Algorithm catalogue¶

115 algorithms in 26 categories, every one of them grounded in the published literature. This page and every algorithm page are generated from the registry at build time, so they are exactly what spectro list, list_algorithms() and the MCP server expose.

Each algorithm declares a backend (what it leans on), its literature references, its parameters with defaults, and what it reads from and writes to the WorkContext. Tools and agents can read the same catalogue as JSON validated by a JSON Schema (schema version 1, spectro-kernel 0.6.2).

Input / output¶

Algorithm	What it does	Backend	Version
`read_ascii_spectrum`	Read a 1D spectrum from a two- or three-column text file.	`numpy`	`1.0.0`
`read_echelle_fits`	Read a multi-order échelle FITS file into `ctx.spectra`.	`astropy`	`1.0.0`
`read_fits`	Read a 1D spectrum from a FITS file (local path or http(s) URL).	`astropy`	`2.0.0`
`read_sdss_spectrum`	Read an SDSS-format spectrum (`spec-*.fits`) into `ctx.spectrum`.	`astropy`	`1.1.0`
`read_votable_spectrum`	Read a 1D spectrum from a VOTable file (the IVOA Virtual Observatory format).	`astropy`	`1.0.0`

Master frames¶

Algorithm	What it does	Backend	Version
`bias_combine`	Combine a stack of bias frames into one master bias.	`numpy`	`1.0.0`
`bias_combine_easyspec`	Combine bias frames into a master bias via `easyspec.cleaning.master`.	`easyspec`	`1.1.1`
`dark_combine`	Combine a stack of dark frames into a master dark.	`numpy`	`2.0.0`
`dark_combine_easyspec`	Combine dark frames into a master dark via `easyspec.cleaning.master`.	`easyspec`	`1.0.1`
`flat_combine`	Combine a stack of flat frames into a master flat (raw, not normalised).	`numpy`	`2.0.0`
`flat_combine_easyspec`	Combine flat frames into a master flat via `easyspec.cleaning.master`.	`easyspec`	`1.0.1`

Preprocessing (2-D image)¶

Algorithm	What it does	Backend	Version
`correct_slant_affine`	Make monochromatic lines parallel to the rows by a horizontal shear.	`scipy`	`1.0.0`
`correct_smile_polynomial`	Undo smile curvature via the Schroeder even-order expansion.	`scipy`	`1.0.0`
`correct_tilt_affine`	Re-align the slit with the detector columns by a vertical shear.	`scipy`	`1.0.0`
`dark_subtract`	Subtract a master dark from `ctx.image`.	`numpy`	`1.0.0`
`denoise_gaussian_2d`	Separable isotropic Gaussian smoothing of `ctx.image`.	`scipy`	`1.0.0`
`denoise_median_2d`	Square median filter over `ctx.image`, optionally banded by rows.	`scipy`	`1.0.0`
`flat_normalize`	Divide `ctx.image` by a master flat normalised to unity.	`numpy`	`1.0.1`
`flat_normalize_easyspec`	Flat-field correct a science frame via `cleaning.flatten`.	`easyspec`	`1.0.1`
`outlier_rejection_mad_adaptive`	Replace pixels whose deviation from a local median exceeds `threshold·MAD`.	`numpy`	`1.0.1`
`subtract_bias_easyspec`	Subtract a master bias from a single science frame via `cleaning.debias`.	`easyspec`	`1.0.1`
`subtract_dark_easyspec`	Subtract a master dark from a science frame via `cleaning.sub_dark`.	`easyspec`	`1.0.1`
`subtract_sky_2d`	Subtract a per-column sky model fitted from off-trace rows of `ctx.image`.	`numpy`	`1.0.1`

Cosmic-ray rejection¶

Algorithm	What it does	Backend	Version
`clip_cosmic_rays`	Detect and replace cosmic-ray hits on `ctx.image`.	`scipy`	`1.0.0`
`cosmic_ray_remove_easyspec`	Cosmic-ray (and optional gain) correction via `CR_and_gain_corrections`.	`easyspec`	`1.0.1`

