R/pca.h.R
In hyunsooseol/snowCluster: Multivariate Analysis
Defines functions
pca
Documented in
pca
# This file is automatically generated, you probably don't want to edit this
pcaOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"pcaOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
mode = "simple",
labels = NULL,
vars = NULL,
eigen = FALSE,
plot = FALSE,
plot1 = FALSE,
plot2 = FALSE,
vars1 = NULL,
facs = NULL,
plot3 = FALSE,
plot4 = FALSE,
width = 500,
height = 500,
width1 = 500,
height1 = 500,
width2 = 500,
height2 = 500,
width3 = 500,
height3 = 500,
width4 = 500,
height4 = 500, ...) {
super$initialize(
package="snowCluster",
name="pca",
requiresData=TRUE,
...)
private$..mode <- jmvcore::OptionList$new(
"mode",
mode,
options=list(
"simple",
"complex"),
default="simple")
private$..labels <- jmvcore::OptionVariable$new(
"labels",
labels,
suggested=list(
"nominal"),
permitted=list(
"id",
"factor"))
private$..vars <- jmvcore::OptionVariables$new(
"vars",
vars,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..eigen <- jmvcore::OptionBool$new(
"eigen",
eigen,
default=FALSE)
private$..plot <- jmvcore::OptionBool$new(
"plot",
plot,
default=FALSE)
private$..plot1 <- jmvcore::OptionBool$new(
"plot1",
plot1,
default=FALSE)
private$..plot2 <- jmvcore::OptionBool$new(
"plot2",
plot2,
default=FALSE)
private$..vars1 <- jmvcore::OptionVariables$new(
"vars1",
vars1,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..facs <- jmvcore::OptionVariable$new(
"facs",
facs,
suggested=list(
"nominal"),
permitted=list(
"factor"))
private$..plot3 <- jmvcore::OptionBool$new(
"plot3",
plot3,
default=FALSE)
private$..plot4 <- jmvcore::OptionBool$new(
"plot4",
plot4,
default=FALSE)
private$..width <- jmvcore::OptionInteger$new(
"width",
width,
default=500)
private$..height <- jmvcore::OptionInteger$new(
"height",
height,
default=500)
private$..width1 <- jmvcore::OptionInteger$new(
"width1",
width1,
default=500)
private$..height1 <- jmvcore::OptionInteger$new(
"height1",
height1,
default=500)
private$..width2 <- jmvcore::OptionInteger$new(
"width2",
width2,
default=500)
private$..height2 <- jmvcore::OptionInteger$new(
"height2",
height2,
default=500)
private$..width3 <- jmvcore::OptionInteger$new(
"width3",
width3,
default=500)
private$..height3 <- jmvcore::OptionInteger$new(
"height3",
height3,
default=500)
private$..width4 <- jmvcore::OptionInteger$new(
"width4",
width4,
default=500)
private$..height4 <- jmvcore::OptionInteger$new(
"height4",
height4,
default=500)
self$.addOption(private$..mode)
self$.addOption(private$..labels)
self$.addOption(private$..vars)
self$.addOption(private$..eigen)
self$.addOption(private$..plot)
self$.addOption(private$..plot1)
self$.addOption(private$..plot2)
self$.addOption(private$..vars1)
self$.addOption(private$..facs)
self$.addOption(private$..plot3)
self$.addOption(private$..plot4)
self$.addOption(private$..width)
self$.addOption(private$..height)
self$.addOption(private$..width1)
self$.addOption(private$..height1)
self$.addOption(private$..width2)
self$.addOption(private$..height2)
self$.addOption(private$..width3)
self$.addOption(private$..height3)
self$.addOption(private$..width4)
self$.addOption(private$..height4)
}),
active = list(
mode = function() private$..mode$value,
labels = function() private$..labels$value,
vars = function() private$..vars$value,
eigen = function() private$..eigen$value,
plot = function() private$..plot$value,
plot1 = function() private$..plot1$value,
plot2 = function() private$..plot2$value,
vars1 = function() private$..vars1$value,
facs = function() private$..facs$value,
plot3 = function() private$..plot3$value,
plot4 = function() private$..plot4$value,
width = function() private$..width$value,
