Directory structure:
blog: submodule containing BLOGdata: symlink to data dirjava-src: dynamics and observation functionspython-src: code for generating the model from dataexperiments: stuff that's in flux all the time
Here is an example initial setup on a Ubuntu machine. You only have to do this once. You can skip some steps; for example if you don't want to use a virtualenv, you can install the Python packages system-wide, and if you already have sbt you don't need to reinstall it.
cd ppaml-slam
# Create Python virtualenv and install requirements.
mkvirtualenv ppaml-slam
setvirtualenvproject
pip install -r requirements.txt
# Check out and compile BLOG submodule.
git submodule update --init
cd blog
sudo apt-get install sbt
sbt compile stage
cd ..
# Make sure data/ is a symlink to the data dir.
# It should contain directories `1_straight` etc.
ln -s ....path-to-data.... data
You have to do the following in every terminal. This will set up the
appropriate PYTHONPATH and CLASSPATH so that all the components are found.
source setup_env
cd java-src
# Compile:
make
# Run unit tests:
make test
cd experiments
# Generate car.blog in the current directory:
python -m ppaml_car.blog_gen 2_bend noisy
# Run BLOG particle filter and write out.json:
../blog/blog -e blog.engine.ParticleFilter -n 100 -r -o out.json car.blog
# Evaluate results:
python -m ppaml_car.evaluate 2_bend out.json --plot