orca.transform.spectrum_v3

Dynamic-spectrum helpers (v3) * 100% read-only MeasurementSet access * Optionally respects MS FLAG column * bcal optional; if present, used at native resolution (NO rebin) * NO spectral averaging: 192 chans/subband → 16 SPWs → 3072 total chans

Attributes

`logger`
`N_CHAN_OUT`
`REDIS_URL`
`REDIS_EXPIRE_S`
`REDIS_KEY_PREFIX`
`ROW_NUMS`

Functions

`dynspec_map_v3`(→ List[_SnapshotSpectrumV3])	Map step on a SINGLE MS:
`dynspec_reduce_v3`(→ None)	Reduce step:

Module Contents

orca.transform.spectrum_v3.logger[source]

orca.transform.spectrum_v3.N_CHAN_OUT = 192[source]

orca.transform.spectrum_v3.REDIS_URL[source]

orca.transform.spectrum_v3.REDIS_EXPIRE_S = 36000[source]

orca.transform.spectrum_v3.REDIS_KEY_PREFIX = 'spec-v3-'[source]

orca.transform.spectrum_v3.ROW_NUMS = [('LWA-128&LWA-160', 54282), ('LWA-048&LWA-051', 33335), ('LWA-018&LWA-237', 30360),...[source]

orca.transform.spectrum_v3.dynspec_map_v3(subband_no: int, scan_no: int, ms: str, bcal: str | None = None, use_ms_flags: bool = True) → List[_SnapshotSpectrumV3][source]

Map step on a SINGLE MS:

Reads DATA & FLAG (cross-correlations only)
Optionally applies bcal at native resolution (192 channels) — NO rebin
Stores incoherent-sum and selected-baseline spectra in Redis

Returns JSONable _SnapshotSpectrumV3 list (for the reducer).

orca.transform.spectrum_v3.dynspec_reduce_v3(spectra: Iterable[List[_SnapshotSpectrumV3]], start_ts: datetime.datetime, out_dir: str) → None[source]

Reduce step:

Gathers Redis blobs from dynspec_map_v3 outputs
Builds 4×(time×freq) cubes per type, freq = 192×16 = 3072
Writes FITS into {out_dir}/{type}/{DATE}-{corr}.fits