OPERATOR-Object {RGMQL} | R Documentation

## OPERATOR object class constructor

### Description

This class constructor is used to create instances of OPERATOR object, to be used in GMQL functions that require operator on value.

### Usage

    META(value, type = NULL)

    NIL(type)

    SQRT(value)

### Arguments

`value` | string identifying name of metadata attribute
`type` | string identifying the type of the attribute value; it must be: INTEGER, DOUBLE or STRING. For NIL() function, only INTEGER and DOUBLE are allowed

### Details

- META: It prepares input parameter to be passed to library function meta, performing all the type conversions needed

- SQRT: It prepares input parameter to be passed to library function sqrt, performing all the type conversions needed

- NIL: It prepares input parameter to be passed to library function null, performing all the type conversions needed

### Value

Operator object

### Examples

    ## This statement initializes and runs the GMQL server for local execution
    ## and creation of results on disk. Then, with system.file() it defines
    ## the path to the folder "DATASET" in the subdirectory "example"
    ## of the package "RGMQL" and opens such folder as a GMQL dataset
    ## named "exp"

    init_gmql()
    test_path <- system.file("example", "DATASET", package = "RGMQL")
    exp = read_gmql(test_path)

    ## This statement allows to select, in all input samples, all those regions
    ## for which the region attribute score has a value which is greater
    ## than the metadata attribute value "avg_score" in their sample.

    data = filter(exp, r_predicate = score > META("avg_score"))

    ## This statement defines new numeric region attributes with "null" value.
    ## The syntax for creating a new attribute with null value is
    ## attribute_name = NULL(TYPE), where type may be INTEGER or DOUBLE.

    out = select(exp, regions_update = list(signal = NIL("INTEGER"),
        pvalue = NIL("DOUBLE")))

    ## This statement allows to build an output dataset named 'out' such that
    ## all the samples from the input dataset 'exp' are conserved,
    ## as well as their region attributes (and their values)
    ## and their metadata attributes (and their values).
    ## The new metadata attribute 'concSq' is added to all output samples
    ## with value correspondent to the mathematical squared root
    ## of the pre-existing metadata attribute 'concentration'.

    out = select(exp, metadata_update = list(concSq = SQRT("concentration")))

[Package RGMQL version 1.2.0 Index]