R/04_stat_qc_capability.R
In kenithgrey/rQC: Quality Control Charts for 'ggplot'
Defines functions
stat_QC_CAPA
stat_QC_cap_vlines
stat_QC_cap_vlabels
stat_QC_cap_hlines
stat_QC_cap_hlabels
stat_QC_cap_summary
stat_QC_Capability
Documented in
stat_QC_CAPA
stat_QC_Capability
stat_QC_cap_hlabels
stat_QC_cap_hlines
stat_QC_cap_summary
stat_QC_cap_vlabels
stat_QC_cap_vlines
##############################
# Copyright 2018 Kenith Grey #
##############################
# Copyright Notice --------------------------------------------------------
# This file is part of ggQC.
#
# ggQC is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# ggQC is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with ggQC. If not, see <http://www.gnu.org/licenses/>.
stat_QC_CAPABILITY <- ggplot2::ggproto("stat_QC_CAPABILITY", ggplot2::Stat,
compute_group = function(data, scales, n=1, USL=USL, LSL=LSL,
digits = 8, method = NULL, show = show,
geom.type=geom.type, direction = direction, type = type,
py=NA, px=NA){
# print(geom.type)
#print(digits)
if(method=="XmR"){
QC_Lines <- QC_Lines(data = data$x,method="XmR")
LCL <- QC_Lines[[1]]
center <- QC_Lines[[2]]
UCL <- QC_Lines[[3]]
Sigma <- QC_Lines$sigma
QC_CAP <- QC_Capability(data=data$x, LSL=LSL, USL = USL,
method="XmR", digits = 20)
#if(!is.na(type)) print(QC_CAP)
}else{
QC_Lines <- QC_Lines(data = data, value = "x", grouping = "QC.Subgroup",
n = 1, method=method)
LCL <- QC_Lines[[5]]
center <- QC_Lines[[6]]
UCL <- QC_Lines[[7]]
Sigma <- QC_Lines$sigma
QC_CAP <- QC_Capability(data=data, value="x", grouping = "QC.Subgroup",
LSL=LSL, USL = USL, method = method, digits = 20)
}
QCM <- data.frame(
label=c("LCL", "X", "UCL", "Sigma"),
values=c(LCL, center, UCL, Sigma))
QC_CAP <- rbind(QC_CAP, QCM)
QC_CAP <- transform(QC_CAP,
label = as.character(label),
values = round(as.numeric(values), digits)
)
# Takes care of vlines and vlabels ----------------------------------------
if(any(geom.type %in% c("vline", "label")) & direction == "v" & is.na(type) ){
vlines_df <- data.frame(xintercept = c(LSL,LCL, center, UCL, USL),
label = c("LSL", "LCL", "X", "UCL", "USL"),
x = c(LSL, LCL, center, UCL, USL),
y = c(Inf,Inf,Inf,Inf,Inf),
vjust = c(1,1,1,1,1),
hjust = c(0.5,0.5,0.5,0.5,0.5)
)
vlines_df <- vlines_df[vlines_df$label %in% show,]
return(vlines_df)
}
if(any(geom.type %in% c("hline", "label")) & direction == "h" & is.na(type)){
hlines_df <- data.frame(yintercept = c(LSL,LCL, center, UCL, USL),
label = c("LSL", "LCL", "X", "UCL", "USL"),
y = c(LSL, LCL, center, UCL, USL),
x = c(Inf,Inf,Inf,Inf,Inf),
vjust = c(.5,.5,.5,.5,.5),
hjust = c(1.1,1.1,1.1,1.1,1.1)
)
hlines_df <- hlines_df[hlines_df$label %in% show,]
return(hlines_df)
}
#print("hello")
hyphens <- paste0(rep("-",digits/2), collapse = "")
header <- paste0("---", hyphens, "[ Capability Data ]", hyphens, "---\n",collapse = "")
#print(header)
if(geom.type == "label" & type == "table"){
QC_CAP[1,1] <- "TOL (sigma)"
QC_CAP[2,1] <- "DNS (sigma)"
#print(QC_CAP)
QC_CAP$ABR <- substr(QC_CAP$label, 1,3)
if("all" %in% show || "ALL" %in% show){
#do nothing
}else{
QC_CAP <- QC_CAP[QC_CAP$ABR %in% show,]
QC_CAP <- QC_CAP[match(show, QC_CAP$ABR),]
}
capa <- paste0(header, paste0(QC_CAP$label,": " , QC_CAP$values, collapse = "\n"))
#print(capa)
#print(QC_CAP)
#print(show)
df <-
data.frame(
hjust = 1, vjust=0,
x = px,
y = py,
label=capa
)
#print(df)
# df <- df[df$label %in% show,]
return(df)
}
}
)
#' @title Generic Function for drawing QC capability information on plots
#' @description Generic Function for drawing QC capability information on plots
#' @param LSL numeric, Customer's lower specification limit
#' @param USL numeric, Customer's Upper specification limit
#' @param method string, calling the following methods:
#' \itemize{
#' \item \bold{Individuals Charts}: XmR,
#' \item \bold{Studentized Charts}: xBar.rBar, xBar.rMedian, xBar.sBar, xMedian.rBar,
#' xMedian.rMedian
#' }
#' @param show -
#' @param digits -
#' @param na.rm -
#' @param direction -
#' @param type -
#' @inheritParams ggplot2::stat_identity
#' @return ggplot control charts.
