# pySplashsurf
pySplashsurf provides Python bindings for `splashsurf`, an open source surface reconstruction library for particle data from SPH simulations.
Detailed information on the surface reconstruction and library itself and its API can be found on the [project website (splashsurf.physics-simulation.org)](https://splashsurf.physics-simulation.org/) or the [main repository](https://github.com/InteractiveComputerGraphics/splashsurf).
## Installation
Requires Python version 3.10+
```
pip install pysplashsurf
```
To install pysplashsurf with meshio support (which adds some additional IO functionality), use
```
pip install pysplashsurf[meshio]
```
This will add support for the `.bgeo` file extension to meshio, so that particle data in the `BGEOV` format can be read using meshio.
Meshio is also required for the `write_to_file` method from the bindings to work.
The rest of the package, including the CLI, will still work even if meshio is not installed.
## Usage
pySplashsurf can either be used as a library in Python scripts or as a command line tool that provides the same interface as the original Rust [`splashsurf`](https://github.com/InteractiveComputerGraphics/splashsurf) CLI itself.
### CLI
To use the CLI, you can use the `pysplashsurf` command after installing the package:
```bash
pysplashsurf --help
```
For example, to reconstruct a surface from particle data in a VTK file with some smoothing:
```bash
splashsurf reconstruct particles.vtk -r=0.025 -l=2.0 -c=0.5 -t=0.6 --mesh-smoothing-weights=on --mesh-smoothing-iters=15 --normals=on --normals-smoothing-iters=10
```
For more information on the CLI and its arguments, refer to the [splashsurf documentation](https://github.com/InteractiveComputerGraphics/splashsurf).
### Library
Example to reconstruct the surface from an input file, apply some post-processing methods and write the data back to a file:
```python
import meshio
import numpy as np
import pysplashsurf
# Load particles from mesh file
mesh = meshio.read("input.vtk")
particles = np.array(mesh.points, dtype=np.float64)
# Reconstruct the points/particles with some post-processing
mesh_with_data, reconstruction = pysplashsurf.reconstruction_pipeline(
particles,
particle_radius=0.025,
rest_density=1000.0,
smoothing_length=2.0,
cube_size=0.5,
iso_surface_threshold=0.6,
mesh_smoothing_weights=True,
mesh_smoothing_weights_normalization=13.0,
mesh_smoothing_iters=25,
normals_smoothing_iters=10,
mesh_cleanup=True,
compute_normals=True,
subdomain_grid=True,
subdomain_num_cubes_per_dim=64,
output_mesh_smoothing_weights=True
)
# Write the mesh with attributes to file using meshio
mesh_with_data.write_to_file("surface.vtk")
```
The `reconstruction_pipeline` method provides (mostly) the same arguments as the splashsurf binary CLI.
It may be necessary to specify the `dtype` of a function input (as done for `particles` in the example) so that the bindings know what data type to use internally.
The extension supports single (`np.float32`) and double precision floats (`np.float64`).
## Build instructions
You can also manually build the package from the source code:
1. Clone the repository
2. cd to the `pysplashsurf` directory
3. Create an environment from `python_environment.yaml` and activate it
- I recommend creating it in a subfolder, e.g.
```conda env create --prefix ./env -f python_environment.yaml```
- Then activate it using `conda activate ./env`
4. Now, to build the project, use maturin: `maturin develop`
- Maturin automatically installs the resulting binary in your python environment
- Set the release flag `-r` or `--release` to build an optimized binary, however, compilation time will be slightly longer
### Documentation Build
To generate the Sphinx documentation, make sure that the package is installed through, e.g., maturin, and then run `make html` in the `pysplashsurf/pysplashsurf/docs` directory.
The resulting HTML files will be in `pysplashsurf/pysplashsurf/docs/build/html`.
### Stub File Generation
To automatically generate a stub file for the package, run `cargo run --bin stub_gen --no-default-features` from the root project folder (from `pysplashsurf/`).
Raw data
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