Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

test_cross_engine_read_write_netcdf3 is now failing on master #2050

Closed
shoyer opened this issue Apr 10, 2018 · 3 comments
Closed

test_cross_engine_read_write_netcdf3 is now failing on master #2050

shoyer opened this issue Apr 10, 2018 · 3 comments

Comments

@shoyer
Copy link
Member

shoyer commented Apr 10, 2018

Only on Python 3.5 and 3.6 for now:

=================================== FAILURES ===================================
__________ GenericNetCDFDataTest.test_cross_engine_read_write_netcdf3 __________
self = <xarray.tests.test_backends.GenericNetCDFDataTest testMethod=test_cross_engine_read_write_netcdf3>
    def test_cross_engine_read_write_netcdf3(self):
        data = create_test_data()
        valid_engines = set()
        if has_netCDF4:
            valid_engines.add('netcdf4')
        if has_scipy:
            valid_engines.add('scipy')
    
        for write_engine in valid_engines:
            for format in ['NETCDF3_CLASSIC', 'NETCDF3_64BIT']:
                with create_tmp_file() as tmp_file:
                    data.to_netcdf(tmp_file, format=format,
                                   engine=write_engine)
                    for read_engine in valid_engines:
                        with open_dataset(tmp_file,
>                                         engine=read_engine) as actual:
xarray/tests/test_backends.py:1596: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
xarray/backends/api.py:299: in open_dataset
    autoclose=autoclose)
xarray/backends/netCDF4_.py:280: in open
    ds = opener()
xarray/backends/netCDF4_.py:204: in _open_netcdf4_group
    ds = nc4.Dataset(filename, mode=mode, **kwargs)
netCDF4/_netCDF4.pyx:2015: in netCDF4._netCDF4.Dataset.__init__
    ???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
>   ???
E   OSError: [Errno -36] NetCDF: Invalid argument: b'/tmp/tmpu5no_wbf/temp-1157.nc'
netCDF4/_netCDF4.pyx:1636: OSError
___ GenericNetCDFDataTestAutocloseTrue.test_cross_engine_read_write_netcdf3 ____
self = <xarray.tests.test_backends.GenericNetCDFDataTestAutocloseTrue testMethod=test_cross_engine_read_write_netcdf3>
    def test_cross_engine_read_write_netcdf3(self):
        data = create_test_data()
        valid_engines = set()
        if has_netCDF4:
            valid_engines.add('netcdf4')
        if has_scipy:
            valid_engines.add('scipy')
    
        for write_engine in valid_engines:
            for format in ['NETCDF3_CLASSIC', 'NETCDF3_64BIT']:
                with create_tmp_file() as tmp_file:
                    data.to_netcdf(tmp_file, format=format,
                                   engine=write_engine)
                    for read_engine in valid_engines:
                        with open_dataset(tmp_file,
>                                         engine=read_engine) as actual:
xarray/tests/test_backends.py:1596: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
xarray/backends/api.py:299: in open_dataset
    autoclose=autoclose)
xarray/backends/netCDF4_.py:280: in open
    ds = opener()
xarray/backends/netCDF4_.py:204: in _open_netcdf4_group
    ds = nc4.Dataset(filename, mode=mode, **kwargs)
netCDF4/_netCDF4.pyx:2015: in netCDF4._netCDF4.Dataset.__init__
    ???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
>   ???
E   OSError: [Errno -36] NetCDF: Invalid argument: b'/tmp/tmp9ak1v4wj/temp-1238.nc'
netCDF4/_netCDF4.pyx:1636: OSError

Here's the diff of conda packages:

--- broken.txt	2018-04-10 11:22:39.400835307 -0700
+++ works.txt	2018-04-10 11:23:12.840755416 -0700
@@ -9,2 +9,2 @@
-boto3                     1.7.2                      py_0    conda-forge
-botocore                  1.10.2                     py_0    conda-forge
+boto3                     1.7.0                      py_0    conda-forge
+botocore                  1.10.1                     py_0    conda-forge
@@ -23 +23 @@
-curl                      7.59.0                        1    conda-forge
+curl                      7.59.0                        0    conda-forge
@@ -29 +29 @@
-distributed               1.21.6                   py36_0    conda-forge
+distributed               1.21.5                   py36_0    conda-forge
@@ -62 +62 @@
-libgdal                   2.2.4                         1    conda-forge
+libgdal                   2.2.4                         0    conda-forge
@@ -66 +66 @@
-libnetcdf                 4.5.0                         3    conda-forge
+libnetcdf                 4.4.1.1                      10    conda-forge
@@ -83 +83 @@
-netcdf4                   1.3.1                    py36_2    conda-forge
+netcdf4                   1.3.1                    py36_1    conda-forge
@@ -85 +85 @@
-numcodecs                 0.5.5                    py36_0    conda-forge
+numcodecs                 0.5.4                    py36_0    conda-forge
@@ -131 +131 @@
-tornado                   5.0.2                    py36_0    conda-forge
+tornado                   5.0.1                    py36_1    conda-forge

