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here is the log from the commit of package python-scikit-image for
openSUSE:Factory checked in at 2026-09-12 21:21:21
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Comparing /work/SRC/openSUSE:Factory/python-scikit-image (Old)
and /work/SRC/openSUSE:Factory/.python-scikit-image.new.1265 (New)
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Package is "python-scikit-image"
Sat Sep 12 21:21:21 2026 rev:30 rq:1377432 version:0.26.0
Changes:
--------
--- /work/SRC/openSUSE:Factory/python-scikit-image/python-scikit-image.changes
2026-05-28 17:29:28.262007119 +0200
+++
/work/SRC/openSUSE:Factory/.python-scikit-image.new.1265/python-scikit-image.changes
2026-09-12 21:25:09.662040819 +0200
@@ -1,0 +2,9 @@
+Fri Sep 11 14:41:51 UTC 2026 - Markéta Machová <[email protected]>
+
+- Add few upstream patches to make tests pass:
+ * scipy118.patch
+ * numpy25.patch
+ * ellipse.patch
+ * scipy-spatial.patch
+
+-------------------------------------------------------------------
New:
----
ellipse.patch
numpy25.patch
scipy-spatial.patch
scipy118.patch
----------(New B)----------
New: * numpy25.patch
* ellipse.patch
* scipy-spatial.patch
New: * scipy118.patch
* numpy25.patch
* ellipse.patch
New: * ellipse.patch
* scipy-spatial.patch
New:- Add few upstream patches to make tests pass:
* scipy118.patch
* numpy25.patch
----------(New E)----------
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Other differences:
------------------
++++++ python-scikit-image.spec ++++++
--- /var/tmp/diff_new_pack.BccSG4/_old 2026-09-12 21:25:11.270108311 +0200
+++ /var/tmp/diff_new_pack.BccSG4/_new 2026-09-12 21:25:11.280108731 +0200
@@ -38,11 +38,19 @@
Source0:
https://files.pythonhosted.org/packages/source/s/scikit-image/%{srcname}-%{version}.tar.gz
# PATCH-FIX-UPSTREAM Based on gh#scikit-image/scikit-image#8010
Patch0: support-new-pillow.patch
+# PATCH-FIX-UPSTREAM https://github.com/scikit-image/scikit-image/pull/8157
Fix minkowski distanced invocation for SciPy >= 1.18
+Patch1: scipy118.patch
+# PATCH-FIX-UPSTREAM https://github.com/scikit-image/scikit-image/pull/8020
Avoid deprecated assign to ndarray.shape
+Patch2: numpy25.patch
+# PATCH-FIX-UPSTREAM https://github.com/scikit-image/scikit-image/pull/8054
MAINT: make ellipse fitting forward compatible
+Patch3: ellipse.patch
+# PATCH-FIX-UPSTREAM
https://github.com/scikit-image/scikit-image/commit/a6a9591dd122d4fe259a5aab881808883797082c
Fix nightlies: update deprecated scipy call, fix underdetermined test
+Patch4: scipy-spatial.patch
BuildRequires: %{python_module Cython >= 3.0.4}
BuildRequires: %{python_module devel >= 3.10}
BuildRequires: %{python_module meson-python >= 0.15}
-BuildRequires: %{python_module numpy-devel >= 1.24}
-BuildRequires: %{python_module packaging >= 21}
+BuildRequires: %{python_module numpy-devel >= 2.1}
+BuildRequires: %{python_module packaging >= 24}
BuildRequires: %{python_module pip}
BuildRequires: %{python_module pythran}
BuildRequires: %{python_module setuptools}
@@ -55,24 +63,24 @@
Requires: python-imageio >= 2.33
Requires: python-lazy-loader >= 0.4
Requires: python-networkx >= 3
-Requires: python-numpy >= 1.24
-Requires: python-packaging >= 21.0
-Requires: python-scipy >= 1.11.4
-Requires: python-tifffile >= 2022.8.12
+Requires: python-numpy >= 2.1
+Requires: python-packaging >= 24.0
+Requires: python-scipy >= 1.15
+Requires: python-tifffile >= 2025.1.10
Requires(post): update-alternatives
Requires(postun): update-alternatives
-Recommends: python-PyWavelets >= 1.6
+Recommends: python-PyWavelets >= 1.7
Recommends: python-QtPy
Recommends: python-SimpleITK
