vfgpar: Plots for visual fields data

Description

Graphical tools for visualization and statistical analysis of visual fields.

Usage

vfgpar(
  coord,
  tess = vftess(coord),
  probs = c(0, 0.005, 0.01, 0.02, 0.05, 0.95, 0.98, 0.99, 0.995, 1),
  cols = c("#000000", colorRampPalette(c("#FF0000", "#FFFF00"))(4), "#F7F0EB",
    colorRampPalette(c("#00FF00", "#008000"))(4)),
  floor = 0,
  ltprobs = c(0, 0.005, 0.01, 0.02, 0.05, 0.95, 1),
  ltcols = c("#000000", colorRampPalette(c("#FF0000", "#FFFF00"))(4), "#F7F0EB",
    "#008000"),
  gtprobs = c(0, 0.05, 0.95, 0.98, 0.99, 0.995, 1),
  gtcols = c("#000000", "#FF0000", "#F7F0EB", colorRampPalette(c("#00FF00",
    "#008000"))(4)),
  neprobs = c(0, 0.0025, 0.005, 0.01, 0.25, 0.975, 0.99, 0.995, 0.9975, 1),
  necols = c("#000000", colorRampPalette(c("#FF0000", "#FFFF00"))(4), "#F7F0EB",
    colorRampPalette(c("#FFFF00", "#FF0000"))(4)),
  bprobs = c(0, 0.005, 0.01, 0.02, 0.05, 0.95, 0.98, 0.99, 0.995, 1),
  bcols = c("#000000", colorRampPalette(c("#FF0000", "#FFFF00"))(4), "#F7F0EB",
    colorRampPalette(c("#00FF00", "#008000"))(4))
)
vftess(coord, floor = 0, delta = 3)
vfcolscheme(
  probs = c(0, 0.005, 0.01, 0.02, 0.05, 0.95, 0.98, 0.99, 0.995, 1),
  cols = c("#000000", colorRampPalette(c("#FF0000", "#FFFF00"))(4), "#F7F0EB",
    colorRampPalette(c("#00FF00", "#008000"))(4)),
  floor = 0
)
vfprogcolscheme(
  probs = c(0, 0.005, 0.01, 0.02, 0.05, 0.95, 1),
  cols = c("#000000", colorRampPalette(c("#FF0000", "#FFFF00"))(4), "#F7F0EB", "#008000")
)
vfplot(vf, td = NULL, tdp = NULL, pd = NULL, pdp = NULL, type = "td", ...)
vfplotplr(
  vf,
  alternative = "LT",
  xoffs = 0,
  yoffs = 0,
  addSpark = FALSE,
  thr = 2,
  width = 4,
  height = 2,
  ...
)
vflegoplot(
  vf,
  type = "td",
  grp = 3,
  addSpark = FALSE,
  thr = 2,
  width = 4,
  height = 2,
  ...
)
vfsparklines(vf, thr = 2, width = 4, height = 2, add = FALSE, ...)

Value

vfgpar returns a list with graphical parameters to be used for vfplots

vftess returns a list with the xlim, ylim, tessellation tiles and an outer hull to be used for vfplots

vfcolscheme returns a list with a lookup table and a function that define the color scheme to be used for vfplots

vfprogcolscheme returns the default vfcolscheme to be used for vfplots

vfplot No return value

vfplotplr No return value

vflegoplot No return value

vfsparklines No return value

Arguments

coord: print x and y coordinates. Check section Structure of graphical parameters for details
tess: tesselation for the visual field maps. Check section Tesselation in visualFields for details
probs: probability scale to use for TD and PD values. It is a numeric vector of probabilities with values in [0,1]. The values 0 and 1 must be included. Although not technically necessary, it would be best if it is the same as for the normative values used
cols: corresponding colors for each of the probability levels
floor: Flooring value, typically in dB. Default is 0
ltprobs, ltcols: color map for progression with the alternative hypothesis lower than (LT)
gtprobs, gtcols: color map for progression with the alternative hypothesis lower than (GT)
neprobs, necols: color map for progression with the alternative hypothesis not equal (NE)
bprobs, bcols: color map for progression with blth alternative hypotheses LT and GT (B for both)
delta: Distance over which the boundary should be shifted. See for polyclip
vf: the visual fields data to plot
td: the total deviation values. If NULL (default) then use visualFields normative values
tdp: the total deviation probability values. If NULL (default) then use visualFields normative values
pd: the pattern deviation values. If NULL (default) then use visualFields normative values
pdp: the pattern deviation probability values. If NULL (default) then use visualFields normative values
type: the type of data to plot: sensitivities (`s`), total deviation values (`td`), pattern deviation values (`pd`), a hybrid plot that shows sensitivity grayscale with TD values and corresponding probability levels (`tds`), or PD values and corresponding probability levels (`pds`). Default is `td`.
...: other graphical arguments. See plot
alternative: alternative hypothesis used in progression analyses. Allowed values are `LT` (as in "lower than", default), `GT` (as in "greater than"), `NE` (as in "not equal"), and `both` (both `LT` and `GT`)
xoffs, yoffs: offset x and y where to print the slope values. That is, the distance from the center of each Voronoy polygons in degrees of visual angle
addSpark: whether to overlay a sparkline graph in each visual field location. The parameters thr, width, and height are used only if addSpark is TRUE. Default value is FALSE.
thr: threshold used for the median absolute deviation of residuals from simple linear regression. If greater than the threshold, the sparkline for that location is plotted in red and with a thicker line. Default is `2` (dB)
width: the width of each pointwise sparkline plot. Default is `4` (degrees of visual angle)
height: the height of each pointwise sparkline plot. Default is `2` (degrees of visual angle)
grp: number of baseline (first) and last visual fields to group. Default is `3`
add: whether to generate a new plot (`FALSE`, as default) or to add to an existing figure (`TRUE`)

