plot_correlation_heatmap: Plot a Heatmap for a Correlation Matrix

In rettopnivek/arfpam: Assorted R Functions for Processing, Analysis, and Modeling

Plot a Heatmap for a Correlation Matrix

Description

Generates a heatmap of the upper triangle of a correlation matrix.

Usage

plot_correlation_heatmap(
  x,
  ttl = "Correlation matrix",
  labels = NULL,
  lyt = NULL,
  gradient = c("#E69F00", "#56B4E9"),
  txtSz = 1.25,
  mc_adjust = "BH",
  cut_off = 0.05,
  new = T,
  H = 20/3,
  W = 25/3,
  abbr_labels = TRUE,
  status = FALSE
)

Arguments

x	A data frame (all variables will be used when generating the correlation matrix).
ttl	An optional title for the figure.
labels	The labels for the rows/columns. Users can pass a list with two character vectors of matching length to provide separate labels for rows and columns.
lyt	An optional matrix specifying the layout of the main panel (1) versus the side panel (2) with the color gradient.
gradient	The final end colors for the negative and positive correlations, respectively.
txtSz	The size of the text in the figure (a second value can be provided to adjust variable labels separately).
mc_adjust	The method to use when correcting for multiple comparisons (see p.adjust).
cut_off	Cut-off for statistical significance.
new	Logical; if TRUE generates a new plotting window via x11.
H	The height in inches of the figure if a new plotting window is generated.
W	The width in inches of the figure if a new plotting window is generated.
abbr_labels	Logical; if TRUE abbreviates labels to 4 characters. A second value can be provided to abbreviate labels on the top separately.
status	Logical; if TRUE displays the progress of the function for debugging purposes.

Value

A heatmap for the upper-triangle portion of the correlation matrix.

Examples

# Load data
data("mtcars")
x <- mtcars[, c(1,3,4,5,6,7)]
plot_correlation_heatmap( x, new = FALSE )

# Simulate a correlation matrix

# 5 x 5 matrix of random values
rand_mat <- matrix( rnorm(25), 5, 5 )
# Create covariance matrix by
# multiplying matrix by its transpose
cov_mat <- rand_mat %*% t( rand_mat )
corr_mat <- cov_mat/sqrt(diag(cov_mat)%*%t(diag(cov_mat)))

# Simulate data
x <- MASS::mvrnorm( 100, rep( 0, nrow( corr_mat ) ), corr_mat )
colnames( x ) <- paste0( 'V', 1:ncol( x ) )
x <- data.frame(x)
plot_correlation_heatmap( x, new = FALSE )

rettopnivek/arfpam documentation built on Oct. 20, 2024, 7:24 p.m.