ds.sqrt.RdComputes the square root values for a specified numeric or integer vector.
This function is similar to R function sqrt.
ds.sqrt(x = NULL, newobj = NULL, datasources = NULL)a character string providing the name of a numeric or an integer vector.
a character string that provides the name for the output variable
that is stored on the data servers. Default name is set to sqrt.newobj.
a list of DSConnection-class objects obtained after login.
If the datasources argument is not specified the default set of connections will be
used: see datashield.connections_default.
ds.sqrt assigns a vector for each study that includes the square root values of
the input numeric or integer vector specified in the argument x. The created vectors
are stored in the servers.
The function calls the server-side function sqrtDS that computes the
square root values of the elements of a numeric or integer vector and assigns a new vector
with those square root values on the server-side. The name of the new generated vector is
specified by the user through the argument newobj, otherwise is named by default to
sqrt.newobj.
if (FALSE) { # \dontrun{
# Connecting to the Opal servers
require('DSI')
require('DSOpal')
require('dsBaseClient')
builder <- DSI::newDSLoginBuilder()
builder$append(server = "study1",
url = "http://192.168.56.100:8080/",
user = "administrator", password = "datashield_test&",
table = "CNSIM.CNSIM1", driver = "OpalDriver")
builder$append(server = "study2",
url = "http://192.168.56.100:8080/",
user = "administrator", password = "datashield_test&",
table = "CNSIM.CNSIM2", driver = "OpalDriver")
builder$append(server = "study3",
url = "http://192.168.56.100:8080/",
user = "administrator", password = "datashield_test&",
table = "CNSIM.CNSIM3", driver = "OpalDriver")
logindata <- builder$build()
# Log onto the remote Opal training servers
connections <- DSI::datashield.login(logins = logindata, assign = TRUE, symbol = "D")
# Example 1: Get the square root of LAB_HDL variable
ds.sqrt(x='D$LAB_HDL', newobj='LAB_HDL.sqrt', datasources=connections)
# compare the mean of LAB_HDL and of LAB_HDL.sqrt
# Note here that the number of missing values is bigger in the LAB_HDL.sqrt
ds.mean(x='D$LAB_HDL', datasources=connections)
ds.mean(x='LAB_HDL.sqrt', datasources=connections)
# Example 2: Generate a repeated vector of the squares of integers from 1 to 10
# and get their square roots
ds.make(toAssign='rep((1:10)^2, times=10)', newobj='squares.vector', datasources=connections)
ds.sqrt(x='squares.vector', newobj='sqrt.vector', datasources=connections)
ds.table(rvar='squares.vector')$output.list$TABLE_rvar.by.study_counts
ds.table(rvar='sqrt.vector')$output.list$TABLE_rvar.by.study_counts
# clear the Datashield R sessions and logout
datashield.logout(connections)
} # }