[Rd] Type annotations for R function parameters.

[Brian Rowe]

The type constraints in lambda.r make this relatively easy. The idea is to add a declaration before a function that provides static typing on the function arguments. The type constraint also specifies the return type, so it would be straightforward to construct a graph. Where a type variable is used, then there would need to be a run-time determination for the actual types as happens in Haskell. Obviously to have a complete graph of a program would require the whole program to be written using lambda.r.

For example you can decorate two separate function clauses each with their own type constraint.

slice(x, pivot, inclusive) %::% a : numeric : logical : list
slice(x, pivot, inclusive=FALSE) %as% {
  left <- x[1:pivot]
  right <- x[(pivot+as.numeric(!inclusive)):length(x)]
  list(left, right)
}

slice(x, expression) %::% a : logical : list
slice(x, expression) %as% {
  left <- x[expression]
  right <- x[!expression]
  list(left, right)
}

This calls the first clause since the second argument is numeric.
> x <- rnorm(10)
> slice(x, 4)
[[1]]
[1]  1.2468112 -0.2795106  0.5775026  1.0521653

[[2]]
[1] -1.0493246 -2.0634126  0.0368455 -1.8431248 -0.3630197  0.1015901


This calls the second clause since x < 0 is logical.
> slice(x, x < 0)
[[1]]
[1] -0.2795106 -1.0493246 -2.0634126 -1.8431248 -0.3630197

[[2]]
[1] 1.2468112 0.5775026 1.0521653 0.0368455 0.1015901


This fails since no clause of the function accepts a character as the second argument.
> slice(x, 'a')
Error in UseFunction(slice, "slice", ...) :
  No valid function for 'slice(c(1.24681120969809,-0.279510617209735,0.577502630574721,1.05216534148533, ...),a)'


Warm Regards,
Brian



On Aug 30, 2013, at 5:19 AM, Оботуров Артем <oboturov at gmail.com> wrote:

> Hello.
> 
> One of my clients asked if it would be possible to have an IDE which could
> use type discovery for R functions to make flow-like construction of an R
> program. Something like a LabView graphical composition of processing
> elements.
> 
> They called this type of program composition a "workflow".
> 
> I looked at some of this programs, like:
> * Orange http://orange.biolab.si/
> * RedR http://www.red-r.org/
> * Rattle http://rattle.togaware.com/
> * Rpad https://code.google.com/p/rpad/
> 
> and all of them did type introspection (they made mapping between R
> functions and their IDE's visual framework) by hand for each function of
> supported packages which is time and resource consuming.
> 
> So, to reduce an amount of code to be written for adapters between R and
> IDE some kind of annotations could be introduced over parameters and return
> values. Those could be optional and will help to discover type information
> for support of dynamic composition of programs.
> 
> Do you have any suggestions on the topic?
> 
> Best regards,
> 
> Artem Oboturov
> 
> 	[[alternative HTML version deleted]]
> 
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