Installation

Setting up and running locally

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Tested with following configurations:

• Python 2.7.12, R i386 3.4.3 (32-bit), Linux 4.10.0-37-generic x86_64
• Python 2.7.12, R i386 3.4.3 (32-bit), Windows 10 Home (version 1709, build 16299.248)

• Download CrowdNav & install required dependencies

  • Resource to install setuptools
  • Resource to install SUMO for Linux and Windows
  • Run Zookeeper & Kafka
  • Create a host entry by adding 127.0.0.1 Kafka to /etc/hosts file

• Run CrowdNav and start simulation

• Download ElasticSearch 5.6.3 and follow these instructions according to ElasticSearch 5.6.3. Installation can be verified by sending a GET request to (or navigating via browser) http://localhost:9200/

• Download R.

  • For Linux see this tutorial.
  • For Windows:
    • extend PATH variable with R's home. See these instructions. This and this might also be helpful.

• Download OEDA

• In OEDA/R folder:

  • Run RScript install_packages.R
  • Run RScript start_R_server.R (make sure localhost:8004 is not being used before running)

• In OEDA/Backend folder:

  • Instructions to install libraries for Windows: (as they are around 80 MBs in total, we have not included them in the repository), also see and C++ compiler for Windows

    • Download following wheels and install them by running pip install wheel_name.whl
      • numpy‑1.13.3+mkl‑cp27‑cp27m Most libraries depend on this, so install this first.
      • scipy‑1.0.0‑cp27‑cp27m
      • scikit_learn‑0.19.1‑cp27‑cp27m
      • matplotlib‑2.2.0‑cp27‑cp27m
      • rpy2‑2.7.8‑cp27‑none
      • pandas‑0.22.0‑cp27‑cp27m
      • Cython‑0.27.3‑cp27‑cp27m

  • Run python setup.py install

  • Change user_db_config.json according to your specifications (database host, port) by using user_db_config.json.template located in /oeda/databases

  • Change experiment_db_config.json if you would like to insert experiment data to an index instead of rtx

  • Run npm install -g nodemon

  • Run nodemon server.py

• In OEDA/Frontend folder:

  • Run npm install -g @angular/cli
  • Run npm install
  • Run serve.sh for Linux or serve.bat for Windows and navigate to localhost:4200

Running via Docker

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Under development