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pytec/.flake8
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3
pytec/.flake8
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@ -0,0 +1,3 @@
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[flake8]
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max-line-length = 88
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extend-ignore = E203,E701
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@ -12,31 +12,32 @@ from pytec.client import Client
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class PIDAutotuneState(Enum):
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STATE_OFF = 'off'
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STATE_RELAY_STEP_UP = 'relay step up'
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STATE_RELAY_STEP_DOWN = 'relay step down'
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STATE_SUCCEEDED = 'succeeded'
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STATE_FAILED = 'failed'
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STATE_OFF = "off"
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STATE_RELAY_STEP_UP = "relay step up"
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STATE_RELAY_STEP_DOWN = "relay step down"
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STATE_SUCCEEDED = "succeeded"
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STATE_FAILED = "failed"
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class PIDAutotune:
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PIDParams = namedtuple('PIDParams', ['Kp', 'Ki', 'Kd'])
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PIDParams = namedtuple("PIDParams", ["Kp", "Ki", "Kd"])
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PEAK_AMPLITUDE_TOLERANCE = 0.05
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_tuning_rules = {
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"ziegler-nichols": [0.6, 1.2, 0.075],
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"tyreus-luyben": [0.4545, 0.2066, 0.07214],
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"tyreus-luyben": [0.4545, 0.2066, 0.07214],
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"ciancone-marlin": [0.303, 0.1364, 0.0481],
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"pessen-integral": [0.7, 1.75, 0.105],
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"some-overshoot": [0.333, 0.667, 0.111],
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"no-overshoot": [0.2, 0.4, 0.0667]
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"some-overshoot": [0.333, 0.667, 0.111],
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"no-overshoot": [0.2, 0.4, 0.0667],
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}
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def __init__(self, setpoint, out_step=10, lookback=60,
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noiseband=0.5, sampletime=1.2):
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def __init__(
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self, setpoint, out_step=10, lookback=60, noiseband=0.5, sampletime=1.2
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):
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if setpoint is None:
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raise ValueError('setpoint must be specified')
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raise ValueError("setpoint must be specified")
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self._inputs = deque(maxlen=round(lookback / sampletime))
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self._setpoint = setpoint
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@ -68,7 +69,7 @@ class PIDAutotune:
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"""Get a list of all available tuning rules."""
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return self._tuning_rules.keys()
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def get_pid_parameters(self, tuning_rule='ziegler-nichols'):
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def get_pid_parameters(self, tuning_rule="ziegler-nichols"):
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"""Get PID parameters.
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Args:
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@ -93,27 +94,33 @@ class PIDAutotune:
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"""
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now = time_input * 1000
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if (self._state == PIDAutotuneState.STATE_OFF
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or self._state == PIDAutotuneState.STATE_SUCCEEDED
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or self._state == PIDAutotuneState.STATE_FAILED):
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if (
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self._state == PIDAutotuneState.STATE_OFF
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or self._state == PIDAutotuneState.STATE_SUCCEEDED
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or self._state == PIDAutotuneState.STATE_FAILED
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):
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self._state = PIDAutotuneState.STATE_RELAY_STEP_UP
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self._last_run_timestamp = now
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# check input and change relay state if necessary
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if (self._state == PIDAutotuneState.STATE_RELAY_STEP_UP
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and input_val > self._setpoint + self._noiseband):
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if (
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self._state == PIDAutotuneState.STATE_RELAY_STEP_UP
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and input_val > self._setpoint + self._noiseband
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):
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self._state = PIDAutotuneState.STATE_RELAY_STEP_DOWN
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logging.debug('switched state: {0}'.format(self._state))
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logging.debug('input: {0}'.format(input_val))
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elif (self._state == PIDAutotuneState.STATE_RELAY_STEP_DOWN
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and input_val < self._setpoint - self._noiseband):
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logging.debug("switched state: {0}".format(self._state))
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logging.debug("input: {0}".format(input_val))
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elif (
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self._state == PIDAutotuneState.STATE_RELAY_STEP_DOWN
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and input_val < self._setpoint - self._noiseband
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):
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self._state = PIDAutotuneState.STATE_RELAY_STEP_UP
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logging.debug('switched state: {0}'.format(self._state))
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logging.debug('input: {0}'.format(input_val))
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logging.debug("switched state: {0}".format(self._state))
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logging.debug("input: {0}".format(input_val))
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# set output
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if (self._state == PIDAutotuneState.STATE_RELAY_STEP_UP):
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if self._state == PIDAutotuneState.STATE_RELAY_STEP_UP:
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self._output = self._initial_output - self._outputstep
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elif self._state == PIDAutotuneState.STATE_RELAY_STEP_DOWN:
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self._output = self._initial_output + self._outputstep