#' @examples
#' # Load Libraries ----------------------------------------------------------
#' require(ggQC)
#' require(ggplot2)
#'
#'
#' # Setup Data --------------------------------------------------------------
#' set.seed(5555)
#' Process1 <- data.frame(ProcessID = as.factor(rep(1,100)),
#' Value = rnorm(100,10,1),
#' Subgroup = rep(1:20, each=5),
#' Process_run_id = 1:100)
#' set.seed(5556)
#' Process2 <- data.frame(ProcessID = as.factor(rep(2,100)),
#' Value = rnorm(100,20, 1),
#' Subgroup = rep(1:10, each=10),
#' Process_run_id = 101:200)
#'
#' df <- rbind(Process1, Process2)
#'
#' ######################
#' ## Example 1 XmR ##
#' ######################
#' ##You may need to use the r-studio Zoom for these plots or make the size of the
#' ##stat_QC_cap_summary smaller with size = some number"
#'
#' method <- "XmR"
#'
#' # Normal Histogram XmR --------------------------------------------------------
#'
#' EX1.1 <- ggplot(df[df$ProcessID == 1,], aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_histogram(binwidth = 1, color="purple") +
#' geom_hline(yintercept=0, color="grey") +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, show=c("X", "LSL", "USL"), method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, show=c("X", "LSL", "USL"), method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),
#' #show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=2, size=4) +
#' scale_x_continuous(expand = expand_scale(mult = c(0.15,.8))) +
#' ylim(0,45)
#' #Ex1.1
#'
#' # Facet Histogram XmR -----------------------------------------------------
#'
#' EX1.2 <- ggplot(df[order(df$Process_run_id),],
#' aes(x=Value, QC.Subgroup=Subgroup, color=ProcessID)) +
#' geom_histogram(binwidth = 1) +
#' geom_hline(yintercept=0, color="grey") +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),#show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=4, size=4) +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8))) +
#' facet_grid(.~ProcessID) + ylim(0,45)
#' #EX1.2
#'
#' # Facet Density Plot XmR -------------------------------------------------
#'
#' EX1.3 <- ggplot(df[df$ProcessID == 1,], aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_density(bw = .4, fill="purple", trim=TRUE) +
#' geom_hline(yintercept=0, color="grey") +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, show=c("X", "LSL", "USL"), method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, show=c("X", "LSL", "USL"), method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),
#' #show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=2, size=4) +
#'
#' scale_x_continuous(expand = expand_scale(mult = c(0.15,.8))) + ylim(0,.5)
#' #EX1.3
#'
#' # Facet Density Plot XmR --------------------------------------------------
#'
#' EX1.4 <- ggplot(df[order(df$Process_run_id),],
#' aes(x=Value, QC.Subgroup=Subgroup, color=ProcessID)) +
#' geom_density(bw = .4, fill="grey", trim=TRUE ) +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method, #py=.3,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),
#' #show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=4, size=4) +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8))) +
#' # geom_hline(yintercept=0, color="black") +
#' facet_grid(.~ProcessID) + ylim(0,.5)
#' #EX1.4
#'
#'
#' ########################################
#' ## Example 2: xBar.rBar or xBar.sBar ##
#' ########################################
#'
#' method <- "xBar.rBar" #Alternativly Use "xBar.sBar" if desired
#'
#'
#' # Single Histogram xBar.rBar ----------------------------------------------
#'
#' EX2.1 <- ggplot(df[df$ProcessID==1,], aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_histogram(binwidth = 1) +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method, #py=.3,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),
#' #show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=4, size=4) +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8))) #+
#' #EX2.1
#'
#'
#' # Faceted Histogram xBar.rBar ---------------------------------------------
#'
#' EX2.2 <- ggplot(df, aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_histogram(binwidth = 1) +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method, #py=.3,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),
#' #show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=4, size=4) +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8)))+
#' facet_grid(.~ProcessID, scales="free_x")
#' #EX2.2
#'
#' # Single Density xBar.rBar ----------------------------------------------
#'
#' EX2.3 <- ggplot(df[df$ProcessID==1,], aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_density(bw = .4, fill="grey", alpha=.4) +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method, #py=.3,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),
#' #show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=4, size=4) +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8))) #+
#' #EX2.3
#'
#' # Faceted Density xBar.rBar ---------------------------------------------
#'
#' EX2.4 <- ggplot(df, aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_density(bw = .4, fill="grey", alpha=.4) +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method, #py=.3,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),
#' #show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=4, size=4) +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8)))+
#' facet_grid(.~ProcessID, scales="free_x")
#' #EX2.4
#'
#'
#' ###############################
#' ## Example 3: xBar.rMedian ##
#' ###############################
#'
#' ## Plots involving medians should give warning: "median based QC methods represent
#' ## at best *potential* process capability"
#'
#' ##These plot work the same as in examples 2.X; below is an example.
