datashield · OllyButters · Aug 14, 2019 · Aug 13, 2019 · Aug 14, 2019 · Aug 14, 2019
diff --git a/NAMESPACE b/NAMESPACE
@@ -19,9 +19,9 @@ export(ds.contourPlot)
 export(ds.cor)
 export(ds.corTest)
 export(ds.cov)
+export(ds.dataFrame)
 export(ds.dataFrameSort)
 export(ds.dataFrameSubset)
-export(ds.dataframe)
 export(ds.densityGrid)
 export(ds.dim)
 export(ds.exists)

diff --git a/R/ds.cbind.R b/R/ds.cbind.R
@@ -5,7 +5,7 @@
 #' is combined column by column to produce a matrix written to the
 #' which is written to the serverside. For more details see 
 #' the native R function {cbind}. The handling of argument <x>
-#' is the same as for {ds.dataframe}
+#' is the same as for {ds.dataFrame}
 #' @param x This is a vector of character strings representing the names of the elemental
 #' components to be combined  For example, the call:
 #' ds.cbind(x=c('DF_input','matrix.m','var_age'),newobj='cbind_output') will

diff --git a/R/ds.dataframe.R → R/ds.dataFrame.R b/R/ds.dataframe.R → R/ds.dataFrame.R
@@ -1,26 +1,26 @@
 #' 
-#' @title ds.dataframe calling dataframeDS
+#' @title ds.dataFrame calling dataframeDS
 #' @description Creates a data frame from its elemental components: pre-existing data frames;
 #' single variables; matrices
 #' @details A data frame is a list of variables all with the same number of rows with unique row
-#' names, which is of class 'data.frame'. ds.dataframe will create a data frame by combining
+#' names, which is of class 'data.frame'. ds.dataFrame will create a data frame by combining
 #' a series of elemental components which may be pre-existing data.frames, matrices or variables.
 #' A critical requirement is that the length of all component variables, and the
 #' number of rows of the component data.frames or matrices must all be the same. The output
-#' data.frame will then have this same number of rows. ds.dataframe calls the serverside
+#' data.frame will then have this same number of rows. ds.dataFrame calls the serverside
 #' function dataframeDS which is almost the same as the native R function data.frame()
 #' and so several of the arguments are precisely the same as for data.frame() 
 #' @param x This is a vector of character strings representing the names of the elemental
 #' components to be combined. For example, the call:
-#' ds.dataframe(x=c('DF_input','matrix.m','var_age'),newobj='DF_output') will
+#' ds.dataFrame(x=c('DF_input','matrix.m','var_age'),newobj='DF_output') will
 #' combine a pre-existing data.frame called DF_input with a matrix and a variable
 #' called var_age. The output will be the combined data.frame DF_output. As many
 #' elemental components as needed may be combined in any order e.g. 3 data.frames,
 #' 7 variables and 2 matrices. For convenience the x argument can alternatively
 #' be specified in a two step procedure, the first being a call to
 #' the native R environment on the client server:
 #' x.components<-c('DF_input1','matrix.m','DF_input2', 'var_age'); 
-#' ds.dataframe(x=x.components,newobj='DF_output')
+#' ds.dataFrame(x=x.components,newobj='DF_output')
 #' @param row.names	NULL or a single integer or character string specifying a
 #' column to be used as row names, or a character or integer vector giving the
 #' row names for the data frame.
@@ -32,7 +32,7 @@
 #' If necessary they are adjusted (by make.names) so that they are.
 #' As a slight modification to the standard data.frame() function in native
 #' R, if any column names are duplicated, the second and subsequent
-#' occurances are given the suffixes .1, .2 etc by ds.dataframe and so
+#' occurances are given the suffixes .1, .2 etc by ds.dataFrame and so
 #' there are never any duplicates when check.names is invoked by the
 #' serverside function dataframeDS
 #' @param stringsAsFactors logical: should character vectors be converted
@@ -61,7 +61,7 @@
 #' indicating whether <newobj> has been created in each data source and if so whether
 #' it is in a valid form. If its form is not valid in at least one study - e.g. because
 #' a disclosure trap was tripped and creation of the full output object was blocked -
-#' ds.dataframe() also returns any studysideMessages that can explain the error in creating
+#' ds.dataFrame() also returns any studysideMessages that can explain the error in creating
 #' the full output object. As well as appearing on the screen at run time,if you wish to
 #' see the relevant studysideMessages at a later date you can use the {ds.message}
 #' function. If you type ds.message("newobj") it will print out the relevant
@@ -71,7 +71,7 @@
 #' will return the message: "ALL OK: there are no studysideMessage(s) on this datasource".
 #' @author DataSHIELD Development Team
 #' @export
-ds.dataframe<-function(x=NULL,row.names=NULL,check.rows=FALSE,check.names=TRUE,stringsAsFactors=TRUE,completeCases=FALSE,DataSHIELD.checks=FALSE,newobj='df_new',datasources=NULL,notify.of.progress=FALSE){
+ds.dataFrame<-function(x=NULL,row.names=NULL,check.rows=FALSE,check.names=TRUE,stringsAsFactors=TRUE,completeCases=FALSE,DataSHIELD.checks=FALSE,newobj='df_new',datasources=NULL,notify.of.progress=FALSE){
 