height = function() private$..height$value,
width1 = function() private$..width1$value,
height1 = function() private$..height1$value,
width2 = function() private$..width2$value,
height2 = function() private$..height2$value,
width3 = function() private$..width3$value,
height3 = function() private$..height3$value,
width4 = function() private$..width4$value,
height4 = function() private$..height4$value),
private = list(
..mode = NA,
..labels = NA,
..vars = NA,
..eigen = NA,
..plot = NA,
..plot1 = NA,
..plot2 = NA,
..vars1 = NA,
..facs = NA,
..plot3 = NA,
..plot4 = NA,
..width = NA,
..height = NA,
..width1 = NA,
..height1 = NA,
..width2 = NA,
..height2 = NA,
..width3 = NA,
..height3 = NA,
..width4 = NA,
..height4 = NA)
)
pcaResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"pcaResults",
inherit = jmvcore::Group,
active = list(
instructions = function() private$.items[["instructions"]],
eigen = function() private$.items[["eigen"]],
plot = function() private$.items[["plot"]],
plot1 = function() private$.items[["plot1"]],
plot2 = function() private$.items[["plot2"]],
plot3 = function() private$.items[["plot3"]],
plot4 = function() private$.items[["plot4"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="PCA & Group plot",
refs="snowCluster")
self$add(jmvcore::Html$new(
options=options,
name="instructions",
title="Instructions",
visible=TRUE))
self$add(jmvcore::Table$new(
options=options,
name="eigen",
title="Eigenvalues",
visible="(eigen)",
clearWith=list(
"mode",
"vars",
"labels"),
columns=list(
list(
`name`="comp",
`title`="Component",
`type`="text"),
list(
`name`="eigen",
`title`="Eigenvalue",
`type`="number"),
list(
`name`="varProp",
`title`="% of Variance",
`type`="number"),
list(
`name`="varCum",
`title`="Cumulative %",
`type`="number"))))
self$add(jmvcore::Image$new(
options=options,
name="plot",
title="Variable Contributions",
requiresData=TRUE,
refs="factoextra",
visible="(plot)",
renderFun=".plot",
clearWith=list(
"mode",
"vars",
"labels",
"width",
"height")))
self$add(jmvcore::Image$new(
options=options,
name="plot1",
title="Individual Plot",
requiresData=TRUE,
refs="factoextra",
visible="(plot1)",
renderFun=".plot1",
clearWith=list(
"mode",
"vars",
"labels",
"width1",
"height1")))
self$add(jmvcore::Image$new(
options=options,
name="plot2",
title="Biplot",
requiresData=TRUE,
refs="factoextra",
visible="(plot2)",
renderFun=".plot2",
clearWith=list(
"mode",
"vars",
"labels",
"width2",
"height2")))
self$add(jmvcore::Image$new(
options=options,
name="plot3",
title="Individuals by groups",
requiresData=TRUE,
refs="factoextra",
visible="(plot3)",
renderFun=".plot3",
clearWith=list(
"mode",
"vars1",
"labels",
"width3",
"height3")))
self$add(jmvcore::Image$new(
options=options,
name="plot4",
title="PCA-Biplot",
requiresData=TRUE,
refs="factoextra",
visible="(plot4)",
renderFun=".plot4",
clearWith=list(
"mode",
"vars1",
"labels",
"width4",
"height4")))}))
pcaBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"pcaBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "snowCluster",
name = "pca",
version = c(1,0,0),
options = options,
results = pcaResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = FALSE,
requiresMissings = FALSE,
weightsSupport = 'auto')
}))
#' PCA & Group plot
#'
#'
#' @param data The data as a data frame.
#' @param mode .
#' @param labels .
#' @param vars .
#' @param eigen .
#' @param plot .
#' @param plot1 .
#' @param plot2 .
#' @param vars1 .
#' @param facs .
#' @param plot3 .
#' @param plot4 .
#' @param width .
#' @param height .
#' @param width1 .
#' @param height1 .
#' @param width2 .
#' @param height2 .
#' @param width3 .
#' @param height3 .
#' @param width4 .
#' @param height4 .
