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Plots.R
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Plots.R
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############################################
## Code to produce plots as in the paper ##
############################################
rm(list = ls())
# Set seed
set.seed(50)
# Set working directory
setwd("...")
require(oro.nifti)
norm_vec <- function(x) sqrt(sum(x^2))
#########################
## Read in the data ##
#########################
data <- read.table('foci.txt', header = F, sep = "\t")
data <- data[, c(2:4, 1)]
names(data) <- c('X','Y', 'Z', 'study') # Coordinates and study number
attach(data)
data[1:10, ]
N <- length(unique(data[, 4]))
ni <- tabulate(data$study) # Number of foci per study
exclude <- which(ni == 0) # Contrasts to exclude because no foci are left
ni <- ni[which((tabulate(data$study) != 0) == TRUE)]
ID <- rep(1:N, ni)
d <- dim(data)[2] - 1 # Number of dimensions
data <- cbind(data[, c(1:d)], ID)
##################
## Create axes ##
##################
mask_full = readNIfTI('brainmask.nii') # Finer grid used for plotting: 2 x 2 x 2 mm brain mask (voxels 91 x 109 x 91)
# attributes(mask_full)
# mask_centre <- c(90, -126, -72)
Ix <- seq(1, 182, by = 2)
Iy <- seq(1, 218, by = 2)
Iz <- seq(1, 182, by = 2)
A <- (Iy[2] - Iy[1])*(Ix[2] - Ix[1])*(Iz[2] - Iz[1]) # Volume of each voxel
# Axes to reproduce plots similar to those in the paper (make it a squared figure)
Ixplotting <- seq(-109, 107, by = 2)
Iyplotting <- seq(-127, 89, by = 2)
Izplotting <- seq(-91, 125, by = 2)
Ixresc <- seq(-91, 89, by = 2)
Iyresc <- seq(-127, 89, by = 2)
Izresc <- seq(-73, 107, by = 2)
########################################################
## Define radial cubic B-splines or Gaussian kernels ##
########################################################
# ND: mask is 91 x 109 x 91, but mask is null above z = 82
# Discard slices above z = 79 provided there are no foci falling outside the mask
Grid <- c()
grid_slice <- as.matrix(expand.grid(Ix,Iy))
for (n in 17:48){ # 1:91
map = mask_full[,,n]
map = map > 0.5
msk = as.vector(map)
Grid <- rbind(Grid, cbind(grid_slice[msk, ], Iz[n]))
}
dim(Grid)
rm(grid_slice)
##################################################
## Restrict computation to points in the mask ##
## to avoid bias from off-mask estimation ##
##################################################
xx <- seq(40, 145, length.out = 8)
yy <- seq(40, 180, length.out = 8)
zz <- seq(38, 90, length.out = 7)
kernels <- expand.grid(xx, yy, zz)
knots <- kernels
# At every odd numbered z slice, shift the x coordinate to re-create a chess-like kernel grid
for (n in 1:floor(length(zz)/2)){
kernels[which(kernels[, 3] == zz[n*2]), 1] <- kernels[which(kernels[, 3] == zz[2*n]), 1] + 10
}
knots <- kernels[- which(kernels[, 1] > 145), ]
nu <- 1/(2*256)
d <- 3
B.pred <- matrix(0, dim(Grid)[1], dim(knots)[1]) # Observed matrix of basis functions
for (i in 1:dim(B.pred)[1]){
obs.knot <- matrix(as.numeric(Grid[i, 1:d]), dim(knots)[1], d, byrow = TRUE) - knots
B.pred[i, ] <- as.matrix(exp(-nu * apply(obs.knot, 1, norm_vec)^2))
}
B.pred <- cbind(1, B.pred) # Dense basis for integral evaluation
for (i in 1:dim(B.pred)[2]){
ind = which(B.pred[, i] < 1e-35)
if (length(ind) > 0) B.pred[ind, i] = 0
}
p = dim(B.pred)[2]
#######################################
## Define global constants ##
#######################################
nrun = 50000;
burn = 25000;
thin = 50;
every = 100;
start = 250; # Starting iteration to update the stepsize
sp = (nrun - burn)/thin; # Number of posterior samples
maxk = 50 # Must correspond to the same value Matlab code
######################################
## Reading covariates in ##
######################################
Z = read.table('covariates.txt');
r = dim(Z)[2]; # Number of covariates per study
######################################
## Reading study-type in ##
######################################
outcome <- read.table('studytype.txt'); Y = outcome
anger <- which(outcome[, 1] == 1)
disgust <- which(outcome[, 1] == 2)