#'
#' method <- "xBar.rMedian"
#' EX3.1 <- ggplot(df[order(df$Process_run_id),], aes(x=Value, QC.Subgroup=Run)) +
#' geom_histogram(binwidth = 1) +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method, #py=.3,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),
#' #show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=4, size=4) +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8)))
#'#EX3.1
stat_QC_CAPA <- function(
LSL, USL, method="xBar.rBar",
digits=1,
mapping = NULL, data = NULL,
geom = "vline",
position = "identity", na.rm = FALSE,
show.legend = NA, inherit.aes = TRUE,
show = c("LSL","USL"), direction="v",
type = NA, ...) {
if(!method %in% c("xBar.rBar", "xBar.rMedian", "xBar.sBar",
"xMedian.rBar", "xMedian.rMedian", "XmR")){
stop("Error: This feature only works with the following methods
xBar.rBar, xBar.rMedian, xBar.sBar xMedian.rBar, xMedian.rMedian, XmR")
}
if(method %in% c("xBar.rMedian", "xMedian.rBar", "xMedian.rMedian")){
warning("median based QC methods represent at best *potential* process capability", call. = F)
}
#Lines, #Lables #Table
ggplot2::layer(
stat = stat_QC_CAPABILITY, data = data, mapping = mapping,
geom = geom, position = position, show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(na.rm = na.rm, n=1, digits=digits,
method=method, USL=USL, LSL=LSL,
show=show, geom.type = geom,
direction = direction, type=type,
...)
)
}
#' @export
#' @title Vertical Line Capability Stat
#' @description Draws Vertical Capability Stats
#' @inheritParams stat_QC_CAPA
#' @param show vector, indicating which lines to draw ie., c("LCL", "LSL", "X", "USL", "UCL")
#' \itemize{
#' \item \bold{LCL}: Lower Control Limit
#' \item \bold{LSL}: Lower Specification Limit
#' \item \bold{X}: Process Center
#' \item \bold{USL}: Upper Specification Limit
#' \item \bold{UCL}: Upper Control Limit
#' }
#' @inheritParams ggplot2::stat_identity
#' @return vertical lines for histogram and density plots.
#' @inherit stat_QC_CAPA examples
#'
stat_QC_cap_vlines <- function(
LSL, USL, method="xBar.rBar",
show = c("LSL","USL"),
mapping = NULL, data = NULL,
inherit.aes = TRUE, ...){
stat_QC_CAPA(
LSL=LSL, USL=USL, method=method,
mapping = mapping, data = data,
geom = "vline",
position = "identity", na.rm = FALSE,
show.legend = NA, inherit.aes = inherit.aes,
show = show, direction="v",
type = NA, ...)
}
#' @export
#' @title Vertical Label Capability Stat
#' @description Draws Vertical Lables on Vertical Capability lines
#' @inheritParams stat_QC_CAPA
#' @param show vector, indicating which lines to draw ie., c("LCL", "LSL", "X", "USL", "UCL")
#' \itemize{
#' \item \bold{LCL}: Lower Control Limit
#' \item \bold{LSL}: Lower Specification Limit
#' \item \bold{X}: Process Center
#' \item \bold{USL}: Upper Specification Limit
#' \item \bold{UCL}: Upper Control Limit
#' }
#' @inheritParams ggplot2::stat_identity
#' @return vertical lines for histogram and density plots.
#' @inherit stat_QC_CAPA examples
#'
stat_QC_cap_vlabels <- function(
LSL, USL, method="xBar.rBar",
show = c("LSL","USL"),
mapping = NULL, data = NULL,
inherit.aes = TRUE, ...){
stat_QC_CAPA(
LSL=LSL, USL=USL, method=method,
mapping = mapping, data = data,
geom = "label",
position = "identity", na.rm = FALSE,
show.legend = NA, inherit.aes = inherit.aes,
show = show, direction="v",
type = NA, ...)
}
#' @export
#' @title horizontal Line Capability Stat
#' @description Draws horizontal Capability Lines
#' @inheritParams stat_QC_CAPA
#' @param show vector, indicating which lines to draw ie., c("LCL", "LSL", "X", "USL", "UCL")
#' \itemize{
#' \item \bold{LCL}: Lower Control Limit
#' \item \bold{LSL}: Lower Specification Limit
#' \item \bold{X}: Process Center
#' \item \bold{USL}: Upper Specification Limit
#' \item \bold{UCL}: Upper Control Limit
#' }
#' @inheritParams ggplot2::stat_identity
#' @return horizontal lines for histogram and density plots.
#' @inherit stat_QC_CAPA examples
#'
stat_QC_cap_hlines <- function(
LSL, USL, method="xBar.rBar",
show = c("LSL","USL"),
mapping = NULL, data = NULL,
inherit.aes = TRUE, ...){
stat_QC_CAPA(
LSL=LSL, USL=USL, method=method,
mapping = mapping, data = data,
geom = "hline",
position = "identity", na.rm = FALSE,
show.legend = NA, inherit.aes = inherit.aes,
show = show, direction="h",
type = NA, ...)
}
#' @export
#' @title horizontal Label Capability Stat
#' @description Draws horizontal Lables on horizontal Capability lines
#' @inheritParams stat_QC_CAPA
#' @param show vector, indicating which lines to draw ie., c("LCL", "LSL", "X", "USL", "UCL")
#' \itemize{
#' \item \bold{LCL}: Lower Control Limit
#' \item \bold{LSL}: Lower Specification Limit
#' \item \bold{X}: Process Center
#' \item \bold{USL}: Upper Specification Limit
#' \item \bold{UCL}: Upper Control Limit
#' }
#' @inheritParams ggplot2::stat_identity
#' @return horizontal lines for histogram and density plots.
