recompute replayed the Kalman over stored rows at their own spacing while q
stays tuned for the live 2 s cadence. Q scales with dt^3, so at the 30 s
persist interval the process noise was 3375x too large and the filter tracked
noise instead of smoothing: it wrote indoor temperature rates of +/-20 C/h into
the history. This is the exact trap DESIGN.md section 2 documents for
simulate.py, which does scale q, and I walked into it anyway. Now rescaled per
step, because tiering means the stored cadence is not constant. Mean |rate| on
the real board dropped to 2.73 C/h; what remains above 10 is the filter's
warm-up transient in the first four samples, which is honest.
Readout scene puts the actual numbers between the animations: temperature,
humidity, sea-level pressure and the signed three hour forecast, each in its
channel colour, scrolling. Text is drawn whole-pixel on purpose. Everything
else here is sub-pixel and that is what makes it look good, but splitting a
3 px glyph across two columns halves its peak and smears it illegible. Crisp
beats smooth when the thing has to be read.
site.environment and site.enclosure record where the sensor lives and what has
changed around it, with POST /api/environment to change them at runtime. This
is not cosmetic: closing a door changes how strongly the sensor couples to
outside, which is a regime change in the process the heads are fitting, and at
lambda 0.9985 they carry about 55 hours of memory. Left alone they keep
predicting the old room for two days. Page-Hinkley would notice eventually but
needs matured forecasts to do it, which at the long horizons is the same two
days. So the endpoint marks a discontinuity and queues a retrain.
24 fps costs about 11% of one core on a Zero 2 W, measured on the board. That
is a reasonable default for something you look at, but it is a decorative load
sharing a 512 MB machine with the forecaster, so it should be the owner's
choice. server.led_fps is clamped to 4..30.
Particle fall speed now divides by the configured rate rather than the module
constant, so rain falls at the same real-world speed whatever the frame rate,
instead of slowing down when you turn the frame rate down.
1. POST /api/recompute re-derives every compensated column from the untouched
raw values, removing the step a calibration otherwise leaves through the
history. Possible because temp_raw, cpu_temp and hum are never overwritten.
Idempotent by construction and tested per row: 0 of 6051 rows change on a
second run. 6069 rows in 0.25 s here, so a few seconds on the Pi.
2. Calibration now emits a 'discontinuity' event alongside the calibration log,
so downstream views can find the boundary without parsing prose.
3. Vendored Tailwind, Chart.js, hammer, the zoom plugin, KaTeX with its 20
woff2 faces, and both Google fonts into ashvale/static, served by the
station. 1.4 MB. Verified with every non-localhost request aborted in the
browser: zero external requests, equations still render, fonts still load.
The dashboard no longer needs internet.
4. 54 pytest cases over the pure numerics: physics closed forms and round
trips, both compensator inverse properties, the Kalman covariance
invariants and NIS consistency, the RLS trace cap under a deliberately
unexcited regressor, conformal coverage, and the Zambretti ordering. Wired
into CI after the seed step so the recompute cases have history. Writing
them caught my own sign error on the conformal update: a hit raises alpha
and narrows the band, which reads backwards until you follow it through.
5. Stats for Nerds gains the condition number of each head's covariance, a
standardised innovation histogram per Kalman filter from a bounded 600
sample ring buffer, and a reliability strip of realised against nominal
coverage. All arithmetic on data already in memory.
6. OutdoorProbe reads a DS18B20 over the kernel 1-Wire driver, no new
dependency. Polled on its own slower cadence because the sensor blocks for
up to 750 ms during conversion, which would eat a third of the 2 s sample
budget. Rejects the 85000 power-on sentinel and out-of-range values, and
reports age so a dead probe cannot masquerade as fresh.
Shutdown hang, the cause of every restart taking systemd's full 90 s timeout
and ending in SIGKILL: /api/stream looped forever with no disconnect or
shutdown check, so an open dashboard was an in-flight request that never
completed and uvicorn's graceful shutdown waited on it. Reproduced cleanly:
with no stream client the process stopped in 2 s, with one open client it was
still running after 15 s. Fixed by bounding timeout_graceful_shutdown, and by
having the generator exit on client disconnect and on a shutdown event. Now
7 s with a client attached.
Equations rendered as blank boxes whenever the KaTeX CDN was unreachable,
which is a real case for a Pi on wifi. The elements carried the TeX only in a
data attribute, so with no KaTeX there was nothing to display. The source is
now written into the element as text first and KaTeX replaces it, so it
degrades to readable TeX. Verified by aborting the katex request. A window
load handler re-runs typesetting for a slow CDN. The code comment claiming
this fallback already existed was wrong and is corrected.
New Stats for Nerds tab over a new read-only /api/nerd endpoint: Kalman NIS
and covariance per signal, both compensators, all 18 RLS heads with trace(P)
against the cap, |theta|, EWMA RMSE, conformal alpha against target, realised
coverage and ensemble weights, plus per-head feature attribution over the 33
standardised weights, the Mahalanobis and Page-Hinkley detector state,
climatology harmonics and precipitation coefficients.
Methods overhaul: KaTeX now renders the equations. They were previously passed
through .replace(/[{}\\]/g,' '), which stripped every brace and backslash and
turned real mathematics into mush. Stages 2, 3, 5, 6 and 7 gained full
derivations (RLS normal equations and the trace cap, Joseph-form Kalman with
NIS, adaptive conformal with its coverage limit, ridge harmonic regression with
anomaly decay) and a per-symbol legend rendered inline.
Conditions ahead gains weather icons chosen from measured cloud index, solar
elevation and temperature rather than the barometric class alone, so a fine
barometer under overcast draws a cloud and after sunset draws a moon. Snow is
selected on temperature.
Seven day outlook moves to the top of Live, directly under the nav. Tab renamed
Models and Calibration.
Verified in Chromium at 1600x900: Live, History, Models and Nerd all report
zero scrollbars, zero clipping, no page scroll, zero console errors. Methods
keeps its documented prose scroller. Backtest numerically unchanged.
Seven day outlook moves from History to Live, which now runs four rows.
Conditions ahead tightened so the Live column no longer needs a scroller.
Adds HumidityCompensator: an additive RH offset estimated by one-step RLS from
a trusted hygrometer, clamped to +/-35%, persisted, exposed at
POST /api/calibrate/humidity and on the renamed Models and calibration tab.
It also implements the psychrometric term (RH moved from element temperature
onto air temperature via conserved vapour pressure) but leaves it OFF by
default. The thermal argument predicts a hot element reads low; measured
against a reference hygrometer this board read 75.4% where the truth was
50.4%, so it reads HIGH and that correction would push it the wrong way. When
the flag is enabled, simulate.py applies the exact inverse, per the
simulator/compensator trap in DESIGN.md section 2.
Models pane rebuilt: the scorecard is one column per target so all 18 heads
are visible, and no panel on the tab uses an internal scroller. Verified in
Chromium at 1600x900: Live, History and Models all report zero scrollbars,
zero clipping, no page scroll, zero console errors. Backtest is numerically
identical to the previous commit, confirming the humidity work is a no-op
while the flag is off.
kemal