fear <- which(outcome[, 1] == 3)
happy <- which(outcome[, 1] == 4)
sad <- which(outcome[, 1] == 5)
# binary <- matrix(NA, length(ID), 1)
# for (i in 1:N) binary[which(ID == i),1] <- outcome[i, 1]
# anger_studies <- data[binary == 1, 1:d]
# disgust_studies <- data[binary == 2, 1:d]
# fear_studies <- data[binary == 3, 1:d]
# happy_studies <- data[binary == 4, 1:d]
# sad_studies <- data[binary == 5, 1:d]
train <- as.matrix(as.numeric(read.table(file = "train.txt", header = FALSE, sep = ",")))
test <- setdiff(1:N, train)
##################################################
## Code for 3D plotting of the intensities ##
## Need to extract the basis evaluated at the ##
## matching z-slice ##
##################################################
library(fields)
theta <- as.matrix(read.table(file = "thetacbma_post.txt", header = FALSE, sep = " "))
##############################################
## Plotting posterior means log intensities ##
##############################################
type1 <- which(Y == 1);
type1_cbma <- matrix(0, sp, p)
for (i in 1:length(type1)){
j = type1[i]
ind <- c()
for (l in 1:p){
k = l - 1
ind[l] <- k*N + j
}
type1_cbma <- type1_cbma + theta[, ind]
}
type1_cbma <- type1_cbma/length(type1)
intensity1_cbma <- apply((B.pred %*% t(type1_cbma)), 1, mean)
type2 <- which(Y == 2);
type2_cbma <- matrix(0, sp, p)
for (i in 1:length(type2)){
j = type2[i]
ind <- c()
for (l in 1:p){
k = l - 1
ind[l] <- k*N + j
}
type2_cbma <- type2_cbma + theta[, ind]
}
type2_cbma <- type2_cbma/length(type2)
intensity2_cbma <- apply((B.pred %*% t(type2_cbma)), 1, mean)
type3 <- which(Y == 3);
type3_cbma <- matrix(0, sp, p)
for (i in 1:length(type3)){
j = type3[i]
ind <- c()
for (l in 1:p){
k = l - 1
ind[l] <- k*N + j
}
type3_cbma <- type3_cbma + theta[, ind]
}
type3_cbma <- type3_cbma/length(type3)
intensity3_cbma <- apply((B.pred %*% t(type3_cbma)), 1, mean)
type4 <- which(Y == 4);
type4_cbma <- matrix(0, sp, p)
for (i in 1:length(type4)){
j = type4[i]
ind <- c()
for (l in 1:p){
k = l - 1
ind[l] <- k*N + j
}
type4_cbma <- type4_cbma + theta[, ind]
}
type4_cbma <- type4_cbma/length(type4)
intensity4_cbma <- apply((B.pred %*% t(type4_cbma)), 1, mean)
type5 <- which(Y == 5);
type5_cbma <- matrix(0, sp, p)
for (i in 1:length(type5)){
j = type5[i]
ind <- c()
for (l in 1:p){
k = l - 1
ind[l] <- k*N + j
}
type5_cbma <- type5_cbma + theta[, ind]
}
type5_cbma <- type5_cbma/length(type5)
intensity5_cbma <- apply((B.pred %*% t(type5_cbma)), 1, mean)
## Choose some axial slices ##
set = c( 20, 24, 28, 32, 38, 45)
for (i in 1:length(set)){
n = set[i]
# This is the z coordinate in mms of what I'm plotting (the center of the voxel)
map = mask_full[,,n]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
int1 <- intensity1_cbma[which(Grid[, 3] == Iz[n])]
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (f in 1:dim(mask.pos)[1]){
pos <- mask.pos[f, ]
image_matrix[pos[1], pos[2]] <- (int1[f])
}
image_matrix1 <- rbind(matrix(NA, nrow = 9, ncol = length(Iy)), image_matrix, matrix(NA, nrow = 9, ncol = length(Iy)))
scale1 <- range((image_matrix1), na.rm = TRUE)
int2 <- intensity2_cbma[which(Grid[, 3] == Iz[n])]
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (f in 1:dim(mask.pos)[1]){
pos <- mask.pos[f, ]
image_matrix[pos[1], pos[2]] <- (int2[f])
}
image_matrix2 <- rbind(matrix(NA, nrow = 9, ncol = length(Iy)), image_matrix, matrix(NA, nrow = 9, ncol = length(Iy)))
scale2 <- range((image_matrix2), na.rm = TRUE)
int3 <- intensity3_cbma[which(Grid[, 3] == Iz[n])]
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (f in 1:dim(mask.pos)[1]){
pos <- mask.pos[f, ]
image_matrix[pos[1], pos[2]] <- (int3[f])
}
image_matrix3 <- rbind(matrix(NA, nrow = 9, ncol = length(Iy)), image_matrix, matrix(NA, nrow = 9, ncol = length(Iy)))
scale3 <- range((image_matrix3), na.rm = TRUE)
int4 <- intensity4_cbma[which(Grid[, 3] == Iz[n])]
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (f in 1:dim(mask.pos)[1]){
pos <- mask.pos[f, ]
image_matrix[pos[1], pos[2]] <- (int4[f])
}