-Recommends: python-astropy >= 5
+Recommends: python-astropy >= 6.1
Recommends: python-cloudpickle >= 1.1.1
-Recommends: python-dask-array >= 2023.2.0
-Recommends: python-matplotlib >= 3.7
+Recommends: python-dask-array >= 2025.1.0
+Recommends: python-matplotlib >= 3.10
Recommends: python-pooch >= 1.6.0
Recommends: python-pyamg >= 5.2
%if %{with test}
-BuildRequires: %{python_module dask-array >= 2023.2.0}
-BuildRequires: %{python_module matplotlib >= 3.7}
+BuildRequires: %{python_module dask-array >= 2025.1.0}
+BuildRequires: %{python_module matplotlib >= 3.10}
BuildRequires: %{python_module numpydoc >= 1.7}
BuildRequires: %{python_module pytest >= 8}
BuildRequires: %{python_module pytest-localserver}
++++++ ellipse.patch ++++++
>From b9b377cb403284954533b4cc2e61543a79e2d04c Mon Sep 17 00:00:00 2001
From: Evgeni Burovski <[email protected]>
Date: Fri, 6 Mar 2026 09:01:52 +0100
Subject: [PATCH] MAINT: make ellipse fitting forward compatible (#8054)
NumPy plans to change it's `linalg.eig` routine to always return complex
results. Currently, it returns either complex or real values,
depending on whether the eigenvalues lie on the real axis or not.
See https://github.com/numpy/numpy/pull/30411
The only effect on scikit-image AFAICS, is in the ellipse estimation
routines, which require that eigenvalues are real. In fact, the story
seems to be somewhat convoluted:
- some datasets produce non-zero imaginary parts, which break
`EllipseModel.fit`,
https://github.com/scikit-image/scikit-image/issues/7013
- the current failure mode is a TypeError from an in-place modulo operation,
`phi %= np.pi`, where `phi` is constructed from eigenvalues/eigenvectors
-
https://github.com/scikit-image/scikit-image/issues/7013#issuecomment-1583203321
asks for a reproducer, and
https://github.com/numpy/numpy/issues/29000#issuecomment-3414690376 has
some discussion of potential fixes/enhancements
This PR makes a minimal fix to make `EllipseModel.fit`: take the real
part of eigenvalues/eigenvectors explicitly, and raise an error if
either of them has non-zero imaginary parts.
---------
Co-authored-by: Stefan van der Walt <[email protected]>
---
src/skimage/measure/fit.py | 11 +++++++++++
1 file changed, 11 insertions(+)
diff --git a/src/skimage/measure/fit.py b/src/skimage/measure/fit.py
index 62aec90f79b..1cc8d678c9d 100644
--- a/src/skimage/measure/fit.py
+++ b/src/skimage/measure/fit.py
@@ -904,6 +904,17 @@ def _estimate(self, data, warn_only=True):
# from this equation [eqn. 28]
eig_vals, eig_vecs = np.linalg.eig(M)
+ # https://github.com/scikit-image/scikit-image/issues/7013
+ if not (np.all(np.isreal(eig_vals)) and np.all(np.isreal(eig_vecs))):
+ raise ValueError(
+ "Uh oh! We expected real eigenvalues and -vectors. "
+ "We've had one report of this issue in the past, but couldn't
reproduce it. "
+ "Please help us fix it by sharing your input data at\n\n"
+ " https://github.com/scikit-image/scikit-image/issues/7013\n";
+ )
+ eig_vals = eig_vals.real
+ eig_vecs = eig_vecs.real
+
# eigenvector must meet constraint 4ac - b^2 to be valid.
cond = 4 * np.multiply(eig_vecs[0, :], eig_vecs[2, :]) - np.power(
eig_vecs[1, :], 2
++++++ numpy25.patch ++++++
>From 7737c0446bb30ca14782b488ce2399c7c752f640 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Lars=20Gr=C3=BCter?= <[email protected]>
Date: Fri, 6 Mar 2026 00:39:28 +0100
Subject: [PATCH] Avoid deprecated assign to ndarray.shape (#8020)
We also had to update our minimum requirements to get everything running
smoothly (certain versions of NumPy didn't have the `copy` flag yet, and once
that version of NumPy becomes the minimum there's a cascade of dependency
updates).
