nipy · effigies · Oct 4, 2024 · Jun 17, 2024 · Jun 17, 2024 · Jun 18, 2024
diff --git a/.github/workflows/coverage.yml b/.github/workflows/coverage.yml
@@ -19,7 +19,7 @@ jobs:
     steps:
       - uses: actions/checkout@v4
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
           allow-prereleases: true
@@ -41,6 +41,8 @@ jobs:
           pwd
           ls -lR ..
       - name: Upload to codecov
-        uses: codecov/codecov-action@v3
+        uses: codecov/codecov-action@v4
         with:
           files: tmp/coverage.xml
+        env:
+          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
diff --git a/.github/workflows/doc-build.yml b/.github/workflows/doc-build.yml
@@ -24,7 +24,7 @@ jobs:
           sudo apt install -y graphviz
       - uses: actions/checkout@v4
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
           allow-prereleases: true

diff --git a/.github/workflows/lint.yml b/.github/workflows/lint.yml
@@ -17,7 +17,7 @@ jobs:
       - uses: actions/checkout@v4
 
       - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
 

diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
@@ -28,7 +28,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     steps:
       - uses: actions/checkout@v4
-      - uses: actions/setup-python@v4
+      - uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python_version }}
           allow-prereleases: true
@@ -47,7 +47,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-      - uses: actions/setup-python@v4
+      - uses: actions/setup-python@v5
         with:
           python-version: "3.12"
       - name: Install

diff --git a/doc/devel/code_discussions/coordmap_notes.rst b/doc/devel/code_discussions/coordmap_notes.rst
@@ -495,8 +495,10 @@ AffineTransform(
                  [  0.,   0.,   1.]])
 )
 
->>> bounding_box(y70, (x_spec[1], z_spec[1]))
-((-92.0, 92.0), (70.0, 70.0), (-70.0, 100.0))
+>>> x_lims, y_lims, z_lims = bounding_box(y70, (x_spec[1], z_spec[1]))
+>>> assert np.all(x_lims == (-92, 92))
+>>> assert np.all(y_lims == (70, 70))
+>>> assert np.all(z_lims == (-70, 100))
 
 Maybe these aren't things that "normal human beings" (to steal a quote from
 Gael) can use, but they're explicit and they are tied to precise mathematical

diff --git a/doc/users/coordinate_map.rst b/doc/users/coordinate_map.rst
@@ -170,8 +170,8 @@ We resample the 'subject' image to the 'atlas image
 True
 >>> normalized_subject_im.coordmap == atlas_im.coordmap
 True
->>> np.all(normalized_subject_im.affine == atlas_im.affine)
-True
+>>> # Normalized image now has atlas affine.
+>>> assert np.all(normalized_subject_im.affine == atlas_im.affine)
 
 ***********************
 Mathematical definition

diff --git a/lib/fff_python_wrapper/fffpy.c b/lib/fff_python_wrapper/fffpy.c
@@ -9,11 +9,7 @@
    because PyArray_API is defined static, in order not to share that symbol
    within the dso. (import_array() asks the pointer value to the python process)
 */
-/*
- * deal with differences in macro return result between Python 2 and 3
- * http://mail.scipy.org/pipermail/numpy-discussion/2010-December/054350.html
- */
-IMP_OUT fffpy_import_array(void) {
+void* fffpy_import_array(void) {
   import_array();
 }
 
@@ -47,7 +43,7 @@ void fff_vector_fetch_using_NumPy(fff_vector* y, const char* x, npy_intp stride,
   PyArrayObject* X = (PyArrayObject*) PyArray_New(&PyArray_Type, 1, dim, type, strides,
 						  (void*)x, itemsize, NPY_BEHAVED, NULL);
   PyArrayObject* Y = (PyArrayObject*) PyArray_SimpleNewFromData(1, dim, NPY_DOUBLE, (void*)y->data);
-  PyArray_CastTo(Y, X);
+  PyArray_CopyInto(Y, X);
   Py_XDECREF(Y);
   Py_XDECREF(X);
   return;
@@ -215,7 +211,7 @@ fff_matrix* fff_matrix_fromPyArray(const PyArrayObject* x)
     dim[1] = dim1;
 
     xd = (PyArrayObject*) PyArray_SimpleNewFromData(2, dim, NPY_DOUBLE, (void*)y->data);
-    PyArray_CastTo(xd, (PyArrayObject*)x);
+    PyArray_CopyInto(xd, (PyArrayObject*)x);
     Py_XDECREF(xd);
   }
 
