Write a Maxent Prediction Grid as a PNG Image — maxent_write_prediction

Converts a GridFloat prediction grid to a colour PNG image using the canonical Maxent colour ramp (red = high, blue = low). Optionally overlays presence and test-point locations, and renders a small legend.

Usage

maxent_write_prediction_png(
  grid,
  filename,
  presence_rows = NULL,
  presence_cols = NULL,
  test_rows = NULL,
  test_cols = NULL,
  mode = "plain",
  legend = TRUE,
  width = 800L,
  height = 600L
)

Arguments

grid: External pointer to a GridFloat prediction grid (e.g. from maxent_project_cloglog).
filename: Character: path for the output PNG file.
presence_rows: Integer vector of presence row indices (0-based) or NULL (default).
presence_cols: Integer vector of presence column indices (0-based) or NULL (default).
test_rows: Integer vector of test-set row indices (0-based) or NULL (default).
test_cols: Integer vector of test-set column indices (0-based) or NULL (default).
mode: Colour mode passed to maxent_color_ramp: one of "plain" (default), "log", "blackandwhite", or "redandyellow".
legend: Logical: draw a colour-bar legend (default TRUE).
width: Integer: PNG width in pixels (default 800).
height: Integer: PNG height in pixels (default 600).

Value

Invisibly returns filename.

Examples

# \donttest{
set.seed(42)
n <- 50L; idx <- c(5L, 15L, 25L, 35L, 45L)
env <- list(bio1 = runif(n), bio12 = runif(n))
feats <- maxent_generate_features(env, types = "linear")
model <- maxent_featured_space(n, idx, feats)
maxent_fit(model, max_iter = 100)
#> $loss
#> [1] 3.781356
#> 
#> $entropy
#> [1] 3.887762
#> 
#> $iterations
#> [1] 100
#> 
#> $converged
#> [1] FALSE
#> 
#> $lambdas
#> [1] 0.6202339 0.4108689
#> 
g1 <- maxent_grid_from_matrix(matrix(env$bio1, 5, 10),
        -120, 35, 1, name = "bio1")
g2 <- maxent_grid_from_matrix(matrix(env$bio12, 5, 10),
        -120, 35, 1, name = "bio12")
pred <- maxent_project_cloglog(model, list(g1, g2), c("bio1", "bio12"))
maxent_write_prediction_png(pred, tempfile(fileext = ".png"))
# }