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@ -156,8 +163,8 @@ class PIDAutotune:
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self._peak_count += 1
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self._peaks.append(input_val)
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self._peak_timestamps.append(now)
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logging.debug('found peak: {0}'.format(input_val))
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logging.debug('peak count: {0}'.format(self._peak_count))
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logging.debug("found peak: {0}".format(input_val))
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logging.debug("peak count: {0}".format(self._peak_count))
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# check for convergence of induced oscillation
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# convergence of amplitude assessed on last 4 peaks (1.5 cycles)
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@ -167,20 +174,19 @@ class PIDAutotune:
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abs_max = self._peaks[-2]
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abs_min = self._peaks[-2]
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for i in range(0, len(self._peaks) - 2):
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self._induced_amplitude += abs(self._peaks[i]
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- self._peaks[i+1])
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self._induced_amplitude += abs(self._peaks[i] - self._peaks[i + 1])
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abs_max = max(self._peaks[i], abs_max)
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abs_min = min(self._peaks[i], abs_min)
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self._induced_amplitude /= 6.0
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# check convergence criterion for amplitude of induced oscillation
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amplitude_dev = ((0.5 * (abs_max - abs_min)
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- self._induced_amplitude)
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/ self._induced_amplitude)
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amplitude_dev = (
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0.5 * (abs_max - abs_min) - self._induced_amplitude
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) / self._induced_amplitude
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logging.debug('amplitude: {0}'.format(self._induced_amplitude))
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logging.debug('amplitude deviation: {0}'.format(amplitude_dev))
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logging.debug("amplitude: {0}".format(self._induced_amplitude))
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logging.debug("amplitude deviation: {0}".format(amplitude_dev))
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if amplitude_dev < PIDAutotune.PEAK_AMPLITUDE_TOLERANCE:
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self._state = PIDAutotuneState.STATE_SUCCEEDED
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@ -194,25 +200,24 @@ class PIDAutotune:
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if self._state == PIDAutotuneState.STATE_SUCCEEDED:
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self._output = 0
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logging.debug('peak finding successful')
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logging.debug("peak finding successful")
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# calculate ultimate gain
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self._Ku = 4.0 * self._outputstep / \
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(self._induced_amplitude * math.pi)
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print('Ku: {0}'.format(self._Ku))
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self._Ku = 4.0 * self._outputstep / (self._induced_amplitude * math.pi)
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print("Ku: {0}".format(self._Ku))
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# calculate ultimate period in seconds
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period1 = self._peak_timestamps[3] - self._peak_timestamps[1]
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period2 = self._peak_timestamps[4] - self._peak_timestamps[2]
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self._Pu = 0.5 * (period1 + period2) / 1000.0
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print('Pu: {0}'.format(self._Pu))
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print("Pu: {0}".format(self._Pu))
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for rule in self._tuning_rules:
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params = self.get_pid_parameters(rule)
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print('rule: {0}'.format(rule))
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print('Kp: {0}'.format(params.Kp))
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print('Ki: {0}'.format(params.Ki))
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print('Kd: {0}'.format(params.Kd))
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print("rule: {0}".format(rule))
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print("Kp: {0}".format(params.Kp))
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print("Ki: {0}".format(params.Ki))
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print("Kd: {0}".format(params.Kd))
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return True
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return False
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@ -239,16 +244,17 @@ def main():
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data = next(tec.report_mode())
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ch = data[channel]
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tuner = PIDAutotune(target_temperature, output_step,
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lookback, noiseband, ch['interval'])
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tuner = PIDAutotune(
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target_temperature, output_step, lookback, noiseband, ch["interval"]
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)
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for data in tec.report_mode():
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ch = data[channel]
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temperature = ch['temperature']
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temperature = ch["temperature"]
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if (tuner.run(temperature, ch['time'])):
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if tuner.run(temperature, ch["time"]):
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break
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tuner_out = tuner.output()
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@ -1,6 +1,6 @@
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from pytec.client import Client
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tec = Client() #(host="localhost", port=6667)
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tec = Client() # (host="localhost", port=6667)
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tec.set_param("b-p", 1, "t0", 20)
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print(tec.get_output())
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print(tec.get_pid())
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@ -7,9 +7,10 @@ from pytec.client import Client
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TIME_WINDOW = 300.0
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tec = Client()
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target_temperature = tec.get_pid()[0]['target']
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target_temperature = tec.get_pid()[0]["target"]
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print("Channel 0 target temperature: {:.3f}".format(target_temperature))
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class Series:
