Merge pull request #340 from lorenalves/master

Hotfix bug in neuron labelling
e-sensing · Aug 16, 2021 · 9b3f842 · 9b3f842
2 parents 4f229b7 + e0485b1
commit 9b3f842
Show file tree

Hide file tree

Showing 2 changed files with 30 additions and 9 deletions.
diff --git a/R/sits_plot.R b/R/sits_plot.R
@@ -919,13 +919,15 @@ plot.keras_model <- function(x, y, ...) {
     if (type == "mapping") {
         graphics::plot(koh$som_properties,
                        bgcol = koh$som_properties$paint_map,
-                       "mapping", whatmap = whatmap
+                       "mapping", whatmap = whatmap,
+                       codeRendering = "lines"
         )
     }
     else if (type == "codes") {
         graphics::plot(koh$som_properties,
                        bgcol = koh$som_properties$paint_map,
-                       "codes", whatmap = whatmap
+                       "codes", whatmap = whatmap,
+                       codeRendering = "lines"
         )
     }
 

diff --git a/R/sits_som.R b/R/sits_som.R
@@ -184,13 +184,32 @@ sits_som_map <- function(data,
                                            id_neuron == neuron_id
             )
 
-            # if more than one sample has been mapped, the a posteriori
-            # probability is considered
-            if (nrow(labels_neuron) > 1)
-                label_max <- nnet::which.is.max(labels_neuron$post_prob)
-            else
-                label_max <- nnet::which.is.max(labels_neuron$prior_prob)
-            return(labels_neuron[label_max, ]$label_samples)
+            #Get the maximum value of the prior probability
+            max_prob_index <- which.max(labels_neuron$prior_prob)
+            prob_max <- labels_neuron[max_prob_index, ]$prior_prob
+
+            #How many elements there are with the maximumn value?
+            number_of_label_max <- which(labels_neuron$prior_prob == prob_max )
+            label_max_final <- nnet::which.is.max(labels_neuron$prior_prob)
+
+
+            # if more than one sample has been mapped AND their max are the same,
+            # then a posteriori probability is considered
+            if (length(number_of_label_max) > 1)
+            {
+                #Get the maximum posterior among the tied classes
+                max_post <- max(labels_neuron[number_of_label_max, ]$post_prob)
+
+                # Where are the duplicated values?
+                label_max_post <- which(labels_neuron$post_prob == max_post )
+
+                #Is this value are in the maximum vector of the prior probability?
+                index_prior_max <- which(label_max_post %in% number_of_label_max == TRUE)
+                label_max_final <- label_max_post[index_prior_max]
+            }else
+                label_max_final <- nnet::which.is.max(labels_neuron$prior_prob)
+
+            return(labels_neuron[label_max_final, ]$label_samples)
         })
     labels_max <- unlist(lab_max)