ds.make: Calculates a new object in the server-side

View source: R/ds.make.R

ds.makeR Documentation

Calculates a new object in the server-side

Description

This function defines a new object in the server-side via an allowed function or an arithmetic expression.

ds.make function is equivalent to ds.assign, but runs slightly faster.

Usage

ds.make(toAssign = NULL, newobj = NULL, datasources = NULL)

Arguments

toAssign

a character string specifying the function or the arithmetic expression.

newobj

a character string that provides the name for the output variable that is stored on the data servers. Default make.newobj.

datasources

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.

Details

If the new object is created successfully, the function will verify its existence on the required servers. Please note there are certain modes of failure where it is reported that the object has been created but it is not there. This reflects a failure in the processing of some sort and warrants further exploration of the details of the call to ds.make and the variables/objects which it invokes.

TROUBLESHOOTING: please note we have recently identified an error that makes ds.make fail and DataSHIELD crash.

The error arises from a call such as ds.make(toAssign = '5.3 + beta*xvar', newobj = 'predvals'). This is a typical call you may make to get the predicted values from a simple linear regression model where a y variable is regressed against an x variable (xvar) where the estimated regression intercept is 5.3 and beta is the estimated regression slope.

This call appears to fail because in interpreting the arithmetic function which is its first argument it first encounters the (length 1) scalar 5.3 and when it then encounters the xvar vector which has more than one element it fails - apparently because it does not recognise that you need to replicate the 5.3 value the appropriate number of times to create a vector of length equal to xvar with each value equal to 5.3.

There are two work-around solutions here:

(1) explicitly create a vector of appropriate length with each value equal to 5.3. To do this there is a useful trick. First identify a convenient numeric variable with no missing values (typically a numeric individual ID) let us call it indID equal in length to xvar (xvar may include NAs but that doesn't matter provided indID is the same total length). Then issue the call ds.make(toAssign = 'indID-indID+1',newobj = 'ONES'). This creates a vector of ones (called ONES) in each source equal in length to the indID vector in that source. Then issue the second call ds.make(toAssign = 'ONES*5.3',newobj = 'vect5.3') which creates the required vector of length equal to xvar with all elements 5.3. Finally, you can now issue a modified call to reflect what was originally needed: ds.make(toAssign = 'vect5.3+beta*xvar', 'predvals').

(2) Alternatively, if you simply swap the original call around: ds.make(toAssign = '(beta*xvar)+5.3', newobj = 'predvals') the error seems also to be circumvented. This is presumably because the first element of the arithmetic function is of length equal to xvar and it then knows to replicate the 5.3 that many times in the second part of the expression.

The second work-around is easier, but it is worth knowing about the first trick because creating a vector of ones of equal length to another vector can be useful in other settings. Equally the call: ds.make(toAssign = 'indID-indID',newobj = 'ZEROS') to create a vector of zeros of that same length may also be useful.

Server function : messageDS

The ds.make function is a wrapper for the DSI package function datashield.assign

Value

ds.make returns the new object which is written to the server-side. Also a validity message is returned to the client-side indicating whether the new object has been correctly created at each source.

Author(s)

DataSHIELD Development Team

Examples

## Not run: 

  ## Version 6, for version 5 see the Wiki
  
  # connecting to the Opal servers

  require('DSI')
  require('DSOpal')
  require('dsBaseClient')

  builder <- DSI::newDSLoginBuilder()
  builder$append(server = "study1", 
                 url = "http://192.168.56.100:8080/", 
                 user = "administrator", password = "datashield_test&", 
                 table = "SURVIVAL.EXPAND_NO_MISSING1", driver = "OpalDriver")
  builder$append(server = "study2", 
                 url = "http://192.168.56.100:8080/", 
                 user = "administrator", password = "datashield_test&", 
                 table = "SURVIVAL.EXPAND_NO_MISSING2", driver = "OpalDriver")
  builder$append(server = "study3",
                 url = "http://192.168.56.100:8080/", 
                 user = "administrator", password = "datashield_test&", 
                 table = "SURVIVAL.EXPAND_NO_MISSING3", driver = "OpalDriver")
  logindata <- builder$build()
  
  connections <- DSI::datashield.login(logins = logindata, assign = TRUE, symbol = "D") 
  
##Example 1: arithmetic operators 

ds.make(toAssign = "D$age.60 + D$bmi.26", 
        newobj = "exprs1", 
        datasources = connections)
        
ds.make(toAssign = "D$noise.56 + D$pm10.16",
        newobj = "exprs2", 
        datasources = connections)
        
ds.make(toAssign = "(exprs1*exprs2)/3.2",
        newobj = "result.example1", 
        datasources = connections)

##Example 2: miscellaneous operators within functions

ds.make(toAssign = "(D$female)^2",
        newobj = "female2",
       datasources = connections)
       
ds.make(toAssign = "(2*D$female)+(D$log.surv)-(female2*2)",
        newobj = "output.test.1",
        datasources = connections)
        
ds.make(toAssign = "exp(output.test.1)",
        newobj = "output.test",
       datasources = connections)
       
  # clear the Datashield R sessions and logout
  datashield.logout(connections)

## End(Not run)


datashield/dsBaseClient documentation built on May 16, 2023, 10:19 p.m.