Implemented all planned corrections: - finite-size e/m L0 and U - atomic screening and exchange - radiative (electron only so far) Added plotter and csv_export
72 lines
2.0 KiB
Python
72 lines
2.0 KiB
Python
from pathlib import Path
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import numpy as np
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from beta_spectrum.base import SpectrumComponent
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class ExchangeCorrection(SpectrumComponent):
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"""
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Atomic xchange correction using Hayen 2018 Table X coefficients (App. G)
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"""
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def __init__(self, Z: int, filename=None, eps: float = 1e-6):
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self.Z = Z
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self.eps = eps
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if filename is None:
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filename = self._default_coeff_path()
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self.coeffs = self._load_coeffs(filename)
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def _load_coeffs(self, filename):
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data = np.genfromtxt(filename, delimiter=",", names=True)
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for row in data:
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if int(row["Z"]) == self.Z:
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return {
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"a": row["a"],
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"b": row["b"],
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"c": row["c"],
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"d": row["d"],
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"e": row["e"],
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"f": row["f"],
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"g": row["g"],
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"h": row["h"],
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"i": row["i"],
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}
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raise ValueError(f"No exchange coefficients available for Z={self.Z}")
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def _default_coeff_path(self):
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return Path(__file__).resolve().parent.parent / "data" / "exchange_coeff.csv"
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def __call__(self, W: np.ndarray) -> np.ndarray:
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W = np.asarray(W)
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# Define physical cutoff
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W_cut = 1.005
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# Compute full expression ONLY above cutoff
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W_safe = np.maximum(W, W_cut)
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Wp = W_safe - 1.0
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a = self.coeffs["a"]
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b = self.coeffs["b"]
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c = self.coeffs["c"]
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d = self.coeffs["d"]
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e = self.coeffs["e"]
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f_coef = self.coeffs["f"]
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g = self.coeffs["g"]
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h = self.coeffs["h"]
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i = self.coeffs["i"]
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term1 = a / Wp
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term2 = b / (Wp**2)
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term3 = c * np.exp(-d * Wp)
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base = np.maximum(W_safe - f_coef, self.eps)
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term4 = e * np.sin((base**g + h)) / (W_safe**i)
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X_safe = 1.0 + term1 + term2 + term3 + term4
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return X_safe
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