In [409]:
import numpy as np
import glob
import sys
import time
import datetime
import os
import pickle

import matplotlib.pyplot as plt

In [410]:
%matplotlib nbagg

Utilities


In [2]:
def printError(*arg):
    print('Error:', *arg, file=sys.stderr)
    
def printDebug(*arg):
    print('Debug:', *arg, file=sys.stderr)
    
def printWarning(*arg):
    print('Warning:', *arg, file=sys.stderr)

Simulation Model


In [3]:
class WaterHeaterModel:
    def __init__(self, m_w=1, m_h=0.2, T_env=23, P=400, r=0.085,
                 c_pw=4200, c_ph=400, h_w=25, h_a=6, rho_w=1000, rho_h=8800):
        A_hw = np.pi * r ** 2
        V_w = m_w / rho_w
        H_w = V_w / A_hw
        A_wa = H_w * 2 * r * np.pi + A_hw

        V_h = m_h / rho_h
        H_h = V_h / A_hw
        A_ha = H_h * 2 * r * np.pi + A_hw

        alpha = -(h_w * A_hw + h_a * A_ha) / (c_ph * m_h)
        beta = h_w * A_hw / (c_ph * m_h)
        gamma = h_w * A_hw / (c_pw * m_w)
        delta = -(h_w * A_hw + h_a * A_wa) / (c_pw * m_w)

        self.A = np.array([[alpha, beta], [gamma, delta]])

        alpha = P / (c_ph * m_h)
        beta = h_a * A_ha / (c_ph * m_h) * T_env
        gamma = 0
        delta = h_a * A_wa / (c_pw * m_w) * T_env

        self.B = np.array([[alpha, beta], [gamma, delta]])
        
        self.state = np.array([[T_env] * 2], dtype=np.float64).transpose()

    def __call__(self, u, dt):
        u = np.array([[u, 1]]).transpose()
        
        self.state += (np.dot(self.A, self.state) + np.dot(self.B, u)) * dt
        
        return self.state

Simulator Interface


In [764]:
class SimulatorInterface:
    def __init__(self, m=None, time_base=datetime.datetime.now, time_factor=1.0, switching_delay=5.0, accuracy=0.125):
        if m is None:
            m = np.random.rand() + 0.7
        
        self.model = WaterHeaterModel(m)
        self.heating = False
        self.time_base = time_base
        self.last_time = time_base()
        self.time_factor = time_factor
        self.switching_delay = switching_delay
        self.accuracy = accuracy
        self.last_temperature = np.random.rand() * 80 + 20
        self.relays = []
    
    def _update(self):
        current = self.time_base()
        dt = (current - self.last_time).total_seconds() * self.time_factor
        self.advance(dt, current)
        
    def advance(self, dt, current=None):
        if current is None:
            current = self.time_base()
        self.last_time = current
        
        self.relays = [(x[0] - dt, x[1]) for x in self.relays]
        
        while len(self.relays) > 0 and self.relays[0][0] <= 0:
            self.heating = self.relays[0][1]
            self.relays = self.relays[1:]
        
        self.model(float(self.heating), dt)
    
    def read_temperature(self):
        # note: ugly delay like we have in the actual sensor readings
        result = np.round(self.last_temperature / self.accuracy + np.random.randn(1)[0] / 3) * self.accuracy
        self._update()
        self.last_temperature = self.model.state[1][0]
        return result
    
    def write_relay(self, value):
        self._update()
        self.relays.append((self.switching_delay, value))
            
    def close(self):
        pass

Hardware interface


In [125]:
class ElectronicsInterface:
    def __init__(self, gpio_pin=18, sensor=None):
        self.pin = gpio_pin
        self.sensor = None
        self.GPIO = None
        
        if sensor is None:
            temperature_sensors = glob.glob('/sys/bus/w1/devices/28-*/w1_slave')
            
            if len(temperature_sensors) > 1:
                printError('multiple temperature sensors found, please specify - entering fake mode')
                return
            elif len(temperature_sensors) == 0:
                printError('temperature sensor cannot be found - entering fake mode')
                return
            else:
                printDebug('temperature sensor found: ' + temperature_sensors[0])
                sensor = temperature_sensors[0]
        
