In [1]:
:ext QuasiQuotes
import qualified H.Prelude as H
H.initialize H.defaultConfig

## Doing things in R¶

In [2]:
-- print output
[rprint| lm(mpg ~ wt, data = mtcars) |]
Call:
lm(formula = mpg ~ wt, data = mtcars)

Coefficients:
(Intercept)           wt
37.285       -5.344
In [3]:
-- plot stuff
-- we just require ggplot2 as we do everything directly in R
[rgraph|
require(ggplot2)
ggplot(diamonds, aes(carat, price)) + geom_point() + theme(aspect.ratio = 1) |]

Assignment also works as usual:

In [4]:
[rprint| fact <- function(n) if(n == 0) 1 else n * fact(n - 1)
fact(10) |]
[1] 3628800

Call fact again...

In [5]:
[rprint| fact(10) |]
R Runtime Error: Error in fact(10) : could not find function "fact"

The embedded R interpreter is stateful, but for global assignment we need to use <<-

In [6]:
[r| fact <<- function(n) if(n == 0) 1 else n * fact(n - 1) |]
0x00007f86bf8df678
In [7]:
[rprint| fact(25) |]
[1] 1.551121e+25

## Fine, but my data are in Haskell ... how do I ship them over to R?¶

The _hs suffix is used to splice values from Haskell into the R code:

In [8]:
xs = [1..10] :: [Double]
xs
[1.0,2.0,3.0,4.0,5.0,6.0,7.0,8.0,9.0,10.0]
In [9]:
[rprint| mean(xs_hs) |]
[1] 5.5

We can even use functions defined in Haskell in R:

In [10]:
import Data.Int
fact :: Int32 -> Int32
fact 0 = 1
fact n = n * fact (n - 1)

factR x = return $fact x :: H.R s Int32 In [11]: n = 6 :: Int32 [rprint| factR_hs(n_hs) |] [1] 720 ## What if I want to use results from R computations in Haskell?¶ In [12]: get_normals :: Double -> H.R s [Double] get_normals n = do H.dynSEXP <$> [r| rnorm(n_hs) |]
result <- H.runRegion \$ get_normals 4

result
[1.1294181047596081,0.1277917949807154,-0.11111631846148341,1.878786090403989]

Now these are just normal Haskell values you can work with:

In [13]:
:t result
result :: [Double]