Skip to contents

Transform values the way the modules plot them

Source: R/plot_helpers.R
adjusted_values.Rd

The adjustment function (adj.fxn, e.g. log10) is applied first, then the adjustment rescales the result ("z-score" or "relative.to.max"). That is the order a transform and a standardisation are normally combined in: log first, then z-score. dittoViz applies them the other way round when given both, which turns every below-average value into log() of a negative number, so the modules hand dittoViz this whole transform as its function instead (see adjustment_fn()).

Usage

adjusted_values(values, adjustment = NULL, adj.fxn = NULL)

Arguments

values

Vector of values, normally one column of the plotted data.

adjustment

NULL, "", "z-score" or "relative.to.max".

adj.fxn

NULL, "", a name accepted by safe_resolve_adj_fxn(), or a function.

Value

The transformed values, unnamed.

Details

The rescaling is computed over the finite values only, so a value the function makes non-finite (log(0)) is dropped from the plot rather than turning the whole column into NaN.

Anything drawn over an adjusted plot (significance brackets, fit lines, axis limits) has to be computed from these values, not the raw column, or it lands in a different coordinate space from the data.

See also

adjustment_fn(), as_plotted(), adjust_column_values()

Author

Jared Andrews

Examples

adjusted_values(c(1, 10, 100), adjustment = "z-score", adj.fxn = "log10")
#> [1] -1  0  1
adjusted_values(c(1, 2, 4), adjustment = "relative.to.max")
#> [1] 0.25 0.50 1.00