        self.sensor = sensor
        
        try:
            self.read_temperature()
        except:
            printError('temperature sensor cannot be read - entering fake mode.')
            self.sensor = None
            return
        
        try:
            import RPi.GPIO as GPIO
            
            GPIO.setmode(GPIO.BCM)
            GPIO.setup(gpio_pin, GPIO.OUT, initial=GPIO.LOW)
            
            self.GPIO = GPIO
            
            printDebug('GPIO up and running')
        except:
            self.GPIO = None
            printError('GPIO not working - entering fake mode')
            
    def read_temperature(self):
        if self.sensor is not None:
            with open(self.sensor, 'r') as f:
                lines = f.readlines()
        else:
            lines = ['69 01 ff ff 7f ff ff ff 7e : crc=7e YES\n', '69 01 ff ff 7f ff ff ff 7e t=22562\n']
            
        if lines[0].strip()[-3:] == 'YES':
            self.temperature = int(lines[1].strip().split('=')[1]) / 1000
        else:
            self.temperature = np.nan
            printWarning('no temperature read')
            
        return self.temperature
    
    def write_relay(self, value):
        if self.GPIO is not None:
            self.GPIO.output(self.pin, value)
            
    def close(self):
        if self.GPIO is not None:
            self.GPIO.cleanup(self.pin)

In [501]:
time_factor = 100.0

In [261]:
#interface = ElectronicsInterface()
interface = SimulatorInterface(time_factor=time_factor)

In [262]:
interface.write_relay(False)

Let's collect some data!


In [263]:
temperatures = []

In [264]:
interface.read_temperature()


Out[264]:
47.0954219328273

In [265]:
relay_on = True

interface.write_relay(True)

# run for an hour max
for i in range(3600):
    temperature = interface.read_temperature()
    temperatures.append(temperature)
    print(temperature)
    
    if relay_on and temperature >= 50:
        interface.write_relay(False)
        relay_on = False
        
    if os.path.exists('/tmp/stop'):
        break
    
    time.sleep(1 / time_factor)
    
if relay_on:
    interface.write_relay(False)
    relay_on = False


23.0
23.0
23.0
23.0
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48.0532390048

In [266]:
interface.read_temperature()


Out[266]:
48.050638028674285

In [267]:
interface.close()

Investiage


In [268]:
fig = plt.figure()
plt.plot(temperatures)


Out[268]:
[<matplotlib.lines.Line2D at 0x7f5154b0a128>]

In [269]:
max(temperatures)


Out[269]:
56.851921797418413

In [270]:
np.where(np.array(temperatures) > 50)[0][0]


Out[270]:
415

In [271]:
c = 4190
m = 1
dT = max(temperatures) - min(temperatures)
dQ = c * m * dT
P = 400
t = np.where(np.array(temperatures) > 50)[0][0]
E = P * t
nu = dQ / E
print('Wirkungsgrad:', nu)


Wirkungsgrad: 0.854455134525

In [272]:
dQ


Out[272]:
141839.55233118316

In [273]:
dT


Out[273]:
33.851921797418413

In [274]:
t


Out[274]:
415

Second Data Collection: Simple hysteresis control


In [669]:
temperatures = []

In [670]:
target_temperature = 50

In [671]:
interface = SimulatorInterface(time_factor=time_factor)

In [672]:
interface.read_temperature()


Out[672]:
20.70731172150202

In [673]:
dT = target_temperature - interface.read_temperature()

In [674]:
dQ = c * m * dT
boost_time = dQ / (P * nu)

