pySplashsurf

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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) or the main repository.

Installation

Requires Python version 3.7+

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 CLI itself.

CLI

To use the CLI, you can use the pysplashsurf command after installing the package:

pysplashsurf --help

For example, to reconstruct a surface from particle data in a VTK file with some smoothing:

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.

Library

Example to reconstruct the surface from an input file, apply some post-processing methods and write the data back to a file:

import meshio
import numpy as np
import pysplashsurf

mesh = meshio.read("input.vtk")
particles = np.array(mesh.points, dtype=np.float64)

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
)
    
pysplashsurf.write_to_file(mesh_with_data, "output.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 from the root project folder (from pysplashsurf/).

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