art: propagate callAgg function

R/ds.boundedCovarianceDP.R

@@ -1,3 +1,5 @@
+source("R/utils.R")
+
 #' @title Differentially private covariance
 #'
 #' @param x First input to the covariance
@@ -14,14 +16,18 @@
 #' @return \code{ds.boundedCovarianceDP} returns a differentially private covariance
 #' @export
 
-ds.boundedCovarianceDP <- function(x, y, epsilon, x_min, x_max, y_min, y_max, datasources) {
+ds.boundedCovarianceDP <- function(x, y, epsilon, x_min, x_max, y_min, y_max, type="split", datasources=NULL) {
 
   if (is.null(datasources)) {
     datasources <- DSI::datashield.connections_find()
   }
+  if (!type %in% c("both", "split", "combine")) {
+    stop("Type must be one of 'both', 'split' or 'combine'")
+  }
 
-  cally <- paste0("boundedCovarianceDP(", x, ", ", y,  ", ", epsilon, ", ", x_min, ", ", x_max, ", ", y_min, ", ", y_max, ")")
-  result <- DSI::datashield.aggregate(datasources, as.symbol(cally))
+  covariance.split <- callAggregationMethod(datasources, paste0("boundedCovarianceDP(", x, ", ", y,  ", ", epsilon, ", ", x_min, ", ", x_max, ", ", y_min, ", ", y_max, ")"))
 
-  return(result)
+  if (type == "both") stop("Combine type not implemented") 
+  if (type == "combine") stop("NotImplemented") 
+  if (type == "split") return(list(Covariance.by.Study=covariance.split,Nstudies=Nstudies))
 }

R/ds.boundedMeanDP.R

@@ -1,3 +1,5 @@
+source("R/utils.R")
+
 #' @title Differentially private mean
 #'
 #' @param input_data the input vector
@@ -24,16 +26,18 @@ ds.boundedMeanDP <- function(input_data, epsilon, lower_bound, upper_bound, type
   if (is.null(datasources)) {
     datasources <- DSI::datashield.connections_find()
   }
+  if (!type %in% c("both", "split", "combine")) {
+    stop("Type must be one of 'both', 'split' or 'combine'")
+  }
 
-  cally <- paste0("boundedMeanDP(", input_data, ", ", epsilon, ", ", lower_bound, ", ", upper_bound, ")")
-  res.obj <- DSI::datashield.aggregate(datasources, as.symbol(cally))
+  mean.data <- callAggregationMethod(datasources, paste0("boundedMeanDP(", input_data, ", ", epsilon, ", ", lower_bound, ", ", upper_bound, ")"))
 
   Nstudies <- length(datasources)
-  res.mat <- matrix(as.numeric(matrix(unlist(res.obj),nrow=Nstudies,byrow=TRUE)[,1:2]),nrow=Nstudies)
-
-  res.mat.combined <- (t(matrix(res.mat[,2]))%*%res.mat[,1])/sum(res.mat[,2])
+  mean.mat <- matrix(as.numeric(unlist(mean.data)),nrow=Nstudies,byrow=TRUE)
+  mean.split <- mean.mat[,1]
+  mean.combine <- ((t(matrix(mean.mat[,2]))%*%mean.mat[,1])/sum(mean.mat[,2]))[[1]]
 
-  if (type=="combine") return(list(Mean.by.Study=res.mat[,1],Nstudies=Nstudies))
-  if (type=="split") return(list(Global.Mean=res.mat.combined,Nstudies=Nstudies))
-  if (type=="both") return(list(Mean.by.Study=res.mat[,1],Global.Mean=res.mat.combined,Nstudies=Nstudies))
+  if (type=="combine") return(list(Global.Mean=mean.combine,Nstudies=Nstudies))
+  if (type=="split") return(list(Mean.by.Study=mean.split,Nstudies=Nstudies))
+  if (type=="both") return(list(Mean.by.Study=mean.split,Global.Mean=mean.combine,Nstudies=Nstudies))
 }

