58 lines
2.3 KiB
R
58 lines
2.3 KiB
R
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# These functions are not exported, so I won't create their documentation either.
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# I.e. it's not a mistake that the documentation below lacks the " ' " on each line.
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# Covariates
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#
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# Creates a covariate for use in the Java code. These functions don't need to
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# be directly run by a user, as loadData and train will detect, create and use
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# such covariate objects.
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#
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# @name covariates
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#
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# @param name The name of the covariate, that later values will be placed
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# under.
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# @return An internal rJava object for later internal use.
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# @keywords internal
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# @examples
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# # This is unnecessary for a user to do
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#
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# # Create a covariate
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# booleanCovariate <- Java_BooleanCovariate("x1")
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# factorCovariate <- Java_FactorCovariate("x2", c("cat", "dog", "mouse"))
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# numericCovariate <- Java_NumericCovariate("x3")
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#
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# # Call the approriate Java method
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# # The Java createValue method always takes in a String
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# value1 <- .jcall(booleanCovariate, "Lca/joeltherrien/randomforest/covariates/Covariate$Value;", "createValue", "true")
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# value2 <- .jcall(factorCovariate, "Lca/joeltherrien/randomforest/covariates/Covariate$Value;", "createValue", "dog")
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# value3 <- .jcall(numericCovariate, "Lca/joeltherrien/randomforest/covariates/Covariate$Value;", "createValue", "3.14")
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NULL
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# @rdname covariates
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Java_BooleanCovariate <- function(name, index){
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covariate <- .jnew(.class_BooleanCovariate, name, as.integer(index))
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covariate <- .jcast(covariate, .class_Object) # needed for later adding it into Java Lists
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return(covariate)
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}
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# @rdname covariates
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# @param levels The levels of the factor as a character vector
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Java_FactorCovariate <- function(name, index, levels){
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levelsArray <- .jarray(levels, makeResponse(.class_String))
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levelsList <- .jcall("java/util/Arrays", "Ljava/util/List;", "asList", .jcast(levelsArray, "[Ljava/lang/Object;"))
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covariate <- .jnew(.class_FactorCovariate, name, as.integer(index), levelsList)
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covariate <- .jcast(covariate, .class_Object) # needed for later adding it into Java Lists
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return(covariate)
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}
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# @rdname covariates
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Java_NumericCovariate <- function(name, index){
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covariate <- .jnew(.class_NumericCovariate, name, as.integer(index))
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covariate <- .jcast(covariate, .class_Object) # needed for later adding it into Java Lists
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return(covariate)
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}
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