#!/usr/bin/env python from jsk_recognition_msgs.msg import PlotData import numpy as np import rospy import math if __name__ == "__main__": rospy.init_node("sample_2d_plot") pub = rospy.Publisher("~output", PlotData) r = rospy.Rate(10) offset = 0 while not rospy.is_shutdown(): msg = PlotData() msg.xs = np.arange(0, 5, 0.1) msg.ys = [math.sin(x + offset) for x in msg.xs] pub.publish(msg) offset = offset + 0.1 r.sleep()
#!/usr/bin/env python from jsk_recognition_msgs.msg import PlotData import numpy as np import rospy from numpy.random import * import math if __name__ == "__main__": rospy.init_node("sample_2d_plot") pub = rospy.Publisher("~output", PlotData) r = rospy.Rate(10) offset = 0 while not rospy.is_shutdown(): msg = PlotData() msg.xs = randn(50) msg.ys = randn(50) pub.publish(msg) offset = offset + 0.1 r.sleep()
#!/usr/bin/env python from jsk_recognition_msgs.msg import PlotData import numpy as np import rospy import math from random import random if __name__ == "__main__": rospy.init_node("sample_2d_plot") pub = rospy.Publisher("~output", PlotData) r = rospy.Rate(10) offset = 0 while not rospy.is_shutdown(): msg = PlotData() msg.xs = np.arange(0, 5, 0.1) msg.ys = [math.sin(x + offset) for x in msg.xs] msg.label = "sample data" if random() < 0.5: msg.type = PlotData.LINE else: msg.type = PlotData.SCATTER msg.fit_line = random() < 0.5 msg.fit_line_ransac = random() < 0.5 pub.publish(msg) offset = offset + 0.1 r.sleep()