R/ds.boundedStandardDeviationDP.R

@@ -1,3 +1,5 @@
+source("R/utils.R")
+
 #' @title Differentially private standard deviation
 #'
 #' @param input_data the input vector
@@ -11,14 +13,19 @@
 #' @return \code{ds.boundedStandardDeviationDP} returns a differentially private standard deviation
 #' @export
 
-ds.boundedStandardDeviationDP <- function(input_data, epsilon, lower_bound, upper_bound, datasources=NULL) {
+ds.boundedStandardDeviationDP <- function(input_data, epsilon, lower_bound, upper_bound, type="split", datasources=NULL) {
 
   if (is.null(datasources)) {
     datasources <- DSI::datashield.connections_find()
   }
+  if (!type %in% c("both", "split", "combine")) {
+    stop("Type must be one of 'both', 'split' or 'combine'")
+  }
 
-  cally <- paste0("boundedStandardDeviationDP(", input_data, ", ", epsilon, ", ", lower_bound, ", ", upper_bound, ")")
-  result <- DSI::datashield.aggregate(datasources, as.symbol(cally))
+  standardDeviation.split <- callAggregationMethod(datasources, paste0("boundedStandardDeviationDP(", input_data, ", ", epsilon, ", ", lower_bound, ", ", upper_bound, ")"))  
 
-  return(result)
+  return(standardDeviation.split)
+  if (type=="combine") stop("NotImplemented")
+  if (type=="split") return(list(StandardDeviation.by.Study=standardDeviation.split,Nstudies=Nstudies))
+  if (type=="both") stop("Combine type not implemented")
 }

R/ds.boundedSumDP.R

@@ -1,3 +1,5 @@
+source("R/utils.R")
+
 #' @title Differentially private sum
 #'
 #' @param input_data the input vector
@@ -20,13 +22,14 @@ ds.boundedSumDP <- function(input_data, epsilon, lower_bound, upper_bound, type=
   if (is.null(datasources)) {
     datasources <- DSI::datashield.connections_find()
   }
+  if (!type %in% c("both", "split", "combine")) {
+    stop("Type must be one of 'both', 'split' or 'combine'")
+  }
 
-  cally <- paste0("boundedSumDP(", input_data, ", ", epsilon, ", ", lower_bound, ", ", upper_bound, ")")
-  res <- DSI::datashield.aggregate(datasources, as.symbol(cally))
-
-  combined <- sum(unlist(res))
+  sum.split <- callAggregationMethod(datasources, paste0("boundedSumDP(", input_data, ", ", epsilon, ", ", lower_bound, ", ", upper_bound, ")"))
+  sum.combine <- sum(unlist(sum.split))
 
-  if (type=="combine") return(list(Sum.by.Study=res))
-  if (type=="split") return(list(Global.Sum=combined))
-  if (type=="both") return(list(Sum.by.Study=res,Global.Sum=combined))
+  if (type=="combine") return(list(Global.Sum=sum.combine))
+  if (type=="split") return(list(Sum.by.Study=sum.split))
+  if (type=="both") return(list(Sum.by.Study=sum.split,Global.Sum=sum.combine))
 }

R/ds.boundedVarianceDP.R

@@ -15,7 +15,7 @@ source("R/utils.R")
 #' @return \code{ds.boundedVarianceDP} returns a differentially private covariance
 #' @export
 
-ds.boundedVarianceDP <- function(input_data, epsilon, lower_bound, upper_bound, datasources=NULL, type="combine") {
+ds.boundedVarianceDP <- function(input_data, epsilon, lower_bound, upper_bound, type="combine", datasources=NULL) {
 
   if (is.null(datasources)) {
     datasources <- DSI::datashield.connections_find()
@@ -35,13 +35,9 @@ ds.boundedVarianceDP <- function(input_data, epsilon, lower_bound, upper_bound,
   variance.combine <- computeVarCombine(Nstudies, Sum, SumSquares, Nvalid)
   variance.split <- computeVarSplit(Nstudies, Sum, SumSquares, Nvalid)
 