@@ -527,7 +523,11 @@ fffpy_multi_iterator* fffpy_multi_iterator_new(int narr, int axis, ...)
 
   /* Create new instance */
   thisone = (fffpy_multi_iterator*)malloc(sizeof(fffpy_multi_iterator));
-  multi = PyArray_malloc(sizeof(PyArrayMultiIterObject));
+  /* Static size of PyArrayMultiIterObject.
+   *
+   * https://github.com/numpy/numpy/issues/26765#issuecomment-2391737671
+   */
+  multi = PyArray_malloc(PyArrayMultiIter_Type.tp_basicsize);
   vector = (fff_vector**)malloc(narr*sizeof(fff_vector*));
 
   /* Initialize the PyArrayMultiIterObject instance from the variadic arguments */

diff --git a/lib/fff_python_wrapper/fffpy.h b/lib/fff_python_wrapper/fffpy.h
@@ -31,17 +31,8 @@
    static, in order not to share that symbol within the
    dso. (import_array() asks the pointer value to the python process)
 */
-/*
- * deal with differences in macro return result between Python 2 and 3
- * http://mail.scipy.org/pipermail/numpy-discussion/2010-December/054350.html
- */
-#if PY_MAJOR_VERSION >= 3
-typedef int IMP_OUT;
-#else
-typedef void IMP_OUT;
-#endif
 
-extern IMP_OUT fffpy_import_array(void);
+extern void* fffpy_import_array(void);
 
 /*!
   \brief Convert \c PyArrayObject to \c fff_vector

diff --git a/nipy/algorithms/diagnostics/tsdiffplot.py b/nipy/algorithms/diagnostics/tsdiffplot.py
@@ -6,6 +6,7 @@
 
 import nipy
 
+from ...utils import deprecate_with_doc
 from .timediff import time_slice_diffs
 
 
@@ -76,7 +77,7 @@ def xmax_labels(ax, val, xlabel, ylabel):
     return axes
 
 
-@np.deprecate_with_doc('Please see docstring for alternative code')
+@deprecate_with_doc('please see docstring for alternative code')
 def plot_tsdiffs_image(img, axes=None, show=True):
     ''' Plot time series diagnostics for image
 

diff --git a/nipy/algorithms/graph/graph.py b/nipy/algorithms/graph/graph.py
@@ -291,15 +291,15 @@
     the corresponding WeightedGraph instance
     """
     n = X.shape[0]
-    label = np.arange(n).astype(np.int_)
+    label = np.arange(n).astype(np.intp)
 
-    edges = np.zeros((0, 2)).astype(np.int_)
+    edges = np.zeros((0, 2)).astype(np.intp)
     # upper bound on maxdist**2
     maxdist = 4 * np.sum((X - X[0]) ** 2, 1).max()
     nbcc = n
     while nbcc > 1:
         mindist = maxdist * np.ones(nbcc)
-        link = - np.ones((nbcc, 2)).astype(np.int_)
+        link = - np.ones((nbcc, 2)).astype(np.intp)
 