image_matrix4 <- rbind(matrix(NA, nrow = 9, ncol = length(Iy)), image_matrix, matrix(NA, nrow = 9, ncol = length(Iy)))
scale4 <- range((image_matrix4), na.rm = TRUE)
int5 <- intensity5_cbma[which(Grid[, 3] == Iz[n])]
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (f in 1:dim(mask.pos)[1]){
pos <- mask.pos[f, ]
image_matrix[pos[1], pos[2]] <- (int5[f])
}
image_matrix5 <- rbind(matrix(NA, nrow = 9, ncol = length(Iy)), image_matrix, matrix(NA, nrow = 9, ncol = length(Iy)))
scale5 <- range((image_matrix5), na.rm = TRUE)
out_cbma <- c(min(min(scale1), min(scale2), min(scale3), min(scale4), min(scale5)),
max(max(scale1), max(scale2), max(scale3), max(scale4), max(scale5)))
pdf(file = paste("Z = ", Izresc[n], ".pdf"), width = 14, height = 4.5)
m <- rbind(c(0, 1, 0.90, 1), c(0, 1, 0.20, 0.90), c(0, 1, 0, 0.20))
split.screen(m)
screen(1)
par(mar = c(0,1,1,1), oma = c(0, 0, 1, 0))
title(main = paste("Post mean log intensities Z = ", Izresc[n]))
split.screen(c(1,5), screen=2)-> ind2
j = 1
screen(ind2[j])
par(pty = "s", mar = c(0, 0, 1, 0), oma = c( 0, 0, 1, 0 ) )
# par(mfrow = c(2,3), pty = "s", mar = c(2,4,2,3))
image(c(Ixplotting), c(Iyplotting), matrix((image_matrix1), length(Ixplotting), length(Ixplotting), byrow = FALSE), xlab = ' ', ylab = ' ',
zlim = out_cbma, main = "Anger", col = (gray.colors(64, start = 0.9, end = 0.1, gamma = 2.2)), axes = F)
j = 2
screen(ind2[j])
par(pty = "s", mar = c(0, 0, 1, 0), oma = c( 0, 0, 1, 0 ) )
image(c(Ixplotting), c(Iyplotting), matrix((image_matrix2), length(Ixplotting), length(Ixplotting), byrow = FALSE), xlab = ' ', ylab = ' ',
zlim = out_cbma, main = "Disgust", col = (gray.colors(64, start = 0.9, end = 0.1, gamma = 2.2)), axes = F)
j = 3
screen(ind2[j])
par(pty = "s", mar = c(0, 0, 1, 0), oma = c( 0, 0, 1, 0 ) )
image(c(Ixplotting), c(Iyplotting), matrix((image_matrix3), length(Ixplotting), length(Ixplotting), byrow = FALSE), xlab = ' ', ylab = ' ',
zlim = out_cbma, main = "Fear", col = (gray.colors(64, start = 0.9, end = 0.1, gamma = 2.2)), axes = F)
j = 4
screen(ind2[j])
par(pty = "s", mar = c(0, 0, 1, 0), oma = c( 0, 0, 1, 0 ) )
image(c(Ixplotting), c(Iyplotting), matrix((image_matrix4), length(Ixplotting), length(Ixplotting), byrow = FALSE), xlab = ' ', ylab = ' ',
zlim = out_cbma, main = "Happy", col = (gray.colors(64, start = 0.9, end = 0.1, gamma = 2.2)), axes = F)
j = 5
screen(ind2[j])
par(pty = "s", mar = c(0, 0, 1, 0), oma = c( 0, 0, 1, 0 ) )
image(c(Ixplotting), c(Iyplotting), matrix((image_matrix5), length(Ixplotting), length(Ixplotting), byrow = FALSE), xlab = ' ', ylab = ' ',
zlim = out_cbma, main = "Sad", col = (gray.colors(64, start = 0.9, end = 0.1, gamma = 2.2)), axes = F)
screen(3)
par(mfrow = c(1,1),mar = c(2,0,0,0), oma = c(0, 0, 0, 0))
image.plot(zlim = out_cbma, horizontal = T, legend.only = TRUE,
legend.width = .6, col=gray.colors(64, start = 0.9, end = 0.1, gamma = 2.2))
close.screen( all=TRUE)
dev.off()
}
# # # # # # # # # # # # # # # # #
# # -- Examine learnt bases -- #
# # # # # # # # # # # # # # # #
factor <- as.matrix(read.table(file = "Factor.txt", header = FALSE, sep = " ", skip = burn/every))
Lambdaout <- as.matrix(read.table(file = "Lambda.txt", header = FALSE, sep = " "))
j = 1
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
out <- matrix(0, length(ind), maxk)
for(i in 1:sp){
lambda_i = matrix(Lambdaout[i, ], nrow = p, ncol = maxk, byrow = F)
out = out + B.pred[ind, ] %*% lambda_i
}
out <- out / sp
j = 2
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
out2 <- matrix(0, length(ind), maxk)
for(i in 1:sp){
lambda_i = matrix(Lambdaout[i, ], nrow = p, ncol = maxk, byrow = F)
out2 = out2 + B.pred[ind, ] %*% lambda_i
}
out2 <- out2 / sp
j = 3
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
out3 <- matrix(0, length(ind), maxk)
for(i in 1:sp){
lambda_i = matrix(Lambdaout[i, ], nrow = p, ncol = maxk, byrow = F)
out3 = out3 + B.pred[ind, ] %*% lambda_i
}
out3 <- out3 / sp
j = 4
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
out4 <- matrix(0, length(ind), maxk)
for(i in 1:sp){
lambda_i = matrix(Lambdaout[i, ], nrow = p, ncol = maxk, byrow = F)
