VisionEval (VE) is a model system and supporting software framework for building collaborative disaggregate strategic planning models. Background information is available on the project webpage and project administration is available on the linked wiki.
The VE software framework is written in the R programming language for statistical computing and graphics. The software framework is available as a R package, visioneval. The purpose of the model system and framework is to enable models be created in a plug-and-play fashion from modules that are also distributed as R packages. A simple R script is used to implement a model by initializing the model environment and then calling modules successively. This repository contains currently contains a demonstration module package and demonstration model script and associated resources. In the future, the repository will hold a number of working modules, model scripts, and resources that implement the GreenSTEP model and related strategic planning models.
This repository is organized into two directories:
- The sources directory contains four directories:
- visioneval framework package
- VE modules such as VESimHouseholds and VESyntheticFirms
- VE models such as the pilot version of VERPAT
- VE GUI graphical user interface and scenario viewer / visualizer for running and viewing results of VE models
- The api directory contains documentation of the model system. The model system design document is the most complete at the present time. VisionEval framework functions are documented in a network visualization of the functions and their call relationships. Functions are represented by network nodes. Call relationships are represented by arrows which point from the calling function to the called function. Function details are shown at the bottom of the page when a function node is selected.
- Install R 3.3+ in a location where you have write access.
- Start R
- If working within a proxy server (like ODOT), run the following commands to enable install from GitHub:
library(httr)
set_config(use_proxy(url="proxynew.odot.state.or.us", port=8080))
set_config( config( ssl_verifypeer = 0L ) )
- Run the following commands to download and install the required libraries and their dependencies:
source("http://bioconductor.org/biocLite.R")
biocLite()
biocLite("rhdf5")
install.packages("devtools")
install.packages("plyr")
install.packages("shiny")
install.packages("shinyjs")
install.packages("shinyFiles")
install.packages("data.table")
install.packages("DT")
install.packages("shinyBS")
install.packages("future")
install.packages("testit")
install.packages("jsonlite")
install.packages("rhandsontable")
install.packages("shinyAce")
install.packages("envDocument")
install.packages("rhandsontable")
devtools::install_github("tdhock/namedCapture")
devtools::install_github("trestletech/shinyTree")
devtools::install_github("gregorbj/VisionEval/sources/framework/visioneval")
- Run the following commands to download and install the required VE modules:
#the following modules are required for the pilot VERPAT; others are required for VERSPM
devtools::install_github("gregorbj/VisionEval/sources/modules/VESyntheticFirms")
devtools::install_github("gregorbj/VisionEval/sources/modules/VESimHouseholds")
- Git Clone (i.e. copy) this repository to your computer.
- Start R
- Run the following commands:
#point to the location of the cloned repository, not the location of the auto-installed R packages
full_path_to_VERPAT = "C:/projects/development/VisionEval/sources/models/VERPAT"
setwd(full_path_to_VERPAT)
source("run_model.R")
- Git Clone (i.e. copy) this repository to your computer.
- Start R
- Run the following commands:
library("shiny")
runGitHub("gregorbj/VisionEval", subdir="sources/VEGUI", ref="master") #master branch
runGitHub("gregorbj/VisionEval", subdir="sources/VEGUI", ref="develop") #develop branch
- The VE GUI should launch in your browser
- Click "Select Scenario Script" and navigate to the VERPAT run_model.R script in your local repository
- Click "Run" and then "Run Model Script" to run the VERPAT model
For those new to R, we recommend installing R Studio.