In [675]:
boost_time


Out[675]:
331.00041017034675

In [676]:
is_boosting = True
is_controlling = False

relay_on = True

interface.write_relay(True)

start_time = datetime.datetime.now()
last_temp = 0

# run for an two hours max
for i in range(3600 * 3):
    now = datetime.datetime.now()
    temperature = interface.read_temperature()
    temperatures.append((now, temperature, relay_on))
    print(temperature)
    
    if is_boosting:
        if i > boost_time:
            if relay_on:
                interface.write_relay(False)
                relay_on = False
                print('Reached boost time, turning off:', now)
            elif last_temp > temperature:
                print('Temperature falling again, starting control:', now)
                is_boosting = False
                is_controlling = True
                
        last_temp = temperature
    elif is_controlling:
        if i >= 3600 * 3:
            is_controlling = False
            print('Stopping controlling:', now)
            
            if relay_on:
                interface.write_relay(False)
                relay_on = False
            
        elif relay_on and temperature >= target_temperature:
            interface.write_relay(False)
            relay_on = False
        elif not relay_on and temperature < target_temperature:
            interface.write_relay(True)
            relay_on = True
            
        
    if os.path.exists('/tmp/stop'):
        break
        
    sleep_time = i + 1 - (datetime.datetime.now() - start_time).total_seconds() * time_factor
    
    if sleep_time > 0:
        time.sleep(sleep_time / time_factor)
    
if relay_on:
    interface.write_relay(False)
    relay_on = False


23.0
23.0
23.0
23.0
23.0
23.0
23.0
23.0005551263
23.0016653673
23.0033167798
23.0055123092
23.0082457302
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27.4475650365
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27.7766361596
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27.8717633198
27.9195468722
27.9674438332
28.0155298171
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31.0285824997
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32.0026414249
32.0572546364
32.1121058243
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32.386683681
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32.718157391
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33.6667871027
33.7229256868
33.7793825306
33.8355441981
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34.0610947019
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34.2307194195
34.2873395769
34.3441910092
34.4008825076
34.4574076111
34.5143900299
34.5711769035
34.6278981467
34.6848489812
34.74169928
34.7986192823
34.8554662173
34.9128325799
34.9697488981
35.0267677437
35.0839802945
35.141089253
35.1982770549
35.2556235567
35.3128079862
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35.4273873203
35.4847931649
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36.2331073083
36.2908231755
36.3486641341
36.4065144052
36.4644199562
36.5220622725
36.5800659423
36.6380894151
Reached boost time, turning off: 2017-01-08 21:38:32.811924
36.6958368929
36.7541370114
36.8118992215
36.8698829232
36.9279139756
36.9862011875
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37.7525037048
37.8034741681
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39.0168229261
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39.0951223581
39.1337227004
39.1720287952
39.2099927665
39.2473883782
39.2848198675
39.3216200592
39.357967862
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39.5006685772
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40.543585888
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40.6179273311
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40.6662464232
40.6901099671
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40.737000476
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40.7831566264
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40.8945915101
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40.9799203977
41.0007274971
41.021373487
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42.8342699525
42.8343396219
42.8343939557
42.8344335662
42.834458339
42.8344684541
42.8344640402
Temperature falling again, starting control: 2017-01-08 21:38:36.901949
42.8344452521
42.8344123262
42.8343651887
42.8343036855
42.8342288799
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In [677]:
interface.close()

In [678]:
temperatures[-1]


Out[678]:
(datetime.datetime(2017, 1, 8, 21, 40, 17, 481928), 50.506361625162349, False)

In [679]:
start_time


Out[679]:
datetime.datetime(2017, 1, 8, 21, 38, 29, 491849)

In [680]:
plt.figure()
plt.plot([t[0] for t in temperatures], [t[1] for t in temperatures])


Out[680]:
[<matplotlib.lines.Line2D at 0x7f5147fb3320>]

Let's try our own control mechanism


In [784]:
temperatures = []

In [785]:
target_temperature = 50

In [786]:
interface = SimulatorInterface(time_factor=time_factor)

In [787]:
interface.read_temperature()


Out[787]:
89.5

In [788]:
v_boost = c * m / (P * nu)
v_boost


Out[788]:
12.259274450753585

In [789]:
dT = target_temperature - interface.read_temperature()

