Package 'DSLite'

Title: 'DataSHIELD' Implementation on Local Datasets
Description: 'DataSHIELD' is an infrastructure and series of R packages that enables the remote and 'non-disclosive' analysis of sensitive research data. This 'DataSHIELD Interface' implementation is for analyzing datasets living in the current R session. The purpose of this is primarily for lightweight 'DataSHIELD' analysis package development.
Authors: Yannick Marcon [aut, cre]
Maintainer: Yannick Marcon <[email protected]>
License: LGPL (>= 2.1)
Version: 1.5.0
Built: 2024-10-27 03:18:47 UTC
Source: https://github.com/datashield/dslite

Help Index

Binary operation AST node

Description

AST node that represents a binary operation (such as '+', '-' etc.), and therefore having two child nodes.

Super class

DSLite::Node -> BinaryOpNode

Methods

Public methods

Inherited methods

Method add_child()

Two children

Usage
BinaryOpNode$add_child(val)
Arguments
val

Child Node

Method to_string()

Get the string representation of the BinaryOpNode

Usage
BinaryOpNode$to_string()

Method clone()

The objects of this class are cloneable with this method.

Usage
BinaryOpNode$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

Other parser items: FormulaNode, FunctionNode, GroupNode, Node, NumericNode, ParameterNode, RangeNode, StringNode, SymbolNode, UnaryOpNode

Simulated dataset CNSIM 1

Description

Simulated dataset CNSIM 1, in a data.frame with 2163 observations of 11 harmonized variables. The CNSIM dataset contains synthetic data based on a model derived from the participants of the 1958 Birth Cohort, as part of the obesity methodological development project. This dataset does contain some NA values.

Details

Variable Description Type Note
LAB_TSC Total Serum Cholesterol numeric mmol/L
LAB_TRIG Triglycerides numeric mmol/L
LAB_HDL HDL Cholesterol numeric mmol/L
LAB_GLUC_ADJUSTED Non-Fasting Glucose numeric mmol/L
PM_BMI_CONTINUOUS Body Mass Index (continuous) numeric kg/m2
DIS_CVA History of Stroke factor 0 = Never had stroke, 1 = Has had stroke
MEDI_LPD Current Use of Lipid Lowering Medication (from categorical assessment item) factor 0 = Not currently using lipid lowering medication, 1 = Currently using lipid lowering medication
DIS_DIAB History of Diabetes factor 0 = Never had diabetes, 1 = Has had diabetes
DIS_AMI History of Myocardial Infarction factor 0 = Never had myocardial infarction, 1 = Has had myocardial infarction
GENDER Gender factor 0 = Female, 1 = Male
PM_BMI_CATEGORICAL Body Mass Index (categorical) factor 1 = Less than 25 kg/m2, 2 = 25 to 30 kg/m2, 3 = Over 30 kg/m2

Simulated dataset CNSIM 2

Description

Simulated dataset CNSIM 1, in a data.frame with 3088 observations of 11 harmonized variables variables. The CNSIM dataset contains synthetic data based on a model derived from the participants of the 1958 Birth Cohort, as part of the obesity methodological development project. This dataset does contain some NA values.

Details

Variable Description Type Note
LAB_TSC Total Serum Cholesterol numeric mmol/L
LAB_TRIG Triglycerides numeric mmol/L
LAB_HDL HDL Cholesterol numeric mmol/L
LAB_GLUC_ADJUSTED Non-Fasting Glucose numeric mmol/L
PM_BMI_CONTINUOUS Body Mass Index (continuous) numeric kg/m2
DIS_CVA History of Stroke factor 0 = Never had stroke, 1 = Has had stroke
MEDI_LPD Current Use of Lipid Lowering Medication (from categorical assessment item) factor 0 = Not currently using lipid lowering medication, 1 = Currently using lipid lowering medication
DIS_DIAB History of Diabetes factor 0 = Never had diabetes, 1 = Has had diabetes
DIS_AMI History of Myocardial Infarction factor 0 = Never had myocardial infarction, 1 = Has had myocardial infarction
GENDER Gender factor 0 = Female, 1 = Male
PM_BMI_CATEGORICAL Body Mass Index (categorical) factor 1 = Less than 25 kg/m2, 2 = 25 to 30 kg/m2, 3 = Over 30 kg/m2

Simulated dataset CNSIM 3

Description

Simulated dataset CNSIM 1, in a data.frame with 4128 observations of 11 harmonized variables variables. The CNSIM dataset contains synthetic data based on a model derived from the participants of the 1958 Birth Cohort, as part of the obesity methodological development project. This dataset does contain some NA values.

Details

Variable Description Type Note
LAB_TSC Total Serum Cholesterol numeric mmol/L
LAB_TRIG Triglycerides numeric mmol/L
LAB_HDL HDL Cholesterol numeric mmol/L
LAB_GLUC_ADJUSTED Non-Fasting Glucose numeric mmol/L
PM_BMI_CONTINUOUS Body Mass Index (continuous) numeric kg/m2
DIS_CVA History of Stroke factor 0 = Never had stroke, 1 = Has had stroke
MEDI_LPD Current Use of Lipid Lowering Medication (from categorical assessment item) factor 0 = Not currently using lipid lowering medication, 1 = Currently using lipid lowering medication
DIS_DIAB History of Diabetes factor 0 = Never had diabetes, 1 = Has had diabetes
DIS_AMI History of Myocardial Infarction factor 0 = Never had myocardial infarction, 1 = Has had myocardial infarction
GENDER Gender factor 0 = Female, 1 = Male
PM_BMI_CATEGORICAL Body Mass Index (categorical) factor 1 = Less than 25 kg/m2, 2 = 25 to 30 kg/m2, 3 = Over 30 kg/m2

Simulated dataset DASIM 1

Description

Simulated dataset DASIM 1, in a data.frame with 10000 observations of 10 harmonized variables. The DASIM dataset contains synthetic data based on a model derived from the participants of the 1958 Birth Cohort, as part of the obesity methodological development project. This dataset does not contain some NA values.

