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populateRootsWeights <- function(N,L,Z,PolyName,ParamDistrib,NDIi){
# cat("In popRootsWeights\n")
# dummy= NDIi
NDXi = rep(0,N*Z)
dim(NDXi) <- c(N,Z)
NDWi = rep(0,Z)
weighttmp = rep(0,(max(L)*N))
dim(weighttmp) = c(max(L),N)
for (nn in 1:N){
if (!is.null(ParamDistrib)){
if (PolyName[nn] == "JACOBI"){
alpha = ParamDistrib$alpha[nn]
beta = ParamDistrib$beta[nn]
} else if (PolyName[nn] == "LAGUERRE"){
alpha = ParamDistrib$alpha[nn]
beta = 0
} else {stop('Jacobi requires ParamDistrib$alpha and ParamDistrib$beta to be defined.\nLaguerre requires ParamDistrib$shape to be defined.')}
} else{
alpha = 0 #rep(0,N)
beta = 0 #rep(0,N)
}
# Computing the roots
# print(c(L[nn],PolyName[nn],alpha[nn],beta[nn]))
# coeff = polyTermNorm(L[nn],PolyName[nn],alpha[nn],beta[nn])
# cat(L[nn],PolyName[nn],alpha,beta,'\n')
coeff = polyTermNorm(L[nn],PolyName[nn],alpha,beta)
# cat(coeff,'\n')
xi = Re(polyroot(coeff))
# Computing the weights
weight = rep(0.0,L[nn])
for (ii in (1:L[nn])){
weight[ii] = polyWeight(L[nn],xi,ii,PolyName[nn],alpha,beta)
}
weight = weight/sum(weight)
# Sort the roots and weights with increasing roots
ind = sort.list(xi)
xi = xi[ind]
weight = weight[ind]
NDXi[nn,] = xi[NDIi[nn,]]
weighttmp[1:L[nn],nn] = weight
}
for (zz in 1:Z){
tmp = 1
for (nn in 1:N){
tmp = tmp*weighttmp[NDIi[nn,zz],nn]
NDWi[zz] = tmp
}
}
res = list(listNDXi = NDXi, listNDWi = NDWi)
return(res)
}
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