issue_comments

The test is marked as xfail now, so if you merge in master tests should pass. On Sat, Apr 14, 2018 at 5:48 AM Sebastian notifications@github.com wrote:

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 = wpi [ 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?

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