out4 = out4 + B.pred[ind, ] %*% lambda_i
}
out4 <- out4 / sp
j = 5
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
out5 <- matrix(0, length(ind), maxk)
for(i in 1:sp){
lambda_i = matrix(Lambdaout[i, ], nrow = p, ncol = maxk, byrow = F)
out5 = out5 + B.pred[ind, ] %*% lambda_i
}
out5 <- out5 / sp
j = 6
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
out6 <- matrix(0, length(ind), maxk)
for(i in 1:sp){
lambda_i = matrix(Lambdaout[i, ], nrow = p, ncol = maxk, byrow = F)
out6 = out6 + B.pred[ind, ] %*% lambda_i
}
out6 <- out6 / sp
pdf(file = paste("learnt1.pdf"), width = 14, height = 4)
m <- rbind(c(0, 1, 0.90, 1), c(0, 1, 0.2, 0.90), c(0, 1, 0.15, 0.25))
split.screen(m)
screen(1)
par(mar = c(0,1,2,1), oma = c(0, 0, 1, 0))
title(main = expression(paste(tilde(phi)[1])))
# close.screen(all = TRUE)
split.screen(c(1,6), screen = 2)-> ind2
l = 1
j = 1
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out[j, l]
}
image_matrix1 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale1 = range(image_matrix1, na.rm = T)
j = 2
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
maxk <- 50
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out2[j, l]
}
image_matrix2 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale2 = range(image_matrix2, na.rm = T)
j = 3
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
maxk <- 50
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out3[j, l]
}
image_matrix3 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale3 = range(image_matrix3, na.rm = T)
j = 4
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
maxk <- 50
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out4[j, l]
}
image_matrix4 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale4 = range(image_matrix4, na.rm = T)
j = 5
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
maxk <- 50
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out5[j, l]
}
image_matrix5 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale5 = range(image_matrix5, na.rm = T)
j = 6
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
maxk <- 50
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out6[j, l]
}
image_matrix6 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale6 = range(image_matrix6, na.rm = T)
out1range = c(min(min(scale1), min(scale2), min(scale3), min(scale4), min(scale5), min(scale6)),
max(max(scale1), max(scale2), max(scale3), max(scale4), max(scale5), max(scale6)))
g = 1
screen(ind2[g])
j = 1
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix1, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out1range, main = paste("Z=",Izresc[set[j]]))
g = 2
screen(ind2[g])
j = 2
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix2, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out1range, main = paste("Z=",Izresc[set[j]]))
g = 3
screen(ind2[g])
j = 3
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix3, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out1range, main = paste("Z=",Izresc[set[j]]))
g = 4
screen(ind2[g])
j = 4
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix4, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out1range, main = paste("Z=",Izresc[set[j]]))
g = 5
screen(ind2[g])
j = 5
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix5, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out1range, main = paste("Z=",Izresc[set[j]]))
g = 6
screen(ind2[g])
j = 6
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix6, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out1range, main = paste("Z=",Izresc[set[j]]))
screen(3)
par(mfrow = c(1,1),mar = c(2,0,0,0), oma = c(0, 0, 0, 0))
image.plot(zlim = out1range, horizontal = T, legend.only = TRUE,
legend.width = .6, col=gray.colors(64, start = 0, end = 1, gamma = 2.2))
close.screen(all = TRUE)
dev.off()
pdf(file = paste("learnt2.pdf"), width = 14, height = 4)
m <- rbind(c(0, 1, 0.90, 1), c(0, 1, 0.2, 0.90), c(0, 1, 0.15, 0.25))
split.screen(m)
screen(1)
par(mar = c(0,1,2,1), oma = c(0, 0, 1, 0))
title(main = expression(paste(tilde(phi)[2])))
