Plot method for charisma objects

This function creates visualizations of color classification results from a charisma analysis. It can display the original image, recolored image, masked image, color proportions, and pavo color pattern geometry results.

Usage

# S3 method for class 'charisma'
plot(
  x,
  plot.all = TRUE,
  plot.original = FALSE,
  plot.recolored = FALSE,
  plot.masked = FALSE,
  plot.props = FALSE,
  plot.pavo.img = FALSE,
  plot.pavo.classes = FALSE,
  font.size = 1.75,
  props.x.cex = 1.5,
  real.bar.colors = TRUE,
  ...
)

Arguments

x

A charisma object (output from charisma or charisma2).

plot.all

Logical. If TRUE, plots all available visualizations. Default is TRUE.

plot.original

Logical. If TRUE, plots the original image. Default is FALSE.

plot.recolored

Logical. If TRUE, plots the recolored image showing discrete color classifications. Default is FALSE.

plot.masked

Logical. If TRUE, plots the masked image after background removal. Default is FALSE.

plot.props

Logical. If TRUE, plots a bar chart showing the proportion of pixels in each color category. Default is FALSE.

plot.pavo.img

Logical. If TRUE, plots the image used for pavo color pattern geometry analysis. Default is FALSE. Only available if pavo analysis was performed.

plot.pavo.classes

Logical. If TRUE, plots the color palette from pavo k-means clustering. Default is FALSE. Only available if pavo analysis was performed.

font.size

Numeric. Size multiplier for plot text elements. Default is 1.75.

props.x.cex

Numeric. Size multiplier for x-axis labels in the proportions plot. Default is 1.5.

real.bar.colors

Logical. If TRUE, uses actual color values for bars in the proportions plot. If FALSE, uses a default color scheme. Default is TRUE.

...

Additional arguments (currently not used).

Value

This function is called for its side effects (creating plots) and does not return a value.

Details

When plot.all = TRUE, all available plots are displayed in a multi-panel layout. Individual plots can be selected by setting the corresponding plot.* parameters to TRUE.

The function automatically detects whether pavo analysis results are present in the charisma object and adjusts the plot layout accordingly.

See also

charisma for the main classification pipeline, charisma2 for batch processing

Examples

# \donttest{
# Run charisma on an image
img <- system.file("extdata", "Tangara_fastuosa_LACM60421.png",
                   package = "charisma")
result <- charisma(img)
#> Warning: if any are empty, remove them
#> Discrete color classes identified: k=7
#> (black, blue, brown, green, grey, orange, yellow)
#> Image classification in progress...
#> Using single set of coldists for all images.
#> 
#> Warning: Image lighting and quality may vary. Before using results in downstream analyses, check color class outputs, and adjust the CLUT as necessary to capture the appropriate color classes in your image dataset.

# Plot all results
plot(result)

#> Error in par(oldpar): invalid value specified for graphical parameter "pin"

# Plot only original and recolored images
plot(result, plot.all = FALSE, plot.original = TRUE, plot.recolored = TRUE)


# Plot color proportions
plot(result, plot.all = FALSE, plot.props = TRUE)

# }