diff --git a/R/data-model.R b/R/data-model.R
index b85f2c3250bd9c17293faeffdb1b26d8bbb5de2e..dd5b1cf978cf38e399a78aba508ceb2a4db24f2b 100644
--- a/R/data-model.R
+++ b/R/data-model.R
@@ -95,7 +95,9 @@ make_db_precursors <- function(m) {
by=precid]
setindex(masses,isocoarse,precid)
## Add files.
- filetab = m$input$tab$mzml[m$db$cat,.(catid=i.catid,file=file),on=c("set","tag"),nomatch=NULL]
+ filetab = m$input$tab$mzml[m$db$cat,
+ .(catid=i.catid,file=file),
+ on=c("set","tag"),nomatch=NULL]
masses[filetab,file:=i.file,on="catid"]
m$db$precursors = masses
m
diff --git a/R/plotting.R b/R/plotting.R
index 2b83e5684389fa0376375d3638ed8f815050f90d..9a65c9e010593f2938181fbb3fa2758ee32ecbcc 100644
--- a/R/plotting.R
+++ b/R/plotting.R
@@ -194,11 +194,23 @@ mk_logic_exp <- function(rest,sofar=NULL) {
}
-get_data_from_key <- function(tab,key) {
- skey <- mk_logic_exp(key)
- tab <- eval(bquote(tab[.(skey)]))
- setkeyv(tab,names(key))
- tab
+get_data_from_key <- function(db,tab,kvals,outcols) {
+
+ ## Ensure only names that exist in cat are used in selection. Or,
+ ## should we not do this?
+ valid_names = intersect(names(kvals),colnames(db$cat))
+
+ ## Turn list into a data.table.
+ dt = as.data.table(kvals[valid_names])
+
+ ## Get catids.
+ cattab = db$cat[dt,on=valid_names]
+
+ ## Get precids.
+ mztab = db$precursors[cattab,on="catid"]
+ outnames = c(valid_names,outcols)
+ tab[mztab,on="precid"][,..outnames]
+
}
@@ -270,12 +282,15 @@ get_data_4_eic_ms1 <- function(db,extr_ms1,summ_rows,kvals,labs) {
## Which of the selected keys are in the extr_ms1? This can be
## made more obvious to the user, but note necessary atm.
- keys <- names(kvals)
- actual_key <- intersect(keys,names(extr_ms1))
- actual_kvals <- kvals[actual_key]
+ keys = names(kvals)
+ actual_key = intersect(keys,names(extr_ms1))
+ actual_kvals = kvals[actual_key]
browser()
## Subset extr_ms1 by the actual key.
- tab <-get_data_from_key(tab=extr_ms1,key=actual_kvals)
+ tab = get_data_from_key(db=db,
+ tab=extr_ms1,
+ kvals=kvals,
+ outcols = c("mz","rt","intensity"))
## Group the plot data per label group (ie tags, or adducts, or
## both).
@@ -295,8 +310,8 @@ get_data_4_eic_ms1 <- function(db,extr_ms1,summ_rows,kvals,labs) {
}
## Prepare MS2 eic data: rt and intensity + key made of splitby.
-get_data_4_eic_ms2 <- function(summ,kvals,labs) {
- tab <-get_data_from_key(tab=summ,key=kvals)
+get_data_4_eic_ms2 <- function(db,summ,kvals,labs) {
+ tab = get_data_from_key(db=db,tab=summ,kvals=kvals,outcols=names(kvals))
nms <- names(kvals)
byby <- unique(c(nms,labs,"scan"))
pdata <- tab[,.(intensity=ms2_int,rt=ms2_rt),by=byby]
@@ -308,18 +323,27 @@ get_data_4_eic_ms2 <- function(summ,kvals,labs) {
}
-get_rows_from_summ <- function(summ,kvals,...) {
- summ_rows_cols <- union(names(kvals),c(...))
- get_data_from_key(summ,key=kvals)[,unique(.SD),.SDcol=summ_rows_cols]
-}
-
-narrow_summ <- function(summ,kvals,labs,...) {
- keys <- names(kvals)
- ## keys <- keys[!is.na(keys)]
- needed <- setdiff(labs,keys)
- x <- as.list(c(needed,...))