         # find nearest neighbors
         for n1 in range(n):
@@ -427,8 +427,8 @@
     Dramatically slow for non-sparse graphs
     """
     n = len(lil)
-    visited = np.zeros(n).astype(np.int_)
-    label = - np.ones(n).astype(np.int_)
+    visited = np.zeros(n).astype(np.intp)
+    label = - np.ones(n).astype(np.intp)
     k = 0
     while (visited == 0).any():
         front = [np.argmin(visited)]
@@ -500,7 +500,7 @@
         i, j, d = create_edges(lxyz, n18, 2, i, j, d)
     if k == 26:
         i, j, d = create_edges(lxyz, n26, 3, i, j, d)
-    i, j = i.astype(np.int_), j.astype(np.int_)
+    i, j = i.astype(np.intp), j.astype(np.intp)
 
     # reorder the edges to have a more standard order
     order = np.argsort(i + j * (len(i) + 1))
@@ -515,7 +515,7 @@
 
     Parameters
     ----------
-    xyz: array of shape (nsamples, 3) and type np.int_,
+    xyz: array of shape (nsamples, 3) and type np.intp,
     k = 18: the number of neighbours considered. (6, 18 or 26)
 
     Returns
@@ -617,7 +617,7 @@
 
         Parameters
         ----------
-        xyz: array of shape (self.V, 3) and type np.int_,
+        xyz: array of shape (self.V, 3) and type np.intp,
         k = 18: the number of neighbours considered. (6, 18 or 26)
 
         Returns
@@ -637,7 +637,7 @@
             raise TypeError('Creating graph from grid failed. '\
                 'Maybe the grid is too big')
         self.E = np.size(i)
-        self.edges = np.zeros((self.E, 2), np.int_)
+        self.edges = np.zeros((self.E, 2), np.intp)
         self.edges[:, 0] = i
         self.edges[:, 1] = j
         self.weights = np.array(d)
@@ -719,18 +719,18 @@
         weights: array of shape(self.E), concatenated list of weights
         """
         order = np.argsort(self.edges[:, 0] * float(self.V) + self.edges[:, 1])
-        neighb = self.edges[order, 1].astype(np.int_)
+        neighb = self.edges[order, 1].astype(np.intp)
         weights = self.weights[order]
         degree, _ = self.degrees()
-        idx = np.hstack((0, np.cumsum(degree))).astype(np.int_)
+        idx = np.hstack((0, np.cumsum(degree))).astype(np.intp)
         return idx, neighb, weights
 
     def floyd(self, seed=None):
         """ Compute all the geodesic distances starting from seeds
 
         Parameters
         ----------
-        seed= None: array of shape (nbseed), type np.int_
+        seed: None or array of shape (nbseed), type np.intp
              vertex indexes from which the distances are computed
              if seed==None, then every edge is a seed point
 
@@ -880,7 +880,7 @@
 
         Parameters
         ----------
-        seed: array of shape (nseeds), type (np.int_),
+        seed: array of shape (nseeds), type (np.intp),
               vertices from which the cells are built
 
         Returns
@@ -896,7 +896,7 @@
         except:
             raise ValueError('undefined weights')
         dist, active = np.inf * np.ones(self.V), np.ones(self.V)
-        label = - np.ones(self.V, np.int_)
+        label = - np.ones(self.V, np.intp)
         idx, neighb, weight = self.compact_neighb()
         dist[seed] = 0
         label[seed] = np.arange(len(seed))
@@ -930,7 +930,7 @@
 
         Returns
         -------
-        cliques: array of shape (self.V), type (np.int_)
+        cliques: array of shape (self.V), type (np.intp)
           labelling of the vertices according to the clique they belong to
         """
         if (self.weights < 0).any():
@@ -1034,7 +1034,7 @@
         k = self.cc().max() + 1
         E = 2 * self.V - 2
         V = self.V
-        Kedges = np.zeros((E, 2)).astype(np.int_)
+        Kedges = np.zeros((E, 2)).astype(np.intp)
         Kweights = np.zeros(E)
         iw = np.argsort(self.weights)
         label = np.arange(V)

diff --git a/nipy/algorithms/registration/cubic_spline.c b/nipy/algorithms/registration/cubic_spline.c
@@ -199,7 +199,7 @@ void cubic_spline_transform(PyArrayObject* res, const PyArrayObject* src)
   unsigned int axis, aux=0, dimmax=0;
 
