D: [iurt_root_command] chroot Installing /home/pterjan/rpmbuild/SRPMS/python-xarray-2022.11.0-2.mga9.src.rpm Building target platforms: noarch Building for target noarch Executing(%prep): /bin/sh -e /home/pterjan/rpmbuild/tmp/rpm-tmp.mtiLen + umask 022 + cd /home/pterjan/rpmbuild/BUILD + '[' 1 -eq 1 ']' + '[' 1 -eq 1 ']' + '[' 1 -eq 1 ']' + cd /home/pterjan/rpmbuild/BUILD + rm -rf xarray-2022.11.0 + /usr/lib/rpm/rpmuncompress -x /home/pterjan/rpmbuild/SOURCES/xarray-2022.11.0.tar.gz + STATUS=0 + '[' 0 -ne 0 ']' + cd xarray-2022.11.0 + /usr/bin/chmod -Rf a+rX,u+w,g-w,o-w . + RPM_EC=0 ++ jobs -p + exit 0 Executing(%build): /bin/sh -e /home/pterjan/rpmbuild/tmp/rpm-tmp.dBCaB7 + umask 022 + cd /home/pterjan/rpmbuild/BUILD + cd xarray-2022.11.0 + '[' 1 -eq 1 ']' + '[' 1 -eq 1 ']' + mkdir -p /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/.pyproject-builddir + CFLAGS='-O2 -g -pipe -Wformat -Werror=format-security -Wp,-D_FORTIFY_SOURCE=2 -fstack-protector --param=ssp-buffer-size=4 -fasynchronous-unwind-tables' + LDFLAGS=' -Wl,--as-needed -Wl,--no-undefined -Wl,-z,relro -Wl,-O1 -Wl,--build-id=sha1 -Wl,--enable-new-dtags' + TMPDIR=/home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/.pyproject-builddir + /usr/bin/python3 -Bs /usr/lib/rpm/redhat/pyproject_wheel.py /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/pyproject-wheeldir Processing /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0 Preparing metadata (pyproject.toml): started Running command Preparing metadata (pyproject.toml) /usr/lib/python3.10/site-packages/setuptools_scm/git.py:295: UserWarning: git archive did not support describe output warnings.warn("git archive did not support describe output") running dist_info creating /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/.pyproject-builddir/pip-modern-metadata-bv3a_4q7/xarray.egg-info writing /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/.pyproject-builddir/pip-modern-metadata-bv3a_4q7/xarray.egg-info/PKG-INFO writing dependency_links to /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/.pyproject-builddir/pip-modern-metadata-bv3a_4q7/xarray.egg-info/dependency_links.txt writing requirements to /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/.pyproject-builddir/pip-modern-metadata-bv3a_4q7/xarray.egg-info/requires.txt writing top-level names to /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/.pyproject-builddir/pip-modern-metadata-bv3a_4q7/xarray.egg-info/top_level.txt writing manifest file '/home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/.pyproject-builddir/pip-modern-metadata-bv3a_4q7/xarray.egg-info/SOURCES.txt' reading manifest file '/home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/.pyproject-builddir/pip-modern-metadata-bv3a_4q7/xarray.egg-info/SOURCES.txt' adding license file 'LICENSE' writing manifest file '/home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/.pyproject-builddir/pip-modern-metadata-bv3a_4q7/xarray.egg-info/SOURCES.txt' creating '/home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/.pyproject-builddir/pip-modern-metadata-bv3a_4q7/xarray-2022.11.0.dist-info' adding license file "LICENSE" (matched pattern "LICEN[CS]E*") Preparing metadata (pyproject.toml): finished with status 'done' Building wheels for collected packages: xarray Building wheel for xarray (pyproject.toml): started Running command Building wheel for xarray (pyproject.toml) /usr/lib/python3.10/site-packages/setuptools_scm/git.py:295: UserWarning: git archive did not support describe output warnings.warn("git archive did not support describe output") running bdist_wheel running build running build_py creating build creating build/lib creating build/lib/xarray copying xarray/convert.py -> build/lib/xarray copying xarray/__init__.py -> build/lib/xarray copying xarray/tutorial.py -> build/lib/xarray copying xarray/conventions.py -> build/lib/xarray copying xarray/testing.py -> build/lib/xarray creating build/lib/xarray/static copying xarray/static/__init__.py -> build/lib/xarray/static creating build/lib/xarray/tests copying xarray/tests/test_weighted.py -> build/lib/xarray/tests copying xarray/tests/test_plot.py -> build/lib/xarray/tests copying xarray/tests/test_ufuncs.py -> build/lib/xarray/tests copying xarray/tests/test_array_api.py -> build/lib/xarray/tests copying xarray/tests/test_formatting_html.py -> build/lib/xarray/tests copying xarray/tests/test_extensions.py -> build/lib/xarray/tests copying xarray/tests/test_sparse.py -> build/lib/xarray/tests copying xarray/tests/test_indexes.py -> build/lib/xarray/tests copying xarray/tests/test_tutorial.py -> build/lib/xarray/tests copying xarray/tests/test_accessor_dt.py -> build/lib/xarray/tests copying xarray/tests/test_units.py -> build/lib/xarray/tests copying xarray/tests/test_variable.py -> build/lib/xarray/tests copying xarray/tests/test_backends_file_manager.py -> build/lib/xarray/tests copying xarray/tests/test_dask.py -> build/lib/xarray/tests copying xarray/tests/test_nputils.py -> build/lib/xarray/tests copying xarray/tests/test_rolling.py -> build/lib/xarray/tests copying xarray/tests/test_backends_common.py -> build/lib/xarray/tests copying xarray/tests/test_dtypes.py -> build/lib/xarray/tests copying xarray/tests/test_cupy.py -> build/lib/xarray/tests copying xarray/tests/test_indexing.py -> build/lib/xarray/tests copying xarray/tests/test_dataarray.py -> build/lib/xarray/tests copying xarray/tests/test_groupby.py -> build/lib/xarray/tests copying xarray/tests/test_testing.py -> build/lib/xarray/tests copying xarray/tests/conftest.py -> build/lib/xarray/tests copying xarray/tests/test_calendar_ops.py -> build/lib/xarray/tests copying xarray/tests/test_interp.py -> build/lib/xarray/tests copying xarray/tests/test_cftime_offsets.py -> build/lib/xarray/tests copying xarray/tests/test_deprecation_helpers.py -> build/lib/xarray/tests copying xarray/tests/test_missing.py -> build/lib/xarray/tests copying xarray/tests/test_utils.py -> build/lib/xarray/tests copying xarray/tests/test_concat.py -> build/lib/xarray/tests copying xarray/tests/test_print_versions.py -> build/lib/xarray/tests copying xarray/tests/test_accessor_str.py -> build/lib/xarray/tests copying xarray/tests/test_backends_lru_cache.py -> build/lib/xarray/tests copying xarray/tests/test_coding.py -> build/lib/xarray/tests copying xarray/tests/test_duck_array_ops.py -> build/lib/xarray/tests copying xarray/tests/test_backends.py -> build/lib/xarray/tests copying xarray/tests/test_coding_times.py -> build/lib/xarray/tests copying xarray/tests/test_computation.py -> build/lib/xarray/tests copying xarray/tests/test_plugins.py -> build/lib/xarray/tests copying xarray/tests/test_merge.py -> build/lib/xarray/tests copying xarray/tests/test_coding_strings.py -> build/lib/xarray/tests copying xarray/tests/test_backends_api.py -> build/lib/xarray/tests copying xarray/tests/test_cftimeindex.py -> build/lib/xarray/tests copying xarray/tests/__init__.py -> build/lib/xarray/tests copying xarray/tests/test_conventions.py -> build/lib/xarray/tests copying xarray/tests/test_formatting.py -> build/lib/xarray/tests copying xarray/tests/test_backends_locks.py -> build/lib/xarray/tests copying xarray/tests/test_cftimeindex_resample.py -> build/lib/xarray/tests copying xarray/tests/test_coarsen.py -> build/lib/xarray/tests copying xarray/tests/test_distributed.py -> build/lib/xarray/tests copying xarray/tests/test_combine.py -> build/lib/xarray/tests copying xarray/tests/test_dataset.py -> build/lib/xarray/tests copying xarray/tests/test_options.py -> build/lib/xarray/tests creating build/lib/xarray/core copying xarray/core/alignment.py -> build/lib/xarray/core copying xarray/core/npcompat.py -> build/lib/xarray/core copying xarray/core/nputils.py -> build/lib/xarray/core copying xarray/core/pycompat.py -> build/lib/xarray/core copying xarray/core/options.py -> build/lib/xarray/core copying xarray/core/dask_array_ops.py -> build/lib/xarray/core copying xarray/core/variable.py -> build/lib/xarray/core copying xarray/core/computation.py -> build/lib/xarray/core copying xarray/core/dataset.py -> build/lib/xarray/core copying xarray/core/accessor_str.py -> build/lib/xarray/core copying xarray/core/resample.py -> build/lib/xarray/core copying xarray/core/types.py -> build/lib/xarray/core copying xarray/core/groupby.py -> build/lib/xarray/core copying xarray/core/ops.py -> build/lib/xarray/core copying xarray/core/common.py -> build/lib/xarray/core copying xarray/core/_aggregations.py -> build/lib/xarray/core copying xarray/core/resample_cftime.py -> build/lib/xarray/core copying xarray/core/weighted.py -> build/lib/xarray/core copying xarray/core/extensions.py -> build/lib/xarray/core copying xarray/core/combine.py -> build/lib/xarray/core copying xarray/core/_typed_ops.py -> build/lib/xarray/core copying xarray/core/coordinates.py -> build/lib/xarray/core copying xarray/core/pdcompat.py -> build/lib/xarray/core copying xarray/core/formatting_html.py -> build/lib/xarray/core copying xarray/core/accessor_dt.py -> build/lib/xarray/core copying xarray/core/parallel.py -> build/lib/xarray/core copying xarray/core/rolling_exp.py -> build/lib/xarray/core copying xarray/core/formatting.py -> build/lib/xarray/core copying xarray/core/concat.py -> build/lib/xarray/core copying xarray/core/duck_array_ops.py -> build/lib/xarray/core copying xarray/core/__init__.py -> build/lib/xarray/core copying xarray/core/merge.py -> build/lib/xarray/core copying xarray/core/rolling.py -> build/lib/xarray/core copying xarray/core/missing.py -> build/lib/xarray/core copying xarray/core/dataarray.py -> build/lib/xarray/core copying xarray/core/indexing.py -> build/lib/xarray/core copying xarray/core/indexes.py -> build/lib/xarray/core copying xarray/core/dtypes.py -> build/lib/xarray/core copying xarray/core/utils.py -> build/lib/xarray/core copying xarray/core/arithmetic.py -> build/lib/xarray/core copying xarray/core/nanops.py -> build/lib/xarray/core creating build/lib/xarray/backends copying xarray/backends/memory.py -> build/lib/xarray/backends copying xarray/backends/pynio_.py -> build/lib/xarray/backends copying xarray/backends/common.py -> build/lib/xarray/backends copying xarray/backends/netcdf3.py -> build/lib/xarray/backends copying xarray/backends/locks.py -> build/lib/xarray/backends copying xarray/backends/cfgrib_.py -> build/lib/xarray/backends copying xarray/backends/store.py -> build/lib/xarray/backends copying xarray/backends/h5netcdf_.py -> build/lib/xarray/backends copying xarray/backends/file_manager.py -> build/lib/xarray/backends copying xarray/backends/rasterio_.py -> build/lib/xarray/backends copying xarray/backends/netCDF4_.py -> build/lib/xarray/backends copying xarray/backends/__init__.py -> build/lib/xarray/backends copying xarray/backends/lru_cache.py -> build/lib/xarray/backends copying xarray/backends/api.py -> build/lib/xarray/backends copying xarray/backends/pseudonetcdf_.py -> build/lib/xarray/backends copying xarray/backends/zarr.py -> build/lib/xarray/backends copying xarray/backends/plugins.py -> build/lib/xarray/backends copying xarray/backends/pydap_.py -> build/lib/xarray/backends copying xarray/backends/scipy_.py -> build/lib/xarray/backends creating build/lib/xarray/coding copying xarray/coding/calendar_ops.py -> build/lib/xarray/coding copying xarray/coding/variables.py -> build/lib/xarray/coding copying xarray/coding/times.py -> build/lib/xarray/coding copying xarray/coding/cftimeindex.py -> build/lib/xarray/coding copying xarray/coding/frequencies.py -> build/lib/xarray/coding copying xarray/coding/cftime_offsets.py -> build/lib/xarray/coding copying xarray/coding/__init__.py -> build/lib/xarray/coding copying xarray/coding/strings.py -> build/lib/xarray/coding creating build/lib/xarray/plot copying xarray/plot/dataset_plot.py -> build/lib/xarray/plot copying xarray/plot/__init__.py -> build/lib/xarray/plot copying xarray/plot/facetgrid.py -> build/lib/xarray/plot copying xarray/plot/accessor.py -> build/lib/xarray/plot copying xarray/plot/utils.py -> build/lib/xarray/plot copying xarray/plot/dataarray_plot.py -> build/lib/xarray/plot creating build/lib/xarray/indexes copying xarray/indexes/__init__.py -> build/lib/xarray/indexes creating build/lib/xarray/util copying xarray/util/generate_ops.py -> build/lib/xarray/util copying xarray/util/print_versions.py -> build/lib/xarray/util copying xarray/util/__init__.py -> build/lib/xarray/util copying xarray/util/generate_aggregations.py -> build/lib/xarray/util copying xarray/util/deprecation_helpers.py -> build/lib/xarray/util creating build/lib/xarray/static/css copying xarray/static/css/__init__.py -> build/lib/xarray/static/css creating build/lib/xarray/static/html copying xarray/static/html/__init__.py -> build/lib/xarray/static/html running egg_info writing xarray.egg-info/PKG-INFO writing dependency_links to xarray.egg-info/dependency_links.txt writing requirements to xarray.egg-info/requires.txt writing top-level names to xarray.egg-info/top_level.txt reading manifest file 'xarray.egg-info/SOURCES.txt' adding license file 'LICENSE' writing manifest file 'xarray.egg-info/SOURCES.txt' /usr/lib/python3.10/site-packages/setuptools/command/build_py.py:202: SetuptoolsDeprecationWarning: Installing 'xarray.tests.data' as data is deprecated, please list it in `packages`. !! ############################ # Package would be ignored # ############################ Python recognizes 'xarray.tests.data' as an importable package, but it is not listed in the `packages` configuration of setuptools. 'xarray.tests.data' has been automatically added to the distribution only because it may contain data files, but this behavior is likely to change in future versions of setuptools (and therefore is considered deprecated). Please make sure that 'xarray.tests.data' is included as a package by using the `packages` configuration field or the proper discovery methods (for example by using `find_namespace_packages(...)`/`find_namespace:` instead of `find_packages(...)`/`find:`). You can read more about "package discovery" and "data files" on setuptools documentation page. !! check.warn(importable) copying xarray/py.typed -> build/lib/xarray creating build/lib/xarray/tests/data copying xarray/tests/data/example.uamiv -> build/lib/xarray/tests/data copying xarray/tests/data/example_1.nc -> build/lib/xarray/tests/data copying xarray/tests/data/example.ict -> build/lib/xarray/tests/data copying xarray/tests/data/example.grib -> build/lib/xarray/tests/data copying xarray/tests/data/example_1.nc.gz -> build/lib/xarray/tests/data copying xarray/tests/data/bears.nc -> build/lib/xarray/tests/data copying xarray/static/css/style.css -> build/lib/xarray/static/css copying xarray/static/html/icons-svg-inline.html -> build/lib/xarray/static/html copying xarray/core/_typed_ops.pyi -> build/lib/xarray/core installing to build/bdist.linux-x86_64/wheel running install running install_lib creating build/bdist.linux-x86_64 creating build/bdist.linux-x86_64/wheel creating build/bdist.linux-x86_64/wheel/xarray creating build/bdist.linux-x86_64/wheel/xarray/static creating build/bdist.linux-x86_64/wheel/xarray/static/css copying build/lib/xarray/static/css/style.css -> build/bdist.linux-x86_64/wheel/xarray/static/css copying build/lib/xarray/static/css/__init__.py -> build/bdist.linux-x86_64/wheel/xarray/static/css creating build/bdist.linux-x86_64/wheel/xarray/static/html copying build/lib/xarray/static/html/__init__.py -> build/bdist.linux-x86_64/wheel/xarray/static/html copying build/lib/xarray/static/html/icons-svg-inline.html -> build/bdist.linux-x86_64/wheel/xarray/static/html copying build/lib/xarray/static/__init__.py -> build/bdist.linux-x86_64/wheel/xarray/static creating build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_weighted.