pull_requests: 480770321
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| id | node_id | number | state | locked | title | user | body | created_at | updated_at | closed_at | merged_at | merge_commit_sha | assignee | milestone | draft | head | base | author_association | auto_merge | repo | url | merged_by |
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| 480770321 | MDExOlB1bGxSZXF1ZXN0NDgwNzcwMzIx | 4408 | closed | 0 | Fix doctests | 14808389 | This is an attempt to fix the examples in our docstrings. With this, the output of: ```bash python -m pytest --doctest-modules xarray --ignore xarray/tests ``` is <details><summary>remaining warnings and errors</summary> ``` ====================================================================================================== test session starts ======================================================================================================= platform linux -- Python 3.8.5, pytest-6.0.1, py-1.9.0, pluggy-0.13.1 rootdir: ..., configfile: setup.cfg plugins: cov-2.10.0, env-0.6.2, hypothesis-5.23.11 collected 91 items xarray/conventions.py FF [ 2%] xarray/backends/api.py F [ 3%] xarray/coding/cftime_offsets.py . [ 4%] xarray/coding/cftimeindex.py .... [ 8%] xarray/coding/strings.py F [ 9%] xarray/core/accessor_dt.py ... [ 13%] xarray/core/accessor_str.py . [ 14%] xarray/core/alignment.py .. [ 16%] xarray/core/combine.py .. [ 18%] xarray/core/common.py ....F...... [ 30%] xarray/core/computation.py ..... [ 36%] xarray/core/dataarray.py ....................... [ 61%] xarray/core/dataset.py .....F............. [ 82%] xarray/core/extensions.py . [ 83%] xarray/core/groupby.py . [ 84%] xarray/core/indexing.py FF [ 86%] xarray/core/merge.py . [ 87%] xarray/core/nputils.py . [ 89%] xarray/core/options.py . [ 90%] xarray/core/parallel.py . [ 91%] xarray/core/rolling.py .. [ 93%] xarray/core/rolling_exp.py . [ 94%] xarray/core/utils.py . [ 95%] xarray/core/variable.py .. [ 97%] xarray/plot/utils.py .. [100%] ============================================================================================================ FAILURES ============================================================================================================ ___________________________________________________________________________________________ [doctest] xarray.conventions.BoolTypeArray ___________________________________________________________________________________________ 048 Decode arrays on the fly from integer to boolean datatype 049 050 This is useful for decoding boolean arrays from integer typed netCDF 051 variables. 052 053 >>> x = np.array([1, 0, 1, 1, 0], dtype="i1") 054 055 >>> x.dtype Expected: dtype('>i2') Got: dtype('int8') .../xarray/conventions.py:55: DocTestFailure _______________________________________________________________________________________ [doctest] xarray.conventions.NativeEndiannessArray _______________________________________________________________________________________ 021 022 >>> x = np.arange(5, dtype=">i2") 023 024 >>> x.dtype 025 dtype('>i2') 026 027 >>> NativeEndiannessArray(x).dtype 028 dtype('int16') 029 030 >>> NativeEndiannessArray(x)[:].dtype UNEXPECTED EXCEPTION: TypeError("unexpected key type: <class 'slice'>") Traceback (most recent call last): File "~/.conda/envs/xarray/lib/python3.8/doctest.py", line 1336, in __run exec(compile(example.source, filename, "single", File "<doctest xarray.conventions.NativeEndiannessArray[3]>", line 1, in <module> File ".../xarray/conventions.py", line 44, in __getitem__ return np.asarray(self.array[key], dtype=self.dtype) File ".../xarray/core/indexing.py", line 1277, in __getitem__ array, key = self._indexing_array_and_key(key) File ".../xarray/core/indexing.py", line 1269, in _indexing_array_and_key raise TypeError("unexpected key type: {}".format(type(key))) TypeError: unexpected key type: <class 'slice'> .../xarray/conventions.py:30: UnexpectedException __________________________________________________________________________________________ [doctest] xarray.backends.api.save_mfdataset __________________________________________________________________________________________ 1182 compute : bool 1183 If true compute immediately, otherwise return a 1184 ``dask.delayed.Delayed`` object that can be computed later. 