Fixed typos in example code

Author: StuartWheater

R/ds.boxPlot.R

@@ -21,7 +21,7 @@
 #'   ## Version 6, for version 5 see the Wiki
 #'   
 #'   ### Please ensure you have a training Virtual Machine running,
-#'    or that you have a live connection to a server.
+#'   # or that you have a live connection to a server.
 #'      
 #'   # Connecting to the Opal servers
 #' 

R/ds.densityGrid.R

@@ -66,11 +66,11 @@
 #'   # Example2: generate a grid density object for each study separately
 #'   ds.densityGrid(x="D$LAB_TSC",
 #'                  y="D$LAB_HDL",
-#'                  type="split"
+#'                  type="split",
 #'                  datasources = connections[1])#only the first Opal server is used ("study1")
 #'
 #'   # Example3: generate a grid density object where the number of intervals is set to 15, for
-#'               each study separately
+#'   #           each study separately
 #'   ds.densityGrid(x="D$LAB_TSC",
 #'                  y="D$LAB_HDL",
 #'                  type="split",

R/ds.heatmapPlot.R

@@ -133,7 +133,7 @@
 #'                  datasources = connections[1]) #only the first server is used (study1)
 #'                  
 #'   # Example 3: Plot a combined heat map plot using the method 'deterministic' centroids of each 
-#'   k = 7 nearest neighbours for numints = 40
+#'   # k = 7 nearest neighbours for numints = 40
 #'   ds.heatmapPlot(x = 'D$LAB_TSC',
 #'                  y = 'D$LAB_HDL', 
 #'                  numints = 40, 

R/ds.histogram.R

@@ -120,7 +120,7 @@
 #'               datasources = connections) #all studies are used
 #'
 #'   # Example 2: generate a combined histogram with the default small cells counts
-#'                suppression rule
+#'   #             suppression rule
 #'   ds.histogram(x = 'D$PM_BMI_CONTINUOUS',
 #'                method = 'smallCellsRule',
 #'                type = 'combine',

R/ds.matrixDiag.R

@@ -112,7 +112,7 @@
 #'                 datasources = connections)
 #'                 
 #'   #Example 2: Create a square matrix with the server-side scalar as all diagonal values 
-#'   and all the other values = 0
+#'   #and all the other values = 0
 #'   
 #'   #Create a scalar in the server-side
 #'   
@@ -152,7 +152,7 @@
 #'                datasources = connections)
 #'                    
 #'  #Example 4: Create a square matrix with the client-side vector as a diagonal
-#'  and all the other values = 0
+#'  #and all the other values = 0
 #'  
 #'  ds.matrixDiag(x1 = c(2,6,9,10),
 #'                aim = "clientside.vector.2.matrix",
@@ -161,7 +161,7 @@
 #'                datasources = connections)
 #'                
 #'  #Example 5: Create a square matrix with the client-side scalar as all diagonal values 
-#'  and all the other values = 0
+#'  #and all the other values = 0
 #'  
 #'  ds.matrixDiag(x1 = 4,
 #'                aim = "clientside.scalar.2.matrix",

R/ds.recodeValues.R

@@ -69,7 +69,7 @@
 #'                   values2replace.vector = c(1,2), 
 #'                   new.values.vector = c(1,2),
 #'                   missing = 99, 
-#'                   newobj = 'bmi_recoded'
+#'                   newobj = 'bmi_recoded',
 #'                   datasources = connections)
 #'                  
 #'   # Clear the Datashield R sessions and logout                 

R/ds.table2D.R

@@ -56,7 +56,7 @@
 #'   # Example 2: generate a two dimensional table, outputting study specific contingency tables
 #'   ds.table2D(x='D$DIS_DIAB', y='D$GENDER', type='split')
 #'   # display the 5 results items, one at a time to avoid having too much information displayed
-#'   at the same time
+#'   # at the same time
 #'   output$counts
 #'   output$rowPercent
 #'   output$colPercent