fix issue 12

NAMESPACE

@@ -22,6 +22,7 @@ importFrom(Spectra,filterDataOrigin)
 importFrom(Spectra,filterEmptySpectra)
 importFrom(Spectra,filterMzRange)
 importFrom(Spectra,filterRt)
+importFrom(Spectra,isEmpty)
 importFrom(dplyr,first)
 importFrom(dplyr,group_by)
 importFrom(dplyr,select)

R/checkScans.R

@@ -1,8 +1,9 @@
 #' Check if any samples are missing spectra
 #'
-#' @param spectra `Spectra` object 
+#' @param spectra `Spectra` object
 #'
 #' @importFrom ProtGenerics dataOrigin
+#' @importFrom Spectra isEmpty
 #' @return
 #' @export
 #'
@@ -16,4 +17,4 @@ checkScans <- function(spectra){
     stop(paste("File",names,"contains less than 50% of the mean of scans
                    in the samples."))
   }
-}
+}

R/peaks_with_tardis.R

@@ -892,42 +892,42 @@ tardis_peaks <-
 
       results <- results_samples
 
-      if(is.null(max_int_filter) == FALSE ){
+      if(is.null(max_int_filter) == FALSE && max_int_filter != 0){
         results <- results[which(results$MaxInt >= max_int_filter),]
       }
 
       #AUC, int, SNR & peakcor tables for each component peak in every sample
 
       auc_table <- results %>%
         select(Component, Sample, AUC) %>%
-        spread(Sample, AUC)
+        spread(Sample, AUC, fill = NA, drop = FALSE)
 
       write.csv(auc_table, file = paste0(output_directory, "auc_table.csv"))
 
 
       pop_table <- results %>%
         select(Component, Sample, pop) %>%
-        spread(Sample, pop)
+        spread(Sample, pop, fill = NA, drop = FALSE)
 
       write.csv(pop_table, file = paste0(output_directory, "pop_table.csv"))
 
 
       SNR_table <- results %>%
         select(Component, Sample, SNR) %>%
-        spread(Sample, SNR)
+        spread(Sample, SNR, fill = NA, drop = FALSE)
 
       write.csv(SNR_table, file = paste0(output_directory, "snr_table.csv"))
 
       int_table <- results %>%
         select(Component, Sample, MaxInt) %>%
-        spread(Sample, MaxInt)
+        spread(Sample, MaxInt, fill = NA, drop = FALSE)
 
       write.csv(int_table, file = paste0(output_directory, "int_table.csv"))
 
 
       peakcor_table <- results %>%
         select(Component, Sample, peak_cor) %>%
-        spread(Sample, peak_cor)
+        spread(Sample, peak_cor, fill = NA, drop = FALSE)
 
       write.csv(peakcor_table, file = paste0(output_directory, "peakcor_table.csv"))