   /* Copy src into res */
-  PyArray_CastTo(res, (PyArrayObject*)src);
+  PyArray_CopyInto(res, (PyArrayObject*)src);
 
   /* Compute the maximum array dimension over axes */
   for(axis=0; axis<PyArray_NDIM(res); axis++) {

diff --git a/nipy/algorithms/registration/histogram_registration.py b/nipy/algorithms/registration/histogram_registration.py
@@ -14,7 +14,7 @@
 from .optimizer import configure_optimizer
 from .similarity_measures import similarity_measures as _sms
 
-MAX_INT = np.iinfo(np.int_).max
+MAX_INTC = np.iinfo(np.intc).max
 
 # Module globals
 VERBOSE = True  # enables online print statements
@@ -41,7 +41,8 @@ def __init__(self, from_img, to_img,
                  from_bins=256, to_bins=None,
                  from_mask=None, to_mask=None,
                  similarity='crl1', interp='pv',
-                 smooth=0, renormalize=False, dist=None):
+                 smooth=0, renormalize=False, dist=None,
+                 rng=None):
         """
         Creates a new histogram registration object.
 
@@ -77,6 +78,8 @@ def __init__(self, from_img, to_img,
          Standard deviation in millimeters of an isotropic Gaussian
          kernel used to smooth the `To` image. If 0, no smoothing is
          applied.
+        rng : None :class:`numpy.random.Generator`
+         Random number generator.
         """
         # Function assumes xyx_affine for inputs
         from_img = as_xyz_image(from_img)
@@ -125,6 +128,7 @@ def __init__(self, from_img, to_img,
         # Set default registration parameters
         self._set_interp(interp)
         self._set_similarity(similarity, renormalize=renormalize, dist=dist)
+        self.rng = np.random.default_rng() if rng is None else rng
 
     def _get_interp(self):
         return list(interp_methods.keys())[\
@@ -306,7 +310,7 @@ def _eval(self, Tv):
         trans_vox_coords = Tv.apply(self._vox_coords)
         interp = self._interp
         if self._interp < 0:
-            interp = - np.random.randint(MAX_INT)
+            interp = -self.rng.integers(MAX_INTC)
         _joint_histogram(self._joint_hist,
                          self._from_data.flat,  # array iterator
                          self._to_data,

diff --git a/nipy/algorithms/statistics/formula/formulae.py b/nipy/algorithms/statistics/formula/formulae.py
@@ -123,14 +123,14 @@
 from nipy.algorithms.utils.matrices import full_rank, matrix_rank
 
 # Legacy repr printing from numpy.
-from nipy.utils import VisibleDeprecationWarning, _NoValue
+from nipy.utils import VisibleDeprecationWarning, _NoValue, deprecate_with_doc
 
 
 def _to_str(s):
     return s.decode('latin1') if isinstance(s, bytes) else str(s)
 
 
-@np.deprecate(message = "Please use sympy.Dummy instead of this function")
+@deprecate_with_doc("please use sympy.Dummy instead")
 def make_dummy(name):
     """ Make dummy variable of given name
 

diff --git a/nipy/algorithms/statistics/formula/tests/test_formula.py b/nipy/algorithms/statistics/formula/tests/test_formula.py
@@ -9,7 +9,6 @@
 import numpy as np
 import pytest
 import sympy
-from numpy.core.records import fromrecords
 from numpy.testing import assert_almost_equal, assert_array_equal
 from sympy.utilities.lambdify import implemented_function
 
@@ -219,6 +218,7 @@ def test_make_recarray():
     # Test make_array
     # From list / sequence
     # 2D case
+    fromrecords = np.rec.fromrecords
     data_2d = [(3, 4), (4, 6), (7, 9)]
     m = F.make_recarray(data_2d, 'wv', [np.float64, np.int_])
     assert_starr_equal(m, fromrecords(