send_forecast() was defaulting to a cold start at ambient (SudForecastEstimator. estimate()'s default when start_theta isn't passed), so the forecast's t=0 never matched whatever temperature the pot actually was at - understating how long the first ramp would really take whenever it wasn't already cold. Anchoring at tc.get_theta_ist() seemed like the obvious fix but isn't reliable right after Load: that's only ever updated inside process(), which a model-based controller (Smith) doesn't run until its plant params are configured - which now only happens once a Sud is loaded (see the "inert until loaded" change) - so theta_ist can still be sitting at its never-updated __init__ default of 0 the instant send_forecast() reads it. Added TempControllerBase.get_theta_ist_set() (mirroring the existing get_theta_soll_set()) - the raw sensor reading, updated the instant a reading comes in regardless of whether process() has ever run - and used that instead. That still leaves a gap between Load and Start: the real temperature can drift (time passing, manual heating via the Manual tab) between loading a schedule and actually starting it, leaving the forecast anchored to a now-stale temperature. recv()'s 'Start' handler now re-sends the forecast, freshly anchored to the real temperature at that moment, on every fresh start (not a Pause->resume, which keeps the already-established forecast rather than discarding it mid-run). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01DkkuG48uHFCGKe6dPSERFk
375 lines
16 KiB
Python
375 lines
16 KiB
Python
import asyncio
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import bisect
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from tasks import ATask
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from ws.message import MsgIo
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from utils.value import ChangedFloat
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from components import APid, AStirrer
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from components.plant import APlant
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from components.sud import Sud, SudState
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# Upper bound on how many (t, theta) points the forecast is thinned to
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# before going out over the wire (see _send_forecast()) - a fine enough
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# dt over a multi-hour brew can otherwise produce a single JSON message
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# of several MB, large enough to exceed the websockets library's default
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# 1 MiB max_size and get the connection closed outright (code 1009). The
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# GUI's forecast plot is a few hundred pixels wide, so this many points
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# is already far more resolution than it can show; self.forecast_t/
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# forecast_theta themselves stay at full simulated resolution - this
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# only thins the copy actually sent to clients.
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MAX_FORECAST_POINTS = 1000
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def _downsample(t, theta, max_points=MAX_FORECAST_POINTS):
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"""Returns (t, theta) thinned to at most max_points entries by simple
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decimation, always keeping the first and last point - losing a few
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intermediate samples doesn't matter for a plot this size, but losing
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the endpoints would visibly truncate the curve or its final value."""
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n = len(t)
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if n <= max_points:
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return t, theta
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step = -(-n // max_points) # ceil(n / max_points)
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t_ds = t[::step]
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theta_ds = theta[::step]
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if t_ds[-1] != t[-1]:
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t_ds = t_ds + [t[-1]]
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theta_ds = theta_ds + [theta[-1]]
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return t_ds, theta_ds
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class SudTask(ATask):
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def __init__(self, sud: Sud, tc: APid, stirrer: AStirrer, pot: APlant, dt, interval, msg_handler: MsgIo,
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forecast_estimator=None):
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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.stirrer = stirrer
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self.pot = pot
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# Simulated seconds per tick, vs. interval's wall-clock seconds per
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# tick - same dt/interval split Pot/TempController/Stirrer already
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# use internally. Their warp-induced speedup falls out naturally
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# from ticking real physics at simulated dt; Sud has no physics of
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# its own, so hold_remaining must be ticked by dt explicitly to get
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# the same speedup instead of running in real time.
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self.dt = dt
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self.msg_handler = msg_handler
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# Predicts a schedule's actual duration by simulating it with the
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# same plant/controller machinery this server uses for real - see
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# components/sud_forecast.py. Optional only so tests/demos that
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# build a SudTask without one still work; the server always passes
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# one.
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self.forecast_estimator = forecast_estimator
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# The forecast as last computed/corrected (see send_forecast()/
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# _continue_forecast_after_confirm()) - T in simulated seconds,
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# Theta in degrees, parallel lists, both monotonically growing as
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# corrections get spliced in. Covers the whole schedule from the
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# very first Load, including through steps requiring user
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# confirmation - those are simulated as a zero-delay auto-confirm
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# (see components/sud_forecast.py's SudForecastEstimator.
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# estimate()) rather than left unforecast.
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self.forecast_t = []
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self.forecast_theta = []
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# Whether the forecast above actually reaches the schedule's real
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# end (sent as 'Finished') - False only in the pathological case
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# of a step whose target can never be reached (see
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# components/sud_forecast.py's MAX_TICKS).
