Files
forgefirm/scripts/bench/temp_calibrate.py
T
ScottW514 9fae47cf14 The critical tier proven on a rising loop; the board temperatures watched
forgectrl pin 76115fd: the chassis LM75 and the supply sensor ride /status
as temps (degrees and a raw count), the engine ranges them over every run
session into one run-end line, and a critical fault that clears with its
session yields the reason to the standing hold.

Bench: critical_tier_drill.py (a bench tool now, registered as
critical-tier) sets the ceiling, the resume gate and the critical line a
few tenths above the live upstream reading and lets the engine's own
flow-check heater warm the loop through them inside one M8 session;
temp_calibrate.py gains supply-watch, supply-point and supply-fit for the
supply sensor against a thermometer on its heatsink, the fit shown beside
UAPI.md's unverified guess.

Catalog: cooling.gate-off checks the /status temps fields and the run-end
board-temperature line (the unit fake mirrors both, one new failure
case); cooling.critical-tier checks the reason after a faulted session.

Docs: CAMPAIGN-LOG entries for cooling.critical-tier on dev image
20260822154257 and the warm-loop drill (OVERTEMP at 10 s, CRITICAL at
14 s, the fault ending with the session); BRINGUP item 19, the facts bank
(board temperatures at idle), COOLING section 9, the bench README.
2026-08-22 12:56:40 -04:00

