[Git][debian-gis-team/flox][master] Revert "Add upstream patch to fix test failure on i386."
Bas Couwenberg (@sebastic)
gitlab at salsa.debian.org
Fri Jan 13 16:48:05 GMT 2023
Bas Couwenberg pushed to branch master at Debian GIS Project / flox
Commits:
bc74ecad by Bas Couwenberg at 2023-01-13T17:47:46+01:00
Revert "Add upstream patch to fix test failure on i386."
This reverts commit ee43c256b7df83c02edd219d379f2992e3afe6d5.
- - - - -
3 changed files:
- debian/changelog
- − debian/patches/pr201-32bit-support-int64-to-intp.patch
- debian/patches/series
Changes:
=====================================
debian/changelog
=====================================
@@ -2,7 +2,6 @@ flox (0.6.5-4) UNRELEASED; urgency=medium
* Team upload.
* Add gbp.conf to use pristine-tar & --source-only-changes by default.
- * Add upstream patch to fix test failure on i386.
* Temporarily drop python3-dask from build dependencies,
python3-pandas prevents its installation.
=====================================
debian/patches/pr201-32bit-support-int64-to-intp.patch deleted
=====================================
@@ -1,280 +0,0 @@
-Description: 32bit support: int64 to intp
-Author: dcherian <deepak at cherian.net>
-Origin: https://github.com/xarray-contrib/flox/pull/201
-Bug: https://github.com/xarray-contrib/flox/issues/200
-
---- a/tests/test_core.py
-+++ b/tests/test_core.py
-@@ -140,7 +140,7 @@ def test_groupby_reduce(
- elif func == "sum":
- expected_result = np.array(expected, dtype=dtype)
- elif func == "count":
-- expected_result = np.array(expected, dtype=np.int64)
-+ expected_result = np.array(expected, dtype=np.intp)
-
- result, groups, = groupby_reduce(
- array,
-@@ -150,9 +150,9 @@ def test_groupby_reduce(
- fill_value=123,
- engine=engine,
- )
-- # we use pd.Index(expected_groups).to_numpy() which is always int64
-+ # we use pd.Index(expected_groups).to_numpy() which is always intp
- # for the values in this tests
-- g_dtype = by.dtype if expected_groups is None else np.int64
-+ g_dtype = by.dtype if expected_groups is None else np.intp
-
- assert_equal(groups, np.array([0, 1, 2], g_dtype))
- assert_equal(expected_result, result)
-@@ -284,7 +284,7 @@ def test_groupby_reduce_count():
- array = np.array([0, 0, np.nan, np.nan, np.nan, 1, 1])
- labels = np.array(["a", "b", "b", "b", "c", "c", "c"])
- result, _ = groupby_reduce(array, labels, func="count")
-- assert_equal(result, np.array([1, 1, 2], dtype=np.int64))
-+ assert_equal(result, np.array([1, 1, 2], dtype=np.intp))
-
-
- def test_func_is_aggregation():
-@@ -299,7 +299,7 @@ def test_func_is_aggregation():
-
- @requires_dask
- @pytest.mark.parametrize("func", ("sum", "prod"))
-- at pytest.mark.parametrize("dtype", [np.float32, np.float64, np.int32, np.int64])
-+ at pytest.mark.parametrize("dtype", [np.float32, np.float64, np.int32, np.intp])
- def test_groupby_reduce_preserves_dtype(dtype, func):
- array = np.ones((2, 12), dtype=dtype)
- by = np.array([labels] * 2)
-@@ -405,32 +405,32 @@ def test_groupby_agg_dask(func, shape, a
- def test_numpy_reduce_axis_subset(engine):
- # TODO: add NaNs
- by = labels2d
-- array = np.ones_like(by, dtype=np.int64)
-+ array = np.ones_like(by, dtype=np.intp)
