Welcome to savvy’s documentation!

Introduction

Do you savvy your sensitivity analysis results? savvy is a data visualization toolkit that provides interactive visualizations of the results from high dimensionality global sensitivity analyses. Users can visualize Sobol sensitivity analysis results generated by SALib, or any data with the same structure (see the sample SALib output in the folder savvy/sample_data_files/ for this structure).

For information on sensitivity analysis please see the SALib documentation.

savvy was written to visualize the total, first order, and second order sensitivities of 30 outputs from a lignin pyrolysis model with 410 parameters (available here). Consequently, some functionality is specific to our model and is noted as such in relevant docstrings, but overriding the default arguments in these functions allows users to use any SALib output data from SALib.analyze.sobol.

Cite savvy:

Contents

• savvy Requirements
• Getting Started With savvy
  • Installing savvy
  • Installing required packages
  • Installing graph-tool (for mac)
  • Quick Start Tutorial
• Docstrings for savvy modules
  • sensitivity_tools.py
  • data_processing.py
  • plotting.py
  • interactive_plots.py
  • network_tools.py

Package Structure

savvy’s architecture is shown below. Blue rectangles are savvy modules; green diamonds are input or output files; and the red rectangle is any black-box model of your choice that can take a set of inputs and produce outputs you would like to analyze.

Everything in the top half of this diagram, bounded by the green diamonds, is the typical workflow for a standard sensitivity analysis using SALib, and can be performed independently from savvy (using savvy.sensitivity_tools ensures your files will be in the proper format to be visualized with savvy, but is not required to use SALib). Once you have your sensitivity analysis results, with filenames that start with “analysis”, you are ready to visualize with savvy.

Indices and tables

• Index
• Module Index
• Search Page