How to use psyplot - 10 common examples

with self.assertWarnsRegex(RuntimeWarning,
                                           'multiple matches'):
                    coords = 'time lat lon lev x y latitude longitude'.split()
                    ds.t2m.attrs.pop('coordinates', None)
                    for dim in 'xytz':
                        getattr(d, dim).update(coords)
                    for coord in set(coords).intersection(ds.coords):
                        ds.coords[coord].attrs.pop('axis', None)
                    getattr(d, func_name)(ds.t2m)
        uname = uname or name
        circ_name = circ_name or name
        ds = psyd.open_dataset(os.path.join(bt.test_dir, 'test-t2m-u-v.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(name)
        ds.close()
        ds = psyd.open_dataset(os.path.join(bt.test_dir, 'icon_test.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(uname)
        ds.close()
        ds = psyd.open_dataset(
            os.path.join(bt.test_dir, 'circumpolar_test.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(circ_name)
        ds.close()

self.assertIsNone(getattr(d, func_name)(ds.t2m_2d))
            if six.PY3:
                # Test whether the warning is raised if the decoder finds
                # multiple dimensions
                with self.assertWarnsRegex(RuntimeWarning,
                                           'multiple matches'):
                    coords = 'time lat lon lev x y latitude longitude'.split()
                    ds.t2m.attrs.pop('coordinates', None)
                    for dim in 'xytz':
                        getattr(d, dim).update(coords)
                    for coord in set(coords).intersection(ds.coords):
                        ds.coords[coord].attrs.pop('axis', None)
                    getattr(d, func_name)(ds.t2m)
        uname = uname or name
        circ_name = circ_name or name
        ds = psyd.open_dataset(os.path.join(bt.test_dir, 'test-t2m-u-v.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(name)
        ds.close()
        ds = psyd.open_dataset(os.path.join(bt.test_dir, 'icon_test.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(uname)
        ds.close()
        ds = psyd.open_dataset(
            os.path.join(bt.test_dir, 'circumpolar_test.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(circ_name)
        ds.close()

'multiple matches'):
                    coords = 'time lat lon lev x y latitude longitude'.split()
                    ds.t2m.attrs.pop('coordinates', None)
                    for dim in 'xytz':
                        getattr(d, dim).update(coords)
                    for coord in set(coords).intersection(ds.coords):
                        ds.coords[coord].attrs.pop('axis', None)
                    getattr(d, func_name)(ds.t2m)
        uname = uname or name
        circ_name = circ_name or name
        ds = psyd.open_dataset(os.path.join(bt.test_dir, 'test-t2m-u-v.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(name)
        ds.close()
        ds = psyd.open_dataset(os.path.join(bt.test_dir, 'icon_test.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(uname)
        ds.close()
        ds = psyd.open_dataset(
            os.path.join(bt.test_dir, 'circumpolar_test.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(circ_name)
        ds.close()

'multiple matches'):
                    coords = 'time lat lon lev x y latitude longitude'.split()
                    ds.t2m.attrs.pop('coordinates', None)
                    for dim in 'xytz':
                        getattr(d, dim).update(coords)
                    for coord in set(coords).intersection(ds.coords):
                        ds.coords[coord].attrs.pop('axis', None)
                    getattr(d, func_name)(ds.t2m)
        uname = uname or name
        circ_name = circ_name or name
        ds = psyd.open_dataset(os.path.join(bt.test_dir, 'test-t2m-u-v.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(name)
        ds.close()
        ds = psyd.open_dataset(os.path.join(bt.test_dir, 'icon_test.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(uname)
        ds.close()
        ds = psyd.open_dataset(
            os.path.join(bt.test_dir, 'circumpolar_test.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(circ_name)
        ds.close()

if six.PY3:
                # Test whether the warning is raised if the decoder finds
                # multiple dimensions
                with self.assertWarnsRegex(RuntimeWarning,
                                           'multiple matches'):
                    coords = 'time lat lon lev x y latitude longitude'.split()
                    ds.t2m.attrs.pop('coordinates', None)
                    for dim in 'xytz':
                        getattr(d, dim).update(coords)
                    for coord in set(coords).intersection(ds.coords):
                        ds.coords[coord].attrs.pop('axis', None)
                    getattr(d, func_name)(ds.t2m)
        uname = uname or name
        circ_name = circ_name or name
        ds = psyd.open_dataset(os.path.join(bt.test_dir, 'test-t2m-u-v.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(name)
        ds.close()
        ds = psyd.open_dataset(os.path.join(bt.test_dir, 'icon_test.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(uname)
        ds.close()
        ds = psyd.open_dataset(
            os.path.join(bt.test_dir, 'circumpolar_test.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(circ_name)
        ds.close()