Pyodide now depends on a different version of SciPy than the rest of the
library, since it doesn't yet have SciPy 1.15.
Closes #8019
Closes #8025
---------
Co-authored-by: Stefan van der Walt <[email protected]>
Co-authored-by: Stefan van der Walt <[email protected]>
---
.github/workflows/test-pyodide.yaml | 4 +--
environment.yml | 28 +++++++--------
meson.options | 6 ----
pyproject.toml | 34 ++++++++++---------
requirements/default.txt | 9 ++---
requirements/docs.txt | 10 +++---
requirements/optional.txt | 10 +++---
requirements/optional_free_threaded.txt | 8 ++---
src/meson.build | 7 +---
src/skimage/feature/sift.py | 4 +--
src/skimage/graph/_mcp.pyx | 2 +-
src/skimage/io/_plugins/pil_plugin.py | 2 +-
.../measure/_marching_cubes_lewiner.py | 4 +--
src/skimage/morphology/grayreconstruct.py | 4 ++-
src/skimage/restoration/_rolling_ball_cy.pyx | 4 +--
src/skimage/util/_map_array.py | 2 +-
tools/generate_requirements.py | 4 +++
17 files changed, 70 insertions(+), 72 deletions(-)
delete mode 100644 meson.options
Index: scikit_image-0.26.0/meson.options
===================================================================
--- scikit_image-0.26.0.orig/meson.options
+++ /dev/null
@@ -1,6 +0,0 @@
-option(
- 'include-v2',
- type: 'boolean',
- value: true,
- description: 'Include skimage2 namespace in the built package'
-)
Index: scikit_image-0.26.0/pyproject.toml
===================================================================
--- scikit_image-0.26.0.orig/pyproject.toml
+++ scikit_image-0.26.0/pyproject.toml
@@ -202,6 +203,10 @@ filterwarnings = [
# Pyodide warning coming via threadpoolctl, remove when
# https://github.com/joblib/threadpoolctl/pull/201 is released
"ignore:.*JsProxy\\.as_object_map.*:RuntimeWarning",
+ # Warning caused by matplotlib 3.7.0 because it uses deprecated API of
pyparsing 3.3.1
+
"ignore:.*(parseString|resetCache|enablePackrat|oneOf).*:DeprecationWarning:matplotlib",
+ # tifffile (v2025.12.20) uses deprecated NumPy API
+ "ignore:Setting the shape on a NumPy array:DeprecationWarning:tifffile",
]
norecursedirs = ["io/_plugins"]
@@ -226,7 +231,6 @@ build-verbosity = 0
enable="cpython-freethreading"
[tool.cibuildwheel.config-settings]
-setup-args = "-Dinclude-v2=false"
# Could be overwritten using CIBW_CONFIG_SETTINGS environment variable
[[tool.cibuildwheel.overrides]]
Index: scikit_image-0.26.0/src/meson.build
===================================================================
--- scikit_image-0.26.0.orig/src/meson.build
+++ scikit_image-0.26.0/src/meson.build
@@ -1,7 +1,2 @@
-include_v2 = get_option('include-v2')
-
subdir('skimage')
-
-if include_v2
- subdir('skimage2')
-endif
+subdir('skimage2')
Index: scikit_image-0.26.0/src/skimage/feature/sift.py
===================================================================
--- scikit_image-0.26.0.orig/src/skimage/feature/sift.py
+++ scikit_image-0.26.0/src/skimage/feature/sift.py
@@ -304,7 +304,7 @@ class SIFT(FeatureDetector, DescriptorEx
mode='reflect',
)
- # Eq. 10: sigmas.shape = (n_octaves, n_scales + 3).
+ # Eq. 10: sigmas.reshape((n_octaves, n_scales + 3), copy=False).
