angle- and delta velocity bias variance
- the contribution of process noise per iteration for these states can be so
small that it gets lost if using standard floating point summation
Signed-off-by: Roman <bapstroman@gmail.com>
Heading data is assumed to be from a dual antenna array at a specified yaw angle offset in body frame, but with the heading data already corrected for antenna offset. The offset is required to apply the correct compensation for combined rotations and to determine when the yaw observation has become badly conditioned.
* 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
kamilritz
Martina Rivizzigno
RomanBapst
Paul Riseborough
Daniel Agar
Peter Dürr
CarlOlsson
Julian Oes
bugobliterator