# close.screen(all = TRUE)
split.screen(c(1,6), screen = 2)-> ind2
l = 2
j = 1
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out[j, l]
}
image_matrix1 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale1 = range(image_matrix1, na.rm = T)
j = 2
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
maxk <- 50
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out2[j, l]
}
image_matrix2 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale2 = range(image_matrix2, na.rm = T)
j = 3
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
maxk <- 50
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out3[j, l]
}
image_matrix3 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale3 = range(image_matrix3, na.rm = T)
j = 4
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
maxk <- 50
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out4[j, l]
}
image_matrix4 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale4 = range(image_matrix4, na.rm = T)
j = 5
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
maxk <- 50
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out5[j, l]
}
image_matrix5 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale5 = range(image_matrix5, na.rm = T)
j = 6
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
maxk <- 50
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out6[j, l]
}
image_matrix6 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale6 = range(image_matrix6, na.rm = T)
out2range = c(min(min(scale1), min(scale2), min(scale3), min(scale4), min(scale5), min(scale6)),
max(max(scale1), max(scale2), max(scale3), max(scale4), max(scale5), max(scale6)))
l = 1
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix1, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
l = 2
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix2, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
l = 3
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix3, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
l = 4
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix4, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
l = 5
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix5, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
l = 6
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix6, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
screen(3)
par(mfrow = c(1,1),mar = c(2,0,0,0), oma = c(0, 0, 0, 0))
image.plot(zlim = out2range, horizontal = T, legend.only = TRUE,
legend.width = .6, col=gray.colors(64, start = 0, end = 1, gamma = 2.2))
close.screen(all = TRUE)
dev.off()
pdf(file = paste("learnt3.pdf"), width = 14, height = 4)
m <- rbind(c(0, 1, 0.90, 1), c(0, 1, 0.2, 0.90), c(0, 1, 0.15, 0.25))
split.screen(m)
screen(1)
par(mar = c(0,1,2,1), oma = c(0, 0, 1, 0))
title(main = expression(paste(tilde(phi)[3])))
split.screen(c(1,6), screen = 2)-> ind2
l = 3
j = 1
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out[j, l]
}
image_matrix1 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale1 = range(image_matrix1, na.rm = T)
j = 2
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
maxk <- 50
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out2[j, l]
}
image_matrix2 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale2 = range(image_matrix2, na.rm = T)
j = 3
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
maxk <- 50
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out3[j, l]
}
image_matrix3 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale3 = range(image_matrix3, na.rm = T)
j = 4
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out4[j, l]
}
image_matrix4 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale4 = range(image_matrix4, na.rm = T)
j = 5
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out5[j, l]
}
image_matrix5 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale5 = range(image_matrix5, na.rm = T)
j = 6
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out6[j, l]
}
image_matrix6 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale6 = range(image_matrix6, na.rm = T)
