Merge branch 'main' into 1.0.0_alpha

.ci/azure/deploy.yml

@@ -49,9 +49,9 @@ jobs:
 
     - bash: |
         # Update latest symlink
-        cd discretize-docs
-        rm -f en/latest
-        ln -s "en/$BRANCH_NAME" en/latest
+        cd discretize-docs/en
+        rm -f latest
+        ln -s "$BRANCH_NAME" latest
       displayName: Point Latest to tag
       condition: eq(variables.IS_TAG, true)
 

.github/workflows/build_distributions.yml

@@ -18,13 +18,6 @@ jobs:
 
       - name: Build wheels
         uses: pypa/[email protected]
-        # env:
-        #   CIBW_SOME_OPTION: value
-        #    ...
-        # with:
-        #   package-dir: .
-        #   output-dir: wheelhouse
-        #   config-file: "{package}/pyproject.toml"
 
       - uses: actions/upload-artifact@v4
         with:
@@ -63,5 +56,8 @@ jobs:
           merge-multiple: true
 
       - uses: pypa/gh-action-pypi-publish@release/v1
-        # with:
-        # To test: repository-url: https://test.pypi.org/legacy/
+        with:
+          user: __token__
+          password: ${{ secrets.PYPI_API_TOKEN }}
+          skip-existing: true
+          packages-dir: ./dist/

README.rst

@@ -61,24 +61,25 @@ Currently, discretize supports:
 
 Installing
 ^^^^^^^^^^
-**discretize** is on conda-forge
+**discretize** is on conda-forge, and is the recommended installation method.
 
 .. code:: shell
 
     conda install -c conda-forge discretize
 
-**discretize** is on pypi
+Prebuilt wheels of **discretize** are on pypi for most platforms
 
 .. code:: shell
 
     pip install discretize
 
-To install from source
+To install from source, note this requires a `c++` compiler supporting the `c++17` standard.
 
 .. code:: shell
 
     git clone https://github.com/simpeg/discretize.git
-    python setup.py install
+    cd discretize
+    pip install .
 
 Citing discretize
 ^^^^^^^^^^^^^^^^^

discretize/base/base_tensor_mesh.py

@@ -715,6 +715,7 @@ def _get_interpolation_matrix(
                 raise ValueError("Points outside of mesh")
         else:
             indZeros = np.logical_not(self.is_inside(loc))
+            loc = loc.copy()
             loc[indZeros, :] = np.array([v.mean() for v in self.get_tensor("CC")])
 
         location_type = self._parse_location_type(location_type)

discretize/mixins/mpl_mod.py

@@ -450,7 +450,7 @@ def plot_slice(
         the given normal.
 
         >>> M = discretize.TensorMesh([32, 32, 32])
-        >>> v = discretize.utils.random_model(M.vnC, seed=789).reshape(-1, order='F')
+        >>> v = discretize.utils.random_model(M.vnC, random_seed=789).reshape(-1, order='F')
         >>> x_slice, y_slice, z_slice = 0.75, 0.25, 0.9
         >>> plt.figure(figsize=(7.5, 3))
         >>> ax = plt.subplot(131)

discretize/tree_mesh.py

@@ -1,5 +1,7 @@
 """Module containing the TreeMesh implementation."""
 
+import warnings
+
 #      ___          ___       ___          ___          ___          ___
 #     /\  \        /\  \     /\  \        /\  \        /\  \        /\  \
 #    /::\  \      /::\  \    \:\  \      /::\  \      /::\  \      /::\  \
@@ -168,7 +170,7 @@ class TreeMesh(
 
     diagonal_balance : bool, optional
         Whether to balance cells along the diagonal of the tree during construction.
-        This will effect all calls to refine the tree.
+        This will affect all calls to refine the tree.
 
     Examples
     --------
@@ -232,9 +234,20 @@ class TreeMesh(
     _items = {"h", "origin", "cell_state"}
 
     # inheriting stuff from BaseTensorMesh that isn't defined in _QuadTree
-    def __init__(self, h=None, origin=None, diagonal_balance=False, **kwargs):
+    def __init__(self, h=None, origin=None, diagonal_balance=None, **kwargs):
         if "x0" in kwargs:
             origin = kwargs.pop("x0")
+
+        if diagonal_balance is None:
+            diagonal_balance = False
+            warnings.warn(
+                "In discretize v1.0 the TreeMesh will change the default value of "
+                "diagonal_balance to True, which will likely slightly change meshes you have"
+                "previously created. If you need to keep the current behavoir, explicitly set "
+                "diagonal_balance=False.",
+                FutureWarning,
+                stacklevel=2,
+            )
         super().__init__(h=h, origin=origin, diagonal_balance=diagonal_balance)
 
         cell_state = kwargs.pop("cell_state", None)
@@ -925,7 +938,7 @@ def face_z_divergence(self):  # NOQA D102
 
     def point2index(self, locs):  # NOQA D102
         # Documentation inherited from discretize.base.BaseMesh
-        return self.get_containing_cell_indexes(locs)
+        return self.get_containing_cells(locs)
 
     def cell_levels_by_index(self, indices):
         """Fast function to return a list of levels for the given cell indices.

discretize/utils/mesh_utils.py

@@ -13,7 +13,9 @@
 num_types = [int, float]
 
 
-def random_model(shape, seed=None, anisotropy=None, its=100, bounds=None):
+def random_model(
+    shape, random_seed=None, anisotropy=None, its=100, bounds=None, seed=None
+):
     """Create random tensor model.
 