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def __init__(self, conv=lambda x: x):
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self.conv = conv
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@ -26,25 +27,27 @@ class Series:
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drop += 1
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self.x_data = self.x_data[drop:]
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self.y_data = self.y_data[drop:]
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series = {
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# 'adc': Series(),
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# 'sens': Series(lambda x: x * 0.0001),
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'temperature': Series(),
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"temperature": Series(),
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# 'i_set': Series(),
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'pid_output': Series(),
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"pid_output": Series(),
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# 'vref': Series(),
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# 'dac_value': Series(),
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# 'dac_feedback': Series(),
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# 'i_tec': Series(),
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'tec_i': Series(),
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'tec_u_meas': Series(),
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"tec_i": Series(),
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"tec_u_meas": Series(),
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# 'interval': Series(),
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}
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series_lock = Lock()
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quit = False
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def recv_data(tec):
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global last_packet_time
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for data in tec.report_mode():
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@ -55,25 +58,27 @@ def recv_data(tec):
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if k in ch0:
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v = ch0[k]
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if type(v) is float:
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s.append(ch0['time'], v)
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s.append(ch0["time"], v)
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finally:
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series_lock.release()
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if quit:
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break
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thread = Thread(target=recv_data, args=(tec,))
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thread.start()
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fig, ax = plt.subplots()
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for k, s in series.items():
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s.plot, = ax.plot([], [], label=k)
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(s.plot,) = ax.plot([], [], label=k)
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legend = ax.legend()
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def animate(i):
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min_x, max_x, min_y, max_y = None, None, None, None
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series_lock.acquire()
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try:
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for k, s in series.items():
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@ -120,8 +125,8 @@ def animate(i):
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legend.remove()
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legend = ax.legend()
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ani = animation.FuncAnimation(
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fig, animate, interval=1, blit=False, save_count=50)
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ani = animation.FuncAnimation(fig, animate, interval=1, blit=False, save_count=50)
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plt.show()
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quit = True
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@ -3,9 +3,11 @@ import json
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import logging
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import time
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class CommandError(Exception):
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pass
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class Client:
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def __init__(self, host="192.168.1.26", port=23, timeout=None):
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self._socket = socket.create_connection((host, port), timeout)
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@ -17,7 +19,11 @@ class Client:
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for output_channel in output_report:
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for limit in ["max_i_neg", "max_i_pos", "max_v"]:
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if output_channel[limit] == 0.0:
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logging.warning("`{}` limit is set to zero on channel {}".format(limit, output_channel["channel"]))
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logging.warning(
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"`{}` limit is set to zero on channel {}".format(
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limit, output_channel["channel"]
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)
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)
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def _read_line(self):
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# read more lines
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@ -25,7 +31,7 @@ class Client:
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chunk = self._socket.recv(4096)
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if not chunk:
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return None
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buf = self._lines[-1] + chunk.decode('utf-8', errors='ignore')
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buf = self._lines[-1] + chunk.decode("utf-8", errors="ignore")
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self._lines = buf.split("\n")
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line = self._lines[0]
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@ -33,7 +39,7 @@ class Client:
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return line
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def _command(self, *command):
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self._socket.sendall((" ".join(command) + "\n").encode('utf-8'))
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self._socket.sendall((" ".join(command) + "\n").encode("utf-8"))
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line = self._read_line()
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response = json.loads(line)
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@ -130,7 +136,7 @@ class Client:
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'pid_output': 2.067581958092247}
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"""
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while True:
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self._socket.sendall("report\n".encode('utf-8'))
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self._socket.sendall("report\n".encode("utf-8"))
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line = self._read_line()
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if not line:
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break
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