Utilities for Developing R Software (original) (raw)
The oeli package offers a collection of handy functions that I found useful while developing R packages. Perhaps you’ll find them helpful too!
Installation
The released package version can be installed from CRAN via:
Demos
The package includes helpers for various tasks and objects. Some demos are shown below. Click the headings for reference pages with documentation on all available helpers in each category.
Distributions
The package has density and sampling functions for distributions not in base R, such as Dirichlet, multivariate normal, truncated normal, and Wishart.
ddirichlet(x = c(0.2, 0.3, 0.5), concentration = 1:3)
#> [1] 4.5
rdirichlet(concentration = 1:3)
#> [1] 0.1273171 0.5269401 0.3457428
For faster computation, Rcpp implementations are also available:
microbenchmark::microbenchmark(
"R" = rmvnorm(mean = c(0, 0, 0), Sigma = diag(3)),
"Rcpp" = rmvnorm_cpp(mean = c(0, 0, 0), Sigma = diag(3))
)
#> Unit: microseconds
#> expr min lq mean median uq max neval
#> R 200.5 208.25 263.396 217.10 234.35 2154.7 100
#> Rcpp 2.7 2.90 5.386 4.05 4.40 72.0 100
Indexing helpers
Create all possible permutations of vector elements:
permutations(LETTERS[1:3])
#> [[1]]
#> [1] "A" "B" "C"
#>
#> [[2]]
#> [1] "A" "C" "B"
#>
#> [[3]]
#> [1] "B" "A" "C"
#>
#> [[4]]
#> [1] "B" "C" "A"
#>
#> [[5]]
#> [1] "C" "A" "B"
#>
#> [[6]]
#> [1] "C" "B" "A"
Package helpers
Quickly have a basic logo for your new package:
package_logo("my_package", brackets = TRUE, use_logo = FALSE)
How to print a matrix
without filling up the entire console?
x <- matrix(rnorm(10000), ncol = 100, nrow = 100)
print_matrix(x, rowdots = 4, coldots = 4, digits = 2, label = "what a big matrix")
#> what a big matrix : 100 x 100 matrix of doubles
#> [,1] [,2] [,3] ... [,100]
#> [1,] 2.39 0.3 -0.48 ... 0.56
#> [2,] -1.33 0.62 0.37 ... -1.21
#> [3,] -0.03 -0.43 1.71 ... 0.07
#> ... ... ... ... ... ...
#> [100,] 0.14 -0.16 2.49 ... -1.58
And what about a data.frame
?
x <- data.frame(x = rnorm(1000), y = LETTERS[1:10])
print_data.frame(x, rows = 7, digits = 0)
#> x y
#> 1 0 A
#> 2 -1 B
#> 3 0 C
#> 4 -1 D
#> < 993 rows hidden >
#>
#> 998 -1 H
#> 999 -1 I
#> 1000 0 J
Transformation helpers
The [group_data.frame()](reference/group%5Fdata.frame.html)
function groups a given data.frame
based on the values in a specified column:
df <- data.frame("label" = c("A", "B"), "number" = 1:10)
group_data.frame(df = df, by = "label")
#> $A
#> label number
#> 1 A 1
#> 3 A 3
#> 5 A 5
#> 7 A 7
#> 9 A 9
#>
#> $B
#> label number
#> 2 B 2
#> 4 B 4
#> 6 B 6
#> 8 B 8
#> 10 B 10