Python Dataset.isel方法代码示例

# 需要导入模块: from xarray import Dataset [as 别名]
# 或者: from xarray.Dataset import isel [as 别名]
 def test_concat_multiindex(self):
     x = pd.MultiIndex.from_product([[1, 2, 3], ['a', 'b']])
     expected = Dataset({'x': x})
     actual = concat([expected.isel(x=slice(2)),
                      expected.isel(x=slice(2, None))], 'x')
     assert expected.equals(actual)
     assert isinstance(actual.x.to_index(), pd.MultiIndex)

# 需要导入模块: from xarray import Dataset [as 别名]
# 或者: from xarray.Dataset import isel [as 别名]
 def test_save_mfdataset_roundtrip(self):
     original = Dataset({'foo': ('x', np.random.randn(10))})
     datasets = [original.isel(x=slice(5)),
                 original.isel(x=slice(5, 10))]
     with create_tmp_file() as tmp1:
         with create_tmp_file() as tmp2:
             save_mfdataset(datasets, [tmp1, tmp2])
             with open_mfdataset([tmp1, tmp2]) as actual:
                 self.assertDatasetIdentical(actual, original)

# 需要导入模块: from xarray import Dataset [as 别名]
# 或者: from xarray.Dataset import isel [as 别名]
 def test_concat_coords(self):
     data = Dataset({"foo": ("x", np.random.randn(10))})
     expected = data.assign_coords(c=("x", [0] * 5 + [1] * 5))
     objs = [data.isel(x=slice(5)).assign_coords(c=0), data.isel(x=slice(5, None)).assign_coords(c=1)]
     for coords in ["different", "all", ["c"]]:
         actual = concat(objs, dim="x", coords=coords)
         self.assertDatasetIdentical(expected, actual)
     for coords in ["minimal", []]:
         with self.assertRaisesRegexp(ValueError, "not equal across"):
             concat(objs, dim="x", coords=coords)

# 需要导入模块: from xarray import Dataset [as 别名]
# 或者: from xarray.Dataset import isel [as 别名]
 def test_concat_coords(self):
     data = Dataset({'foo': ('x', np.random.randn(10))})
     expected = data.assign_coords(c=('x', [0] * 5 + [1] * 5))
     objs = [data.isel(x=slice(5)).assign_coords(c=0),
             data.isel(x=slice(5, None)).assign_coords(c=1)]
     for coords in ['different', 'all', ['c']]:
         actual = concat(objs, dim='x', coords=coords)
         self.assertDatasetIdentical(expected, actual)
     for coords in ['minimal', []]:
         with self.assertRaisesRegexp(ValueError, 'not equal across'):
             concat(objs, dim='x', coords=coords)

# 需要导入模块: from xarray import Dataset [as 别名]
# 或者: from xarray.Dataset import isel [as 别名]
    def test_open_mfdataset(self):
        original = Dataset({'foo': ('x', np.random.randn(10))})
        with create_tmp_file() as tmp1:
            with create_tmp_file() as tmp2:
                original.isel(x=slice(5)).to_netcdf(tmp1)
                original.isel(x=slice(5, 10)).to_netcdf(tmp2)
                with open_mfdataset([tmp1, tmp2]) as actual:
                    self.assertIsInstance(actual.foo.variable.data, da.Array)
                    self.assertEqual(actual.foo.variable.data.chunks,
                                     ((5, 5),))
                    self.assertDatasetAllClose(original, actual)
                with open_mfdataset([tmp1, tmp2], chunks={'x': 3}) as actual:
                    self.assertEqual(actual.foo.variable.data.chunks,
                                     ((3, 2, 3, 2),))

        with self.assertRaisesRegexp(IOError, 'no files to open'):
            open_mfdataset('foo-bar-baz-*.nc')

# 需要导入模块: from xarray import Dataset [as 别名]
# 或者: from xarray.Dataset import isel [as 别名]
def subset_temporal_index_impl(ds: xr.Dataset,
                               time_ind_min: int,
                               time_ind_max: int) -> xr.Dataset:
    """
    Do a temporal indices based subset

    :param ds: Dataset or dataframe to subset
    :param time_ind_min: Minimum time index to select
    :param time_ind_max: Maximum time index to select
    :return: Subset dataset
    """
    # we're creating a slice that includes both ends
    # to have the same functionality as subset_temporal
    time_slice = slice(time_ind_min, time_ind_max + 1)
    indexers = {'time': time_slice}
    return ds.isel(**indexers)

# 需要导入模块: from xarray import Dataset [as 别名]
# 或者: from xarray.Dataset import isel [as 别名]
def _group_anomaly(group: xr.Dataset,
                   ref: xr.Dataset,
                   monitor: Monitor = Monitor.NONE,
                   step: float = None):
    """
    Calculate anomaly for the given group.

    :param group: Result of a groupby('time.month') operation
    :param ref: Reference dataset
    :param monitor: Monitor of the parent method
    :param step: Step to add to monitor progress
    :return: Group dataset with anomaly calculation applied
    """
    # Retrieve the month of the current group
    month = group['time.month'][0].values
    ret = diff(group, ref.isel(time=month - 1))
    monitor.progress(work=step)
    return ret

# 需要导入模块: from xarray import Dataset [as 别名]
# 或者: from xarray.Dataset import isel [as 别名]
 def test_concat_data_vars(self):
     data = Dataset({'foo': ('x', np.random.randn(10))})
     objs = [data.isel(x=slice(5)), data.isel(x=slice(5, None))]
     for data_vars in ['minimal', 'different', 'all', [], ['foo']]:
         actual = concat(objs, dim='x', data_vars=data_vars)
         self.assertDatasetIdentical(data, actual)