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extract_spectrum_optimal

Optimal (Horne 1986) aperture extraction of ctx.image.
Category Extraction (2-D to 1-D)
Backend scipy - implemented here on top of scipy primitives
Version 1.0.0
Reads ctx.image (an ImageFrame)
Writes spectrum

Empirical profile built from per-column cutouts then smoothed along the dispersion axis with a median filter (robust to residual cosmics, profile = 1 / N at edge columns where the full aperture doesn't fit). Iterative inverse-variance extraction with σ-clip rejection of deviant pixels — the standard Horne recipe. Output uncertainty is the propagated 1-σ. When to choose this vs the lighter alternatives: extract_spectrum_sum is the simplest pure sum (no trace fit); extract_spectrum_boxcar is the edge-safe boxcar with optional Gaussian profile weighting but no variance model, no uncertainty propagation and no cosmic rejection — pick it for high-SNR sources or extended emission. Pick extract_spectrum_optimal when SNR matters most (faint, read-noise-limited targets), when residual cosmics may remain after clip_cosmic_rays, or when the downstream pipeline needs per-pixel Spectrum1D.uncertainty (e.g. radial-velocity error propagation).

Parameters

Parameter Default Required Description
trace_method 'argmax' - easyspec trace method ('argmax' / 'moments' / 'multi').
trace_poly_order 2 - Polynomial order of the trace fit.
trace_y_pixel_range 15 - Half-window (rows) for the trace search.
trace_peak_height 100.0 - Minimum peak height when locating the trace.
trace_peak_distance 50 - Minimum separation between traces (multi mode).
trace_half_width 12 - Aperture half-width (rows) for trace + extraction.
gain 1.0 - Detector gain in e⁻/ADU (variance model).
readnoise 6.0 - Detector read noise in e⁻ (variance model).
profile_smooth_columns 21 - Window (columns) of the median smoothing applied to the empirical profile. Odd; 1 disables smoothing. Larger ⇒ more robust but loses spatial-profile variations along the dispersion axis (curved/tilted traces).
reject_sigma 5.0 - σ threshold for outlier rejection during extraction.
iterations 3 - Maximum extract→reject→re-extract cycles.

Use it

from spectro_kernel import run_algorithm

output = run_algorithm("extract_spectrum_optimal", ctx, {
    "trace_method": "argmax",
    "trace_poly_order": 2,
    "trace_y_pixel_range": 15,
    "trace_peak_height": 100.0,
    "trace_peak_distance": 50,
    "trace_half_width": 12,
    "gain": 1.0,
    "readnoise": 6.0,
    "profile_smooth_columns": 21,
    "reject_sigma": 5.0,
    "iterations": 3
})

The CLI loads a single 1-D spectrum with --input; this algorithm needs ctx.image (an ImageFrame). Run it from Python or as a step of a pipeline preset.

{
  "tool": "extract_spectrum_optimal",
  "arguments": {
    "session_id": "<session_id>",
    "params": {
      "trace_method": "argmax",
      "trace_poly_order": 2,
      "trace_y_pixel_range": 15,
      "trace_peak_height": 100.0,
      "trace_peak_distance": 50,
      "trace_half_width": 12,
      "gain": 1.0,
      "readnoise": 6.0,
      "profile_smooth_columns": 21,
      "reject_sigma": 5.0,
      "iterations": 3
    }
  }
}

Every algorithm is an MCP tool of the same name; describe_algorithm returns this page's metadata as JSON.

References

  • Horne 1986, PASP 98, 609 — optimal extraction algorithm for CCD spectroscopy.
  • Marsh 1989, PASP 101, 1032 — empirical profile for tilted traces.
  • Tody 1986, SPIE 627, 733 — IRAF apall heritage.