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here is the log from the commit of package python-scikit-image for
openSUSE:Factory checked in at 2023-08-28 17:11:59
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Comparing /work/SRC/openSUSE:Factory/python-scikit-image (Old)
and /work/SRC/openSUSE:Factory/.python-scikit-image.new.1766 (New)
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Package is "python-scikit-image"
Mon Aug 28 17:11:59 2023 rev:18 rq:1105471 version:0.21.0
Changes:
--------
--- /work/SRC/openSUSE:Factory/python-scikit-image/python-scikit-image.changes
2023-07-11 15:57:03.917088299 +0200
+++
/work/SRC/openSUSE:Factory/.python-scikit-image.new.1766/python-scikit-image.changes
2023-08-28 17:12:00.545742802 +0200
@@ -1,0 +2,6 @@
+Tue Aug 22 19:18:49 UTC 2023 - Markéta Machová <mmach...@suse.com>
+
+- Add upstream patches np-warn.patch and skimage-numpy125.patch
+ to fix build with NumPy 1.25
+
+-------------------------------------------------------------------
New:
----
np-warn.patch
skimage-numpy125.patch
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Other differences:
------------------
++++++ python-scikit-image.spec ++++++
--- /var/tmp/diff_new_pack.dW8wiw/_old 2023-08-28 17:12:01.829788914 +0200
+++ /var/tmp/diff_new_pack.dW8wiw/_new 2023-08-28 17:12:01.833789058 +0200
@@ -32,6 +32,10 @@
License: BSD-3-Clause
URL: https://scikit-image.org/
Source0:
https://files.pythonhosted.org/packages/source/s/scikit-image/%{srcname}-%{version}.tar.gz
+# PATCH-FIX-UPSTREAM np-warn.patch gh#scikit-image/scikit-image#7052
+Patch: np-warn.patch
+# PATCH-FIX-UPSTREAM skimage-numpy125.patch gh#scikit-image/scikit-image#6970
+Patch: skimage-numpy125.patch
BuildRequires: %{python_module Cython >= 0.29.21}
BuildRequires: %{python_module devel >= 3.7}
BuildRequires: %{python_module meson-python}
++++++ np-warn.patch ++++++
>From 2cc363d015b71b3cbe14f179f19bbb4ea2e6ab0e Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Lars=20Gr=C3=BCter?= <la...@mailbox.org>
Date: Sat, 8 Jul 2023 21:09:06 +0200
Subject: [PATCH] Mark NaN-related deprecation warning in np.clip as optional
(#7052)
We already have our own warning that informs users and this deprecation
didn't really effect the behavior of rescale_intensity. So, mark the
warning as optional until we can remove it. No need for matching the
NumPy version number here.
---
TODO.txt | 3 +++
skimage/exposure/tests/test_exposure.py | 15 ++++++---------
2 files changed, 9 insertions(+), 9 deletions(-)
diff --git a/skimage/exposure/tests/test_exposure.py
b/skimage/exposure/tests/test_exposure.py
index ed8dd6bc85f..8ec7d13bf7f 100644
--- a/skimage/exposure/tests/test_exposure.py
+++ b/skimage/exposure/tests/test_exposure.py
@@ -368,19 +368,16 @@ def test_rescale_nan_warning(in_range, out_range):
)
# 2019/11/10 Passing NaN to np.clip raises a DeprecationWarning for
- # versions above 1.17
- # TODO: Remove once NumPy removes this DeprecationWarning
+ # versions above 1.17, "|\A\Z" marks as optional warning
+ # TODO: Remove once NumPy 1.25.0 is minimal dependency
numpy_warning_1_17_plus = (
- "Passing `np.nan` to mean no clipping in np.clip"
+ "|\\A\\ZPassing `np.nan` to mean no clipping in np.clip"
)
- if in_range == "image":
- exp_warn = [msg, numpy_warning_1_17_plus]
- else:
- exp_warn = [msg]
+ with expected_warnings([msg, numpy_warning_1_17_plus]):
+ result = exposure.rescale_intensity(image, in_range, out_range)
- with expected_warnings(exp_warn):
- exposure.rescale_intensity(image, in_range, out_range)
+ assert np.all(np.isnan(result))
@pytest.mark.parametrize(
++++++ skimage-numpy125.patch ++++++
>From 01a9282f4ea2cd5523ff41e1ebcf88491ac76ca2 Mon Sep 17 00:00:00 2001
From: Jarrod Millman <jarrod.mill...@gmail.com>
Date: Thu, 17 Aug 2023 11:40:50 -0700
Subject: [PATCH] Fix for NumPy 1.25 (#6970)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
* Fix for NumPy 1.25
* Revert #6973
* Revert "Don't test numpy prerelease on azure (#6996)"
This reverts commit e57c23d3d9072fa7b810fc40dc7e9082791b0629.
