Reanchoring used to only happen when a user confirmed a WAIT_USER step, so anything the schedule advanced through on its own (a ramp reaching target, a hold timing out) left the forecast showing a stale, increasingly wrong prediction once reality diverged from it. _reanchor_forecast() now fires from on_step_changed() on every real transition, splicing in a fresh simulation anchored at the real current temperature/elapsed time instead. Also fixes two bugs surfaced while testing that change: - estimate()'s early-return for an empty/not-yet-loaded schedule still returned the old 4-tuple shape, crashing every connection before a Sud was ever Loaded. - send_forecast() and _reanchor_forecast() can run concurrently (e.g. a fresh Start triggers both at once), and whichever resumed second after its own worker-thread simulation would blindly splice its tail onto whatever the other had already written, producing a spurious connecting line across the plot. Both now carry a generation counter and discard their result if a newer call has since committed. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_019qvu5giu7gvRCyEWzf2Vpx
121 lines
4.7 KiB
Python
121 lines
4.7 KiB
Python
import asyncio
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import json
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import os
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import time
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from tasks import ATask
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from components import APid, AHeater
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from components.sud import Sud, SudState
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def _safe_filename_part(text):
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"""Sanitizes text for use in a log filename - sude/*.json names are
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short codes (e.g. "Sud-0010") in practice, but nothing stops a
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client from loading a schedule with spaces, slashes, etc. in its
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Name."""
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return "".join(c if c.isalnum() or c in "-_" else "_" for c in text) or "Sud"
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class SudLogTask(ATask):
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"""Records every sample of the same data the GUI's Automatic tab
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plots live (temp_ist/temp_soll, rate_ist/rate_soll, power_set/
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power_eff - see client/brewpi_gui.py's PlotCanvas.sample()), plus
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the forecast curve it's compared against (tasks/sud.py's SudTask.
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forecast_t/forecast_theta), for the whole duration of a Sud run -
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for later offline analysis. One pair of JSON files per run, scoped
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to that run alone - unlike a continuously-rewritten trace file that
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keeps growing independently of whether a Sud run is even in
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progress.
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A fresh, uniquely-named pair of logs starts the moment a run
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actually starts (Sud.state leaves IDLE/DONE) and is written out
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whole the moment it ends (state reaches DONE, or is aborted back to
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IDLE via Stop) - never partially mid-run, since a half-written file
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is of no use before the run is over anyway. The forecast file is
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written from SudTask.forecast_t/forecast_theta as they stand at
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that point - the *final*, most-corrected version (see tasks/sud.py's
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SudTask._reanchor_forecast()), not the optimistic guess computed
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back at Load.
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Samples are taken once per interval regardless of Sud.state
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(RAMPING/HOLDING/WAIT_USER/PAUSED all keep recording, mirroring
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SudTask.on_state_changed()'s "any of these means a run is in
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progress" - a paused run's temperature is still worth capturing,
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and the real controller keeps actively driving toward its target
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throughout WAIT_USER too)."""
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def __init__(self, sud: Sud, tc: APid, heater: AHeater, heater_task, sud_task, interval, path='./logs'):
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ATask.__init__(self, interval)
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self.sud = sud
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self.tc = tc
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self.heater = heater
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self.heater_task = heater_task
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self.sud_task = sud_task
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self.path = path
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# None while no run is in progress - see on_sud_state_changed().
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self._samples = None
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# Identifies this run's pair of files (log_<run_id>_<name>.json
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# and forecast_<run_id>_<name>.json) - fixed at the moment the run
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# starts, not when it's written out, so the name reflects when
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# the run happened rather than how long it took.
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self._run_id = None
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@staticmethod
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def _is_running(state):
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return state not in (SudState.IDLE, SudState.DONE)
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def on_sud_state_changed(self, state):
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was_running = self._samples is not None
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if self._is_running(state) and not was_running:
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self._samples = []
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self._run_id = time.strftime("%Y%m%dT%H%M%S", time.localtime())
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elif not self._is_running(state) and was_running:
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self._write()
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self._samples = None
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self._run_id = None
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def _write(self):
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if not self._samples:
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return
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os.makedirs(self.path, exist_ok=True)
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name_part = _safe_filename_part(self.sud.name)
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samples_filename = "log_{}_{}.json".format(self._run_id, name_part)
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with open(os.path.join(self.path, samples_filename), "w") as f:
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json.dump({'Name': self.sud.name, 'Samples': self._samples}, f, indent='\t')
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print("Sud log: wrote {} samples to {}".format(len(self._samples), samples_filename))
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forecast_filename = "forecast_{}_{}.json".format(self._run_id, name_part)
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with open(os.path.join(self.path, forecast_filename), "w") as f:
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json.dump({
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'Name': self.sud.name,
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'T': self.sud_task.forecast_t,
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'Theta': self.sud_task.forecast_theta,
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'Finished': self.sud_task.forecast_finished,
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}, f, indent='\t')
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print("Sud log: wrote forecast to {}".format(forecast_filename))
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async def on_process(self):
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print("SudLogTask: started with interval {} s".format(self.interval))
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self.sud.set_on_changed('state', self.on_sud_state_changed)
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while True:
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if self._samples is not None:
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# power_set mirrors the GUI's 'PowerSet' (the continuous,
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# pre-PWM commanded power) - tasks/heater.py's HeaterTask
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# only ever holds this combined value as a local loop
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# variable, recomputed here from the same two attributes
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# it derives it from, rather than restructuring that task
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# just to expose it.
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power_set = max(self.heater_task.power_soll, self.heater_task.power_actor)
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self._samples.append({
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't': self.sud.elapsed,
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'timestamp': time.time(),
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'temp_ist': self.tc.theta_ist,
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'temp_soll': self.tc.theta_soll_set,
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'rate_ist': self.tc.heatrate_ist,
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'rate_soll': self.tc.heatrate_soll,
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'power_set': power_set,
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'power_eff': self.heater.power_eff,
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})
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await asyncio.sleep(self.interval)
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