Melanization landscape: 3D shaded surface and 2D map of a plate

Source: R/plot_landscape.R

Turns a plate into a "melanization landscape". In 3D, each colony rises from the agar with a height and colour given by its local melanization index (MI = 100 - L*), so darker tissue forms higher, browner relief. The bacterium and its halo are painted on the floor. In 2D, the same MI field is drawn over a faded photograph, with the halo and bacterium outlined. An arrow on each colony points to the bacterium and is annotated with the side-specific response delta_MI_facing.

plot_melanization_map(
  x,
  type = c("both", "3d", "2d"),
  mi_range = NULL,
  smooth_mm = 0.25,
  relief_smooth_mm = 1.5,
  taper_mm = 2.5,
  grid = 180,
  theta = -30,
  phi = 32,
  expand = 0.3,
  main = NULL
)

Arguments

x

A mycohalo_result computed with keep_images = TRUE.

type

"both" (3D + 2D side by side), "3d" or "2d".

mi_range

Optional common MI range c(min, max) for colours and heights. Fix it when comparing several plates.

smooth_mm

Smoothing of the MI field (mm).

relief_smooth_mm

Smoothing (mm) of the MI field used for the 3D heights (colours use smooth_mm).

taper_mm

Width of the rounded colony edge in 3D (mm).

grid

Approximate number of grid cells along the longer side of the 3D surface (speed vs. detail).

theta, phi

Viewing angles of the 3D view (see graphics::persp()).

expand

Vertical exaggeration of the 3D relief.

main

Title.

Value

Invisibly, a list with the MI matrix used and the colour ramp.

Details

The MI field is smoothed with a Gaussian of smooth_mm to show tissue- scale structure (margins, sectors, facing-side darkening) rather than single hyphal ridges. In 3D the colony edges are tapered over taper_mm, so colonies look like rounded relief instead of cliffs. The colour scale is a single-hue sepia ramp from light to dark, because MI is a magnitude and melanin is brown-black. Heights and colours share the same scale, set by the observed MI range (or mi_range).

Examples

sim <- simulate_plate(width = 300, height = 400, seed = 42,
                     facing_darkening = 5, edge_lightening = 8)
res <- analyze_plate(sim$image, verbose = FALSE)
plot_melanization_map(res)