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$instructions} \tab \tab \tab \tab \tab a html \cr
#' \code{results$eigen} \tab \tab \tab \tab \tab a table \cr
#' \code{results$plot} \tab \tab \tab \tab \tab an image \cr
#' \code{results$plot1} \tab \tab \tab \tab \tab an image \cr
#' \code{results$plot2} \tab \tab \tab \tab \tab an image \cr
#' \code{results$plot3} \tab \tab \tab \tab \tab an image \cr
#' \code{results$plot4} \tab \tab \tab \tab \tab an image \cr
#' }
#'
#' Tables can be converted to data frames with \code{asDF} or \code{\link{as.data.frame}}. For example:
#'
#' \code{results$eigen$asDF}
#'
#' \code{as.data.frame(results$eigen)}
#'
#' @export
pca <- function(
data,
mode = "simple",
labels,
vars,
eigen = FALSE,
plot = FALSE,
plot1 = FALSE,
plot2 = FALSE,
vars1,
facs,
plot3 = FALSE,
plot4 = FALSE,
width = 500,
height = 500,
width1 = 500,
height1 = 500,
width2 = 500,
height2 = 500,
width3 = 500,
height3 = 500,
width4 = 500,
height4 = 500) {
if ( ! requireNamespace("jmvcore", quietly=TRUE))
stop("pca requires jmvcore to be installed (restart may be required)")
if ( ! missing(labels)) labels <- jmvcore::resolveQuo(jmvcore::enquo(labels))
if ( ! missing(vars)) vars <- jmvcore::resolveQuo(jmvcore::enquo(vars))
if ( ! missing(vars1)) vars1 <- jmvcore::resolveQuo(jmvcore::enquo(vars1))
if ( ! missing(facs)) facs <- jmvcore::resolveQuo(jmvcore::enquo(facs))
if (missing(data))
data <- jmvcore::marshalData(
parent.frame(),
`if`( ! missing(labels), labels, NULL),
`if`( ! missing(vars), vars, NULL),
`if`( ! missing(vars1), vars1, NULL),
`if`( ! missing(facs), facs, NULL))
for (v in facs) if (v %in% names(data)) data[[v]] <- as.factor(data[[v]])
options <- pcaOptions$new(
mode = mode,
labels = labels,
vars = vars,
eigen = eigen,
plot = plot,
plot1 = plot1,
plot2 = plot2,
vars1 = vars1,
facs = facs,
plot3 = plot3,
plot4 = plot4,
width = width,
height = height,
width1 = width1,
height1 = height1,
width2 = width2,
height2 = height2,
width3 = width3,
height3 = height3,
width4 = width4,
height4 = height4)
analysis <- pcaClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
hyunsooseol/snowCluster documentation built on April 5, 2025, 2:06 a.m.
R Package Documentation
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Defines functions pca
Documented in pca
# This file is automatically generated, you probably don't want to edit this
pcaOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"pcaOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
mode = "simple",
labels = NULL,
vars = NULL,
eigen = FALSE,
plot = FALSE,
plot1 = FALSE,
plot2 = FALSE,
vars1 = NULL,
facs = NULL,
plot3 = FALSE,
plot4 = FALSE,
width = 500,
height = 500,
width1 = 500,
height1 = 500,
width2 = 500,
height2 = 500,
width3 = 500,
height3 = 500,
width4 = 500,
height4 = 500, ...) {
super$initialize(
package="snowCluster",
name="pca",
requiresData=TRUE,
...)
private$..mode <- jmvcore::OptionList$new(
"mode",
mode,
options=list(
"simple",
"complex"),
default="simple")
private$..labels <- jmvcore::OptionVariable$new(
"labels",
labels,
suggested=list(
"nominal"),
permitted=list(
"id",
"factor"))
private$..vars <- jmvcore::OptionVariables$new(
"vars",
vars,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..eigen <- jmvcore::OptionBool$new(
"eigen",
eigen,
default=FALSE)
private$..plot <- jmvcore::OptionBool$new(
"plot",
plot,
default=FALSE)
private$..plot1 <- jmvcore::OptionBool$new(
"plot1",
plot1,
default=FALSE)
private$..plot2 <- jmvcore::OptionBool$new(
"plot2",
plot2,
default=FALSE)
private$..vars1 <- jmvcore::OptionVariables$new(
"vars1",
vars1,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..facs <- jmvcore::OptionVariable$new(
"facs",
facs,
suggested=list(
"nominal"),
permitted=list(
"factor"))
private$..plot3 <- jmvcore::OptionBool$new(
"plot3",
plot3,
default=FALSE)
private$..plot4 <- jmvcore::OptionBool$new(
"plot4",
plot4,
default=FALSE)
private$..width <- jmvcore::OptionInteger$new(
"width",
width,
default=500)
private$..height <- jmvcore::OptionInteger$new(
"height",
height,
default=500)
private$..width1 <- jmvcore::OptionInteger$new(
"width1",
width1,
default=500)
private$..height1 <- jmvcore::OptionInteger$new(
"height1",
height1,
default=500)
private$..width2 <- jmvcore::OptionInteger$new(
"width2",
width2,
default=500)
private$..height2 <- jmvcore::OptionInteger$new(
"height2",
height2,
default=500)
private$..width3 <- jmvcore::OptionInteger$new(
"width3",
width3,
default=500)
private$..height3 <- jmvcore::OptionInteger$new(
"height3",
height3,
default=500)
private$..width4 <- jmvcore::OptionInteger$new(
"width4",
width4,
