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Plot a Correlation Heatmap

Source: R/plot.R
plot.smartcormat.Rd

Draws an annotated heatmap of a smart correlation matrix with base R. Each cell is coloured by the correlation and labelled with its value.

Usage

# S3 method for class 'smartcormat'
plot(
  x,
  palette = "blue_red",
  digits = 2,
  title = NULL,
  show_values = TRUE,
  text_size = 1,
  ...
)

plot_cor_heatmap(
  x,
  palette = "blue_red",
  digits = 2,
  title = NULL,
  show_values = TRUE,
  text_size = 1,
  ...
)

Arguments

x

A smartcormat object (from smart_cormat()), or a named list with a correlations element (e.g., from smart_cor_df()).

palette

Character string selecting the colour palette. One of:

  • "blue_red" (default): diverging blue-white-red

  • "purple_green": diverging purple-white-green

  • "viridis": sequential yellow-green-blue

  • "heat": sequential white-yellow-red

  • "cool": sequential white-cyan-blue

digits

Integer. Number of decimal places shown in cell labels. Default: 2.

title

Optional character string for the plot title. If NULL (default), a generic title is used.

show_values

Logical. Whether to display numeric values in each cell. Default: TRUE.

text_size

Numeric. Scaling factor for cell text size. Default: 1.

...

Additional arguments (currently ignored).

Value

Invisibly returns the correlation matrix (numeric).

Details

The function works with any object that contains a correlations element (matrix or data frame). This includes objects returned by smart_cormat() and smart_cor_df().

Custom colour palettes can be supplied by passing a character vector of colours to palette instead of a named preset. The vector should contain at least 3 colours and will be interpolated to 100 steps.

Examples

csv = system.file("extdata", "gss_2024_casestudy.csv", package = "smartcor")
gss = read.csv(csv)

# Plot a smart_cormat result
mat = smart_cormat(
  gss[, c("age", "coninc", "degree", "sex")],
  assume_latent_normal = FALSE,
  verbose = FALSE
)
plot(mat)


# different palettes
plot(mat, palette = "purple_green")

plot(mat, palette = "viridis")


# Plot a smart_cor_df result
res = smart_cor_df(gss[, c("age", "coninc", "degree", "sex")],
                   assume_latent_normal = FALSE)
plot_cor_heatmap(res)


# custom colour vector
plot_cor_heatmap(res, palette = c("darkblue", "white", "darkred"))