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id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at ▲ | closed_at | author_association | active_lock_reason | draft | pull_request | body | reactions | performed_via_github_app | state_reason | repo | type |
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1021396447 | PR_kwDOAMm_X84s9Wtg | 5847 | Display coords' units for slice plots | caenrigen 31376402 | closed | 0 | 10 | 2021-10-08T19:18:38Z | 2021-10-30T14:06:41Z | 2021-10-30T14:06:41Z | CONTRIBUTOR | 0 | pydata/xarray/pulls/5847 | Hi, folks! Thank you for the awesome project! Here is a minor enhancement for the plotting of slices. Before this PR: ```python import xarray as xr import numpy as np dset = xr.Dataset( data_vars=dict( var_a=(("a", "b"), np.array([[1,2], [3,4]])) ), coords=dict( a=("a", np.array([5, 6]), {"unit": "s"}), b=("b", np.array([7, 8]), {"unit": "s"}) ) ) _ = dset.var_a.sel(a=5).plot(marker="o") ``` After this PR (note the title): I did not add any tests, since this change did not break anything I am guessing it is not something being tested.
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819937730 | MDU6SXNzdWU4MTk5Mzc3MzA= | 4985 | Tests fail when installing h5netcdf without netcdf4 | caenrigen 31376402 | closed | 0 | 4 | 2021-03-02T11:42:13Z | 2021-07-17T21:04:59Z | 2021-07-17T21:04:59Z | CONTRIBUTOR | What happened: Created a new conda env for xarray as described in the contribution guide.
Then I installed the What you expected to happen: Tests should not fail if a package is not a requirement and the backends can operate independently. Minimal Complete Verifiable Example:
```python ======================================================================== FAILURES ========================================================================= ________ TestH5NetCDFAlreadyOpen.test_deepcopy ________ [gw0] darwin -- Python 3.8.8 /usr/local/anaconda3/envs/xarray/bin/python3.8 self = <xarray.tests.test_backends.TestH5NetCDFAlreadyOpen object at 0x11ce5d5e0>
/Users/Victor/Documents/ProjectsDev/Qblox/xarray/xarray/tests/test_backends.py:2717: NameError ________ TestH5NetCDFAlreadyOpen.testopen_dataset_group _________ [gw1] darwin -- Python 3.8.8 /usr/local/anaconda3/envs/xarray/bin/python3.8 self = <xarray.tests.test_backends.TestH5NetCDFAlreadyOpen object at 0x11cfe6bb0>
/Users/Victor/Documents/ProjectsDev/Qblox/xarray/xarray/tests/test_backends.py:2690: NameError _________ test_load_single_value_h5netcdf ___________ [gw0] darwin -- Python 3.8.8 /usr/local/anaconda3/envs/xarray/bin/python3.8
/Users/Victor/Documents/ProjectsDev/Qblox/xarray/xarray/backends/api.py:105: ModuleNotFoundError During handling of the above exception, another exception occurred:
/Users/Victor/Documents/ProjectsDev/Qblox/xarray/xarray/backends/api.py:110: ModuleNotFoundError During handling of the above exception, another exception occurred: tmp_path = PosixPath('/private/var/folders/9k/k5388g_s44b_97319sslv9c40000gn/T/pytest-of-Victor/pytest-3/popen-gw0/test_load_single_value_h5netcd0')
/Users/Victor/Documents/ProjectsDev/Qblox/xarray/xarray/tests/test_backends.py:4993: /Users/Victor/Documents/ProjectsDev/Qblox/xarray/xarray/core/dataset.py:1689: in to_netcdf return to_netcdf( /Users/Victor/Documents/ProjectsDev/Qblox/xarray/xarray/backends/api.py:1052: in to_netcdf engine = _get_default_engine(path_or_file) /Users/Victor/Documents/ProjectsDev/Qblox/xarray/xarray/backends/api.py:145: in _get_default_engine engine = _get_default_engine_netcdf()
/Users/Victor/Documents/ProjectsDev/Qblox/xarray/xarray/backends/api.py:114: ValueError ==================================================================== warnings summary ===================================================================== xarray/tests/test_accessor_str.py: 18 warnings /Users/Victor/Documents/ProjectsDev/Qblox/xarray/xarray/core/duck_array_ops.py:248: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison flag_array = (arr1 == arr2) | (isnull(arr1) & isnull(arr2)) xarray/tests/test_dataset.py::TestDataset::test_resample_loffset /Users/Victor/Documents/ProjectsDev/Qblox/xarray/xarray/tests/test_dataset.py:3904: FutureWarning: 'loffset' in .resample() and in Grouper() is deprecated.