225 lines
8.3 KiB
Python

#!/usr/bin/env python3
"""Coolant temperature spot-check helper (runs on the board or from a
host; gfbench: GF_HOST).
The raw->Celsius conversion in UAPI.md is the factory B-equation (10k
B3380 NTC in a 10k divider behind a 1.3x gain stage, 10-bit ADC). This
tool collects reference points - a measured real temperature paired with
the machine's raw ADC readings - and fits a per-machine line to
cross-check that curve against a thermometer.
Usage:
temp_calibrate.py watch [seconds] live raw + current-formula C
(default 60 s)
temp_calibrate.py point <measured_C> [note] record a calibration point
temp_calibrate.py fit fit and print the calibration
temp_calibrate.py supply-watch [seconds] the same for the power supply
temp_calibrate.py supply-point <C> [note] sensor (pic/pwr_temp, raw):
temp_calibrate.py supply-fit thermometer on the heatsink vs
the raw count; UAPI.md's guess
raw * 0.08715 - 21 is shown
beside it. Points go to
supply_calibration.json.
Points accumulate in temp_calibration.json in the bench data directory
(gfbench.data_path: next to this script, or FORGETEST_BENCH_DATA). Take
at least two points as far apart in temperature as practical (e.g. cold
machine in the morning, and warm after a fan-off soak with the flow
heater on).
"""
import json
import os
import sys
import time
from gfbench import board, degc, data_path
STORE = data_path('temp_calibration.json')
SUPPLY_STORE = data_path('supply_calibration.json')
def supply_guess_c(raw):
"""UAPI.md's unverified guess for pic/pwr_temp."""
return raw * 0.08715 - 21
def supply_raw(samples=5, delay=1.0):
acc, n = 0, 0
for _ in range(samples):
out = board('cat /sys/glowforge/pic/pwr_temp').strip()
if out.isdigit():
acc += int(out); n += 1
time.sleep(delay)
return acc / n if n else None
def uapi_c(raw):
"""The UAPI.md factory conversion (B-equation NTC behind divider + gain)."""
return degc(raw)
def raws(samples=5, delay=1.0):
"""Average several readings of both sensors (ADC noise is real)."""
acc1, acc2, n = 0, 0, 0
for _ in range(samples):
out = board('cat /sys/glowforge/pic/water_temp_1 /sys/glowforge/pic/water_temp_2').split()
if len(out) == 2:
acc1 += int(out[0]); acc2 += int(out[1]); n += 1
time.sleep(delay)
return (acc1 / n, acc2 / n) if n else (None, None)
def load():
if os.path.exists(STORE):
with open(STORE) as f:
return json.load(f)
return {'points': []}
def save(data):
with open(STORE, 'w') as f:
json.dump(data, f, indent=2)
def fit(points, key):
"""Least-squares line: measured_C = slope * raw + offset."""
xs = [p[key] for p in points]
ys = [p['measured_c'] for p in points]
n = len(xs)
mx = sum(xs) / n
my = sum(ys) / n
den = sum((x - mx) ** 2 for x in xs)
if den == 0:
return None, None
slope = sum((x - mx) * (y - my) for x, y in zip(xs, ys)) / den
return slope, my - slope * mx
def supply_main(mode):
if mode == 'supply-watch':
seconds = float(sys.argv[2]) if len(sys.argv) > 2 else 60.0
print('pwr_temp raw guess-C (%.0f s)' % seconds)
t0 = time.time()
while time.time() - t0 < seconds:
r = supply_raw(1, 0)
if r is None:
print(' (no reading)')
else:
print(' %6.1f %.2f' % (r, supply_guess_c(r)), flush=True)
time.sleep(2)
return 0
if mode == 'supply-point':
try:
measured = float(sys.argv[2])
except (IndexError, ValueError):
print('supply-point needs the thermometer reading in C (value)')
return 2
note = sys.argv[3] if len(sys.argv) > 3 else ''
print('sampling pwr_temp (5 s)...', flush=True)
r = supply_raw()
if r is None:
print('no reading from the machine')
return 1
data = {'points': []}
if os.path.exists(SUPPLY_STORE):
with open(SUPPLY_STORE) as f:
data = json.load(f)
data['points'].append({'measured_c': measured, 'raw': r, 'note': note,
'when': time.strftime('%Y-%m-%d %H:%M:%S')})
with open(SUPPLY_STORE, 'w') as f:
json.dump(data, f, indent=2)
print('recorded: measured %.2f C raw=%.1f (guess %.1f C) (%d points total in %s)'
% (measured, r, supply_guess_c(r), len(data['points']), SUPPLY_STORE))
return 0
if mode == 'supply-fit':
if not os.path.exists(SUPPLY_STORE):
print('no points yet')
return 1
with open(SUPPLY_STORE) as f:
pts = json.load(f)['points']
if len(pts) < 2:
print('need at least 2 points (have %d)' % len(pts))
return 1
print('points:')
for p in pts:
print(' %6.2f C raw=%.1f guess %.1f C %s %s'
% (p['measured_c'], p['raw'], supply_guess_c(p['raw']), p['when'], p['note']))
slope, offset = fit(pts, 'raw')
if slope is None:
print('points share one raw value; no fit')
return 1
print('fit: degC = %.5f * raw + %.2f (UAPI.md guess: 0.08715 * raw - 21)' % (slope, offset))
worst = max(abs(p['measured_c'] - supply_guess_c(p['raw'])) for p in pts)
print('the guess is off by at most %.1f C at these points' % worst)
return 0
print(__doc__)
return 2
def main():
mode = sys.argv[1] if len(sys.argv) > 1 else 'watch'
if mode.startswith('supply-'):
return supply_main(mode)
if mode == 'watch':
seconds = float(sys.argv[2]) if len(sys.argv) > 2 else 60.0
print('raw1(down) raw2(up) uapi-C down/up (%.0f s)' % seconds)
t0 = time.time()
while time.time() - t0 < seconds:
r1, r2 = raws(1, 0)
if r1 is None:
print(' (no reading)')
else:
print(' %6.1f %6.1f %.2f / %.2f'
% (r1, r2, uapi_c(r1), uapi_c(r2)), flush=True)
time.sleep(2)
elif mode == 'point':
try:
measured = float(sys.argv[2])
except (IndexError, ValueError):
print('point needs the thermometer reading in C (value)')
return 2
note = sys.argv[3] if len(sys.argv) > 3 else ''
print('sampling raws (10 s)...', flush=True)
r1, r2 = raws()
if r1 is None:
print('no readings from the machine')
return 1
data = load()
data['points'].append({'measured_c': measured, 'raw1': r1, 'raw2': r2,
'note': note, 'when': time.strftime('%Y-%m-%d %H:%M:%S')})
save(data)
print('recorded: measured %.2f C raw1=%.1f raw2=%.1f (%d points total in %s)'
% (measured, r1, r2, len(data['points']), STORE))
elif mode == 'fit':
data = load()
pts = data['points']
if len(pts) < 2:
print('need at least 2 points (have %d)' % len(pts))
return 1
print('points:')
for p in pts:
print(' %6.2f C raw1=%.1f raw2=%.1f %s %s'
% (p['measured_c'], p['raw1'], p['raw2'], p['when'], p['note']))
span = max(p['measured_c'] for p in pts) - min(p['measured_c'] for p in pts)
print('\ntemperature span: %.2f C%s' % (span, ' (WARNING: <3 C span, fit is weak)' if span < 3 else ''))
for key, label in (('raw1', 'downstream (water_temp_1)'), ('raw2', 'upstream (water_temp_2)')):
slope, offset = fit(pts, key)
print('\n%s:' % label)
print(' fitted: C = raw * %.6f + %.4f' % (slope, offset))
for raw in (600, 650, 700, 750, 800):
print(' raw %3d -> fitted %6.2f C uapi %6.2f C diff %+.2f'
% (raw, raw * slope + offset, uapi_c(raw),
(raw * slope + offset) - uapi_c(raw)))
else:
print(__doc__)
return 1
return 0
if __name__ == '__main__':
sys.exit(main())