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Handle caching

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This commit is contained in:
Elias Projahn 2021-10-21 17:25:44 +02:00
parent b8365e0efb
commit df6e23d219
7 changed files with 247 additions and 191 deletions
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39
R/clusteriness.R
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@ -37,28 +37,33 @@ clusteriness_priv <- function(data, height = 1000000) {
# Process genes clustering their distance to telomeres.
clusteriness <- function(preset, progress = NULL) {
results <- data.table(gene = preset$gene_ids)
species_ids <- preset$species_ids
gene_ids <- preset$gene_ids
# Prefilter the input data by species.
distances <- geposan::distances[species %chin% preset$species_ids]
cached("clusteriness", c(species_ids, gene_ids), {
results <- data.table(gene = gene_ids)
# Add an index for quickly accessing data per gene.
setkey(distances, gene)
# Prefilter the input data by species.
distances <- geposan::distances[species %chin% species_ids]
genes_done <- 0
genes_total <- length(preset$gene_ids)
# Add an index for quickly accessing data per gene.
setkey(distances, gene)
# Perform the cluster analysis for one gene.
compute <- function(gene_id) {
score <- clusteriness_priv(distances[gene_id, distance])
genes_done <- 0
genes_total <- length(gene_ids)
if (!is.null(progress)) {
genes_done <<- genes_done + 1
progress(genes_done / genes_total)
# Perform the cluster analysis for one gene.
compute <- function(gene_id) {
score <- clusteriness_priv(distances[gene_id, distance])
if (!is.null(progress)) {
genes_done <<- genes_done + 1
progress(genes_done / genes_total)
}
score
}
score
}
results[, score := compute(gene), by = 1:nrow(results)]
results[, score := compute(gene), by = 1:nrow(results)]
})
}