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# ARF S4 Class Definition file
# Wouter D. Weeda, University of Amsterdam
###############################################################################
## arf version class (version is set here)
setClass(
Class='version',
representation=representation(
version='numeric',
build='numeric',
update='numeric'
),
prototype=prototype(
version=1,
build=2,
update=2
)
)
## arf (general) settings class (containing general settings on NLM, starting values and range checks)
setClass(
Class='settings',
representation=representation(
min.iterlim='numeric', #NLM settings
start.method='character', #which method of determining starting values is used
start.maxfac='numeric',
start.vector='numeric', #vector containing startingvalues (if !start.method=='fixed' only t5 and t6 are used) vector is recycled for regions.
chk.method='character', #which method is used to check the range of parameter values
chk.range='numeric', #vector containing ranges for each parameter (vector is recycled for regions)
warn='numeric', #suppress warnings
sw.type='character' #method to use with Residuals ('diag','tria','full','file')
),
prototype=prototype(
min.iterlim=1500,
start.method='rect',
start.maxfac=2,
start.vector=c(0,0,0,0,.1,100),
chk.method='imagedim',
chk.range=c(0,0,0,0,-.9,-1e+64,0,0,0,0,.9,1e+64),
warn=-1,
sw.type='file'
)
)
## make nifti.fileinfo class
setClass(
Class='nifti.fileinfo',
representation=representation(
fullpath='character', #Full path of nifti file
filename='character', #name of nifti file
filetype='character', #type (nifti or analyze)
extension='character', #extension (.nii, .hdr/.img)
gzipped='logical', #gzipped or not
endian='character' #endian
),
prototype=prototype(
gzipped=FALSE,
endian=.Platform$endian
)
)
## nifti.header class (inherits nifti.fileinfo)
setClass(
Class='nifti.header',
contains='nifti.fileinfo',
representation=representation(
sizeof_hdr = 'numeric', #size of header (must be 348))
data_type = 'character',
db_name = 'character',
extents = 'numeric',
session_error = 'numeric',
regular = 'character',
dim_info = 'character',
dims = 'numeric', #dimensions (num of dim, dimx, dimy,...)
intent_p1 = 'numeric',
intent_p2 = 'numeric',
intent_p3 = 'numeric',
intent_code = 'numeric',
datatype = 'numeric', #storage data type
bitpix = 'numeric', #bits per pixel
slice_start = 'numeric',
pixdim = 'numeric',
vox_offset = 'numeric', #offset of data in .nii file
scl_slope = 'numeric',
scl_inter = 'numeric',
slice_end = 'numeric',
slice_code = 'numeric',
xyzt_units = 'numeric',
cal_max = 'numeric',
cal_min = 'numeric',
slice_duration = 'numeric',
toffset = 'numeric',
glmax = 'numeric',
glmin = 'numeric',
descrip = 'character',
aux_file = 'character',
qform_code = 'numeric',
sform_code = 'numeric',
quatern_b = 'numeric',
quatern_c = 'numeric',
quatern_d = 'numeric',
qoffset_x = 'numeric',
qoffset_y = 'numeric',
qoffset_z = 'numeric',
srow_x = 'numeric',
srow_y = 'numeric',
srow_z = 'numeric',
intent_name = 'character', #meaning of data
magic = 'character', #magicstring
data.type='character', #type of data
data.signed='logical' #signed data
),
prototype=prototype(
sizeof_hdr = 348, #size of header (must be 348))
data_type = '',
db_name = '',
extents = 0,
session_error = 0,
regular = 'r',
dim_info = '',
dims = c(2,0,0,0,0,0,0,0), #dimensions (num of dim, dimx, dimy,...)