1185 1186 Examples 1187 -------- 1188 1189 Save a dataset into one netCDF per year of data: 1190 1191 >>> years, datasets = zip(*ds.groupby("time.year")) UNEXPECTED EXCEPTION: NameError("name 'ds' is not defined") Traceback (most recent call last): File "~/.conda/envs/xarray/lib/python3.8/doctest.py", line 1336, in __run exec(compile(example.source, filename, "single", File "<doctest xarray.backends.api.save_mfdataset[0]>", line 1, in <module> NameError: name 'ds' is not defined .../xarray/backends/api.py:1191: UnexpectedException _______________________________________________________________________________________ [doctest] xarray.coding.strings.StackedBytesArray ________________________________________________________________________________________ 199 Wrapper around array-like objects to create a new indexable object where 200 values, when accessed, are automatically stacked along the last dimension. 201 202 >>> StackedBytesArray(np.array(["a", "b", "c"]))[:] UNEXPECTED EXCEPTION: ValueError("can only use StackedBytesArray if argument has dtype='S1'") Traceback (most recent call last): File "~/.conda/envs/xarray/lib/python3.8/doctest.py", line 1336, in __run exec(compile(example.source, filename, "single", File "<doctest xarray.coding.strings.StackedBytesArray[0]>", line 1, in <module> File ".../xarray/coding/strings.py", line 215, in __init__ raise ValueError( ValueError: can only use StackedBytesArray if argument has dtype='S1' .../xarray/coding/strings.py:202: UnexpectedException ________________________________________________________________________________________ [doctest] xarray.core.common.DataWithCoords.pipe ________________________________________________________________________________________ 578 >>> def adder(data, arg): 579 ... return data + arg 580 ... 581 >>> def div(data, arg): 582 ... return data / arg 583 ... 584 >>> def sub_mult(data, sub_arg, mult_arg): 585 ... return (data * mult_arg) - sub_arg 586 ... 587 >>> x.pipe(adder, 2) Differences (unified diff with -expected +actual): @@ -2,6 +2,6 @@ Dimensions: (lat: 2, lon: 2) Coordinates: + * lon (lon) int64 150 160 * lat (lat) int64 10 20 - * lon (lon) int64 150 160 Data variables: temperature_c (lat, lon) float64 12.98 16.3 14.06 12.9 .../xarray/core/common.py:587: DocTestFailure _____________________________________________________________________________________ [doctest] xarray.core.dataset.Dataset.filter_by_attrs ______________________________________________________________________________________ 5719 ... }, 5720 ... coords={ 5721 ... "lon": (["x", "y"], lon), 5722 ... "lat": (["x", "y"], lat), 5723 ... "time": pd.date_range("2014-09-06", periods=3), 5724 ... "reference_time": pd.Timestamp("2014-09-05"), 5725 ... }, 5726 ... ) 5727 >>> # Get variables matching a specific standard_name. 5728 >>> ds.filter_by_attrs(standard_name="convective_precipitation_flux") Differences (unified diff with -expected +actual): @@ -2,8 +2,8 @@ Dimensions: (time: 3, x: 2, y: 2) Coordinates: + lon (x, y) float64 -99.83 -99.32 -99.79 -99.23 + * time (time) datetime64[ns] 2014-09-06 2014-09-07 2014-09-08 + lat (x, y) float64 42.25 42.21 42.63 42.59 reference_time datetime64[ns] 2014-09-05 - lat (x, y) float64 42.25 42.21 42.63 42.59 - * time (time) datetime64[ns] 2014-09-06 2014-09-07 2014-09-08 - lon (x, y) float64 -99.83 -99.32 -99.79 -99.23 Dimensions without coordinates: x, y Data variables: .../xarray/core/dataset.py:5728: DocTestFailure ____________________________________________________________________________________ [doctest] xarray.core.indexing._decompose_outer_indexer _____________________________________________________________________________________ 971 ----- 972 This function is used to realize the vectorized indexing for the backend 973 arrays that only support basic or outer indexing. 974 975 As an example, let us consider to index a few elements from a backend array 976 with a orthogonal indexer ([0, 3, 1], [2, 3, 2]). 977 Even if the backend array only supports basic indexing, it is more 978 efficient to load a subslice of the array than loading the entire array, 979 980 >>> backend_indexer = BasicIndexer(slice(0, 3), slice(2, 3)) UNEXPECTED EXCEPTION: TypeError('__init__() takes 2 positional arguments but 3 were given') Traceback (most recent call last): File "~/.conda/envs/xarray/lib/python3.8/doctest.py", line 1336, in __run exec(compile(example.source, filename, "single", File "<doctest xarray.core.indexing._decompose_outer_indexer[0]>", line 1, in <module> TypeError: __init__() takes 2 positional arguments but 3 were given .../xarray/core/indexing.py:980: UnexpectedException __________________________________________________________________________________ [doctest] xarray.core.indexing._decompose_vectorized_indexer __________________________________________________________________________________ 893 ----- 894 This function is used to realize the vectorized indexing for the backend 895 arrays that only support basic or outer indexing. 896 897 As an example, let us consider to index a few elements from a backend array 898 with a vectorized indexer ([0, 3, 1], [2, 3, 2]). 