plotfield.normalized {vfprogression}

Single plotting function for one 24-2 or 30-2 visual field measurement:

Description

plotfield.normalized plots the following 24-2 or 30-2 visual field measurement: sensitivity, TD, TD prob, PD, and PD prob:

Usage

plotfield.normalized(eigenfields, component = 1,
  zmin = -max(abs(c(min(eigenfields), max(eigenfields)))),
  zmax = max(abs(c(min(eigenfields), max(eigenfields)))),
  color.pal = colorRampPalette(c("red", "white", "blue"), space =
  "Lab")(256), show.colorbar = TRUE, topleftannotation = NULL,
  bottomleftannotation = NULL, labelcex = 2, ...)

Arguments

eigenfields

a vector contains Sensitivity/TD/PD measurement. For 24-2 VF eigenfields should have 52 or 54 elements. For 30-2 VF, eigenfields should have 74 or 76 elements.

component

Number of components to be plotted (default: 1).

zmin

minimum value of the color scale (default: auto defined).

zmax

maximum value of the color scale (default: auto defined).

color.pal

an object that defines color scale theme (default: colorRampPalette(c("red", "white", "blue"), space = "Lab")(256)).

show.colorbar

a logic value to show colorbar (default: TRUE).

topleftannotation

a string annotation shown on the top left side of the plot (default: NULL).

bottomleftannotation

a string annotation shown on the bottom left side of the plot (default: NULL).

labelcex

a numeric variable for label size (default: 2).

...

other variables to be added.

Value

heatmap for sensitivity, TD and PD input

Examples

data(vfseries)
eigenfields = t(vfseries[1, grepl('^s[0-9]+', colnames(vfseries))])
plotfield.normalized(eigenfields)
title(main = "Sensitivity", line = 3)
eigenfields = t(vfseries[1, grepl('^td[0-9]+', colnames(vfseries))])
plotfield.normalized(eigenfields)
title(main = "Total Deviation", line = 3)
eigenfields = t(vfseries[1, grepl('^pd[0-9]+', colnames(vfseries))])
plotfield.normalized(eigenfields)
title(main = "Pattern Deviation", line = 3)