aci-rssa

aci_rssa

Fast, streaming reader for MCNP RSSA (surface source) files, with a Rust core and a Polars-based Python API.

RSSA files record every particle that crosses a given surface during an MCNP (or D1S-UNED) simulation, and can easily reach tens or hundreds of gigabytes. aci_rssa memory-maps the file and decodes track records in parallel (via rayon), handing the result to Python as a Polars DataFrame — either all at once, or as a lazy, batch-at-a-time stream for files too large to fit in memory.

Installation

pip install aci_rssa

Prebuilt wheels are published for Linux, macOS, and Windows (x86_64/arm64) on CPython ≥3.10 — no Rust toolchain needed to install.

Quickstart

from aci_rssa import RSSA

rssa = RSSA.read_from_file("surface_source.w")
print(rssa)  # summary: surfaces, track/history counts, source code

rssa.tracks          # polars.DataFrame: history, particle_type, weight, energy,
                      # time, x, y, z, u, v, w, surface_id
rssa.neutron_tracks   # tracks filtered to neutrons
rssa.photon_tracks    # tracks filtered to everything else (typically photons)

Reading only the header (fast, never touches the potentially huge track data):

from aci_rssa import FileParameters

parameters = FileParameters.read_from_file("surface_source.w")
parameters.nrss       # number of tracks recorded
parameters.surfaces   # surfaces tracks were recorded on

Very large files

For files too large to load eagerly, scan_tracks returns a Polars LazyFrame backed by a Rust reader that decodes the file batch by batch, driven by Polars' query engine — filters and column selection are pushed down so you only decode what you need:

from aci_rssa import scan_tracks
import polars as pl

(
    scan_tracks("surface_source.w")
    .filter(pl.col("energy") > 1.0)
    .select("x", "y", "z", "energy")
    .collect(engine="streaming")
)

RSSAPlot and RSSASpectraPlot accept a LazyFrame directly, so a scan_tracks() result can be plotted without ever loading the file eagerly — construct them by hand instead of going through RSSA.read_from_file()/.plot_cyl()/.plot_plane(), which require an in-memory RSSA:

from aci_rssa import FileParameters, RSSAPlot, scan_tracks

parameters = FileParameters.read_from_file("surface_source.w")  # header only
plot = RSSAPlot(scan_tracks("surface_source.w"), parameters, x_col="x", y_col="y")

(
    plot.set_particle("n")
    .calculate_bins(bin_width=10)
    .get_particle_current(1e17)
    .show()
)

Plotting

rssa.plot_cyl(axis="z").show()      # particle density on a cylindrical surface
rssa.plot_plane(x="x", y="y").show()  # particle density on a planar surface
rssa.plot_spectra().show()            # energy spectrum

Development

This is a Cargo workspace (rssa-core, the pure-Rust parsing/decoding library, and rssa-python, its PyO3 bindings) plus a Python package in python/, built together with maturin.

python -m venv .venv && source .venv/bin/activate
pip install "maturin>=1.9.4,<2.0"
maturin develop --extras test,dev   # builds the extension module, installs test/dev deps

cargo test                          # Rust tests (rssa-core)
pytest                              # Python tests
ty check python/aci_rssa            # type checking

License

Licensed under the European Union Public Licence v1.2 (EUPL-1.2).

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