Grouping of numeric values by similarity

The group function groups numeric values by first ordering and then putting all values into the same group if their difference is smaller defined by parameters tolerance (a constant value) and ppm (a value-specific relative value expressed in parts-per-million).

Usage

group(x, tolerance = 0, ppm = 0)

Arguments

x: increasingly ordered numeric with the values to be grouped.
tolerance: numeric(1) with the maximal accepted difference between values in x to be grouped into the same entity.
ppm: numeric(1) defining a value-dependent maximal accepted difference between values in x expressed in parts-per-million.

Value

integer of length equal to x with the groups.

Note

Since grouping is performed on pairwise differences between consecutive values (after ordering x), the difference between the smallest and largest value in a group can be larger than tolerance and ppm.

Author

Johannes Rainer, Sebastin Gibb

Examples


## Define a (sorted) numeric vector
x <- c(34, 35, 35, 35 + ppm(35, 10), 56, 56.05, 56.1)

## With `ppm = 0` and `tolerance = 0` only identical values are grouped
group(x)
#> [1] 1 2 2 3 4 5 6

## With `tolerance = 0.05`
group(x, tolerance = 0.05)
#> [1] 1 2 2 2 3 3 3

## Also values 56, 56.05 and 56.1 were grouped into a single group,
## although the difference between the smallest 56 and largest value in
## this group (56.1) is 0.1. The (pairwise) difference between the ordered
## values is however 0.05.

## With ppm
group(x, ppm = 10)
#> [1] 1 2 2 2 3 4 5

## Same on an unsorted vector
x <- c(65, 34, 65.1, 35, 66, 65.2)
group(x, tolerance = 0.1)
#> [1] 3 1 3 2 4 3

## Values 65, 65.1 and 65.2 have been grouped into the same group.