#' @inherit stat_QC_CAPA examples
#'
stat_QC_cap_hlabels <- function(
LSL, USL, method="xBar.rBar",
show = c("LSL","USL"),
mapping = NULL, data = NULL,
inherit.aes = TRUE, ...){
stat_QC_CAPA(
LSL=LSL, USL=USL, method=method,
mapping = mapping, data = data,
geom = "label",
position = "identity", na.rm = FALSE,
show.legend = NA, inherit.aes = inherit.aes,
show = show, direction="h",
type = NA, ...)
}
#' @export
#' @title horizontal Label Capability Stat
#' @description Draws horizontal Lables on horizontal Capability lines
#' @inheritParams stat_QC_CAPA
#' @param show vector, indicating which lines to draw ie.,
#' c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk", "LCL", "X", "UCL", "Sig").
#' The order given in the vector is the order presented in the graph.
#' \itemize{
#' \item \bold{TOL}: Tolerance in Sigma Units (USL-LSL)/sigma
#' \item \bold{DNS}: Distance to Nearest Specification Limit in Simga Units
#' \item \bold{Cp}: Cp (Within)
#' \item \bold{Cpk}: Cpk (Within)
#' \item \bold{Pp}: Pp (Between)
#' \item \bold{Ppk}: Ppk (Between)
#' \item \bold{LCL}: Lower Control Limit
#' \item \bold{X}: Process Center
#' \item \bold{UCL}: Upper Control Limit
#' \item \bold{Sig}: Sigma from control charts
#' }
#' @param px numeric, x position for table. Use Inf to force label to x-limit.
#' @param py numeric, y position for table. Use Inf to force label to y-limits. May also need vjust parameter.
#' @param digits integer, how many digits to report.
#' @inheritParams ggplot2::stat_identity
#' @return horizontal lines for histogram and density plots.
#' @inherit stat_QC_CAPA examples
stat_QC_cap_summary <- function(
LSL, USL, method="xBar.rBar", px=Inf, py= -Inf,
show = c("Cp", "Cpk", "Pp", "Ppk"),
digits=8,
mapping = NULL, data = NULL,
inherit.aes = TRUE, ...){
stat_QC_CAPA(
LSL=LSL, USL=USL, method=method,
digits=digits,
mapping = mapping, data = data,
geom = "label",
position = "identity", na.rm = FALSE,
show.legend = NA, inherit.aes = inherit.aes,
show = show, direction=NA,
type = "table", px=px, py=py, ...)
}
#' @export
#' @title Auto QC Capability Stat Function
#' @description Draws lines, lables and summary statistics. Works best with histogram and density plots.
#' @inheritParams stat_QC_CAPA
#' @param show.lines vector, indicating which lines to draw ie., c("LCL", "LSL", "X", "USL", "UCL")
#' \itemize{
#' \item \bold{LCL}: Lower Control Limit
#' \item \bold{LSL}: Lower Specification Limit
#' \item \bold{X}: Process Center
#' \item \bold{USL}: Upper Specification Limit
#' \item \bold{UCL}: Upper Control Limit
#' }
#' @param line.direction string "v" or "h", specifies which direction to draw lines.
#' @param show.line.labels boolean, if TRUE then draw.
#' @param line.label.size numeric, control the size of the line labels.
#' @param show.cap.summary vector, indicating which lines to draw ie.,
#' c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk", "LCL", "X", "UCL", "Sig").
#' The order given in the vector is the order presented in the graph.
#' \itemize{
#' \item \bold{TOL}: Tolerance in Sigma Units (USL-LSL)/sigma
#' \item \bold{DNS}: Distance to Nearest Specification Limit in Simga Units
#' \item \bold{Cp}: Cp (Within)
#' \item \bold{Cpk}: Cpk (Within)
#' \item \bold{Pp}: Pp (Between)
#' \item \bold{Ppk}: Ppk (Between)
#' \item \bold{LCL}: Lower Control Limit
#' \item \bold{X}: Process Center
#' \item \bold{UCL}: Upper Control Limit
#' \item \bold{Sig}: Sigma from control charts
#' }
#' @param cap.summary.size numeric, control the size/scale of the summary text box.
#' @param px numeric, x position for summary text box. Use Inf to force label to x-limit.
#' @param py numeric, y position for summary text box. Use Inf to force label to y-limits. May also need vjust parameter.
#' @param digits integer, how many digits to report.
#' @inheritParams ggplot2::stat_identity
#' @return capability layer for histogram and density plots.
