spatialnoise {neuRosim} | R Documentation |
Generate spatially correlated noise
Description
Generates a spatially correlated noise dataset with specified dimensions and standard deviation.
Usage
spatialnoise(dim, sigma, nscan, method = c("corr", "gammaRF", "gaussRF"),
type=c("gaussian","rician"), rho = 0.75, FWHM = 4, gamma.shape = 6,
gamma.rate = 1, vee=1, template, verbose = TRUE)
Arguments
dim |
A vector specifying the dimensions of the image. |
sigma |
The standard deviation of the noise. |
nscan |
The number of scans in the dataset. |
method |
Method specifying the type of spatial correlation. Default is |
type |
Type of distribution if |
rho |
If |
FWHM |
If |
gamma.shape |
If |
gamma.rate |
If |
vee |
If |
template |
An array representing the anatomical structure or mask with dimensions equal to dim. |
verbose |
Logical indicating if warnings should be printed. |
Details
The function generates spatially correlated noise. When method=="corr"
, AR(1) voxelwise correlations are introduced.
If method=="gaussRF"
of method=="gammaRF"
, respectively a Gaussian Random Field or a Gamma Random Field is created. The result is a noise array with specified dimensions and desired standard deviation.
The generation of the random fields is based on the function Sim.3D.GRF
from J.L. Marchini in the package AnalyzeFMRI.
Value
An array containing the noise with dimensions specified in dim and nscan.
Author(s)
J. Durnez, B. Moerkerke, M. Welvaert
See Also
temporalnoise
, lowfreqdrift
, physnoise
, tasknoise
, systemnoise
, Sim.3D.GRF
Examples
d <- c(10,10,10)
sigma <- 5
nscan <- 100
rhospat <- 0.7
out <- spatialnoise(d, sigma, nscan, method="corr", rho=rhospat, verbose=FALSE)