   # if no opal login details are provided look for 'opal' objects in the environment
   if(is.null(datasources)){
@@ -285,5 +285,5 @@ if(!no.errors){																								#
 #############################################################################################################
 
 }
-#ds.dataframe
+#ds.dataFrame
 
diff --git a/R/ds.dim.R b/R/ds.dim.R
@@ -17,7 +17,7 @@
 #' these objects hold also the data assign to R, as \code{dataframe}, from opal datasources.
 #' @return for an array, \code{NULL} or a vector of mode \code{integer}
 #' @author Amadou Gaye, Julia Isaeva, Demetris Avraam, for DataSHIELD Development Team
-#' @seealso \link{ds.dataframe} to generate a table of type dataframe.
+#' @seealso \link{ds.dataFrame} to generate a table of type dataframe.
 #' @seealso \link{ds.changeRefGroup} to change the reference level of a factor.
 #' @seealso \link{ds.colnames} to obtain the column names of a matrix or a data frame
 #' @seealso \link{ds.asMatrix} to coerce an object into a matrix type.

diff --git a/R/ds.rbind.R b/R/ds.rbind.R
@@ -5,7 +5,7 @@
 #' is combined row by row to produce a matrix
 #' which is written to the serverside. For more details see 
 #' the native R function {rbind}. The handling of argument <x>
-#' is similar to that of functions {ds.cbind} and {ds.dataframe}
+#' is similar to that of functions {ds.cbind} and {ds.dataFrame}
 #' @param x This is a vector of character strings representing the names of the elemental
 #' components to be combined.  For example, the call:
 #' ds.rbind(x=c('matrix.m','matrix.n'),newobj='rbind_output') will

diff --git a/R/ds.reShape.R b/R/ds.reShape.R
@@ -61,7 +61,7 @@
 #' indicating whether <newobj> has been created in each data source and if so whether
 #' it is in a valid form. If its form is not valid in at least one study - e.g. because
 #' a disclosure trap was tripped and creation of the full output object was blocked -
-#' ds.dataframe() also returns any studysideMessages that can explain the error in creating
+#' ds.dataFrame() also returns any studysideMessages that can explain the error in creating
 #' the full output object. As well as appearing on the screen at run time,if you wish to
 #' see the relevant studysideMessages at a later date you can use the {ds.message}
 #' function. If you type ds.message('newobj') it will print out the relevant

diff --git a/man/ds.cbind.Rd b/man/ds.cbind.Rd
diff --git a/man/ds.dataframe.Rd → man/ds.dataFrame.Rd b/man/ds.dataframe.Rd → man/ds.dataFrame.Rd
diff --git a/man/ds.dim.Rd b/man/ds.dim.Rd
diff --git a/man/ds.rbind.Rd b/man/ds.rbind.Rd
diff --git a/man/ds.reShape.Rd b/man/ds.reShape.Rd
diff --git a/tests/testthat/test-arg-ds.dataframe.R → tests/testthat/test-arg-ds.dataFrame.R b/tests/testthat/test-arg-ds.dataframe.R → tests/testthat/test-arg-ds.dataFrame.R
@@ -18,12 +18,12 @@ connect.studies.dataset.cnsim(list("LAB_TSC"))
 # Tests
 #
 
