Can I use plotCHOIR to show the prediction accuracy scores of my pre-generated clusters?

[FY10086]

Hello, I am very interested in the CHOIR you have developed. Currently, I am trying to use plotCHOIR to show the prediction accuracy scores of my clusters, but I have encountered some issues and would like to seek your help. I have already run the code and here is the error:

tmp=select(seu@meta.data,"seurat_cluster.rpca_GSE_c5_c14_c6_c18_c21_c22_c36_sub")
cluster_labels=tmp$seurat_cluster.rpca_GSE_c5_c14_c6_c18_c21_c22_c36_sub
names(cluster_labels)=rownames(tmp)
reduction=as.matrix(seu@reductions$umap.rpca_GSE@cell.embeddings)
reduction=reduction[names(cluster_labels),]

cluster_tree=inferTree(cluster_labels, ## A named vector of cluster IDs. Names must correspond to cell IDs.
dist_matrix = NULL, ## An optional distance matrix of cell to cell distances (based on dimensionality reduction cell embeddings).
reduction = reduction, ## An optional matrix of dimensionality reduction cell embeddings to be used for distance calculations.
verbose = TRUE)

input_matrix <- as.matrix(GetAssayData(seu, assay = "RNA", slot = "data"))

seu=pruneTree(
seu,
cluster_tree = cluster_tree,
input_matrix = input_matrix,
nn_matrix = as(seu@graphs$RNA_nn, "dgCMatrix"),
snn_matrix = as(seu@graphs$RNA_snn, "dgCMatrix"),
reduction = reduction,
n_cores = 4,
verbose = TRUE
)

All the above steps have been successfully completed.

plotCHOIR(seu_sampled,
reduction = "umap.rpca_GSE",
group_by = "seurat_cluster.rpca_GSE_c5_c14_c6_c18_c21_c22_c36_sub",
accuracy_scores = TRUE,
plot_nearest = FALSE)

Error in .validInput(reduction, "reduction", list("plotCHOIR", object, : Input value 'umap.rpca_GSE' for 'reduction' was not found in the provided object, please supply valid input!
Traceback:

1. .validInput(reduction, "reduction", list("plotCHOIR", object,
   . key))
2. stop("Input value '", input, "' for '", name, "' was not found in the provided object, please supply valid input!")
3. .handleSimpleError(function (cnd)
   . {
   . watcher$capture_plot_and_output()
   . cnd <- sanitize_call(cnd)
   . watcher$push(cnd)
   . switch(on_error, continue = invokeRestart("eval_continue"),
   . stop = invokeRestart("eval_stop"), error = NULL)
   . }, "Input value 'umap.rpca_GSE' for 'reduction' was not found in the provided object, please supply valid input!",
   . base::quote(.validInput(reduction, "reduction", list("plotCHOIR",
   . object, key))))

[FY10086]

When I added the reduction embedding to seu@misc$CHOIR$reduction, I was able to plot the data. However, regarding the prediction accuracy scores, I found that what is in seu@misc$CHOIR$records is the results of the clusters after pruning from the other clustering methods I provided, obtained after running pruneTree. I hope to also display the prediction accuracy scores for each cluster before pruning to highlight the superiority of the CHOIR clustering algorithm. Is this possible?