In [1]:
import numpy as np
import glob
import sys
import time
import datetime
import os
import pickle
import matplotlib.pyplot as plt
In [2]:
%matplotlib nbagg
In [3]:
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 [4]:
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 [5]:
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 [6]:
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 [7]:
time_factor = 100.0
In [8]:
#interface = ElectronicsInterface()
interface = SimulatorInterface(time_factor=time_factor)
In [9]:
interface.write_relay(False)
In [7]:
temperatures = []
In [8]:
#target_temperature = 50
target_temperature = 64.5
In [ ]:
interface = SimulatorInterface(time_factor=time_factor)
In [9]:
interface = ElectronicsInterface()
time_factor = 1.0
Debug: temperature sensor found: /sys/bus/w1/devices/28-80000026d00e/w1_slave
Debug: GPIO up and running
In [10]:
interface.read_temperature()
Out[10]:
55.437
In [11]:
#v_boost = c * m / (P * nu)
v_boost = 15
In [12]:
dT = target_temperature - interface.read_temperature()
In [13]:
boost_time = v_boost * dT
In [14]:
boost_time
Out[14]:
135.94500000000005
In [15]:
from enum import Enum
In [16]:
class States(Enum):
BOOST = 1
OVERSHOOT = 2
CONTROL = 3
In [17]:
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
CONTROL_MIN_CHANGE_TIME = 5 * 60 // N_CONTROL
TARGET_ACCURACY = 0.2
MAXIMUM_CONTROL_ERROR = 1.0
BOOST_COOL_SAMPLES = 30
MIN_BOOST_DURATION_FOR_V_UPDATE = 10
MAX_V_BOOST = 16
In [18]:
state = States.OVERSHOOT
relay_on = False
interface.write_relay(False)
current_mean = 0
control_a = 0.1
control_mu = 0.1
control_n = 0
#control_last_errors = []
control_means = []
control_changes = []
control_max = 0.07
control_min = 0.02
#control_cycles = []
control_cycle_state = 0
control_last_min = target_temperature - MAXIMUM_CONTROL_ERROR
control_last_max = target_temperature + MAXIMUM_CONTROL_ERROR
control_applied_change = False
control_last_change = 0
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
start_time = datetime.datetime.now()
handling_temps = []
now = datetime.datetime.now()
# 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, control_min, control_max, control_cycle_state, current_mean))
handling_temps.append(temperature)
print(now, temperature, relay_on, state.value, control_a, control_mu, v_boost, control_min, control_max, control_cycle_state, current_mean)
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 = []
control_cycle_state = 0
control_last_change = 0
start_control = False
if control_n == N_CONTROL:
control_last_change += 1
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)
current_mean = np.mean(handling_temps[-N_CONTROL:])
control_means.append(current_mean)
if current_mean > target_temperature:
if control_cycle_state == 0:
control_cycle_state = 1
control_a = control_min
elif control_cycle_state == 2:
# cycle over!
control_cycle_state = 1
control_a = control_min
if control_max - control_min > 0.01:
if np.mean(control_means) > target_temperature:
control_max -= 0.25 * (control_max - control_min)
control_changes.append(-1)
else:
control_min += 0.25 * (control_max - control_min)
control_changes.append(1)
control_last_min = np.min(control_means)
control_last_max = np.max(control_means)
control_applied_change = False
control_means = []
elif current_mean > control_last_max and (not control_applied_change or control_last_change >= CONTROL_MIN_CHANGE_TIME):
control_min -= 0.25* (control_max - control_min)
control_a = control_min
control_applied_change = True
control_last_change = 0
elif current_mean < target_temperature:
if control_cycle_state == 1:
control_cycle_state = 2
control_a = control_max
control_applied_change = False
elif current_mean < control_last_min and (not control_applied_change or control_last_change >= CONTROL_MIN_CHANGE_TIME):
control_max += 0.25* (control_max - control_min)
control_a = control_max
control_applied_change = True
control_last_change = 0
if False:
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 current_mean > target_temperature + MAXIMUM_CONTROL_ERROR:
state = States.OVERSHOOT
start_cooling = True
control_max /= 2
control_min /= 2
#control_a -= control_mu
#control_changes.append(-1)
elif current_mean < target_temperature - MAXIMUM_CONTROL_ERROR:
state = States.BOOST
start_boost = True
control_max *= 1.5
if control_n == 0 and state == States.CONTROL:
control_turnoff = control_a * T_CONT
if control_turnoff > 0:
relay_target = True
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 boost_cool > BOOST_COOL_SAMPLES:
if np.mean(np.array(handling_temps[-BOOST_COOL_SAMPLES - 1:-1]) - np.array(handling_temps[-BOOST_COOL_SAMPLES:])) > 0:
if boost_heat > MIN_BOOST_DURATION_FOR_V_UPDATE:
v_boost = np.max([np.min([boost_heat / (np.max(handling_temps[-boost_samples:]) - boost_start), MAX_V_BOOST]), 10])
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
2017-02-19 09:41:42.840004 55.437 False 2 0.1 0.1 15 0.02 0.07 0 0
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New v_boost: 16.0
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2017-02-19 09:50:47.830614 60.125 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:50:48.830598 60.125 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:50:49.830595 60.125 True 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 09:58:02.830608 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:03.830608 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:04.830611 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:05.830602 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:06.830608 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:07.830609 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:08.830611 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:09.830623 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:10.830581 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:11.830603 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:12.830614 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:13.830615 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:14.830612 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:15.830624 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:16.830603 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:17.830616 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:18.830605 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:19.830608 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:20.830623 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:21.830623 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:22.830610 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:23.830609 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:24.830617 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:25.830624 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:26.830612 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:27.830611 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:28.830605 63.125 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:29.830622 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
New v_boost: 16.0
2017-02-19 09:58:30.830601 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:31.830609 63.125 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:32.830595 63.125 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:33.830616 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:34.830597 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:35.830617 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:36.830618 63.0 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:37.830612 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:38.830610 63.0 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:39.830594 63.0 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:40.830594 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:41.830600 63.0 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:42.830598 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:43.830598 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:44.830598 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:45.830618 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:46.830607 63.0 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:47.830620 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:48.830613 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:49.830599 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:50.830659 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:51.830600 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:52.830594 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:53.830608 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:54.830607 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:55.830594 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:56.830602 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:57.830601 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:58.830613 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:58:59.830613 