Visualization

This repository uses Jupyter Notebook for data visualization from results generated by the post processor. The post processor can be found here.

Prerequisites

You will need:

• Python3
  • jupyter
  • pandas
  • matplotlib
  • d3graph
  • plotly
• .csv file from post processor

As long as you have the pip command line tool, the modules should be automatically installed when you run the main script. If there is an error installing the modules, whether it be due to user permissions or other reasons, run pip install -r requirements.txt

Instructions

1. Place the .csv file generated from the post processor inside the Jupyter Notebook by following these instructions
2. Call python3 main.py

The Jupyter Notebook should open in a web browser and be ready to visualize post processor data.

Exporting Notebooks

If you would like to export Jupyter Notebooks into a different format like pdf, LaTeX, or Markdown, you can use nbconvert. Note that you may need to install pandoc in order to export to a different output format. To install pandoc, run pip install pandoc or download from here.

To export, follow these instructions:

1. Change into the directory with the Jupyter Notebook in the notebooks directory
2. Call jupyter nbconvert <notebook> --to <format> where notebook is an existing Jupyter Notebook and format is the format type you want to export to. For example, jupyter nbconvert stack_area_plotly.ipynb --to pdf will convert the stack area chart notebook to a PDF document.