# The three extra scales are:
# One for the differences needed for DoG and two auxiliary
# images (one at either end) for peak_local_max with exclude
@@ -317,7 +317,7 @@ class SIFT(FeatureDetector, DescriptorEx
self.scalespace_sigmas = sigmas
# Eq. 7: Gaussian smoothing depends on difference with previous sigma
- # gaussian_sigmas.shape = (n_octaves, n_scales + 2)
+ # gaussian_sigmas.reshape((n_octaves, n_scales + 2), copy=False)
var_diff = np.diff(sigmas * sigmas, axis=1)
gaussian_sigmas = np.sqrt(var_diff) / self.deltas[:, np.newaxis]
Index: scikit_image-0.26.0/src/skimage/graph/_mcp.pyx
===================================================================
--- scikit_image-0.26.0.orig/src/skimage/graph/_mcp.pyx
+++ scikit_image-0.26.0/src/skimage/graph/_mcp.pyx
@@ -77,7 +77,7 @@ def _offset_edge_map(shape, offsets):
[0, 0, 2, 1]], dtype=int8)
"""
- indices = np.indices(shape) # indices.shape = (n,)+shape
+ indices = np.indices(shape) # indices.reshape((n,) + shape, copy=False)
#get the distance from each index to the upper or lower edge in each dim
pos_edges = (shape - indices.T).T
Index: scikit_image-0.26.0/src/skimage/io/_plugins/pil_plugin.py
===================================================================
--- scikit_image-0.26.0.orig/src/skimage/io/_plugins/pil_plugin.py
+++ scikit_image-0.26.0/src/skimage/io/_plugins/pil_plugin.py
@@ -109,7 +109,7 @@ def pil_to_ndarray(image, dtype=None, im
if 'S' in image.mode:
dtype = dtype.replace('u', 'i')
frame = np.frombuffer(frame.tobytes(), dtype)
- frame.shape = shape[::-1]
+ frame = np.reshape(frame, shape[::-1], copy=False)
else:
frame = np.array(frame, dtype=dtype)
Index: scikit_image-0.26.0/src/skimage/measure/_marching_cubes_lewiner.py
===================================================================
--- scikit_image-0.26.0.orig/src/skimage/measure/_marching_cubes_lewiner.py
+++ scikit_image-0.26.0/src/skimage/measure/_marching_cubes_lewiner.py
@@ -210,7 +210,7 @@ def _marching_cubes_lewiner(
normals = np.fliplr(normals)
# Finishing touches to output
- faces.shape = -1, 3
+ faces = np.reshape(faces, (-1, 3), copy=False)
if gradient_direction == 'descent':
# MC implementation is right-handed, but gradient_direction is
# left-handed
@@ -234,7 +234,7 @@ def _to_array(args):
shape, text = args
byts = base64.decodebytes(text.encode('utf-8'))
ar = np.frombuffer(byts, dtype='int8')
- ar.shape = shape
+ ar = np.reshape(ar, shape, copy=False)
return ar
Index: scikit_image-0.26.0/src/skimage/morphology/grayreconstruct.py
===================================================================
--- scikit_image-0.26.0.orig/src/skimage/morphology/grayreconstruct.py
+++ scikit_image-0.26.0/src/skimage/morphology/grayreconstruct.py
@@ -213,5 +213,7 @@ def reconstruction(seed, mask, method='d
# Reshape reconstructed image to original image shape and remove padding.
rec_img = value_map[value_rank[:image_stride]]
- rec_img.shape = np.array(seed.shape) + (np.array(footprint.shape) - 1)
+ rec_img = np.reshape(
+ rec_img, np.array(seed.shape) + (np.array(footprint.shape) - 1),
copy=False
+ )
return rec_img[inside_slices]
Index: scikit_image-0.26.0/src/skimage/restoration/_rolling_ball_cy.pyx
===================================================================
--- scikit_image-0.26.0.orig/src/skimage/restoration/_rolling_ball_cy.pyx
+++ scikit_image-0.26.0/src/skimage/restoration/_rolling_ball_cy.pyx
@@ -112,7 +112,7 @@ def apply_kernel_nan(DTYPE_FLOAT[::1] im
-------
out_data : ndarray
The array passed into ``out``, reshaped to
- ``out_data.shape = img_shape`` (possibly a view) and filled with the
+ ``out_data.reshape(img_shape, copy=False)`` (possibly a view) and
filled with the
estimated background intensity.
See Also
@@ -196,7 +196,7 @@ def apply_kernel(DTYPE_FLOAT[::1] img no
-------
out_data : ndarray
The array passed into ``out``, reshaped to
- ``out_data.shape = img_shape`` (possibly a view) and filled with the
+ ``out_data.reshape(img_shape, copy=False)`` (possibly a view) and
filled with the
estimated background intensity.
