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informatiCup2018 CircleCI

Predicting the optimal strategy for fueling for a given route (task description).

Report
Routes

Project Organization

├── LICENSE
├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── external       <- Data from third party sources.
│   ├── 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
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
└── src                <- Source code for use in this project.
    ├── __init__.py    <- Makes src a Python module
    │
    ├── 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
    │
    └── visualization  <- Scripts to create exploratory and results oriented visualizations
        └── visualize.py

Setup

  • Clone the repository including submodules (to include the challenge data as well):
    git clone --recursive [email protected]:WGierke/informatiCup2018.git
    However, if you already downloaded the InformatiCup2018 repository, you can also create a symbolic link that shows from data/raw/input_data to the informatiCup2018 repository. A sanity check would be that data/raw/input_data/Eingabedaten/Fahrzeugrouten/Bertha\ Benz\ Memorial\ Route.csv is accessible.

  • Install all dependencies
    pip3 install -r requirements.txt

Usage

  • To start the server:
    python3 src/serving/server.py
  • To predict the gas prices given using training data up to a specified point in time for a given point in time:
    python3 src/serving/price_prediction.py --input PATH_TO_PREDICTION_POINTS.CSV
  • To predict an optimal route given the path to an input file:
    python3 src/serving/route_prediction.py --input PATH_TO_ROUTE.CSV

Credits

Materialize
bootstrap-material-datetimepicker