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:00.830602 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:01.830593 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:02.830607 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:03.830607 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:04.830607 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:05.830592 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:06.830600 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:07.830599 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:08.830606 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:09.830599 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:10.830621 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:11.830610 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:12.830588 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:13.829907 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:14.830610 63.0 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:15.830612 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:16.830613 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:17.830609 63.0 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:18.830609 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:19.830621 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:20.830606 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:21.830600 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:22.830608 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:23.830619 63.0 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:24.830605 63.0 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:25.830613 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:26.830634 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:27.830620 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:28.830620 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:29.830630 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:30.830617 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:31.830623 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:32.830618 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:33.830634 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:34.830618 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:35.830619 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:36.830634 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:37.830628 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:38.830640 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:39.830630 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:40.830621 63.062 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:41.830617 63.0 False 1 0.1 0.1 16.0 0.02 0.07 0 0
New v_boost: 16.0
2017-02-19 09:59:42.830620 63.0 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:43.830623 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:44.830681 63.0 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:45.830624 63.0 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:46.830612 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:47.830612 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:48.830621 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:49.830607 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:50.830613 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:51.830626 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:52.830626 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:53.830624 63.062 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:54.830617 63.125 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:55.830608 63.125 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:56.830614 63.125 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:57.830624 63.125 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:58.830607 63.125 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 09:59:59.830613 63.125 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:00.830628 63.187 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:01.830610 63.125 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:02.830611 63.187 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:03.830611 63.187 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:04.830610 63.187 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:05.830614 63.187 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:06.830612 63.187 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:07.830609 63.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:08.830620 63.187 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:09.830633 63.25 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:10.830195 63.25 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:11.830612 63.25 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:12.830609 63.25 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:13.830614 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:14.830613 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:15.830615 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:16.830623 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:17.830602 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:18.830599 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:19.830598 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:20.830604 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:21.830610 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:22.830619 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:23.830610 63.375 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:24.830609 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:25.830614 63.375 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:26.830604 63.375 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:27.830608 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:28.830599 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:29.830597 63.375 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:30.830625 63.375 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:31.830616 63.375 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:32.830611 63.375 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:33.830626 63.375 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:34.830629 63.375 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:35.830624 63.437 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:36.830614 63.375 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:37.830615 63.437 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:38.830638 63.437 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:39.830625 63.437 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:40.830619 63.437 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:41.830615 63.5 False 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:00:44.830615 63.625 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:45.830603 63.625 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:46.830624 63.687 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:47.830620 63.687 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:48.830628 63.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:49.830631 63.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:50.830636 63.812 False 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:00:52.830634 63.812 False 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:00:54.830619 63.812 False 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:00:57.830618 63.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:58.830618 63.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:00:59.830631 63.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:01:00.830641 63.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:01:01.830614 63.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:01:02.830620 63.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:01:03.830628 63.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:01:04.830602 63.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:01:05.830606 63.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:01:06.830619 63.812 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:01:07.830630 63.812 False 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:01:17.830624 63.875 False 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:01:20.830634 63.937 False 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:01:27.830631 63.937 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:01:28.830621 63.937 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:01:29.830618 64.0 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:01:30.830620 63.937 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:01:31.830620 64.0 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:01:32.830633 64.0 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:01:33.830621 64.0 False 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:03:43.830613 64.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:03:44.830611 64.687 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:03:45.830608 64.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:03:46.830616 64.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:03:47.830612 64.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:03:48.830610 64.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:03:49.830628 64.687 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:03:50.830616 64.687 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:03:51.830619 64.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:03:52.830609 64.75 False 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:03:58.830613 64.687 False 1 0.1 0.1 16.0 0.02 0.07 0 0