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self.forecast_finished = True
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# Where each user-confirmation step's zero-delay assumption sits
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# in the forecast timeline above, keyed by the schedule's
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# (absolute) step index - see SudForecastEstimator.estimate()'s
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# confirm_points. Consulted by _continue_forecast_after_confirm()
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# to know where to cut the optimistic guess loose and splice in a
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# freshly anchored simulation once that confirmation actually
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# happens for real.
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self.forecast_confirm_marks = {}
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msg_handler.set_recv_handler(self.recv)
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def apply_plant_params(self, grain_mass, water_mass):
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"""Keeps the real plant's and the controller's internal model's
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plant params in sync with this Sud's own doc - L/Td come straight
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from it (constant for the whole brew), while M/C also fold in the
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given grain_mass/water_mass, which vary over the brew's course
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(malt going in, water boiling off) - mirrors demo_sud.py's
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apply_plant_params(). Called both on every real step transition
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(via on_step_changed(), with that step's own grain_mass/water_mass)
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and once immediately on Load (see recv(), with the doc's own
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initial Sud.grain_mass/water_mass - no need to parse the first
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step out of the schedule for that), so the controller's behavior
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already matches the expected plant as soon as a Sud is loaded,
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not just once a run actually starts."""
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params = self.sud.derive_plant_params(grain_mass, water_mass)
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self.pot.set_plant_params(params)
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if hasattr(self.tc, 'set_model_plant_params'):
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self.tc.set_model_plant_params(params)
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def apply_stirrer(self, phase):
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stirrer_cfg = phase.get('stirrer', {})
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speed = stirrer_cfg.get('speed', 0)
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interval_time = stirrer_cfg.get('interval_time', 0)
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on_ratio = stirrer_cfg.get('on_ratio', 1.0)
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if interval_time > 0:
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self.stirrer.set_cycle_time(interval_time)
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self.stirrer.set_duty_cycle(on_ratio)
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else:
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self.stirrer.set_cycle_time(1.0)
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self.stirrer.set_duty_cycle(1.0 if speed > 0 else 0.0)
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self.stirrer.set_speed(speed)
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def on_step_changed(self, step):
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ramp = step.get('ramp') if step else None
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hold = step.get('hold') if step else None
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# Every step ramps to 'temperature' first, then optionally holds -
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# self.sud.state tells us which phase is currently active; it's
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# already up to date by the time this callback fires, both on a
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# full step transition and on the ramp->hold phase switch within
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# one step (components/sud.py's temp_reached()).
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ramping = self.sud.state == SudState.RAMPING
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phase = ramp if ramping else hold
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if step is not None:
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self.apply_plant_params(step.get('grain_mass', 0), step.get('water_mass', 0))
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if ramping and step['temperature'] is not None:
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self.tc.set_theta_soll(step['temperature'])
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self.tc.set_heatrate_soll(ramp['rate'])
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self.apply_stirrer(phase)
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asyncio.create_task(self.send({'Step': {
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'Index': self.sud.index,
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'Type': 'ramp' if ramping else 'hold' if hold is not None else None,
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'Descr': step.get('descr') if step else None,
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'Temp': step.get('temperature') if step else None,
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'Rate': ramp.get('rate') if ramp else None,
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'Duration': hold.get('duration') if (hold is not None and not ramping) else None,
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'WaitForUser': step.get('user_wait_for_continue', False) if step else None,
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}}))
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def on_state_changed(self, value):
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asyncio.create_task(self.send({'State': str(value)}))
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if value in (SudState.DONE, SudState.IDLE):
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self.stirrer.set_duty_cycle(1.0)
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self.stirrer.set_speed(0)
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# A finished/stopped run no longer owns the controller - hand
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# control back to manual mode (off by default there too).
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self.tc.set_enabled(False)
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else:
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# Any other state (RAMPING/HOLDING/WAIT_USER/PAUSED) means a
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# run is in progress and needs the controller actively driving
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# the heater.
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self.tc.set_enabled(True)
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def on_user_message_changed(self, value):
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asyncio.create_task(self.send({'UserMessage': value}))
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def on_hold_remaining_changed(self, value):
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asyncio.create_task(self.send({'HoldRemaining': value}))
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def on_elapsed_changed(self, value):
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asyncio.create_task(self.send({'Elapsed': value}))
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async def send_forecast(self, doc):
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"""Computes and sends the full forecast for doc, start to finish -
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including through every step requiring user confirmation, which
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is modeled as a zero-delay auto-confirm rather than left
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unforecast (see components/sud_forecast.py's
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SudForecastEstimator.estimate()) - so the whole schedule's
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projected curve is visible right away instead of stopping at the
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first one. Always a fresh start: discards whatever forecast was
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accumulated for the previously loaded schedule.
