Add align pow

R/align_pow-GCIMSDataset.R

@@ -0,0 +1,32 @@
+align_pow <- function(x,
+                      lambdas = pracma::logspace(-2, 4, 31),
+                      p = 10,
+                      max_it = 1000){
+  rics <- x$getRIC()
+  idx_y <- Align::select_reference(rics)
+  X <- as.matrix(rics[-idx_y,])
+  y <- as.matrix(rics[idx_y,])
+  n_samples <- nrow(X)
+  m <- length(y)
+  v <- rep(1,m)
+  iv <- seq(2, m - 1, by = p)
+  v[iv] <- 0
+  W <- Matrix::Diagonal(x = v)
+  val<-Align::compute_val_error(X,y,W,iv,lambdas)
+  opar <- Align::optimize_params(n_samples, lambdas, val$ti_ix, val$e_ix)
+  best_lambdas2 <- opar$best_params
+
+  w<-mapply(Align::pow,x=as.list(data.frame(t(X))), lambda2=as.list(best_lambdas2),MoreArgs = list(y=y,max_it = max_it))
+  w<-as.list((as.data.frame(w)))
+  w<-append(w,list(1:m),idx_y-1)
+  names(w)<-x$sampleNames
+
+  delayed_op <- DelayedOperation(
+    name = "align_pow",
+    fun = align_pow_sample,
+    params_iter = list(w=w)
+  )
+  x$appendDelayedOp(delayed_op)
+  x <- GCIMS:::extract_RIC_and_TIS(x)
+  invisible(x)
+}

R/align_pow-GCIMSSample.R

@@ -0,0 +1,8 @@
+align_pow_sample <- function(x,w){
+  int <- GCIMS::intensity(x)
+  inter <- t(apply(int, 1, Align::interpolation, w = w, return = FALSE))
+  sel <- !is.na(inter[1,])
+  x@retention_time <- x@retention_time[sel]
+  x@data <- inter[,sel]
+  return(x)
+}