New v_boost: 14.285708
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2017-02-19 10:04:23.830609 64.812 False 2 0.1 0.1 14.285708 0.02 0.07 0 0
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2017-02-19 10:04:30.830609 64.812 False 2 0.1 0.1 14.285708 0.02 0.07 0 0
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2017-02-19 10:04:32.830606 64.875 False 2 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:04:33.830609 64.812 False 2 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:04:34.830597 64.812 False 2 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:04:35.830614 64.875 False 2 0.1 0.1 14.285708 0.02 0.07 0 0
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2017-02-19 10:05:03.830619 64.812 False 2 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:05:04.830606 64.812 False 2 0.1 0.1 14.285708 0.02 0.07 0 0
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2017-02-19 10:08:38.830626 62.562 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:39.830625 62.625 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:40.830602 62.625 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:41.830613 62.625 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:42.830599 62.625 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:43.830611 62.625 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:44.830613 62.562 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:45.830609 62.562 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:46.830617 62.562 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:47.830602 62.562 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:48.830603 62.5 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:49.830597 62.5 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:50.830610 62.5 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:51.830608 62.5 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:52.830595 62.5 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:53.830600 62.437 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:54.830617 62.437 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:55.830609 62.437 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
2017-02-19 10:08:56.830620 62.375 False 1 0.1 0.1 14.285708 0.02 0.07 0 0
New v_boost: 10.0
2017-02-19 10:08:57.830614 62.437 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:08:58.830616 62.375 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:08:59.830595 62.375 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:00.830630 62.375 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:01.830602 62.312 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:02.830604 62.312 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:03.830599 62.312 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:04.830586 62.25 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:05.830615 62.187 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:06.830670 62.187 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:07.830596 62.187 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:08.830620 62.187 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:09.830593 62.125 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:10.830613 62.125 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:11.830587 62.125 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:12.830603 62.062 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:13.830609 62.062 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:14.830616 62.062 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:15.830615 62.0 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:16.830616 62.0 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:17.830593 62.0 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:18.830605 62.0 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:19.830605 61.937 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:20.830607 61.937 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:21.830600 61.937 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:22.830600 61.937 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:23.830618 61.875 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:24.830616 61.875 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:25.830593 61.875 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:26.830605 61.812 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:27.830663 61.812 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:28.830602 61.812 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:29.830601 61.812 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:30.830601 61.812 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:31.830602 61.812 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:32.830594 61.75 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:33.830591 61.75 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:34.830601 61.75 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:35.830599 61.75 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:36.830606 61.687 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:37.830603 61.687 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:38.830604 61.687 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:39.830601 61.625 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:40.830597 61.687 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:41.830614 61.625 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:42.830613 61.625 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:43.830612 61.625 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:44.830596 61.625 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:45.830616 61.625 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:46.830603 61.625 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:47.830620 61.562 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:48.830615 61.562 False 1 0.1 0.1 10.0 0.02 0.07 0 0
New v_boost: 10.0
2017-02-19 10:09:49.830606 61.562 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:50.830602 61.562 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:51.830615 61.562 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:52.830603 61.5 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:53.830604 61.5 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:54.830612 61.5 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:55.830598 61.5 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:56.830618 61.5 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:57.830599 61.5 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:58.830592 61.437 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:09:59.830624 61.437 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:00.830617 61.437 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:01.830597 61.437 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:02.830593 61.437 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:03.830591 61.437 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:04.830612 61.437 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:05.830603 61.375 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:06.830602 61.375 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:07.830602 61.375 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:08.830616 61.375 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:09.830599 61.312 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:10.830614 61.375 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:11.830595 61.375 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:12.830607 61.312 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:13.830589 61.375 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:14.830584 61.312 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:15.830606 61.312 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:16.830602 61.312 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:17.830601 61.312 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:18.830602 61.312 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:19.830599 61.312 True 