In [790]:
boost_time = v_boost * dT

In [791]:
boost_time


Out[791]:
331.00041017034681

In [792]:
from enum import Enum, auto

In [793]:
class States(Enum):
    BOOST = auto()
    OVERSHOOT = auto()
    CONTROL = auto()

In [794]:
CONTROL_EPSILON = 0.5
F_SWITCH = 1 / 15
T_CONT = 2 / F_SWITCH
F_READ = 1
T_READ = 1 / F_READ
N_CONTROL = int(T_CONT / T_READ)
NE_CONTROL = 4

NM_CONTROL = 3
NC_CONTROL = 4

TARGET_ACCURACY = 0.2
MAXIMUM_CONTROL_ERROR = 1.0
BOOST_COOL_SAMPLES = 10

In [795]:
state = States.OVERSHOOT

relay_on = False
interface.write_relay(False)

start_time = datetime.datetime.now()
handling_temps = []

control_a = 0.1
control_mu = 0.1
control_n = 0
#control_last_errors = []
control_means = []
control_changes = []

control_turnoff = 0

start_boost = False
start_cooling = True
start_control = False

boost_time = 0
boost_cool = 0
boost_heat = 0
boost_samples = 0
boost_start = 0

# run for three hours max
for i in range(3600 * 3):
    last_time = now
    now = datetime.datetime.now()
    temperature = interface.read_temperature()
    temperatures.append((now, temperature, relay_on, state.value, control_a, control_mu, v_boost))
    handling_temps.append(temperature)
    print(temperature)
    
    dt = (now - last_time).total_seconds() * time_factor
    
    if control_turnoff > 0:
        control_turnoff -= dt
    if boost_time > 0:
        boost_time -= dt
    
    relay_target = relay_on
    
    if state == States.CONTROL:
        control_n += 1
        
        if start_control:
            control_n = 0
            #control_last_errors = []
            
            control_means = []
            control_changes = []

            start_control = False
        
        if control_n == N_CONTROL:
            control_n = 0
            
            #e = np.mean(handling_temps[-N_CONTROL:]) - target_temperature
            #control_last_errors.append(np.sign(e) if np.abs(e) - TARGET_ACCURACY > 0 else 0)
            
            #if len(control_last_errors) >= NE_CONTROL:
            #    control_last_errors = control_last_errors[-NE_CONTROL:]
            #    
            #    #if np.sum(np.abs(control_last_errors)) != 0:
            #    avg_e = np.abs(np.mean(control_last_errors))

            #    control_mu = control_mu * (.5 if avg_e < 1 / NE_CONTROL else (2 if avg_e == NE_CONTROL else 1))

            #control_a -= control_mu * control_last_errors[-1]
            #control_a = np.clip(control_a, 0, 1)

            control_means.append(np.mean(handling_temps[-N_CONTROL:]))
            
            if len(control_means) >= NM_CONTROL:
                control_means = control_means[-NM_CONTROL:]
                direction = np.sign(np.array(control_means[1:]) - control_means[:-1])
                
                a_change = 0
                
                if (direction == -1).all() and control_means[-1] < target_temperature:
                    a_change = 1
                elif (direction == 1).all() and control_means[-1] > target_temperature:
                    a_change = -1
                
                if a_change != 0:
                    control_a += control_mu * a_change
                    
                    control_changes.append(a_change)
                    
                    control_means = []
                    
            if len(control_changes) >= NC_CONTROL:
                control_changes = control_changes[-NC_CONTROL:]
                
                if sum(control_changes) == 0:
                    control_mu /= 2
                    control_changes = []
                elif np.abs(sum(control_changes)) == NC_CONTROL:
                    control_mu *= 2
                    control_changes = []
            
            if handling_temps[-1] > target_temperature + MAXIMUM_CONTROL_ERROR:
                state = States.OVERSHOOT
                start_cooling = True
                #control_a -= control_mu
                #control_changes.append(-1)
                
            elif handling_temps[-1] < target_temperature - MAXIMUM_CONTROL_ERROR:
                state = States.BOOST
                start_boost = True
            