out2range = c(min(min(scale1), min(scale2), min(scale3), min(scale4), min(scale5), min(scale6)),
max(max(scale1), max(scale2), max(scale3), max(scale4), max(scale5), max(scale6)))
l = 1
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix1, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
l = 2
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix2, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
l = 3
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix3, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
l = 4
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix4, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
l = 5
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix5, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
l = 6
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix6, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
screen(3)
par(mfrow = c(1,1),mar = c(2,0,0,0), oma = c(0, 0, 0, 0))
image.plot(zlim = out2range, horizontal = T, legend.only = TRUE,
legend.width = .6, col=gray.colors(64, start = 0, end = 1, gamma = 2.2))
close.screen(all = TRUE)
dev.off()
pdf(file = paste("learnt4.pdf"), width = 14, height = 4)
m <- rbind(c(0, 1, 0.80, 1), c(0, 1, 0.2, 0.90), c(0, 1, 0.15, 0.25))
split.screen(m)
screen(1)
par(mar = c(0,1,2,1), oma = c(0, 0, 1, 0))
title(main = expression(paste(tilde(phi)[4])))
split.screen(c(1,6), screen = 2)-> ind2
l = 4
j = 1
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out[j, l]
}
image_matrix1 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale1 = range(image_matrix1, na.rm = T)
j = 2
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out2[j, l]
}
image_matrix2 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale2 = range(image_matrix2, na.rm = T)
j = 3
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out3[j, l]
}
image_matrix3 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale3 = range(image_matrix3, na.rm = T)
j = 4
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out4[j, l]
}
image_matrix4 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale4 = range(image_matrix4, na.rm = T)
j = 5
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out5[j, l]
}
image_matrix5 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale5 = range(image_matrix5, na.rm = T)
j = 6
ind = which(Grid[, 3] == Iz[set[j]])
map = mask_full[,,set[j]]
map = map > 0.5
msk = as.vector(map)
mask.pos <- which(map == TRUE, arr.ind = TRUE)
image_matrix <- matrix(NA, nrow = length(Ix), ncol = length(Iy))
for (j in 1:dim(mask.pos)[1]){
pos <- mask.pos[j, ]
image_matrix[pos[1], pos[2]] <- out6[j, l]
}
image_matrix6 <- rbind(matrix(NA, 9, length(Iy)), image_matrix, matrix(NA, 9, length(Iy)))
scale6 = range(image_matrix6, na.rm = T)
out2range = c(min(min(scale1), min(scale2), min(scale3), min(scale4), min(scale5), min(scale6)),
max(max(scale1), max(scale2), max(scale3), max(scale4), max(scale5), max(scale6)))
l = 1
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix1, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
l = 2
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix2, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
l = 3
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix3, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
l = 4
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix4, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
l = 5
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix5, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
l = 6
screen(ind2[l])
par(pty = "s", mar = c(0, 0, 0, 0), oma = c( 0, 0, 2, 0 ))
image(c(Ixplotting), c(Iyplotting), image_matrix6, xlab = ' ', ylab = ' ', axes = F,
col = (gray.colors(64, start = 0, end = 1, gamma = 2.2)), zlim = out2range, main = paste("Z=",Izresc[set[l]]))
screen(3)
par(mfrow = c(1,1),mar = c(2,0,0,0), oma = c(0, 0, 0, 0))
image.plot(zlim = out2range, horizontal = T, legend.only = TRUE,
legend.width = .6, col=gray.colors(64, start = 0, end = 1, gamma = 2.2))
close.screen(all = TRUE)
dev.off()