- kwargs = dict(func="count", engine=engine, fill_value=0)
- result, _ = groupby_reduce(array, by, **kwargs, axis=1)
-- assert_equal(result, np.array([[2, 3], [2, 3]], dtype=np.int64))
-+ assert_equal(result, np.array([[2, 3], [2, 3]], dtype=np.intp))
-
- by = np.broadcast_to(labels2d, (3, *labels2d.shape))
- array = np.ones_like(by)
- result, _ = groupby_reduce(array, by, **kwargs, axis=1)
-- subarr = np.array([[1, 1], [1, 1], [0, 2], [1, 1], [1, 1]], dtype=np.int64)
-+ subarr = np.array([[1, 1], [1, 1], [0, 2], [1, 1], [1, 1]], dtype=np.intp)
- expected = np.tile(subarr, (3, 1, 1))
- assert_equal(result, expected)
-
- result, _ = groupby_reduce(array, by, **kwargs, axis=2)
-- subarr = np.array([[2, 3], [2, 3]], dtype=np.int64)
-+ subarr = np.array([[2, 3], [2, 3]], dtype=np.intp)
- expected = np.tile(subarr, (3, 1, 1))
- assert_equal(result, expected)
-
- result, _ = groupby_reduce(array, by, **kwargs, axis=(1, 2))
-- expected = np.array([[4, 6], [4, 6], [4, 6]], dtype=np.int64)
-+ expected = np.array([[4, 6], [4, 6], [4, 6]], dtype=np.intp)
- assert_equal(result, expected)
-
- result, _ = groupby_reduce(array, by, **kwargs, axis=(2, 1))
- assert_equal(result, expected)
-
- result, _ = groupby_reduce(array, by[0, ...], **kwargs, axis=(1, 2))
-- expected = np.array([[4, 6], [4, 6], [4, 6]], dtype=np.int64)
-+ expected = np.array([[4, 6], [4, 6], [4, 6]], dtype=np.intp)
- assert_equal(result, expected)
-
-
-@@ -438,7 +438,7 @@ def test_numpy_reduce_axis_subset(engine
- def test_dask_reduce_axis_subset():
-
- by = labels2d
-- array = np.ones_like(by, dtype=np.int64)
-+ array = np.ones_like(by, dtype=np.intp)
- with raise_if_dask_computes():
- result, _ = groupby_reduce(
- da.from_array(array, chunks=(2, 3)),
-@@ -447,11 +447,11 @@ def test_dask_reduce_axis_subset():
- axis=1,
- expected_groups=[0, 2],
- )
-- assert_equal(result, np.array([[2, 3], [2, 3]], dtype=np.int64))
-+ assert_equal(result, np.array([[2, 3], [2, 3]], dtype=np.intp))
-
- by = np.broadcast_to(labels2d, (3, *labels2d.shape))
- array = np.ones_like(by)
-- subarr = np.array([[1, 1], [1, 1], [123, 2], [1, 1], [1, 1]], dtype=np.int64)
-+ subarr = np.array([[1, 1], [1, 1], [123, 2], [1, 1], [1, 1]], dtype=np.intp)
- expected = np.tile(subarr, (3, 1, 1))
- with raise_if_dask_computes():
- result, _ = groupby_reduce(
-@@ -464,7 +464,7 @@ def test_dask_reduce_axis_subset():
- )
- assert_equal(result, expected)
-
-- subarr = np.array([[2, 3], [2, 3]], dtype=np.int64)
-+ subarr = np.array([[2, 3], [2, 3]], dtype=np.intp)
- expected = np.tile(subarr, (3, 1, 1))
- with raise_if_dask_computes():
- result, _ = groupby_reduce(
-@@ -580,9 +580,9 @@ def test_groupby_all_nan_blocks_dask(exp
- nan_labels[:5] = np.nan
-
- array, by, expected = (
-- np.ones((2, 12), dtype=np.int64),
-+ np.ones((2, 12), dtype=np.intp),
- np.array([nan_labels, nan_labels[::-1]]),
-- np.array([2, 8, 4], dtype=np.int64),
-+ np.array([2, 8, 4], dtype=np.intp),
- )
-
- actual, _ = groupby_reduce(
-@@ -672,7 +672,7 @@ def test_groupby_bins(chunk_labels, chun
- engine=engine,
- method=method,
- )
-- expected = np.array([3, 1, 0], dtype=np.int64)
-+ expected = np.array([3, 1, 0], dtype=np.intp)
