iNZight Lite

This is the online version of iNZight (http://lite.docker.stat.auckland.ac.nz)

To run locally:

With Docker

1. Ensure that Docker is installed and running
2. Either pull the image from dockerhub, or within the root lite directory, run make build TAG=latest to build the latest image
3. In the root lite directory, run make run TAG=latest to run on localhost at port 3838

Directly

iNZight Lite is a shiny app, so you can run it locally if you have R installed. If you use RStudio, see instructions further down.

1. Download and unzip or clone this repository

   Note: if you use Git to clone the repository, you can easily keep Lite updated via git pull

2. Open R and set the working directory to the Lite folder

setwd("/path/to/Lite")

3. Install the devtools R package (if you don't already have it):

install.packages("devtools")

4. Install package dependencies (NOTE: we host iNZight packages on our own server, see below)

devtools::install_deps(repos = c("http://r.docker.stat.auckland.ac.nz/R",
                                 "https://cloud.r-project.org/"))

5. Run the iNZight Lite app!

shiny::runApp()

RStudio users:

1. If you have git installed: in RStudio > File > New Project > Version Control > Git

   • For the URL, enter: https://github.com/iNZightVIT/Lite.git
   • And choose a location to save the app
   • Then Create Project

   If you don't have git:

   • Download and unzip the app
   • In the folder, double click Lite.rproj to open the project in RStudio

2. To install the dependencies, enter the following into the Console:

install.packages("devtools")  ## skip if you know you already have devtools
devtools::install_deps(repos = c("http://r.docker.stat.auckland.ac.nz/R",
                                 "https://cloud.r-project.org/"))

3. To run iNZight Lite, open the ui.R file and click the Run App button at the top.

Send bug reports/errors to [email protected].

Directories:

• data: This directory holds all the data. The data must be placed in sub-directories, which will come up as data categories within iNZight-Lite.

• www: This directory is used for graphics and/or web-related files such as .css and .gif/.jpeg/.png javascript files. Images are stored in a sub-directory called "images". Javascript code is stored in a subdirectory "js".

• panels: This directory contains the gui, server, help, and other functions for each module.

Main files:

• README: Documentation for iNZight Lite. Update as required.

• global.R: Defines functions and variables that are used globally. For now, all non-GUI functions are stored here.

• server.R: Script for shiny server.

• ui.R: Defines the main GUI.

• functions.R Defines al functions used in iNZight-lite, some of them are also in iNZightTools.

• data: This directory holds all the data. The data must be placed in sub-directories, which will come up as data categories within iNZight Lite.

• www: This directory is used for graphics and/or web-related files such as .css and .gif/.jpeg/.png. Images are stored in a sub-directory called "images".

• panels: This directory contains the gui, server, help, and other functions for each module. The directory/file names will be of the form:

  • [Directory] N_(sub-)panel-name
  • [File] 1_panelname-panel-gui.R
  • [File] 2_panelname-panel-server.R
  • [File] 3_panelname-panel-help.R
  • [File] 4_panelname-panel-null.R
  • [File] 5_panelname-panel-other.R

iNZight-lite URL feature

Some GET parameters can be added to the URL to access iNZight-lite. In the moment the following are implemented.

• url: An URL to a dataset sitting somewhere in the internet.
• example: A name of an data set inside the data folder.
• land: The place where iNZight-lite starts. If not specified it is "About". Three possibilities (visualize, timeSeries, regression).
• x: The x variable in the visualize module
• y: The y variable in the visualize module
• time: The variable in time series where the dates are stored. -seriesVars A comma seperated list of column names. This names are set in time series to be plotted
• Y: The dependend variable in regression.
• predict: Comma seperated list with predictor variables.
• confound: Comma seperated list for confounding variables.