The culprit is almost certainly libnetcdf 4.4.1.1 -> 4.5.0

It looks like it's basically this issue again: Unidata/netcdf-c#657

We could fix this either by skipping the tests in xarray's CI or upgrading netCDF-C on conda forge to 4.6.0 or 4.6.1.
This was referenced Apr 10, 2018
Closed
Merged
Merged
@sebix
Copy link
Contributor

sebix commented Apr 14, 2018

Same problem here. Full log:

[   69s] =================================== FAILURES ===================================
[   69s] ______________ GenericNetCDFDataTest.test_append_overwrite_values ______________
[   69s] 
[   69s] self = <xarray.tests.test_backends.GenericNetCDFDataTest testMethod=test_append_overwrite_values>
[   69s] 
[   69s]     def test_append_overwrite_values(self):
[   69s]         # regression for GH1215
[   69s]         data = create_test_data()
[   69s]         with create_tmp_file(allow_cleanup_failure=False) as tmp_file:
[   69s]             self.save(data, tmp_file, mode='w')
[   69s]             data['var2'][:] = -999
[   69s]             data['var9'] = data['var2'] * 3
[   69s] >           self.save(data[['var2', 'var9']], tmp_file, mode='a')
[   69s] 
[   69s] xarray/tests/test_backends.py:796: 
[   69s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[   69s] xarray/tests/test_backends.py:162: in save
[   69s]     **kwargs)
[   69s] xarray/core/dataset.py:1137: in to_netcdf
[   69s]     unlimited_dims=unlimited_dims)
[   69s] xarray/backends/api.py:657: in to_netcdf
[   69s]     unlimited_dims=unlimited_dims)
[   69s] xarray/core/dataset.py:1074: in dump_to_store
[   69s]     unlimited_dims=unlimited_dims)
[   69s] xarray/backends/common.py:363: in store
[   69s]     unlimited_dims=unlimited_dims)
[   69s] xarray/backends/common.py:402: in set_variables
[   69s]     self.writer.add(source, target)
[   69s] xarray/backends/common.py:265: in add
[   69s]     target[...] = source
[   69s] xarray/backends/scipy_.py:61: in __setitem__
[   69s]     data[key] = value
[   69s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[   69s] 
[   69s] self = <scipy.io.netcdf.netcdf_variable object at 0x7f0f9970d090>
[   69s] index = Ellipsis
[   69s] data = array([[-999., -999., -999., -999., -999., -999., -999., -999., -999.],
[   69s]       ...999.],
[   69s]        [-999., -999., -999., -999., -999., -999., -999., -999., -999.]])
[   69s] 
[   69s]     def __setitem__(self, index, data):
[   69s]         if self.maskandscale:
[   69s]             missing_value = (
[   69s]                     self._get_missing_value() or
[   69s]                     getattr(data, 'fill_value', 999999))
[   69s]             self._attributes.setdefault('missing_value', missing_value)
[   69s]             self._attributes.setdefault('_FillValue', missing_value)
[   69s]             data = ((data - self._attributes.get('add_offset', 0.0)) /
[   69s]                     self._attributes.get('scale_factor', 1.0))
[   69s]             data = np.ma.asarray(data).filled(missing_value)
[   69s]             if self._typecode not in 'fd' and data.dtype.kind == 'f':
[   69s]                 data = np.round(data)
[   69s]     
[   69s]         # Expand data for record vars?
[   69s]         if self.isrec:
[   69s]             if isinstance(index, tuple):
[   69s]                 rec_index = index[0]
[   69s]             else:
[   69s]                 rec_index = index
[   69s]             if isinstance(rec_index, slice):
[   69s]                 recs = (rec_index.start or 0) + len(data)
[   69s]             else:
[   69s]                 recs = rec_index + 1
[   69s]             if recs > len(self.data):
[   69s]                 shape = (recs,) + self._shape[1:]
[   69s]                 # Resize in-place does not always work since
[   69s]                 # the array might not be single-segment
[   69s]                 try:
[   69s]                     self.data.resize(shape)
[   69s]                 except ValueError:
