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ekf2_post-processing: use estimator_status_flags instead of bitmasks

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bresch
2022-05-24 16:15:42 +02:00
committed by Mathieu Bresciani
parent 016b8aeb35
commit d04a91a3ae
5 changed files with 72 additions and 167 deletions
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Tools/ecl_ekf/plotting/pdf_report.py
+34 -28
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@@ -11,7 +11,7 @@ import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
from pyulog import ULog
from analysis.post_processing import magnetic_field_estimates_from_states, get_estimator_check_flags
from analysis.post_processing import magnetic_field_estimates_from_states, get_gps_check_fail_flags
from plotting.data_plots import TimeSeriesPlot, InnovationPlot, ControlModeSummaryPlot, \
CheckFlagsPlot
from analysis.detectors import PreconditionError
@@ -33,6 +33,11 @@ def create_pdf_report(ulog: ULog, multi_instance: int, output_plot_filename: str
except:
raise PreconditionError('could not find estimator_status instance', multi_instance)
try:
estimator_status_flags = ulog.get_dataset('estimator_status_flags', multi_instance).data
except:
raise PreconditionError('could not find estimator_status_flags instance', multi_instance)
try:
estimator_states = ulog.get_dataset('estimator_states', multi_instance).data
except:
@@ -68,12 +73,13 @@ def create_pdf_report(ulog: ULog, multi_instance: int, output_plot_filename: str
except:
raise PreconditionError('could not find innovation data')
control_mode, innov_flags, gps_fail_flags = get_estimator_check_flags(estimator_status)
gps_fail_flags = get_gps_check_fail_flags(estimator_status)
status_time = 1e-6 * estimator_status['timestamp']
status_flags_time = 1e-6 * estimator_status_flags['timestamp']
b_finishes_in_air, b_starts_in_air, in_air_duration, in_air_transition_time, \
on_ground_transition_time = detect_airtime(control_mode, status_time)
on_ground_transition_time = detect_airtime(estimator_status_flags, status_flags_time)
with PdfPages(output_plot_filename) as pdf_pages:
@@ -173,9 +179,9 @@ def create_pdf_report(ulog: ULog, multi_instance: int, output_plot_filename: str
# plot control mode summary A
data_plot = ControlModeSummaryPlot(
status_time, control_mode, [['tilt_aligned', 'yaw_aligned'],
['using_gps', 'using_optflow', 'using_evpos'], ['using_barohgt', 'using_gpshgt',
'using_rnghgt', 'using_evhgt'], ['using_magyaw', 'using_mag3d', 'using_magdecl']],
status_flags_time, estimator_status_flags, [['cs_tilt_align', 'cs_yaw_align'],
['cs_gps', 'cs_opt_flow', 'cs_ev_pos'], ['cs_baro_hgt', 'cs_gps_hgt',
'cs_rng_hgt', 'cs_ev_hgt'], ['cs_mag_hdg', 'cs_mag_3d', 'cs_mag_dec']],
x_label='time (sec)', y_labels=['aligned', 'pos aiding', 'hgt aiding', 'mag aiding'],
annotation_text=[['tilt alignment', 'yaw alignment'], ['GPS aiding', 'optical flow aiding',
'external vision aiding'], ['Baro aiding', 'GPS aiding', 'rangefinder aiding',
@@ -188,7 +194,7 @@ def create_pdf_report(ulog: ULog, multi_instance: int, output_plot_filename: str
# plot control mode summary B
# construct additional annotations for the airborne plot
airborne_annotations = list()
if np.amin(np.diff(control_mode['airborne'])) > -0.5:
if np.amin(np.diff(estimator_status_flags['cs_in_air'])) > -0.5:
airborne_annotations.append(
(on_ground_transition_time, 'air to ground transition not detected'))
else:
@@ -197,7 +203,7 @@ def create_pdf_report(ulog: ULog, multi_instance: int, output_plot_filename: str
if in_air_duration > 0.0:
airborne_annotations.append(((in_air_transition_time + on_ground_transition_time) / 2,
'duration = {:.1f} sec'.format(in_air_duration)))
if np.amax(np.diff(control_mode['airborne'])) < 0.5:
if np.amax(np.diff(estimator_status_flags['cs_in_air'])) < 0.5:
airborne_annotations.append(
(in_air_transition_time, 'ground to air transition not detected'))
else:
@@ -205,7 +211,7 @@ def create_pdf_report(ulog: ULog, multi_instance: int, output_plot_filename: str
(in_air_transition_time, 'in-air at {:.1f} sec'.format(in_air_transition_time)))
