.MemoryView.memoryview_cwrapper
    ???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: buffer source array is read-only

stringsource:350: ValueError

During handling of the above exception, another exception occurred:

self = <climada.util.test.test_finance.TestWBData testMethod=test_income_grp_sxm_1999_pass>

    def test_income_grp_sxm_1999_pass(self):
        """Test income_group function Sint Maarten."""
        ref_year = 1999
        with self.assertLogs('climada.util.finance', level='INFO') as cm:
>           ig_year, ig_val = income_group('SXM', ref_year, SHP_FILE)

climada/util/test/test_finance.py:70: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

cntry_iso = 'SXM', ref_year = 1999
shp_file = <cartopy.io.shapereader.FionaReader object at 0x78e38acc9650>

    def income_group(cntry_iso, ref_year, shp_file=None):
        """Get country's income group from World Bank's data at a given year,
        or closest year value. If no data, get the natural earth's approximation.
    
        Parameters
        ----------
        cntry_iso : str
            key = ISO alpha_3 country
        ref_year : int
            reference year
        shp_file : cartopy.io.shapereader.Reader, optional
            shape file with
            INCOME_GRP attribute for every country. Load Natural Earth admin0
            if not provided.
        """
        try:
            close_year, close_val = world_bank(cntry_iso, ref_year, 'INC_GRP')
        except (KeyError, IndexError):
            # take value from natural earth repository
            close_year, close_val = nat_earth_adm0(cntry_iso, 'INCOME_GRP',
                                                   shp_file=shp_file)
        finally:
>           LOGGER.info('Income group %s %s: %s.', cntry_iso, close_year, close_val)
E           UnboundLocalError: cannot access local variable 'close_year' where it is not associated with a value

climada/util/finance.py:127: UnboundLocalError

ValueError: buffer source array is read-only
self = <climada.util.test.test_finance.TestWBData testMethod=test_wb_income_grp_sxm_pass>

    def test_wb_income_grp_sxm_pass(self):
        """Test world_bank function Sint Maarten."""
        ref_year = 2012
>       wb_year, wb_val = world_bank('SXM', ref_year, 'INC_GRP')

climada/util/test/test_finance.py:59: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
climada/util/finance.py:210: in world_bank
    dfr_wb = dfr_wb.replace(INCOME_GRP_WB_TABLE.keys(),
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/generic.py:7867: in replace
    new_data = self._mgr.replace_list(
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/internals/base.py:253: in replace_list
    bm = self.apply_with_block(
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/internals/managers.py:354: in apply
    applied = getattr(b, f)(**kwargs)
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/internals/blocks.py:908: in replace_list
    b.refs.referenced_blocks.index(ref)
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/ops/common.py:76: in new_method
    return method(self, other)
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/arraylike.py:40: in __eq__
    return self._cmp_method(other, operator.eq)
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/indexes/base.py:7129: in _cmp_method
    result = ops.comp_method_OBJECT_ARRAY(op, self._values, other)
../../../micromamba/envs/climada_env_3.11/lib/python3.11/site-packages/pandas/core/ops/array_ops.py:131: in comp_method_OBJECT_ARRAY
    result = libops.scalar_compare(x.ravel(), y, op)
ops.pyx:32: in pandas._libs.ops.scalar_compare
    ???
stringsource:660: in View.MemoryView.memoryview_cwrapper
    ???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

>   ???
E   ValueError: buffer source array is read-only

stringsource:350: ValueError

ValueError: assignment destination is read-only
self = <climada.util.test.test_lines_polys_handler.TestExposureGeomToPnt testMethod=test_point_exposure_from_polygons_on_grid>

    def test_point_exposure_from_polygons_on_grid(self):
        """Test disaggregation of polygons to points on grid"""
        exp_poly = EXP_POLY.copy()
        res = 0.1
        exp_poly.set_gdf(exp_poly.gdf[exp_poly.gdf['population']<400000])
>       height, width, trafo = u_coord.pts_to_raster_meta(
            exp_poly.gdf.geometry.bounds, (res, res)
            )

climada/util/test/test_lines_polys_handler.py:214: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

points_bounds =              minx       miny     maxx       maxy
Zeeland  4.767854  51.941171  5.61974  52.285491
res = array([0.1, 0.1])

    def pts_to_raster_meta(points_bounds, res):
        """Transform vector data coordinates to raster.
    
        If a raster of the given resolution doesn't exactly fit the given bounds, the raster might have
        slightly larger (but never smaller) bounds.
    
        Parameters
        ----------
        points_bounds : tuple
            points total bounds (xmin, ymin, xmax, ymax)
        res : tuple
            resolution of output raster (xres, yres)
    
        Returns
        -------
        nrows : int
            Number of rows.
        ncols : int
            Number of columns.
        ras_trans : affine.Affine
            Affine transformation defining the raster.
        """
        bounds = np.asarray(points_bounds).reshape(2, 2)
        res = np.asarray(res).ravel()
        if res.size == 1:
            res = np.array([res[0], res[0]])
        sizes = bounds[1, :] - bounds[0, :]
        nsteps = np.floor(sizes / np.abs(res)) + 1
        nsteps[np.abs(nsteps * res) < sizes + np.abs(res) / 2] += 1
>       bounds[:, res < 0] = bounds[::-1, res < 0]
E       ValueError: assignment destination is read-only

climada/util/coordinates.py:1748: ValueError