本文整理汇总了Python中xarray.Dataset.isel方法的典型用法代码示例。如果您正苦于以下问题:Python Dataset.isel方法的具体用法?Python Dataset.isel怎么用?Python Dataset.isel使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类xarray.Dataset
的用法示例。
在下文中一共展示了Dataset.isel方法的8个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_concat_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_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)
示例2: test_save_mfdataset_roundtrip
# 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)
示例3: test_concat_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)
示例4: test_concat_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)
示例5: test_open_mfdataset
# 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')
示例6: subset_temporal_index_impl
# 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)
示例7: _group_anomaly
# 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
示例8: test_concat_data_vars
# 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)