default=500)
private$..height4 <- jmvcore::OptionInteger$new(
"height4",
height4,
default=500)
self$.addOption(private$..mode)
self$.addOption(private$..labels)
self$.addOption(private$..vars)
self$.addOption(private$..eigen)
self$.addOption(private$..plot)
self$.addOption(private$..plot1)
self$.addOption(private$..plot2)
self$.addOption(private$..vars1)
self$.addOption(private$..facs)
self$.addOption(private$..plot3)
self$.addOption(private$..plot4)
self$.addOption(private$..width)
self$.addOption(private$..height)
self$.addOption(private$..width1)
self$.addOption(private$..height1)
self$.addOption(private$..width2)
self$.addOption(private$..height2)
self$.addOption(private$..width3)
self$.addOption(private$..height3)
self$.addOption(private$..width4)
self$.addOption(private$..height4)
}),
active = list(
mode = function() private$..mode$value,
labels = function() private$..labels$value,
vars = function() private$..vars$value,
eigen = function() private$..eigen$value,
plot = function() private$..plot$value,
plot1 = function() private$..plot1$value,
plot2 = function() private$..plot2$value,
vars1 = function() private$..vars1$value,
facs = function() private$..facs$value,
plot3 = function() private$..plot3$value,
plot4 = function() private$..plot4$value,
width = function() private$..width$value,
height = function() private$..height$value,
width1 = function() private$..width1$value,
height1 = function() private$..height1$value,
width2 = function() private$..width2$value,
height2 = function() private$..height2$value,
width3 = function() private$..width3$value,
height3 = function() private$..height3$value,
width4 = function() private$..width4$value,
height4 = function() private$..height4$value),
private = list(
..mode = NA,
..labels = NA,
..vars = NA,
..eigen = NA,
..plot = NA,
..plot1 = NA,
..plot2 = NA,
..vars1 = NA,
..facs = NA,
..plot3 = NA,
..plot4 = NA,
..width = NA,
..height = NA,
..width1 = NA,
..height1 = NA,
..width2 = NA,
..height2 = NA,
..width3 = NA,
..height3 = NA,
..width4 = NA,
..height4 = NA)
)
pcaResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"pcaResults",
inherit = jmvcore::Group,
active = list(
instructions = function() private$.items[["instructions"]],
eigen = function() private$.items[["eigen"]],
plot = function() private$.items[["plot"]],
plot1 = function() private$.items[["plot1"]],
plot2 = function() private$.items[["plot2"]],
plot3 = function() private$.items[["plot3"]],
plot4 = function() private$.items[["plot4"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="PCA & Group plot",
refs="snowCluster")
self$add(jmvcore::Html$new(
options=options,
name="instructions",
title="Instructions",
visible=TRUE))
self$add(jmvcore::Table$new(
options=options,
name="eigen",
title="Eigenvalues",
visible="(eigen)",
clearWith=list(
"mode",
"vars",
"labels"),
columns=list(
list(
`name`="comp",
`title`="Component",
`type`="text"),
list(
`name`="eigen",
`title`="Eigenvalue",
`type`="number"),
list(
`name`="varProp",
`title`="% of Variance",
`type`="number"),
list(
`name`="varCum",
`title`="Cumulative %",
`type`="number"))))
self$add(jmvcore::Image$new(
options=options,
name="plot",
title="Variable Contributions",
requiresData=TRUE,
refs="factoextra",
visible="(plot)",
renderFun=".plot",
clearWith=list(
"mode",
"vars",
"labels",
"width",
"height")))
self$add(jmvcore::Image$new(
options=options,
name="plot1",
title="Individual Plot",
requiresData=TRUE,
refs="factoextra",
visible="(plot1)",
renderFun=".plot1",
clearWith=list(
"mode",
"vars",
"labels",
"width1",
"height1")))
self$add(jmvcore::Image$new(
options=options,
name="plot2",
title="Biplot",
requiresData=TRUE,
refs="factoextra",
visible="(plot2)",
renderFun=".plot2",
clearWith=list(
"mode",
"vars",
"labels",
"width2",
"height2")))
self$add(jmvcore::Image$new(
options=options,
name="plot3",
title="Individuals by groups",
requiresData=TRUE,
refs="factoextra",
visible="(plot3)",
renderFun=".plot3",
clearWith=list(
"mode",
"vars1",
"labels",
"width3",
"height3")))
self$add(jmvcore::Image$new(
options=options,
name="plot4",
title="PCA-Biplot",
requiresData=TRUE,
refs="factoextra",
visible="(plot4)",
renderFun=".plot4",
clearWith=list(
"mode",
"vars1",
"labels",
"width4",
"height4")))}))
pcaBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"pcaBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "snowCluster",
name = "pca",
version = c(1,0,0),
options = options,
results = pcaResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = FALSE,
requiresMissings = FALSE,
weightsSupport = 'auto')
}))
#' PCA & Group plot
#'
#'
#' @param data The data as a data frame.