#' @seealso for more control over lines, labels, and capability data see the following functions:
#'\itemize{
#' \item \code{\link{stat_QC_cap_vlabels}}
#' \item \code{\link{stat_QC_cap_hlabels}}
#' \item \code{\link{stat_QC_cap_vlines}}
#' \item \code{\link{stat_QC_cap_hlines}}
#' \item \code{\link{stat_QC_cap_summary}}
#'}
#' @examples
#' # Load Libraries ----------------------------------------------------------
#' require(ggQC)
#' require(ggplot2)
#' # Setup Data --------------------------------------------------------------
#' set.seed(5555)
#' Process1 <- data.frame(ProcessID = as.factor(rep(1,100)),
#' Value = rnorm(100,10,1),
#' Subgroup = rep(1:20, each=5),
#' Process_run_id = 1:100)
#' set.seed(5556)
#' Process2 <- data.frame(ProcessID = as.factor(rep(2,100)),
#' Value = rnorm(100,20, 1),
#' Subgroup = rep(1:10, each=10),
#' Process_run_id = 101:200)
#' df <- rbind(Process1, Process2)
#'
#' ######################
#' ## Example 1 XmR ##
#' ######################
#'
#' ##You may need to use the r-studio Zoom for these plots or make the size of the
#' ##stat_QC_cap_summary smaller with size = some number"
#'
#' # Normal Histogram XmR --------------------------------------------------------
#' EX1.1 <- ggplot(df[df$ProcessID == 1,], aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_histogram(binwidth = 1, color="purple") +
#' geom_hline(yintercept=0, color="grey") +
#' stat_QC_Capability(LSL=5, USL=15, show.cap.summary = "all", method="XmR") +
#' scale_x_continuous(expand = expand_scale(mult = c(0.15,.8))) +
#' ylim(0,45)
#' #Ex1.1
#'
#' # Facet Histogram XmR -----------------------------------------------------
#' EX1.2 <- ggplot(df[order(df$Process_run_id),],
#' aes(x=Value, QC.Subgroup=Subgroup, color=ProcessID)) +
#' geom_histogram(binwidth = 1) +
#' geom_hline(yintercept=0, color="grey") +
#' stat_QC_Capability(LSL=5, USL=15, show.cap.summary = "all", method="XmR") +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8))) +
#' facet_grid(.~ProcessID, scales = "free_x") + ylim(0,45)
#' #EX1.2
#'
#' # Normal Density XmR --------------------------------------------------------
#' EX1.3 <- ggplot(df[df$ProcessID == 1,], aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_density(bw = .4, fill="purple", trim=TRUE) +
#' geom_hline(yintercept=0, color="grey") +
#' stat_QC_Capability(LSL=5, USL=15, show.cap.summary = "all", method="XmR") +
#' scale_x_continuous(expand = expand_scale(mult = c(0.15,.8))) + ylim(0,.5)
#' #EX1.3
#'
#' ########################################
#' ## Example 2: xBar.rBar or xBar.sBar ##
#' ########################################
#' # Single Histogram xBar.rBar ----------------------------------------------
#' EX2.1 <- ggplot(df[df$ProcessID==1,], aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_histogram(binwidth = 1) +
#' stat_QC_Capability(LSL=5, USL=15, method="xBar.rBar") +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8))) #+
#' #EX2.1
stat_QC_Capability <- function(
LSL, USL, method = "xBar.rBar",
show.lines = c("LSL","USL"),
line.direction = "v",
show.line.labels = TRUE,
line.label.size = 3,
show.cap.summary = c("Cp", "Cpk", "Pp", "Ppk"),
cap.summary.size = 4,
px=Inf, py= -Inf,
digits = 3){
if(!method %in% c("xBar.rBar", "xBar.rMedian", "xBar.sBar",
"xMedian.rBar", "xMedian.rMedian", "XmR")){
stop("Error: This feature only works with the following methods
xBar.rBar, xBar.rMedian, xBar.sBar xMedian.rBar, xMedian.rMedian, XmR")
}
if(line.direction == "v"){
theLines <- stat_QC_cap_vlines(LSL = LSL, USL=USL, method = method,
show=show.lines)
theLabels <- stat_QC_cap_vlabels(LSL = LSL, USL=USL, method = method,
show=show.lines, size=line.label.size)
}else if(line.direction == "h"){
theLines <- stat_QC_cap_hlines(LSL = LSL, USL=USL, method = method,
show=show.lines)
theLabels <- stat_QC_cap_hlabels(LSL = LSL, USL=USL, method = method,
show=show.lines, size=line.label.size)
}
if(any(show.cap.summary %in% c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk", "LCL", "X", "UCL", "Sig", "all", "ALL"))){
theSUMMARY <- stat_QC_cap_summary(LSL = LSL, USL = USL, method = method,
show = show.cap.summary, digits = digits,
px = px, py=py, size=cap.summary.size)
}else{
theSUMMARY <- NULL
}
if(!show.line.labels){
theLabels <- NULL
}
return(list(theLines, theLabels, theSUMMARY))
}
kenithgrey/rQC documentation built on May 20, 2019, 9:04 a.m.
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Defines functions stat_QC_CAPA stat_QC_cap_vlines stat_QC_cap_vlabels stat_QC_cap_hlines stat_QC_cap_hlabels stat_QC_cap_summary stat_QC_Capability
Documented in stat_QC_CAPA stat_QC_Capability stat_QC_cap_hlabels stat_QC_cap_hlines stat_QC_cap_summary stat_QC_cap_vlabels stat_QC_cap_vlines
##############################
# Copyright 2018 Kenith Grey #
##############################
# Copyright Notice --------------------------------------------------------
# This file is part of ggQC.
#
# ggQC is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# ggQC is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with ggQC. If not, see <http://www.gnu.org/licenses/>.
