add numpy 2 support

.github/workflows/main.yml

@@ -58,9 +58,7 @@ jobs:
       matrix:
         cfg:
         - { os: ubuntu-latest, arch: x86_64 }
-        - { os: ubuntu-latest, arch: i686 }
         - { os: windows-latest, arch: AMD64 }
-        - { os: windows-latest, arch: x86 }
         - { os: macos-latest, arch: x86_64 }
         - { os: macos-latest, arch: arm64 }
         - { os: macos-latest, arch: universal2 }
@@ -71,7 +69,7 @@ jobs:
           fetch-depth: '0'
 
       - name: Build wheels
-        uses: pypa/cibuildwheel@v2.16.2
+        uses: pypa/cibuildwheel@v2.17.0
         env:
           CIBW_ARCHS: ${{ matrix.cfg.arch }}
         with:
@@ -82,36 +80,51 @@ jobs:
           path: ./dist/*.whl
 
   build_sdist:
-    name: sdist on ${{ matrix.os }} with py ${{ matrix.python-version }}
+    name: sdist on ${{ matrix.os }} with py ${{ matrix.ver.py }} numpy${{ matrix.ver.np }} scipy${{ matrix.ver.sp }}
     runs-on: ${{ matrix.os }}
     strategy:
       fail-fast: false
       matrix:
         os: [ubuntu-latest, windows-latest, macos-latest]
-        python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
-
+        # https://github.com/scipy/oldest-supported-numpy/blob/main/setup.cfg
+        ver:
+          - {py: '3.8', np: '==1.20.0', sp: '==1.5.4'}
+          - {py: '3.9', np: '==1.20.0', sp: '==1.5.4'}
+          - {py: '3.10', np: '==1.21.6', sp: '==1.7.2'}
+          - {py: '3.11', np: '==1.23.2', sp: '==1.9.2'}
+          - {py: '3.12', np: '==1.26.2', sp: '==1.11.2'}
+          - {py: '3.12', np: '>=2.0.0rc1', sp: '>=1.13.0'}
     steps:
       - uses: actions/checkout@v2
         with:
           fetch-depth: '0'
 
-      - name: Set up Python ${{ matrix.python-version }}
+      - name: Set up Python ${{ matrix.ver.py }}
         uses: actions/setup-python@v2
         with:
-          python-version: ${{ matrix.python-version }}
+          python-version: ${{ matrix.ver.py }}
 
       - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install build "coveralls>=3.0.0"
+
+      - name: bleeding edge
+        if: matrix.ver.np == '>=2.0.0rc1'
+        run: |
+          python -m pip install git+https://github.com/dfm/emcee.git
+
+      - name: Install GSTools
         env:
           GSTOOLS_BUILD_PARALLEL: 1
         run: |
-          python -m pip install --upgrade pip
-          pip install build coveralls>=3.0.0
           pip install -v --editable .[test]
 
       - name: Run tests
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
         run: |
+          pip install "numpy${{ matrix.ver.np }}" "scipy${{ matrix.ver.sp }}"
           python -m pytest --cov gstools --cov-report term-missing -v tests/
           python -m coveralls --service=github
 
@@ -121,7 +134,7 @@ jobs:
           python -m build --sdist --outdir dist .
 
       - uses: actions/upload-artifact@v2
-        if: matrix.os == 'ubuntu-latest' && matrix.python-version == '3.9'
+        if: matrix.os == 'ubuntu-latest' && matrix.ver.py == '3.9'
         with:
           path: dist/*.tar.gz
 

.gitignore

@@ -117,6 +117,7 @@ src/gstools/_version.py
 # generated docs
 docs/source/examples/
 docs/source/api/
+docs/source/sg_execution_times.rst
 
 # other settings
 .vscode/

CHANGELOG.md

@@ -2,6 +2,25 @@
 
 All notable changes to **GSTools** will be documented in this file.
 
