MRIaggr (version 1.1.5)

df2array: data.frame to array converter

Description

Convert observations stored in the data.frame format into the array format.

Usage

df2array(contrast, coords, format = "any", default_value = NA, range.coords = NULL)

Arguments

contrast

the dataset containing the observations in rows and the contrast parameters in columns. vector or data.frame. REQUIRED.

coords

the spatial coordinates of the observations. matrix with a number of rows equal to the number of rows of data. REQUIRED.

format

the format of the output. Can be "any","matrix","data.frame" or "list".

default_value

the element used to fill the missing observations. numeric.

range.coords

the maximum coordinate in each dimension to be considered. numeric vector with length equal to the number of columns of coords.

Value

a list containing :

• [[contrast]] : list containing the new contrast in the new format.
• [[coords]] : a data.frame containing the coordinates of each observation.
• [[unique_coords.group]] : two list containing the possibles coordinates in each dimension.

Details

FUNCTION: If contrast contains several parameters, they are treated one at a time and the result is returned in the form of a list. If range.coords is NULL then the maxima coordinates are those of the coords argument. If only one parameter is specified and the format is set to "any" then a vector is returned.

Examples

#### 1- with simulated data ####
## simulate
set.seed(10)
n <- 4
Y <- rnorm(n^2)

## conversion
res1 <- df2array(contrast = Y, coords = expand.grid(1:n + 0.5, 1:n + 0.5))
res2 <- df2array(contrast = Y, coords = expand.grid(1:n, 1:n), format = "matrix")
res3 <- df2array(contrast = Y, coords = expand.grid(2 * (1:n), 2 * (1:n)))
res4 <- df2array(contrast=cbind(Y ,Y, Y), coords = expand.grid(2 * (1:n), 2 * (1:n)),
                    range.coords = c(10,10))
					
## display
par(mfrow = c(2,2), mar = rep(2,4), mgp = c(1.5,0.5,0))
fields::image.plot(unique(res1$coords[,1]), unique(res1$coords[,2]), res1$contrast[[1]],
                   xlab = "", ylab = "")
fields::image.plot(unique(res2$coords[,1]), unique(res2$coords[,2]), res2$contrast,
                   xlab = "", ylab = "")
fields::image.plot(res3$contrast[[1]])
fields::image.plot(res4$contrast[[2]])

#### 2- with MRIaggr data ####
## load a MRIaggr object
data("MRIaggr.Pat1_red", package = "MRIaggr")
carto <- selectContrast(MRIaggr.Pat1_red, param = "DWI_t0", format = "vector")
coords <- selectCoords(MRIaggr.Pat1_red)
coords[,1] <- coords[,1] + 30
coords[,2] <- coords[,2] + 15

## converion 1
array.DWI_t0 <- df2array(carto, coords = coords, default_value = 1000)$contrast[[1]]

# display
fields::image.plot(min(coords[,1]):max(coords[,1]), min(coords[,2]):max(coords[,2]),
                   array.DWI_t0[,,1], xlab = "i", ylab = "j")

## conversion 2
array.DWI_t0 <- df2array(contrast=carto, coords = coords, default_value = 1000, 
                         range.coords = c(128,128,3))$contrast[[1]]

# display
fields::image.plot(1:128, 1:128, array.DWI_t0[,,1], xlab = "i", ylab = "k")