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:20.830601 61.312 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:21.830609 61.312 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:22.830593 61.312 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:23.830592 61.312 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:24.830613 61.312 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:25.830599 61.312 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:26.830600 61.312 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:27.830614 61.312 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:28.830592 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:29.830612 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:30.830604 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:31.830593 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:32.830596 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:33.830606 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:34.830590 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:35.830587 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:36.830609 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:37.830598 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:38.830617 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:39.830603 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:40.830602 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:41.830601 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:42.830671 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:43.830609 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:44.830608 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:45.830608 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:46.830598 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:47.830599 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:48.830601 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
2017-02-19 10:10:49.830614 61.25 False 1 0.1 0.1 10.0 0.02 0.07 0 0
New v_boost: 16.0
/usr/lib/python3.6/site-packages/ipykernel/__main__.py:215: RuntimeWarning: divide by zero encountered in double_scalars
2017-02-19 10:10:50.830607 61.25 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:10:51.830592 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:10:52.830601 61.187 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:10:53.830601 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:10:54.830604 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:10:55.830618 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:10:56.830615 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:10:57.830608 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:10:58.830603 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:10:59.830606 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:00.830623 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:01.830599 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:02.830612 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:03.830619 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:04.830614 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:05.830581 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:06.830610 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:07.830589 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:08.830615 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:09.830603 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:10.830599 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:11.830592 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:12.830610 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:13.830592 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:14.830611 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:15.830603 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:16.830603 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:17.830606 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:11:20.830603 61.25 True 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:11:22.830595 61.312 True 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:11:24.830598 61.312 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:25.830617 61.312 True 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:11:26.830619 61.312 True 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:17:09.830633 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:17:12.830636 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:17:14.830627 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:17:15.830623 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:17:16.830622 63.375 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:17:17.830633 63.375 False 1 0.1 0.1 16.0 0.02 0.07 0 0
2017-02-19 10:17:18.830630 63.375 False 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:17:23.830635 63.312 False 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:17:29.830634 63.25 False 1 0.1 0.1 16.0 0.02 0.07 0 0
New v_boost: 16.0
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2017-02-19 10:17:38.830631 63.312 True 1 0.1 0.1 16.0 0.02 0.07 0 0
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2017-02-19 10:17:41.830625 63.312 True 1 0.1 0.1 16.0 0.02 0.07 0 0
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New v_boost: 16.0
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2017-02-19 10:52:08.830615 64.437 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:09.830585 64.437 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:10.830588 64.437 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:11.830589 64.437 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:12.830592 64.437 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:13.830593 64.437 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:14.830592 64.437 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:15.830589 64.437 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:16.830611 64.437 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:17.830606 64.437 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:18.830589 64.437 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:19.830596 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:20.830591 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:21.830597 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:22.830613 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:23.830615 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:24.830602 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:25.830612 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:26.830611 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:27.830596 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:28.830593 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:29.830596 64.437 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:30.830588 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:31.830591 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4266666667
2017-02-19 10:52:32.830609 64.5 True 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:33.830600 64.5 True 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:34.930777 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:35.830493 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:36.830592 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:37.830596 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:38.830615 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:39.830598 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:40.830615 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:41.830615 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:42.830609 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:43.830602 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:44.830587 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:45.830587 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:46.830592 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:47.830599 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:48.830599 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:49.830598 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:50.830610 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:51.830591 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:52.830590 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:53.830608 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:54.830591 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:55.830601 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:56.830597 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:57.830592 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:58.830606 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:52:59.830588 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:53:00.830619 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:53:01.830614 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.4622
