laurence
5286a2e81b
The scripts that processed the NGC 5128 session of 2026-07-21 previously lived inside the data directory and addressed it with absolute paths. Code and data are now separated: the code lives here, and a session is located at runtime through the ASTRO_SESSION environment variable. layout.py is what makes that work. It maps a FILENAME to the subdirectory that file belongs in, using the same rules the session directories are organised with, so a script can go on asking for 'master-Red.fit' or '_stars.npz' without any call site knowing the directory structure. Anything unrecognised resolves to the session root, which is visible and correctable rather than silently wrong. restructure.py reorganises a flat session directory into that layout. It is idempotent and dry-run by default. The 50 session scripts are kept as they were run rather than tidied into a library. They were written in sequence as the work went along, several of them by parallel agents, and they show it - but they are the honest provenance of a published set of results, and the productionised pipeline should be able to reproduce those results exactly. Verified before committing: all 51 files compile without warnings, and verify_core.py, closeup.py and triptych.py were run end to end against the reorganised session, correctly finding inputs across calibrated/, stacks/masters/ and final/ and writing outputs back to the right places.
146 lines
6.6 KiB
Python
146 lines
6.6 KiB
Python
"""Write the final flagged-object CSVs, with an identification and verdict
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attached to every row.
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Two files are produced.
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mo-flagged-objects.csv is the short list: the six sources that survived every
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cut of the transient search, plus the (zero) moving-object candidates, each
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with the identification established from published catalogues and an explicit
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assessment. This is the file to read.
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mo-transient-candidates.csv (written by mo_transient.py) is the long list of
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all 567 catalogue non-matches, kept for completeness. Almost all of them are
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faint objects below the depth at which Gaia DR3 and SkyMapper DR2 are complete
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against this galaxy, and are not individually assessed.
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"""
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import csv
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import os
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import numpy as np
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import mo_common as C
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# Identifications from cross-matching against published Centaurus A cluster
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# catalogues (Woodley+2007 J/AJ/134/494 and others), SIMBAD, NED and a blanket
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# VizieR cone search. Separations quoted are to the matched catalogue entry.
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IDENT = {
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"201.672625": dict(
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name="WHH-31", otype="GlC (SIMBAD)", sep=0.10,
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refs="Woodley+2007; Hughes+2021 #86; SCABS GC prob=1.0",
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cat_phot="V=19.50 B=20.44 R=18.94",
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assessment="Known Centaurus A globular cluster. Not a transient."),
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"201.500583": dict(
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name="pff_gc-081", otype="GlC (SIMBAD)", sep=0.32,
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refs="Woodley+2007; Hughes+2021 ID 248669; SCABS GC prob=1.0",
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cat_phot="V=19.34 B=20.17 R=18.80",
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assessment="Known Centaurus A globular cluster. Not a transient."),
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"201.441625": dict(
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name="WHH-24", otype="GlC (SIMBAD)", sep=0.19,
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refs="Woodley+2007; SCABS GC prob=1.0",
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cat_phot="V=19.63 B=20.43 R=19.12",
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assessment="Known Centaurus A globular cluster. Not a transient."),
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"201.407000": dict(
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name="resolved object at the position of CAVS 210 / "
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"Gaia DR3 6088701636326983168",
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otype="resolved (1.34x PSF, elongation 1.40); not a point source",
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sep=1.32,
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refs="de Jong+2008 J/A+A/478/755 (CAVS 210); DENIS 1996-2001; "
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"Swift/UVOT SSC (12 ObsIDs); XMM-OM ~2020; VHS DR4; KS4 DR1",
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cat_phot="Gaia DR3 G=21.03 at 1.32\" (point source); "
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"DENIS I=18.23 J=16.44; UVOT U=18.2-18.6",
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assessment="NOT a transient and NOT a brightening; the 2.8 mag "
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"difference from Gaia is a measurement artefact. The "
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"source is resolved (r50 = 2.96 px vs PSF 2.21 px, "
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"elongation 1.40), so an integrated aperture magnitude is "
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"not comparable with Gaia's point-source G; Gaia has no "
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"entry at all for the extended object and nothing within "
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"25\" brighter than G=19.8. It is steady over the session "
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"(rms 0.066 mag vs 0.039 for comparison stars) and is "
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"present on 1990s DSS2 red plates at the same brightness "
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"relative to its neighbours (implied change +0.26 mag). "