if six.PY3:
                # Test whether the warning is raised if the decoder finds
                # multiple dimensions
                with self.assertWarnsRegex(RuntimeWarning,
                                           'multiple matches'):
                    coords = 'time lat lon lev x y latitude longitude'.split()
                    ds.t2m.attrs.pop('coordinates', None)
                    for dim in 'xytz':
                        getattr(d, dim).update(coords)
                    for coord in set(coords).intersection(ds.coords):
                        ds.coords[coord].attrs.pop('axis', None)
                    getattr(d, func_name)(ds.t2m)
        uname = uname or name
        circ_name = circ_name or name
        ds = psyd.open_dataset(os.path.join(bt.test_dir, 'test-t2m-u-v.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(name)
        ds.close()
        ds = psyd.open_dataset(os.path.join(bt.test_dir, 'icon_test.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(uname)
        ds.close()
        ds = psyd.open_dataset(
            os.path.join(bt.test_dir, 'circumpolar_test.nc'))
        d = psyd.CFDecoder(ds)
        check_ds(circ_name)
        ds.close()

def test_update_06_2variables(self):
        """test the change of the variable of a concatenated array"""
        ds = psyd.open_dataset(bt.get_file('test-t2m-u-v.nc'))
        arr = ds[['t2m', 'u']].to_array().isel(time=0, lev=0, lat=0)
        arr.attrs['test'] = 4
        self.assertNotIn('test', ds.t2m.attrs)
        arr.name = 'something'
        arr.psy.base = ds
        self.assertEqual(dict(arr.psy.idims), {'time': 0, 'lev': 0, 'lat': 0,
                                               'lon': slice(None)})
        self.assertEqual(arr.coords['variable'].values.tolist(), ['t2m', 'u'])
        # update to next time step
        arr.psy.update(time=1, name=['u', 'v'])
        self.assertEqual(arr.time, ds.time[1])
        self.assertEqual(arr.coords['variable'].values.tolist(), ['u', 'v'])
        self.assertEqual(arr.values.tolist(),
                         ds[['u', 'v']].to_array()[
                             :, 1, 0, 0, :].values.tolist())
        self.assertEqual(dict(arr.psy.idims), {'time': 1, 'lev': 0, 'lat': 0,

def test_fldstd_01_lola(self):
        from psyplot.project import Cdo
        fname = bt.get_file('test-t2m-u-v.nc')
        ds = psyd.open_dataset(fname)
        psyd.rcParams['gridweights.use_cdo'] = True
        std = ds.psy.t2m.psy.fldstd(keepdims=True).values
        ref = Cdo().fldstd(input=fname, returnArray='t2m')
        self.assertAlmostArrayEqual(std, ref)
        # try it with the self defined gridweights
        psyd.rcParams['gridweights.use_cdo'] = False
        std = ds.psy.t2m.psy.fldstd(keepdims=True).values
        self.assertAlmostArrayEqual(std, ref, rtol=1e-3)
        ds.close()

def _test_engine(self, engine):
        from importlib import import_module
        fname = self.fname
        ds = psyd.open_dataset(fname, engine=engine).load()
        self.assertEqual(ds.psy.filename, fname)
        store_mod, store = ds.psy.data_store
        # try to load the dataset
        mod = import_module(store_mod)
        try:
            ds2 = psyd.open_dataset(getattr(mod, store).open(fname))
        except AttributeError:
            ds2 = psyd.open_dataset(getattr(mod, store)(fname))
        ds.close()
        ds2.close()
        ds.psy.filename = None
        dumped_fname, dumped_store_mod, dumped_store = psyd.get_filename_ds(
            ds, dump=True, engine=engine, paths=True)
        self.assertTrue(dumped_fname)
        self.assertTrue(osp.exists(dumped_fname),
                        msg='Missing %s' % fname)

def test_open_dataset(self):
        fname = self.test_to_netcdf()
        ref_ds = self._test_ds
        ds = psyd.open_dataset(fname)
        self.assertEqual(
            pd.to_datetime(ds.time.values).tolist(),
            pd.to_datetime(ref_ds.time.values).tolist())