        if control_n == 0 and state == States.CONTROL:
            relay_target = True
            control_turnoff = control_a * T_CONT
        
    elif state == States.BOOST:
        if start_boost:
            boost_start = handling_temps[-1]
            dT = target_temperature - boost_start
            boost_time = v_boost * dT
            boost_heat = boost_time
            
            relay_target = True
            start_boost = False
            boost_samples = 0
        else:
            boost_samples += 1
        
        if boost_time <= 0:
            if relay_on:
                relay_target = False
                boost_heat -= boost_time
                boost_cool = 0
            else:
                boost_cool += dt
                
                if len(handling_temps) > BOOST_COOL_SAMPLES:
                    if np.mean(np.array(handling_temps[-BOOST_COOL_SAMPLES - 1:-1]) - np.array(handling_temps[-BOOST_COOL_SAMPLES:])) > 0:
                        v_boost = boost_heat / (np.max(handling_temps[-boost_samples:]) - boost_start)
                        print('New v_boost:', v_boost)
                        
                        if handling_temps[-1] > target_temperature:
                            state = States.OVERSHOOT
                            start_cooling = True
                            #v_boost /= 2
                            # TODO: v_boost is BAD now!
                        elif handling_temps[-1] > target_temperature - CONTROL_EPSILON:
                            state = States.CONTROL
                            start_control = True
                        else:
                            start_boost = True
        
        # overshooting, stop heating early!
        elif relay_on and handling_temps[-1] >= target_temperature:
            relay_target = False
            boost_heat -= boost_time
            boost_time = 0
            boost_cool = 0
        
    elif state == States.OVERSHOOT:
        relay_target = False
        
        if handling_temps[-1] < target_temperature - CONTROL_EPSILON:
            state = States.BOOST
            start_boost = True
        elif handling_temps[-1] < target_temperature:
            state = States.CONTROL
            start_control = True

    # actually switch the relay!
    if relay_on != relay_target:
        relay_on = relay_target
        interface.write_relay(relay_on)
        
    if os.path.exists('/tmp/stop'):
        break
        
    sleep_time = i + 1 - (datetime.datetime.now() - start_time).total_seconds() * time_factor
    
    if state == States.CONTROL and relay_on and sleep_time > control_turnoff:
        if control_turnoff > 0:
            time.sleep(control_turnoff / time_factor)
        control_turnoff = 0
        relay_on = False
        interface.write_relay(relay_on)
        
        sleep_time -= control_turnoff
    
    if sleep_time > 0:
        time.sleep(sleep_time / time_factor)
    