-  if (type == "both") {
-      return(list(Variance.by.Study=variance.split,Global.Variance=variance.combine,Nstudies=Nstudies))
-  } else if (type == "combine") {
-      return(list(Global.Variance=variance.combine,Nstudies=Nstudies))
-  } else if (type == "split") {
-      return(list(Variance.by.Study=variance.split,Nstudies=Nstudies))
-  }
+  if (type == "both") return(list(Variance.by.Study=variance.split,Global.Variance=variance.combine,Nstudies=Nstudies))
+  if (type == "combine") return(list(Global.Variance=variance.combine,Nstudies=Nstudies))
+  if (type == "split") return(list(Variance.by.Study=variance.split,Nstudies=Nstudies))
 }
 
 computeVarCombine <- function(Nstudies, Sum, SumSquares, Nvalid) {

R/ds.countDP.R

@@ -1,3 +1,5 @@
+source("R/utils.R")
+
 #' @title Differentially private count
 #'
 #' @param input_data the input vector
@@ -19,12 +21,10 @@ ds.countDP <- function(input_data, epsilon, type="combine", datasources=NULL) {
     datasources <- DSI::datashield.connections_find()
   }
 
-  cally <- paste0("countDP(", input_data, ", ", epsilon, ")")
-  res <- DSI::datashield.aggregate(datasources, as.symbol(cally))
-
-  combined <- sum(unlist(res))
+  count.split <- callAggregationMethod(datasources, paste0("countDP(", input_data, ", ", epsilon, ")"))
+  count.combine <- sum(unlist(count.split))
 
-  if (type=="combine") return(list(Count.by.Study=res))
-  if (type=="split") return(list(Global.Count=combined))
-  if (type=="both") return(list(Count.by.Study=res,Global.Count=combined))
+  if (type=="combine") return(list(Global.Count=count.combine))
+  if (type=="split") return(list(Count.by.Study=count.split))
+  if (type=="both") return(list(Count.by.Study=count.split,Global.Count=count.combine))
 }

R/ds.maxDP.R

@@ -1,3 +1,5 @@
+source("R/utils.R")
+
 #' @title Differentially private max
 #'
 #' @param input_data the input vector
@@ -20,13 +22,14 @@ ds.maxDP <- function(input_data, epsilon, lower_bound, upper_bound, type="combin
   if (is.null(datasources)) {
     datasources <- DSI::datashield.connections_find()
   }
+  if (!type %in% c("both", "split", "combine")) {
+    stop("Type must be one of 'both', 'split' or 'combine'")
+  }
 
-  cally <- paste0("maxDP(", input_data, ", ", epsilon, ", ", lower_bound, ", ", upper_bound, ")")
-  res <- DSI::datashield.aggregate(datasources, as.symbol(cally))
-
-  combined <- max(unlist(res))
+  max.split <- callAggregationMethod(datasources, paste0("maxDP(", input_data, ", ", epsilon, ", ", lower_bound, ", ", upper_bound, ")"))
+  max.combine <- max(unlist(max.split))
 
-  if (type=="combine") return(list(Max.by.Study=res))
-  if (type=="split") return(list(Global.Max=combined))
-  if (type=="both") return(list(Max.by.Study=res,Global.Max=combined))
+  if (type=="combine") return(list(Global.Max=max.combine))
+  if (type=="split") return(list(Max.by.Study=max.split))
+  if (type=="both") return(list(Max.by.Study=max.split,Global.Max=max.combine))
 }

R/ds.medianDP.R

@@ -1,3 +1,5 @@
+source("R/utils.R")
+
 #' @title Differentially private median
 #'
 #' @param input_data the input vector
@@ -11,14 +13,18 @@
 #' @return \code{ds.medianDP} returns a differentially private median
 #' @export
 
-ds.medianDP <- function(input_data, epsilon, lower_bound, upper_bound, datasources=NULL) {
+ds.medianDP <- function(input_data, epsilon, lower_bound, upper_bound, type="split", datasources=NULL) {
 
   if (is.null(datasources)) {
     datasources <- DSI::datashield.connections_find()
   }
+  if (!type %in% c("both", "split", "combine")) {
+    stop("Type must be one of 'both', 'split' or 'combine'")
+  }
 
