Since this is an old post and still seems to be active in the community, I am going to provide an example, in general, how can we do real-time plotting. Here I used matplotlib FuncAnimation function.
import matplotlib.pyplot as plt
import rospy
import tf
from nav_msgs.msg import Odometry
from tf.transformations import quaternion_matrix
import numpy as np
from matplotlib.animation import FuncAnimation
class Visualiser:
def __init__(self):
self.fig, self.ax = plt.subplots()
self.ln, = plt.plot([], [], 'ro')
self.x_data, self.y_data = [] , []
def plot_init(self):
self.ax.set_xlim(0, 10000)
self.ax.set_ylim(-7, 7)
return self.ln
def getYaw(self, pose):
quaternion = (pose.orientation.x, pose.orientation.y, pose.orientation.z,
pose.orientation.w)
euler = tf.transformations.euler_from_quaternion(quaternion)
yaw = euler[2]
return yaw
def odom_callback(self, msg):
yaw_angle = self.getYaw(msg.pose.pose)
self.y_data.append(yaw_angle)
x_index = len(self.x_data)
self.x_data.append(x_index+1)
def update_plot(self, frame):
self.ln.set_data(self.x_data, self.y_data)
return self.ln
rospy.init_node('lidar_visual_node')
vis = Visualiser()
sub = rospy.Subscriber('/dji_sdk/odometry', Odometry, vis.odom_callback)
ani = FuncAnimation(vis.fig, vis.update_plot, init_func=vis.plot_init)
plt.show(block=True)
Take a look at https://github.com/facontidavide/Plot... - I haven't tried it yet but I'd like to hear if it addresses some of your needs.
There is an infinity of answers on stackoverflow treating the continuous update of a matplotlib figure.