     Creates a random tensor model by convolving a kernel function with a
@@ -28,7 +30,7 @@ def random_model(shape, seed=None, anisotropy=None, its=100, bounds=None):
     ----------
     shape : (dim) tuple of int
         shape of the model.
-    seed : numpy.random.Generator, int, optional
+    random_seed : numpy.random.Generator, int, optional
         pick which model to produce, prints the seed if you don't choose
     anisotropy : numpy.ndarray, optional
         this is the kernel that is convolved with the model
@@ -55,7 +57,7 @@ def random_model(shape, seed=None, anisotropy=None, its=100, bounds=None):
     >>> vmin, vmax = 0., 1.
     >>> mesh = TensorMesh([h, h])
 
-    >>> model = random_model(mesh.shape_cells, seed=4, bounds=[vmin, vmax])
+    >>> model = random_model(mesh.shape_cells, random_seed=4, bounds=[vmin, vmax])
 
     >>> fig = plt.figure(figsize=(5, 4))
     >>> ax = plt.subplot(111)
@@ -67,8 +69,17 @@ def random_model(shape, seed=None, anisotropy=None, its=100, bounds=None):
     if bounds is None:
         bounds = [0, 1]
 
-    rng = np.random.default_rng(seed)
-    if seed is None:
+    if seed is not None:
+        warnings.warn(
+            "Deprecated in version 0.11.0. The `seed` keyword argument has been renamed to `random_seed` "
+            "for consistency across the package. Please update your code to use the new keyword argument.",
+            FutureWarning,
+            stacklevel=2,
+        )
+        random_seed = seed
+
+    rng = np.random.default_rng(random_seed)
+    if random_seed is None:
         print("Using a seed of: ", rng.bit_generator.seed_seq)
 
     if type(shape) in num_types:

docs/_static/versions.json

@@ -4,10 +4,15 @@
         "url": "https://discretize.simpeg.xyz/en/main/"
     },
     {
-        "name": "0.10.0 (stable)",
-        "version": "v0.10.0",
-        "url": "https://discretize.simpeg.xyz/en/v0.10.0/",
+        "name": "0.11.0 (stable)",
+        "version": "v0.11.0",
+        "url": "https://discretize.simpeg.xyz/en/v0.11.0/",
         "preferred": true
+    },
+    {
+        "name": "0.10.0",
+        "version": "v0.10.0",
+        "url": "https://discretize.simpeg.xyz/en/v0.10.0/"
     }
 ]
 

docs/conf.py

@@ -257,7 +257,7 @@ def linkcode_resolve(domain, info):
     "icon_links": [
         {
             "name": "GitHub",
-            "url": "https://github.com/simpeg/simpeg",
+            "url": "https://github.com/simpeg/discretize",
             "icon": "fab fa-github",
         },
         {