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Anchored at the real current temperature
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(self.tc.get_theta_ist_set()), not a cold start at ambient - the
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pot may already be warm (a previous run, or manual heating) at
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the moment this Sud is loaded, and a forecast that assumes
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ambient regardless would reach every target later than it
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actually will, never lining up with the actual trace even at
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t=0. Deliberately the raw sensor reading (theta_ist_set), not
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the controller's own get_theta_ist() (theta_ist) -
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_continue_forecast_after_confirm() can trust that one because a
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real run has been actively ticking for a while by the time it
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runs, but this is called right after Load, before this
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controller may have processed even a single tick yet (e.g. its
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plant params/model only just got configured - see SudTask.
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recv()), so theta_ist itself could still be sitting at its
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never-updated __init__ default.
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Those zero-delay assumptions get corrected piecewise as real
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confirmations actually happen - see
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_continue_forecast_after_confirm()."""
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if self.forecast_estimator is None:
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return
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# Runs the simulation in a worker thread - it's CPU-bound and can
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# take a couple hundred ms for a long schedule, which would
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# otherwise stall every other task (heater, sensor, ...) for that
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# whole window.
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loop = asyncio.get_event_loop()
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start_theta = self.tc.get_theta_ist_set()
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t, theta, final_state, confirm_points = await loop.run_in_executor(
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None, self.forecast_estimator.estimate, doc, start_theta)
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self.forecast_t = t
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self.forecast_theta = theta
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self.forecast_finished = (final_state == SudState.DONE)
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self.forecast_confirm_marks = dict(confirm_points)
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await self._send_forecast()
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async def _send_forecast(self):
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t, theta = _downsample(self.forecast_t, self.forecast_theta)
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await self.send({'Forecast': {
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'T': t,
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'Theta': theta,
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'Finished': self.forecast_finished,
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}})
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async def _continue_forecast_after_confirm(self, confirmed_index, confirmed_target):
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"""Corrects the optimistic, zero-delay guess send_forecast() (or a
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previous call to this method) made at confirmed_index's
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user-confirmation step, now that the confirmation has actually
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happened for real - see SudForecastEstimator.estimate()'s
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docstring for why that assumption can't just be trusted as-is.
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Truncates the forecast right back to that point and splices in a
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freshly anchored simulation of the rest of the schedule, anchored
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at the real elapsed time (self.sud.elapsed) - so an actual delay
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shows up honestly as a gap rather than as the assumed zero - and
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the real current temperature (more trustworthy than whatever the
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now-superseded guess predicted it would be by now).
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confirmed_target is the real controller's theta_soll_set at the
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moment of confirmation (captured by recv() *before* calling
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Sud.confirm(), since that synchronously pushes the next step's
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own target onto it) - used to fill the real-world wait itself
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(see below).
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No-op if confirmed_index was never part of a computed forecast in
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the first place (e.g. the estimator isn't configured)."""
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if self.forecast_estimator is None:
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return
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mark_t = self.forecast_confirm_marks.pop(confirmed_index, None)
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if mark_t is None:
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return
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# Drop the now-stale tail (everything beyond the confirmation
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# point) - both the curve itself and any confirm marks that fell
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# within it, since they're about to be replaced by fresh ones.
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cut = bisect.bisect_right(self.forecast_t, mark_t)
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self.forecast_t = self.forecast_t[:cut]
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self.forecast_theta = self.forecast_theta[:cut]
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self.forecast_confirm_marks = {idx: t for idx, t in self.forecast_confirm_marks.items() if t <= mark_t}
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schedule = self.sud.schedule
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index = self.sud.index
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if not (0 <= index < len(schedule)):
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self.forecast_finished = True
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await self._send_forecast()
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return
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doc = {
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'Name': self.sud.name,
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'Description': self.sud.description,
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'pot_mass': self.sud.pot_mass,
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'pot_material': self.sud.pot_material,
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'L': self.sud.L,
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'Td': self.sud.Td,
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'grain_mass': self.sud.grain_mass,
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'water_mass': self.sud.water_mass,
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'steps': schedule[index:],
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}
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start_theta = self.tc.get_theta_ist()
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real_elapsed = self.sud.elapsed
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loop = asyncio.get_event_loop()
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t, theta, final_state, confirm_points = await loop.run_in_executor(None, self.forecast_estimator.estimate, doc, start_theta)
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# Bridge the gap between the confirmation point and the real
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# elapsed time it actually happened at - the real controller
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# stays enabled and actively holding through WAIT_USER, so
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# confirmed_target (its setpoint at the time) is what it was
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# actually converging toward during the wait, not whatever
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# (possibly still mid-ramp) value the forecast happened to log
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# the instant WAIT_USER tripped.