Details

Variable Description Type Note
LAB_TSC Total Serum Cholesterol numeric mmol/L
LAB_TRIG Triglycerides numeric mmol/L
LAB_HDL HDL Cholesterol numeric mmol/L
LAB_GLUC_FASTING Fasting Glucose numeric mmol/L
PM_BMI_CONTINUOUS Body Mass Index (continuous) numeric kg/m2
DIS_CVA History of Stroke factor 0 = Never had stroke, 1 = Has had stroke
DIS_DIAB History of Diabetes factor 0 = Never had diabetes, 1 = Has had diabetes
DIS_AMI History of Myocardial Infarction factor 0 = Never had myocardial infarction, 1 = Has had myocardial infarction
GENDER Gender factor 0 = Female, 1 = Male
PM_BMI_CATEGORICAL Body Mass Index (categorical) factor 1 = Less than 25 kg/m2, 2 = 25 to 30 kg/m2, 3 = Over 30 kg/m2

Simulated dataset DASIM 2

Description

Simulated dataset DASIM 2, in a data.frame with 10000 observations of 10 harmonized variables. The DASIM dataset contains synthetic data based on a model derived from the participants of the 1958 Birth Cohort, as part of the obesity methodological development project. This dataset does not contain some NA values.

Details

Variable Description Type Note
LAB_TSC Total Serum Cholesterol numeric mmol/L
LAB_TRIG Triglycerides numeric mmol/L
LAB_HDL HDL Cholesterol numeric mmol/L
LAB_GLUC_FASTING Fasting Glucose numeric mmol/L
PM_BMI_CONTINUOUS Body Mass Index (continuous) numeric kg/m2
DIS_CVA History of Stroke factor 0 = Never had stroke, 1 = Has had stroke
DIS_DIAB History of Diabetes factor 0 = Never had diabetes, 1 = Has had diabetes
DIS_AMI History of Myocardial Infarction factor 0 = Never had myocardial infarction, 1 = Has had myocardial infarction
GENDER Gender factor 0 = Female, 1 = Male
PM_BMI_CATEGORICAL Body Mass Index (categorical) factor 1 = Less than 25 kg/m2, 2 = 25 to 30 kg/m2, 3 = Over 30 kg/m2

Simulated dataset DASIM 3

Description

Simulated dataset DASIM 3, in a data.frame with 10000 observations of 10 harmonized variables. The DASIM dataset contains synthetic data based on a model derived from the participants of the 1958 Birth Cohort, as part of the obesity methodological development project. This dataset does not contain some NA values.

Details

Variable Description Type Note
LAB_TSC Total Serum Cholesterol numeric mmol/L
LAB_TRIG Triglycerides numeric mmol/L
LAB_HDL HDL Cholesterol numeric mmol/L
LAB_GLUC_FASTING Fasting Glucose numeric mmol/L
PM_BMI_CONTINUOUS Body Mass Index (continuous) numeric kg/m2
DIS_CVA History of Stroke factor 0 = Never had stroke, 1 = Has had stroke
DIS_DIAB History of Diabetes factor 0 = Never had diabetes, 1 = Has had diabetes
DIS_AMI History of Myocardial Infarction factor 0 = Never had myocardial infarction, 1 = Has had myocardial infarction
GENDER Gender factor 0 = Female, 1 = Male
PM_BMI_CATEGORICAL Body Mass Index (categorical) factor 1 = Less than 25 kg/m2, 2 = 25 to 30 kg/m2, 3 = Over 30 kg/m2

Default DataSHIELD configuration

Description

Find the R packages that have DataSHIELD server configuration information in them and extract this information in a data frame of aggregation/assignment methods and a named list of R options. The DataSHIELD packages can be filtered by specifying explicitly the package names to be included or excluded. The package exclusion prevails over the inclusion.

Usage

defaultDSConfiguration(include = NULL, exclude = NULL)

Arguments

include

Character vector of package names to be explicitly included. If NULL, do not filter packages.
exclude

Character vector of package names to be explicitly excluded. If NULL, do not filter packages.

Examples

## Not run: 
# detect DS packages
defaultDSConfiguration()
# exclude a DS package
defaultDSConfiguration(exclude="dsBase")
# include explicitely some DS packages
defaultDSConfiguration(include=c("dsBase", "dsOmics"))

## End(Not run)

Simulated dataset DISCORDANT 1

Description

Simulated dataset DISCORDANT 1, in a data.frame with 12 observations of 2 discordant variables.

Details

Variable Description Type
A Dummy data integer
B Dummy data integer

Simulated dataset DISCORDANT 2

Description

Simulated dataset DISCORDANT 2, in a data.frame with 12 observations of 2 discordant variables.

Details

Variable Description Type
A Dummy data integer
C Dummy data integer

Simulated dataset DISCORDANT 3

Description

Simulated dataset DISCORDANT 3, in a data.frame with 12 observations of 2 discordant variables.

Details

Variable Description Type
B Dummy data integer
C Dummy data integer

Aggregate data

Description

Aggregate some data from the DataSHIELD R session using a valid R expression. The aggregation expression must satisfy the data repository's DataSHIELD configuration.

Usage

## S4 method for signature 'DSLiteConnection'
dsAggregate(conn, expr, async = TRUE)

Arguments

conn

DSLiteConnection-class object.
expr

Expression to evaluate.
async

Whether the result of the call should be retrieved asynchronously. When TRUE (default) the calls are parallelized over the connections, when the connection supports that feature, with an extra overhead of requests.

Assign the result of an expression

Description

Assign a result of the execution of an expression in the DataSHIELD R session.

Usage

## S4 method for signature 'DSLiteConnection'
dsAssignExpr(conn, symbol, expr, async = TRUE)

Arguments

conn

DSLiteConnection-class object.
symbol

Name of the R symbol.
expr

A R expression with allowed assign functions calls.
async

Whether the result of the call should be retrieved asynchronously. When TRUE (default) the calls are parallelized over the connections, when the connection supports that feature, with an extra overhead of requests.

Value

A DSLiteResult-class object.

Assign a resource

Description

Assign a DSLite resource in the DataSHIELD R session.

Usage

## S4 method for signature 'DSLiteConnection'
dsAssignResource(conn, symbol, resource, async = TRUE)

Arguments

conn

DSLiteConnection-class object.
symbol

Name of the R symbol.
resource

Fully qualified name of a resource object living in the DSLite server.
async

Whether the result of the call should be retrieved asynchronously. When TRUE (default) the calls are parallelized over the connections, when the connection supports that feature, with an extra overhead of requests.

Value

A DSLiteResult-class object.

Assign a table

Description

Assign a DSLite dataset in the DataSHIELD R session.