#' @param mode .
#' @param labels .
#' @param vars .
#' @param eigen .
#' @param plot .
#' @param plot1 .
#' @param plot2 .
#' @param vars1 .
#' @param facs .
#' @param plot3 .
#' @param plot4 .
#' @param width .
#' @param height .
#' @param width1 .
#' @param height1 .
#' @param width2 .
#' @param height2 .
#' @param width3 .
#' @param height3 .
#' @param width4 .
#' @param height4 .
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$instructions} \tab \tab \tab \tab \tab a html \cr
#' \code{results$eigen} \tab \tab \tab \tab \tab a table \cr
#' \code{results$plot} \tab \tab \tab \tab \tab an image \cr
#' \code{results$plot1} \tab \tab \tab \tab \tab an image \cr
#' \code{results$plot2} \tab \tab \tab \tab \tab an image \cr
#' \code{results$plot3} \tab \tab \tab \tab \tab an image \cr
#' \code{results$plot4} \tab \tab \tab \tab \tab an image \cr
#' }
#'
#' Tables can be converted to data frames with \code{asDF} or \code{\link{as.data.frame}}. For example:
#'
#' \code{results$eigen$asDF}
#'
#' \code{as.data.frame(results$eigen)}
#'
#' @export
pca <- function(
data,
mode = "simple",
labels,
vars,
eigen = FALSE,
plot = FALSE,
plot1 = FALSE,
plot2 = FALSE,
vars1,
facs,
plot3 = FALSE,
plot4 = FALSE,
width = 500,
height = 500,
width1 = 500,
height1 = 500,
width2 = 500,
height2 = 500,
width3 = 500,
height3 = 500,
width4 = 500,
height4 = 500) {
if ( ! requireNamespace("jmvcore", quietly=TRUE))
stop("pca requires jmvcore to be installed (restart may be required)")
if ( ! missing(labels)) labels <- jmvcore::resolveQuo(jmvcore::enquo(labels))
if ( ! missing(vars)) vars <- jmvcore::resolveQuo(jmvcore::enquo(vars))
if ( ! missing(vars1)) vars1 <- jmvcore::resolveQuo(jmvcore::enquo(vars1))
if ( ! missing(facs)) facs <- jmvcore::resolveQuo(jmvcore::enquo(facs))
if (missing(data))
data <- jmvcore::marshalData(
parent.frame(),
`if`( ! missing(labels), labels, NULL),
`if`( ! missing(vars), vars, NULL),
`if`( ! missing(vars1), vars1, NULL),
`if`( ! missing(facs), facs, NULL))
for (v in facs) if (v %in% names(data)) data[[v]] <- as.factor(data[[v]])
options <- pcaOptions$new(
mode = mode,
labels = labels,
vars = vars,
eigen = eigen,
plot = plot,
plot1 = plot1,
plot2 = plot2,
vars1 = vars1,
facs = facs,
plot3 = plot3,
plot4 = plot4,
width = width,
height = height,
width1 = width1,
height1 = height1,
width2 = width2,
height2 = height2,
width3 = width3,
height3 = height3,
width4 = width4,
height4 = height4)
analysis <- pcaClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
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