Skip to contents

Generate a "Thermal Cloud" Visualization (Phyllotaxis Layout)

Source: R/visualization.r
plot_thermal_cloud.Rd

Arranges a collection of segmented thermal objects into an organic, spiral "cloud" formation. Unlike a rigid grid, this layout uses a golden-angle spiral (phyllotaxis) algorithm to cluster subjects efficiently. This is particularly effective for visualizing the diversity of thermal phenotypes in large datasets or creating artistic figures for presentations and covers.

Usage

plot_thermal_cloud(
  img_list,
  spread_factor = 1.1,
  jitter_factor = 0.5,
  palette = "inferno",
  text_color = "black",
  text_size = 3,
  show_labels = TRUE
)

Arguments

img_list

A list of 'BioThermR' objects. For best results, these should be pre-processed (e.g., background removed via roi_filter_threshold).

spread_factor

Numeric. Multiplier for the distance between objects. Values > 1.0 increase spacing (airier cloud), values < 1.0 pack objects tighter. Default is 1.1.

jitter_factor

Numeric. Introduces random noise to the placement coordinates to break perfect symmetry and create a more natural look. Default is 0.5.

palette

String. The color palette from the 'viridis' package. Default is "inferno".

text_color

String. Color of the filename labels. Default is "black".

text_size

Integer. Font size for the labels. Default is 3.

show_labels

Logical. If TRUE, displays the filename below each object. Default is TRUE.

Value

A ggplot object with a white background and void theme.

Details

The function performs object-centric rendering:

  1. Extraction: For each image, it extracts only the valid foreground pixels (non-NA), ignoring the original frame dimensions.

  2. Re-centering: Each object is mathematically centered at (0,0) relative to its own coordinate system.

  3. Placement: Objects are placed along a spiral path defined by the Golden Angle (~137.5 degrees).

The spacing and randomness of the spiral can be tuned using spread_factor and jitter_factor.

Examples

if (FALSE) { # \dontrun{
# Load data
batch <- read_thermal_batch("data/mice")

# Create an artistic thermal cloud
p_cloud <- plot_thermal_cloud(batch, spread_factor = 1.5, jitter_factor = 2.0)

# Save for cover art
ggsave("thermal_cloud_cover.png", p_cloud, width = 15, height = 15, dpi = 300)
} # }