[   69s]                     self.__dict__['data'] = np.resize(self.data, shape).astype(self.data.dtype)
[   69s] >       self.data[index] = data
[   69s] E       ValueError: assignment destination is read-only
[   69s] 
[   69s] /usr/lib64/python2.7/site-packages/scipy/io/netcdf.py:996: ValueError
[   69s] ___________________ GenericNetCDFDataTest.test_append_write ____________________
[   69s] 
[   69s] self = <xarray.tests.test_backends.GenericNetCDFDataTest testMethod=test_append_write>
[   69s] 
[   69s]     def test_append_write(self):
[   69s]         # regression for GH1215
[   69s]         data = create_test_data()
[   69s] >       with self.roundtrip_append(data) as actual:
[   69s] 
[   69s] xarray/tests/test_backends.py:786: 
[   69s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[   69s] /usr/lib64/python2.7/contextlib.py:17: in __enter__
[   69s]     return self.gen.next()
[   69s] xarray/tests/test_backends.py:155: in roundtrip_append
[   69s]     self.save(data[[key]], path, mode=mode, **save_kwargs)
[   69s] xarray/tests/test_backends.py:162: in save
[   69s]     **kwargs)
[   69s] xarray/core/dataset.py:1137: in to_netcdf
[   69s]     unlimited_dims=unlimited_dims)
[   69s] xarray/backends/api.py:657: in to_netcdf
[   69s]     unlimited_dims=unlimited_dims)
[   69s] xarray/core/dataset.py:1074: in dump_to_store
[   69s]     unlimited_dims=unlimited_dims)
[   69s] xarray/backends/common.py:363: in store
[   69s]     unlimited_dims=unlimited_dims)
[   69s] xarray/backends/common.py:402: in set_variables
[   69s]     self.writer.add(source, target)
[   69s] xarray/backends/common.py:265: in add
[   69s]     target[...] = source
[   69s] xarray/backends/scipy_.py:61: in __setitem__
[   69s]     data[key] = value
[   69s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[   69s] 
[   69s] self = <scipy.io.netcdf.netcdf_variable object at 0x7f0f991df910>
[   69s] index = Ellipsis, data = array([0. , 0.5, 1. , 1.5, 2. , 2.5, 3. , 3.5, 4. ])
[   69s] 
[   69s]     def __setitem__(self, index, data):
[   69s]         if self.maskandscale:
[   69s]             missing_value = (
[   69s]                     self._get_missing_value() or
[   69s]                     getattr(data, 'fill_value', 999999))
[   69s]             self._attributes.setdefault('missing_value', missing_value)
[   69s]             self._attributes.setdefault('_FillValue', missing_value)
[   69s]             data = ((data - self._attributes.get('add_offset', 0.0)) /
[   69s]                     self._attributes.get('scale_factor', 1.0))
[   69s]             data = np.ma.asarray(data).filled(missing_value)
[   69s]             if self._typecode not in 'fd' and data.dtype.kind == 'f':
[   69s]                 data = np.round(data)
[   69s]     
[   69s]         # Expand data for record vars?
[   69s]         if self.isrec:
[   69s]             if isinstance(index, tuple):
[   69s]                 rec_index = index[0]
[   69s]             else:
[   69s]                 rec_index = index
[   69s]             if isinstance(rec_index, slice):
[   69s]                 recs = (rec_index.start or 0) + len(data)
[   69s]             else:
[   69s]                 recs = rec_index + 1
[   69s]             if recs > len(self.data):
[   69s]                 shape = (recs,) + self._shape[1:]
[   69s]                 # Resize in-place does not always work since
[   69s]                 # the array might not be single-segment
[   69s]                 try:
[   69s]                     self.data.resize(shape)
[   69s]                 except ValueError:
[   69s]                     self.__dict__['data'] = np.resize(self.data, shape).astype(self.data.dtype)
[   69s] >       self.data[index] = data
[   69s] E       ValueError: assignment destination is read-only
[   69s] 
[   69s] /usr/lib64/python2.7/site-packages/scipy/io/netcdf.py:996: ValueError
[   69s] _______ GenericNetCDFDataTestAutocloseTrue.test_append_overwrite_values ________
[   69s] 
