An IDE facilitating statistical analysis by providing a node editor to enhance R.

Understand that this app was only tested with Chrome (v59). Other browsers might cause issues.

This project was generated with Angular CLI version 1.1.3.

Install the following development tools:

1. R. (Note: Installing RStudio also installs R.)
2. Node and npm. (Note: Installing Node also installs npm.)
3. Angular CLI. (Note: Use npm install -g @angular/cli in the terminal.)

To install the app itself:

1. Install the OpenCPU R package in an R terminal, using install.packages("opencpu").

2. Install the app's dependencies, using npm install.

3. Install the StatLets R package, found in ./R-package, in an R terminal using library(devtools); install().

   • Make sure the working directory is set to ./R-package.
   • Reinstall StatLets's R package whenever it is changed (e.g., a new R function is added).

The app consists of two parts.

1. To start the OpenCPU backend, which executes the R code, open an R terminal and run Rscript scripts/startOpenCPU.R.
2. Run ng serve for a dev server. Navigate to http://localhost:4200/. The app will automatically reload if you change any of the source files.

Run ng generate component component-name to generate a new component. You can also use ng generate directive|pipe|service|class|module.

Run ng build to build the project. The build artifacts will be stored in the dist/ directory. Use the -prod flag for a production build.

Run ng test to execute the unit tests via Karma.

Run ng e2e to execute the end-to-end tests via Protractor. Before running the tests make sure you are serving the app via ng serve.

To get more help on the Angular CLI use ng help or go check out the Angular CLI README.