* Unfortunately, due to the SWIG dependency, we need sudo to install on
Travis (conflicts when adding with debian-sid source prevent using addons)
which means we cannot use the container-based infrastructure anymore.
* Building the Python bindings requires g++5 (at least with -Werr set).
* When building the Python bindings on Travis, the numpy includes are not found
by cmake, so they have to be added separately by running a Python process with
`numpy.get_include()`
* The build script now (somewhat clumsily) depends on the RUN_PYTEST environment
variable. If it is set to anything other than "", it will make the tests and
run tests and benchmarks
* Add requirements.txt file with required Python packages
* Read requirements.txt from CMakeLists.txt to check dependencies and alert the
user if necessary.
* Add SWIG interface definition (and external numpy interface) to ecl classes
* Add section in CMakeLists.txt to build Python bindings and execute
Python-based tests
* Write (property-based) tests that show the basic functionality of the Python
bindings and the EKF (using pytest and hypothesis libraries)
* Write minimal benchmark for the EKF update (using benchmark plugin for pytest)
* Add plotting utilities to analyze tests
* Add lint script to keep the Python scripts clean
* This is a sane choice (and should arguably always be done for classes with
virtual methods to avoid undefined behavior)
* It is required for wrapping the EstimatorInterface with SWIG (without virtual
destructor, deriving from the EstimatorInterface leads to
-Werror=delete-non-virtual-dtor).
When starting aiding using EV only and commencing GPS aiding later, this change means that the GPS origin is set to the local position 0,0 point rather than the current vehicle position. This avoids large changes in local position when GPs aiding starts.
Fuse external vision data using a relative position odometry method when GPS data is also being used and enable both GPOS and EV data to be fused on the same time step.
Moves calculation only required for mag heading fusion into the if (_control_status.flags.mag_hdg) branch
When using EV yaw, the observed yaw angle is calculated directly from the EV quaternions using derived expressions from references in code comments.