Difference between revisions of "Statistical Algorithms Importer: Linux-compiled Project"

Latest revision as of 17:11, 18 October 2018

This page explains how to create a Linux-compiled project using the Statistical Algorithms Importer (SAI) portlet.

Linux Project, SAI

Project Configuration

Define project's metadata

Linux Info, SAI

Add input and output parameters and click on "Set Code" to indicate the main file to execute (i.e. the .sh file)

Linux I/O, SAI

Add information about the running environment (e.g. Linux version etc.)

Linux Interpreter, SAI

After the software creation phase a Main.R file and a Taget folder are created

Linux Create, SAI

Example Download

File:LinuxBlackBox.zip

Inheritance of Global and Infrastructure Variables

At each run of the process the globalvariables.csv file is created locally to the process (i.e. it can be read as ./globalvariables.csv), which contains the following global variables that are meant to allow the process to properly contact the e-Infrastructure services:

• gcube_username (the user who run the computation, e.g. gianpaolo.coro)

• gcube_context (the VRE the process was run in, e.g. d4science.research-infrastructures.eu/gCubeApps/RPrototypingLab)

• gcube_token (the token of the user for the VRE, e.g. 1234-567-890)

The format of the CSV file is like the one of the following example:

globalvariable,globalvalue
gcube_username,gianpaolo.coro
gcube_context,/d4science.research-infrastructures.eu/gCubeApps/RPrototypingLab
gcube_token,1234-567-890