rexafs for Python

Rust-powered X-ray absorption analysis with the same spectrum methods as Rust. The private native extension is rexafs._core.

import numpy as np
from rexafs import Spectrum, AUTOBK, BackgroundMethod

data = np.loadtxt("spectrum.dat")  # energy (eV), absorption mu
spectrum = Spectrum.from_arrays(data[:, 0], data[:, 1]).fft()
print(spectrum.e0(), spectrum.chi(), spectrum.chir_mag())

background = AUTOBK()
background.rbkg = 1.2
spectrum.set_background_method(BackgroundMethod.AUTOBK(background)).fft()

normalize(), calc_background(), fft() and ifft() execute the selected stage and return the same spectrum. Missing prerequisite stages run with their configured parameters or defaults. set_e0(value) overrides the edge energy. Use PrePostEdge/NormalizationMethod to configure normalization and XrayFFTF with set_fft to configure the forward transform. Parameter names match Rust; window and solver fields accept Rust variant names as strings.

Input lists, NumPy arrays and strided views are converted to float64 and checked for finite values, equal lengths and strictly increasing energy. Result getters return owned NumPy arrays, or None before their stage runs. Inputs and returned arrays do not share mutable storage with the spectrum. Input/normalization errors raise ValueError; other stage failures raise RuntimeError. Stages release the GIL while Rust computes.

from rexafs import io
spectra = [io.read_qas_transmission(path).fft() for path in ["scan01.dat", "scan02.dat"]]

The old process, ProcessedSpectrum, and free batch/pipeline wrappers have been removed. See the shared API guide for configuration, invalidation, algorithm selection and migration details. MBack and ILPBkg are still unimplemented placeholders; selecting them raises an error.

Build

Registry publication is pending. Build from the repository root with CPython 3.10–3.14:

uv venv --python 3.14
uv pip install maturin numpy
uv run --no-project maturin develop --release

Fitting, structures, plotting and direct ReFEFF calculation remain Rust/desktop APIs. Licensed under MIT OR Apache-2.0.

New AUTOBK objects use a single linear solve with clamp_lambda = 0.001. Set clamp_lambda to 0 to disable the endpoint penalty. The low-end weight is clamp_lo = 0, the high-end weight is clamp_hi = 1, and nclamp = 3. The FixedPenalty model does not add a separate ridge penalty on coefficients. See the full definition.

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Data verified by PyPI on Sep 6, 2026
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  • Released:
Newer release available (0.2.7)

1 maintainer

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Avatar for ameyanagi from gravatar.com ameyanagi

Credits

Author: Ameyanagi

GitHub Statistics

Data verified by PyPI on Sep 6, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

MIT OR Apache-2.0

Requires

Python <3.15, >=3.10

Classifiers

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0.2.7

5 files

0.2.6

5 files

0.2.5

21 files

0.2.4

21 files

0.2.3

21 files

0.2.1

21 files

0.2.0

21 files

0.1.4

21 files

0.1.3

21 files

0.1.2

21 files

This release

0.1.1 This release

21 files

0.1.0

21 files

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