Usage

## S4 method for signature 'DSLiteConnection'
dsAssignTable(
  conn,
  symbol,
  table,
  variables = NULL,
  missings = FALSE,
  identifiers = NULL,
  id.name = NULL,
  async = TRUE
)

Arguments

conn

DSLiteConnection-class object.
symbol

Name of the R symbol.
table

Fully qualified name of a dataset living in the DSLite server.
variables

The variable names to be filtered in.
missings

Ignored.
identifiers

Name of the identifiers mapping to use when assigning entities to R (currently NOT supported by DSLite).
id.name

Name of the column that will contain the entity identifiers. If not specified, the identifiers will be the data frame row names. When specified this column can be used to perform joins between data frames.
async

Whether the result of the call should be retrieved asynchronously. When TRUE (default) the calls are parallelized over the connections, when the connection supports that feature, with an extra overhead of requests.

Value

A DSLiteResult-class object.

Connect to a DSLite server

Description

Connect to a DSLite server, with provided datasets symbol names.

Usage

## S4 method for signature 'DSLiteDriver'
dsConnect(drv, name, url, restore = NULL, profile = NULL, ...)

Arguments

drv

DSLiteDriver-class class object.
name

Name of the connection, which must be unique among all the DataSHIELD connections.
url

A R symbol that refers to a DSLiteServer object that holds the datasets of interest. The option "datashield.env" can be used to specify where to search for this symbol value. If not specified, the environment is the global one.
restore

Workspace name to be restored in the newly created DataSHIELD R session.
profile

Name of the profile that will be given to the DSLiteServer configuration. Make different DSLiteServers to support different configurations.
...

Unused, needed for compatibility with generic.

Value

A DSLiteConnection-class object.

Disconnect from a DSLite server

Description

Save the session in a local file if requested.

Usage

## S4 method for signature 'DSLiteConnection'
dsDisconnect(conn, save = NULL)

Arguments

conn

DSLiteConnection-class class object
save

Save the DataSHIELD R session with provided ID (must be a character string).

Fetch the result

Description

Fetch the DataSHIELD operation result.

Usage

## S4 method for signature 'DSLiteResult'
dsFetch(res)

Arguments

res

DSLiteResult-class object.

Value

TRUE if table exists.

Get result info

Description

Get the information about a command (if still available).

Usage

## S4 method for signature 'DSLiteResult'
dsGetInfo(dsObj, ...)

Arguments

dsObj

DSLiteResult-class class object
...

Unused, needed for compatibility with generic.

Value

The result information, including its status.

Verify DSLite server resource

Description

Verify resource exists and can be accessible for performing DataSHIELD operations.

Usage

## S4 method for signature 'DSLiteConnection'
dsHasResource(conn, resource)

Arguments

conn

DSLiteConnection-class class object.
resource

The fully qualified name of the resource.

Value

TRUE if dataset exists.

Verify DSLite server dataset

Description

Verify dataset exists and can be accessible for performing DataSHIELD operations.

Usage

## S4 method for signature 'DSLiteConnection'
dsHasTable(conn, table)

Arguments

conn

DSLiteConnection-class class object.
table

The fully qualified name of the dataset.

Value

TRUE if dataset exists.

DSLite asynchronous support

Description

No asynchronicity on any DataSHIELD operations.

Usage

## S4 method for signature 'DSLiteConnection'
dsIsAsync(conn)

Arguments

conn

DSLiteConnection-class class object

Value

The named list of logicals detailing the asynchronicity support.

Get whether the operation is completed

Description

Always TRUE because of synchronous operations.

Usage

## S4 method for signature 'DSLiteResult'
dsIsCompleted(res)

Arguments

res

DSLiteResult-class object.

Value

Always TRUE.

Keep connection with a DSLite server alive

Description

No operation due to the DSLiteServer nature.

Usage

## S4 method for signature 'DSLiteConnection'
dsKeepAlive(conn)

Arguments

conn

DSLiteConnection-class class object

List methods

Description

List methods defined in the DataSHIELD configuration.

Usage

## S4 method for signature 'DSLiteConnection'
dsListMethods(conn, type = "aggregate")

Arguments

conn

DSLiteConnection-class class object
type

Type of the method: "aggregate" (default) or "assign".

Value

A data frame.

List packages

Description

List packages defined in the DataSHIELD configuration.

Usage

## S4 method for signature 'DSLiteConnection'
dsListPackages(conn)

Arguments

conn

DSLiteConnection-class class object

Value

A data frame.

List profiles

Description

List profiles defined in the DataSHIELD configuration.

Usage

## S4 method for signature 'DSLiteConnection'
dsListProfiles(conn)

Arguments

conn

DSLiteConnection-class class object

Value

A list containing the "available" character vector of profile names and the "current" profile (in case a default one was assigned).

List DSLite server resources

Description

List resource names living in the DSLite server for performing DataSHIELD operations.

Usage

## S4 method for signature 'DSLiteConnection'
dsListResources(conn)

Arguments

conn

DSLiteConnection-class class object

Value

The fully qualified names of the resources.

List R symbols

Description

List symbols living in the DataSHIELD R session.

Usage

## S4 method for signature 'DSLiteConnection'
dsListSymbols(conn)

Arguments

conn

DSLiteConnection-class class object

Value

A character vector.

List DSLite server datasets

Description

List dataset names living in the DSLite server for performing DataSHIELD operations.

Usage

## S4 method for signature 'DSLiteConnection'
dsListTables(conn)

Arguments

conn

DSLiteConnection-class class object

Value

The fully qualified names of the tables.

List workspaces

Description

List workspaces saved in the data repository.

Usage

## S4 method for signature 'DSLiteConnection'
dsListWorkspaces(conn)

Arguments

conn

DSLiteConnection-class class object

Value

A data frame.

Create a DSLite driver

Description

Convenient function for creating a DSLiteDriver object.

Usage

DSLite()

Lightweight DataSHIELD server-side component

Description

DSLiteServer mimics a DataSHIELD server by holding datasets and exposing DataSHIELD-like functions: aggregate and assign. A DataSHIELD session is a R environment where the assignment and the operations happen.

Methods

Public methods

Method new()

Create new DSLiteServer instance. See defaultDSConfiguration function for including or excluding packages when discovering the DataSHIELD configuration from the DataSHIELD server-side packages (meta-data from the DESCRIPTION files).

Usage
DSLiteServer$new(
  tables = list(),
  resources = list(),
  config = DSLite::defaultDSConfiguration(),
  strict = TRUE,
  home = file.path(tempdir(), ".dslite"),
  profile = "default"
)
Arguments
tables

A named list of data.frames representing the harmonized tables.

resources

A named list of resourcer::Resource objects representing accessible data or computation resources.

config

The DataSHIELD configuration. Default is to discover it from the DataSHIELD server-side R packages.

strict

Logical to specify whether the DataSHIELD configuration must be strictly applied. Default is TRUE.

home

Folder location where are located the session work directory and where to read and dump workspace images.

profile

The DataSHIELD profile name, used to give a name to the DS configuration. Default is "default". Default is in a hidden folder of the R session's temporary directory.

