fix logging

OHDSI · Jan 17, 2025 · 77d961a · 77d961a
1 parent aa88866
commit 77d961a
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Showing 3 changed files with 7 additions and 7 deletions.
diff --git a/R/Imputation.R b/R/Imputation.R
@@ -100,7 +100,7 @@ simpleImpute <- function(trainData, featureEngineeringSettings, done = FALSE) {
   start <- Sys.time()
   if (!done) {
     ParallelLogger::logInfo("Imputing missing values with simpleImputer using: ",
-      featureEngineeringSettings$method, "and missing threshold: ",
+      featureEngineeringSettings$method, " and missing threshold: ",
       featureEngineeringSettings$missingThreshold)
     outputData <- list(
       labels = trainData$labels,
@@ -177,7 +177,7 @@ simpleImpute <- function(trainData, featureEngineeringSettings, done = FALSE) {
     done <- TRUE
   } else {
     ParallelLogger::logInfo("Applying imputation to test data with simpleImputer
-      using method: ", featureEngineeringSettings$method, "and missing threshold: ",
+      using method: ", featureEngineeringSettings$method, " and missing threshold: ",
       featureEngineeringSettings$missingThreshold)
     outputData <- list(
       labels = trainData$labels,
@@ -315,7 +315,7 @@ iterativeImpute <- function(trainData, featureEngineeringSettings, done = FALSE)
     done <- TRUE
   } else {
     ParallelLogger::logInfo("Applying imputation to test data with iterativeImputer
-      using method: ", featureEngineeringSettings$method, "and missing threshold: ",
+      using method: ", featureEngineeringSettings$method, " and missing threshold: ",
       featureEngineeringSettings$missingThreshold)
     outputData <- list(
       labels = trainData$labels,
@@ -336,7 +336,7 @@ iterativeImpute <- function(trainData, featureEngineeringSettings, done = FALSE)
         by = "analysisId"
       ) %>%
       dplyr::mutate(isBinary = .data$isBinary == "Y") %>%
-      dplyr::select(.data$covariateId, .data$isBinary) %>%
+      dplyr::select("covariateId", "isBinary") %>%
       dplyr::compute()
     on.exit(outputData$covariateData$covariateIsBinary <- NULL, add = TRUE)
     outputData$covariateData$covariates <- outputData$covariateData$covariates %>%

diff --git a/R/ParamChecks.R b/R/ParamChecks.R
@@ -84,7 +84,7 @@ checkIsClass <- function(parameter, classes) {
 checkInStringVector <- function(parameter, values) {
   name <- deparse(substitute(parameter))
   if (!parameter %in% values) {
-    ParallelLogger::logError(paste0(name, " should be ", paste0(as.character(values), collapse = "or ")))
+    ParallelLogger::logError(paste0(name, " should be ", paste0(as.character(values), collapse = " or ")))
     stop(paste0(name, " has incorrect value"))
   }
   return(TRUE)

diff --git a/tests/testthat/test-featureEngineering.R b/tests/testthat/test-featureEngineering.R
@@ -355,7 +355,7 @@ test_that("normalization works", {
   testNormData <- addFeature(testData, 12101, -10, 10)
   metaData <- attr(normalizedData$covariateData, "metaData")
   testSettings <- metaData$featureEngineering$minMaxNormalize$settings$featureEngineeringSettings
-  testNormalizedData <- minMaxNormalize(testNormData, testSettings, normalized = TRUE)
+  testNormalizedData <- minMaxNormalize(testNormData, testSettings, done = TRUE)
 
   feature <- normalizedData$covariateData$covariates %>%
     dplyr::filter(.data$covariateId == 12101) %>%
@@ -375,7 +375,7 @@ test_that("normalization works", {
   newTrainData <- robustNormalize(data, normalizer)
   metaData <- attr(newTrainData$covariateData, "metaData")
   testSettings <- metaData$featureEngineering$robustNormalize$settings$featureEngineeringSettings
-  newTestData <- robustNormalize(testNormData, testSettings, normalized = TRUE)
+  newTestData <- robustNormalize(testNormData, testSettings, done = TRUE)
   feature <- newTrainData$covariateData$covariates %>%
     dplyr::filter(.data$covariateId == 12101) %>%
     dplyr::pull(.data$covariateValue)