mergeLayers {recolorize}

Merge layers in a recolorized image

Description

Merges specified layers in a recolorized image. This is a good option if you want to manually specify which layers to merge (and what color to make the resulting merged layer); it's also called on by other recolorize functions like recluster to merge layers that have been identified as highly similar in color using a given distance metric.

Usage

mergeLayers(
  recolorize_obj,
  merge_list = NULL,
  color_to = "weighted average",
  plotting = TRUE
)

Arguments

recolorize_obj

An object of class "recolorize", such as from recolorize, recluster, or imposeColors.

merge_list

A list of numeric vectors specifying which layers to merge. Layers not included in this list are unchanged. See examples.

color_to

Color(s) for the merged layers. See examples.

plotting

Logical. Plot the results of the layer merging next to the original color fit for comparison?

Details

Colors can be supplied as numeric RGB triplets (e.g. c(1, 1, 1) for white), a valid R color name ("white"), or a hex code (⁠"#FFFFFF⁠). Alternatively, color_to = "weighted average" will set the merged layer to the average color of the layers being merged, weighted by their relative size. Must be either a single value or a vector the same length as merge_list. If a single color is supplied, then all merged layers will be set to that color (so this really is only useful if you're already merging those layers into a single layer).

Value

A recolorize class object with merged layers. The order of the returned layers depends on merge_list: the first layers will be any not included in the list, followed by the new merged layers. If you start with layers 1-8 and merge layers 4 & 5 and 7 & 8, the returned 5 layers will be, in order and in terms of the original layers: 1, 2, 3, 6, 4 & 5 (merged), 7 & 8 (merged). This is probably easiest to see in the examples.

Examples

# image path:
img <- system.file("extdata/corbetti.png", package = "recolorize")

# initial fit, 8 bins:
init_fit <- recolorize(img)
# redundant green, red, and blue clusters

# to make it easier to see, we can plot the numbered palette:
plot(init_fit)

# based on visual inspection, we should merge:
mlist <- list(c(3, 5),
              c(4, 7),
              c(6, 8))

# we can merge with that list, leaving layers 1 & 2 intact:
vis_merge <- mergeLayers(init_fit,
                         merge_list = mlist)

# we can include layers 1 & 2 as their own list elements,
# leaving them intact (result is identical to above):
mlist2 <- list(1, 2,
               c(3, 5),
               c(4, 7),
               c(6, 8))
redundant_merge <- mergeLayers(init_fit,
                               merge_list = mlist2)

# we can also swap layer order this way without actually merging layers:
swap_list <- list(2, 5, 3, 4, 1)
swap_layers <- mergeLayers(redundant_merge,
                           merge_list = swap_list)

# merging everything but the first layer into a single layer,
# and making that merged layer orange (result looks
# a bit like a milkweed bug):
milkweed_impostor <- mergeLayers(init_fit,
                                 merge_list = list(c(2:8)),
                                 color_to = "orange")

# we can also shuffle all the layer colors while
# leaving their geometry intact:
centers <- vis_merge$centers
centers <- centers[sample(1:nrow(centers), nrow(centers)), ]
shuffle_layers <- mergeLayers(vis_merge,
                              merge_list = as.list(1:5),
                              color_to = centers)
# (this is not really the intended purpose of this function)