stat_QC_CAPABILITY <- ggplot2::ggproto("stat_QC_CAPABILITY", ggplot2::Stat,
compute_group = function(data, scales, n=1, USL=USL, LSL=LSL,
digits = 8, method = NULL, show = show,
geom.type=geom.type, direction = direction, type = type,
py=NA, px=NA){
# print(geom.type)
#print(digits)
if(method=="XmR"){
QC_Lines <- QC_Lines(data = data$x,method="XmR")
LCL <- QC_Lines[[1]]
center <- QC_Lines[[2]]
UCL <- QC_Lines[[3]]
Sigma <- QC_Lines$sigma
QC_CAP <- QC_Capability(data=data$x, LSL=LSL, USL = USL,
method="XmR", digits = 20)
#if(!is.na(type)) print(QC_CAP)
}else{
QC_Lines <- QC_Lines(data = data, value = "x", grouping = "QC.Subgroup",
n = 1, method=method)
LCL <- QC_Lines[[5]]
center <- QC_Lines[[6]]
UCL <- QC_Lines[[7]]
Sigma <- QC_Lines$sigma
QC_CAP <- QC_Capability(data=data, value="x", grouping = "QC.Subgroup",
LSL=LSL, USL = USL, method = method, digits = 20)
}
QCM <- data.frame(
label=c("LCL", "X", "UCL", "Sigma"),
values=c(LCL, center, UCL, Sigma))
QC_CAP <- rbind(QC_CAP, QCM)
QC_CAP <- transform(QC_CAP,
label = as.character(label),
values = round(as.numeric(values), digits)
)
# Takes care of vlines and vlabels ----------------------------------------
if(any(geom.type %in% c("vline", "label")) & direction == "v" & is.na(type) ){
vlines_df <- data.frame(xintercept = c(LSL,LCL, center, UCL, USL),
label = c("LSL", "LCL", "X", "UCL", "USL"),
x = c(LSL, LCL, center, UCL, USL),
y = c(Inf,Inf,Inf,Inf,Inf),
vjust = c(1,1,1,1,1),
hjust = c(0.5,0.5,0.5,0.5,0.5)
)
vlines_df <- vlines_df[vlines_df$label %in% show,]
return(vlines_df)
}
if(any(geom.type %in% c("hline", "label")) & direction == "h" & is.na(type)){
hlines_df <- data.frame(yintercept = c(LSL,LCL, center, UCL, USL),
label = c("LSL", "LCL", "X", "UCL", "USL"),
y = c(LSL, LCL, center, UCL, USL),
x = c(Inf,Inf,Inf,Inf,Inf),
vjust = c(.5,.5,.5,.5,.5),
hjust = c(1.1,1.1,1.1,1.1,1.1)
)
hlines_df <- hlines_df[hlines_df$label %in% show,]
return(hlines_df)
}
#print("hello")
hyphens <- paste0(rep("-",digits/2), collapse = "")
header <- paste0("---", hyphens, "[ Capability Data ]", hyphens, "---\n",collapse = "")
#print(header)
if(geom.type == "label" & type == "table"){
QC_CAP[1,1] <- "TOL (sigma)"
QC_CAP[2,1] <- "DNS (sigma)"
#print(QC_CAP)
QC_CAP$ABR <- substr(QC_CAP$label, 1,3)
if("all" %in% show || "ALL" %in% show){
#do nothing
}else{
QC_CAP <- QC_CAP[QC_CAP$ABR %in% show,]
QC_CAP <- QC_CAP[match(show, QC_CAP$ABR),]
}
capa <- paste0(header, paste0(QC_CAP$label,": " , QC_CAP$values, collapse = "\n"))
#print(capa)
#print(QC_CAP)
#print(show)
df <-
data.frame(
hjust = 1, vjust=0,
x = px,
y = py,
label=capa
)
#print(df)
# df <- df[df$label %in% show,]
return(df)
}
}
)
#' @title Generic Function for drawing QC capability information on plots
#' @description Generic Function for drawing QC capability information on plots
#' @param LSL numeric, Customer's lower specification limit
#' @param USL numeric, Customer's Upper specification limit
#' @param method string, calling the following methods:
#' \itemize{
#' \item \bold{Individuals Charts}: XmR,
#' \item \bold{Studentized Charts}: xBar.rBar, xBar.rMedian, xBar.sBar, xMedian.rBar,
#' xMedian.rMedian
#' }
#' @param show -
#' @param digits -
#' @param na.rm -
#' @param direction -
#' @param type -
#' @inheritParams ggplot2::stat_identity
#' @return ggplot control charts.