- x <- c(list(summ,kvals),x)
- do.call(get_rows_from_summ,x)
+## get_rows_from_summ <- function(db,summ,kvals,...) {
+## summ_rows_cols <- union(names(kvals),c(...))
+## get_data_from_key(db=db,tab=summ,kvals=kvals)[,unique(.SD),.SDcol=summ_rows_cols]
+## }
+
+narrow_summ <- function(db,summ,kvals,labs,...) {
+ keys = names(kvals)
+ nms = union(names(kvals),
+ labs)
+ nms = union(nms,c(...))
+ nsumm = get_data_from_key(db=db,
+ tab=summ,
+ kvals=kvals,
+ outcols=nms)
+ ## ## keys <- keys[!is.na(keys)]
+ ## needed <- setdiff(labs,keys)
+ ## x <- as.list(c(needed,...))
+
+ ## x <- c(list(db=db,tab=summ,kvals=kvals),x)
+ ## do.call(get_rows_from_summ,x)
+ nsumm
}
@@ -329,13 +353,14 @@ make_eic_ms1_plot <- function(db,extr_ms1,summ,kvals,labs,axis="linear",rt_range
## If nothing selected, just return NULL.
if (is.null(kvals)) return(NULL)
- key <- names(kvals)
+ key = names(kvals)
## Get metadata.
## TODO: FIXME: Somehow calculating representationve ms1_rt for
## plots is wrong. Horrible and wrong. Will remove those labels
## until we fix.
- summ_rows <- narrow_summ(summ,kvals,labs,"mz","ms1_rt","ms1_int","Name","SMILES","qa_ms1_exists","scan","ms2_sel")
+ summ_rows = narrow_summ(db=db,summ,kvals,labs,"mz","ms1_rt","ms1_int","Name","SMILES","qa_ms1_exists","scan","ms2_sel")
+ browser()
rows_key <- union(data.table::key(summ_rows),labs)
summ_rows$sel_ms1_rt=NA_real_
summ_rows[ms2_sel==T,sel_ms1_rt:=ms1_rt[which.max(ms1_int)],by=rows_key]
@@ -387,7 +412,7 @@ make_eic_ms2_plot <- function(summ,kvals,labs,axis="linear",rt_range=NULL,asp=1,
if (is.null(kvals)) return(NULL)
## Get metadata.
- summ_rows <- narrow_summ(summ,kvals,labs,"mz","ms2_rt","ms2_int","Name","SMILES")
+ summ_rows <- narrow_summ(db=db,summ,kvals,labs,"mz","ms2_rt","ms2_int","Name","SMILES")
## Get plotting data for the compound.
pdata <- get_data_4_eic_ms2(summ,
@@ -423,15 +448,19 @@ make_eic_ms2_plot <- function(summ,kvals,labs,axis="linear",rt_range=NULL,asp=1,
}
-make_spec_ms2_plot <- function(extr_ms2,summ,kvals,labs,axis="linear",asp=1, colrdata=NULL) {
+make_spec_ms2_plot <- function(db,extr_ms2,summ,kvals,labs,axis="linear",asp=1, colrdata=NULL) {
## Only the chosen ones.
- mdata <- get_data_from_key(summ,key=kvals)[ms2_sel==T]
+ mdata = get_data_from_key(db=db,
+ tab=summ,
+ kvals=kvals,
+ outcols=union(names(kvals),
+ colnames(summ)))[ms2_sel==T]
common_key <- intersect(names(extr_ms2),names(kvals))
common_vals <- kvals[common_key]
if (length(common_key) == 0L) return(NULL)
- subxdata <- get_data_from_key(extr_ms2,key=common_vals)
+ subxdata <- get_data_from_key(db=db,tab=extr_ms2,kvals=common_vals)
if (NROW(mdata)==0L) return(NULL)
if (NROW(subxdata) == 0L) return(NULL)
ans <- data.table(scan=mdata[,unique(scan)],key="scan")