* Skip warning check on older, noisier versions of NumPy
* Remove upperpin
* Use stable sort in _raveled_offsets_and_distances
NumPy enabled optimizations for quicksort on AVX-512 enabled
processors [1]. We sort based on neighbor distances which can be equal.
The default quicksort is not stable and could have different behavior on
AVX-512. Test this assumption.
[1]
https://numpy.org/devdocs/release/1.25.0-notes.html#faster-np-argsort-on-avx-512-enabled-processors
* Fix forgotten doctest in _offsets_to_raveled_neighbors
after updating to stable sort internally.
* Fix for NumPy 1.25
* Revert #6973
* Revert "Don't test numpy prerelease on azure (#6996)"
This reverts commit e57c23d3d9072fa7b810fc40dc7e9082791b0629.
* Skip warning check on older, noisier versions of NumPy
* Remove upperpin
* Use stable sort in _raveled_offsets_and_distances
NumPy enabled optimizations for quicksort on AVX-512 enabled
processors [1]. We sort based on neighbor distances which can be equal.
The default quicksort is not stable and could have different behavior on
AVX-512. Test this assumption.
[1]
https://numpy.org/devdocs/release/1.25.0-notes.html#faster-np-argsort-on-avx-512-enabled-processors
* Fix forgotten doctest in _offsets_to_raveled_neighbors
after updating to stable sort internally.
* Handle rank>0 scalar arrays
https://github.com/numpy/numpy/issues/10404
* Use stable sort
* Use stable sort in max_tree (debug)
See if it does anything.
* Use stable sort in _get_high_intensity_peaks (debug)
See if it does anything.
* Upper pin numpy<1.26 for tests
---------
Co-authored-by: Stefan van der Walt <stef...@berkeley.edu>
Co-authored-by: Lars Grüter <la...@mailbox.org>
---
.github/workflows/wheels_recipe.yml | 24 ++++++++++-------------
azure-pipelines.yml | 4 ++--
skimage/exposure/tests/test_exposure.py | 26 ++++++++++---------------
skimage/feature/peak.py | 2 +-
skimage/measure/fit.py | 4 ++--
skimage/morphology/_util.py | 11 ++++++-----
skimage/morphology/max_tree.py | 2 +-
skimage/morphology/tests/test_util.py | 22 ++++++++++-----------
tools/github/before_install.sh | 5 ++---
9 files changed, 45 insertions(+), 55 deletions(-)
diff --git a/skimage/exposure/tests/test_exposure.py
b/skimage/exposure/tests/test_exposure.py
index 8ec7d13bf7f..ac2cf02be0c 100644
--- a/skimage/exposure/tests/test_exposure.py
+++ b/skimage/exposure/tests/test_exposure.py
@@ -7,6 +7,7 @@
assert_array_almost_equal,
assert_array_equal,
assert_equal)
+from packaging.version import Version
from skimage import data
from skimage import exposure
@@ -354,6 +355,10 @@ def test_rescale_same_values():
assert_array_almost_equal(out, image)
+@pytest.mark.skipif(
+ Version(np.__version__) < Version('1.25'),
+ reason="Older NumPy throws a few extra warnings here"
+)
@pytest.mark.parametrize(
"in_range,out_range", [("image", "dtype"),
("dtype", "image")]
@@ -362,22 +367,11 @@ def test_rescale_nan_warning(in_range, out_range):
image = np.arange(12, dtype=float).reshape(3, 4)
image[1, 1] = np.nan
- msg = (
- r"One or more intensity levels are NaN\."