intent_p1 = 0,
intent_p2 = 0,
intent_p3 = 0,
intent_code = 0,
datatype = 16, #storage data type
bitpix = 32, #bits per pixel
slice_start = 0,
pixdim = c(0,0,0,0,0,0,0,0),
vox_offset = 0, #offset of data in .nii file
scl_slope = 0,
scl_inter = 0,
slice_end = 0,
slice_code = 0,
xyzt_units = 0,
cal_max = 0,
cal_min = 0,
slice_duration = 0,
toffset = 0,
glmax = 0,
glmin = 0,
descrip = 'ARFv1b1',
aux_file = '',
qform_code = 0,
sform_code = 0,
quatern_b = 0,
quatern_c = 0,
quatern_d = 0,
qoffset_x = 0,
qoffset_y = 0,
qoffset_z = 0,
srow_x = c(0,0,0,0),
srow_y = c(0,0,0,0),
srow_z = c(0,0,0,0),
intent_name = 'character', #meaning of data
magic = 'n+1', #magicstring
data.type = 'double', #type of data
data.signed = TRUE #signed data
)
)
## fmri data class (inherits nifti.header)
setClass(
Class='fmri.data',
contains='nifti.header',
representation=representation(
datavec='numeric'
)
)
## arf data class (containing info on the locations of the data and weightfiles, the dimensions, number of trials, and relevant nifti parameters.)
setClass(
Class='data',
representation=representation(
name='character', #indicator of data (subject,condition etc.)
fullpath='character', #fullpath of files
datafiles='character', #vector of char containing trial datafiles
weightfiles='character', #vector of char containing weight datafiles
avgdatfile='character', #filename of average data
avgWfile='character', #filename of average weights
trials='numeric' #number of trials
)
)
## arf model class (containing information on the fitted arf model, it extends the data class)
setClass(
Class='model',
contains='data',
representation=representation(
modelname='character', #name of the model (default is region_n)
convergence='character', #convergence information
minimum='numeric', #minimum of objective function
estimates='numeric', #vector of parameter estimates (t1r1..t6r1,t1r2..t6r2,t1rR..t6rR)
hessian='matrix', #hessian matrix
varcov='matrix', #variance covariance matrix (full form)
warnings='character', #warnings (pos def var/covar etc.)
fit='numeric', #fit value (BIC)
wald='ANY', #object of class 'wald'
regions='numeric', #number of fitted regions
startval='numeric', #vector of starting values
proctime='numeric',
valid='logical' #is model valid (converged and no warnings)
),
prototype=prototype(
valid=FALSE
)
)
## arf sequence class (containing info (fit, valid) on a sequence of models)
setClass(
Class='sequence',
representation=representation(
current='numeric', #current number of regions in model
regions='numeric', #vector of regions to fit (can be sequential or any other combination)
mnames='character', #vector of names of models
fit='numeric', #vector of fit measures (to evaluate best fit)
minimum='numeric', #which region has the minimum
valid='numeric' #vector of validity of solutions (all estimates and variances ok)
),
prototype=prototype(
current=1,
minimum=0
)
)
## wald statistics class
setClass(
Class='wald',
representation=representation(
design='matrix', #design
stats='matrix', #statistic
df1='numeric', #df1
df2='numeric', #df2
pvalues='matrix' #pvalues
)
)
## arf analysis class (not yet implemented)
setClass(
Class='analysis',
representation=representation(
name='character', #name of the analysis
modelobjects='ANY', #names of model objects in the analysis
designmatrix='numeric', #designmatrix of analysis
rfx='logical' #perform random-effects analysis?
)
)
## arf sims class (only for simulation of data) (not yet implemented)
setClass(
Class='sims',
representation=representation(
numsims='numeric', #number of simulations
numtrials='numeric', #number of trials
theta='numeric', #vector of parameter values to simulate
shapemodel='character', #which shape model of signal
noisemodel='character', #which noise calc method
noiseFWHM='numeric', #FWHM of noise
imageFWHM='numeric', #FWHM of signal+noise smoother
sequence='numeric', #sequence of regions to be fit
SNR='numeric' #which signal to noise ratio is used?
)
)
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