# traclus_impl
### Purpose This is a Python implementation of the Traclus algorithm. It works for 2-D trajectories. Note that this was written as a piece of a senior project. This traclus implementation should functionally work, but it is currently slow on larger sets of trajectories.
### Install The easiest way to install is with pip install traclus_impl.
### Usage To run the Traclus algorithm, run traclus_impl.main.py, passing it the name of an input file and output file. The input file contains a json object with parameters to traclus and the raw trajectories. See “traclus_impl.integ_tests.raw_campus_trajectories.txt” for an example input file. The output file will contain a json list of representative trajectories. Optionally, provide names of files to dump the output from the partitioning and clustering stages to.
Example: navigate to directory where traclus_impl.main.py is and run “python main.py -i ./raw_traj_input -o ./traclus_output
Note that the actual entry point function of the real computation is “run_traclus” in traclus_impl.coordination.py. The “run_traclus” function takes Traclus arguments and a list of trajectories. The list of trajectories input to “run_traclus” is a list of traclus_impl.geometry.Point objects, and it returns a list of representative line segments as this same type of object.
main.py only parses arguments to traclus, calls run_traclus, and writes them to a file. It is mostly just an example of a way to use the “run_traclus” function.
The best example of complete usage is the test in “traclus_impl.integ_tests.campus_trajectories_processing_test.py”.
### Intermediate output hooks ### The “run_traclus” function in traclus_impl.coordination.py optionally takes hooks for the output of the partitioning stage and clustering stage. The hook functions for these in main.py and the “traclus_impl.integ_tests.campus_trajectories_processing_test.py” tests show some example usage.
### Running the tests. Tests exist under the traclus_impl.tests and traclus_impl.integ_tests. To run all of the tests from the commandline, navigate to the package’s root and run: python -m unittest discover -p “_test.py”
### Notes on Performance ### * Currently, the main bottleneck seems to be the quadratic clustering, and future work includes improving this. For some larger trajectory sets such as the elk file under integ_tests/deer_tests, this implementation will take a very long time. * traclus_impl.integ_tests.deer_tests.run_traclus.py is mostly used for profiling this traclus implementation on the trajectories in that folder.
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