- for left, right in zip(groups, pd.IntervalIndex.from_arrays([1, 2, 4], [2, 4, 5]).to_numpy()):
- assert left == right
- assert_equal(actual, expected)
-@@ -772,7 +772,7 @@ def test_fill_value_behaviour(func, chun
-
- @requires_dask
- @pytest.mark.parametrize("func", ["mean", "sum"])
-- at pytest.mark.parametrize("dtype", ["float32", "float64", "int32", "int64"])
-+ at pytest.mark.parametrize("dtype", ["float32", "float64", "int32", "intp"])
- def test_dtype_preservation(dtype, func, engine):
- if func == "sum" or (func == "mean" and "float" in dtype):
- expected = np.dtype(dtype)
-@@ -789,10 +789,8 @@ def test_dtype_preservation(dtype, func,
-
-
- @requires_dask
-- at pytest.mark.parametrize("dtype", [np.int32, np.int64])
-- at pytest.mark.parametrize(
-- "labels_dtype", [pytest.param(np.int32, marks=pytest.mark.xfail), np.int64]
--)
-+ at pytest.mark.parametrize("dtype", [np.int32, np.intp])
-+ at pytest.mark.parametrize("labels_dtype", [pytest.param(np.int32, marks=pytest.mark.xfail), np.intp])
- @pytest.mark.parametrize("method", ["map-reduce", "cohorts"])
- def test_cohorts_map_reduce_consistent_dtypes(method, dtype, labels_dtype):
- repeats = np.array([4, 4, 12, 2, 3, 4], dtype=np.int32)
-@@ -801,7 +799,7 @@ def test_cohorts_map_reduce_consistent_d
-
- actual, actual_groups = groupby_reduce(array, labels, func="count", method=method)
- assert_equal(actual_groups, np.arange(6, dtype=labels.dtype))
-- assert_equal(actual, repeats.astype(np.int64))
-+ assert_equal(actual, repeats.astype(np.intp))
-
- actual, actual_groups = groupby_reduce(array, labels, func="sum", method=method)
- assert_equal(actual_groups, np.arange(6, dtype=labels.dtype))
-@@ -817,7 +815,7 @@ def test_cohorts_nd_by(func, method, axi
- o2 = dask.array.ones((2, 3), chunks=-1)
-
- array = dask.array.block([[o, 2 * o], [3 * o2, 4 * o2]])
-- by = array.compute().astype(np.int64)
-+ by = array.compute().astype(np.intp)
- by[0, 1] = 30
- by[2, 1] = 40
- by[0, 4] = 31
-@@ -842,9 +840,9 @@ def test_cohorts_nd_by(func, method, axi
-
- actual, groups = groupby_reduce(array, by, sort=False, **kwargs)
- if method == "map-reduce":
-- assert_equal(groups, np.array([1, 30, 2, 31, 3, 4, 40], dtype=np.int64))
-+ assert_equal(groups, np.array([1, 30, 2, 31, 3, 4, 40], dtype=np.intp))
- else:
-- assert_equal(groups, np.array([1, 30, 2, 31, 3, 40, 4], dtype=np.int64))
-+ assert_equal(groups, np.array([1, 30, 2, 31, 3, 40, 4], dtype=np.intp))
- reindexed = reindex_(actual, groups, pd.Index(sorted_groups))
- assert_equal(reindexed, expected)
-
-@@ -967,7 +965,7 @@ def test_factorize_values_outside_bins()
- fastpath=True,
- )
- actual = vals[0]
-- expected = np.array([[-1, -1], [-1, 0], [6, 12], [18, 24], [-1, -1]], np.int64)
-+ expected = np.array([[-1, -1], [-1, 0], [6, 12], [18, 24], [-1, -1]], np.intp)
- assert_equal(expected, actual)
-
-
-@@ -978,7 +976,7 @@ def test_multiple_groupers_bins(chunk) -
-
- xp = dask.array if chunk else np
- array_kwargs = {"chunks": 2} if chunk else {}
-- array = xp.ones((5, 2), **array_kwargs, dtype=np.int64)
-+ array = xp.ones((5, 2), **array_kwargs, dtype=np.intp)
-
- actual, *_ = groupby_reduce(
- array,
-@@ -991,7 +989,7 @@ def test_multiple_groupers_bins(chunk) -