if relay_on:
    interface.write_relay(False)
    relay_on = False


23.0
23.0
23.0
23.0
23.0
23.0
23.0
23.0
23.125
23.0
23.0
23.0
23.0
23.0
23.0
23.125
23.0
23.0
23.125
23.125
23.0
23.125
23.0
23.125
23.125
23.125
23.125
23.125
23.125
23.125
23.25
23.125
23.25
23.125
23.25
23.25
23.25
23.25
23.375
23.375
23.375
23.375
23.375
23.375
23.25
23.375
23.5
23.5
23.625
23.5
23.625
23.625
23.5
23.75
23.75
23.75
23.75
23.75
23.75
23.75
23.875
23.875
23.875
23.875
24.0
24.0
24.0
24.125
24.0
24.125
24.125
24.25
24.25
24.25
24.375
24.375
24.375
24.5
24.5
24.5
24.5
24.5
24.625
24.625
24.625
24.75
24.75
24.875
24.75
24.875
24.875
25.0
25.0
25.0
25.125
25.0
25.25
25.25
25.25
25.25
25.375
25.375
25.375
25.5
25.5
25.5
25.625
25.625
25.75
25.75
25.875
25.875
25.875
26.0
25.875
26.125
26.125
26.25
26.375
26.25
26.375
26.375
26.375
26.5
26.5
26.5
26.625
26.625
26.75
26.75
26.75
26.875
26.875
27.0
27.0
27.125
27.125
27.25
27.125
27.375
27.375
27.375
27.375
27.5
27.625
27.625
27.625
27.75
27.75
27.875
27.875
28.0
28.0
28.125
28.125
28.25
28.125
28.25
28.375
28.5
28.5
28.625
28.625
28.75
28.625
28.75
28.875
28.875
29.0
29.0
29.125
29.125
29.125
29.25
29.375
29.375
29.5
29.5
29.625
29.625
29.625
29.75
29.75
29.875
29.875
30.0
30.0
30.0
30.25
30.25
30.375
30.375
30.5
30.5
30.625
30.625
30.75
30.75
30.875
30.875
31.0
31.0
31.0
31.25
31.25
31.25
31.375
31.375
31.5
31.5
31.5
31.625
31.75
31.75
31.875
31.875
32.0
32.125
32.125
32.25
32.25
32.375
32.375
32.5
32.5
32.625
32.75
32.875
32.75
32.875
33.0
33.0
33.125
33.125
33.125
33.25
33.375
33.375
33.5
33.5
33.625
33.75
33.75
33.75
33.875
33.875
34.0
34.125
34.125
34.25
34.375
34.375
34.5
34.5
34.5
34.75
34.75
34.75
34.875
35.0
34.875
35.125
35.125
35.25
35.25
35.375
35.5
35.5
35.5
35.625
35.75
35.875
35.875
36.0
35.875
36.125
36.125
36.25
36.25
36.375
36.5
36.5
36.625
36.5
36.625
36.75
36.875
36.875
37.0
37.0
37.125
37.25
37.25
37.375
37.5
37.5
37.5
37.625
37.75
37.75
37.875
37.875
38.125
38.0
38.125
38.125
38.25
38.375
38.375
38.375
38.625
38.625
38.625
38.875
38.75
38.875
39.0
39.125
39.25
39.25
39.375
39.375
39.5
39.5
39.625
39.75
39.625
39.75
39.875
39.875
40.125
40.125
40.25
40.25
40.375
40.375
40.5
40.625
40.625
40.625
40.875
40.75
40.875
41.0
41.0
41.0
41.25
41.25
41.375
41.375
41.5
41.5
41.625
41.625
41.75
41.75
41.875
41.875
42.0
42.125
42.125
42.125
42.25
42.25
42.375
42.375
42.375
42.5
42.5
42.625
42.625
42.75
42.75
42.875
42.875
42.875
43.0
43.125
43.125
43.125
43.25
43.25
43.375
43.375
43.5
43.5
43.5
43.5
43.625
43.75
43.75
43.625
43.875
43.875
43.875
43.875
44.0
44.0
44.125
44.0
44.125
44.125
44.25
44.25
44.25
44.375
44.375
44.375
44.5
44.5
44.5
44.625
44.625
44.625
44.625
44.75
44.75
44.75
44.875
45.0
45.0
44.875
44.875
45.0
45.0
45.125
45.125
45.25
45.25
45.125
45.125
45.25
45.25
45.375
45.375
45.375
45.375
45.375
45.5
45.5
45.5
45.625
45.625
45.625
45.625
45.75
45.625
45.75
45.75
45.75
45.875
45.875
45.75
45.875
45.875
46.0
45.875
46.0
46.0
45.875
46.0
46.125
46.0
46.125
46.125
46.125
46.25
46.25