Returns

A DSLiteServer object

Method config()

Get or set the DataSHIELD configuration.

Usage
DSLiteServer$config(value)
Arguments
value

The DataSHIELD configuration: aggregate/assign methods in data frames and a named list of options.

Returns

The DataSHIELD configuration, if no parameter is provided.

Method profile()

Get or set the DataSHIELD profile name.

Usage
DSLiteServer$profile(value)
Arguments
value

The DataSHIELD profile name.

Returns

The DataSHIELD profile, if no parameter is provided.

Method strict()

Get or set the level of strictness (stop when function call is not configured)

Usage
DSLiteServer$strict(value)
Arguments
value

The strict logical field.

Returns

The strict field if no parameter is provided.

Method home()

Get or set the home folder location where are located the session work directories and where to read and dump workspace images.

Usage
DSLiteServer$home(value)
Arguments
value

The path to the home folder.

Returns

The home folder path if no parameter is provided.

Method workspaces()

List the saved workspaces in the home folder.

Usage
DSLiteServer$workspaces(prefix = NULL)
Arguments
prefix

Filter workspaces starting with provided prefix (optional).

Method workspace_save()

Save the session's workspace image identified by the sid identifier with the provided name in the home folder.

Usage
DSLiteServer$workspace_save(sid, name)
Arguments
sid,

Session ID

name

The name to be given to the workspace's image.

Method workspace_restore()

Restore a saved session's workspace image into the session identified by the sid identifier with the provided name in the home folder.

Usage
DSLiteServer$workspace_restore(sid, name)
Arguments
sid,

Session ID

name

The name of the workspace's image to restore.

Method workspace_rm()

Remove the workspace image with the provided name from the home folder.

Usage
DSLiteServer$workspace_rm(name)
Arguments
name

The name of the workspace.

Method aggregateMethods()

Get or set the aggregate methods.

Usage
DSLiteServer$aggregateMethods(value)
Arguments
value

A data.frame with columns: name (the client function call), value (the translated server call), package (relevant when extracted from a DataSHIELD server-side package), version (relevant when extracted from a DataSHIELD server-side package), type ("aggregate"), class ("function" for package functions or "script" for custom scripts).

Returns

The aggregate methods when no parameter is provided.

Method aggregateMethod()

Get or set an aggregate method.

Usage
DSLiteServer$aggregateMethod(name, value)
Arguments
name

The client function call.

value

The translated server call: either a package function reference or function expression. Remove the method when NULL.

Returns

The aggregate method when no value parameter is provided.

Method assignMethods()

Get or set the assign methods.

Usage
DSLiteServer$assignMethods(value)
Arguments
value

A data.frame with columns: name (the client function call), value (the translated server call), package (relevant when extracted from a DataSHIELD server-side package), version (relevant when extracted from a DataSHIELD server-side package), type ("assign"), class ("function" for package functions or "script" for custom scripts).

Returns

The assign methods when no parameter is provided.

Method assignMethod()

Get or set an assign method.

Usage
DSLiteServer$assignMethod(name, value)
Arguments
name

The client function call

value

The translated server call: either a package function reference or function expression. Remove the method when NULL.

Returns

The assign method when no value parameter is provided.

Method options()

Get or set the DataSHIELD R options that are applied when a new DataSHIELD session is started.

Usage
DSLiteServer$options(value)
Arguments
value

A named list of options.

Returns

The R options when no parameter is provided.

Method option()

Get or set a R option.

Usage
DSLiteServer$option(key, value)
Arguments
key

The R option's name.

value

The R option's value. Remove the option when NULL.

Returns

The R option's value when only key parameter is provided.

Method newSession()

Create a new DataSHIELD session (contained execution environment), apply options that are defined in the DataSHIELD configuration and restore workspace image if restore workspace name argument is provided.

Usage
DSLiteServer$newSession(restore = NULL, profile = NULL)
Arguments
restore

The workspace image to be restored (optional).

profile

The requested profile name (optional). If provided, new session creation will fail in case it does not match the server's profile name.

Method hasSession()

Check a DataSHIELD session is alive.

Usage
DSLiteServer$hasSession(sid)
Arguments
sid

The session ID.

Method getSession()

Get the DataSHIELD session's environment.

Usage
DSLiteServer$getSession(sid)
Arguments
sid

The session ID.

Method getSessionIds()

Get the DataSHIELD session IDs.

Usage
DSLiteServer$getSessionIds()

Method getSessionData()

Get the symbol value from the DataSHIELD session's environment.

Usage
DSLiteServer$getSessionData(sid, symbol)
Arguments
sid

The session ID.

symbol

The symbol name.

Method closeSession()

Destroy DataSHIELD session and save workspace image if save workspace name argument is provided.

Usage
DSLiteServer$closeSession(sid, save = NULL)
Arguments
sid

The session ID.

save

The name of the workspace image to be saved (optional).

Method tableNames()

List the names of the tables that can be assigned.

Usage
DSLiteServer$tableNames()

Method hasTable()

Check a table exists.

Usage
DSLiteServer$hasTable(name)
Arguments
name

The table name to be looked for.

Method resourceNames()

List the names of the resources (resourcer::Resource objects) that can be assigned.

Usage
DSLiteServer$resourceNames()

Method hasResource()

Check a resource (resourcer::Resource object) exists.

Usage
DSLiteServer$hasResource(name)
Arguments
name

The resource name to be looked for.

Method symbols()

List the symbols living in a DataSHIELD session.

Usage
DSLiteServer$symbols(sid)
Arguments
sid

The session ID.

Method symbol_rm()

Remove a symbol from a DataSHIELD session.

Usage
DSLiteServer$symbol_rm(sid, name)
Arguments
sid

The session ID.

name

The symbol name.

Method assignTable()

Assign a table to a symbol in a DataSHIELD session. Filter table columns with the variables names provided.

Usage
DSLiteServer$assignTable(sid, symbol, name, variables = NULL, id.name = NULL)
Arguments
sid

The session ID.

symbol

The symbol to be assigned.

name

The table's name.

variables

The variable names to be filtered in (optional).

id.name

The column name to be used for the entity's identifier (optional).

