Matplotlib -센서값을 이용한 실시간 그래프 2개 구현

import RPi.GPIO as GPIO
from matplotlib import pyplot as plt
from matplotlib import animation
import numpy as np
import random
import time
import spidev

spi=spidev.SpiDev()
spi.open(0, 0)
spi.max_speed_hz=1000000
def ReadChannel(channel):
    adc=spi.xfer2([1,(8+channel)<<4,0])
    data=((adc[1]&3)<<8)+adc[2]
    return data

mcp3008_channel=0




fig = plt.figure()     #figure(도표) 생성

ax = plt.subplot(211, xlim=(0, 50), ylim=(0, 1024))
ax_2 = plt.subplot(212, xlim=(0, 50), ylim=(0, 512))



max_points = 50
max_points_2 = 50
line, = ax.plot(np.arange(max_points), 
                np.ones(max_points, dtype=np.float)*np.nan, lw=1, c='blue',ms=1)
line_2, = ax_2.plot(np.arange(max_points_2), 
                np.ones(max_points, dtype=np.float)*np.nan, lw=1,ms=1)


def init():
    return line
def init_2():
    return line_2


def animate(i):
    y = ReadChannel(mcp3008_channel)
    old_y = line.get_ydata()
    new_y = np.r_[old_y[1:], y]
    line.set_ydata(new_y)
    print(new_y)
    return line

def animate_2(i):
    y_2 = random.randint(0,512)
    old_y_2 = line_2.get_ydata()
    new_y_2 = np.r_[old_y_2[1:], y_2]
    line_2.set_ydata(new_y_2)
    print(new_y_2)
    return line_2


anim = animation.FuncAnimation(fig, animate  , init_func= init ,frames=200, interval=50, blit=False)
anim_2 = animation.FuncAnimation(fig, animate_2  , init_func= init_2 ,frames=200, interval=10, blit=False)
plt.show()

라즈베리파이에서, 센서값을 받아 2개의 그래프를 그리려는 목적이 있었습니다. (다만 센서가 하나뿐이라 하나는 랜덤함수로 대체)

위 그래프 : 가변저항 센서값

아래 : 랜덤함수

 

 

 

 

* 정리한 코드

import RPi.GPIO as GPIO
from matplotlib import pyplot as plt
from matplotlib import animation
import numpy as np
import random, time, spidev

spi=spidev.SpiDev()
spi.open(0, 0)
spi.max_speed_hz=1000000

def ReadChannel(channel):
    adc=spi.xfer2([1,(8+channel)<<4,0])
    data=((adc[1]&3)<<8)+adc[2]
    return data
mcp3008_channel=0
fig = plt.figure()    
ax = plt.subplot(211, xlim=(0, 50), ylim=(0, 1024))
ax_2 = plt.subplot(212, xlim=(0, 50), ylim=(0, 512))

max_points = 50
max_points_2 = 50

line, = ax.plot(np.arange(max_points), 
                np.ones(max_points, dtype=np.float)*np.nan, lw=1, c='blue',ms=1)
line_2, = ax_2.plot(np.arange(max_points_2), 
                np.ones(max_points, dtype=np.float)*np.nan, lw=1,ms=1)

def animate(i):
    y = ReadChannel(mcp3008_channel)
    # y = random.randint(0,1000)
    old_y = line.get_ydata()
    new_y = np.r_[old_y[1:], y]
    line.set_ydata(new_y)
    print(new_y)
    return line
    
def animate_2(i):
    y_2 = random.randint(0,512)
    old_y_2 = line_2.get_ydata()
    new_y_2 = np.r_[old_y_2[1:], y_2]
    line_2.set_ydata(new_y_2)
    print(new_y_2)
    return line_2


anim = animation.FuncAnimation(fig, animate ,interval = 10)
anim_2 = animation.FuncAnimation(fig, animate_2  , interval=10)
plt.show()