transport trajectory search
├── LICENSE
├── Makefile <- Makefile with commands like `make data` or `make train`
├── README.md <- The top-level README for developers using this project.
├── data
│ ├── external <- Data from third party sources.
│ ├── interim <- Intermediate data containing candidate trajectory ID and rtree files.
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
│
├── docs <- A default Sphinx project; see sphinx-doc.org for details
│
├── models <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks <- Jupyter notebooks for visualizing trajectories and compute performance statistics.
│ ├── pruning_power.py
│ └── trajectory_viz.py
│
├── references <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated graphics and figures to be used in reporting
│
├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
│
├── setup.py <- makes project pip installable (pip install -e .) so src can be imported
├── src <- Source code for use in this project.
│ ├── __init__.py <- Makes src a Python module
│ │
│ ├── data <- Scripts to process raw data
│ │ └── make_trajectory.py
│ │
│ ├── features <- Scripts to build rtree
│ │ ├── build_rtree.py
│ │ └── build_bbox.py
│ │
│ ├── models <- Scripts to search rtrees and then use EDR to compute top-k
│ │ │ trajectories
│ │ │ <- Script to sequential scan all trajectories and find top-k
│ │ ├── predict_model.py
│ │ ├── search_rtree.py
│ │ └── build_truth.py
│ │
│ └── statistics <- Scripts to compute top k accuracy of result
│ └── topkAccuracy.py
│
└── tox.ini <- tox file with settings for running tox; see tox.testrun.org
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