docs/release/0.11.0-notes.rst

@@ -0,0 +1,89 @@
+.. currentmodule:: discretize
+
+.. _0.11.0_notes:
+
+===================================
+``discretize`` 0.11.0 Release Notes
+===================================
+
+October 24, 2024
+
+This minor release contains many bugfixes and updates related to new package builds.
+
+Numpy 2
+-------
+`discretize` now fully supports `numpy` 2! It is both built against and tested against `numpy` 2.0. It still
+has a minimum required runtime of `numpy` 1.22 though, as building against numpy 2.0 emits ABI compatible calls for
+older numpy versions.
+
+Of note to developers, we now require `numpy` 2.0 for building as it makes use of the `numpy-config` tool to locate
+the `numpy` include directory.
+
+Python versions
+---------------
+`discretize` has bumped its minimum supported `python` version to 3.10, and is tested against versions 3.10-3.13. In the
+future we intended to stay in line with the minimum `python` version supported by the most recent `numpy` release.
+
+
+Random Generators
+-----------------
+`discretize` and its testing utilities now make use of ``numpy.random.RandomGenerator`` to make draws from random
+number generators instead of the deprecated ``numpy.random.rand`` functions. These functions now support a new keyword
+argument `random_seed` :
+
+* :func:``discretize.tests.setup_mesh`` (only used when ``"random" in mesh_type``)
+* :func:``discretize.tests.check_derivative``  (only used when ``dx=None``)
+* :func:``discretize.tests.assert_isadjoint``
+* :func:``discretize.tests.OrderTest.orderTest``  (only used when ``"random" in mesh_type``)
+* :func:``discretize.utils.random_model``
+
+Maintainers of downstream packages should explicitly set seeded generators when using these methods for testing
+purposess to ensure reproducibility.
+
+
+Cell Bounds
+-----------
+:class:``discretize.TensorMesh`` and :class:``discretize.TreeMesh`` now have a ``cell_bounds`` property that returns the
+``(x_min, x_max, y_min, y_max, z_min, z_max)`` of every cell in the mesh at once. Also now the
+:class:``discretize.tree_mesh.TreeCell`` has a corresponding ``bounds`` property.
+
+
+``TreeMesh`` updates
+--------------------
+You can now query a :class:``discretize.TreeMesh`` for cells contained in the same geometric primitives that are supported
+for refining. In addition there is a new :func:``discretize.TreeMesh.refine_plane`` method for refining along a plane.
+
+
+Contributors
+============
+
+* @jcapriot
+* @santisoler
+* @prisae
+* @xiaolongw1223
+* @lheagy
+* @omid-b
+
+Pull requests
+=============
+
+* `#347 <https://github.com/simpeg/discretize/pull/347>`__: Replace deprecated Numpy's `product` by `prod`
+* `#351 <https://github.com/simpeg/discretize/pull/351>`__: Replace Slack links for Mattermost links
+* `#353 <https://github.com/simpeg/discretize/pull/353>`__: Fix typo in tutorials
+* `#354 <https://github.com/simpeg/discretize/pull/354>`__: Update year in LICENSE
+* `#356 <https://github.com/simpeg/discretize/pull/356>`__: Expose TreeMesh geometric intersections used for refine functions.
+* `#358 <https://github.com/simpeg/discretize/pull/358>`__: Replace hanging CurviMesh in docstring for CurvilinearMesh
+* `#360 <https://github.com/simpeg/discretize/pull/360>`__: Update use of `numpy`'s random number generators.
+* `#364 <https://github.com/simpeg/discretize/pull/364>`__: Fix slicer re #363
+* `#366 <https://github.com/simpeg/discretize/pull/366>`__: Add `TensorMesh.cell_bounds` property
+* `#367 <https://github.com/simpeg/discretize/pull/367>`__: Add `TreeCell.bounds` and `TreeMesh.cell_bounds` methods
+* `#368 <https://github.com/simpeg/discretize/pull/368>`__: Set minimum to Python 3.10 (and general CI Maintenance)
+* `#371 <https://github.com/simpeg/discretize/pull/371>`__: Add version switcher to discretize docs
+* `#372 <https://github.com/simpeg/discretize/pull/372>`__: Deploy docs to a new folder named after their tagged version
+* `#373 <https://github.com/simpeg/discretize/pull/373>`__: display dev doc banner
+* `#374 <https://github.com/simpeg/discretize/pull/374>`__: Bump pydata_sphinx_theme version to 0.15.4
+* `#375 <https://github.com/simpeg/discretize/pull/375>`__: Fix caching of internal projection matrices
+* `#376 <https://github.com/simpeg/discretize/pull/376>`__: Fix macos-latest build
+* `#379 <https://github.com/simpeg/discretize/pull/379>`__: Numpy2.0 updates
+* `#380 <https://github.com/simpeg/discretize/pull/380>`__: Create build_distributions.yml
+* `#381 <https://github.com/simpeg/discretize/pull/381>`__: 0.11.0 Release Notes

docs/release/index.rst

@@ -4,6 +4,7 @@ Release Notes
 .. toctree::
    :maxdepth: 2
 
+   0.11.0  <0.11.0-notes>
    0.10.0  <0.10.0-notes>
    0.9.0  <0.9.0-notes>
    0.8.3  <0.8.3-notes>

examples/plot_image.py

@@ -11,7 +11,7 @@
 
 def run(plotIt=True):
     M = discretize.TensorMesh([32, 32])
-    v = discretize.utils.random_model(M.vnC, seed=789)
+    v = discretize.utils.random_model(M.vnC, random_seed=789)
     v = discretize.utils.mkvc(v)
 
     O = discretize.TreeMesh([32, 32])

tests/tree/test_tree.py

@@ -573,5 +573,22 @@ def test_insert_point(self):
         self.assertEqual(mesh1.nC, mesh2.nC)
 
 
+@pytest.mark.parametrize("dim", [2, 3])
+def test_cell_locator(dim):
+    mesh = discretize.TreeMesh((16, 16, 16)[:dim])
+    mesh.insert_cells([0.5, 0.5, 0.5][:dim], levels=-1)
+
+    query_point = [0.21, 0.42, 0.22][:dim]
+    identified_cell = mesh.point2index(query_point)
+    found = False
+    for i, cell in enumerate(mesh):
+        bounds = cell.bounds.reshape((-1, 2))
+
+        if np.all((bounds[:, 0] <= query_point) & (bounds[:, 1] >= query_point)):
+            found = True
+            assert i == identified_cell
+    assert found
+
+
 if __name__ == "__main__":
     unittest.main()