See Also
Index: scikit_image-0.26.0/src/skimage/util/_map_array.py
===================================================================
--- scikit_image-0.26.0.orig/src/skimage/util/_map_array.py
+++ scikit_image-0.26.0/src/skimage/util/_map_array.py
@@ -58,7 +58,7 @@ def map_array(input_arr, input_vals, out
)
try:
out_view = out.view()
- out_view.shape = (-1,) # no-copy reshape/ravel
+ out_view = np.reshape(out_view, (-1,), copy=False)
except AttributeError: # if out strides are not compatible with 0-copy
raise ValueError(
'If out array is provided, it should be either contiguous '
Index: scikit_image-0.26.0/tools/generate_requirements.py
===================================================================
--- scikit_image-0.26.0.orig/tools/generate_requirements.py
+++ scikit_image-0.26.0/tools/generate_requirements.py
@@ -58,6 +58,10 @@ def generate_environment_yml(req_section
lines.append(f" - {dep}")
+ # Strip duplicates
+ if re.split('[>=]', lines[-2])[0] == re.split('[>=]',
lines[-1])[0]:
+ lines = lines[:-1]
+
with open("environment.yml", "w") as f:
f.writelines(f"{line}\n" for line in lines)
++++++ scipy-spatial.patch ++++++
>From a6a9591dd122d4fe259a5aab881808883797082c Mon Sep 17 00:00:00 2001
From: Steven Silvester <[email protected]>
Date: Wed, 13 May 2026 12:48:18 -0500
Subject: [PATCH] Fix nightlies: update deprecated scipy call, fix
underdetermined test
- Replace deprecated usages of `scipy` `distance_matrix` function by
`spatial.distance.cdist`.
- Update `test_polynomial_weighted_estimation` to be robust. Previously had an
under-determined system (third degree polynomial, with only eight data points).
---
src/skimage/measure/fit.py | 1 +
src/skimage/transform/_thin_plate_splines.py | 6 +++---
tests/skimage/transform/test_geometric.py | 12 +++++++-----
3 files changed, 11 insertions(+), 8 deletions(-)
Index: scikit_image-0.26.0/src/skimage/measure/fit.py
===================================================================
--- scikit_image-0.26.0.orig/src/skimage/measure/fit.py
+++ scikit_image-0.26.0/src/skimage/measure/fit.py
@@ -621,6 +621,7 @@ class CircleModel(_BaseModel):
warn_only=warn_only,
)
+ # Compute the Euclidean distances from the center.
center = C[0:2]
# Can remove once SciPy 1.18 is the default
if version.parse(scipy.__version__) >= version.parse('1.18.0dev0'):
Index: scikit_image-0.26.0/src/skimage/transform/_thin_plate_splines.py
===================================================================
--- scikit_image-0.26.0.orig/src/skimage/transform/_thin_plate_splines.py
+++ scikit_image-0.26.0/src/skimage/transform/_thin_plate_splines.py
@@ -1,7 +1,7 @@
from typing import Self
import numpy as np
-from scipy.spatial import distance_matrix
+from scipy.spatial.distance import cdist
from .._shared.utils import check_nD, _deprecate_estimate, FailedEstimation
@@ -180,7 +180,7 @@ class ThinPlateSplineTransform:
self.src = src
n, d = src.shape
- dist = distance_matrix(src, src)
+ dist = cdist(src, src)
K = self._radial_basis_kernel(dist)
P = np.hstack([np.ones((n, 1)), src])
n_plus_3 = n + 3
@@ -197,7 +197,7 @@ class ThinPlateSplineTransform:
def _radial_distance(self, coords):
"""Compute the radial distance between input points and source
points."""
- dists = distance_matrix(coords, self.src)
+ dists = cdist(coords, self.src)
return self._radial_basis_kernel(dists)
def _spline_function(self, coords, radial_dist):
Index: scikit_image-0.26.0/tests/skimage/transform/test_geometric.py
===================================================================
--- scikit_image-0.26.0.orig/tests/skimage/transform/test_geometric.py
+++ scikit_image-0.26.0/tests/skimage/transform/test_geometric.py
@@ -861,10 +861,12 @@ def test_polynomial_estimation():
def test_polynomial_weighted_estimation():
- # Over-determined solution with same points, and unity weights
- tform = estimate_transform('polynomial', SRC, DST, order=10)
+ # Use order=2 so the system is over-determined with 8 points:
+ # A has shape (16, 13), giving a unique least-squares solution.
