Load a visual field csv file

A visual field csv file can be loaded using the generic function read.csv(filename). The csv file should contain a minimum number of variables needed for the simulation:

• ID: patient ID
• pd: pupil distance (mm)
• gender: patient gender is used to estimate pupil distance when pupil distance data is not available
• eye : left (OS) or right (OD) eye
• 24-2 visual field data (54 data points)

atbino.df <- read.csv(system.file("extdata", "atbinocular.csv", 
                                   package = "binovisualfields"))
#yourdf <- read.csv("yourdata.csv"")  specify path and data file name to load your own data
at_id <- unique(atbino.df$id)
at_gender <- atbino.df$gender[1:length(at_id)]

Create visual field matrices

The left and right visual field data can be extracted from the loaded atbino.df data frame.

at_left_visual_fields <- atbino.df[atbino.df$seye=="OS", 4:ncol(atbino.df)]
at_rght_visual_fields <- atbino.df[atbino.df$seye=="OD", 4:ncol(atbino.df)]

After initializing the left and right visual field array for all patients, visual field matrices can be obtained using the function makevf and stored in data arrays.

#initialize vf array for all patients
vf_matrix <- matrix(NA, ncol=10, nrow = 8)
at_rght_vf_array <- replicate(nrow(at_rght_visual_fields), vf_matrix)
for (i in 1:nrow(at_rght_visual_fields)){
  at_rght_vf_array[,,i] <- makevf(unlist(at_rght_visual_fields[i,], use.names = F), eye="right")
}

at_left_vf_array <- replicate(nrow(at_left_visual_fields), vf_matrix)
for (i in 1:nrow(at_rght_visual_fields)){
  at_left_vf_array[,,i] <- makevf(unlist(at_left_visual_fields[i,], use.names = F), eye="left")
}

Plot individual dataset by ID

id <- 3
pindex  <- match(id, at_id)
left_vf <- at_left_vf_array[, , pindex]
rght_vf <- at_rght_vf_array[, , pindex]
gender  <- at_gender[pindex]

fix_dist <- c(600, 0)
theta_left <- caltheta(fix_dist, gender = gender, eye = "left")
theta_rght <- caltheta(fix_dist, gender = gender, eye = "right")

object_distances <- seq(300, 1000, 100)
c_vf  <- binovfcal(left_vf, rght_vf, theta_left, theta_rght, object_distances, gender=gender)

Subsetting

Each matrix in the integrated visual field array is named by it corresponding object distance. For example, to extract the integrated visual field for the object distance of 500 mm, one way is as the following

c_vf <- c_vf[, , as.character(500)]

plot the figures

The function plotvfray plots the interaction between the left and right visual field from a top view. The function plotvf plots both monocular visual field or simulated integrated visual field. The following code output all plots for each distance plane specified in the dist_planes vector into a pdf file.

filename <- paste0("archetypes", id, ".pdf")
pdf(filename, width=16)
options(error=dev.off)

layout(matrix(c(1, 1, 1, 1, 1, 1, 2, 4, 5, 3, 4, 5), 3, 4),  heights = c(3, 3, 1))
m_xs <- seq(-27, 27, length.out = 10)
c_xs <- seq(-63, 63, 6)
for (i in object_distances) {
  plotvfray (left_vf, rght_vf, theta_left, theta_rght, fix_dist, i)
  plotvf(m_xs, left_vf, "Left Monocular")
  plotvf(m_xs, rght_vf, "Right Monocular")
  plotvf(c_xs, c_vf[, , as.character(i)],
        paste0("DD-IVF Fixation Distance = ", fix_dist[1], "mm, Object Distance = ", i, "mm"))
  colorkey()
}
dev.off()
options(error=NULL)