add numpy 2 support

.github/workflows/main.yml

@@ -16,16 +16,14 @@ jobs:
   source_check:
     name: source check
     runs-on: ubuntu-latest
-    strategy:
-      fail-fast: false
 
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
         with:
           fetch-depth: '0'
 
       - name: Set up Python 3.9
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v5
         with:
           python-version: 3.9
 
@@ -38,6 +36,10 @@ jobs:
         run: |
           python -m black --check --diff --color .
 
+      - name: black preview
+        run: |
+          python -m black --preview --diff --color .
+
       - name: isort check
         run: |
           python -m isort --check --diff --color .
@@ -58,60 +60,73 @@ 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 }
 
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
         with:
           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:
           output-dir: dist
 
-      - uses: actions/upload-artifact@v2
+      - uses: actions/upload-artifact@v3
         with:
           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
+      - uses: actions/checkout@v4
         with:
           fetch-depth: '0'
 
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
+      - name: Set up Python ${{ matrix.ver.py }}
+        uses: actions/setup-python@v5
         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
 
@@ -120,8 +135,8 @@ jobs:
           # PEP 517 package builder from pypa
           python -m build --sdist --outdir dist .
 
-      - uses: actions/upload-artifact@v2
-        if: matrix.os == 'ubuntu-latest' && matrix.python-version == '3.9'
+      - uses: actions/upload-artifact@v3
+        if: matrix.os == 'ubuntu-latest' && matrix.ver.py == '3.9'
         with:
           path: dist/*.tar.gz
 
@@ -130,7 +145,7 @@ jobs:
     runs-on: ubuntu-latest
 
     steps:
-      - uses: actions/download-artifact@v2
+      - uses: actions/download-artifact@v3
         with:
           name: artifact
           path: dist

.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/00_misc/00_tpl_stable.py

@@ -40,6 +40,7 @@
    \sigma^2_{\ell_{\mathrm{up}}} &=
    C\cdot\frac{\ell_{\mathrm{up}}^{2H}}{2H}
 """
+
 import numpy as np
 
 import gstools as gs

examples/00_misc/01_export.py

@@ -7,6 +7,7 @@
 
 These can be viewed for example with `Paraview <https://www.paraview.org/>`__.
 """
+
 # sphinx_gallery_thumbnail_path = 'pics/paraview.png'
 import gstools as gs
 

examples/00_misc/02_check_rand_meth_sampling.py

@@ -2,6 +2,7 @@
 Check Random Sampling
 ---------------------
 """
+
 import numpy as np
 from matplotlib import pyplot as plt
 from mpl_toolkits.mplot3d import Axes3D

examples/00_misc/04_herten.py

@@ -30,6 +30,7 @@
 functions, since the only produce the ``herten_transmissivity.gz``
 and ``grid_dim_origin_spacing.txt``, which are already present.
 """
+
 import os
 
 import matplotlib.pyplot as plt

examples/00_misc/05_standalone_field.py

@@ -7,6 +7,7 @@
 In the following example we will produce 10000 random points in 4D with
 random values and plot them.
 """
+
 import numpy as np
 
 import gstools as gs

examples/01_random_field/03_unstr_srf_export.py

@@ -6,6 +6,7 @@
 Normally, such a grid would be read in, but we can simply generate one and
 then create a random field at those coordinates.
 """
+
 import numpy as np
 
 import gstools as gs

examples/01_random_field/04_srf_merge.py

@@ -6,6 +6,7 @@
 to merge two unstructured rectangular fields.
 
 """
+
 # sphinx_gallery_thumbnail_number = 2
 import numpy as np
 

examples/01_random_field/06_pyvista_support.py

@@ -12,6 +12,7 @@
 The :any:`Field.mesh` method enables easy field creation on PyVista meshes
 used by the :any:`SRF` or :any:`Krige` class.
 """
+
 # sphinx_gallery_thumbnail_path = 'pics/GS_pyvista_cut.png'
 import pyvista as pv
 
@@ -21,8 +22,8 @@
 # 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/02_cov_model/01_basic_methods.py

@@ -36,6 +36,7 @@
 correlation function as demonstrated in the introductory example.
 If one of the above functions is given, the others will be determined:
 """
+
 import gstools as gs
 
 model = gs.Exponential(dim=3, var=2.0, len_scale=10, nugget=0.5)

examples/02_cov_model/02_aniso_rotation.py

@@ -6,6 +6,7 @@
 represents the isotropic case for the model.
 Nevertheless, you can provide anisotropy ratios by:
 """
+
 import gstools as gs
 
 model = gs.Gaussian(dim=3, var=2.0, len_scale=10, anis=0.5)

examples/02_cov_model/03_spectral_methods.py

@@ -23,6 +23,7 @@
 
 You can access these methods by:
 """
+
 import gstools as gs
 
 model = gs.Gaussian(dim=3, var=2.0, len_scale=10)

examples/02_cov_model/04_different_scales.py

@@ -16,6 +16,7 @@
 
 You can access it by:
 """
+
 import gstools as gs
 
 model = gs.Stable(dim=3, var=2.0, len_scale=10)

examples/02_cov_model/05_additional_para.py

@@ -10,6 +10,7 @@
 
 This leads to the so called **stable** covariance model and we can define it by
 """
+
 import numpy as np
 
 import gstools as gs

examples/02_cov_model/06_fitting_para_ranges.py

@@ -6,6 +6,7 @@
 variogram data. In the following we will use the self defined stable model
 from a previous example.
 """
+
 import numpy as np
 
 import gstools as gs

examples/03_variogram/00_fit_variogram.py

@@ -2,6 +2,7 @@
 Fit Variogram
 -------------
 """
+
 import numpy as np
 
 import gstools as gs

examples/03_variogram/01_find_best_model.py

@@ -2,6 +2,7 @@
 Finding the best fitting variogram model
 ----------------------------------------
 """
+
 import numpy as np
 from matplotlib import pyplot as plt
 

examples/03_variogram/02_multi_vario.py

@@ -5,6 +5,7 @@
 In this example, we demonstrate how to estimate a variogram from multiple
 fields on the same point-set that should have the same statistical properties.
 """
+
 import matplotlib.pyplot as plt
 import numpy as np
 

examples/03_variogram/03_directional_2d.py

@@ -7,6 +7,7 @@
 
 Afterwards we will fit a model to this estimated variogram and show the result.
 """
+
 import numpy as np
 from matplotlib import pyplot as plt
 

examples/03_variogram/04_directional_3d.py

@@ -7,6 +7,7 @@
 
 Afterwards we will fit a model to this estimated variogram and show the result.
 """
+
 import matplotlib.pyplot as plt
 import numpy as np
 from mpl_toolkits.mplot3d import Axes3D

examples/03_variogram/05_auto_fit_variogram.py

@@ -2,6 +2,7 @@
 Fit Variogram with automatic binning
 ------------------------------------
 """
+
 import numpy as np
 
 import gstools as gs

examples/03_variogram/06_auto_bin_latlon.py

@@ -8,6 +8,7 @@
 
 We use a data set from 20 meteo-stations choosen randomly.
 """
+
 import numpy as np
 
 import gstools as gs

examples/04_vector_field/00_2d_vector_field.py

@@ -5,6 +5,7 @@
 As a first example we are going to generate a 2d vector field with a Gaussian
 covariance model on a structured grid:
 """
+
 import numpy as np
 
 import gstools as gs