Method assignResource()

Assign a resource as a resourcer::ResourceClient object to a symbol in a DataSHIELD session.

Usage
DSLiteServer$assignResource(sid, symbol, name)
Arguments
sid

The session ID.

symbol

The symbol name.

name

The name of the resource.

Method assignExpr()

Evaluate an assignment expression in a DataSHIELD session.

Usage
DSLiteServer$assignExpr(sid, symbol, expr)
Arguments
sid

The session ID.

symbol

The symbol name.

expr

The R expression to evaluate.

Method aggregate()

Evaluate an aggregate expression in a DataSHIELD session.

Usage
DSLiteServer$aggregate(sid, expr)
Arguments
sid

The session ID.

expr

The R expression to evaluate.

Method clone()

The objects of this class are cloneable with this method.

Usage
DSLiteServer$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

Other server-side items: newDSLiteServer()

Restore workspace

Description

Restore workspace from the data repository.

Usage

## S4 method for signature 'DSLiteConnection'
dsRestoreWorkspace(conn, name)

Arguments

conn

DSLiteConnection-class class object
name

Name of the workspace.

Remove a R symbol

Description

Remoe a symbol living in the DataSHIELD R session.

Usage

## S4 method for signature 'DSLiteConnection'
dsRmSymbol(conn, symbol)

Arguments

conn

DSLiteConnection-class class object
symbol

Name of the R symbol.

Remove a workspace

Description

Remove a workspace on the data repository.

Usage

## S4 method for signature 'DSLiteConnection'
dsRmWorkspace(conn, name)

Arguments

conn

DSLiteConnection-class class object
name

Name of the workspace.

Save workspace

Description

Save workspace on the data repository.

Usage

## S4 method for signature 'DSLiteConnection'
dsSaveWorkspace(conn, name)

Arguments

conn

DSLiteConnection-class class object
name

Name of the workspace.

Formula AST node

Description

AST node that reprsents a formula (such as NAME ~ terms).

Super class

DSLite::Node -> FormulaNode

Methods

Public methods

Inherited methods

Method add_child()

Two children

Usage
FormulaNode$add_child(val)
Arguments
val

Child Node

Method to_string()

Get the string representation of the BinaryOpNode

Usage
FormulaNode$to_string()

Method clone()

The objects of this class are cloneable with this method.

Usage
FormulaNode$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

Other parser items: BinaryOpNode, FunctionNode, GroupNode, Node, NumericNode, ParameterNode, RangeNode, StringNode, SymbolNode, UnaryOpNode

Function AST node

Description

AST node that represents a function with its arguments.

Super class

DSLite::Node -> FunctionNode

Methods

Public methods

Inherited methods

Method to_string()

Get the string representation of the FunctionNode

Usage
FunctionNode$to_string()

Method clone()

The objects of this class are cloneable with this method.

Usage
FunctionNode$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

Other parser items: BinaryOpNode, FormulaNode, GroupNode, Node, NumericNode, ParameterNode, RangeNode, StringNode, SymbolNode, UnaryOpNode

Get data value from DSLite connection(s)

Description

Get the data value corresponding to the variable with the symbol name from the DSLiteServer associated to the DSConnection-class object(s). Can be useful when developping a DataSHIELD package.

Usage

getDSLiteData(conns, symbol)

Arguments

conns

DSConnection-class object or a list of DSConnection-classs.
symbol

Symbol name identifying the variable in the DSLiteServer's "server-side" environment(s).

Value

The data value or a list of values depending on the connections parameter. The value is NA when the connection object is not of class DSLiteConnection-class.

Examples

## Not run: 
# DataSHIELD login
logindata <- setupCNSIMTest()
conns <- datashield.login(logindata, assign=TRUE)
# retrieve symbol D value from each DataSHIELD connections
getDSLiteData(conns, "D")
# retrieve symbol D value from a specific DataSHIELD connection
getDSLiteData(conns$sim1, "D")

## End(Not run)

Group AST node

Description

AST node that reprsents a group of tokens enclosed by parenthesis.

Super class

DSLite::Node -> GroupNode

Methods

Public methods

Inherited methods

Method to_string()

Get the string representation of the GroupNode

Usage
GroupNode$to_string()

Method clone()

The objects of this class are cloneable with this method.

Usage
GroupNode$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

Other parser items: BinaryOpNode, FormulaNode, FunctionNode, Node, NumericNode, ParameterNode, RangeNode, StringNode, SymbolNode, UnaryOpNode

DataSHIELD login data for the CNSIM simulated datasets

Description

DataSHIELD login data.frame for connecting with CNSIM datasets. The CNSIM datasets contain synthetic data based on a model derived from the participants of the 1958 Birth Cohort, as part of the obesity methodological development project. These datasets do contain some NA values.

Details

Field Description Type Note
server Server/study name char
url Server/study URL char DSLiteServer instance symbol name
user User name char Always empty for DSLiteServer
password User password char Always empty for DSLiteServer
table Table unique name char As registered in the DSLiteServer
options Connection options char Always empty for DSLiteServer
driver Connection driver char DSLiteServer

DataSHIELD login data for the DASIM simulated datasets

Description

DataSHIELD login data.frame for connecting with DASIM datasets. The DASIM datasets contain synthetic data based on a model derived from the participants of the 1958 Birth Cohort, as part of the obesity methodological development project. These datasets do not contain some NA values.

Details

Field Description Type Note
server Server/study name char
url Server/study URL char DSLiteServer instance symbol name
user User name char Always empty for DSLiteServer
password User password char Always empty for DSLiteServer
table Table unique name char As registered in the DSLiteServer
options Connection options char Always empty for DSLiteServer
driver Connection driver char DSLiteServer

DataSHIELD login data for the DISCORDANT simulated datasets

Description

DataSHIELD login data.frame for connecting with DISCORDANT datasets which purpose is to test datasets that are NOT harmonized.

Details

Field Description Type Note
server Server/study name char
url Server/study URL char DSLiteServer instance symbol name
user User name char Always empty for DSLiteServer
password User password char Always empty for DSLiteServer
table Table unique name char As registered in the DSLiteServer
options Connection options char Always empty for DSLiteServer
driver Connection driver char DSLiteServer

DataSHIELD login data for the simulated survival expand-with-missing datasets

Description

DataSHIELD login data.frame for connecting with SURVIVAL datasets which purpose is to perform survival tests. The datasets contain synthetic data based on a simulated survival model, including a censoring indicator.