[   69s] self = <xarray.tests.test_backends.GenericNetCDFDataTestAutocloseTrue testMethod=test_append_overwrite_values>
[   69s] 
[   69s]     def test_append_overwrite_values(self):
[   69s]         # regression for GH1215
[   69s]         data = create_test_data()
[   69s]         with create_tmp_file(allow_cleanup_failure=False) as tmp_file:
[   69s]             self.save(data, tmp_file, mode='w')
[   69s]             data['var2'][:] = -999
[   69s]             data['var9'] = data['var2'] * 3
[   69s] >           self.save(data[['var2', 'var9']], tmp_file, mode='a')
[   69s] 
[   69s] xarray/tests/test_backends.py:796: 
[   69s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[   69s] xarray/tests/test_backends.py:162: in save
[   69s]     **kwargs)
[   69s] xarray/core/dataset.py:1137: in to_netcdf
[   69s]     unlimited_dims=unlimited_dims)
[   69s] xarray/backends/api.py:657: in to_netcdf
[   69s]     unlimited_dims=unlimited_dims)
[   69s] xarray/core/dataset.py:1074: in dump_to_store
[   69s]     unlimited_dims=unlimited_dims)
[   69s] xarray/backends/common.py:363: in store
[   69s]     unlimited_dims=unlimited_dims)
[   69s] xarray/backends/common.py:402: in set_variables
[   69s]     self.writer.add(source, target)
[   69s] xarray/backends/common.py:265: in add
[   69s]     target[...] = source
[   69s] xarray/backends/scipy_.py:61: in __setitem__
[   69s]     data[key] = value
[   69s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[   69s] 
[   69s] self = <scipy.io.netcdf.netcdf_variable object at 0x7f0f9aca4fd0>
[   69s] index = Ellipsis
[   69s] data = array([[-999., -999., -999., -999., -999., -999., -999., -999., -999.],
[   69s]       ...999.],
[   69s]        [-999., -999., -999., -999., -999., -999., -999., -999., -999.]])
[   69s] 
[   69s]     def __setitem__(self, index, data):
[   69s]         if self.maskandscale:
[   69s]             missing_value = (
[   69s]                     self._get_missing_value() or
[   69s]                     getattr(data, 'fill_value', 9[   64.291734] serial8250: too much work for irq4
[   69s] 99999))
[   69s]             self._attributes.setdefault('missing_value', missing_value)
[   69s]             self._attributes.setdefault('_FillValue', missing_value)
[   69s]             data = ((data - self._attributes.get('add_offset', 0.0)) /
[   69s]                     self._attributes.get('scale_factor', 1.0))
[   69s]             data = np.ma.asarray(data).filled(missing_value)
[   69s]             if self._typecode not in 'fd' and data.dtype.kind == 'f':
[   69s]                 data = np.round(data)
[   69s]     
[   69s]         # Expand data for record vars?
[   69s]         if self.isrec:
[   69s]             if isinstance(index, tuple):
[   69s]                 rec_index = index[0]
[   69s]             else:
[   69s]                 rec_index = index
[   69s]             if isinstance(rec_index, slice):
[   69s]                 recs = (rec_index.start or 0) + len(data)
[   69s]             else:
[   69s]                 recs = rec_index + 1
[   69s]             if recs > len(self.data):
[   69s]                 shape = (recs,) + self._shape[1:]
[   69s]                 # Resize in-place does not always work since
[   69s]                 # the array might not be single-segment
[   69s]                 try:
[   69s]                     self.data.resize(shape)
[   69s]                 except ValueError:
[   69s]                     self.__dict__['data'] = np.resize(self.data, shape).astype(self.data.dtype)
[   69s] >       self.data[index] = data
[   69s] E       ValueError: assignment destination is read-only
[   69s] 
[   69s] /usr/lib64/python2.7/site-packages/scipy/io/netcdf.py:996: ValueError
[   69s] _____________ GenericNetCDFDataTestAutocloseTrue.test_append_write _____________
[   69s] 
[   69s] self = <xarray.tests.test_backends.GenericNetCDFDataTestAutocloseTrue testMethod=test_append_write>
[   69s] 
[   69s]     def test_append_write(self):
