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2021-07-29 08:32:23 +02:00

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Python
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#!/usr/bin/env python
# This Script creates a lookup table from the measured error CSV
# Wayne Glettig, 16.7.2021
import rospy
from sensor_msgs.msg import JointState
import matplotlib.pyplot as plt
import requests
import time
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
DMS_X=[];
DMS_Y=[];
DMS_Z=[];
DMS_Seq=[];
DMS_Secs=[];
DMS_Nsecs=[];
OMEGA =0;
def callback_LJUE9_JointState(data):
global OMEGA
OMEGA = data.position[0]
def callback_readbackCAL_JointState(data):
global DMS_X,DMS_Y,DMS_Z,DMS_Seq,DMS_Secs,DMS_Nsecs
DMS_X.append(data.position[0])
DMS_Y.append(data.position[1])
DMS_Z.append(data.position[2])
DMS_Secs.append(data.header.stamp.secs)
DMS_Nsecs.append(data.header.stamp.nsecs)
DMS_Seq.append(data.header.seq)
def set_axes_equal(ax):
'''Make axes of 3D plot have equal scale so that spheres appear as spheres,
cubes as cubes, etc.. This is one possible solution to Matplotlib's
ax.set_aspect('equal') and ax.axis('equal') not working for 3D.
Input
ax: a matplotlib axis, e.g., as output from plt.gca().
'''
x_limits = ax.get_xlim3d()
y_limits = ax.get_ylim3d()
z_limits = ax.get_zlim3d()
x_range = abs(x_limits[1] - x_limits[0])
x_middle = np.mean(x_limits)
y_range = abs(y_limits[1] - y_limits[0])
y_middle = np.mean(y_limits)
z_range = abs(z_limits[1] - z_limits[0])
z_middle = np.mean(z_limits)
print (f"x_range: {x_range}")
print (f"y_range: {y_range}")
print (f"z_range: {z_range}")
print (f"x_middle: {x_middle}")
print (f"y_middle: {y_middle}")
print (f"z_middle: {z_middle}")
# The plot bounding box is a sphere in the sense of the infinity
# norm, hence I call half the max range the plot radius.
plot_radius = 0.5*max([x_range, y_range, z_range])
ax.set_xlim3d([x_middle - plot_radius, x_middle + plot_radius])
ax.set_ylim3d([y_middle - plot_radius, y_middle + plot_radius])
ax.set_zlim3d([z_middle - plot_radius, z_middle + plot_radius])
def calculate_correction(VECT):
current = VECT[0]
centre = (max(VECT) + min(VECT))/2.
correction = -(current-centre)
print (f"MAX= {max(VECT)}, MIN= {min(VECT)}")
print (f"current {current}")
print (f"centre {centre}")
print (f"CORRECTION: {correction}")
#if __name__ == '__main__':
smargopolo_server = "http://smargopolo:3000"
response = requests.put(smargopolo_server+"/targetSCS?PHI=0")
print ("Setting up ROS")
#connect to ROS topics for OMEGA and DMS values:
rospy.init_node('DMS_Recorder', anonymous=True)
subsOMEGA=rospy.Subscriber("/LJUE9_JointState", JointState, callback_LJUE9_JointState)
subsDMS =rospy.Subscriber("/readbackCAL", JointState, callback_readbackCAL_JointState)
time.sleep(1)
print ("Moving phi to -180deg")
response = requests.put(smargopolo_server+"/targetSCS?PHI=-90")
time.sleep(5)
response = requests.put(smargopolo_server+"/targetSCS?PHI=-180")
time.sleep(5)
print ("moving to phi=180deg")
response = requests.put(smargopolo_server+"/targetSCS?PHI=-90")
time.sleep(5)
response = requests.put(smargopolo_server+"/targetSCS?PHI=0")
time.sleep(5)
response = requests.put(smargopolo_server+"/targetSCS?PHI=90")
time.sleep(5)
response = requests.put(smargopolo_server+"/targetSCS?PHI=180")
time.sleep(5)
print ("moving to phi=0deg")
response = requests.put(smargopolo_server+"/targetSCS?PHI=0")
time.sleep(8)
#stop ROS to stop measuring.
rospy.signal_shutdown('finished measuring')
print ("Stopped collecting data.")
################################################################################
fig = plt.figure()
ax=fig.add_subplot(111, projection='3d')
ax.plot(DMS_Z,DMS_X,DMS_Y)
ax.set_xlabel("DMS_Z")
ax.set_ylabel("DMS_X")
ax.set_zlabel("DMS_Y")
ax.plot(DMS_Z[0:1],DMS_X[0],DMS_Y[0], 'rx')
set_axes_equal(ax)
fig.show()
fig2 = plt.figure()
ax2=fig2.add_subplot(111)
ax2.plot(DMS_X, label='DMS_X')
ax2.plot(DMS_Y, label='DMS_Y')
ax2.plot(DMS_Z, label='DMS_Z')
ax2.legend()
fig2.show()
################################################################################
calculate_correction(DMS_X)
calculate_correction(DMS_Y)
calculate_correction(DMS_Z)