项目希望runtime可视化某个中间变量，核心思想如下：
输出log经由stdout输入python并构造animation完成可视化。
"""
=====
Decay
=====
This example showcases:
- using a generator to drive an animation,
- changing axes limits during an animation.
"""
SCRIPT="n=0;while true;do echo $n,$n;n=$((n+1));done"
import subprocess
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
def data_gen():
cmd = subprocess.Popen(SCRIPT, shell=True, stdout=subprocess.PIPE)
for line in cmd.stdout:
yield eval(line.decode().strip()) # remove prefix b' and \n
def init():
ax.set_ylim(-1.1, 1.1)
ax.set_xlim(0, 100)
del xdata[:]
del ydata[:]
line.set_data(xdata, ydata)
# return line,
plt.style.use('dark_background')
fig, ax = plt.subplots()
line, = ax.plot([], [], lw=2, color='lime')
xdata, ydata = [], []
def run(data):
# update the data
t, y = data
xdata.append(t)
ydata.append(np.sin(2*np.pi*y/10) * np.exp(-y/100.))
xmin, xmax = ax.get_xlim()
if t >= xmax:
ax.set_xlim(xmin, 2*xmax)
ax.figure.canvas.draw()
line.set_data(xdata, ydata)
# return line,
ani = animation.FuncAnimation(fig, run, data_gen, interval=50, init_func=init) # 50ms = 20fps
plt.show()
matplotlib.animation.FuncAnimation — Matplotlib 3.5.0 documentation