Structure of graphical parameters

Graphical parameters for visualFields must be a list containing

coord print x and y coordinates. They could be different from the the real visual field location testing coordinates in complex visual field grids to help readability and improve visualization of statistical results
tess tesselation for the visual field maps. Check section Tesselation in visualFields
colmap color map representing the probability scale. Check section Color schemes in visualFields

A default graphical parameters can be generated with generategpar

Tesselation in visualFields

A tesselation in visualFields must be defined with a list containing

xlim,
ylim 2-dimensional vectors containing the minimum and maximum x and y values
floor the value to be assinged to any sensitivity value lower than floor
tiles a list of as many tiles defining the tesselation as visual field test locations. Each element of the list is a table with x and y coordinates defining a polygon containing the corresponding test location. Each polygon is thus the tile for each visual field test location
hull a table with x and y coordinates defining the outer hull of the tessellation

A default tessellation can be generated with vftess

Color schemes in visualFields

A color scheme in visualFields must be defined with a list containing

map a table mapping probabilities levels with colors defined in hexadecimal base
fun a function that takes sensitivity values and deviation probability levels and returns the corresponding color code.

A default color scheme can be generated with vfcolscheme

Details

The following functions generate plots using visual fields data

vfgpar generates simple graphical parameters
vftess generates a structure to handle the visual field tessellation. Check section Tesselation in visualFields below for further details
vfcolscheme generates the structures to handle the color scheme Check section Color schemes in visualFields below for further details
vfprogcolscheme generates the structures to handle the color scheme for progression analysis. Check section Color schemes in visualFields below for further details
vfplot plots a single test for visual field data
vfplotsens plots a single test for visual field sensitivity data with a grayscale where darker means greater sensitivity loss
vfplotdev plots a single test for visual field total or pattern deviation data with probability scales represented in color
vfplotplr plots the results of pointwise linear regression for a series of visual fields for an eye from a subject
vflegoplot the legoplot shows the differences between the average values of visual field tests taken as baseline and those at the end of follow up
vflegoplotsens the legoplot for visual field sensitivity data with a grayscale where darker means greater sensitivity loss
vflegoplotdev the legoplot for visual field total or pattern deviation data with probability scales represented in color
vfsparklines the sparklines graph shows spark lines for the series of visual field sensitivities, or total or pattern deviation data for each location

Examples

Run this code

# generate a structure with default graphical parameters for the 30-2 map
vfgpar(locmaps$p30d2$coord)
# generate a structure with default tesselation for the 30-2 map
vftess(locmaps$p30d2$coord)
# default color scheme
vfcolscheme()
# default color scheme for progression
vfprogcolscheme()
# plot visual field values for the last field in the series for the first
# subject in the dataset vfpwgSunyiu24d2
# grayscale with sensitivity values
vfplot(vfselect(vffilter(vfpwgRetest24d2, id == 1), n = 1), type = "s")
# TD values
vfplot(vfselect(vffilter(vfpwgRetest24d2, id == 1), n = 1), type = "td")
# PD values
vfplot(vfselect(vffilter(vfpwgRetest24d2, id == 1), n = 1), type = "pd")
# hybrid sensitivities and TD values
vfplot(vfselect(vffilter(vfpwgRetest24d2, id == 1), n = 1), type = "tds")
# hybrid sensitivities and PD values
vfplot(vfselect(vffilter(vfpwgRetest24d2, id == 1), n = 1), type = "pds")
# plot results from pointwise linear regression for the series of
# visual fields for the right eye in the dataset vfpwgSunyiu24d2
# with sensitivity values
vfplotplr(vffilter(vfpwgSunyiu24d2, eye == "OD"))
# TD values
vfplotplr(gettd(vffilter(vfpwgSunyiu24d2, eye == "OD")))
# PD values
vfplotplr(getpd(gettd(vffilter(vfpwgSunyiu24d2, eye == "OD"))))
# legoplot for the series of visual fields for the right eye
# of the subject in the dataset vfpwgSunyiu24d2
# with sensitivity values
vflegoplot(vffilter(vfpwgSunyiu24d2, eye == "OD"), type = "s")
# TD values
vflegoplot(vffilter(vfpwgSunyiu24d2, eye == "OD"), type = "td")
# PD values
vflegoplot(vffilter(vfpwgSunyiu24d2, eye == "OD"), type = "pd")
# sparklines for the series of visual fields for the right eye of
# the subject in the dataset vfpwgSunyiu24d2
# with sensitivity values
vfsparklines(vffilter(vfpwgSunyiu24d2, eye == "OD"))
# TD values
vfsparklines(gettd(vffilter(vfpwgSunyiu24d2, eye == "OD")))
# PD values
vfsparklines(getpd(gettd(vffilter(vfpwgSunyiu24d2, eye == "OD"))))

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