46.25
46.25
46.25
46.25
46.25
46.25
46.375
46.375
46.375
46.375
46.5
46.375
46.5
46.5
46.5
46.5
46.5
46.625
46.625
46.625
46.625
46.75
46.75
46.75
46.75
46.625
46.625
46.75
46.75
46.875
46.75
46.75
46.875
46.75
46.875
46.875
46.875
46.875
47.0
47.0
46.875
46.875
46.875
47.0
47.0
47.0
47.0
47.125
47.0
47.0
47.0
47.125
47.125
47.125
47.125
47.125
47.125
47.125
47.125
47.125
47.25
47.125
47.125
47.25
47.125
47.25
47.25
47.25
47.25
47.25
47.375
47.375
47.25
47.375
47.25
47.375
47.375
47.375
47.375
47.375
47.375
47.375
47.5
47.375
47.375
47.375
47.5
47.5
47.375
47.5
47.5
47.5
47.375
New v_boost: 13.5510204082
47.5
47.5
47.5
47.625
47.5
47.5
47.5
47.625
47.625
47.625
47.625
47.625
47.625
47.625
47.625
47.625
47.75
47.625
47.625
47.625
47.625
47.75
47.75
47.625
47.75
47.75
47.875
47.875
47.875
47.875
47.875
47.875
48.0
48.0
48.0
48.0
48.125
48.0
48.125
48.125
48.125
48.25
48.125
48.125
48.125
48.25
48.25
48.25
48.375
48.375
48.375
48.5
48.5
48.375
48.375
48.5
48.5
48.5
48.5
48.5
48.625
48.625
48.625
48.625
48.625
48.625
48.75
48.75
48.75
48.75
48.75
48.75
48.75
48.875
48.875
49.0
48.875
48.875
48.875
49.0
49.0
49.125
49.0
49.0
49.0
49.125
49.0
49.125
49.125
49.125
49.125
49.125
49.25
49.25
49.125
49.25
49.25
49.25
49.25
49.25
49.25
49.25
49.25
49.375
49.375
49.375
49.375
49.5
49.375
49.5
49.375
49.375
49.375
49.375
49.375
49.5
49.5
49.5
49.5
49.625
49.5
49.5
49.625
49.625
49.625
49.625
49.5
49.625
49.625
49.625
49.625
49.75
49.625
49.625
49.625
49.75
49.625
49.625
49.625
49.75
49.75
49.75
49.75
49.75
49.75
49.75
49.75
49.75
49.75
49.875
49.75
49.875
49.75
49.75
49.875
49.875
49.75
49.875
49.875
50.0
49.875
49.875
49.875
49.875
50.0
49.875
49.875
50.0
49.875
50.0
49.875
49.875
50.0
49.875
50.0
50.0
50.0
50.0
50.0
50.0
50.0
50.0
50.0
50.0
50.125
50.0
50.0
50.125
50.0
50.0
50.125
50.0
50.0
50.0
50.0
New v_boost: 12.9531809524
50.125
50.125
50.125
50.125
50.0
50.125
50.125
50.125
50.125
50.125
50.125
50.125
50.125
50.125
50.125
50.25
50.125
50.25
50.25
50.125
50.25
50.25
50.25
50.125
50.125
50.25
50.25
50.25
50.25
50.125
50.25
50.125
50.25
50.25
50.25
50.25
50.25
50.25
50.25
50.25
50.375
50.25
50.375
50.25
50.25
50.25
50.25
50.375
50.25
50.375
50.25
50.375
50.25
50.375
50.375
50.375
50.25
50.375
50.5
50.375
50.5
50.375
50.5
50.375
50.375
50.375
50.375
50.375
50.375
50.375
50.375
50.375
50.5
50.5
50.5
50.375
50.5
50.5
50.5
50.5
50.5
50.5
50.5
50.625
50.5
50.375
50.5
50.5
50.5
50.5
50.5
50.5
50.5
50.5
50.625
50.625
50.625
50.5
50.625
50.625
50.5
50.625
50.625
50.625
50.5
50.625
50.625
50.75
50.625
50.625
50.5
50.625
50.625
50.75
50.625
50.625
50.625
50.75
50.625
50.75
50.75
50.625
50.625
50.625
50.625
50.625
50.75
50.625
50.75
50.75
50.75
50.625
50.625
50.625
50.75
50.75
50.625
50.75
50.625
50.625
50.625
50.625
50.625
50.75
50.625
50.75
50.625
50.625
50.75
50.75
50.625
50.75
50.75
50.625
50.75
50.75
50.75
50.75
50.75
50.625
50.75
50.75
50.75
50.625
50.75
50.75
50.625
50.75
50.75
50.625
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.625
