em.spheroids {unfoldr} | R Documentation |
Estimate the joint size-shape-orientation distribution of spheroids
em.spheroids(P, F, maxIt, nCores = getOption("par.unfoldr", 2L))
P |
coefficient array |
F |
input histogram |
maxIt |
maximum number of EM iterations |
nCores |
number of cpu cores to be used |
Given an array of coefficients P
, see coefficientMatrixSpheroids
and an input histogram
F
of measured planar characteristics of section profiles, the function estimates the spatial joint
size-shape-orientation distribution of the corresponding spheroids in 3D by a discretized version of the
Expectation Maximization (EM) algorithm. A number of cpu cores can be set by the option 'par.unfoldr
'
for parallel computations. The function is also internally called by unfold
in case of spheroids.
trivariate histogram
M. Baaske
Bene\check{\textrm{s}}, V. and Rataj, J. Stochastic Geometry: Selected Topics Kluwer Academic Publishers, Boston, 2004
## Comment: Trivariate unfolding of spheroid distribution ## set number of cpu cores (optional) options(par.unfoldr=2L) ## Intensity: mean number of spheroids per unit volume lam <- 1000 ## simulation parameters theta <- list("size"=list("meanlog"=-2.5,"sdlog"=0.5), "shape"=list(0.5),"orientation"=list("kappa"=2)) ## simualtion set.seed(1234) S <- simPoissonSystem(theta,lam,size="rlnorm", orientation="rbetaiso",box=list(c(0,5)),type="prolate",pl=1) ## unfolding sp <- verticalSection(S,2.5) ret <- unfold(sp,c(7,6,5),kap=1.25) cat("Intensities: ", sum(ret$N_V)/25, "vs.",lam,"\n")