Extraction (2-D to 1-D)¶

Algorithm	What it does	Backend	Version
`detect_trace`	Detect the spectral trace on `ctx.image` and expose it on `ctx.extras["trace"]`.	`scipy`	`1.0.1`
`extract_sky_lateral_bands`	Median-combine two off-trace sky bands into a 1D pixel-axis reference.	`numpy`	`1.0.0`
`extract_spectrum_boxcar`	Trace (easyspec) + pure-numpy aperture extraction on `ctx.image`.	`easyspec`	`2.0.0`
`extract_spectrum_easyspec`	Trace and extract a 1D spectrum from a 2D frame via easyspec.	`easyspec`	`2.0.0`
`extract_spectrum_optimal`	Optimal (Horne 1986) aperture extraction of `ctx.image`.	`scipy`	`1.0.0`
`extract_spectrum_sum`	Extract a 1D spectrum from `ctx.image` by summing across the trace.	`numpy`	`2.0.0`

Wavelength calibration¶

Algorithm	What it does	Backend	Version
`fit_emission_lines_gaussian`	Measure sub-pixel centroids of several emission lines at once.	`astropy`	`1.0.0`
`match_lamp_lines`	Auto-identify arc-lamp lines against the bundled NIST atlas.	`scipy`	`1.0.2`
`measure_arc_geometry`	Measure smile_radius + slant_deg from an arc-lamp 2-D image.	`scipy`	`2.0.0`
`reidentify_arc_features`	Re-anchor stored (pixel, λ) arc features onto a fresh arc exposure.	`scipy`	`1.0.0`
`wavelength_calibrate_easyspec`	Fit a wavelength polynomial via `extraction.wavelength_calibration` and apply it.	`easyspec`	`1.0.1`
`wavelength_calibrate_polynomial`	Fit a polynomial to (pixel → wavelength) pairs and apply it to the spectrum.	`numpy`	`1.0.1`
`wavelength_calibration_in_situ`	Refine the wavelength zero-point from simultaneously-acquired sky lines.	`astropy`	`1.0.0`
`wavelength_calibration_solar`	Calibrate a solar spectrum from built-in Fraunhofer line wavelengths.	`scipy`	`2.0.0`

Flux calibration¶

Algorithm	What it does	Backend	Version
`flux_calibrate_easyspec`	Flux-calibrate `ctx.spectrum` via a standard-star observation.	`easyspec`	`1.0.1`
`response_from_standard`	Derive the instrumental response curve from a standard-star observation.	`scipy`	`1.0.1`

Continuum¶

Algorithm	What it does	Backend	Version
`compare_normalisations`	Run every continuum-normalisation method on `ctx.spectrum` and collect them.	`numpy`	`1.0.1`
`normalize_edges`	Normalise a spectrum using a continuum fitted only on its line-free edges.	`numpy`	`1.0.1`
`normalize_max`	Normalise a spectrum by dividing the flux by its maximum value.	`numpy`	`1.0.1`
`normalize_percentile`	Normalise a spectrum by dividing the flux by a high percentile of itself.	`numpy`	`1.0.1`
`normalize_polynomial`	Normalise the continuum to unity with a sigma-clipped polynomial fit.	`numpy`	`1.1.0`
`normalize_to_region`	Divide the flux by its NaN-safe mean over `[wave_lo, wave_hi]`.	`numpy`	`1.0.0`
`subtract_continuum`	Subtract a sigma-clipped polynomial continuum, leaving the line residual.	`numpy`	`1.0.1`

Smoothing¶

Algorithm	What it does	Backend	Version
`compare_smoothings`	Run every smoothing kernel on `ctx.spectrum` and collect the results.	`numpy`	`1.0.1`
`smooth_gaussian`	Smooth a spectrum by convolution with a Gaussian kernel.	`scipy`	`1.0.1`
`smooth_savgol`	Smooth a spectrum with a Savitzky-Golay filter.	`scipy`	`1.0.1`

Resampling¶

Algorithm	What it does	Backend	Version
`resample_flux_conserving`	Resample onto a new wavelength grid while preserving integrated flux.	`specutils`	`1.0.1`
`resample_linear`	Resample a spectrum onto a uniform wavelength grid by linear interpolation.	`numpy`	`1.0.1`

Transforms¶

Algorithm	What it does	Backend	Version
`clip_sigma`	Remove outlier samples (cosmic rays, hot pixels) by iterative sigma clipping.	`scipy`	`1.0.1`
`combine_spectra_arithmetic`	Add, subtract, multiply or divide `ctx.spectrum` by a reference.	`numpy`	`1.0.1`
`extract_region`	Crop a spectrum to the wavelength window `[wavelength_min, wavelength_max]`.	`numpy`	`1.0.0`
`mask_range`	Flag every sample inside a wavelength window as masked.	`numpy`	`1.0.0`