[   69s]         # regression for GH1215
[   69s]         data = create_test_data()
[   69s] >       with self.roundtrip_append(data) as actual:
[   69s] 
[   69s] xarray/tests/test_backends.py:786: 
[   69s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[   69s] /usr/lib64/python2.7/contextlib.py:17: in __enter__
[   69s]     return self.gen.next()
[   69s] xarray/tests/test_backends.py:155: in roundtrip_append
[   69s]     self.save(data[[key]], path, mode=mode, **save_kwargs)
[   69s] xarray/tests/test_backends.py:162: in save
[   69s]     **kwargs)
[   69s] xarray/core/dataset.py:1137: in to_netcdf
[   69s]     unlimited_dims=unlimited_dims)
[   69s] xarray/backends/api.py:657: in to_netcdf
[   69s]     unlimited_dims=unlimited_dims)
[   69s] xarray/core/dataset.py:1074: in dump_to_store
[   69s]     unlimited_dims=unlimited_dims)
[   69s] xarray/backends/common.py:363: in store
[   69s]     unlimited_dims=unlimited_dims)
[   69s] xarray/backends/common.py:402: in set_variables
[   69s]     self.writer.add(source, target)
[   69s] xarray/backends/common.py:265: in add
[   69s]     target[...] = source
[   69s] xarray/backends/scipy_.py:61: in __setitem__
[   69s]     data[key] = value
[   69s] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
[   69s] 
[   69s] self = <scipy.io.netcdf.netcdf_variable object at 0x7f0f992c80d0>
[   69s] index = Ellipsis, data = array([0. , 0.5, 1. , 1.5, 2. , 2.5, 3. , 3.5, 4. ])
[   69s] 
[   69s]     def __setitem__(self, index, data):
[   69s]         if self.maskandscale:
[   69s]             missing_value = (
[   69s]                     self._get_missing_value() or
[   69s]                     getattr(data, 'fill_value', 999999))
[   69s]             self._attributes.setdefault('missing_value', missing_value)
[   69s]             self._attributes.setdefault('_FillValue', missing_value)
[   69s]             data = ((data - self._attributes.get('add_offset', 0.0)) /
[   69s]                     self._attributes.get('scale_factor', 1.0))
[   69s]             data = np.ma.asarray(data).filled(missing_value)
[   69s]             if self._typecode not in 'fd' and data.dtype.kind == 'f':
[   69s]                 data = np.round(data)
[   69s]     
[   69s]         # Expand data for record vars?
[   69s]         if self.isrec:
[   69s]             if isinstance(index, tuple):
[   69s]                 rec_index = index[0]
[   69s]             else:
[   69s]                 rec_index = index
[   69s]             if isinstance(rec_index, slice):
[   69s]                 recs = (rec_index.start or 0) + len(data)
[   69s]             else:
[   69s]                 recs = rec_index + 1
[   69s]             if recs > len(self.data):
[   69s]                 shape = (recs,) + self._shape[1:]
[   69s]                 # Resize in-place does not always work since
[   69s]                 # the array might not be single-segment
[   69s]                 try:
[   69s]                     self.data.resize(shape)
[   69s]                 except ValueError:
[   69s]                     self.__dict__['data'] = np.resize(self.data, shape).astype(self.data.dtype)
[   69s] >       self.data[index] = data
[   69s] E       ValueError: assignment destination is read-only
[   69s] 
[   69s] /usr/lib64/python2.7/site-packages/scipy/io/netcdf.py:996: ValueError
[   69s] =============================== warnings summary ===============================
[   69s] xarray/tests/test_backends.py::ScipyInMemoryDataTest::test_default_fill_value
[   69s]   /home/abuild/rpmbuild/BUILD/xarray-0.10.3/xarray/conventions.py:748: SerializationWarning: saving variable x with floating point data as an integer dtype without any _FillValue to use for NaNs
[   69s]     for k, v in iteritems(variables))
[   69s] 
[   69s] xarray/tests/test_backends.py::ScipyInMemoryDataTest::test_pickle
