Move the processing code under pipeline/

Preparing to merge this repository into a combined astrophotography
repo. session-scripts/ becomes pipeline/ because the scripts import
layout.py from their own directory and must stay together, and because
'pipeline' says what it is rather than how it came about. observing/
stays at the top level: observing plans are not processing code.

pipeline/gaia_colours.py

@@ -0,0 +1,49 @@
+"""Fetch Gaia DR3 BP-RP colours for the field, cached for colour calibration.
+
+The first composite balanced colour on "the average field star is grey", which
+is a workable fudge but is biased by whatever mix of spectral types the field
+happens to contain. With real colours available, a much better anchor exists:
+pick the stars that actually ARE solar-coloured (BP-RP near 0.82) and force
+those to neutral. That is the same principle as a photometric colour
+calibration, without needing the filters' response curves.
+
+ESA's archive was down during this work, so this uses the VizieR mirror of the
+identical catalogue.
+"""
+import os
+
+import numpy as np
+from astropy import units as u
+from astropy.coordinates import SkyCoord
+
+import layout
+
+OUT = layout.SESSION
+CACHE = layout.path("_gaia_colours.npz")
+CENTRE = SkyCoord("13h25m27.37s", "-43d01m10.9s")
+
+if os.path.exists(CACHE):
+    z = np.load(CACHE)
+    print(f"cached: {len(z['ra'])} stars with colours")
+else:
+    from astroquery.vizier import Vizier
+    v = Vizier(columns=["RA_ICRS", "DE_ICRS", "Gmag", "BP-RP"],
+               column_filters={"Gmag": "<18", "BP-RP": ">-1"},
+               row_limit=50000)
+    res = v.query_region(CENTRE, radius=0.45 * u.deg, catalog="I/355/gaiadr3")
+    t = res[0]
+    ok = ~np.isnan(np.asarray(t["BP-RP"], float))
+    ra = np.asarray(t["RA_ICRS"], float)[ok]
+    dec = np.asarray(t["DE_ICRS"], float)[ok]
+    g = np.asarray(t["Gmag"], float)[ok]
+    bprp = np.asarray(t["BP-RP"], float)[ok]
+    np.savez_compressed(CACHE, ra=ra, dec=dec, g=g, bprp=bprp)
+    print(f"fetched {len(ra)} stars with BP-RP")
+    z = dict(ra=ra, dec=dec, g=g, bprp=bprp)
+
+bprp = z["bprp"]
+solar = np.abs(bprp - 0.82) < 0.15
+print(f"BP-RP range {bprp.min():.2f} to {bprp.max():.2f}, "
+      f"median {np.median(bprp):.2f}")
+print(f"solar-coloured stars (BP-RP 0.67-0.97): {solar.sum()}")
+print(f"G range {z['g'].min():.1f} to {z['g'].max():.1f}")