Quality / SNR¶

Algorithm	What it does	Backend	Version
`compare_snr_methods`	Run every SNR estimator on `ctx.spectrum` and collect their numbers.	`numpy`	`1.0.1`
`snr_der`	Derivative-based SNR estimator (DER_SNR, Stoehr et al. 2008).	`numpy`	`1.0.0`
`snr_edge`	Estimate SNR from the flat, line-free regions at the spectrum's edges.	`numpy`	`1.0.1`
`snr_linear_fit`	Estimate SNR from the scatter around a linear fit of a continuum region.	`numpy`	`1.0.1`
`validate_bess_header`	Check a FITS header against the BeSS keyword contract.	`numpy`	`1.0.0`

Line detection¶

Algorithm	What it does	Backend	Version
`detect_lines`	Detect emission/absorption peaks, optionally matched to a named catalogue.	`scipy`	`1.2.1`

Line fitting¶

Algorithm	What it does	Backend	Version
`compare_line_fits`	Fit one spectral line with every profile in turn and pick the best one.	`scipy`	`1.0.0`
`equivalent_width`	Measure a line's equivalent width without assuming a profile shape.	`numpy`	`1.1.0`
`fit_gaussian_line`	Fit a single Gaussian (plus a linear continuum) to one spectral line.	`scipy`	`1.1.0`
`fit_lorentzian_line`	Fit a single Lorentzian (plus a linear continuum) to one spectral line.	`scipy`	`1.0.0`
`fit_voigt_line`	Fit a single Voigt profile (plus a linear continuum) to one spectral line.	`scipy`	`1.0.0`
`vr_ratio`	Violet/Red intensity ratio of a double-peaked emission line.	`scipy`	`1.0.1`

Corrections¶

Algorithm	What it does	Backend	Version
`air_to_vacuum`	Convert the wavelength axis from air to vacuum wavelengths.	`numpy`	`1.0.1`
`barycentric_correction`	Compute the barycentric (or heliocentric) correction and Julian date, and shift the spectrum.	`astropy`	`1.1.0`
`doppler_shift`	Doppler-shift the wavelength axis by a radial velocity.	`astropy`	`1.0.0`
`extinction_correct_easyspec`	Apply atmospheric extinction correction to `ctx.spectrum` via easyspec.	`easyspec`	`1.0.1`
`fit_telluric_scaling`	Fit the airmass that best matches a telluric template to `ctx.spectrum`.	`scipy`	`1.0.1`
`remove_telluric_division`	Remove telluric absorption by dividing the science spectrum by a reference.	`numpy`	`1.1.0`
`synth_telluric`	Generate a synthetic telluric transmission spectrum.	`numpy`	`1.0.1`
`vacuum_to_air`	Convert the wavelength axis from vacuum to air wavelengths.	`numpy`	`1.0.1`

Radial velocity¶

Algorithm	What it does	Backend	Version
`cross_correlate_rv`	Measure radial velocity by cross-correlation against a template spectrum.	`scipy`	`2.1.0`
`fit_keplerian_orbit`	Fit a single-companion Keplerian RV curve to a velocity time series.	`scipy`	`1.1.0`
`measure_radial_velocity`	Measure a radial velocity from the Doppler shift of a single line.	`scipy`	`1.1.0`
`redshift_lines`	Redshift z by per-line Gaussian fits against a list of rest-frame anchors.	`scipy`	`1.0.1`
`rv_precision_bouchy`	Compute the fundamental photon-noise limit on RV precision (Bouchy 2001).	`numpy`	`1.0.1`

Time series¶

Algorithm	What it does	Backend	Version
`lomb_scargle`	Compute a Lomb-Scargle periodogram and report the dominant period.	`astropy`	`1.1.1`
`phase_fold`	Phase-fold a light curve on a known period.	`numpy`	`1.0.1`

Stacking¶

Algorithm	What it does	Backend	Version
`merge_echelle_orders`	Merge every Spectrum1D in `ctx.spectra` into a single `ctx.spectrum`.	`numpy`	`1.0.1`
`stack_spectra`	Combine every spectrum in `ctx.spectra` into one stacked spectrum.	`numpy`	`2.0.0`

