ayatori

Python module that processes public transport information (in GTFS format) to create route generation algorithms. Currently in progress of reworking the repo.

Installation guide

Please read install.md for details on how to set up this project.

Project Organization

├── LICENSE
├── tasks.py           <- Invoke with commands like `notebook`.
├── README.md          <- The top-level README for developers using this project.
├── install.md         <- Detailed instructions to set up this project.
├── data
│   ├── external       <- Data from third party sources.
│   ├── interim        <- Intermediate data that has been transformed.
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
├── models             <- Trained and serialized models, model predictions, or model summaries.
│
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jqp-initial-data-exploration`.
│
├── 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.
│
├── environment.yml    <- The requirements file for reproducing the analysis environment.
│
├── .here              <- File that will stop the search if none of the other criteria
│                         apply when searching head of project.
│
├── setup.py           <- Makes project pip installable (pip install -e .)
│                         so ayatori can be imported.
│
└── ayatori               <- Source code for use in this project.
    ├── __init__.py    <- Makes ayatori a Python module.
    │
    ├── data           <- Scripts to download or generate data.
    │   └── make_dataset.py
    │
    ├── features       <- Scripts to turn raw data into features for modeling.
    │   └── build_features.py
    │
    ├── models         <- Scripts to train models and then use trained models to make
    │   │                 predictions.
    │   ├── predict_model.py
    │   └── train_model.py
    │
    ├── utils          <- Scripts to help with common tasks.
        └── paths.py   <- Helper functions to relative file referencing across project.
    │
    └── visualization  <- Scripts to create exploratory and results oriented visualizations.
        └── visualize.py

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Project based on the cookiecutter conda data science project template.