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.
74 lines
3 KiB
Python
74 lines
3 KiB
Python
"""Is the nucleus of NGC 5128 actually saturated, or was that a foreground star?
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The earlier claim - that the core clips at 65313 ADU in a single 300 s sub -
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came from taking the maximum inside a 300x300 px box centred on the frame. That
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box is wide enough to contain a bright foreground star, so the measurement
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proves only that SOMETHING in the middle of the frame is bright. This checks
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where the bright pixels actually are, and what the galaxy itself peaks at once
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stars are filtered out.
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"""
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import numpy as np
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from astropy import units as u
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from astropy.coordinates import SkyCoord
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from astropy.io import fits
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from astropy.wcs import WCS
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from scipy.ndimage import median_filter
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import layout
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SUB = layout.path("calibrated-T32-qisback-NGC5128-20260721-190133"
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"-Luminance-BIN2-W-300-002.fit")
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MASTER = layout.path("master-Luminance.fit")
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# NGC 5128's nucleus, from SIMBAD, not from "the middle of the frame".
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NUCLEUS = SkyCoord("13h25m27.6s", "-43d01m08.8s")
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with fits.open(MASTER) as hd:
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wcs = WCS(hd[0].header, naxis=2)
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nx_c, ny_c = wcs.world_to_pixel(NUCLEUS)
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print(f"nucleus lands at master pixel ({nx_c:.1f}, {ny_c:.1f})")
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data = fits.getdata(SUB).astype(np.float32)
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ny, nx = data.shape
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print(f"single sub {nx} x {ny}, global max {data.max():.0f} ADU")
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# Where are the saturated-ish pixels?
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ys, xs = np.where(data > 60000)
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print(f"{len(xs)} pixels above 60000 ADU")
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if len(xs):
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# Cluster them crudely by proximity to see how many distinct objects.
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print(f" x range {xs.min()}-{xs.max()}, y range {ys.min()}-{ys.max()}")
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cx, cy = nx / 2.0, ny / 2.0
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d = np.hypot(xs - cx, ys - cy)
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print(f" distance from frame centre: min {d.min():.0f} px, "
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f"median {np.median(d):.0f} px, max {d.max():.0f} px")
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# The brightest pixel specifically
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iy, ix = np.unravel_index(np.argmax(data), data.shape)
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print(f" brightest pixel at ({ix}, {iy}), "
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f"{np.hypot(ix - cx, iy - cy):.0f} px from frame centre")
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# The galaxy's own peak: median filter removes stars, which are small, while
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# leaving the smooth galaxy light essentially untouched.
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h = 400
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y0, y1 = int(ny / 2) - h, int(ny / 2) + h
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x0, x1 = int(nx / 2) - h, int(nx / 2) + h
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core = data[y0:y1, x0:x1]
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smooth = median_filter(core, size=15)
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print(f"\ninner {2*h}x{2*h} px box:")
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print(f" raw max {core.max():9.1f} ADU")
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print(f" median-filtered max {smooth.max():9.1f} ADU <- galaxy light")
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iy, ix = np.unravel_index(np.argmax(smooth), smooth.shape)
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print(f" galaxy peak at frame pixel ({x0+ix}, {y0+iy})")
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# How many pixels of the median-filtered (star-free) galaxy are near clipping?
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for lvl in (30000, 50000, 60000):
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print(f" star-free pixels above {lvl}: {(smooth > lvl).sum()}")
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# And in the master stack.
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mdata = fits.getdata(MASTER).astype(np.float32)
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mcore = mdata[y0:y1, x0:x1]
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msmooth = median_filter(mcore, size=15)
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print(f"\nmaster stack inner box: raw max {mcore.max():.1f}, "
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f"star-free max {msmooth.max():.1f} ADU")
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print(f" master 99.995th percentile (the stretch white point) "
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f"{np.percentile(mdata, 99.995):.1f} ADU")
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