[   69s]   /usr/lib64/python2.7/site-packages/scipy/io/netcdf.py:299: RuntimeWarning: Cannot close a netcdf_file opened with mmap=True, when netcdf_variables or arrays referring to its data still exist. All data arrays obtained from such files refer directly to data on disk, and must be copied before the file can be cleanly closed. (See netcdf_file docstring for more information on mmap.)
[   69s]     ), category=RuntimeWarning)
[   69s] 
[   69s] xarray/tests/test_dataarray.py::TestDataArray::test_reindex_regressions
[   69s]   /home/abuild/rpmbuild/BUILD/xarray-0.10.3/xarray/core/dataarray.py:882: FutureWarning: Indexer has dimensions ('time2',) that are different from that to be indexed along time. This will behave differently in the future.
[   69s]     method=method, tolerance=tolerance, copy=copy, **indexers)
[   69s] 
[   69s] xarray/tests/test_missing.py::test_scipy_methods_function
[   69s]   /usr/lib64/python2.7/site-packages/scipy/interpolate/polyint.py:511: RuntimeWarning: overflow encountered in multiply
[   69s]     self.wi[:j] *= (self.xi[j]-self.xi[:j])
[   69s]   /usr/lib64/python2.7/site-packages/scipy/interpolate/polyint.py:512: RuntimeWarning: overflow encountered in reduce
[   69s]     self.wi[j] = np.multiply.reduce(self.xi[:j]-self.xi[j])
[   69s]   /usr/lib64/python2.7/site-packages/scipy/interpolate/polyint.py:609: RuntimeWarning: invalid value encountered in true_divide
[   69s]     p = np.dot(c,self.yi)/np.sum(c,axis=-1)[...,np.newaxis]
[   69s]   /usr/lib64/python2.7/site-packages/scipy/interpolate/polyint.py:324: RuntimeWarning: overflow encountered in multiply
[   69s]     pi = w*pi
[   69s]   /usr/lib64/python2.7/site-packages/scipy/interpolate/polyint.py:325: RuntimeWarning: invalid value encountered in multiply
[   69s]     p += pi[:,np.newaxis] * self.c[k]
[   69s]   /usr/lib64/python2.7/site-packages/scipy/interpolate/polyint.py:325: RuntimeWarning: invalid value encountered in add
[   69s]     p += pi[:,np.newaxis] * self.c[k]
[   69s] 
[   69s] xarray/tests/test_variable.py::TestVariable::test_index_0d_not_a_time
[   69s]   /home/abuild/rpmbuild/BUILD/xarray-0.10.3/xarray/core/duck_array_ops.py:137: FutureWarning: In the future, 'NAT == x' and 'x == NAT' will always be False.
[   69s]     flag_array = (arr1 == arr2)
[   69s]   /home/abuild/rpmbuild/BUILD/xarray-0.10.3/xarray/tests/test_variable.py:141: FutureWarning: In the future, 'NAT == x' and 'x == NAT' will always be False.
[   69s]     assert variable.values[0] == expected_value0
[   69s]   /home/abuild/rpmbuild/BUILD/xarray-0.10.3/xarray/tests/test_variable.py:142: FutureWarning: In the future, 'NAT == x' and 'x == NAT' will always be False.
[   69s]     assert variable[0].values == expected_value0
[   69s] 
[   69s] xarray/tests/test_variable.py::TestVariableWithDask::test_index_0d_not_a_time
[   69s]   /usr/lib/python2.7/site-packages/dask/local.py:271: FutureWarning: In the future, 'NAT == x' and 'x == NAT' will always be False.
[   69s]     return func(*args2)
[   69s] 
[   69s] -- Docs: http://doc.pytest.org/en/latest/warnings.html
[   69s]  4 failed, 2621 passed, 1443 skipped, 19 xfailed, 4 xpassed, 13 warnings in 44.85 seconds

With python-netCDF4 == 1.3.1, scipy == 1.0.0, netcdf == 4.4.1

Probably a conditional skip is a (short term) solution?

@shoyer
Copy link
Member Author

shoyer commented Apr 14, 2018 via email

@sebix
Copy link
Contributor

sebix commented Apr 15, 2018 via email

shoyer added a commit to shoyer/xarray that referenced this issue Feb 3, 2019
@shoyer
Reenable cross engine read write netCDF test
6fb8e6e 
Fixes pydata#2050

I'm not quite sure what was going on, but it passes now.
@shoyer shoyer mentioned this issue Feb 3, 2019
Merged
1 task
jhamman pushed a commit that referenced this issue Feb 4, 2019
@shoyer
Reenable cross engine read write netCDF test (#2739)
053aed1 
Fixes #2050

I'm not quite sure what was going on, but it passes now.
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
None yet
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
2 participants
@sebix @shoyer