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.625
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.625
50.75
50.75
50.625
50.75
50.875
50.75
50.875
50.75
50.75
50.75
50.75
50.75
50.75
50.625
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.625
50.75
50.75
50.75
50.75
50.75
50.625
50.625
50.75
50.75
50.75
50.75
50.75
50.625
50.75
50.625
50.75
50.75
50.625
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.625
50.625
50.75
50.625
50.75
50.625
50.625
50.75
50.75
50.625
50.625
50.625
50.75
50.75
50.625
50.625
50.75
50.75
50.75
50.75
50.75
50.75
50.75
50.625
50.625
50.75
50.625
50.625
50.625
50.75
50.625
50.5
50.625
50.625
50.625
50.625
50.75
50.625
50.625
50.625
50.625
50.625
50.625
50.625
50.625
50.625
50.625
50.625
50.625
50.625
50.625
50.5
50.625
50.625
50.625
50.625
50.625
50.625
50.625
50.625
50.5
50.5
50.625
50.625
50.625
50.625
50.625
50.625
50.625
50.625
50.625
50.625
50.625
50.5
50.625
50.5
50.5
50.5
50.5
50.5
50.625
50.625
50.5
50.625
50.5
50.375
50.625
50.625
50.5
50.5
50.5
50.625
50.5
50.5
50.5
50.5
50.5
50.625
50.625
50.5
50.375
50.625
50.5
50.5
50.5
50.5
50.375
50.5
50.5
50.5
50.5
50.5
50.5
50.5
50.5
50.5
50.5
50.5
50.625
50.375
50.5
50.5
50.375
50.5
50.375
50.375
50.5
50.5
50.5
50.5
50.5
50.5
50.375
50.5
50.5
50.5
50.5
50.375
50.5
50.375
50.5
50.375
50.375
50.375
50.375
50.375
50.5
50.375
50.375
50.375
50.375
50.375
50.375
50.5
50.375
50.375
50.375
50.375
50.375
50.375
50.375
50.375
50.375
50.375
50.375
50.375
50.375
50.375
50.375
50.375
50.5
50.375
50.375
50.375
50.375
50.25
50.375
50.25
50.375
50.25
50.25
50.375
50.375
50.375
50.375
50.25
50.25
50.25
50.375
50.25
50.25
50.25
50.375
50.375
50.25
50.25
50.375
50.25
50.25
50.25
50.375
50.25
50.25
50.25
50.25
50.25
50.25
50.375
50.25
50.25
50.25
50.25
50.25
50.25
50.25
50.125
50.25
50.125
50.25
50.125
50.25
50.25
50.25
50.125
50.25
50.25
50.25
50.125
50.25
50.25
50.125
50.125
50.25
50.25
50.25
50.25
50.25
50.25
50.25
50.125
50.125
50.25
50.25
50.125
50.125
50.25
50.25
50.125
50.125
50.125
50.25
50.125
50.25
50.125
50.125
50.125
50.125
50.25
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In [796]:
interface.close()

In [797]:
temperatures[-1]


Out[797]:
(datetime.datetime(2017, 1, 8, 22, 2, 58, 522643),
 49.875,
 False,
 3,
 0.04375000000000002,
 0.00625,
 12.953180952380947)

In [798]:
start_time


Out[798]:
datetime.datetime(2017, 1, 8, 22, 1, 10, 532568)

In [799]:
N_CONTROL


Out[799]:
30

In [800]:
fig = plt.figure()
plt.plot([t[0] for t in temperatures], [t[1] - 50 for t in temperatures])
plt.plot([t[0] for t in temperatures], [t[2] for t in temperatures])
plt.plot([t[0] for t in temperatures], [t[3] for t in temperatures])
plt.plot([t[0] for t in temperatures], [t[4] for t in temperatures])
plt.plot([t[0] for t in temperatures], [t[5] for t in temperatures])
plt.plot([t[0] for t in temperatures], [t[6] for t in temperatures])
plt.legend(['temperature', 'relay_on', 'state', 'a', 'mu', 'v_boost'])


Out[800]:
<matplotlib.legend.Legend at 0x7f514deddb38>