fix param vs modelSettings input to fitFunctions

OHDSI · Aug 17, 2022 · 628d07b · 628d07b
1 parent 4874f1f
commit 628d07b
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Showing 6 changed files with 13 additions and 10 deletions.
diff --git a/R/DeepNNTorch.R b/R/DeepNNTorch.R
@@ -62,13 +62,13 @@ setDeepNNTorch <- function(
 
 #' Fits a deep neural network
 #' @param trainData     Training data object
-#' @param param         Hyperparameters to search over
+#' @param modelSettings modelSettings object
 #' @param search        Which kind of search strategy to use
 #' @param analysisId    Analysis Id
 #' @export
 fitDeepNNTorch <- function(
   trainData,
-  param, 
+  modelSettings, 
   search='grid', 
   analysisId)
   {
@@ -80,6 +80,7 @@ fitDeepNNTorch <- function(
     stop('DeepNNTorch requires correct covariateData')
   }
 
+  param <- modelSettings$param
   # get the settings from the param
   settings <- attr(param, 'settings')
 

diff --git a/R/Estimator.R b/R/Estimator.R
@@ -22,14 +22,14 @@
 #' fits a deep learning estimator to data.
 #' 
 #' @param trainData      the data to use
-#' @param param          model parameters
+#' @param modelSettings  modelSettings object
 #' @param analysisId     Id of the analysis
 #' @param ...            Extra inputs
 #'
 #' @export
 fitEstimator <- function(
   trainData, 
-  param, 
+  modelSettings, 
   analysisId,
   ...
 ) {
@@ -39,6 +39,8 @@ fitEstimator <- function(
   # check covariate data
   if(!FeatureExtraction::isCovariateData(trainData$covariateData)){stop("Needs correct covariateData")}
 
+  param <- modelSettings$param
+
   # get the settings from the param
   settings <- attr(param, 'settings')
   if(!is.null(trainData$folds)){

diff --git a/man/fitDeepNNTorch.Rd b/man/fitDeepNNTorch.Rd
diff --git a/man/fitEstimator.Rd b/man/fitEstimator.Rd
diff --git a/tests/testthat/test-Estimator.R b/tests/testthat/test-Estimator.R
@@ -102,7 +102,7 @@ modelSettings <- setResNet(numLayers=1, sizeHidden=16, hiddenFactor=1,
                            randomSample = 1, epochs=1)
 
 sink(nullfile())  
-results <- fitEstimator(trainData$Train, param = modelSettings$param, analysisId = 1)
+results <- fitEstimator(trainData$Train, modelSettings = modelSettings, analysisId = 1)
 sink()
 
 test_that('Estimator fit function works', {

diff --git a/tests/testthat/test-Transformer.R b/tests/testthat/test-Transformer.R
@@ -12,7 +12,7 @@ test_that('Transformer settings work', {
 
 test_that('fitEstimator with Transformer works', {
 
-  results <- fitEstimator(trainData$Train, settings$param, analysisId=1)
+  results <- fitEstimator(trainData$Train, settings, analysisId=1)
 
   expect_equal(class(results), 'plpModel')
   expect_equal(attr(results, 'modelType'), 'binary')