thermostat/pytec/plot.py

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import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from threading import Thread, Lock
from pytec.client import Client
TIME_WINDOW = 300.0
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tec = Client()
target_temperature = tec.get_pid()[0]['target']
print("Channel 0 target temperature: {:.3f}".format(target_temperature))
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class Series:
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def __init__(self, conv=lambda x: x):
self.conv = conv
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self.x_data = []
self.y_data = []
def append(self, x, y):
self.x_data.append(x)
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self.y_data.append(self.conv(y))
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def clip(self, min_x):
drop = 0
while drop < len(self.x_data) and self.x_data[drop] < min_x:
drop += 1
self.x_data = self.x_data[drop:]
self.y_data = self.y_data[drop:]
series = {
'adc': Series(),
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'sens': Series(lambda x: x * 0.0001),
'temperature': Series(lambda t: t - target_temperature),
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'i_set': Series(),
'pid_output': Series(),
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'vref': Series(),
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'dac_value': Series(),
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'dac_feedback': Series(),
'i_tec': Series(),
'tec_i': Series(),
'tec_u_meas': Series(),
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'interval': Series(),
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}
series_lock = Lock()
quit = False
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last_packet_time = None
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def recv_data(tec):
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global last_packet_time
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for data in tec.report_mode():
if data['channel'] == 0:
series_lock.acquire()
try:
time = data['time'] / 1000.0
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if last_packet_time:
data['interval'] = time - last_packet_time
last_packet_time = time
for k, s in series.items():
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if k in data:
v = data[k]
if type(v) is float:
s.append(time, v)
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finally:
series_lock.release()
if quit:
break
thread = Thread(target=recv_data, args=(tec,))
thread.start()
fig, ax = plt.subplots()
for k, s in series.items():
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s.plot, = ax.plot([], [], label=k)
legend = ax.legend()
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def animate(i):
min_x, max_x, min_y, max_y = None, None, None, None
series_lock.acquire()
try:
for k, s in series.items():
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s.plot.set_data(s.x_data, s.y_data)
if len(s.y_data) > 0:
s.plot.set_label("{}: {:.3f}".format(k, s.y_data[-1]))
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if len(s.x_data) > 0:
min_x_ = min(s.x_data)
if min_x is None:
min_x = min_x_
else:
min_x = min(min_x, min_x_)
max_x_ = max(s.x_data)
if max_x is None:
max_x = max_x_
else:
max_x = max(max_x, max_x_)
if len(s.y_data) > 0:
min_y_ = min(s.y_data)
if min_y is None:
min_y = min_y_
else:
min_y = min(min_y, min_y_)
max_y_ = max(s.y_data)
if max_y is None:
max_y = max_y_
else:
max_y = max(max_y, max_y_)
if min_x is not None and max_x - TIME_WINDOW > min_x:
for s in series.values():
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s.clip(max_x - TIME_WINDOW)
finally:
series_lock.release()
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if min_x != max_x:
ax.set_xlim(min_x, max_x)
if min_y != max_y:
margin_y = 0.01 * (max_y - min_y)
ax.set_ylim(min_y - margin_y, max_y + margin_y)
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global legend
legend.remove()
legend = ax.legend()
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ani = animation.FuncAnimation(
fig, animate, interval=1, blit=False, save_count=50)
plt.show()
quit = True
thread.join()