+ # order=3 would require > 20 rows (i.e. > 10 points) to be over-determined.
+ tform = estimate_transform('polynomial', SRC, DST, order=2)
tform_w = estimate_transform(
- 'polynomial', SRC, DST, order=10, weights=np.ones(SRC.shape[0])
+ 'polynomial', SRC, DST, order=2, weights=np.ones(SRC.shape[0])
)
assert_almost_equal(tform.params, tform_w.params)
@@ -872,12 +874,12 @@ def test_polynomial_weighted_estimation(
# the same result.
point_weights = np.ones(SRC.shape[0] + 1)
point_weights[0] = 1.0e-15
- tform1 = estimate_transform('polynomial', SRC, DST, order=10)
+ tform1 = estimate_transform('polynomial', SRC, DST, order=2)
tform2 = estimate_transform(
'polynomial',
SRC[np.arange(-1, SRC.shape[0]), :],
DST[np.arange(-1, SRC.shape[0]), :],
- order=10,
+ order=2,
weights=point_weights,
)
assert_almost_equal(tform1.params, tform2.params, decimal=4)
++++++ scipy118.patch ++++++
>From 3f8abbeb7fb87669e5d5620f0d4f38379b3e4641 Mon Sep 17 00:00:00 2001
From: Stefan van der Walt <[email protected]>
Date: Wed, 13 May 2026 06:09:09 -0700
Subject: [PATCH] Fix minkowski distanced invocation for SciPy >= 1.18 (#8157)
SciPy now raises a warning for `spatial.minkowski_distance`, need to use
`spatial.distance.minkowski` instead.
Without this fix, we don't build nightlies.
---
TODO.txt | 2 ++
src/skimage/measure/fit.py | 11 ++++++++---
2 files changed, 10 insertions(+), 3 deletions(-)
Index: scikit_image-0.26.0/TODO.txt
===================================================================
--- scikit_image-0.26.0.orig/TODO.txt
+++ scikit_image-0.26.0/TODO.txt
@@ -42,6 +42,8 @@ Other
`scipy.linalg.eigsh` is available everywhere, remove the compatibility logic
in
`skimage/graph/_graph_cut.py::_ncut_relabel` and the `xfail` mark in
`tests/skimage/graph/test_rag.py::test_reproducibility`.
+* Once SciPy 1.18 is minimal required version, remove minkowski
+ distance branching from `src/skimage/measure/fit.py`.
Post numpy 2
------------
Index: scikit_image-0.26.0/src/skimage/measure/fit.py
===================================================================
--- scikit_image-0.26.0.orig/src/skimage/measure/fit.py
+++ scikit_image-0.26.0/src/skimage/measure/fit.py
@@ -5,7 +5,8 @@ from warnings import warn, catch_warning
import numpy as np
from numpy.linalg import inv
-from scipy import optimize, spatial
+from packaging import version
+import scipy
from .._shared.utils import (
_deprecate_estimate,
@@ -621,7 +622,11 @@ class CircleModel(_BaseModel):
)
center = C[0:2]
- distances = spatial.minkowski_distance(center, data)
+ # Can remove once SciPy 1.18 is the default
+ if version.parse(scipy.__version__) >= version.parse('1.18.0dev0'):
+ distances = scipy.spatial.distance.minkowski(center, data)
+ else:
+ distances = scipy.spatial.minkowski_distance(center, data)
r = np.sqrt(np.mean(distances**2))
# Revert normalization and set init params.
@@ -1022,7 +1027,7 @@ class EllipseModel(_BaseModel):
xi = x[i]
yi = y[i]
# faster without Dfun, because of the python overhead
- t, _ = optimize.leastsq(fun, t0[i], args=(xi, yi))
+ t, _ = scipy.optimize.leastsq(fun, t0[i], args=(xi, yi))
residuals[i] = np.sqrt(fun(t, xi, yi))
return residuals