Details

Field Description Type Note
server Server/study name char
url Server/study URL char DSLiteServer instance symbol name
user User name char Always empty for DSLiteServer
password User password char Always empty for DSLiteServer
table Table unique name char As registered in the DSLiteServer
options Connection options char Always empty for DSLiteServer
driver Connection driver char DSLiteServer

DataSHIELD login data for the TESTING.DATASET simulated datasets

Description

DataSHIELD login data.frame for connecting with TESTING.DATASET datasets which purpose is to evaluate each base data types.

Details

Field Description Type Note
server Server/study name char
url Server/study URL char DSLiteServer instance symbol name
user User name char Always empty for DSLiteServer
password User password char Always empty for DSLiteServer
table Table unique name char As registered in the DSLiteServer
options Connection options char Always empty for DSLiteServer
driver Connection driver char DSLiteServer

Create a new DSLite server

Description

Shortcut function to create a new DSLiteServer instance.

Usage

newDSLiteServer(
  tables = list(),
  resources = list(),
  config = DSLite::defaultDSConfiguration(),
  strict = TRUE,
  home = file.path(tempdir(), ".dslite")
)

Arguments

tables

A named list of data.frames representing the harmonized tables.
resources

A named list of resourcer::Resource objects representing accessible data or computation resources.
config

The DataSHIELD configuration. Default is to discover it from the DataSHIELD server-side R packages. See defaultDSConfiguration function for including or excluding packages when discovering the DataSHIELD configuration from the DataSHIELD server-side packages (meta-data from the DESCRIPTION files).
strict

Logical to specify whether the DataSHIELD configuration must be strictly applied. Default is TRUE.
home

Folder location where are located the session work directory and where to read and dump workspace images. Default is in a hidden folder of the R session's temporary directory.

See Also

Other server-side items: DSLiteServer

Simple AST node

Description

Abstract Syntaxic Tree (AST) node that will be created by the DSLite R parser.

Public fields

name

Token value

parent

Parent Node

children

Children Nodes

Methods

Public methods

Method new()

Simple node constructor

Usage
Node$new(name = NA, parent = NA)
Arguments
name

Token value

parent

Parent Node

Returns

A Node object

Method set_parent()

Set parent Node

Usage
Node$set_parent(val)
Arguments
val

Parent Node

Method add_child()

Add a child Node

Usage
Node$add_child(val)
Arguments
val

Child Node

Method to_string()

The string representation of the Node

Usage
Node$to_string()

Method to_string_children()

Get the string representation of the Node's children

Usage
Node$to_string_children()

Method accept()

Accept visitor

Usage
Node$accept(visitor)
Arguments
visitor

Node visitor object

Method clone()

The objects of this class are cloneable with this method.

Usage
Node$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

Other parser items: BinaryOpNode, FormulaNode, FunctionNode, GroupNode, NumericNode, ParameterNode, RangeNode, StringNode, SymbolNode, UnaryOpNode

Numeric AST node

Description

AST node that reprsents a numeric (integer or float) value.

Super class

DSLite::Node -> NumericNode

Methods

Public methods

Inherited methods

Method add_child()

No children

Usage
NumericNode$add_child(val)
Arguments
val

Child Node

Method to_string()

Get the string representation of the NumericNode

Usage
NumericNode$to_string()

Method clone()

The objects of this class are cloneable with this method.

Usage
NumericNode$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

Other parser items: BinaryOpNode, FormulaNode, FunctionNode, GroupNode, Node, ParameterNode, RangeNode, StringNode, SymbolNode, UnaryOpNode

Parameter AST node

Description

AST node that represents a function's named parameter (such as NAME = expression).

Super class

DSLite::Node -> ParameterNode

Methods

Public methods

Inherited methods

Method add_child()

Two children

Usage
ParameterNode$add_child(val)
Arguments
val

Child Node

Method to_string()

Get the string representation of the BinaryOpNode

Usage
ParameterNode$to_string()

Method clone()

The objects of this class are cloneable with this method.

Usage
ParameterNode$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

Other parser items: BinaryOpNode, FormulaNode, FunctionNode, GroupNode, Node, NumericNode, RangeNode, StringNode, SymbolNode, UnaryOpNode

Range AST node

Description

AST node that represents a range of values (such as min expression:max expression), therefore having two child nodes.

Super class

DSLite::Node -> RangeNode

Methods

Public methods

Inherited methods

Method add_child()

Two children

Usage
RangeNode$add_child(val)
Arguments
val

Child Node

Method to_string()

Get the string representation of the BinaryOpNode

Usage
RangeNode$to_string()

Method clone()

The objects of this class are cloneable with this method.

Usage
RangeNode$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

Other parser items: BinaryOpNode, FormulaNode, FunctionNode, GroupNode, Node, NumericNode, ParameterNode, StringNode, SymbolNode, UnaryOpNode

Setup a test environment based on the CNSIM simulated datasets

Description

Load the CNSIM datasets, the corresponding login data object, instanciate a new DSLiteServer hosting these datasets and verify that the required DataSHIELD server-side packages are installed.

Usage

setupCNSIMTest(packages = c(), env = parent.frame())

Arguments

packages

DataSHIELD server-side packages which local installation must be verified so that the DSLiteServer can auto-configure itself and can execute the DataSHIELD operations. Default is none.
env

The environment where DataSHIELD objects should be looked for: the DSLiteServer and the DSIConnection objects. Default is the Global environment.

Value

The login data for the datashield.login function.

See Also

Other setup functions: setupDASIMTest(), setupDATASETTest(), setupDISCORDANTTest(), setupDSLiteServer(), setupSURVIVALTest()

Examples

## Not run: 
logindata <- setupCNSIMTest()
conns <- datashield.login(logindata, assign=TRUE)
# do DataSHIELD analysis
datashield.logout(conns)

## End(Not run)

Setup a test environment based on the DASIM simulated datasets

Description

Load the DASIM datasets, the corresponding login data object, instanciate a new DSLiteServer hosting these datasets and verify that the required DataSHIELD server-side packages are installed.

Usage

setupDASIMTest(packages = c(), env = parent.frame())

Arguments

packages

DataSHIELD server-side packages which local installation must be verified so that the DSLiteServer can auto-configure itself and can execute the DataSHIELD operations. Default is none.
env

The environment where DataSHIELD objects should be looked for: the DSLiteServer and the DSIConnection objects. Default is the Global environment.

Value

The login data for the datashield.login function.

