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 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(lambda t: t - target_temperature), 'i_set': Series(), 'pid_output': Series(), 'vref': Series(), 'dac_value': Series(), 'dac_feedback': Series(), 'i_tec': Series(), 'tec_i': Series(), 'tec_u_meas': Series(), } series_lock = Lock() quit = False def recv_data(tec): for data in tec.report_mode(): if data['channel'] == 0: series_lock.acquire() try: time = data['time'] / 1000.0 for k, s in series.items(): v = data[k] if k in data and type(v) is float: s.append(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 is not None and max_x - TIME_WINDOW > min_x: for s in series.values(): s.clip(max_x - TIME_WINDOW) finally: series_lock.release() margin_y = 0.01 * (max_y - min_y) ax.set_xlim(min_x, max_x) 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()