- r" Rescaling will broadcast NaN to the full image\."
- )
-
- # 2019/11/10 Passing NaN to np.clip raises a DeprecationWarning for
- # versions above 1.17, "|\A\Z" marks as optional warning
- # TODO: Remove once NumPy 1.25.0 is minimal dependency
- numpy_warning_1_17_plus = (
- "|\\A\\ZPassing `np.nan` to mean no clipping in np.clip"
- )
-
- with expected_warnings([msg, numpy_warning_1_17_plus]):
- result = exposure.rescale_intensity(image, in_range, out_range)
-
- assert np.all(np.isnan(result))
+ with expected_warnings([
+ r"One or more intensity levels are NaN\."
+ r" Rescaling will broadcast NaN to the full image\."
+ ]):
+ exposure.rescale_intensity(image, in_range, out_range)
@pytest.mark.parametrize(
diff --git a/skimage/feature/peak.py b/skimage/feature/peak.py
index 4097d8245b1..5dca21d8dbb 100644
--- a/skimage/feature/peak.py
+++ b/skimage/feature/peak.py
@@ -15,7 +15,7 @@ def _get_high_intensity_peaks(image, mask, num_peaks,
min_distance, p_norm):
coord = np.nonzero(mask)
intensities = image[coord]
# Highest peak first
- idx_maxsort = np.argsort(-intensities)
+ idx_maxsort = np.argsort(-intensities, kind="stable")
coord = np.transpose(coord)[idx_maxsort]
if np.isfinite(num_peaks):
diff --git a/skimage/measure/fit.py b/skimage/measure/fit.py
index dd0135290a2..0a21f8000fc 100644
--- a/skimage/measure/fit.py
+++ b/skimage/measure/fit.py
@@ -576,8 +576,8 @@ def residuals(self, data):
N = data.shape[0]
def fun(t, xi, yi):
- ct = math.cos(t)
- st = math.sin(t)
+ ct = math.cos(np.squeeze(t))
+ st = math.sin(np.squeeze(t))
xt = xc + a * ctheta * ct - b * stheta * st
yt = yc + a * stheta * ct + b * ctheta * st
return (xi - xt) ** 2 + (yi - yt) ** 2
diff --git a/skimage/morphology/_util.py b/skimage/morphology/_util.py
index c04cd13d6f4..d19fd6263e8 100644
--- a/skimage/morphology/_util.py
+++ b/skimage/morphology/_util.py
@@ -148,16 +148,17 @@ def _raveled_offsets_and_distances(
spacing = np.ones(ndim)
weighted_offsets = offsets * spacing
distances = np.sqrt(np.sum(weighted_offsets**2, axis=1))
- sorted_raveled_offsets = raveled_offsets[np.argsort(distances)]
- sorted_distances = np.sort(distances)
+ sorted_raveled_offsets = raveled_offsets[np.argsort(distances,
kind="stable")]
+ sorted_distances = np.sort(distances, kind="stable")
# If any dimension in image_shape is smaller than footprint.shape
# duplicates might occur, remove them
if any(x < y for x, y in zip(image_shape, footprint.shape)):
# np.unique reorders, which we don't want
_, indices = np.unique(sorted_raveled_offsets, return_index=True)
- sorted_raveled_offsets = sorted_raveled_offsets[np.sort(indices)]
- sorted_distances = sorted_distances[np.sort(indices)]
+ indices = np.sort(indices, kind="stable")
+ sorted_raveled_offsets = sorted_raveled_offsets[indices]
+ sorted_distances = sorted_distances[indices]
