Spectral segment

Spectral segment#

A segment is one wavelength chunk of the spectrum.
PySME is segment-aware by design: most spectral arrays are stored as a list-like object with one entry per segment.

Why segments exist#

Segments are useful when:

  • your observation is naturally split into orders/chunks

  • different chunks have different wavelength sampling/resolution/radial velocity.

  • you want to process only part of the spectrum in synthesis/solve

How segments are defined#

PySME can get segment information from either:

  • sme.wave: explicit wavelength arrays (recommended when available)

  • sme.wran: only segment boundaries [[w0_start, w0_end], [w1_start, w1_end], ...]

If sme.wave exists, it effectively defines segment boundaries.
If only sme.wran is given, PySME synthesizes each segment within those ranges.

Segment-aware inputs#

Typical segment-aware fields are:

  • wave

  • spec

  • uncs

  • mask

  • synth

  • cont

  • wint (optional transfer grid)

  • vrad

  • cscale

You can pass these as:

  • a single 1D array for one segment

  • a list of arrays for multiple segments

Parameters that are not segmented#

Some model parameters are global (single value for all segments), e.g.:

  • vmic

  • vmac

  • vsini

Some are scalar-or-per-segment, e.g.:

  • ipres: can be one value or one value per segment

  • vrad: handled per segment, depending on vrad_flag

Choosing which segments to run#

Both synthesize_spectrum(...) and solve(...) accept a segments argument.

  • segments="all": run all segments

  • segments=[0, 2, ...]: run selected segments only

Invalid indices raise an error.
Segments that are fully masked as bad pixels are skipped automatically.

Practical notes#

  • Keep segment ordering consistent across all segment-aware inputs.

  • If you provide per-segment arrays, lengths must match within each segment.

  • For simple single-chunk workflows, using one 1D wave array is enough.

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