See Also

Other setup functions: setupCNSIMTest(), setupDATASETTest(), setupDISCORDANTTest(), setupDSLiteServer(), setupSURVIVALTest()

Examples

## Not run: 
logindata <- setupDASIMTest()
conns <- datashield.login(logindata, assign=TRUE)
# do DataSHIELD analysis
datashield.logout(conns)

## End(Not run)

Setup a test environment based on the TESTING.DATASET simulated datasets

Description

Load the TESTING.DATASET datasets, the corresponding login data object, instanciate a new DSLiteServer hosting these datasets and verify that the required DataSHIELD server-side packages are installed.

Usage

setupDATASETTest(packages = c(), env = parent.frame())

Arguments

packages

DataSHIELD server-side packages which local installation must be verified so that the DSLiteServer can auto-configure itself and can execute the DataSHIELD operations. Default is none.
env

The environment where DataSHIELD objects should be looked for: the DSLiteServer and the DSIConnection objects. Default is the Global environment.

Value

The login data for the datashield.login function.

See Also

Other setup functions: setupCNSIMTest(), setupDASIMTest(), setupDISCORDANTTest(), setupDSLiteServer(), setupSURVIVALTest()

Examples

## Not run: 
logindata <- setupDATASETTest()
conns <- datashield.login(logindata, assign=TRUE)
# do DataSHIELD analysis
datashield.logout(conns)

## End(Not run)

Setup a test environment based on the DISCORDANT simulated datasets

Description

Load the DISCORDANT datasets, the corresponding login data object, instanciate a new DSLiteServer hosting these datasets and verify that the required DataSHIELD server-side packages are installed.

Usage

setupDISCORDANTTest(packages = c(), env = parent.frame())

Arguments

packages

DataSHIELD server-side packages which local installation must be verified so that the DSLiteServer can auto-configure itself and can execute the DataSHIELD operations. Default is none.
env

The environment where DataSHIELD objects should be looked for: the DSLiteServer and the DSIConnection objects. Default is the Global environment.

Value

The login data for the datashield.login function.

See Also

Other setup functions: setupCNSIMTest(), setupDASIMTest(), setupDATASETTest(), setupDSLiteServer(), setupSURVIVALTest()

Examples

## Not run: 
logindata <- setupDISCORDANTTest()
conns <- datashield.login(logindata, assign=TRUE)
# do DataSHIELD analysis
datashield.logout(conns)

## End(Not run)

Setup an environment based on named datasets and logindata

Description

Load the provided datasets and the corresponding logindata object, instanciate a new DSLiteServer hosting these datasets, verifies that the required DataSHIELD server-side packages are installed. All the data structures are loaded by data which supports various formats (see data() documentation).

Usage

setupDSLiteServer(
  packages = c(),
  datasets,
  logindata,
  pkgs = NULL,
  dslite.server = NULL,
  env = parent.frame()
)

Arguments

packages

DataSHIELD server-side packages which local installation must be verified so that the DSLiteServer can auto-configure itself and can execute the DataSHIELD operations. Default is none.
datasets

Names of the datasets to be loaded using data.
logindata

Name of the login data object to be loaded using data.
pkgs

The package(s) to look in for datasets, default is all, then the 'data' subdirectory (if present) of the current working directory (same behavior as 'package' argument in data).
dslite.server

Symbol name to which the DSLiteServer should be assigned to. If not provided, the symbol name will be the first not null one specified in the 'url' column of the loaded login data.
env

The environment where DataSHIELD objects should be looked for: the DSLiteServer and the DSIConnection objects. Default is the Global environment.

Value

The login data for the datashield.login function.

See Also

Other setup functions: setupCNSIMTest(), setupDASIMTest(), setupDATASETTest(), setupDISCORDANTTest(), setupSURVIVALTest()

Examples

## Not run: 
logindata <- setupDSLiteServer(
                 datasets = c("CNSIM1", "CNSIM2", "CNSIM3"),
                 logindata = "logindata.dslite.cnsim", pkgs = "DSLite",
                 dslite.server = "dslite.server")
conns <- datashield.login(logindata, assign=TRUE)
# do DataSHIELD analysis
datashield.logout(conns)

## End(Not run)

Setup a test environment based on the SURVIVAL (EXPAND_WITH_MISSING) simulated datasets

Description

Load the SURVIVAL (EXPAND_WITH_MISSING) datasets, the corresponding login data object, instanciate a new DSLiteServer hosting these datasets and verify that the required DataSHIELD server-side packages are installed.

Usage

setupSURVIVALTest(packages = c(), env = parent.frame())

Arguments

packages

DataSHIELD server-side packages which local installation must be verified so that the DSLiteServer can auto-configure itself and can execute the DataSHIELD operations. Default is none.
env

The environment where DataSHIELD objects should be looked for: the DSLiteServer and the DSIConnection objects. Default is the Global environment.

Value

The login data for the datashield.login function.

See Also

Other setup functions: setupCNSIMTest(), setupDASIMTest(), setupDATASETTest(), setupDISCORDANTTest(), setupDSLiteServer()

Examples

## Not run: 
logindata <- setupSURVIVALTest()
conns <- datashield.login(logindata, assign=TRUE)
# do DataSHIELD analysis
datashield.logout(conns)

## End(Not run)

String AST node

Description

AST node that represent a string value, either single or double quoted.

Super class

DSLite::Node -> StringNode

Methods

Public methods

Inherited methods

Method add_child()

No children

Usage
StringNode$add_child(val)
Arguments
val

Child Node

Method to_string()

Get the string representation of the StringNode

Usage
StringNode$to_string()

Method clone()

The objects of this class are cloneable with this method.

Usage
StringNode$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

Other parser items: BinaryOpNode, FormulaNode, FunctionNode, GroupNode, Node, NumericNode, ParameterNode, RangeNode, SymbolNode, UnaryOpNode

Simulated survival expand-with-missing dataset 1

Description

Simulated dataset SURVIVAL.EXPAND_WITH_MISSING 1, in a data.frame with 2060 observations of 12 harmonized variables. The dataset contains synthetic data based on a simulated survival model, including a censoring indicator.

Details

Variable Description Type Note
id Unique individual ID integer
study.id Study ID integer
time.id Time ID integer
starttime Start of follow up numeric years
endtime End of follow up numeric years
survtime Survtime numeric years
cens Censoring status factor 0 = not censored, 1 = censored
age.60 Age centred at 60 numeric
female Gender factor 0 = Male, 1 = Female
noise.56 Noise pollution centred at 56 numeric dB
pm10.16 Particulate matter centred at 16 numeric µg/m3
bmi.26 Body mass index centred at 26 numeric kg/m2

Simulated survival expand-with-missing dataset 2

Description

Simulated dataset SURVIVAL.EXPAND_WITH_MISSING 2, in a data.frame with 1640 observations of 12 harmonized variables. The dataset contains synthetic data based on a simulated survival model, including a censoring indicator.