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_plot.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_ufuncs.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_array_api.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_formatting_html.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_extensions.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_sparse.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_indexes.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_tutorial.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_accessor_dt.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_units.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_variable.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_backends_file_manager.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_dask.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_nputils.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_rolling.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_backends_common.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_dtypes.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_cupy.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_indexing.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_dataarray.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_groupby.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_testing.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/conftest.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_calendar_ops.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_interp.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_cftime_offsets.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_deprecation_helpers.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_missing.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_utils.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_concat.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_print_versions.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_accessor_str.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_backends_lru_cache.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_coding.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_duck_array_ops.py -> build/bdist.linux-x86_64/wheel/xarray/tests creating build/bdist.linux-x86_64/wheel/xarray/tests/data copying build/lib/xarray/tests/data/example.uamiv -> build/bdist.linux-x86_64/wheel/xarray/tests/data copying build/lib/xarray/tests/data/example_1.nc -> build/bdist.linux-x86_64/wheel/xarray/tests/data copying build/lib/xarray/tests/data/example.ict -> build/bdist.linux-x86_64/wheel/xarray/tests/data copying build/lib/xarray/tests/data/example.grib -> build/bdist.linux-x86_64/wheel/xarray/tests/data copying build/lib/xarray/tests/data/example_1.nc.gz -> build/bdist.linux-x86_64/wheel/xarray/tests/data copying build/lib/xarray/tests/data/bears.nc -> build/bdist.linux-x86_64/wheel/xarray/tests/data copying build/lib/xarray/tests/test_backends.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_coding_times.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_computation.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_plugins.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_merge.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_coding_strings.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_backends_api.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_cftimeindex.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/__init__.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_conventions.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_formatting.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_backends_locks.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_cftimeindex_resample.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_coarsen.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_distributed.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_combine.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_dataset.py -> build/bdist.linux-x86_64/wheel/xarray/tests copying build/lib/xarray/tests/test_options.py -> build/bdist.linux-x86_64/wheel/xarray/tests creating build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/alignment.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/npcompat.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/nputils.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/pycompat.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/options.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/dask_array_ops.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/variable.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/computation.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/dataset.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/accessor_str.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/resample.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/types.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/groupby.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/ops.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/common.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/_aggregations.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/resample_cftime.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/weighted.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/extensions.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/combine.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/_typed_ops.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/coordinates.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/pdcompat.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/formatting_html.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/accessor_dt.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/parallel.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/rolling_exp.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/formatting.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/concat.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/_typed_ops.pyi -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/duck_array_ops.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/__init__.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/merge.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/rolling.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/missing.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/dataarray.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/indexing.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/indexes.