ds.abs.RdComputes the absolute values for a specified numeric or integer vector.
This function is similar to R function abs.
ds.abs(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 abs.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.abs assigns a vector for each study that includes the absolute 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 absDS that computes the
absolute values of the elements of a numeric or integer vector and assigns a new vector
with those absolute 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
abs.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: Generate a normally distributed variable with zero mean and variance equal
# to one and then get their absolute values
ds.rNorm(samp.size=100, mean=0, sd=1, newobj='var.norm', datasources=connections)
# check the quantiles
ds.summary(x='var.norm', datasources=connections)
ds.abs(x='var.norm', newobj='var.norm.abs', datasources=connections)
# check now the changes in the quantiles
ds.summary(x='var.norm.abs', datasources=connections)
# Example 2: Generate a sequence of negative integer numbers from -200 to -100
# and then get their absolute values
ds.seq(FROM.value.char = '-200', TO.value.char = '-100', BY.value.char = '1',
newobj='negative.integers', datasources=connections)
# check the quantiles
ds.summary(x='negative.integers', datasources=connections)
ds.abs(x='negative.integers', newobj='positive.integers', datasources=connections)
# check now the changes in the quantiles
ds.summary(x='positive.integers', datasources=connections)
# clear the Datashield R sessions and logout
datashield.logout(connections)
} # }