mirror of
https://github.com/lynchaos/ashvale-station.git
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kemal
98210bff8f
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.
180 lines
6.6 KiB
Python
180 lines
6.6 KiB
Python
# Copyright 2026 Kemal Yaylali
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Compensators and the Kalman bank.
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The inverse-property tests here exist because getting that algebra wrong has
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already cost this project twice: once on temperature, where a mismatched
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simulator injected 1.2 C of phantom noise floor, and once on humidity, where
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the correction ran the wrong way against a reference hygrometer.
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"""
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from __future__ import annotations
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import numpy as np
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import pytest
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from ashvale.estimation import HumidityCompensator, KalmanCV, ThermalCompensator
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from ashvale.physics import dew_point, saturation_vapour_pressure
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# ---------------------------------------------------------------- thermal
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def test_thermal_forward_model_is_the_exact_inverse_of_the_compensator():
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"""T_raw = (T + k*T_cpu)/(1+k) must invert T = T_raw - k(T_cpu - T_raw)."""
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for k, t_true, t_cpu in [(0.55, 19.0, 40.0), (0.26, 24.4, 40.2), (1.0, 5.0, 30.0)]:
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c = ThermalCompensator(k0=k, k_min=0.0, k_max=2.0)
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t_raw = (t_true + k * t_cpu) / (1.0 + k)
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assert c.compensate(t_raw, t_cpu) == pytest.approx(t_true, abs=1e-9)
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def test_thermal_calibration_moves_k_toward_the_truth():
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c = ThermalCompensator(k0=0.30, k_min=0.05, k_max=1.5)
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k_true, t_true, t_cpu = 0.62, 19.0, 41.0
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t_raw = (t_true + k_true * t_cpu) / (1.0 + k_true)
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before = abs(c.k - k_true)
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c.calibrate(t_raw, t_cpu, t_true)
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assert abs(c.k - k_true) < before
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def test_thermal_clamp_survives_a_mistyped_reference():
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c = ThermalCompensator(k0=0.55, k_min=0.15, k_max=1.20)
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for _ in range(50):
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c.calibrate(25.0, 40.0, -300.0) # absurd reference
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assert c.k_min <= c.k <= c.k_max
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def test_thermal_compensation_is_a_noop_without_a_gradient():
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c = ThermalCompensator(k0=0.8)
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assert c.compensate(21.0, 21.0) == pytest.approx(21.0)
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# and never amplifies when the CPU is cooler than the sensor
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assert c.compensate(21.0, 15.0) == pytest.approx(21.0)
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# ---------------------------------------------------------------- humidity
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def test_humidity_psychrometric_round_trip():
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"""The simulator's forward model must invert the compensator exactly."""
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rh_true, t_true, t_raw = 62.0, 19.0, 25.6
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rh_sensor = rh_true * float(saturation_vapour_pressure(t_true) /
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saturation_vapour_pressure(t_raw))
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hc = HumidityCompensator(psychrometric=True)
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assert hc.compensate(rh_sensor, t_raw, t_true) == pytest.approx(rh_true, abs=1e-6)
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def test_humidity_psychrometric_preserves_dew_point():
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"""Vapour pressure is the conserved quantity, so dew point must not move."""
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rh_sensor, t_raw, t_true = 60.0, 25.6, 19.0
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hc = HumidityCompensator(psychrometric=True)
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out = hc.compensate(rh_sensor, t_raw, t_true)
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assert float(dew_point(t_true, out)) == pytest.approx(float(dew_point(t_raw, rh_sensor)),
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abs=1e-6)
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def test_humidity_psychrometric_disabled_by_default():
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hc = HumidityCompensator()
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assert hc.compensate(60.0, 25.6, 19.0) == pytest.approx(60.0)
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def test_humidity_offset_converges_on_a_reference():
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"""The measured case: board reads 75.35% where the truth is 50.4%."""
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hc = HumidityCompensator()
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errors = []
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for _ in range(6):
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hc.calibrate(75.35, 27.94, 24.86, 50.4)
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errors.append(abs(hc.compensate(75.35, 27.94, 24.86) - 50.4))
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assert errors[-1] < errors[0]
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assert errors[-1] < 0.5
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def test_humidity_offset_is_clamped():
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hc = HumidityCompensator()
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for _ in range(50):
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hc.calibrate(50.0, 20.0, 20.0, 100.0)
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assert hc.off_min <= hc.offset <= hc.off_max
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def test_humidity_output_stays_in_range():
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hc = HumidityCompensator(offset=30.0)
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assert 0.0 <= hc.compensate(95.0, 20.0, 20.0) <= 100.0
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hc2 = HumidityCompensator(offset=-30.0)
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assert 0.0 <= hc2.compensate(5.0, 20.0, 20.0) <= 100.0
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def test_humidity_state_round_trips_through_dict():
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hc = HumidityCompensator(offset=-24.2, psychrometric=True)
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hc.calibrate(70.0, 25.0, 21.0, 50.0)
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back = HumidityCompensator.from_dict(hc.to_dict())
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assert back.offset == pytest.approx(hc.offset)
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assert back.psychrometric is hc.psychrometric
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assert back.n_calibrations == hc.n_calibrations
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# ---------------------------------------------------------------- kalman
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def test_kalman_covariance_stays_symmetric_and_psd():
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"""Joseph form exists precisely so this holds over a long run."""
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kf = KalmanCV(q=1e-6, r=0.05)
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rng = np.random.default_rng(7)
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for _ in range(20000):
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kf.update(20.0 + 0.05 * rng.normal(), 2.0)
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P = np.asarray(kf.P, dtype=float)
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assert np.allclose(P, P.T, atol=1e-12)
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assert np.all(np.linalg.eigvalsh(P) > -1e-12)
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def test_kalman_tracks_a_constant_and_reports_zero_rate():
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kf = KalmanCV(q=1e-8, r=0.01)
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for _ in range(2000):
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kf.update(15.0, 2.0)
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assert kf.level == pytest.approx(15.0, abs=1e-3)
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assert kf.rate == pytest.approx(0.0, abs=1e-5)
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def test_kalman_recovers_a_known_ramp_rate():
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kf = KalmanCV(q=1e-4, r=0.01)
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true_rate = 0.5 / 3600.0 # 0.5 units per hour
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for i in range(6000):
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kf.update(10.0 + true_rate * i * 2.0, 2.0)
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assert kf.rate * 3600.0 == pytest.approx(0.5, rel=0.05)
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def test_kalman_ignores_non_finite_measurements():
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kf = KalmanCV(q=1e-6, r=0.05)
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kf.update(20.0, 2.0)
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lvl_before = kf.level
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kf.update(float("nan"), 2.0)
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assert kf.level == pytest.approx(lvl_before)
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def test_kalman_nis_is_near_one_when_noise_matches_the_model():
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"""NIS is the honest self-check: consistent filter, NIS about 1."""
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r = 0.04
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kf = KalmanCV(q=1e-7, r=r)
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rng = np.random.default_rng(11)
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nis = []
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for i in range(4000):
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kf.update(18.0 + np.sqrt(r) * rng.normal(), 2.0)
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if i > 500:
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nis.append(kf.nis)
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assert 0.5 < float(np.mean(nis)) < 2.0
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def test_kalman_state_round_trips_through_dict():
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kf = KalmanCV(q=1e-6, r=0.05)
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for _ in range(50):
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kf.update(12.0, 2.0)
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back = KalmanCV.from_dict(kf.to_dict())
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assert back.level == pytest.approx(kf.level)
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assert back.rate == pytest.approx(kf.rate)
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