Embeddings¶

Algorithm	What it does	Backend	Version
`embed_band_power`	Embed a spectrum as the integrated flux in N adjacent wavelength bands.	`numpy`	`2.0.1`
`embed_continuum_subtracted`	Subtract the polynomial continuum, then embed the line residual.	`scipy`	`1.0.1`
`embed_lick_indices`	Embed a spectrum as the canonical Lick/IDS line-strength indices.	`numpy`	`2.0.1`
`embed_log_lambda`	Resample to a uniform log-λ grid, then embed.	`scipy`	`1.0.1`
`embed_pretrained`	Embed a spectrum with a local pre-trained PyTorch model.	`pytorch`	`1.0.1`
`embed_remote`	Embed a spectrum via a remote HTTPS inference endpoint.	`httpx`	`1.0.1`
`embed_spectrum`	Compute a fixed-length, L2-normalised embedding of a spectrum.	`scipy`	`1.2.1`
`embed_wavelets`	Embed a spectrum via a truncated discrete wavelet transform.	`pywavelets`	`2.0.1`

Nebular diagnostics¶

Algorithm	What it does	Backend	Version
`bpt_line_ratios`	Measure BPT line ratios + classify a galaxy (HII / Composite / Seyfert / LINER).	`scipy`	`1.1.0`
`oiii_electron_temperature`	Electron temperature Te (K) from the [O III] (λ4959+λ5007)/λ4363 ratio.	`scipy`	`2.0.0`
`sii_electron_density`	Electron density n_e (cm⁻³) from the [S II] λ6716/λ6731 ratio.	`scipy`	`1.1.0`

Kinematics¶

Algorithm	What it does	Backend	Version
`rotation_curve`	Projected long-slit rotation curve v_los(r) from Hα per slit offset.	`scipy`	`2.0.1`

Spectral classification¶

Algorithm	What it does	Backend	Version
`classify_template_chi2`	Spectral classification by χ² against a Pickles-style template atlas.	`scipy`	`1.1.0`

External catalogues¶

Algorithm	What it does	Backend	Version
`gaia_query`	Cone-search the Gaia archive around ICRS coordinates.	`astroquery`	`1.0.0`
`simbad_query`	Resolve an object name against SIMBAD and store the record in the context.	`astroquery`	`1.0.0`
`vizier_query`	Look up an object in VizieR — the CDS table service.	`astroquery`	`1.0.0`

Visualisation¶

Algorithm	What it does	Backend	Version
`plot_3d_surface_plotly`	Render every spectrum in `ctx.spectra` as one row of a 3D surface.	`plotly`	`1.0.0`
`plot_animation_plotly`	Render an animated Plotly figure that plays through `ctx.spectra`.	`plotly`	`1.0.0`
`plot_dynamic_spectrum`	Render every spectrum in `ctx.spectra` as one row of a 2D heatmap.	`plotly`	`1.0.0`
`plot_overlay_plotly`	Render every spectrum in `ctx.spectra` overlaid on one Plotly figure.	`plotly`	`1.0.0`
`plot_spectrum_plotly`	Render `ctx.spectrum` as a Plotly line figure.	`plotly`	`1.0.0`

Export¶

Algorithm	What it does	Backend	Version
`export_csv`	Export `ctx.spectrum` to a CSV file.	`numpy`	`1.0.0`
`export_fits`	Export `ctx.spectrum` to a FITS file.	`astropy`	`1.0.0`
`export_fits_bess`	Export `ctx.spectrum` as a BeSS / ARAS-compliant FITS image.	`astropy`	`1.0.0`
`export_hdf5`	Export `ctx.spectrum` to an HDF5 file.	`numpy`	`1.0.1`
`export_votable`	Export `ctx.spectrum` to a VOTable file (IVOA exchange format).	`astropy`	`1.0.0`

Advanced¶

Algorithm	What it does	Backend	Version
`aperture_photometry`	Differential aperture photometry on `ctx.image` (photutils).	`photutils`	`1.0.0`
`disentangle_sb2`	Separate the spectra of the two components of an SB2 spectroscopic binary.	`numpy`	`1.1.0`
`doppler_tomogram`	Doppler tomogram of a binary from N phase-resolved spectra.	`numpy`	`2.0.0`