005ba07750a8c15a330d7568e1729391b19bd4b9
4
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 Claude
|
efa9e4084a |
Draw the whole catalogue, and build the aggregation the rest would need
Two things, one verified and one that cannot be. The render budget is now the whole catalogue: 68388 stars, one instanced draw call, which is what a GPU should be asked to do. The budget itself stays, because the catalogue is meant to grow past what any machine should draw at once — Gaia alone could contribute a million — and at that point the selection is what keeps the field legible rather than a grey wash. A `?stars=` override handles the machines that cannot, including the software rasterizer the end-to-end suite runs against, whose frame rate is two orders of magnitude below a real GPU's and which was measuring the rasterizer rather than the app. The aggregation is the second thing, and none of it has run. Every ESA, NOIRLab, SDSS and Euclid endpoint is unreachable from here — only GitHub raw is, which is why HYG and OpenNGC are the current sources. So this is infrastructure and a Gaia query written against the published DR3 schema, not data. What the framework encodes is that these surveys are not interchangeable. The distinction is not size but whether a catalogue knows how far away its objects are, because a 3D map cannot place a star it only has a direction for. Gaia is the only one of the five that can add stars here, because it is the only one that measures parallaxes. DECaPS2 has fifty times Gaia's object count and photometry alone — not one of its 3.32 billion objects can be placed in depth. Euclid's bulge is 8 kpc away, where a parallax is microarcseconds; its contribution would be imagery. SDSS-V and SAGA are keyed to stars something else already places, so they enrich rather than extend. Those roles are recorded as data the ETL prints, not as prose that can drift. Overlapping catalogues are reconciled on direction rather than on 3D proximity, which is the one non-obvious part. Two surveys agree on a star's direction to within an arcsecond and disagree on its distance by tens of per cent, so a star at 200 pc is 50 pc from itself between catalogues while being unmistakably the same object. Matching in 3D would need a tolerance so loose it swallowed real neighbours. The better parallax wins where both reach; where only one does, the star stays. Names become dense-with-holes with a source dictionary, because a survey catalogue has no proper names — writing "Gaia DR3 4472832130942575872" once per star would cost 25 MB per million to repeat what two adjacent fields already say. An empty entry costs three bytes and is regenerated on load. The Sun needed its own case in the merge: it sits at the origin, has no direction to compare, and appears in every catalogue. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01WaySiNst4HhDXBHnMy8p5G |
||
|
Claude
|
29fd92d118 |
Widen the star catalogue, and separate what is drawn from what is known
The map held 8750 stars within 50 pc and rendered 371 systems. Both were lower than they needed to be, for different reasons. The star catalogue was capped by its own encoding as much as by the cutoff: one JSON object per star, eight key names repeated each time, 157 bytes a star. At the range HYG actually reaches that is 17 MB to download and parse before the first frame. So the numbers move into two binary column stores — positions in stars.bin, which the GPU is handed verbatim, and id/magnitude/colour/spectral index in stars-meta.bin — and the JSON keeps only the strings, with 2600 distinct spectral classifications collapsed to a dictionary. The layout is defined once, in star-catalog.ts, and the ETL and the app both use it, so the writer and the reader cannot drift. The cutoff then goes to 250 pc: 68388 stars, 7.8x as many for 1.7x the bytes. That is where HYG's measurements stop rather than a round number — 98.6% of its rows are Hipparcos, whose parallaxes are good to about a milliarcsecond, so beyond 250 pc it would be plotting noise. Drawing all of them is a separate question from knowing them, and it is answered separately. The field draws a budget: every star inside 25 pc, because the nearest are faint red dwarfs and Proxima Centauri is magnitude 11, then the brightest of everything beyond. Search, navigation and the planet cross-reference still see the whole catalogue. A real GPU would draw all 68388 without noticing; the budget is for the machines that would not, and it is one constant. Systems were limited by something else entirely. The archive data already shipped named 4735 host stars and only 388 resolved, because the rest lay outside a 50 pc catalogue — and the cross-reference kept only its own result, so redoing it meant re-downloading an archive that is not reachable from here. Host coordinates are now stored with each planet, and the match is re-resolved at build time against whatever catalogue the run produced. Even name matching alone, which needs no coordinates and so works on the records already shipped, rescues 335 planets across 238 systems: 371 renderable systems become 609. Two selection rules were tuned for a 50 pc bubble and no longer fit. Tethers followed the Sun's nearest neighbours, which are a speck at this range, and now follow the brightest; labels were ranked by proximity, which named whatever sat nearest the middle of the screen, and are now ranked by brightness — so the view names Canopus, Achernar and Spica rather than a clump of catalogue designations. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01WaySiNst4HhDXBHnMy8p5G |
||
|
Claude
|
4aca223027 |
Regenerate the star catalogue, fixing 2331 names and 875 colours
Two ETL bugs, both fixed at the source and then re-run against HYG. Star ids,
ordering and positions are all unchanged, so stars.bin is byte-identical and
every exoplanet cross-reference still resolves.
Names. HYG's `gl` column already carries its own catalogue prefix ("Gl 581",
"GJ 3512"), unlike the bare numbers in `hd` and `hip`, so prefixing it again
produced 2331 of 8750 stars named "Gl GJ 1076". That corrupted three surfaces at
once: search, the on-screen labels, and exoplanet host-star name matching, which
compares normalised names and could never match "glgj1076" to "gj1076".
Colours. `Number(row['ci']) || 0` cannot tell a blank cell from a real zero, and
0 is a real B-V colour index meaning a hot blue-white A-type star. All 875
affected stars turned out to be blanks — the catalogue contains no genuine zero
inside the distance cutoff — so several hundred red dwarfs were rendering
blue-white. colorIndex is now `number | null` rather than defaulted, because any
numeric default is indistinguishable from a measurement.
Consumers resolve the gap from the spectral type instead. That needs real
parsing: HYG's `spect` column runs to 134 distinct spellings among the affected
stars alone, including a bare lowercase "m" for 354 of them, plus "k-m" ranges,
"dM4" luminosity prefixes and "K:" uncertainty flags. 622 of the 875 recover a
class this way — 497 of them M-class — and the remaining 253, which carry no
classification at all, fall back to neutral white.
The parse is anchored at the start of the string rather than scanning it. A scan
is the obvious implementation and is quietly wrong: the ETL writes the literal
"Unknown" for unclassified stars, that contains a K, and every one of those 253
would have been classified as an orange K-type. A test covers it.
Also lifts parseOptionalNumber out of fetchExoplanets into lib/csv, where both
fetchers now use it, and gives magnitude a faint default instead of 0 — no
current star is affected, but 0 would mean "as bright as Vega" and render an
unphotometered star as one of the largest points on the map.
Tests: 145 passing, up from 116, including the first coverage of
StarFieldRenderer. Build, both typechecks and the Playwright suite are green.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01WaySiNst4HhDXBHnMy8p5G
|
||
 Senrokai
|
d7e8ea1d4d |
@
Add star-map Angular app, ETL pipeline, and caveman plugin Angular 3D star map (galaxy/system/body views, Three.js rendering, navigation store) plus the NASA ETL tooling that builds the star, exoplanet and solar-system datasets, Playwright e2e suite, and the cs:caveman Claude Code plugin (command, agent, skill). Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> @ |