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if self.forecast_t and self.forecast_t[-1] < real_elapsed:
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self.forecast_t.append(real_elapsed)
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self.forecast_theta.append(confirmed_target)
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self.forecast_t.extend(real_elapsed + seconds for seconds in t)
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self.forecast_theta.extend(theta)
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# confirm_points' indices/times are relative to this sub-schedule
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# (starting fresh at doc['steps'][0]) - rebase both onto the real
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# schedule's absolute indices and the master forecast timeline.
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self.forecast_confirm_marks.update(
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(index + local_index, real_elapsed + local_t) for local_index, local_t in confirm_points)
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self.forecast_finished = (final_state == SudState.DONE)
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await self._send_forecast()
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async def recv(self, data):
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for pair in data.items():
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if 'Start' in pair[0]:
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# A fresh start (not a resume from Pause, which keeps
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# whatever forecast the run already established) re-
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# anchors the forecast to the real temperature right now
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# - that's the actual "t=0" the about-to-start actual
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# trace will be plotted from, which may no longer match
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# whatever temperature existed back at Load (time passed,
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# possibly manual heating in between).
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fresh_start = self.sud.state in (SudState.IDLE, SudState.DONE)
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self.sud.start()
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if fresh_start:
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asyncio.create_task(self.send_forecast(self.sud.save()))
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elif 'Confirm' in pair[0]:
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confirmed_index = self.sud.index
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confirmed_target = self.tc.get_theta_soll_set()
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self.sud.confirm()
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asyncio.create_task(self._continue_forecast_after_confirm(confirmed_index, confirmed_target))
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elif 'Pause' in pair[0]:
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self.sud.pause()
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elif 'Stop' in pair[0]:
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self.sud.stop()
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elif 'Save' in pair[0]:
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doc = self.sud.save()
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await self.send({'Json': doc})
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await self.send_forecast(doc)
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elif 'Load' in pair[0]:
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if self.sud.load(pair[1]):
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await self.send({'Name': self.sud.name, 'Description': self.sud.description})
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await self.send({'Json': pair[1]})
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# on_step_changed() only re-applies plant params once a
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# real step starts (Start) - apply them right away too,
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# so the controller already matches this Sud's own pot/
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# L/Td/initial grain_mass/water_mass from the moment
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# it's loaded, rather than whatever the previously
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# loaded Sud (or the generic startup baseline - see
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# server/brewpi.py) left behind.
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if self.sud.schedule:
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self.apply_plant_params(self.sud.grain_mass, self.sud.water_mass)
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await self.send_forecast(pair[1])
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else:
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# Sud.load() refuses while a run is in progress (state
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# not IDLE/DONE) - tell the client why instead of
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# silently dropping the request. The client has no
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# business pre-emptively guessing this itself from its
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# own (replicated, laggy) view of the state.
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#
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# Immediately cleared back to None - unlike every other
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# field here, this is a one-shot event, not state. The
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# dispatcher has no concept of "don't persist this into
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# global_state" (see ws/user.py's update()), so without
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# clearing it, any client connecting later - even one
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# that never touched Load - would get this stale error
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# replayed on connect, with nothing it just did to
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# explain why.
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await self.send({'Error': 'Cannot load a new schedule while a run is in progress - stop it first.'})
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await self.send({'Error': None})
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async def send(self, data):
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await self.msg_handler.send(data)
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async def on_process(self):
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print("{}: Started with interval {} s".format(self.msg_handler.get_key(), self.interval))
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self.sud.set_on_changed('step', self.on_step_changed)
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self.sud.set_on_changed('state', self.on_state_changed)
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self.sud.set_on_changed('user_message', self.on_user_message_changed)
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self.sud.set_on_changed('hold_remaining', ChangedFloat(self.on_hold_remaining_changed, prec=0).set)
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self.sud.set_on_changed('elapsed', ChangedFloat(self.on_elapsed_changed, prec=1).set)
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asyncio.create_task(self.send({'Name': self.sud.name, 'Description': self.sud.description}))
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while True:
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if self.sud.state == SudState.RAMPING and self.tc.is_holding():
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self.sud.temp_reached()
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self.sud.tick(self.dt)
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await asyncio.sleep(self.interval)
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