131 lines
3.7 KiB
Python
131 lines
3.7 KiB
Python
import numpy as np
|
|
import matplotlib.pyplot as plt
|
|
import matplotlib.animation as animation
|
|
from threading import Thread, Lock
|
|
from pytec.client import Client
|
|
|
|
if __name__ == "__main__":
|
|
|
|
TIME_WINDOW = 300.0
|
|
|
|
tec = Client()
|
|
target_temperature = tec.get_pid()[0]['target']
|
|
print("Channel 0 target temperature: {:.3f}".format(target_temperature))
|
|
|
|
class Series:
|
|
def __init__(self, conv=lambda x: x):
|
|
self.conv = conv
|
|
self.x_data = []
|
|
self.y_data = []
|
|
|
|
def append(self, x, y):
|
|
self.x_data.append(x)
|
|
self.y_data.append(self.conv(y))
|
|
|
|
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(),
|
|
'sens': Series(lambda x: x * 0.0001),
|
|
'temperature': Series(),
|
|
'i_set': Series(),
|
|
'pid_output': Series(),
|
|
'vref': Series(),
|
|
'dac_value': Series(),
|
|
'dac_feedback': Series(),
|
|
'i_tec': Series(),
|
|
'tec_i': Series(),
|
|
'tec_u_meas': Series(),
|
|
'interval': Series(),
|
|
}
|
|
series_lock = Lock()
|
|
|
|
quit = False
|
|
|
|
def recv_data(tec):
|
|
global last_packet_time
|
|
for data in tec.report_mode():
|
|
ch0 = data[0]
|
|
series_lock.acquire()
|
|
try:
|
|
for k, s in series.items():
|
|
if k in ch0:
|
|
v = ch0[k]
|
|
if type(v) is float:
|
|
s.append(ch0['time'], v)
|
|
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():
|
|
s.plot, = ax.plot([], [], label=k)
|
|
legend = ax.legend()
|
|
|
|
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():
|
|
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]))
|
|
|
|
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 and max_x - TIME_WINDOW > min_x:
|
|
for s in series.values():
|
|
s.clip(max_x - TIME_WINDOW)
|
|
finally:
|
|
series_lock.release()
|
|
|
|
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)
|
|
|
|
global legend
|
|
legend.remove()
|
|
legend = ax.legend()
|
|
|
|
ani = animation.FuncAnimation(
|
|
fig, animate, interval=1, blit=False, save_count=50)
|
|
|
|
plt.show()
|
|
quit = True
|
|
thread.join()
|