PX4-Autopilot/Tools/ecl_ekf/analysis/post_processing.py

55 lines
2.4 KiB
Python

#! /usr/bin/env python3
"""
function collection for post-processing of ulog data.
"""
from typing import Tuple
import numpy as np
def get_gps_check_fail_flags(estimator_status: dict) -> dict:
"""
:param estimator_status:
:return:
"""
gps_fail_flags = dict()
# 0 : insufficient fix type (no 3D solution)
# 1 : minimum required sat count fail
# 2 : maximum allowed PDOP fail
# 3 : maximum allowed horizontal position error fail
# 4 : maximum allowed vertical position error fail
# 5 : maximum allowed speed error fail
# 6 : maximum allowed horizontal position drift fail
# 7 : maximum allowed vertical position drift fail
# 8 : maximum allowed horizontal speed fail
# 9 : maximum allowed vertical velocity discrepancy fail
gps_fail_flags['gfix_fail'] = ((2 ** 0 & estimator_status['gps_check_fail_flags']) > 0) * 1
gps_fail_flags['nsat_fail'] = ((2 ** 1 & estimator_status['gps_check_fail_flags']) > 0) * 1
gps_fail_flags['pdop_fail'] = ((2 ** 2 & estimator_status['gps_check_fail_flags']) > 0) * 1
gps_fail_flags['herr_fail'] = ((2 ** 3 & estimator_status['gps_check_fail_flags']) > 0) * 1
gps_fail_flags['verr_fail'] = ((2 ** 4 & estimator_status['gps_check_fail_flags']) > 0) * 1
gps_fail_flags['serr_fail'] = ((2 ** 5 & estimator_status['gps_check_fail_flags']) > 0) * 1
gps_fail_flags['hdrift_fail'] = ((2 ** 6 & estimator_status['gps_check_fail_flags']) > 0) * 1
gps_fail_flags['vdrift_fail'] = ((2 ** 7 & estimator_status['gps_check_fail_flags']) > 0) * 1
gps_fail_flags['hspd_fail'] = ((2 ** 8 & estimator_status['gps_check_fail_flags']) > 0) * 1
gps_fail_flags['veld_diff_fail'] = ((2 ** 9 & estimator_status['gps_check_fail_flags']) > 0) * 1
return gps_fail_flags
def magnetic_field_estimates_from_states(estimator_states: dict) -> Tuple[float, float, float]:
"""
:param estimator_states:
:return:
"""
rad2deg = 57.2958
field_strength = np.sqrt(
estimator_states['states[16]'] ** 2 + estimator_states['states[17]'] ** 2 +
estimator_states['states[18]'] ** 2)
declination = rad2deg * np.arctan2(estimator_states['states[17]'],
estimator_states['states[16]'])
inclination = rad2deg * np.arcsin(
estimator_states['states[18]'] / np.maximum(field_strength, np.finfo(np.float32).eps))
return declination, field_strength, inclination