Binning

Aggregate values in x for bins defined on y: all values in x for values in y falling into a bin (defined on y) are aggregated with the provided function FUN.

Usage

bin(
  x,
  y,
  size = 1,
  breaks = seq(floor(min(y)), ceiling(max(y)), by = size),
  FUN = max,
  returnMids = TRUE,
  .check = TRUE
)

Arguments

x

numeric with the values that should be aggregated/binned.

y

numeric with same length than x with values to be used for the binning. y must be increasingly sorted, or else an error will be thrown.

size

numeric(1) with the size of a bin.

breaks

numeric defining the breaks (bins). See breaks_ppm() to define breaks with increasing size (depending on ppm).

FUN

function to be used to aggregate values of x falling into the bins defined by breaks. FUN is expected to return a numeric(1).

returnMids

logical(1) whether the midpoints for the breaks should be returned in addition to the binned (aggregated) values of x. Setting returnMids = FALSE might be useful if the breaks are defined before hand and binning needs to be performed on a large set of values (i.e. within a loop for multiple pairs of x and y values).

.check

logical(1) whether to check that y is an ordered vector. Setting .check = FALSE will improve performance, provided you are sure that y is always ordered.

Value

Depending on the value of returnMids:

• returnMids = TRUE (the default): returns a list with elements x (aggregated values of x) and mids (the bin mid points).

• returnMids = FALSE: returns a numeric with just the binned values for x.

See also

Other grouping/matching functions: closest(), gnps()

Author

Johannes Rainer, Sebastian Gibb

Examples

## Define example intensities and m/z values
ints <- abs(rnorm(20, mean = 40))
mz <- seq(1:length(ints)) + rnorm(length(ints), sd = 0.001)

## Bin intensities by m/z bins with a bin size of 2
bin(ints, mz, size = 2)
#> $x
#>  [1] 40.25532 39.99443 41.14841 39.75580 39.71729 40.62898 42.06502 40.51243
#>  [9] 40.54300 39.08593
#> 
#> $mids
#>  [1]  2  4  6  8 10 12 14 16 18 20
#> 

## Repeat but summing up intensities instead of taking the max
bin(ints, mz, size = 2, FUN = sum)
#> $x
#>  [1] 116.41801  39.99443 119.94815  79.50848  39.71729  80.07528  80.43404
#>  [8] 118.12740  80.49039  39.08593
#> 
#> $mids
#>  [1]  2  4  6  8 10 12 14 16 18 20
#> 

## Get only the binned values without the bin mid points.
bin(ints, mz, size = 2, returnMids = FALSE)
#>  [1] 40.25532 39.99443 41.14841 39.75580 39.71729 40.62898 42.06502 40.51243
#>  [9] 40.54300 39.08593