-context("ds.dataframe::arg::test errors")
+context("ds.dataFrame::arg::test errors")
 test_that("dataframe_erros", {
-    expect_error(ds.dataframe(), "Please provide the name of the list that holds the input vectors!", fixed=TRUE)
+    expect_error(ds.dataFrame(), "Please provide the name of the list that holds the input vectors!", fixed=TRUE)
 
     ds.asList(x='D$A', newobj="as_list")
-    expect_error(ds.dataframe("as_list", DataSHIELD.checks=TRUE), " Only objects of type 'data.frame', 'matrix', 'numeric', 'integer', 'character', 'factor' and 'logical' are allowed.", fixed=TRUE)
+    expect_error(ds.dataFrame("as_list", DataSHIELD.checks=TRUE), " Only objects of type 'data.frame', 'matrix', 'numeric', 'integer', 'character', 'factor' and 'logical' are allowed.", fixed=TRUE)
 })
 
 #

diff --git a/tests/testthat/test-disc-ds.mean.R b/tests/testthat/test-disc-ds.mean.R
@@ -21,7 +21,7 @@ connect.studies.dataset.cnsim(list("LAB_TSC", "LAB_TRIG"))
 context("ds.mean::disc::type=both")
 test_that("mean values [both]", {
     myvectors <- c("D$LAB_TSC", "D$LAB_TRIG")
-    ds.dataframe(x=myvectors, newobj="unsubset_df")
+    ds.dataFrame(x=myvectors, newobj="unsubset_df")
 
     ds.dataFrameSubset(df.name="unsubset_df", V1.name="D$LAB_TSC", V2.name="D$LAB_TRIG", Boolean.operator=">", newobj="subset_df")
 

diff --git a/tests/testthat/test-disc-ds.var.R b/tests/testthat/test-disc-ds.var.R
@@ -21,7 +21,7 @@ connect.studies.dataset.cnsim(list("LAB_TSC", "LAB_TRIG"))
 context("ds.var::disc::type=both")
 test_that("var values [both]", {
     myvectors <- c("D$LAB_TSC", "D$LAB_TRIG")
-    ds.dataframe(x=myvectors, newobj="unsubset_df")
+    ds.dataFrame(x=myvectors, newobj="unsubset_df")
 
     ds.dataFrameSubset(df.name="unsubset_df", V1.name="D$LAB_TSC", V2.name="D$LAB_TRIG", Boolean.operator=">", newobj="subset_df")
 

diff --git a/tests/testthat/test-smk-checkClass.R b/tests/testthat/test-smk-checkClass.R
@@ -69,7 +69,7 @@ test_that("simple test", {
 
 test_that("data.frame test", {
     myvectors <- c('D$LAB_TSC', 'D$LAB_HDL')
-    ds.dataframe(x=myvectors)
+    ds.dataFrame(x=myvectors)
 
     res <- checkClass(ds.test_env$connection.opal, "df_new")
 

diff --git a/tests/testthat/test-smk-ds.colnames.R b/tests/testthat/test-smk-ds.colnames.R
@@ -21,7 +21,7 @@ connect.studies.dataset.cnsim(list("LAB_TSC", "LAB_TRIG"))
 context("ds.colnames::smk")
 test_that("simple colnames", {
     myvectors <- c("D$LAB_TSC", "D$LAB_TRIG")
-    ds.dataframe(x=myvectors, newobj="new_df")
+    ds.dataFrame(x=myvectors, newobj="new_df")
 
     res <- ds.colnames("new_df")
 

diff --git a/tests/testthat/test-smk-ds.dataframe.R → tests/testthat/test-smk-ds.dataFrame.R b/tests/testthat/test-smk-ds.dataframe.R → tests/testthat/test-smk-ds.dataFrame.R
@@ -18,21 +18,21 @@ connect.studies.dataset.cnsim(list("LAB_TSC", "LAB_HDL"))
 # Tests
 #
 