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/dtypes.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/utils.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/arithmetic.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/core/nanops.py -> build/bdist.linux-x86_64/wheel/xarray/core copying build/lib/xarray/convert.py -> build/bdist.linux-x86_64/wheel/xarray creating build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/memory.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/pynio_.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/common.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/netcdf3.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/locks.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/cfgrib_.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/store.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/h5netcdf_.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/file_manager.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/rasterio_.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/netCDF4_.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/__init__.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/lru_cache.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/api.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/pseudonetcdf_.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/zarr.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/plugins.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/pydap_.py -> build/bdist.linux-x86_64/wheel/xarray/backends copying build/lib/xarray/backends/scipy_.py -> build/bdist.linux-x86_64/wheel/xarray/backends creating build/bdist.linux-x86_64/wheel/xarray/coding copying build/lib/xarray/coding/calendar_ops.py -> build/bdist.linux-x86_64/wheel/xarray/coding copying build/lib/xarray/coding/variables.py -> build/bdist.linux-x86_64/wheel/xarray/coding copying build/lib/xarray/coding/times.py -> build/bdist.linux-x86_64/wheel/xarray/coding copying build/lib/xarray/coding/cftimeindex.py -> build/bdist.linux-x86_64/wheel/xarray/coding copying build/lib/xarray/coding/frequencies.py -> build/bdist.linux-x86_64/wheel/xarray/coding copying build/lib/xarray/coding/cftime_offsets.py -> build/bdist.linux-x86_64/wheel/xarray/coding copying build/lib/xarray/coding/__init__.py -> build/bdist.linux-x86_64/wheel/xarray/coding copying build/lib/xarray/coding/strings.py -> build/bdist.linux-x86_64/wheel/xarray/coding copying build/lib/xarray/__init__.py -> build/bdist.linux-x86_64/wheel/xarray copying build/lib/xarray/tutorial.py -> build/bdist.linux-x86_64/wheel/xarray creating build/bdist.linux-x86_64/wheel/xarray/plot copying build/lib/xarray/plot/dataset_plot.py -> build/bdist.linux-x86_64/wheel/xarray/plot copying build/lib/xarray/plot/__init__.py -> build/bdist.linux-x86_64/wheel/xarray/plot copying build/lib/xarray/plot/facetgrid.py -> build/bdist.linux-x86_64/wheel/xarray/plot copying build/lib/xarray/plot/accessor.py -> build/bdist.linux-x86_64/wheel/xarray/plot copying build/lib/xarray/plot/utils.py -> build/bdist.linux-x86_64/wheel/xarray/plot copying build/lib/xarray/plot/dataarray_plot.py -> build/bdist.linux-x86_64/wheel/xarray/plot copying build/lib/xarray/conventions.py -> build/bdist.linux-x86_64/wheel/xarray creating build/bdist.linux-x86_64/wheel/xarray/indexes copying build/lib/xarray/indexes/__init__.py -> build/bdist.linux-x86_64/wheel/xarray/indexes copying build/lib/xarray/testing.py -> build/bdist.linux-x86_64/wheel/xarray copying build/lib/xarray/py.typed -> build/bdist.linux-x86_64/wheel/xarray creating build/bdist.linux-x86_64/wheel/xarray/util copying build/lib/xarray/util/generate_ops.py -> build/bdist.linux-x86_64/wheel/xarray/util copying build/lib/xarray/util/print_versions.py -> build/bdist.linux-x86_64/wheel/xarray/util copying build/lib/xarray/util/__init__.py -> build/bdist.linux-x86_64/wheel/xarray/util copying build/lib/xarray/util/generate_aggregations.py -> build/bdist.linux-x86_64/wheel/xarray/util copying build/lib/xarray/util/deprecation_helpers.py -> build/bdist.linux-x86_64/wheel/xarray/util running install_egg_info Copying xarray.egg-info to build/bdist.linux-x86_64/wheel/xarray-2022.11.0-py3.10.egg-info running install_scripts adding license file "LICENSE" (matched pattern "LICEN[CS]E*") creating build/bdist.linux-x86_64/wheel/xarray-2022.11.0.dist-info/WHEEL creating '/home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/.pyproject-builddir/pip-wheel-_u1diu5s/tmpdy_byhq1/xarray-2022.11.0-py3-none-any.whl' and adding 'build/bdist.linux-x86_64/wheel' to it adding 'xarray/__init__.py' adding 'xarray/conventions.py' adding 'xarray/convert.py' adding 'xarray/py.typed' adding 'xarray/testing.py' adding 'xarray/tutorial.py' adding 'xarray/backends/__init__.py' adding 'xarray/backends/api.py' adding 'xarray/backends/cfgrib_.py' adding 'xarray/backends/common.py' adding 'xarray/backends/file_manager.py' adding 'xarray/backends/h5netcdf_.py' adding 'xarray/backends/locks.py' adding 'xarray/backends/lru_cache.py' adding 'xarray/backends/memory.py' adding 'xarray/backends/netCDF4_.py' adding 'xarray/backends/netcdf3.py' adding 'xarray/backends/plugins.py' adding 'xarray/backends/pseudonetcdf_.py' adding 'xarray/backends/pydap_.py' adding 'xarray/backends/pynio_.py' adding 'xarray/backends/rasterio_.py' adding 'xarray/backends/scipy_.py' adding 'xarray/backends/store.py' adding 'xarray/backends/zarr.py' adding 'xarray/coding/__init__.py' adding 'xarray/coding/calendar_ops.py' adding 'xarray/coding/cftime_offsets.py' adding 'xarray/coding/cftimeindex.py' adding 'xarray/coding/frequencies.py' adding 'xarray/coding/strings.py' adding 'xarray/coding/times.py' adding 'xarray/coding/variables.py' adding 'xarray/core/__init__.py' adding 'xarray/core/_aggregations.py' adding 'xarray/core/_typed_ops.py' adding 'xarray/core/_typed_ops.pyi' adding 'xarray/core/accessor_dt.py' adding 'xarray/core/accessor_str.py' adding 'xarray/core/alignment.py' adding 'xarray/core/arithmetic.py' adding 'xarray/core/combine.py' adding 'xarray/core/common.py' adding 'xarray/core/computation.py' adding 'xarray/core/concat.py' adding 'xarray/core/coordinates.py' adding 'xarray/core/dask_array_ops.py' adding 'xarray/core/dataarray.py' adding 'xarray/core/dataset.py' adding 'xarray/core/dtypes.py' adding 'xarray/core/duck_array_ops.py' adding 'xarray/core/extensions.py' adding 'xarray/core/formatting.py' adding 'xarray/core/formatting_html.py' adding 'xarray/core/groupby.py' adding 'xarray/core/indexes.py' adding 'xarray/core/indexing.py' adding 'xarray/core/merge.py' adding 'xarray/core/missing.py' adding 'xarray/core/nanops.py' adding 'xarray/core/npcompat.py' adding 'xarray/core/nputils.py' adding 'xarray/core/ops.py' adding 'xarray/core/options.py' adding 'xarray/core/parallel.py' adding 'xarray/core/pdcompat.py' adding 'xarray/core/pycompat.py' adding 'xarray/core/resample.py' adding 'xarray/core/resample_cftime.py' adding 'xarray/core/rolling.py' adding 'xarray/core/rolling_exp.py' adding 'xarray/core/types.py' adding 'xarray/core/utils.py' adding 'xarray/core/variable.py' adding 'xarray/core/weighted.py' adding 'xarray/indexes/__init__.py' adding 'xarray/plot/__init__.py' adding 'xarray/plot/accessor.py' adding 'xarray/plot/dataarray_plot.py' adding 'xarray/plot/dataset_plot.py' adding 'xarray/plot/facetgrid.py' adding 'xarray/plot/utils.py' adding 'xarray/static/__init__.py' adding 'xarray/static/css/__init__.py' adding 'xarray/static/css/style.css' adding 