Details

Variable Description Type Note
id Unique individual ID integer
study.id Study ID integer
time.id Time ID integer
starttime Start of follow up numeric years
endtime End of follow up numeric years
survtime Survtime numeric years
cens Censoring status factor 0 = not censored, 1 = censored
age.60 Age centred at 60 numeric
female Gender factor 0 = Male, 1 = Female
noise.56 Noise pollution centred at 56 numeric dB
pm10.16 Particulate matter centred at 16 numeric µg/m3
bmi.26 Body mass index centred at 26 numeric kg/m2

Simulated survival expand-with-missing dataset 3

Description

Simulated dataset SURVIVAL.EXPAND_WITH_MISSING 3, in a data.frame with 2688 observations of 12 harmonized variables. The dataset contains synthetic data based on a simulated survival model, including a censoring indicator.

Details

Variable Description Type Note
id Unique individual ID integer
study.id Study ID integer
time.id Time ID integer
starttime Start of follow up numeric years
endtime End of follow up numeric years
survtime Survtime numeric years
cens Censoring status factor 0 = not censored, 1 = censored
age.60 Age centred at 60 numeric
female Gender factor 0 = Male, 1 = Female
noise.56 Noise pollution centred at 56 numeric dB
pm10.16 Particulate matter centred at 16 numeric µg/m3
bmi.26 Body mass index centred at 26 numeric kg/m2

Symbol AST node

Description

AST node that represents a R symbol (variable name, function name etc.).

Super class

DSLite::Node -> SymbolNode

Methods

Public methods

Inherited methods

Method add_child()

No children

Usage
SymbolNode$add_child(val)
Arguments
val

Child Node

Method to_string()

Get the string representation of the SymbolNode

Usage
SymbolNode$to_string()

Method clone()

The objects of this class are cloneable with this method.

Usage
SymbolNode$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

Other parser items: BinaryOpNode, FormulaNode, FunctionNode, GroupNode, Node, NumericNode, ParameterNode, RangeNode, StringNode, UnaryOpNode

Simulated dataset TESTING.DATASET 1

Description

Simulated dataset TESTING.DATASET 1, in a data.frame with 71 observations of 17 harmonized variables.

Details

Variable Description Type
ID Dummy data integer
CHARACTER Dummy data char
LOGICAL Dummy data logical
NA_VALUES Dummy data logical
NULL_VALUES Dummy data logical
INTEGER Dummy data integer
NON_NEGATIVE_INTEGER Dummy data integer
POSITIVE_INTEGER Dummy data integer
NEGATIVE_INTEGER Dummy data integer
NUMERIC Dummy data numeric
NON_NEGATIVE_NUMERIC Dummy data numeric
POSITIVE_NUMERIC Dummy data numeric
NEGATIVE_NUMERIC Dummy data numeric
FACTOR_CHARACTER Dummy data factor
FACTOR_INTEGER Dummy data factor
IDENTIFIER Dummy data integer
CATEGORY Dummy data integer

Simulated dataset TESTING.DATASET 2

Description

Simulated dataset TESTING.DATASET 2, in a data.frame with 71 observations of 17 harmonized variables.

Details

Variable Description Type
ID Dummy data integer
CHARACTER Dummy data char
LOGICAL Dummy data logical
NA_VALUES Dummy data logical
NULL_VALUES Dummy data logical
INTEGER Dummy data integer
NON_NEGATIVE_INTEGER Dummy data integer
POSITIVE_INTEGER Dummy data integer
NEGATIVE_INTEGER Dummy data integer
NUMERIC Dummy data numeric
NON_NEGATIVE_NUMERIC Dummy data numeric
POSITIVE_NUMERIC Dummy data numeric
NEGATIVE_NUMERIC Dummy data numeric
FACTOR_CHARACTER Dummy data factor
FACTOR_INTEGER Dummy data factor
IDENTIFIER Dummy data integer
CATEGORY Dummy data integer

Simulated dataset TESTING.DATASET 3

Description

Simulated dataset TESTING.DATASET 3, in a data.frame with 71 observations of 17 harmonized variables.

Details

Variable Description Type
ID Dummy data integer
CHARACTER Dummy data char
LOGICAL Dummy data logical
NA_VALUES Dummy data logical
NULL_VALUES Dummy data logical
INTEGER Dummy data integer
NON_NEGATIVE_INTEGER Dummy data integer
POSITIVE_INTEGER Dummy data integer
NEGATIVE_INTEGER Dummy data integer
NUMERIC Dummy data numeric
NON_NEGATIVE_NUMERIC Dummy data numeric
POSITIVE_NUMERIC Dummy data numeric
NEGATIVE_NUMERIC Dummy data numeric
FACTOR_CHARACTER Dummy data factor
FACTOR_INTEGER Dummy data factor
IDENTIFIER Dummy data integer
CATEGORY Dummy data integer

Parse an expression according to DataSHIELD syntax rules and returns an Abstract Syntaxic Tree (AST) node.

Description

Parse an expression according to DataSHIELD syntax rules and returns an Abstract Syntaxic Tree (AST) node.

Usage

testParse(expr, debug = FALSE)

Arguments

expr

Expression
debug

Parser debug logger activated

Value

An Abstract Syntaxic Tree node

Examples

## Not run: 
# a function call with a valid formula
ast <- testParse("someregression(D$height ~ D$diameter + D$length)")
# a function call with an invalid formula including a function call
testParse("someregression(D$height ~ D$diameter + poly(D$length,3,raw=TRUE))")

## End(Not run)

Unary operator AST node

Description

AST node that represents a unary operator (such as '-'), therefore having a single child node.

Super class

DSLite::Node -> UnaryOpNode

Methods

Public methods

Inherited methods

Method add_child()

One children

Usage
UnaryOpNode$add_child(val)
Arguments
val

Child Node

Method to_string()

Get the string representation of the UnaryOpNode

Usage
UnaryOpNode$to_string()

Method clone()

The objects of this class are cloneable with this method.

Usage
UnaryOpNode$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

See Also

Other parser items: BinaryOpNode, FormulaNode, FunctionNode, GroupNode, Node, NumericNode, ParameterNode, RangeNode, StringNode, SymbolNode