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Observed since 20 Oct, 18:03 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
Ultra-accurate and fast FM function evaluator with <4.5e-16 relative error
Ultra-accurate and fast FM function evaluator with <4.5e-16 relative error (~2x machine epsilon).
pip install accurpy
from accurpy import syncF, fm_scaled
# Compute FM(x) * exp(x) - the numerically stable form
result = syncF(1.0)
# Compute FM(x) = exp(-x) * integral of t^(-1/2) * exp(-t) / (1 + t/x) dt
result_scaled = fm_scaled(1.0)
# Works with numpy arrays
import numpy as np
x = np.linspace(0.001, 100, 1000)
y = syncF(x)
The C extension uses METH_O calling convention with PyFloat_AS_DOUBLE for minimal overhead:
| x range | syncF(x) time | Notes |
|---|---|---|
| Small (1e-8) | ~38 ns | Cube-root expansion |
| Wide (1.0) | ~45 ns | Rational approximation |
| Large (1e10) | ~32 ns | Asymptotic expansion |
Comparable to math.sin (~38 ns) - only ~20 ns above the minimum possible CPython C-extension overhead (~16 ns for extract+create).
Array throughput: ~10 ns/element.
MIT
Download counts and popularity will appear here as the collector receives them.
| Version | Published | Direct dependencies | Open version |
|---|---|---|---|
| 0.2.3 | 1 Dec 2025 | 1 |
This describes our collected data; it is not a security assessment.
Observed since 20 Oct, 18:03 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package:6231172de561311a5fb79fbfefc3f66a18087a6f5943bf6944d7414e75855abc