-context("ds.dataframe::smk::create a dataframe")
+context("ds.dataFrame::smk::create a dataframe")
 test_that("dataframe_exists", {
     vectors <- c('D$LAB_TSC', 'D$LAB_HDL')
-    ds.dataframe(x=vectors)
+    ds.dataFrame(x=vectors)
     res <- ds.ls(datasources=ds.test_env$connection.opal)
 
     expect_equal(res$sim1[2], "df_new")
     expect_equal(res$sim2[2], "df_new")
     expect_equal(res$sim3[2], "df_new")
 })
 
-context("ds.dataframe::smk::create a dataframe, with DataSHIELD.checks")
+context("ds.dataFrame::smk::create a dataframe, with DataSHIELD.checks")
 test_that("dataframe_exists, with DataSHIELD.checks", {
     vectors <- c('D$LAB_TSC', 'D$LAB_HDL')
-    ds.dataframe(x=vectors, DataSHIELD.checks=TRUE)
+    ds.dataFrame(x=vectors, DataSHIELD.checks=TRUE)
     res <- ds.ls(datasources=ds.test_env$connection.opal)
 
     expect_equal(res$sim1[2], "df_new")

diff --git a/tests/testthat/test-smk-ds.dataFrameSort.R b/tests/testthat/test-smk-ds.dataFrameSort.R
@@ -21,7 +21,7 @@ connect.studies.dataset.cnsim(list("LAB_TSC", "LAB_HDL"))
 context("ds.dataFrameSort::smk::create a sorted dataframe")
 test_that("dataFrameSort_exists", {
     myvectors <- c('D$LAB_TSC', 'D$LAB_HDL')
-    ds.dataframe(x=myvectors, newobj="unsorted_df")
+    ds.dataFrame(x=myvectors, newobj="unsorted_df")
 
     res <- ds.dataFrameSort(df.name="unsorted_df", sort.key.name="D$LAB_TSC", newobj="sorted_df")
 

diff --git a/tests/testthat/test-smk-ds.dataFrameSubset.R b/tests/testthat/test-smk-ds.dataFrameSubset.R
@@ -21,7 +21,7 @@ connect.studies.dataset.cnsim(list("LAB_TSC", "LAB_HDL"))
 context("ds.dataFrameSubset::smk::create a subset dataframe")
 test_that("dataFrameSubset_exists", {
     myvectors <- c('D$LAB_TSC', 'D$LAB_HDL')
-    ds.dataframe(x=myvectors, newobj="unsubset_df")
+    ds.dataFrame(x=myvectors, newobj="unsubset_df")
 
     res <- ds.dataFrameSubset(df.name="unsubset_df", V1.name="D$LAB_TSC", V2.name="D$LAB_HDL", Boolean.operator="!=", newobj="subset_df")
 

diff --git a/tests/testthat/test-smk-ds.isValid.R b/tests/testthat/test-smk-ds.isValid.R
@@ -31,7 +31,7 @@ test_that("isValid", {
     expect_true(res1$sim3)
 
 #    myvectors <- c("D$LAB_TSC", "D$LAB_TRIG")
-#    ds.dataframe(x=myvectors, newobj="unsubset_df")
+#    ds.dataFrame(x=myvectors, newobj="unsubset_df")
 #    ds.dataFrameSubset(df.name="unsubset_df", V1.name="D$LAB_TSC", V2.name="D$LAB_TRIG", Boolean.operator=">", newobj="subset_df")
 
 #    res2 <- ds.isValid(x="subset_df")

diff --git a/tests/testthat/test-smk-ds.merge.R b/tests/testthat/test-smk-ds.merge.R
@@ -22,8 +22,8 @@ context("ds.merge::smk")
 test_that("simple test", {
     spec_vectors_1 <- c('D$LAB_TSC', 'D$LAB_HDL')
     spec_vectors_2 <- c('D$LAB_TSC', 'D$DIS_AMI')
-    ds.dataframe(x=spec_vectors_1, newobj="test_1_df")
-    ds.dataframe(x=spec_vectors_2, newobj="test_2_df")
+    ds.dataFrame(x=spec_vectors_1, newobj="test_1_df")
+    ds.dataFrame(x=spec_vectors_2, newobj="test_2_df")
 
     res <- ds.merge(x.name="test_1_df", y.name="test_2_df", by.x.names="D$LAB_TSC", by.y.names="D$LAB_TSC", newobj="merge_newobj")