1 / 17

Extending ArcGIS with R

Extending ArcGIS with R. Mark Janikas , PhD mjanikas@esri.com. Outline . Introduction What is R? Why should I use it? Application Point Clustering Integration options R versus Rpy Conclusions and Future Directions. What is R? Why should I use it?.

rogan-humphrey
Télécharger la présentation

Extending ArcGIS with R

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Extending ArcGIS with R Mark Janikas, PhD mjanikas@esri.com

  2. Outline • Introduction • 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 • 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 • 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 • Could be expanded upon • Calling Python from R • Leveraging geoprocessing within the R environment • RSPython: http://www.omegahat.org/RSPython/

  16. Links • R • http://www.r-project.org/index.html • RPy (Link to RPy2) • http://rpy.sourceforge.net/ • Python • http://www.python.org/ • NumPy • http://www.numpy.org/

  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

More Related