Trimming data frames using a numeric interval

Trims data frames with 2 or more numeric columns using a numeric interval. Returns rows with numeric values that fall within the interval.

Usage

trim(x, ...)

# Default S3 method
trim(x, xlim = NULL, ...)

# S3 method for class 'dna_seg'
trim(x, xlim = NULL, ...)

# S3 method for class 'comparison'
trim(x, xlim1 = c(-Inf, Inf), xlim2 = c(-Inf, Inf), ...)

# S3 method for class 'annotation'
trim(x, xlim = NULL, ...)

# S3 method for class 'seg_plot'
trim(x, xlim = NULL, ...)

Arguments

x: An object to trim, generally a data.frame, data.table, or seg_plot object
...: Unused.
xlim: A numeric of length 2. In a general case, the rows whose values are included in this interval are returned
xlim1: A numeric of length 2, used only for comparison objects, the interval to filter the first side.
xlim2: A numeric of length 2, used only for comparison objects, the interval to filter the second side.

Value

An object with the same type as x, with the rows (or subset) corresponding to the given interval

Details

By default it uses the first 2 numeric columns in x. If x is a dna_seg object, it uses the start and end columns. If x is a comparison object, it filters using the start1 and end1 columns with the xlim1 argument, and start2 and end2 with the xlim2 argument. If x is annotation object, it uses the x1 and x2 columns. If x is a seg_plot object, the function uses the xargs variable from x to define which vectors determine the x position (they should be the same length). Then, all the variables (including those inside the gp variable) that are the same length as the x vectors are trimmed, so that only the rows for which the x values are inside the xlim argument are kept.

Author

Lionel Guy

Examples

## Load
data(barto)
xlim_ref <- c(10000, 45000)
## Seg 2 (ref)
barto$dna_segs[[2]] <- trim(barto$dna_segs[[2]], xlim = xlim_ref)
## Seg 1
barto$comparisons[[1]] <- trim(barto$comparisons[[1]], xlim2 = xlim_ref)
xlim1 <- range(barto$comparisons[[1]], overall = FALSE)$xlim1
barto$dna_segs[[1]] <- trim(barto$dna_segs[[1]], xlim = xlim1)
## Seg 3
barto$comparisons[[2]] <- trim(barto$comparisons[[2]], xlim1 = xlim_ref)
xlim3 <- range(barto$comparisons[[2]], overall = FALSE)$xlim2
barto$dna_segs[[3]] <- trim(barto$dna_segs[[3]], xlim = xlim3)
## Seg 4
barto$comparisons[[3]] <- trim(barto$comparisons[[3]], xlim1 = xlim3)
xlim4 <- range(barto$comparisons[[3]], overall = FALSE)$xlim2
barto$dna_segs[[4]] <- trim(barto$dna_segs[[4]], xlim = xlim4)
## Plot
plot_gene_map(barto$dna_segs, barto$comparisons)


## With seg_plot
x <- 1:20
y <- rnorm(20)
sp <- seg_plot(func = pointsGrob,
               args = list(x = x, y = y, gp = gpar(col = 1:20, cex = 1:3)))
## Trim 
sp_trim <- trim(sp, c(3, 10))
str(sp_trim)
#> List of 5
#>  $ func :function (x = stats::runif(10), y = stats::runif(10), pch = 1, size = unit(1, 
#>     "char"), default.units = "native", name = NULL, gp = gpar(), vp = NULL)  
#>  $ args :List of 4
#>   ..$ x            : int [1:8] 3 4 5 6 7 8 9 10
#>   ..$ y            : num [1:8] 1.1269 0.1399 0.1003 -1.2045 -0.0835 ...
#>   ..$ gp           :List of 2
#>   .. ..$ col: int [1:8] 3 4 5 6 7 8 9 10
#>   .. ..$ cex: num [1:3] 1 2 3
#>   .. ..- attr(*, "class")= chr "gpar"
#>   ..$ default.units: chr "native"
#>  $ xargs: chr [1:5] "x" "x0" "x1" "x2" ...
#>  $ yargs: chr [1:5] "y" "y0" "y1" "y2" ...
#>  $ ylim : NULL
#>  - attr(*, "class")= chr [1:2] "seg_plot" "list"
range(sp_trim$arg$x)
#> [1]  3 10