Merge remote-tracking branch 'upstream/RELEASE_next_patch' into RELEA…

…SE_next_minor

.github/workflows/tests.yml

@@ -40,6 +40,9 @@ jobs:
           - os: ubuntu
             PYTHON_VERSION: '3.10'
             PIP_SELECTOR: '[all, tests, coverage]'
+          - os: ubuntu
+            PYTHON_VERSION: '3.11'
+            PIP_SELECTOR: '[all, tests, coverage]'
 
     steps:
       - uses: actions/checkout@v3.3.0
@@ -54,6 +57,13 @@ jobs:
           python --version
           pip --version
 
+      - name: Install numba rc
+        if: contains(matrix.PYTHON_VERSION, '3.11')
+        # Require for python 3.11 support, remove when numba 0.57 is release
+        shell: bash
+        run: |
+          pip install numba --pre
+
       - name: Install oldest supported version
         if: ${{ matrix.OLDEST_SUPPORTED_VERSION }}
         run: |

conda_environment.yml

@@ -7,7 +7,7 @@ dependencies:
 # dask-core < 2021.3.1 doesn't have fsspec as dependency
 - fsspec
 - h5py
-- imageio
+- imageio <2.28
 - ipyparallel
 - ipython !=8.0.*
 - jinja2

hyperspy/model.py

@@ -281,11 +281,22 @@ def __init__(self):
                 The Model that the event belongs to
             """, arguments=['obj'])
 
+        # The private _binned attribute is created to store temporarily
+        # axes.is_binned or not. This avoids evaluating it during call of
+        # the model function, which is detrimental to the performances of
+        # multifit(). Setting it to None ensures that the existing behaviour
+        # is preserved.
+        self._binned = None
+
     def __hash__(self):
         # This is needed to simulate a hashable object so that PySide does not
         # raise an exception when using windows.connect
         return id(self)
 
+    def __call__(self, non_convolved=False, onlyactive=False, component_list=None, binned=None):
+        """Evaluate the model numerically. Implementation requested in all sub-classes"""
+        raise NotImplementedError
+
     def store(self, name=None):
         """Stores current model in the original signal
 
@@ -942,7 +953,7 @@ def _model2plot(self, axes_manager, out_of_range2nans=True):
     def _model_function(self, param):
         self.p0 = param
         self._fetch_values_from_p0()
-        to_return = self.__call__(non_convolved=False, onlyactive=True)
+        to_return = self.__call__(non_convolved=False, onlyactive=True, binned=self._binned)
         return to_return
 
     @property
@@ -1221,7 +1232,7 @@ def _get_variance(self, only_current=True):
 
     def _calculate_chisq(self):
         variance = self._get_variance()
-        d = self(onlyactive=True).ravel() - self.signal(as_numpy=True)[
+        d = self(onlyactive=True, binned=self._binned).ravel() - self.signal(as_numpy=True)[
             np.where(self.channel_switches)]
         d *= d / (1. * variance)  # d = difference^2 / variance.
         self.chisq.data[self.signal.axes_manager.indices[::-1]] = d.sum()
@@ -1902,6 +1913,10 @@ def multifit(
         maxval = self.axes_manager._get_iterpath_size(masked_elements)
         show_progressbar = show_progressbar and (maxval != 0)
 
+        #The _binned attribute is evaluated only once in the multifit procedure
+        #and stored in an instance variable
+        self._binned = is_binned(self.signal)
+
         if linear_fitting:
             # Check that all non-free parameters don't change accross
             # the navigation dimension. If this is the case, we can fit the
@@ -1993,6 +2008,10 @@ def multifit(
                     para.map['std'] = para.std
                     para.map['is_set'] = True
 
+                # _binned attribute is re-set to None before early return so the
+                # behaviour of future fit() calls is not altered. In future
+                # implementation, a more elegant implementation could be found
+                self._binned = None
                 return
 
         i = 0
@@ -2031,6 +2050,11 @@ def multifit(
             _logger.info(f"Deleting temporary file: {autosave_fn}.npz")
             os.remove(autosave_fn + ".npz")
 
+        #_binned attribute is re-set to None so the behaviour of future fit() calls
+        #is not altered. In future implementation, a more elegant implementation
+        # could be found
+        self._binned = None
+
     multifit.__doc__ %= (SHOW_PROGRESSBAR_ARG)
 
     def save_parameters2file(self, filename):

hyperspy/utils/peakfinders2D.py

@@ -109,9 +109,8 @@ def find_local_max(z, **kwargs):
     z : :py:class:`numpy.ndarray`
         Array of image intensities.
     **kwargs : dict
-        Keyword arguments to be passed to the ``peak_local_max`` method of
-        the ``scikit-image`` library. See its documentation for details
-        https://scikit-image.org/docs/dev/api/skimage.feature.html#peak-local-max
+        Keyword arguments to be passed to the
+        :py:func:`skimage.feature.peak_local_max` function.
 
     Returns
     -------
@@ -457,9 +456,8 @@ def find_peaks_dog(z, min_sigma=1., max_sigma=50., sigma_ratio=1.6,
     z : :py:class:`numpy.ndarray`
         2-d array of intensities
     min_sigma, max_sigma, sigma_ratio, threshold, overlap, exclude_border :
-        Additional parameters to be passed to the algorithm. See `blob_dog`
-        documentation for details:
-        https://scikit-image.org/docs/dev/api/skimage.feature.html#blob-dog
+        Additional parameters to be passed to the
+        :py:func:`skimage.feature.blob_dog` function
 
     Returns
     -------
@@ -502,9 +500,8 @@ def find_peaks_log(z, min_sigma=1., max_sigma=50., num_sigma=10,
     z : :py:class:`numpy.ndarray`
         Array of image intensities.
     min_sigma, max_sigma, num_sigma, threshold, overlap, log_scale, exclude_border :
-        Additional parameters to be passed to the ``blob_log`` method of the
-        ``scikit-image`` library. See its documentation for details:
-        https://scikit-image.org/docs/dev/api/skimage.feature.html#blob-log
+        Additional parameters to be passed to the
+        :py:func:`skimage.feature.blob_log` function.
 
     Returns
     -------

setup.py

@@ -68,7 +68,7 @@
                'pint>=0.10',
                'numexpr',
                'sparse',
-               'imageio',
+               'imageio<2.28',
                'pyyaml',
                # prettytable and ptable are API compatible
                # prettytable is maintained and ptable is an unmaintained fork
@@ -421,6 +421,7 @@ def __exit__(self, type, value, traceback):
             "Programming Language :: Python :: 3.8",
             "Programming Language :: Python :: 3.9",
             "Programming Language :: Python :: 3.10",
+            "Programming Language :: Python :: 3.11",
             "Development Status :: 4 - Beta",
             "Environment :: Console",
             "Intended Audience :: Science/Research",

upcoming_changes/3125.bugfix.rst

@@ -0,0 +1 @@
+Use intersphinx links to fix links to scikit-image documentation

upcoming_changes/3126.enhancements.rst

@@ -0,0 +1 @@
+Improve performance of `model.multifit` by avoiding `axes.is_binned` repeated evaluation

upcoming_changes/3134.maintenance.rst

@@ -0,0 +1 @@
+Add support for python 3.11

upcoming_changes/3138.maintenance.rst

@@ -0,0 +1 @@
+Pin ``imageio`` to <2.28