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Tools/ecl_ekf: Improvements to ecl log analysis scripts 

Fix error in scaling of population high frequency vibration metrics
Add histograms for delta angle and velocity bias data
Fix variable descriptions
This commit is contained in:
Paul Riseborough 2017-04-20 19:27:58 +10:00 committed by Lorenz Meier
parent 2a34bde0e9
commit 1843061376
1 changed files with 36 additions and 9 deletions
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45
Tools/ecl_ekf/batch_process_metadata_ekf.py
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@ -91,7 +91,7 @@ population_results = {
'imu_coning_max_avg':[float('NaN'),'The mean of the maximum in-flight values of the IMU delta angle coning vibration level (mrad)'],
'imu_coning_mean_avg':[float('NaN'),'The mean of the mean in-flight value of the IMU delta angle coning vibration level (mrad)'],
'imu_hfdang_max_avg':[float('NaN'),'The mean of the maximum in-flight values of the IMU high frequency delta angle vibration level (mrad)'],
'imu_hfdang_mean_avg':[float('NaN'),'The mean of the mean in-flight value of the IMU delta hihg frequency delta angle vibration level (mrad)'],
'imu_hfdang_mean_avg':[float('NaN'),'The mean of the mean in-flight value of the IMU delta high frequency delta angle vibration level (mrad)'],
'imu_hfdvel_max_avg':[float('NaN'),'The mean of the maximum in-flight values of the IMU high frequency delta velocity vibration level (m/s)'],
'imu_hfdvel_mean_avg':[float('NaN'),'The mean of the mean in-flight value of the IMU delta high frequency delta velocity vibration level (m/s)'],
'obs_ang_median_avg':[float('NaN'),'The mean of the median in-flight value of the output observer angular tracking error magnitude (mrad)'],
@ -388,9 +388,9 @@ if (len(result1) > 0 and len(result2) > 0):
# IMU high frequency delta velocity vibration levels
temp = np.asarray([population_data[k].get('imu_hfdvel_peak') for k in found_keys])
result1 = 1000.0 * temp[np.isfinite(temp)]
result1 = temp[np.isfinite(temp)]
temp = np.asarray([population_data[k].get('imu_hfdvel_mean') for k in found_keys])
result2 = 1000.0 * temp[np.isfinite(temp)]
result2 = temp[np.isfinite(temp)]
if (len(result1) > 0 and len(result2) > 0):
population_results['imu_hfdvel_max_avg'][0] = np.mean(result1)
@ -464,6 +464,36 @@ if (len(result) > 0):
pp.savefig()
plt.close(13)
# IMU delta angle bias
temp = np.asarray([population_data[k].get('imu_dang_bias_median') for k in found_keys])
result = temp[np.isfinite(temp)]
if (len(result) > 0):
plt.figure(14,figsize=(20,13))
plt.hist(result)
plt.title("Gaussian Histogram - IMU Delta Angle Bias Median")
plt.xlabel("imu_dang_bias_median (rad)")
plt.ylabel("Frequency")
pp.savefig()
plt.close(14)
# IMU delta velocity bias
temp = np.asarray([population_data[k].get('imu_dvel_bias_median') for k in found_keys])
result = temp[np.isfinite(temp)]
if (len(result) > 0):
plt.figure(15,figsize=(20,13))
plt.hist(result)
plt.title("Gaussian Histogram - IMU Delta Velocity Bias Median")
plt.xlabel("imu_dvel_bias_median (m/s)")
plt.ylabel("Frequency")
pp.savefig()
plt.close(15)
# close the pdf file
pp.close()
print('Population summary plots saved in population_data.pdf')
@ -525,12 +555,9 @@ single_log_results = {
'ofx_fail_percentage':[float('NaN'),'The percentage of in-flight recorded failure events for the optical flow sensor X-axis innovation consistency test.'],
'ofy_fail_percentage':[float('NaN'),'The percentage of in-flight recorded failure events for the optical flow sensor Y-axis innovation consistency test.'],
'on_ground_transition_time':[float('NaN'),'The time in seconds measured from startup that the EKF transitioned out of in-air mode. Set to a nan if a transition event is not detected.'],
'output_obs_ang_err_mean':[float('NaN'),'Mean in-flight value of the output observer angular error (rad)'],
'output_obs_ang_err_peak':[float('NaN'),'Peak in-flight value of the output observer angular error (rad)'],
'output_obs_pos_err_mean':[float('NaN'),'Mean in-flight value of the output observer position error (m)'],
'output_obs_pos_err_peak':[float('NaN'),'Peak in-flight value of the output observer position error (m)'],
'output_obs_vel_err_mean':[float('NaN'),'Mean in-flight value of the output observer velocity error (m/s)'],
'output_obs_vel_err_peak':[float('NaN'),'Peak in-flight value of the output observer velocity error (m/s)'],
'output_obs_ang_err_median':[float('NaN'),'Median in-flight value of the output observer angular error (rad)'],
'output_obs_pos_err_median':[float('NaN'),'Median in-flight value of the output observer position error (m)'],
'output_obs_vel_err_median':[float('NaN'),'Median in-flight value of the output observer velocity error (m/s)'],
'pos_fail_percentage':[float('NaN'),'The percentage of in-flight recorded failure events for the velocity sensor consolidated innovation consistency test.'],
'pos_percentage_amber':[float('NaN'),'The percentage of in-flight position sensor consolidated innovation consistency test values > 0.5.'],
'pos_percentage_red':[float('NaN'),'The percentage of in-flight position sensor consolidated innovation consistency test values > 1.0.'],