Please note that currently this project is not compatable with Windows operating systems.
This project wraps the Realtime Online Spatiotemporal Topic Modeling (ROST) library from WHOI's WARPLab.
In order to run this project you will need to clone their repository and follow
the installation instructions found in their README.
Once ROST is installed, change the rost_path variable in conf.py to be the path to /rost-cli/bin/ directory
on your machine.
The dependencies of this project are listed requirements.txt. The code below will install these
requirements in a virtual environment. This requires virtualenv, if you don't have it just run
a quick pip install virtualenv.
$ virtualenv --python=python3.6 venv
$ source venv/bin/activate
(venv) $ pip install -r requirements.txt
Once all dependencies are installed, the project can be run with (venv) $ ./run_model.sh, which will run all
project modules using the parameters specified in conf.py.
Modules can be run individually with (venv) $ python module_name.py. For example, the stft module
can be run individually with (venv) $ python stft.py. You may want to run the modules
individually to test different parameters of that module without rerunning the previous modules.
A successful run will produce a plot similar to the following:
On top is a spectrogram of a ~50 second segment of the target file specified in conf.py. On bottom
is a stacked bar plot of topic probabilities over documents, where documents represent small increments
of time.
- If the modules are run individually, they should be run in the order that they are run in run_model.sh. each is dependant on the output of the last.
- If visualize.py raises an error saying that Python was not installed as a framework, try the solution here