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- LIGHTBURN.md: mandatory "Before you cut" safety section; the walkthrough now reflects the firing machine (dry runs need the layer output off or M5; live first-cut instructions); the homing entry documents homing_mode and the gfcloud method; the machine address is a placeholder. - README.md: condensed safety section linking the full text and the regulatory notes. - INSTALL.md: "Regulatory and legal" section ahead of the install steps; routine updates route through the panel updater rather than the installer. - BRINGUP.md: the release signing key is described as held offline (no on-disk path); bench address and credential notes removed; Next-work item 7 corrected (the installer embeds the production release key); status entry for audit remediation Phases 0-1; the GATE A kernel drills join the pending image-flash checklist. - bench scripts: the target host comes from GF_HOST (or argv) instead of a hardcoded address. - laser_stream_test.py: per-session controller runs with a hermetic cooling-verdict publisher; new assertions that every stream terminates with FIRE clear (including M3 held to stream end) and that no FIRE bit rides a zero-step gap; a cycle-churn session exercises the stop/start seams. Audit findings D-1, D-2, D-3, D-5, D-10, D-12, B-10, and the harness half of D-4/G-1.
140 lines
4.8 KiB
Python
140 lines
4.8 KiB
Python
#!/usr/bin/env python3
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"""Coolant temperature spot-check helper (runs on Windows, reads the
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board over ssh).
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The raw->Celsius conversion in UAPI.md is the factory B-equation (10k
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B3380 NTC in a 10k divider behind a 1.3x gain stage, 10-bit ADC). This
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tool collects reference points - a measured real temperature paired with
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the machine's raw ADC readings - and fits a per-machine line to
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cross-check that curve against a thermometer.
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Usage:
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temp_calibrate.py watch live raw + current-formula C
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temp_calibrate.py point <measured_C> record a calibration point
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temp_calibrate.py fit fit and print the calibration
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Points accumulate in temp_calibration.json next to this script. Take at
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least two points as far apart in temperature as practical (e.g. cold
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machine in the morning, and warm after a fan-off soak with the flow
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heater on).
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"""
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import json
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import math
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import os
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import subprocess
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import sys
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import time
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HOST = os.environ.get('GF_HOST')
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if not HOST:
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raise SystemExit('set GF_HOST to the machine IP address')
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STORE = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'temp_calibration.json')
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def uapi_c(raw):
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"""The UAPI.md factory conversion (B-equation NTC behind divider + gain)."""
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adc_f = 1024.0 * 1.3
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if raw <= 0 or raw >= adc_f:
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return float('nan')
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rinf = 10000.0 * math.exp(-3380.0 / 298.15)
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r = 10000.0 / (adc_f / raw - 1.0)
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return 3380.0 / math.log(r / rinf) - 273.15
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def board(cmd):
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r = subprocess.run(['wsl', '-d', 'forge-yocto', '--', 'ssh',
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'-o', 'PreferredAuthentications=none',
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'root@' + HOST, cmd],
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capture_output=True, text=True, timeout=30)
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return r.stdout.strip()
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def raws(samples=5, delay=1.0):
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"""Average several readings of both sensors (ADC noise is real)."""
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acc1, acc2, n = 0, 0, 0
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for _ in range(samples):
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out = board('cat /sys/glowforge/pic/water_temp_1 /sys/glowforge/pic/water_temp_2').split()
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if len(out) == 2:
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acc1 += int(out[0]); acc2 += int(out[1]); n += 1
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time.sleep(delay)
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return (acc1 / n, acc2 / n) if n else (None, None)
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def load():
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if os.path.exists(STORE):
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with open(STORE) as f:
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return json.load(f)
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return {'points': []}
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def save(data):
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with open(STORE, 'w') as f:
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json.dump(data, f, indent=2)
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def fit(points, key):
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"""Least-squares line: measured_C = slope * raw + offset."""
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xs = [p[key] for p in points]
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ys = [p['measured_c'] for p in points]
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n = len(xs)
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mx = sum(xs) / n
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my = sum(ys) / n
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den = sum((x - mx) ** 2 for x in xs)
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if den == 0:
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return None, None
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slope = sum((x - mx) * (y - my) for x, y in zip(xs, ys)) / den
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return slope, my - slope * mx
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def main():
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mode = sys.argv[1] if len(sys.argv) > 1 else 'watch'
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if mode == 'watch':
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print('raw1(down) raw2(up) uapi-C down/up (ctrl-C to stop)')
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while True:
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r1, r2 = raws(1, 0)
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print(' %6.1f %6.1f %.2f / %.2f'
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% (r1, r2, uapi_c(r1), uapi_c(r2)))
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time.sleep(2)
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elif mode == 'point':
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measured = float(sys.argv[2])
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note = sys.argv[3] if len(sys.argv) > 3 else ''
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print('sampling raws (10 s)...')
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r1, r2 = raws()
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data = load()
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data['points'].append({'measured_c': measured, 'raw1': r1, 'raw2': r2,
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'note': note, 'when': time.strftime('%Y-%m-%d %H:%M:%S')})
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save(data)
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print('recorded: measured %.2f C raw1=%.1f raw2=%.1f (%d points total)'
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% (measured, r1, r2, len(data['points'])))
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elif mode == 'fit':
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data = load()
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pts = data['points']
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if len(pts) < 2:
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print('need at least 2 points (have %d)' % len(pts))
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return 1
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print('points:')
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for p in pts:
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print(' %6.2f C raw1=%.1f raw2=%.1f %s %s'
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% (p['measured_c'], p['raw1'], p['raw2'], p['when'], p['note']))
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span = max(p['measured_c'] for p in pts) - min(p['measured_c'] for p in pts)
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print('\ntemperature span: %.2f C%s' % (span, ' (WARNING: <3 C span, fit is weak)' if span < 3 else ''))
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for key, label in (('raw1', 'downstream (water_temp_1)'), ('raw2', 'upstream (water_temp_2)')):
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slope, offset = fit(pts, key)
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print('\n%s:' % label)
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print(' fitted: C = raw * %.6f + %.4f' % (slope, offset))
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for raw in (600, 650, 700, 750, 800):
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print(' raw %3d -> fitted %6.2f C uapi %6.2f C diff %+.2f'
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% (raw, raw * slope + offset, uapi_c(raw),
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(raw * slope + offset) - uapi_c(raw)))
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else:
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print(__doc__)
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return 1
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return 0
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if __name__ == '__main__':
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sys.exit(main())
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