'xarray/static/html/__init__.py' adding 'xarray/static/html/icons-svg-inline.html' adding 'xarray/tests/__init__.py' adding 'xarray/tests/conftest.py' adding 'xarray/tests/test_accessor_dt.py' adding 'xarray/tests/test_accessor_str.py' adding 'xarray/tests/test_array_api.py' adding 'xarray/tests/test_backends.py' adding 'xarray/tests/test_backends_api.py' adding 'xarray/tests/test_backends_common.py' adding 'xarray/tests/test_backends_file_manager.py' adding 'xarray/tests/test_backends_locks.py' adding 'xarray/tests/test_backends_lru_cache.py' adding 'xarray/tests/test_calendar_ops.py' adding 'xarray/tests/test_cftime_offsets.py' adding 'xarray/tests/test_cftimeindex.py' adding 'xarray/tests/test_cftimeindex_resample.py' adding 'xarray/tests/test_coarsen.py' adding 'xarray/tests/test_coding.py' adding 'xarray/tests/test_coding_strings.py' adding 'xarray/tests/test_coding_times.py' adding 'xarray/tests/test_combine.py' adding 'xarray/tests/test_computation.py' adding 'xarray/tests/test_concat.py' adding 'xarray/tests/test_conventions.py' adding 'xarray/tests/test_cupy.py' adding 'xarray/tests/test_dask.py' adding 'xarray/tests/test_dataarray.py' adding 'xarray/tests/test_dataset.py' adding 'xarray/tests/test_deprecation_helpers.py' adding 'xarray/tests/test_distributed.py' adding 'xarray/tests/test_dtypes.py' adding 'xarray/tests/test_duck_array_ops.py' adding 'xarray/tests/test_extensions.py' adding 'xarray/tests/test_formatting.py' adding 'xarray/tests/test_formatting_html.py' adding 'xarray/tests/test_groupby.py' adding 'xarray/tests/test_indexes.py' adding 'xarray/tests/test_indexing.py' adding 'xarray/tests/test_interp.py' adding 'xarray/tests/test_merge.py' adding 'xarray/tests/test_missing.py' adding 'xarray/tests/test_nputils.py' adding 'xarray/tests/test_options.py' adding 'xarray/tests/test_plot.py' adding 'xarray/tests/test_plugins.py' adding 'xarray/tests/test_print_versions.py' adding 'xarray/tests/test_rolling.py' adding 'xarray/tests/test_sparse.py' adding 'xarray/tests/test_testing.py' adding 'xarray/tests/test_tutorial.py' adding 'xarray/tests/test_ufuncs.py' adding 'xarray/tests/test_units.py' adding 'xarray/tests/test_utils.py' adding 'xarray/tests/test_variable.py' adding 'xarray/tests/test_weighted.py' adding 'xarray/tests/data/bears.nc' adding 'xarray/tests/data/example.grib' adding 'xarray/tests/data/example.ict' adding 'xarray/tests/data/example.uamiv' adding 'xarray/tests/data/example_1.nc' adding 'xarray/tests/data/example_1.nc.gz' adding 'xarray/util/__init__.py' adding 'xarray/util/deprecation_helpers.py' adding 'xarray/util/generate_aggregations.py' adding 'xarray/util/generate_ops.py' adding 'xarray/util/print_versions.py' adding 'xarray-2022.11.0.dist-info/LICENSE' adding 'xarray-2022.11.0.dist-info/METADATA' adding 'xarray-2022.11.0.dist-info/WHEEL' adding 'xarray-2022.11.0.dist-info/top_level.txt' adding 'xarray-2022.11.0.dist-info/RECORD' removing build/bdist.linux-x86_64/wheel Building wheel for xarray (pyproject.toml): finished with status 'done' Created wheel for xarray: filename=xarray-2022.11.0-py3-none-any.whl size=963748 sha256=d390a7fed3ec4046a14acae4a46f59547f779c4a61ef0ee5a94c81290cf63209 Stored in directory: /home/pterjan/.cache/pip/wheels/09/d8/32/72cb1902f6a7328cf5ef0ce7999ebbd0c551d23152de8ecfb6 Successfully built xarray + RPM_EC=0 ++ jobs -p + exit 0 Executing(%install): /bin/sh -e /home/pterjan/rpmbuild/tmp/rpm-tmp.B6r1WX + umask 022 + cd /home/pterjan/rpmbuild/BUILD + '[' 1 -eq 1 ']' + '[' /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch '!=' / ']' + rm -rf /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch ++ dirname /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch + mkdir -p /home/pterjan/rpmbuild/BUILDROOT + mkdir /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch + cd xarray-2022.11.0 + '[' 1 -eq 1 ']' ++ sed -E 's/([^-]+)-([^-]+)-.+\.whl/\1==\2/' ++ ls /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/pyproject-wheeldir/xarray-2022.11.0-py3-none-any.whl ++ xargs basename --multiple + specifier=xarray==2022.11.0 + TMPDIR=/home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/.pyproject-builddir + /usr/bin/python3 -m pip install --root /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch --prefix /usr --no-deps --disable-pip-version-check --progress-bar off --verbose --ignore-installed --no-warn-script-location --no-index --no-cache-dir --find-links /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/pyproject-wheeldir xarray==2022.11.0 Using pip 23.0.1 from /usr/lib/python3.10/site-packages/pip (python 3.10) Looking in links: /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/pyproject-wheeldir Processing ./pyproject-wheeldir/xarray-2022.11.0-py3-none-any.whl Installing collected packages: xarray Successfully installed xarray-2022.11.0 + '[' -d /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch/usr/bin ']' + rm -f /home/pterjan/rpmbuild/BUILD/python-xarray-2022.11.0-2.mga9.noarch-pyproject-ghost-distinfo + site_dirs=() + '[' -d /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch/usr/lib/python3.10/site-packages ']' + site_dirs+=("/usr/lib/python3.10/site-packages") + '[' /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch/usr/lib64/python3.10/site-packages '!=' /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch/usr/lib/python3.10/site-packages ']' + '[' -d /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch/usr/lib64/python3.10/site-packages ']' + for site_dir in ${site_dirs[@]} + for distinfo in /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch$site_dir/*.dist-info + echo '%ghost /usr/lib/python3.10/site-packages/xarray-2022.11.0.dist-info' + sed -i s/pip/rpm/ /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch/usr/lib/python3.10/site-packages/xarray-2022.11.0.dist-info/INSTALLER + PYTHONPATH=/usr/lib/rpm/redhat + /usr/bin/python3 -B /usr/lib/rpm/redhat/pyproject_preprocess_record.py --buildroot /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch --record /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch/usr/lib/python3.10/site-packages/xarray-2022.11.0.dist-info/RECORD --output /home/pterjan/rpmbuild/BUILD/python-xarray-2022.11.0-2.mga9.noarch-pyproject-record + rm -fv /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch/usr/lib/python3.10/site-packages/xarray-2022.11.0.dist-info/RECORD removed '/home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch/usr/lib/python3.10/site-packages/xarray-2022.11.0.dist-info/RECORD' + rm -fv /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch/usr/lib/python3.10/site-packages/xarray-2022.11.0.dist-info/REQUESTED removed '/home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch/usr/lib/python3.10/site-packages/xarray-2022.11.0.dist-info/REQUESTED' ++ wc -l /home/pterjan/rpmbuild/BUILD/python-xarray-2022.11.0-2.mga9.noarch-pyproject-ghost-distinfo ++ cut -f1 '-d ' + lines=1 + '[' 1 -ne 1 ']' + /usr/bin/python3 /usr/lib/rpm/redhat/pyproject_save_files.py --output-files /home/pterjan/rpmbuild/BUILD/python-xarray-2022.11.0-2.mga9.noarch-pyproject-files --output-modules /home/pterjan/rpmbuild/BUILD/python-xarray-2022.11.0-2.mga9.noarch-pyproject-modules --buildroot /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch --sitelib /usr/lib/python3.10/site-packages --sitearch /usr/lib64/python3.10/site-packages --python-version 3.10 --pyproject-record /home/pterjan/rpmbuild/BUILD/python-xarray-2022.11.0-2.mga9.noarch-pyproject-record --prefix /usr xarray + /usr/bin/find-debuginfo -j16 --strict-build-id -m -i --build-id-seed 2022.11.0-2.mga9 --unique-debug-suffix -2022.11.0-2.mga9.noarch --unique-debug-src-base python-xarray-2022.11.0-2.mga9.noarch --run-dwz --dwz-low-mem-die-limit 10000000 --dwz-max-die-limit 50000000 -S debugsourcefiles.list /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0 + /usr/lib/rpm/check-buildroot + '[' -n '' ']' + /usr/share/spec-helper/clean_files + '[' -n '' ']' + /usr/share/spec-helper/compress_files .xz + '[' -n '' ']' + /usr/share/spec-helper/relink_symlinks + '[' -n '' ']' + /usr/share/spec-helper/clean_perl + '[' -n '' ']' + /usr/share/spec-helper/lib_symlinks + '[' -n '' ']' + /usr/share/spec-helper/gprintify + '[' -n '' ']' + /usr/share/spec-helper/fix_mo + '[' -n '' ']' + /usr/share/spec-helper/fix_pamd + '[' -n '' ']' + /usr/share/spec-helper/remove_info_dir + '[' -n '' ']' + /usr/share/spec-helper/fix_eol + '[' -n '' ']' + /usr/share/spec-helper/check_desktop_files + '[' -n '' ']' + /usr/share/spec-helper/check_elf_files + /usr/lib/rpm/check-rpaths + /usr/lib/rpm/brp-remove-la-files + /usr/lib/rpm/redhat/brp-mangle-shebangs + /usr/lib/rpm/redhat/brp-python-bytecompile '' 1 0 Bytecompiling .py files below /home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch/usr/lib/python3.10 using python3.10 + /usr/lib/rpm/redhat/brp-python-hardlink Executing(%check): /bin/sh -e /home/pterjan/rpmbuild/tmp/rpm-tmp.NQJGun + umask 022 + cd /home/pterjan/rpmbuild/BUILD + cd xarray-2022.11.0 + '[' 1 -eq 1 ']' + CFLAGS='-O2 -g -pipe -Wformat -Werror=format-security -Wp,-D_FORTIFY_SOURCE=2 -fstack-protector --param=ssp-buffer-size=4 -fasynchronous-unwind-tables' + LDFLAGS=' -Wl,--as-needed -Wl,--no-undefined -Wl,-z,relro -Wl,-O1 -Wl,--build-id=sha1 -Wl,--enable-new-dtags' + PATH=/home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch/usr/bin:/usr/local/bin:/usr/bin:/usr/local/sbin:/usr/sbin:/usr/lib64/qt5/bin:/home/pterjan/.local/bin:/home/pterjan/bin + PYTHONPATH=/home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch/usr/lib64/python3.10/site-packages:/home/pterjan/rpmbuild/BUILDROOT/python-xarray-2022.11.0-2.mga9.noarch/usr/lib/python3.10/site-packages + PYTHONDONTWRITEBYTECODE=1 + PYTEST_ADDOPTS=' --ignore=/home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/.pyproject-builddir' + /usr/bin/pytest ============================= test session starts ============================== platform linux -- Python 3.10.11, pytest-7.1.3, pluggy-1.0.0 rootdir: /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0, 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[100%] =================================== FAILURES =================================== _____ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-1-None-True] _____ self = center = True, min_periods = None, window = 1, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ____ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-1-None-False] _____ self = center = False, min_periods = None, window = 1, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-1-1-True] _______ self = center = True, min_periods = 1, window = 1, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-1-1-False] ______ self = center = False, min_periods = 1, window = 1, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-1-2-True] _______ self = center = True, min_periods = 1, window = 1, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-1-2-False] ______ self = center = False, min_periods = 1, window = 1, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-1-3-True] _______ self = center = True, min_periods = 1, window = 1, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-1-3-False] ______ self = center = False, min_periods = 1, window = 1, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError _____ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-2-None-True] _____ self = center = True, min_periods = None, window = 2, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ____ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-2-None-False] _____ self = center = False, min_periods = None, window = 2, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-2-1-True] _______ self = center = True, min_periods = 1, window = 2, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-2-1-False] ______ self = center = False, min_periods = 1, window = 2, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-2-2-True] _______ self = center = True, min_periods = 2, window = 2, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-2-2-False] ______ self = center = False, min_periods = 2, window = 2, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-2-3-True] _______ self = center = True, min_periods = 2, window = 2, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-2-3-False] ______ self = center = False, min_periods = 2, window = 2, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError _____ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-3-None-True] _____ self = center = True, min_periods = None, window = 3, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ____ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-3-None-False] _____ self = center = False, min_periods = None, window = 3, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-3-1-True] _______ self = center = True, min_periods = 1, window = 3, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-3-1-False] ______ self = center = False, min_periods = 1, window = 3, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-3-2-True] _______ self = center = True, min_periods = 2, window = 3, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-3-2-False] ______ self = center = False, min_periods = 2, window = 3, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-3-3-True] _______ self = center = True, min_periods = 3, window = 3, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-3-3-False] ______ self = center = False, min_periods = 3, window = 3, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError _____ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-4-None-True] _____ self = center = True, min_periods = None, window = 4, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ____ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-4-None-False] _____ self = center = False, min_periods = None, window = 4, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-4-1-True] _______ self = center = True, min_periods = 1, window = 4, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-4-1-False] ______ self = center = False, min_periods = 1, window = 4, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-4-2-True] _______ self = center = True, min_periods = 2, window = 4, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-4-2-False] ______ self = center = False, min_periods = 2, window = 4, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-4-3-True] _______ self = center = True, min_periods = 3, window = 4, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[sum-4-3-False] ______ self = center = False, min_periods = 3, window = 4, name = 'sum' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:24: in move_sum return move_func(np.nansum, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError _____ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-1-None-True] _____ self = center = True, min_periods = None, window = 1, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ____ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-1-None-False] _____ self = center = False, min_periods = None, window = 1, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-1-1-True] _______ self = center = True, min_periods = 1, window = 1, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-1-1-False] ______ self = center = False, min_periods = 1, window = 1, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-1-2-True] _______ self = center = True, min_periods = 1, window = 1, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-1-2-False] ______ self = center = False, min_periods = 1, window = 1, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-1-3-True] _______ self = center = True, min_periods = 1, window = 1, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-1-3-False] ______ self = center = False, min_periods = 1, window = 1, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError _____ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-2-None-True] _____ self = center = True, min_periods = None, window = 2, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ____ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-2-None-False] _____ self = center = False, min_periods = None, window = 2, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-2-1-True] _______ self = center = True, min_periods = 1, window = 2, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-2-1-False] ______ self = center = False, min_periods = 1, window = 2, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-2-2-True] _______ self = center = True, min_periods = 2, window = 2, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-2-2-False] ______ self = center = False, min_periods = 2, window = 2, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-2-3-True] _______ self = center = True, min_periods = 2, window = 2, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-2-3-False] ______ self = center = False, min_periods = 2, window = 2, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError _____ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-3-None-True] _____ self = center = True, min_periods = None, window = 3, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ____ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-3-None-False] _____ self = center = False, min_periods = None, window = 3, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-3-1-True] _______ self = center = True, min_periods = 1, window = 3, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-3-1-False] ______ self = center = False, min_periods = 1, window = 3, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-3-2-True] _______ self = center = True, min_periods = 2, window = 3, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-3-2-False] ______ self = center = False, min_periods = 2, window = 3, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-3-3-True] _______ self = center = True, min_periods = 3, window = 3, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-3-3-False] ______ self = center = False, min_periods = 3, window = 3, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError _____ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-4-None-True] _____ self = center = True, min_periods = None, window = 4, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ____ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-4-None-False] _____ self = center = False, min_periods = None, window = 4, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-4-1-True] _______ self = center = True, min_periods = 1, window = 4, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-4-1-False] ______ self = center = False, min_periods = 1, window = 4, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-4-2-True] _______ self = center = True, min_periods = 2, window = 4, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-4-2-False] ______ self = center = False, min_periods = 2, window = 4, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-4-3-True] _______ self = center = True, min_periods = 3, window = 4, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError ______ TestDataArrayRolling.test_rolling_reduce_nonnumeric[max-4-3-False] ______ self = center = False, min_periods = 3, window = 4, name = 'max' @pytest.mark.parametrize("center", (True, False)) @pytest.mark.parametrize("min_periods", (None, 1, 2, 3)) @pytest.mark.parametrize("window", (1, 2, 3, 4)) @pytest.mark.parametrize("name", ("sum", "max")) def test_rolling_reduce_nonnumeric(self, center, min_periods, window, name) -> None: da = DataArray( [0, np.nan, 1, 2, np.nan, 3, 4, 5, np.nan, 6, 7], dims="time" ).isnull() if min_periods is not None and window < min_periods: min_periods = window rolling_obj = da.rolling(time=window, center=center, min_periods=min_periods) # add nan prefix to numpy methods to get similar behavior as bottleneck actual = rolling_obj.reduce(getattr(np, "nan%s" % name)) > expected = getattr(rolling_obj, name)() /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/tests/test_rolling.py:234: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:155: in method return self._numpy_or_bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:578: in _numpy_or_bottleneck_reduce return self._bottleneck_reduce( /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/rolling.py:539: in _bottleneck_reduce values = func( /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:49: in move_max return move_func(np.nanmax, a, window, min_count, axis=axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:150: in move_func idx = _mask(a, window, mc, axis) /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: in _mask idx = np.empty(a.shape, dtype=np.bool) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ attr = 'bool' def __getattr__(attr): # Warn for expired attributes, and return a dummy function # that always raises an exception. import warnings try: msg = __expired_functions__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) def _expired(*args, **kwds): raise RuntimeError(msg) return _expired # Emit warnings for deprecated attributes try: val, msg = __deprecated_attrs__[attr] except KeyError: pass else: warnings.warn(msg, DeprecationWarning, stacklevel=2) return val if attr in __future_scalars__: # And future warnings for those that will change, but also give # the AttributeError warnings.warn( f"In the future `np.{attr}` will be defined as the " "corresponding NumPy scalar.", FutureWarning, stacklevel=2) if attr in __former_attrs__: > raise AttributeError(__former_attrs__[attr]) E AttributeError: module 'numpy' has no attribute 'bool'. E `np.bool` was a deprecated alias for the builtin `bool`. To avoid this error in existing code, use `bool` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.bool_` here. E The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: E https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations /usr/lib64/python3.10/site-packages/numpy/__init__.py:305: AttributeError =============================== warnings summary =============================== xarray/tests/test_array_api.py::test_astype xarray/tests/test_dataset.py::TestDataset::test_unary_ops /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/duck_array_ops.py:187: RuntimeWarning: invalid value encountered in cast return data.astype(dtype, **kwargs) xarray/tests/test_array_api.py::test_astype /usr/lib64/python3.10/site-packages/numpy/array_api/_data_type_functions.py:20: RuntimeWarning: invalid value encountered in cast return Array._new(x._array.astype(dtype=dtype, copy=copy)) xarray/tests/test_backends.py: 