899 Even if the backend array only supports outer indexing, it is more 900 efficient to load a subslice of the array than loading the entire array, 901 902 >>> backend_indexer = OuterIndexer([0, 1, 3], [2, 3]) UNEXPECTED EXCEPTION: TypeError('__init__() takes 2 positional arguments but 3 were given') Traceback (most recent call last): File "~/.conda/envs/xarray/lib/python3.8/doctest.py", line 1336, in __run exec(compile(example.source, filename, "single", File "<doctest xarray.core.indexing._decompose_vectorized_indexer[0]>", line 1, in <module> TypeError: __init__() takes 2 positional arguments but 3 were given .../xarray/core/indexing.py:902: UnexpectedException ======================================================================================================== warnings summary ======================================================================================================== xarray/core/common.py::xarray.core.common.DataWithCoords.resample xarray/core/common.py::xarray.core.common.DataWithCoords.resample xarray/core/common.py::xarray.core.common.DataWithCoords.resample .../xarray/core/common.py:1230: FutureWarning: 'base' in .resample() and in Grouper() is deprecated. The new arguments that you should use are 'offset' or 'origin'. >>> df.resample(freq="3s", base=2) becomes: >>> df.resample(freq="3s", offset="2s") grouper = pd.Grouper( xarray/core/dataarray.py::xarray.core.dataarray.DataArray.argmax xarray/core/dataarray.py::xarray.core.dataarray.DataArray.idxmax .../xarray/core/dataarray.py:4090: DeprecationWarning: Behaviour of argmin/argmax with neither dim nor axis argument will change to return a dict of indices of each dimension. To get a single, flat index, please use np.argmin(da.data) or np.argmax(da.data) instead of da.argmin() or da.argmax(). result = self.variable.argmax(dim, axis, keep_attrs, skipna) xarray/core/dataarray.py::xarray.core.dataarray.DataArray.argmin xarray/core/dataarray.py::xarray.core.dataarray.DataArray.idxmin .../xarray/core/dataarray.py:3987: DeprecationWarning: Behaviour of argmin/argmax with neither dim nor axis argument will change to return a dict of indices of each dimension. To get a single, flat index, please use np.argmin(da.data) or np.argmax(da.data) instead of da.argmin() or da.argmax(). result = self.variable.argmin(dim, axis, keep_attrs, skipna) xarray/core/dataarray.py::xarray.core.dataarray.DataArray.roll .../xarray/core/dataarray.py:2974: FutureWarning: roll_coords will be set to False in the future. Explicitly set roll_coords to silence warning. ds = self._to_temp_dataset().roll( xarray/core/dataset.py::xarray.core.dataset.Dataset.roll <doctest xarray.core.dataset.Dataset.roll[1]>:1: FutureWarning: roll_coords will be set to False in the future. Explicitly set roll_coords to silence warning. -- Docs: https://docs.pytest.org/en/stable/warnings.html ==================================================================================================== short test summary info ===================================================================================================== FAILED xarray/conventions.py::xarray.conventions.BoolTypeArray FAILED xarray/conventions.py::xarray.conventions.NativeEndiannessArray FAILED xarray/backends/api.py::xarray.backends.api.save_mfdataset FAILED xarray/coding/strings.py::xarray.coding.strings.StackedBytesArray FAILED xarray/core/common.py::xarray.core.common.DataWithCoords.pipe FAILED xarray/core/dataset.py::xarray.core.dataset.Dataset.filter_by_attrs FAILED xarray/core/indexing.py::xarray.core.indexing._decompose_outer_indexer FAILED xarray/core/indexing.py::xarray.core.indexing._decompose_vectorized_indexer ============================================================================================ 8 failed, 83 passed, 9 warnings in 3.73s ============================================================================================ ``` </details> where `DataWithCoords.pipe` and `Dataset.filter_by_attrs` fail mostly because the order of the coords is not deterministic. Should we sort before formatting the coords? Does anyone know what `ds` in `save_mfdataset` should look like? Also, how do we fix the construction of `OuterIndexer` and `VectorizedIndexer`? - [x] Closes #3837 - [ ] Tests added - [x] Passes `isort . && black . && mypy . && flake8` - [ ] User visible changes (including notable bug fixes) are documented in `whats-new.rst` Edit: if we merge #4409 before this, we can make sure *all* doctests pass. | 2020-09-06T13:42:39Z | 2020-09-11T21:27:06Z | 2020-09-11T12:34:34Z | 2020-09-11T12:34:34Z | 23dc2fc9f2785c348ff821bf2da61dfa2206d283 | 0 | 25b0ab889291e729d20e9e00bbde9eea6c9a44dc | a6eccfa346b14d83a745cdbfe4718d8c046c5e12 | MEMBER | 13221727 | https://github.com/pydata/xarray/pull/4408 |
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