#' @examples
#' # Load Libraries ----------------------------------------------------------
#' require(ggQC)
#' require(ggplot2)
#'
#'
#' # Setup Data --------------------------------------------------------------
#' set.seed(5555)
#' Process1 <- data.frame(ProcessID = as.factor(rep(1,100)),
#' Value = rnorm(100,10,1),
#' Subgroup = rep(1:20, each=5),
#' Process_run_id = 1:100)
#' set.seed(5556)
#' Process2 <- data.frame(ProcessID = as.factor(rep(2,100)),
#' Value = rnorm(100,20, 1),
#' Subgroup = rep(1:10, each=10),
#' Process_run_id = 101:200)
#'
#' df <- rbind(Process1, Process2)
#'
#' ######################
#' ## Example 1 XmR ##
#' ######################
#' ##You may need to use the r-studio Zoom for these plots or make the size of the
#' ##stat_QC_cap_summary smaller with size = some number"
#'
#' method <- "XmR"
#'
#' # Normal Histogram XmR --------------------------------------------------------
#'
#' EX1.1 <- ggplot(df[df$ProcessID == 1,], aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_histogram(binwidth = 1, color="purple") +
#' geom_hline(yintercept=0, color="grey") +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, show=c("X", "LSL", "USL"), method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, show=c("X", "LSL", "USL"), method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),
#' #show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=2, size=4) +
#' scale_x_continuous(expand = expand_scale(mult = c(0.15,.8))) +
#' ylim(0,45)
#' #Ex1.1
#'
#' # Facet Histogram XmR -----------------------------------------------------
#'
#' EX1.2 <- ggplot(df[order(df$Process_run_id),],
#' aes(x=Value, QC.Subgroup=Subgroup, color=ProcessID)) +
#' geom_histogram(binwidth = 1) +
#' geom_hline(yintercept=0, color="grey") +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),#show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=4, size=4) +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8))) +
#' facet_grid(.~ProcessID) + ylim(0,45)
#' #EX1.2
#'
#' # Facet Density Plot XmR -------------------------------------------------
#'
#' EX1.3 <- ggplot(df[df$ProcessID == 1,], aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_density(bw = .4, fill="purple", trim=TRUE) +
#' geom_hline(yintercept=0, color="grey") +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, show=c("X", "LSL", "USL"), method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, show=c("X", "LSL", "USL"), method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),
#' #show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=2, size=4) +
#'
#' scale_x_continuous(expand = expand_scale(mult = c(0.15,.8))) + ylim(0,.5)
#' #EX1.3
#'
#' # Facet Density Plot XmR --------------------------------------------------
#'
#' EX1.4 <- ggplot(df[order(df$Process_run_id),],
#' aes(x=Value, QC.Subgroup=Subgroup, color=ProcessID)) +
#' geom_density(bw = .4, fill="grey", trim=TRUE ) +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method, #py=.3,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),
#' #show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=4, size=4) +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8))) +
#' # geom_hline(yintercept=0, color="black") +
#' facet_grid(.~ProcessID) + ylim(0,.5)
#' #EX1.4
#'
#'
#' ########################################
#' ## Example 2: xBar.rBar or xBar.sBar ##
#' ########################################
#'
#' method <- "xBar.rBar" #Alternativly Use "xBar.sBar" if desired
#'
#'
#' # Single Histogram xBar.rBar ----------------------------------------------
#'
#' EX2.1 <- ggplot(df[df$ProcessID==1,], aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_histogram(binwidth = 1) +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method, #py=.3,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),
#' #show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=4, size=4) +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8))) #+
#' #EX2.1
#'
#'
#' # Faceted Histogram xBar.rBar ---------------------------------------------
#'
#' EX2.2 <- ggplot(df, aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_histogram(binwidth = 1) +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method, #py=.3,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),
#' #show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=4, size=4) +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8)))+
#' facet_grid(.~ProcessID, scales="free_x")
#' #EX2.2
#'
#' # Single Density xBar.rBar ----------------------------------------------
#'
#' EX2.3 <- ggplot(df[df$ProcessID==1,], aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_density(bw = .4, fill="grey", alpha=.4) +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method, #py=.3,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),
#' #show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=4, size=4) +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8))) #+
#' #EX2.3
#'
#' # Faceted Density xBar.rBar ---------------------------------------------
#'
#' EX2.4 <- ggplot(df, aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_density(bw = .4, fill="grey", alpha=.4) +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method, #py=.3,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),
#' #show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=4, size=4) +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8)))+
#' facet_grid(.~ProcessID, scales="free_x")
#' #EX2.4
#'
#'
#' ###############################
#' ## Example 3: xBar.rMedian ##
#' ###############################
#'
#' ## Plots involving medians should give warning: "median based QC methods represent
#' ## at best *potential* process capability"
#'
#' ##These plot work the same as in examples 2.X; below is an example.
#'
#' method <- "xBar.rMedian"
#' EX3.1 <- ggplot(df[order(df$Process_run_id),], aes(x=Value, QC.Subgroup=Run)) +
#' geom_histogram(binwidth = 1) +
#' stat_QC_cap_vlines(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_vlabels(LSL = 5, USL = 15, method=method) +
#' stat_QC_cap_summary(LSL = 5, USL = 15, method=method, #py=.3,
#' #show="ALL",
#' #show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk",
#' # "LCL", "X", "UCL", "Sig"),
#' #show=c("Sig","TOL", "DNS"),
#' show=c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk"),
#' color="black", digits=4, size=4) +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8)))
#'#EX3.1
stat_QC_CAPA <- function(
LSL, USL, method="xBar.rBar",
digits=1,
mapping = NULL, data = NULL,
geom = "vline",
position = "identity", na.rm = FALSE,
show.legend = NA, inherit.aes = TRUE,
show = c("LSL","USL"), direction="v",
type = NA, ...) {
if(!method %in% c("xBar.rBar", "xBar.rMedian", "xBar.sBar",
"xMedian.rBar", "xMedian.rMedian", "XmR")){
stop("Error: This feature only works with the following methods
xBar.rBar, xBar.rMedian, xBar.sBar xMedian.rBar, xMedian.rMedian, XmR")
}
if(method %in% c("xBar.rMedian", "xMedian.rBar", "xMedian.rMedian")){
warning("median based QC methods represent at best *potential* process capability", call. = F)
}
#Lines, #Lables #Table
ggplot2::layer(
stat = stat_QC_CAPABILITY, data = data, mapping = mapping,
geom = geom, position = position, show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(na.rm = na.rm, n=1, digits=digits,
method=method, USL=USL, LSL=LSL,
show=show, geom.type = geom,
direction = direction, type=type,
...)