-  cally <- paste0("medianDP(", input_data, ", ", epsilon, ", ", lower_bound, ", ", upper_bound, ")")
-  result <- DSI::datashield.aggregate(datasources, as.symbol(cally))
+  median.split <- callAggregationMethod(datasources, paste0("medianDP(", input_data, ", ", epsilon, ", ", lower_bound, ", ", upper_bound, ")"))
 
-  return(result)
+  if (type == "both") stop("Combine type not implemented") 
+  if (type == "combine") stop("NotImplemented") 
+  if (type == "split") return(list(Median.by.Study=median.split,Nstudies=Nstudies))
 }

R/ds.minDP.R

@@ -1,3 +1,5 @@
+source("R/utils.R")
+
 #' @title Differentially private min
 #'
 #' @param input_data the input vector
@@ -20,12 +22,14 @@ ds.minDP <- function(input_data, epsilon, lower_bound, upper_bound, type="combin
   if (is.null(datasources)) {
     datasources <- DSI::datashield.connections_find()
   }
+  if (!type %in% c("both", "split", "combine")) {
+    stop("Type must be one of 'both', 'split' or 'combine'")
+  }
 
-  cally <- paste0("minDP(", input_data, ", ", epsilon, ", ", lower_bound, ", ", upper_bound, ")")
-  res <- DSI::datashield.aggregate(datasources, as.symbol(cally))
-
-  combined <- min(unlist(res))
+  min.split <- callAggregationMethod(datasources, paste0("minDP(", input_data, ", ", epsilon, ", ", lower_bound, ", ", upper_bound, ")"))
+  min.combine <- min(unlist(min.split))
 
-  if (type=="combine") return(list(Min.by.Study=res))
-  if (type=="split") return(list(Global.Min=combined))
-  if (type=="both") return(list(Min.by.Study=res,Global.Min=combined))}
+  if (type=="combine") return(list(Global.Min=min.combine))
+  if (type=="split") return(list(Min.by.Study=min.split))
+  if (type=="both") return(list(Min.by.Study=min.split,Global.Min=min.combine))
+}

R/ds.studentTestDP.R

@@ -18,7 +18,7 @@ source("R/utils.R")
 #' @return \code{ds.studentTestDP} returns a differentially private student-test
 #' @export
 
-ds.studentTestDP <- function(datasources, x, y, epsilon, x_min, x_max, y_min, y_max, type="combine") {
+ds.studentTestDP <- function(x, y, epsilon, x_min, x_max, y_min, y_max, type="combine", datasources=NULL) {
     if (is.null(datasources)) {
         datasources <- DSI::datashield.connections_find()
     }
@@ -35,13 +35,9 @@ ds.studentTestDP <- function(datasources, x, y, epsilon, x_min, x_max, y_min, y_
     studentTest.combine <- computeStudentTestCombine(Nstudies, res_x, res_y)
     studentTest.split <- computeStudentTestSplit(Nstudies, res_x, res_y)
 
-    if (type == "both") {
-        return(list(StudentTest.by.Study=studentTest.split,Global.StudentTest=studentTest.combine,Nstudies=Nstudies))
-    } else if (type == "combine") {
-        return(list(Global.StudentTest=studentTest.combine,Nstudies=Nstudies))
-    } else if (type == "split") {
-        return(list(StudentTest.by.Study=studentTest.split,Nstudies=Nstudies))
-    }
+    if (type == "both") return(list(StudentTest.by.Study=studentTest.split,Global.StudentTest=studentTest.combine,Nstudies=Nstudies))
+    if (type == "combine") return(list(Global.StudentTest=studentTest.combine,Nstudies=Nstudies))
+    if (type == "split") return(list(StudentTest.by.Study=studentTest.split,Nstudies=Nstudies))
 }
 
 computeGlobalStats <- function(Nstudies, input) {