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ecl-ekf tools: clean up - move code to correct scope

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- move code that is needed for general analysis out of plot scope
This commit is contained in:
johannes
2018-04-27 22:34:17 +02:00
committed by Lorenz Meier
parent 12e967173d
commit a0b4bbed5e
1 changed files with 7 additions and 4 deletions
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Tools/ecl_ekf/process_logdata_ekf.py
+7 -4
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@@ -75,13 +75,13 @@ if ('accel_inconsistency_m_s_s' in sensor_preflight.keys()) and ('gyro_inconsist
pp.savefig() pp.savefig()
plt.close(0) plt.close(0)
# vertical velocity and position innovations
plt.figure(1,figsize=(20,13))
# generate max, min and 1-std metadata # generate max, min and 1-std metadata
innov_time = 1e-6*ekf2_innovations['timestamp'] innov_time = 1e-6*ekf2_innovations['timestamp']
status_time = 1e-6*estimator_status['timestamp'] status_time = 1e-6*estimator_status['timestamp']
# vertical velocity and position innovations
plt.figure(1,figsize=(20,13))
# generate metadata for velocity innovations # generate metadata for velocity innovations
innov_2_max_arg = np.argmax(ekf2_innovations['vel_pos_innov[2]']) innov_2_max_arg = np.argmax(ekf2_innovations['vel_pos_innov[2]'])
innov_2_max_time = innov_time[innov_2_max_arg] innov_2_max_time = innov_time[innov_2_max_arg]
@@ -784,7 +784,7 @@ pp.savefig()
plt.close(10) plt.close(10)
# innovation_check_flags summary # innovation_check_flags summary
plt.figure(11,figsize=(20,13))
# 0 - true if velocity observations have been rejected # 0 - true if velocity observations have been rejected
# 1 - true if horizontal position observations have been rejected # 1 - true if horizontal position observations have been rejected
# 2 - true if true if vertical position observations have been rejected # 2 - true if true if vertical position observations have been rejected
@@ -808,6 +808,9 @@ hagl_innov_fail = ((2**8 & estimator_status['innovation_check_flags']) > 0)*1
ofx_innov_fail = ((2**9 & estimator_status['innovation_check_flags']) > 0)*1 ofx_innov_fail = ((2**9 & estimator_status['innovation_check_flags']) > 0)*1
ofy_innov_fail = ((2**10 & estimator_status['innovation_check_flags']) > 0)*1 ofy_innov_fail = ((2**10 & estimator_status['innovation_check_flags']) > 0)*1
# plot innovation_check_flags summary
plt.figure(11,figsize=(20,13))
plt.subplot(5,1,1) plt.subplot(5,1,1)
plt.title('EKF Innovation Test Fails') plt.title('EKF Innovation Test Fails')
plt.plot(status_time,vel_innov_fail,'b',label='vel NED') plt.plot(status_time,vel_innov_fail,'b',label='vel NED')