kdtools

The kdtools package exports a C++ header implementing sorting and searching on ranges of tuple-like objects without using trees. Note that searching and sorting are supported on mixed-types. It is based on a kd-tree-like recursive sorting algorithm. Once sorted, one can perform a range- or nearest-neighbor- query. More details are here. Methods and benchmarks are here.

library(kdtools)
x = kd_sort(matrix(runif(400), 200))
plot(x, type  = 'l', asp = 1, axes = FALSE, xlab = NA, ylab = NA)
points(x, pch = 19, col = rainbow(200, alpha = 0.25), cex = 2)
y = kd_range_query(x, c(1/4, 1/4), c(3/4, 3/4))
points(y, pch = 19, cex = 0.5, col = "red")

Native Data Frame Support

The core C++ header implements sorting and searching on vectors of tuples with the number of dimensions determined at compile time. I have generalized the package code to work on an arbitrary data frame (or any list of equal-length vectors). This sorting and search works on any times that are equality-comparable and less-than-comparable in the C++ STL sense.

df <- kd_sort(data.frame(a = runif(12),
                         b = as.integer(rpois(12, 1)),
                         c = sample(month.name),
                         stringsAsFactors = FALSE))
print(df)
#>             a b         c
#> 8  0.22005867 0  December
#> 1  0.05100523 0   January
#> 9  0.12662847 0      June
#> 12 0.04077643 0 September
#> 10 0.06624199 3     April
#> 6  0.18405158 3  November
#> 5  0.22156547 0     March
#> 3  0.85750353 0    August
#> 11 0.30600644 0  February
#> 4  0.92848702 0       May
#> 2  0.91278945 3      July
#> 7  0.47418294 0   October
lower <- list(0.1, 1L, "August")
upper <- list(0.9, 4L, "September")
i <- kd_rq_indices(df, lower, upper)
print(i)
#> [1] 6
df[i, ]
#>           a b        c
#> 6 0.1840516 3 November