seems to be working on extended example cases too

R/match_spec.R

@@ -12,7 +12,7 @@
 #' \code{max_cor_named()} formats the top correlation values from a correlation
 #' matrix as a named vector.
 #' \code{filter_spec()} filters an Open Specy object.
-#' \code{os_similarity()} EXPERIMENTAL, returns a single similarity metric between two OpenSpecy objects based on the method. 
+#' \code{os_similarity()} EXPERIMENTAL, returns a single similarity metric between two OpenSpecy objects based on the method used. 
 #' @param x an \code{OpenSpecy} object, typically with unknowns.
 #' @param conform Whether to conform the spectra to the library wavenumbers or not.
 #' @param type the type of conformation to make returned by \code{conform_spec()}
@@ -55,7 +55,19 @@
 #' \code{cor_spec()} returns a correlation matrix.
 #' \code{get_metadata()} returns a \code{\link[data.table]{data.table-class}()}
 #' with the metadata for columns which have information.
-#' \code{os_similarity()} returns a single numeric value representing the type of similarity metric requested.
+#' \code{os_similarity()} returns a single numeric value representing the type 
+#' of similarity metric requested. 'wavenumber' similarity is based on the 
+#' proportion of wavenumber values that overlap between the two objects, 
+#' 'metadata' is the proportion of metadata column names, 
+#' 'hamming' is something similar to the hamming distance where we discretize 
+#' all spectra in the OpenSpecy object by wavenumber intensity values and then 
+#' relate the wavenumber intensity value distributions by mean difference in 
+#' min-max normalized space. 'pca' tests the distance between the OpenSpecy 
+#' objects in PCA space using the first 4 component values and calculating the 
+#' max-range normalized distance between the mean components. The first two
+#' metrics are pretty straightforward and definitely ready to go, the 'hamming'
+#' and 'pca' metrics are pretty experimental but appear to be working under our
+#' current test cases. 
 #'
 #' @examples
 #' data("test_lib")
@@ -392,6 +404,12 @@ os_similarity.OpenSpecy <- function(x, y, method = "hamming", na.rm = T, ...) {
                                  collapse = " ")),
                     call. = F)
 
+        if(ncol(x$spectra) + ncol(y$spectra) < 8 & method == "pca")
+            stop("There must be at least 8 spectra total combined from the two Open Specy objects",
+                 "to conduct the pca analysis. Consider using the hamming distance if you want a multispectra-metric", 
+                 "with fewer spectra.",
+                 call. = F)
+
         spec_y <- y$spectra[y$wavenumber %in% x$wavenumber, ]
         spec_y <- spec_y[, lapply(.SD, make_rel, na.rm = na.rm)]
         spec_y <- spec_y[, lapply(.SD, mean_replace)]
@@ -401,6 +419,7 @@ os_similarity.OpenSpecy <- function(x, y, method = "hamming", na.rm = T, ...) {
 
     }
     if(method == "pca"){
+
         perform_combined_pca <- function(spec_obj1, spec_obj2) {
             # Extract intensities and transpose
             intensities1 <- t(spec_obj1)

tests/testthat/test-match_spec.R

@@ -7,6 +7,8 @@ data("raman_hdpe")
 
 CA_test_lib <- filter_spec(test_lib, test_lib$metadata$SpectrumIdentity == "CA" )
 
+hdpe_test_lib <- filter_spec(test_lib, test_lib$metadata$sample_name == "0031bb13faea1e04b52ffbeca009e8ab")
+
 tiny_map <- read_extdata("CA_tiny_map.zip") |>
   read_any() |>
   conform_spec(range = test_lib$wavenumber,
@@ -34,8 +36,18 @@ test_that("os_similarity() returns correct values", {
 
     CA2 <- conform_spec(CA_test_lib, tiny_map$wavenumber, res = NULL, type = "roll") 
 
+    hdpe2 <- conform_spec(hdpe_test_lib, tiny_map$wavenumber, res = NULL, type = "roll") 
+
     unknown2 <- conform_spec(unknown, tiny_map$wavenumber, res = NULL, type = "roll") 
 
+    ramanhdpe2 <- conform_spec(raman_hdpe, tiny_map$wavenumber, res = NULL, type = "roll") |>
+        smooth_intens()
+
+    #hamming still calculates a value for single spectra comparisons but probably not a great metric. 
+    expect_true(os_similarity(ramanhdpe2, hdpe2) > os_similarity(ramanhdpe2,CA2)) |> expect_warning() |> expect_warning()
+
+    os_similarity(ramanhdpe2, hdpe2, method = "pca") |> expect_error() |> expect_warning()
+
     expect_true(os_similarity(test_lib2, test_lib2) > os_similarity(tiny_map, test_lib2))
     expect_true(os_similarity(tiny_map, CA2) > os_similarity(tiny_map, unknown2)) |> expect_warning()
     expect_true(os_similarity(tiny_map, CA2, method = "pca") > os_similarity(x = tiny_map, y = unknown2, method = "pca")) |> expect_warning()