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"Even the PSF-scaled 2 px core gives G=18.63. See "
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"notes-transient-search.md section 4.3 and NGC5128-mo-cavs210.png."),
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"201.303542": dict(
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name="WHH-10", otype="GlC (SIMBAD)", sep=0.23,
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refs="Woodley+2007; SCABS GC prob=1.0",
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cat_phot="V=19.57 B=20.36 R=19.07",
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assessment="Known Centaurus A globular cluster. Not a transient."),
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"201.256708": dict(
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name="pff_gc-029 / GC0103", otype="GlC (SIMBAD)", sep=0.23,
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refs="Woodley+2007; Peng+2004; Spitler+2008; Hughes+2021; Dumont+2022",
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cat_phot="V=19.37 B=19.75 R=19.06 Ks=14.69",
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assessment="Known Centaurus A globular cluster, well studied. "
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"Not a transient."),
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}
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def ident_for(ra):
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for k, v in IDENT.items():
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if abs(float(k) - ra) < 1e-4:
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return v
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return dict(name="", otype="", sep=np.nan, refs="", cat_phot="",
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assessment="UNIDENTIFIED - needs follow-up")
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FIELDS = ["search", "ra_hms", "dec_dms", "ra_deg", "dec_deg", "x_ref",
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"y_ref", "g_mag_this_image", "snr", "r50_over_psf", "n_subs",
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"snr_R", "snr_G", "snr_B", "dist_from_cenA_arcmin",
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"identification", "object_type", "match_sep_arcsec",
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"catalogue_photometry", "references", "assessment"]
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def main():
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rows = []
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vet = list(np.load(os.path.join(C.OUT, "_mo_vetted.npy"),
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allow_pickle=True))
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vet.sort(key=lambda r: r["dist_cenA_arcmin"])
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for r in vet:
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d = ident_for(r["ra_deg"])
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rows.append({
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"search": "transient",
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"ra_hms": r["ra_hms"], "dec_dms": r["dec_dms"],
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"ra_deg": r["ra_deg"], "dec_deg": r["dec_deg"],
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"x_ref": r["x"], "y_ref": r["y"],
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"g_mag_this_image": r["g_mag"], "snr": r["snr"],
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"r50_over_psf": r["r50_over_psf"], "n_subs": r["n_subs"],
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"snr_R": r["snr_R"], "snr_G": r["snr_G"], "snr_B": r["snr_B"],
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"dist_from_cenA_arcmin": r["dist_cenA_arcmin"],
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"identification": d["name"], "object_type": d["otype"],
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"match_sep_arcsec": d["sep"],
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"catalogue_photometry": d["cat_phot"],
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"references": d["refs"], "assessment": d["assessment"]})
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# Moving-object search: zero candidates, but the file should say so
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# explicitly rather than being empty.
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mo = os.path.join(C.OUT, "mo-moving-candidates.csv")
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nmov = 0
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if os.path.exists(mo):
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with open(mo) as fh:
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nmov = max(0, sum(1 for _ in fh) - 1)
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if nmov == 0:
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rows.append({f: "" for f in FIELDS} | {
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"search": "moving-object",
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"identification": "(no candidates)",
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"assessment": "Blind tracklet search over the 12 luminance subs "
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"returned 0 candidates. Sensitivity measured by "
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"synthetic injection: 50% recovery at G=18.9 for "
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"8-40 arcsec/hr; no sensitivity below ~4 arcsec/hr. "
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"The only catalogued minor planet within 30' of the "
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"pointing, (427494) 2002 BK26 at V=21.7, fell 2.4' "
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"outside the frame."})
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out = os.path.join(C.OUT, "mo-flagged-objects.csv")
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with open(out, "w", newline="", encoding="utf-8") as fh:
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w = csv.DictWriter(fh, fieldnames=FIELDS)
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w.writeheader()
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w.writerows(rows)
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print(f"wrote {out} ({len(rows)} rows)")
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for r in rows:
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print(f" {r['search']:14s} {r['identification'][:44]:44s} "
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f"{str(r['g_mag_this_image']):>6s} "
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f"{r['assessment'][:60]}")
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if __name__ == "__main__":
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main()
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