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	Add more optimization targets
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					 2 changed files with 19 additions and 6 deletions
				
			
		
							
								
								
									
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							|  | @ -34,11 +34,14 @@ ranking <- function(results, weights) { | |||
| #' @param results Results from [analyze()] or [ranking()]. | ||||
| #' @param methods Methods to include in the score. | ||||
| #' @param reference_gene_ids IDs of the reference genes. | ||||
| #' @param target The optimization target. It may be one of "mean", "min" or | ||||
| #'   "max" and results in the respective rank being optimized. | ||||
| #' | ||||
| #' @returns Named list pairing method names with their optimal weights. | ||||
| #' | ||||
| #' @export | ||||
| optimize_weights <- function(results, methods, reference_gene_ids) { | ||||
| optimize_weights <- function(results, methods, reference_gene_ids, | ||||
|                              target = "mean") { | ||||
|     # Create the named list from the factors vector. | ||||
|     weights <- function(factors) { | ||||
|         result <- NULL | ||||
|  | @ -50,13 +53,20 @@ optimize_weights <- function(results, methods, reference_gene_ids) { | |||
|         result | ||||
|     } | ||||
| 
 | ||||
|     # Compute the mean rank of the reference genes when applying the weights. | ||||
|     mean_rank <- function(factors) { | ||||
|     # Compute the target rank of the reference genes when applying the weights. | ||||
|     target_rank <- function(factors) { | ||||
|         data <- ranking(results, weights(factors)) | ||||
|         data[gene %chin% reference_gene_ids, mean(rank)] | ||||
| 
 | ||||
|         data[gene %chin% reference_gene_ids, if (target == "min") { | ||||
|             min(rank) | ||||
|         } else if (target == "max") { | ||||
|             max(rank) | ||||
|         } else { | ||||
|             mean(rank) | ||||
|         }] | ||||
|     } | ||||
| 
 | ||||
|     factors <- stats::optim(rep(1.0, length(methods)), mean_rank)$par | ||||
|     factors <- stats::optim(rep(1.0, length(methods)), target_rank)$par | ||||
|     total_weight <- sum(factors) | ||||
| 
 | ||||
|     weights(factors / total_weight) | ||||
|  |  | |||
|  | @ -4,7 +4,7 @@ | |||
| \alias{optimize_weights} | ||||
| \title{Find the best weights to rank the results.} | ||||
| \usage{ | ||||
| optimize_weights(results, methods, reference_gene_ids) | ||||
| optimize_weights(results, methods, reference_gene_ids, target = "mean") | ||||
| } | ||||
| \arguments{ | ||||
| \item{results}{Results from \code{\link[=analyze]{analyze()}} or \code{\link[=ranking]{ranking()}}.} | ||||
|  | @ -12,6 +12,9 @@ optimize_weights(results, methods, reference_gene_ids) | |||
| \item{methods}{Methods to include in the score.} | ||||
| 
 | ||||
| \item{reference_gene_ids}{IDs of the reference genes.} | ||||
| 
 | ||||
| \item{target}{The optimization target. It may be one of "mean", "min" or | ||||
| "max" and results in the respective rank being optimized.} | ||||
| } | ||||
| \value{ | ||||
| Named list pairing method names with their optimal weights. | ||||
|  |  | |||
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