2017-02-19 10:53:02.830613 64.5 True 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:03.830599 64.5 True 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:04.930800 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:05.830489 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:06.830598 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:07.830618 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:08.830612 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:09.830598 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:10.830601 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:11.830597 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:12.830592 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:13.830600 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:14.830615 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:15.830612 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:16.830614 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:17.830613 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:18.830596 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:19.830593 64.562 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:20.830593 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:21.830598 64.562 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:22.830597 64.562 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:23.830617 64.562 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:24.830614 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:25.830611 64.562 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:26.830614 64.562 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:27.830593 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:28.830662 64.562 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:29.830642 64.5 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:30.830612 64.562 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:31.830601 64.562 False 3 0.07 0.1 16.0 0.02 0.07 2 64.5
2017-02-19 10:53:33.431315 64.5 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:33.830029 64.5 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:34.830617 64.5 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:35.830598 64.5 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:36.830591 64.5 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:37.830612 64.5 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:38.830630 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:39.830600 64.5 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:40.830609 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:41.830597 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:42.830590 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:43.830590 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:44.830593 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:45.830597 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:46.830607 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:47.830608 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:48.830592 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:49.830606 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:50.830601 64.5 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:51.830594 64.5 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:52.830604 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:53.830607 64.5 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:54.830617 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:55.830615 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:56.830612 64.5 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:57.830616 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:58.830597 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:53:59.830609 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:54:00.830636 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:54:01.830599 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5186
2017-02-19 10:54:03.431304 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:03.830012 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:04.830602 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:05.830610 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:06.830602 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:07.830584 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:08.830622 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:09.830607 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:10.830607 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:11.830606 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:12.830606 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:13.830588 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:14.830591 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:15.830590 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:16.830614 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:17.830590 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:18.830617 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:19.830600 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:20.830601 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:21.830614 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:22.830600 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:23.830598 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:24.830598 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:25.830590 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:26.830601 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:27.830598 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:28.830600 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:29.830585 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:30.830604 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:31.830598 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.5392666667
2017-02-19 10:54:33.431305 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:33.830013 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:34.830616 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:35.830599 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:36.830590 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:37.830603 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:38.830637 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:39.830590 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:40.830599 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:41.830686 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:42.830609 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:43.830584 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:44.830603 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:45.830594 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:46.830610 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:47.830597 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:48.830590 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:49.830617 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:50.830621 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:51.830635 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
2017-02-19 10:54:52.830635 64.562 False 3 0.02 0.1 16.0 0.02 0.05750000000000001 1 64.562
In [19]:
interface.close()
In [34]:
temperatures[-1]
Out[34]:
(datetime.datetime(2017, 2, 2, 8, 55, 40, 64046),
64.25,
False,
3,
0.07,
0.1,
13.506963080972508,
0.02,
0.07,
2,
64.274799999999999)
In [35]:
start_time
Out[35]:
datetime.datetime(2017, 2, 2, 8, 0, 21, 63072)
In [36]:
N_CONTROL
Out[36]:
30
In [20]:
fig = plt.figure()
plt.plot([t[0] for t in temperatures], [t[1] - 64.5 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.plot([t[0] for t in temperatures], [t[7] for t in temperatures])
plt.plot([t[0] for t in temperatures], [t[8] for t in temperatures])
plt.plot([t[0] for t in temperatures], [t[9] for t in temperatures])
plt.plot([t[0] for t in temperatures], [t[10] for t in temperatures])
plt.legend(['temperature', 'relay_on', 'state', 'a', 'mu', 'v_boost', 'min', 'max', 'cycle_state', 'current_mean'])
Out[20]:
<matplotlib.legend.Legend at 0x6f109af0>
In [25]:
fig = plt.figure()
plt.plot([t[0] for t in temperatures], [t[1] - target_temperature 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.plot([t[0] for t in temperatures], [t[7] for t in temperatures])
plt.plot([t[0] for t in temperatures], [t[8] for t in temperatures])
plt.plot([t[0] for t in temperatures], [t[9] for t in temperatures])
plt.plot([t[0] for t in temperatures], [t[10] for t in temperatures])
plt.legend(['temperature', 'relay_on', 'state', 'a', 'mu', 'v_boost', 'min', 'max', 'cycle_state', 'current_mean'])
Out[25]:
<matplotlib.legend.Legend at 0x6ee719b0>
In [39]:
with open('onsen_ei_zwei.pkl', 'wb') as f:
pickle.dump(temperatures, f)
Content source: neXyon/suvicoco
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