CSF 3DFin

.github/workflows/wheels.yml

@@ -14,16 +14,16 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        os: [ubuntu-20.04, windows-2019, macOS-11]
+        os: [ubuntu-22.04, windows-2022, macOS-12]
 
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
 
       # Used to host cibuildwheel
-      - uses: actions/setup-python@v3
+      - uses: actions/setup-python@v5
 
       - name: Install cibuildwheel
-        run: python -m pip install cibuildwheel==2.12.2
+        run: python -m pip install cibuildwheel==2.16.5
 
       - name: Build wheels
         run: python -m cibuildwheel --output-dir wheelhouse
@@ -40,9 +40,9 @@ jobs:
     #Only publish to PyPI when a commit is tagged
     if: github.event_name == 'push' && startsWith(github.event.ref, 'refs/tags')
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
 
-      - uses: actions/setup-python@v3
+      - uses: actions/setup-python@v5
 
       - uses: actions/download-artifact@v3
         with:
@@ -55,7 +55,8 @@ jobs:
           TWINE_PASSWORD: ${{ secrets.PYPI_TOKEN }}
         # construct the source package and upload src and wheels to PiPy
         run: |
-          python -m pip install twine
-          python setup.py sdist 
+          python -m pip install --upgrade pip
+          python -m pip install twine build
+          python -m build --sdist
           twine upload dist/*
           twine upload wheelhouse/*.whl

README.md

@@ -7,6 +7,13 @@ W. Zhang, J. Qi*, P. Wan, H. Wang, D. Xie, X. Wang, and G. Yan, “An Easy-to-Us
 (http://www.mdpi.com/2072-4292/8/6/501/htm)
 
 
+**This is a modified version of the Original Code for 3DFin purposes**
+
+List of changes:
+
+- Better handling of numpy arrays in the python bindings (avoid expensive copies)
+
+
 **New feature has been implemented:**
 
 Now, We has wrapped a Python interface for CSF with swig. It is simpler to use now. This new feature can make CSF easier to be embeded into a large project. For example, it can work with Laspy (https://github.com/laspy/laspy). What you do is just read a point cloud into a python 2D list, and pass it to CSF.

pyproject.toml

@@ -1,3 +1,6 @@
 [build-system]
-requires = ["setuptools"]
-build-backend = "setuptools.build_meta"
+requires = ["wheel","setuptools", "oldest-supported-numpy"]
+build-backend = "setuptools.build_meta"
+
+[tool.cibuildwheel]
+build = "cp3{9,10,11,12}-*" 

python/CSF/CSF.i

@@ -7,6 +7,11 @@
 
 %include "std_string.i"
 %include "std_vector.i"
+%include "numpy.i"
+
+%init %{
+import_array();
+%}
 
 namespace std
 {
@@ -16,4 +21,5 @@ namespace std
     %template(VecDouble) vector<double>;
 }
 
+%apply (double* IN_ARRAY2, int DIM1, int DIM2) {(double *points, int rows, int cols)};
 %include "../src/CSF.h"