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Create an R code only version of tripack functions
Delaunay triangulation can be useful in the fitting of bivariate surfaces over non-convex regions, and solving of closest node and shortest path problems in the presence of physical barriers (e.g., the shortest water route from Athens to Liverpool or the optimai path of a robot making its mail delivery route on the floor of a business establishment).
The R package tripack is used by numerous other packages, but it is based on legacy FORTRAN code. The algorithm is documented in C;ine and Rena (1990), and it would be helpful for many other people's work to have it natively coded in R.
What exactly do you want your contributor to code in the 10 week coding period? What functions? What do they do? Docs? Tests? Vignettes?
Mentors, please explain how this project will produce a useful package for the R community.
MENTORS: fill in this part. each project needs 2 mentors. One should be an expert R programmer with previous package development experience, and the other can be a domain expert in some other field or application area (optimization, bioinformatics, machine learning, data viz, etc). Ideally one of the two mentors should have previous experience with GSOC (either as a contributor or mentor). Please provide contact info for each mentor, along with qualifications.
IMPORTANT: you MUST write "EVALUATING" for one mentor, who will be required to do the three evaluations of the contributor during the summer. In previous years we have had issues with mentors who do not fill in evaluations, and when this happens R project is penalized (money is taken away), although contributors are not penalized (contributors are passed by default if no mentor eval is submitted). Therefore one mentor must take responsibility for doing the evaluations, and you must indicate that here, and your contributor must indicate that as well in the application. If it is not clear which mentor will be the EVALUATING mentor then your project will not be accepted. Example:
Contributors, please contact mentors below after completing at least one of the tests below.
- EVALUATING MENTOR: Toby Hocking toby.hocking@r-project.org is the author of R packages X and Y.
- Other Dev other.dev@gmail.com is an expert in machine learning, and has previous GSOC experience with NAME_OF_OPEN_SOURCE_ORGANIZATION in 2015-2016.
Contributors, please do one or more of the following tests before contacting the mentors above.
MENTORS: write several tests that potential contributors can do to demonstrate their capabilities for this particular project. Ask some hard questions that will give you insight about how the contributors write code to solve problems. You'll see that the harder the questions that you ask, the easier it will be for you to choose between the contributors that apply for your project! Please modify the suggestions below to make them specific for your project.
- Easy: something that any useR should be able to do, e.g. download some existing package listed in the Related Work, and run it on some example data.
- Medium: something a bit more complicated. You can encourage contributors to write a script or some functions that show their R coding abilities.
- Hard: Can the contributor write a package with Rd files, tests, and vignettes? If your package interfaces with non-R code, can the contributor write in that other language?
Contributors, please post a link to your test results here.
- EXAMPLE CONTRIBUTOR 1 NAME, LINK TO GITHUB PROFILE, LINK TO TEST RESULTS.