+## [Unreleased] - ?
+
+### Enhancements
+
+- added global variable `config.NUM_THREADS` to select number of threads for parallel computation ([#336](https://github.com/GeoStat-Framework/GSTools/pull/336))
+- prepare numpy 2 support ([#340](https://github.com/GeoStat-Framework/GSTools/pull/340))
+  - numpy 2.0.0rc1 for building extensions (for Python 3.9 and above)
+  - check multiple numpy and scipy versions in CI
+  - fixed minimal versions for numpy
+  - use `np.asarray` everywhere with `np.atleast_(n)d`
+  - fix long/longlong integer issue in cython on windows by always using 64bit integers
+
+### Bugfixes
+- build docs with latest sphinx version ([#340](https://github.com/GeoStat-Framework/GSTools/pull/340))
+
+### Changes
+- require pyvista 0.40 at least ([#340](https://github.com/GeoStat-Framework/GSTools/pull/340))
+
+
 ## [1.5.1] - Nifty Neon - 2023-11
 
 ### Enhancements

README.md

@@ -345,7 +345,7 @@ in memory for immediate 3D plotting in Python.
 
 ## Requirements:
 
-- [NumPy >= 1.14.5](https://www.numpy.org)
+- [NumPy >= 1.20.0](https://www.numpy.org)
 - [SciPy >= 1.1.0](https://www.scipy.org/scipylib)
 - [hankel >= 1.0.0](https://github.com/steven-murray/hankel)
 - [emcee >= 3.0.0](https://github.com/dfm/emcee)
@@ -366,7 +366,7 @@ You can contact us via <info@geostat-framework.org>.
 
 ## License
 
-[LGPLv3][license_link] © 2018-2021
+[LGPLv3][license_link] © 2018-2024
 
 [pip_link]: https://pypi.org/project/gstools
 [conda_link]: https://docs.conda.io/en/latest/miniconda.html

docs/source/conf.py

@@ -259,10 +259,9 @@ def setup(app):
 # Example configuration for intersphinx: refer to the Python standard library.
 intersphinx_mapping = {
     "Python": ("https://docs.python.org/", None),
-    "NumPy": ("http://docs.scipy.org/doc/numpy/", None),
-    "SciPy": ("http://docs.scipy.org/doc/scipy/reference", None),
-    "matplotlib": ("http://matplotlib.org", None),
-    "Sphinx": ("http://www.sphinx-doc.org/en/stable/", None),
+    "NumPy": ("https://numpy.org/doc/stable/", None),
+    "SciPy": ("https://docs.scipy.org/doc/scipy/", None),
+    "matplotlib": ("https://matplotlib.org/stable/", None),
     "hankel": ("https://hankel.readthedocs.io/en/latest/", None),
     "emcee": ("https://emcee.readthedocs.io/en/latest/", None),
 }

docs/source/index.rst

@@ -414,7 +414,7 @@ in memory for immediate 3D plotting in Python.
 Requirements
 ============
 
-- `Numpy >= 1.14.5 <http://www.numpy.org>`_
+- `NumPy >= 1.20.0 <http://www.numpy.org>`_
 - `SciPy >= 1.1.0 <http://www.scipy.org>`_
 - `hankel >= 1.0.0 <https://github.com/steven-murray/hankel>`_
 - `emcee >= 3.0.0 <https://github.com/dfm/emcee>`_

examples/01_random_field/06_pyvista_support.py

@@ -21,8 +21,8 @@
 # We create a structured grid with PyVista containing 50 segments on all three
 # axes each with a length of 2 (whatever unit).
 
-dim, spacing = (50, 50, 50), (2, 2, 2)
-grid = pv.UniformGrid(dim, spacing)
+dims, spacing = (50, 50, 50), (2, 2, 2)
+grid = pv.ImageData(dimensions=dims, spacing=spacing)
 
 ###############################################################################
 # Now we set up the SRF class as always. We'll use an anisotropic model.

examples/04_vector_field/01_3d_vector_field.py

@@ -17,7 +17,7 @@
 ###############################################################################
 # create a uniform grid with PyVista
 dims, spacing, origin = (40, 30, 10), (1, 1, 1), (-10, 0, 0)
-mesh = pv.UniformGrid(dims=dims, spacing=spacing, origin=origin)
+mesh = pv.ImageData(dimensions=dims, spacing=spacing, origin=origin)
 