data_plot = ControlModeSummaryPlot(
status_time, control_mode, [['airborne'], ['estimating_wind']],
status_flags_time, estimator_status_flags, [['cs_in_air'], ['cs_wind']],
x_label='time (sec)', y_labels=['airborne', 'estimating wind'], annotation_text=[[], []],
additional_annotation=[airborne_annotations, []],
plot_title='EKF Control Status - Figure B', pdf_handle=pdf_pages)
@@ -214,15 +220,15 @@ def create_pdf_report(ulog: ULog, multi_instance: int, output_plot_filename: str
# plot innovation_check_flags summary
data_plot = CheckFlagsPlot(
status_time, innov_flags, [['vel_innov_fail', 'posh_innov_fail'], ['posv_innov_fail',
'hagl_innov_fail'],
['magx_innov_fail', 'magy_innov_fail', 'magz_innov_fail',
'yaw_innov_fail'], ['tas_innov_fail'], ['sli_innov_fail'],
['ofx_innov_fail',
'ofy_innov_fail']], x_label='time (sec)',
status_flags_time, estimator_status_flags, [['reject_hor_vel', 'reject_hor_pos'], ['reject_ver_vel', 'reject_ver_pos',
'reject_hagl'],
['reject_mag_x', 'reject_mag_y', 'reject_mag_z',
'reject_yaw'], ['reject_airspeed'], ['reject_sideslip'],
['reject_optflow_x',
'reject_optflow_y']], x_label='time (sec)',
y_labels=['failed', 'failed', 'failed', 'failed', 'failed', 'failed'],
y_lim=(-0.1, 1.1),
legend=[['vel NED', 'pos NE'], ['hgt absolute', 'hgt above ground'],
legend=[['vel NE', 'pos NE'], ['vel D', 'hgt absolute', 'hgt above ground'],
['mag_x', 'mag_y', 'mag_z', 'yaw'], ['airspeed'], ['sideslip'],
['flow X', 'flow Y']],
plot_title='EKF Innovation Test Fails', annotate=False, pdf_handle=pdf_pages)
@@ -344,33 +350,33 @@ def create_pdf_report(ulog: ULog, multi_instance: int, output_plot_filename: str
data_plot.close()
def detect_airtime(control_mode, status_time):
def detect_airtime(estimator_status_flags, status_flags_time):
# define flags for starting and finishing in air
b_starts_in_air = False
b_finishes_in_air = False
# calculate in-air transition time
if (np.amin(control_mode['airborne']) < 0.5) and (np.amax(control_mode['airborne']) > 0.5):
in_air_transtion_time_arg = np.argmax(np.diff(control_mode['airborne']))
in_air_transition_time = status_time[in_air_transtion_time_arg]
elif (np.amax(control_mode['airborne']) > 0.5):
in_air_transition_time = np.amin(status_time)
if (np.amin(estimator_status_flags['cs_in_air']) < 0.5) and (np.amax(estimator_status_flags['cs_in_air']) > 0.5):
in_air_transtion_time_arg = np.argmax(np.diff(estimator_status_flags['cs_in_air']))
in_air_transition_time = status_flags_time[in_air_transtion_time_arg]
elif (np.amax(estimator_status_flags['cs_in_air']) > 0.5):
in_air_transition_time = np.amin(status_flags_time)
print('log starts while in-air at ' + str(round(in_air_transition_time, 1)) + ' sec')
b_starts_in_air = True
else:
in_air_transition_time = float('NaN')
print('always on ground')
# calculate on-ground transition time
if (np.amin(np.diff(control_mode['airborne'])) < 0.0):
on_ground_transition_time_arg = np.argmin(np.diff(control_mode['airborne']))
on_ground_transition_time = status_time[on_ground_transition_time_arg]
elif (np.amax(control_mode['airborne']) > 0.5):
on_ground_transition_time = np.amax(status_time)
if (np.amin(np.diff(estimator_status_flags['cs_in_air'])) < 0.0):
on_ground_transition_time_arg = np.argmin(np.diff(estimator_status_flags['cs_in_air']))
on_ground_transition_time = status_flags_time[on_ground_transition_time_arg]
elif (np.amax(estimator_status_flags['cs_in_air']) > 0.5):
on_ground_transition_time = np.amax(status_flags_time)
print('log finishes while in-air at ' + str(round(on_ground_transition_time, 1)) + ' sec')
b_finishes_in_air = True
else:
on_ground_transition_time = float('NaN')
print('always on ground')
if (np.amax(np.diff(control_mode['airborne'])) > 0.5) and (np.amin(np.diff(control_mode['airborne'])) < -0.5):
if (np.amax(np.diff(estimator_status_flags['cs_in_air'])) > 0.5) and (np.amin(np.diff(estimator_status_flags['cs_in_air'])) < -0.5):
if ((on_ground_transition_time - in_air_transition_time) > 0.0):
in_air_duration = on_ground_transition_time - in_air_transition_time
else: