使用for循环（python）生成多个line.set_ydata

Question

首先，这是我在这个论坛上的第一篇文章。通常，我可以通过查看此论坛中的帖子来解决我的问题，但在这种情况下，我找不到信息。提前感谢您的支持。

我正在尝试绘制来自一个 PCB 板的多个 IC 的数据（电压和温度）。目前我只是使用随机生成的数字。我在两个不同的图形（子图）中实时显示结果。通过硬写每个 IC 的数据，我已经成功地为固定数量的 IC 做到了这一点，例如line17.set_ydata([np.nan] * len(x))

问题在于 PCB 可以有不同数量的 IC 进行检查。例如，如果 PCB 有 5 个设备，我将需要 10 个 lineXX.set_ydata(..)，但另一方面，如果 PCB 有 10 个 IC，那么在这种情况下，我将需要 20 个 lineXX.set_ydata。未来将作为输入参数的IC数量。

我想要的是使用 for 循环替换所有 lineXX.set_ydata(..) 和 linexx, = （用于绘图）。

这是我的代码：

from collections import deque
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from matplotlib.ticker import FuncFormatter

def init():
    # I want to replace this code with a for cycle
    line0.set_ydata ( [np.nan] * len(x) )
    line1.set_ydata ( [np.nan] * len(x) )
    line2.set_ydata ( [np.nan] * len(x) )
    line3.set_ydata ( [np.nan] * len(x) )
    line4.set_ydata ( [np.nan] * len(x) )
    line5.set_ydata ( [np.nan] * len(x) )
    line6.set_ydata ( [np.nan] * len(x) )
    line7.set_ydata ( [np.nan] * len(x) )
    line8.set_ydata ( [np.nan] * len(x) )
    line9.set_ydata ( [np.nan] * len(x) )
    line10.set_ydata( [np.nan] * len(x) )
    line11.set_ydata( [np.nan] * len(x) )
    line12.set_ydata( [np.nan] * len(x) )
    line13.set_ydata( [np.nan] * len(x) )
    line14.set_ydata( [np.nan] * len(x) )
    line15.set_ydata( [np.nan] * len(x) )
    line16.set_ydata( [np.nan] * len(x) )
    line17.set_ydata( [np.nan] * len(x) )
    
    print('test')
    return 

def animate(i):
    # Add next value
    for ic in range(0, total_ics):
        data_temp[ic].append(np.random.randint(0, max_rand))
        data_volt[ic].append(np.random.randint(0, max_rand))
    
    # I want to replace this code with a for cycle
    line0.set_ydata(data_temp[0])
    line1.set_ydata(data_temp[1])
    line2.set_ydata(data_temp[2])
    line3.set_ydata(data_temp[3])
    line4.set_ydata(data_temp[4])
    line5.set_ydata(data_temp[5])
    line6.set_ydata(data_temp[6])
    line7.set_ydata(data_temp[7])
    line8.set_ydata(data_temp[8])

    # I want to replace this code with a for cycle
    line9.set_ydata(data_volt[0])
    line10.set_ydata(data_volt[1])
    line11.set_ydata(data_volt[2])
    line12.set_ydata(data_volt[3])
    line13.set_ydata(data_volt[4])
    line14.set_ydata(data_volt[5])
    line15.set_ydata(data_volt[6])
    line16.set_ydata(data_volt[7])
    line17.set_ydata(data_volt[8])

    #plt.savefig('e:\\python temp\\fig_{:02}'.format(i))
    print(i)
    return

colors = ['','#1F77B4' ,'#FF7F0E' , '#2CA02C', '#D62728', '#9467BD' , '#8C564B' , '#E377C2' , '#7F7F7F' , '#BCBD22' , '#17BECF']

max_x = 601
max_rand = 100

total_ics = 9
data_temp = []
data_volt = []

for ic in range(0, total_ics ):
    data_temp.append(deque(np.zeros(max_x), maxlen=max_x))
    data_volt.append(deque(np.zeros(max_x), maxlen=max_x))

x = np.arange(0, max_x)     

fig, (ax_temp, ax_volt) = plt.subplots(2, 1 , figsize=(15,8), num='Temperature and Voltage Plotting', constrained_layout=True)
ax_temp.set_ylim(0, max_rand)
ax_temp.set_xlim(0, max_x-1)

ax_volt.set_ylim(0, max_rand)
ax_volt.set_xlim(0, max_x-1)

# I want to replace this code with a for cycle
line0,  = ax_temp.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[1])
line1,  = ax_temp.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[2])
line2,  = ax_temp.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[3])
line3,  = ax_temp.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[4])
line4,  = ax_temp.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[5])
line5,  = ax_temp.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[6])
line6,  = ax_temp.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[7])
line7,  = ax_temp.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[8])
line8,  = ax_temp.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[9])

line9,  = ax_volt.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[1])
line10, = ax_volt.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[2])
line11, = ax_volt.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[3])
line12, = ax_volt.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[4])
line13, = ax_volt.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[5])
line14, = ax_volt.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[6])
line15, = ax_volt.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[7])
line16, = ax_volt.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[8])
line17, = ax_volt.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[9])

ax_temp.xaxis.set_major_formatter(FuncFormatter(lambda x, pos: '{:.0f}s'.format(max_x - x - 1 )))
ax_volt.xaxis.set_major_formatter(FuncFormatter(lambda x, pos: '{:.0f}s'.format(max_x - x - 1 )))
plt.xlabel('Seconds ago')

ani = animation.FuncAnimation(
    fig, animate, init_func=init, interval=1000, blit=False, save_count=10)

plt.show()

干杯

Answer 1

考虑将行存储在一个数组中。 Python 有一些很好的列表理解语法，可以大大减少你的代码大小。

我会将它分成两个数组，一个用于temp，一个用于volt。

要创建线条，您可以执行以下操作：

temp_lines = [ax_temp.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[i])[0] for i in range(1,10)]
volt_lines = [ax_volt.plot(x, np.random.randint(0, max_rand, max_x), lw=0.2, color=colors[i])[0] for i in range(1,10)]

然后在您的init 中，您可以执行以下操作：

[line.set_ydata ([np.nan] * len(x)) for line in temp_lines]
[line.set_ydata ([np.nan] * len(x)) for line in volt_lines]

在你的animate:

[line.set_ydata(data_temp[i]) for i, line in enumerate(temp_lines)]
[line.set_ydata(data_volt[i]) for i, line in enumerate(volt_lines)]

这相当于下面的 for 循环：

for i, line in enumerate(temp_lines):
    line.set_ydata(data_temp[i])

for i, line in enumerate(volt_lines):
    line.set_ydata(data_volt[i])