 ###############################################################################
 # create an incompressible random 3d velocity field on the given mesh

pyproject.toml

@@ -2,8 +2,9 @@
 requires = [
     "setuptools>=64",
     "setuptools_scm>=7",
-    "oldest-supported-numpy",
-    "Cython>=3.0",
+    "numpy>=2.0.0rc1,<2.3; python_version >= '3.9'",
+    "oldest-supported-numpy; python_version < '3.9'",
+    "Cython>=3.0.10,<3.1.0",
     "extension-helpers>=1",
 ]
 build-backend = "setuptools.build_meta"
@@ -48,7 +49,7 @@ dependencies = [
     "emcee>=3.0.0",
     "hankel>=1.0.0",
     "meshio>=5.1.0",
-    "numpy>=1.14.5",
+    "numpy>=1.20.0",
     "pyevtk>=1.1.1",
     "scipy>=1.1.0",
 ]
@@ -60,20 +61,20 @@ doc = [
     "meshzoo>=0.7",
     "numpydoc>=1.1",
     "pykrige>=1.5,<2",
-    "pyvista>=0.29",
-    "sphinx>=4",
+    "pyvista>=0.40",
+    "sphinx>=7",
     "sphinx-gallery>=0.8",
-    "sphinx-rtd-theme>=1,<1.1",
+    "sphinx-rtd-theme>=2",
     "sphinxcontrib-youtube>=1.1",
 ]
 plotting = [
     "matplotlib>=3",
-    "pyvista>=0.29",
+    "pyvista>=0.40",
 ]
 rust = ["gstools_core>=0.2.0,<1"]
 test = ["pytest-cov>=3"]
 lint = [
-    "black",
+    "black>=23,<24",
     "pylint",
     "isort[colors]",
     "cython-lint",
@@ -161,11 +162,9 @@ target-version = [
 # Switch to using build
 build-frontend = "build"
 # Disable building PyPy wheels on all platforms, 32bit for py3.10/11/12, musllinux builds, py3.6/7
-skip = ["cp36-*", "cp37-*", "pp*", "cp31*-win32", "cp31*-manylinux_i686", "*-musllinux_*"]
+skip = ["cp36-*", "cp37-*", "pp*", "*-win32", "*-manylinux_i686", "*-musllinux_*"]
 # Run the package tests using `pytest`
 test-extras = "test"
 test-command = "pytest -v {package}/tests"
 # Skip trying to test arm64 builds on Intel Macs
 test-skip = "*-macosx_arm64 *-macosx_universal2:arm64"
-# no wheels for linux-32bit anymore for numpy>=1.22
-environment = "PIP_PREFER_BINARY=1"

src/gstools/field/base.py

@@ -362,7 +362,7 @@ def transform(
         ----------
         method : :class:`str`
             Method to use.
-            See :any:`gstools.transform` for available transformations.
+            See :py:mod:`gstools.transform` for available transformations.
         field : :class:`str`, optional
             Name of field to be transformed. The default is "field".
         store : :class:`str` or :class:`bool`, optional

src/gstools/krige/base.py

@@ -383,9 +383,7 @@ def _pre_ext_drift(self, pnt_cnt, ext_drift=None, set_cond=False):
             the drift values at the given positions
         """
         if ext_drift is not None:
-            ext_drift = np.array(
-                ext_drift, dtype=np.double, ndmin=2, copy=False
-            )
+            ext_drift = np.atleast_2d(np.asarray(ext_drift, dtype=np.double))
             if ext_drift.size == 0:  # treat empty array as no ext_drift
                 return np.array([])
             if set_cond:

src/gstools/tools/geometric.py

@@ -383,7 +383,7 @@ def generate_st_grid(pos, time, mesh_type="unstructured"):
     if mesh_type != "unstructured":
         pos = generate_grid(pos)
     else:
-        pos = np.array(pos, dtype=np.double, ndmin=2, copy=False)
+        pos = np.atleast_2d(np.asarray(pos, dtype=np.double))
     out = [np.repeat(p.reshape(-1), np.size(time)) for p in pos]
     out.append(np.tile(time, np.size(pos[0])))
     return np.asarray(out, dtype=np.double)
@@ -552,7 +552,7 @@ def format_unstruct_pos_shape(pos, shape, check_stacked_shape=False):
     # now we try to be smart
     pre_len = len(np.atleast_1d(pos))
     # care about 1D: pos can be given as 1D array here -> convert to 2D array
-    pos = np.array(pos, dtype=np.double, ndmin=2, copy=False)
+    pos = np.atleast_2d(np.asarray(pos, dtype=np.double))
     post_len = len(pos)
     # first array dimension should be spatial dimension (1D is special case)
     dim = post_len if pre_len == post_len else 1
@@ -606,7 +606,7 @@ def ang2dir(angles, dtype=np.double, dim=None):
         the array of direction vectors
     """
     pre_dim = np.asanyarray(angles).ndim
-    angles = np.array(angles, ndmin=2, dtype=dtype, copy=False)
+    angles = np.atleast_2d(np.asarray(angles, dtype=dtype))
     if len(angles.shape) > 2:
         raise ValueError(f"Can't interpret angles array {angles}")
     dim = angles.shape[1] + 1 if dim is None else dim