8 warnings xarray/tests/test_coding_times.py: 3 warnings /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/coding/times.py:601: RuntimeWarning: invalid value encountered in cast int_num = np.asarray(num, dtype=np.int64) xarray/tests/test_backends.py::TestScipyInMemoryData::test_roundtrip_numpy_datetime_data xarray/tests/test_backends.py::TestScipyInMemoryData::test_roundtrip_numpy_datetime_data xarray/tests/test_backends.py::TestScipyFileObject::test_roundtrip_numpy_datetime_data xarray/tests/test_backends.py::TestScipyFileObject::test_roundtrip_numpy_datetime_data xarray/tests/test_backends.py::TestScipyFilePath::test_roundtrip_numpy_datetime_data xarray/tests/test_backends.py::TestScipyFilePath::test_roundtrip_numpy_datetime_data xarray/tests/test_backends.py::TestGenericNetCDFData::test_roundtrip_numpy_datetime_data xarray/tests/test_backends.py::TestGenericNetCDFData::test_roundtrip_numpy_datetime_data /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/coding/times.py:242: RuntimeWarning: invalid value encountered in cast flat_num_dates_ns_int = (flat_num_dates * _NS_PER_TIME_DELTA[delta]).astype( xarray/tests/test_backends.py: 4 warnings xarray/tests/test_coding_times.py: 10 warnings /usr/lib64/python3.10/site-packages/pandas/core/arrays/timedeltas.py:1014: RuntimeWarning: invalid value encountered in cast base = data.astype(np.int64) xarray/tests/test_backends.py: 4 warnings xarray/tests/test_coding_times.py: 10 warnings /usr/lib64/python3.10/site-packages/pandas/core/arrays/timedeltas.py:1018: RuntimeWarning: invalid value encountered in cast data = (base * m + (frac * m).astype(np.int64)).view("timedelta64[ns]") xarray/tests/test_backends.py: 12 warnings /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/coding/variables.py:167: DeprecationWarning: NumPy will stop allowing conversion of out-of-bound Python integers to integer arrays. The conversion of 255 to int8 will fail in the future. For the old behavior, usually: np.array(value).astype(dtype)` will give the desired result (the cast overflows). encoding["_FillValue"] = dtype.type(fv) xarray/tests/test_dataarray.py: 5 warnings xarray/tests/test_dataset.py: 7 warnings xarray/tests/test_groupby.py: 2 warnings <__array_function__ internals>:200: RuntimeWarning: invalid value encountered in cast xarray/tests/test_dataset.py::TestDataset::test_assign_coords_existing_multiindex /home/pterjan/rpmbuild/BUILD/xarray-2022.11.0/xarray/core/common.py:609: FutureWarning: Updating MultiIndexed coordinate 'x' would corrupt indices for other variables: ['level_1', 'level_2']. This will raise an error in the future. Use `.drop_vars({'level_1', 'x', 'level_2'})` before assigning new coordinate values. data.coords.update(results) xarray/tests/test_print_versions.py::test_show_versions /usr/lib/python3.10/site-packages/_distutils_hack/__init__.py:33: UserWarning: Setuptools is replacing distutils. warnings.warn("Setuptools is replacing distutils.") xarray/tests/test_rolling.py: 64 warnings /usr/lib64/python3.10/site-packages/bottleneck/slow/move.py:168: FutureWarning: In the future `np.bool` will be defined as the corresponding NumPy scalar. idx = np.empty(a.shape, dtype=np.bool) -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html =========================== short test summary info ============================ FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-1-None-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-1-None-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-1-1-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-1-1-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-1-2-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-1-2-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-1-3-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-1-3-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-2-None-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-2-None-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-2-1-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-2-1-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-2-2-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-2-2-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-2-3-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-2-3-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-3-None-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-3-None-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-3-1-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-3-1-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-3-2-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-3-2-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-3-3-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-3-3-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-4-None-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-4-None-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-4-1-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-4-1-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-4-2-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-4-2-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-4-3-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[sum-4-3-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-1-None-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-1-None-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-1-1-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-1-1-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-1-2-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-1-2-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-1-3-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-1-3-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-2-None-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-2-None-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-2-1-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-2-1-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-2-2-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-2-2-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-2-3-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-2-3-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-3-None-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-3-None-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-3-1-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-3-1-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-3-2-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-3-2-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-3-3-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-3-3-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-4-None-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-4-None-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-4-1-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-4-1-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-4-2-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-4-2-False] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-4-3-True] FAILED xarray/tests/test_rolling.py::TestDataArrayRolling::test_rolling_reduce_nonnumeric[max-4-3-False] = 64 failed, 5300 passed, 5053 skipped, 20 xfailed, 24 xpassed, 142 warnings in 257.09s (0:04:17) = error: Bad exit status from /home/pterjan/rpmbuild/tmp/rpm-tmp.NQJGun (%check) RPM build errors: Bad exit status from /home/pterjan/rpmbuild/tmp/rpm-tmp.NQJGun (%check) I: [iurt_root_command] ERROR: chroot