1. Extending ArcGIS with R
Mark Janikas, PhD

2. Outline Introduction Application Integration options
What is R? Why should I use it?
Application
Point Clustering
Integration options
R versus Rpy
Conclusions and Future Directions

3. What is R? Why should I use it?
R (The R Project for Statistical Computing) is an open-source data analysis package. (GNU S)
Widely Used
Over 60 CRAN sites across 30+ countries
Its Free
GNU GENERAL PUBLIC LICENSE
Base is powerful
Statistics, Linear Algebra, Visualization , etc…
Its extendible
1800+ Contributed Extensions
splancs, spatstat, spdep, rgdal, maptools, shapefiles

4. R Point Clustering Tools for ArcGIS
Resource Center (Code Gallery)
Contains two tools… that do the same thing!

5. Application: Point Clustering
Cluster a given a set of point locations:
Spatial Proximity
Attributes Values

6. Integration with ArcGIS
Two (Three) Integration Options With ArcGIS
Both require Python
Both have pros and cons
ESRI UC Plenary 2008
predicting plant species in unknown areas

7. Integration: R Option Decouples R and Python Python R
Retrieves and organize parameters from ArcGIS
Convert Data (Interchange)
Shapefiles, netcdf, img etc….
Spawns R given the *.r file with provided parameters R
Does the analysis
Python Script
ArcGIS
R Script

8. Integration: RPy Option
R and Python closely coupled
RPy (RPy2)
Python Interface to the R Programming Language
Python
Retrieves and organize parameters from ArcGIS
RPy module is imported and R commands are executed within the Python script file
ArcGIS
Python Script
R Processing

9. Which One Should I Use? R Option Attractive to R Programmers
“Out of Proc”: Spawning R on every execute
Use Copy Features!!!
selection sets
Projections and other environment variables
You must use an R library for handling shapefiles
maptools, shapefiles
Two files per script tool (*.py and *.r)

10. R Option Code Snippet

11. Which One Should I Use? Cont…
RPy Option
For more advanced users (Python and R knowledge)
“In Process”
Will be MUCH faster after the first call
Honors selection sets
A robust choice of database formats
Will honor environment settings (GP Functions)
Only a single file associated with your script tool

12. RPy Option Code Snippet
Source R Libraries
NumPy and R Interchange
Cluster Analysis
Create Output

13. Which One Should I Use? Cont…
Wait… Why would I go with the R Option?
Doesn’t have as many dependencies/layers
RPy
Python, R, and RPy builds have to play nice!
You must know Python, some R and now RPy.
Currently there is an open bug in RPy that must be fixed in order to run in the “In Process” mode in ArcGIS
Manual fix in the portal tool documentation
Both methods require the editing of Environment Variables in order to run properly

14. Conclusions R Can be integrated with ArcGIS using Python
contains “cutting edge” data analysis techniques from a wide body of academic and applied fields
extendible
Open-source
Can be integrated with ArcGIS using Python
R versus RPy (RPy2)
Pros and Cons

15. Future Directions RPy2 Web Portal: RTools Calling Python from R
Could be expanded upon
Calling Python from R
Leveraging geoprocessing within the R environment
RSPython:

16. Links R RPy (Link to RPy2) Python NumPy
RPy (Link to RPy2)
Python
NumPy

17. Related Sessions
Developing Python Scripts for Data Analysis Tips and Tricks
Geoprocessing Demo Theater – W, 5:00 – 6:00
Spatial Statistics: Using Spatial Statistics
TH 1:30 – 2:45
Regression Analysis for Spatial Data with ArcGIS 9.3
TH 3:15 – 4:30