src/gstools/transform/field.py

@@ -111,7 +111,7 @@ def apply(fld, method, field="field", store=True, process=False, **kwargs):
         Field class containing a generated field.
     method : :class:`str`
         Method to use.
-        See :any:`gstools.transform` for available transformations.
+        See :py:mod:`gstools.transform` for available transformations.
     field : :class:`str`, optional
         Name of field to be transformed. The default is "field".
     store : :class:`str` or :class:`bool`, optional

src/gstools/variogram/estimator.pyx

@@ -12,6 +12,7 @@ IF OPENMP:
 
 cimport numpy as np
 from libc.math cimport M_PI, acos, atan2, cos, fabs, isnan, pow, sin, sqrt
+from libc.stdint cimport int64_t
 
 
 def set_num_threads(num_threads):
@@ -116,7 +117,7 @@ ctypedef double (*_estimator_func)(const double) nogil
 
 cdef inline void normalization_matheron(
     double[:] variogram,
-    long[:] counts,
+    int64_t[:] counts,
 ):
     cdef int i
     for i in range(variogram.shape[0]):
@@ -125,10 +126,10 @@ cdef inline void normalization_matheron(
 
 cdef inline void normalization_cressie(
     double[:] variogram,
-    long[:] counts,
+    int64_t[:] counts,
 ):
     cdef int i
-    cdef long cnt
+    cdef int64_t cnt
     for i in range(variogram.shape[0]):
         # avoid division by zero
         cnt = max(counts[i], 1)
@@ -139,28 +140,28 @@ cdef inline void normalization_cressie(
 
 ctypedef void (*_normalization_func)(
     double[:],
-    long[:],
+    int64_t[:],
 )
 
 cdef inline void normalization_matheron_vec(
     double[:, :] variogram,
-    long[:, :] counts,
+    int64_t[:, :] counts,
 ):
     cdef int d
     for d in range(variogram.shape[0]):
         normalization_matheron(variogram[d, :], counts[d, :])
 
 cdef inline void normalization_cressie_vec(
     double[:, :] variogram,
-    long[:, :] counts,
+    int64_t[:, :] counts,
 ):
     cdef int d
     for d in range(variogram.shape[0]):
         normalization_cressie(variogram[d, :], counts[d, :])
 
 ctypedef void (*_normalization_func_vec)(
     double[:, :],
-    long[:, :],
+    int64_t[:, :],
 )
 
 cdef _estimator_func choose_estimator_func(str estimator_type):
@@ -221,7 +222,7 @@ def directional(
     cdef int f_max = f.shape[0]
 
     cdef double[:, :] variogram = np.zeros((d_max, len(bin_edges)-1))
-    cdef long[:, :] counts = np.zeros((d_max, len(bin_edges)-1), dtype=long)
+    cdef int64_t[:, :] counts = np.zeros((d_max, len(bin_edges)-1), dtype=np.int64)
     cdef int i, j, k, m, d
     cdef double dist
 
@@ -287,7 +288,7 @@ def unstructured(
     cdef int f_max = f.shape[0]
 
     cdef double[:] variogram = np.zeros(len(bin_edges)-1)
-    cdef long[:] counts = np.zeros(len(bin_edges)-1, dtype=long)
+    cdef int64_t[:] counts = np.zeros(len(bin_edges)-1, dtype=np.int64)
     cdef int i, j, k, m
     cdef double dist
 
@@ -324,7 +325,7 @@ def structured(
     cdef int k_max = i_max + 1
 
     cdef double[:] variogram = np.zeros(k_max)
-    cdef long[:] counts = np.zeros(k_max, dtype=long)
+    cdef int64_t[:] counts = np.zeros(k_max, dtype=np.int64)
     cdef int i, j, k
 
     cdef int num_threads_c = set_num_threads(num_threads)
@@ -356,7 +357,7 @@ def ma_structured(
     cdef int k_max = i_max + 1
 
     cdef double[:] variogram = np.zeros(k_max)
-    cdef long[:] counts = np.zeros(k_max, dtype=long)
+    cdef int64_t[:] counts = np.zeros(k_max, dtype=np.int64)
     cdef int i, j, k
 
     cdef int num_threads_c = set_num_threads(num_threads)