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:
- R. (Note: Installing RStudio also installs R.)
- Node and npm. (Note: Installing Node also installs npm.)
- Angular CLI. (Note: Use
npm install -g @angular/cli
in the terminal.)
To install the app itself:
-
Install the OpenCPU R package in an R terminal, using
install.packages("opencpu")
. -
Install the app's dependencies, using
npm install
. -
Install the StatLets R package, found in
./R-package
, in an R terminal usinglibrary(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).
- Make sure the working directory is set to
The app consists of two parts.
- To start the OpenCPU backend, which executes the R code,
open an R terminal and run
Rscript scripts/startOpenCPU.R
. - 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.