Currently, I am attempting to visualize multiple data points being transmitted over the USART serial bus from a microcontroller using Python. It would be ideal if I could plot all this data simultaneously and in real-time.
Interestingly, when plotting a single graph, the data updates in real-time; however, when utilizing subplots, there is a noticeable delay even with only one subchannel being plotted. Can anyone shed light on why subplotting in Python seems to slow down the process?
I conducted some measurements regarding the time consumed by the update() function, which appears to be around 2ms or less. On the other hand, the data reception interval is every 5ms or longer. What steps can I take to enhance the processing speed?
Warm regards: Sebastian T.
Below is the code snippet:
import serial
import matplotlib.pyplot as plt
import matplotlib.animation as anim
import time
from collections import deque
#SERIAL#######################################################
try:
ser = serial.Serial()
ser.baudrate=115200;
ser.port = 'COM7'
ser.open()
except:
ser.close()
print('Problem occurred')
ser.flushInput()
ser.flushOutput()
#PLOT##########################################################
MAX_X = 250 #width of graph
MAX_Y = 70000 #height of graph
# initialize line to horizontal line on 0
line1 = deque([0.0]*MAX_X, maxlen=MAX_X)
line2 = deque([0.0]*MAX_X, maxlen=MAX_X)
line3 = deque([0.0]*MAX_X, maxlen=MAX_X)
line4 = deque([0.0]*MAX_X, maxlen=MAX_X)
line5 = deque([0.0]*MAX_X, maxlen=MAX_X)
plt.close('all')
fig, (ax1, ax2, ax3, ax4) = plt.subplots(4, 1)
l1, = ax1.plot([], [])
l2, = ax2.plot([], [])
l3, = ax3.plot([], [])
l4, = ax4.plot([], [])
l=[l1, l2, l3, l4]
for ax in [ax1, ax2, ax3, ax4]:
ax.set_ylim(-(MAX_Y/2), MAX_Y/2)
ax.set_xlim(-(MAX_X/2), MAX_X/2)
ax.grid()
def update(fn, data):
try:
t = time.time()
# prepare Data
data_raw = ser.readline()
data_raw = data_raw.split(',')
data_raw = data_raw[1::2]
# Update Plots
line1.append(int(data_raw[0]))
line2.append(int(data_raw[1]))
line3.append(int(data_raw[2]))
line4.append(int(data_raw[3]))
# Set Data
l[0].set_data(range(-MAX_X/2, MAX_X/2), line1)
l[1].set_data(range(-MAX_X/2, MAX_X/2), line2)
l[2].set_data(range(-MAX_X / 2, MAX_X / 2), line3)
l[3].set_data(range(-MAX_X / 2, MAX_X / 2), line4)
print(time.time() - t)
except:
print('exception')
ser.close()
ani = anim.FuncAnimation(fig, update, fargs=(0,), frames=1, interval=100)
plt.show()