- ),
- func="count",
- )
-- expected = np.eye(5, 5, dtype=np.int64)
-+ expected = np.eye(5, 5, dtype=np.intp)
- assert_equal(expected, actual)
-
-
-@@ -1015,12 +1013,12 @@ def test_multiple_groupers(chunk, by1, b
-
- xp = dask.array if chunk else np
- array_kwargs = {"chunks": 2} if chunk else {}
-- array = xp.ones((5, 2), **array_kwargs, dtype=np.int64)
-+ array = xp.ones((5, 2), **array_kwargs, dtype=np.intp)
-
- if chunk:
- by2 = dask.array.from_array(by2)
-
-- expected = np.ones((5, 2), dtype=np.int64)
-+ expected = np.ones((5, 2), dtype=np.intp)
- actual, *_ = groupby_reduce(
- array, by1, by2, axis=(0, 1), func="count", expected_groups=expected_groups
- )
-@@ -1066,38 +1064,38 @@ def test_factorize_reindex_sorting_strin
- )
-
- expected = factorize_(**kwargs, reindex=True, sort=True)[0]
-- assert_equal(expected, np.array([0, 1, 4, 2], dtype=np.int64))
-+ assert_equal(expected, np.array([0, 1, 4, 2], dtype=np.intp))
-
- expected = factorize_(**kwargs, reindex=True, sort=False)[0]
-- assert_equal(expected, np.array([0, 3, 4, 1], dtype=np.int64))
-+ assert_equal(expected, np.array([0, 3, 4, 1], dtype=np.intp))
-
- expected = factorize_(**kwargs, reindex=False, sort=False)[0]
-- assert_equal(expected, np.array([0, 1, 2, 3], dtype=np.int64))
-+ assert_equal(expected, np.array([0, 1, 2, 3], dtype=np.intp))
-
- expected = factorize_(**kwargs, reindex=False, sort=True)[0]
-- assert_equal(expected, np.array([0, 1, 3, 2], dtype=np.int64))
-+ assert_equal(expected, np.array([0, 1, 3, 2], dtype=np.intp))
-
-
- def test_factorize_reindex_sorting_ints():
- kwargs = dict(
- by=(np.array([-10, 1, 10, 2, 3, 5]),),
- axis=-1,
-- expected_groups=(np.array([0, 1, 2, 3, 4, 5], np.int64),),
-+ expected_groups=(np.array([0, 1, 2, 3, 4, 5], np.intp),),
- )
-
- expected = factorize_(**kwargs, reindex=True, sort=True)[0]
-- assert_equal(expected, np.array([6, 1, 6, 2, 3, 5], dtype=np.int64))
-+ assert_equal(expected, np.array([6, 1, 6, 2, 3, 5], dtype=np.intp))
-
- expected = factorize_(**kwargs, reindex=True, sort=False)[0]
-- assert_equal(expected, np.array([6, 1, 6, 2, 3, 5], dtype=np.int64))
-+ assert_equal(expected, np.array([6, 1, 6, 2, 3, 5], dtype=np.intp))
-
- kwargs["expected_groups"] = (np.arange(5, -1, -1),)
-
- expected = factorize_(**kwargs, reindex=True, sort=True)[0]
-- assert_equal(expected, np.array([6, 1, 6, 2, 3, 5], dtype=np.int64))
-+ assert_equal(expected, np.array([6, 1, 6, 2, 3, 5], dtype=np.intp))
-
- expected = factorize_(**kwargs, reindex=True, sort=False)[0]
-- assert_equal(expected, np.array([6, 4, 6, 3, 2, 0], dtype=np.int64))
-+ assert_equal(expected, np.array([6, 4, 6, 3, 2, 0], dtype=np.intp))
-
-
- @requires_dask
=====================================
debian/patches/series
=====================================
@@ -1,2 +1 @@
0001-Compatibility-with-Pandas-older-than-1.4.patch
-pr201-32bit-support-int64-to-intp.patch
View it on GitLab: https://salsa.debian.org/debian-gis-team/flox/-/commit/bc74ecad52210b839ec0c1e25f725d0cff1aa29b
--
View it on GitLab: https://salsa.debian.org/debian-gis-team/flox/-/commit/bc74ecad52210b839ec0c1e25f725d0cff1aa29b
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