becomes:
xarray/tests/test_dataarray.py::TestDataArray::test_resample /Users/Victor/Documents/ProjectsDev/Qblox/xarray/xarray/tests/test_dataarray.py:2994: FutureWarning: 'loffset' in .resample() and in Grouper() is deprecated.
becomes:
xarray/tests/test_dataarray.py::TestDataArray::test_polyfit[True-False] xarray/tests/test_dataarray.py::TestDataArray::test_polyfit[False-False] /Users/Victor/Documents/ProjectsDev/Qblox/xarray/xarray/core/dataset.py:6396: RuntimeWarning: overflow encountered in multiply scale = np.sqrt((lhs * lhs).sum(axis=0)) -- Docs: https://docs.pytest.org/en/stable/warnings.html ================================================================= short test summary info ================================================================= FAILED xarray/tests/test_backends.py::TestH5NetCDFAlreadyOpen::test_deepcopy - NameError: name 'nc4' is not defined FAILED xarray/tests/test_backends.py::TestH5NetCDFAlreadyOpen::test_open_dataset_group - NameError: name 'nc4' is not defined FAILED xarray/tests/test_backends.py::test_load_single_value_h5netcdf - ValueError: cannot read or write netCDF files without netCDF4-python or scipy in... ============================== 3 failed, 3474 passed, 4472 skipped, 65 xfailed, 17 xpassed, 22 warnings in 66.86s (0:01:06) =============================== ``` Anything else we need to know?: Tests still fail when installing They only pass after installing both Environment: Output of <tt>xr.show_versions()</tt>INSTALLED VERSIONS ------------------ commit: 48378c4b11c5c2672ff91396d4284743165b4fbe python: 3.8.8 | packaged by conda-forge | (default, Feb 20 2021, 16:12:38) [Clang 11.0.1 ] python-bits: 64 OS: Darwin OS-release: 18.7.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: en_US.UTF-8 LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.12.0 libnetcdf: None xarray: 0.17.1.dev3+g48378c4b pandas: 1.2.2 numpy: 1.20.1 scipy: None netCDF4: None pydap: None h5netcdf: 0.10.0 h5py: 3.1.0 Nio: None zarr: None cftime: 1.4.1 nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: None distributed: None matplotlib: None cartopy: None seaborn: None numbagg: None pint: None setuptools: 49.6.0.post20210108 pip: 21.0.1 conda: None pytest: 6.2.2 IPython: None sphinx: None |
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completed | xarray 13221727 | issue | ||||||
819967505 | MDExOlB1bGxSZXF1ZXN0NTgyOTg5Mjc2 | 4986 | Added support for numpy.bool_ | caenrigen 31376402 | closed | 0 | 2 | 2021-03-02T12:22:17Z | 2021-06-30T17:49:25Z | 2021-03-12T14:19:15Z | CONTRIBUTOR | 0 | pydata/xarray/pulls/4986 | Hi folks! Thank you for the awesome project! Xarray rocks! We have adopted xarray fully in a new project and would appreciate a review on this PR asap.
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xarray 13221727 | pull | |||||
819379617 | MDU6SXNzdWU4MTkzNzk2MTc= | 4981 | Allows numpy.bool_ attrs when writing with h5netcdf engine | caenrigen 31376402 | closed | 0 | 5 | 2021-03-01T22:53:04Z | 2021-03-12T14:19:14Z | 2021-03-12T14:19:14Z | CONTRIBUTOR | What happened: Round trip dataset using What you expected to happen: Attributes of Minimal Complete Verifiable Example: ```python import h5netcdf import numpy as np import xarray as xr dset = xr.Dataset( coords={"x0": np.array([1, 2, 3])}, data_vars={"y0": ("x0", np.array([5, 6, 7]))} ) dset.attrs["my_bool_attr"] = True print(type(dset.attrs["my_bool_attr"])) print("\n", dset) ``` ``` <class 'bool'> <xarray.Dataset> Dimensions: (x0: 3) Coordinates: * x0 (x0) int64 1 2 3 Data variables: y0 (x0) int64 5 6 7 Attributes: my_bool_attr: True ``` ```python file_name = "my_dset.nc" dset.to_netcdf(file_name, engine="h5netcdf", invalid_netcdf=True) loaded_dset = xr.load_dataset(file_name, engine="h5netcdf") print(type(loaded_dset.attrs["my_bool_attr"])) print("\n", loaded_dset) This should be workingfile_name2 = "file_numpy_bool.nc" loaded_dset.to_netcdf(file_name2, engine="h5netcdf", invalid_netcdf=True) loaded_dset2 = xr.load_dataset(file_name2, engine="h5netcdf") print("\n", loaded_dset) ``` Raises: ``` <class 'numpy.bool_'> <xarray.Dataset> Dimensions: (x0: 3) Coordinates: * x0 (x0) int64 1 2 3 Data variables: y0 (x0) int64 5 6 7 Attributes: my_bool_attr: True TypeError Traceback (most recent call last) <ipython-input-6-f74d2909a4a1> in <module> 6 # This should be working 7 file_name2 = "file_numpy_bool.nc" ----> 8 loaded_dset.to_netcdf(file_name2, engine="h5netcdf", invalid_netcdf=True) 9 loaded_dset2 = xr.load_dataset(file_name2, engine="h5netcdf") 10 /usr/local/anaconda3/envs/dclab/lib/python3.7/site-packages/xarray/core/dataset.py in to_netcdf(self, path, mode, format, group, engine, encoding, unlimited_dims, compute, invalid_netcdf) 1697 unlimited_dims=unlimited_dims, 1698 compute=compute, -> 1699 invalid_netcdf=invalid_netcdf, 1700 ) 1701 /usr/local/anaconda3/envs/dclab/lib/python3.7/site-packages/xarray/backends/api.py in to_netcdf(dataset, path_or_file, mode, format, group, engine, encoding, unlimited_dims, compute, multifile, invalid_netcdf) 1057 # validate Dataset keys, DataArray names, and attr keys/values 1058 _validate_dataset_names(dataset) -> 1059 _validate_attrs(dataset) 1060 1061 try: /usr/local/anaconda3/envs/dclab/lib/python3.7/site-packages/xarray/backends/api.py in _validate_attrs(dataset) 229 # Check attrs on the dataset itself 230 for k, v in dataset.attrs.items(): --> 231 check_attr(k, v) 232 233 # Check attrs on each variable within the dataset /usr/local/anaconda3/envs/dclab/lib/python3.7/site-packages/xarray/backends/api.py in check_attr(name, value) 221 if not isinstance(value, (str, Number, np.ndarray, np.number, list, tuple)): 222 raise TypeError( --> 223 f"Invalid value for attr {name!r}: {value!r} must be a number, " 224 "a string, an ndarray or a list/tuple of " 225 "numbers/strings for serialization to netCDF " TypeError: Invalid value for attr 'my_bool_attr': True must be a number, a string, an ndarray or a list/tuple of numbers/strings for serialization to netCDF files ``` Anything else we need to know?: Xarray is awesome!! Thank you, guys! ❤ We are adopting it fully for a quantum computing experimental framework (Quantify). This issue is very critical for us at the moment 😭 For reference, the following works in ```python with h5netcdf.File('mydata.nc', 'w', invalid_netcdf=True) as f: f.dimensions = {'x': 5} v = f.create_variable('hello', ('x',), float) v.attrs['foo'] = True print(v.attrs) print(type(v.attrs["foo"])) with h5netcdf.File('mydata.nc', 'r') as file: v = file['hello'] print(v.attrs) print(type(v.attrs["foo"])) with h5netcdf.File('mydata.nc', 'w', invalid_netcdf=True) as f: f.dimensions = {'x': 5} v = f.create_variable('hello', ('x',), float) v.attrs['foo'] = np.bool_(True) print(v.attrs) print(type(v.attrs["foo"])) ```
How to fix: In
I did a quick test ( Considering that it is a single line of code, could this be deployed relatively easily into the master branch by some maintainer? That would be highly appreciated! 🥺 Environment: Output of <tt>xr.show_versions()</tt>INSTALLED VERSIONS ------------------ commit: None python: 3.7.6 | packaged by conda-forge | (default, Jan 7 2020, 22:05:27) [Clang 9.0.1 ] python-bits: 64 OS: Darwin OS-release: 18.7.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: en_US.UTF-8 LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.4 libnetcdf: None xarray: 0.17.0 pandas: 1.0.1 numpy: 1.19.3 scipy: 1.5.4 netCDF4: None pydap: None h5netcdf: 0.10.0 h5py: 2.10.0 Nio: None zarr: 2.6.1 cftime: None nc_time_axis: None PseudoNetCDF: None rasterio: None cfgrib: None iris: None bottleneck: None dask: None distributed: None matplotlib: 3.1.3 cartopy: None seaborn: 0.11.0 numbagg: None pint: None setuptools: 45.2.0.post20200209 pip: 20.0.2 conda: None pytest: 5.3.5 IPython: 7.12.0 sphinx: 3.2.1 |
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completed | xarray 13221727 | issue |
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