# Remove "offset to center"
sorted_raveled_offsets = sorted_raveled_offsets[1:]
@@ -198,7 +199,7 @@ def _offsets_to_raveled_neighbors(image_shape, footprint,
center, order='C'):
>>> _offsets_to_raveled_neighbors((4, 5), np.ones((4, 3)), (1, 1))
array([-5, -1, 1, 5, -6, -4, 4, 6, 10, 9, 11])
>>> _offsets_to_raveled_neighbors((2, 3, 2), np.ones((3, 3, 3)), (1, 1, 1))
- array([ 2, -6, 1, -1, 6, -2, 3, 8, -3, -4, 7, -5, -7, -8, 5, 4, -9,
+ array([-6, -2, -1, 1, 2, 6, -8, -7, -5, -4, -3, 3, 4, 5, 7, 8, -9,
9])
"""
raveled_offsets = _raveled_offsets_and_distances(
diff --git a/skimage/morphology/max_tree.py b/skimage/morphology/max_tree.py
index 49832e1c2b2..0f7c2bd29e4 100644
--- a/skimage/morphology/max_tree.py
+++ b/skimage/morphology/max_tree.py
@@ -131,7 +131,7 @@ def max_tree(image, connectivity=1):
offset).astype(np.int32)
# pixels need to be sorted according to their gray level.
- tree_traverser = np.argsort(image.ravel()).astype(np.int64)
+ tree_traverser = np.argsort(image.ravel(), kind="stable").astype(np.int64)
# call of cython function.
_max_tree._max_tree(image.ravel(), mask.ravel().astype(np.uint8),
diff --git a/skimage/morphology/tests/test_util.py
b/skimage/morphology/tests/test_util.py
index bc9a0fcbb6e..43024440224 100644
--- a/skimage/morphology/tests/test_util.py
+++ b/skimage/morphology/tests/test_util.py
@@ -98,9 +98,9 @@ def test_offsets_to_raveled_neighbors_explicit_0():
)
desired = np.array([
- 3, -600, 1, -1, 600, -3, 4, 2, 603, -2, -4,
- -597, 601, -599, -601, -603, 599, 597, 602, -604, 596, -596,
- -598, -602, 598, 604
+ -600, -3, -1, 1, 3, 600, -603, -601, -599, -597, -4,
+ -2, 2, 4, 597, 599, 601, 603, -604, -602, -598, -596,
+ 596, 598, 602, 604
])
assert_array_equal(offsets, desired)
@@ -115,12 +115,12 @@ def test_offsets_to_raveled_neighbors_explicit_1():
)
desired = np.array([
- 216, 24, -24, 3, -216, 1, -1, -3, 215, -27, -25, -23, -21, -2,
- -192, 192, 2, 4, 21, 23, 25, 27, -4, 217, 213, -219, 219, -217,
- -213, -215, 240, -240, 193, 239, -237, 241, -239, 218, -220, 22,
- -241, 243, 189, 26, -243, 191, 20, -218, 195, -193, 220, -191,
- -212, -189, 214, 28, -195, -214, -28, 212, -22, 237, -20, -26, 236,
- 196, 190, 242, 238, 194, 188, -244, -188, -196, -194, -190, -238,
- -236, 244, -242, 5, 221, -211, -19, 29, -235, -187, 197, 245
- ])
+ -216, -24, -3, -1, 1, 3, 24, 216, -240, -219, -217,
-215, -213,
+ -192, -27, -25, -23, -21, -4, -2, 2, 4, 21, 23,
25, 27,
+ 192, 213, 215, 217, 219, 240, -243, -241, -239, -237, -220,
-218, -214,
+ -212, -195, -193, -191, -189, -28, -26, -22, -20, 20, 22,
26, 28,
+ 189, 191, 193, 195, 212, 214, 218, 220, 237, 239, 241,
243, -244,
+ -242, -238, -236, -196, -194, -190, -188, 188, 190, 194, 196,
236, 238,
+ 242, 244, 5, -211, -19, 29, 221, -235, -187, 197, 245
+ ])
assert_array_equal(offsets, desired)
