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
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)
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
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
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)
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
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48.0611005986
48.0582465246
48.0557503169
48.0532390048
In [266]:
interface.read_temperature()
Out[266]:
48.050638028674285
In [267]:
interface.close()
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
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
23.0115115398
23.0153049396
23.0196116802
23.0244598768
23.0297931736
23.0356464938
23.0420252717
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Reached boost time, turning off: 2017-01-08 21:38:32.811924
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Temperature falling again, starting control: 2017-01-08 21:38:36.901949
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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>]
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
50.125
50.125
50.125
50.25
50.25
50.125
50.25
50.125
50.125
50.125
50.0
50.125
50.25
50.0
50.125
50.125
50.125
50.125
50.125
50.125
50.125
50.125
50.125
50.125
50.125
50.0
50.125
50.0
50.0
50.0
50.125
50.125
50.125
50.0
50.125
50.125
50.125
50.0
50.125
50.0
50.125
50.125
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
50.0
50.0
50.0
50.0
50.0
50.0
50.0
50.0
50.0
50.0
49.875
50.0
50.0
50.0
50.0
50.0
50.0
49.875
49.875
50.0
50.0
50.0
49.875
50.0
49.875
50.0
50.0
50.0
50.0
49.875
49.875
50.0
49.875
49.875
50.0
49.875
49.875
49.875
50.0
50.0
49.875
49.875
49.875
50.0
49.875
49.875
49.875
49.875
49.875
49.875
49.875
50.0
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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>
Content source: neXyon/suvicoco
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