)
}
#' @export
#' @title Vertical Line Capability Stat
#' @description Draws Vertical Capability Stats
#' @inheritParams stat_QC_CAPA
#' @param show vector, indicating which lines to draw ie., c("LCL", "LSL", "X", "USL", "UCL")
#' \itemize{
#' \item \bold{LCL}: Lower Control Limit
#' \item \bold{LSL}: Lower Specification Limit
#' \item \bold{X}: Process Center
#' \item \bold{USL}: Upper Specification Limit
#' \item \bold{UCL}: Upper Control Limit
#' }
#' @inheritParams ggplot2::stat_identity
#' @return vertical lines for histogram and density plots.
#' @inherit stat_QC_CAPA examples
#'
stat_QC_cap_vlines <- function(
LSL, USL, method="xBar.rBar",
show = c("LSL","USL"),
mapping = NULL, data = NULL,
inherit.aes = TRUE, ...){
stat_QC_CAPA(
LSL=LSL, USL=USL, method=method,
mapping = mapping, data = data,
geom = "vline",
position = "identity", na.rm = FALSE,
show.legend = NA, inherit.aes = inherit.aes,
show = show, direction="v",
type = NA, ...)
}
#' @export
#' @title Vertical Label Capability Stat
#' @description Draws Vertical Lables on Vertical Capability lines
#' @inheritParams stat_QC_CAPA
#' @param show vector, indicating which lines to draw ie., c("LCL", "LSL", "X", "USL", "UCL")
#' \itemize{
#' \item \bold{LCL}: Lower Control Limit
#' \item \bold{LSL}: Lower Specification Limit
#' \item \bold{X}: Process Center
#' \item \bold{USL}: Upper Specification Limit
#' \item \bold{UCL}: Upper Control Limit
#' }
#' @inheritParams ggplot2::stat_identity
#' @return vertical lines for histogram and density plots.
#' @inherit stat_QC_CAPA examples
#'
stat_QC_cap_vlabels <- function(
LSL, USL, method="xBar.rBar",
show = c("LSL","USL"),
mapping = NULL, data = NULL,
inherit.aes = TRUE, ...){
stat_QC_CAPA(
LSL=LSL, USL=USL, method=method,
mapping = mapping, data = data,
geom = "label",
position = "identity", na.rm = FALSE,
show.legend = NA, inherit.aes = inherit.aes,
show = show, direction="v",
type = NA, ...)
}
#' @export
#' @title horizontal Line Capability Stat
#' @description Draws horizontal Capability Lines
#' @inheritParams stat_QC_CAPA
#' @param show vector, indicating which lines to draw ie., c("LCL", "LSL", "X", "USL", "UCL")
#' \itemize{
#' \item \bold{LCL}: Lower Control Limit
#' \item \bold{LSL}: Lower Specification Limit
#' \item \bold{X}: Process Center
#' \item \bold{USL}: Upper Specification Limit
#' \item \bold{UCL}: Upper Control Limit
#' }
#' @inheritParams ggplot2::stat_identity
#' @return horizontal lines for histogram and density plots.
#' @inherit stat_QC_CAPA examples
#'
stat_QC_cap_hlines <- function(
LSL, USL, method="xBar.rBar",
show = c("LSL","USL"),
mapping = NULL, data = NULL,
inherit.aes = TRUE, ...){
stat_QC_CAPA(
LSL=LSL, USL=USL, method=method,
mapping = mapping, data = data,
geom = "hline",
position = "identity", na.rm = FALSE,
show.legend = NA, inherit.aes = inherit.aes,
show = show, direction="h",
type = NA, ...)
}
#' @export
#' @title horizontal Label Capability Stat
#' @description Draws horizontal Lables on horizontal Capability lines
#' @inheritParams stat_QC_CAPA
#' @param show vector, indicating which lines to draw ie., c("LCL", "LSL", "X", "USL", "UCL")
#' \itemize{
#' \item \bold{LCL}: Lower Control Limit
#' \item \bold{LSL}: Lower Specification Limit
#' \item \bold{X}: Process Center
#' \item \bold{USL}: Upper Specification Limit
#' \item \bold{UCL}: Upper Control Limit
#' }
#' @inheritParams ggplot2::stat_identity
#' @return horizontal lines for histogram and density plots.
#' @inherit stat_QC_CAPA examples
#'
stat_QC_cap_hlabels <- function(
LSL, USL, method="xBar.rBar",
show = c("LSL","USL"),
mapping = NULL, data = NULL,
inherit.aes = TRUE, ...){
stat_QC_CAPA(
LSL=LSL, USL=USL, method=method,
mapping = mapping, data = data,
geom = "label",
position = "identity", na.rm = FALSE,
show.legend = NA, inherit.aes = inherit.aes,
show = show, direction="h",
type = NA, ...)
}
#' @export
#' @title horizontal Label Capability Stat
#' @description Draws horizontal Lables on horizontal Capability lines
#' @inheritParams stat_QC_CAPA
#' @param show vector, indicating which lines to draw ie.,
#' c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk", "LCL", "X", "UCL", "Sig").
#' The order given in the vector is the order presented in the graph.
#' \itemize{
#' \item \bold{TOL}: Tolerance in Sigma Units (USL-LSL)/sigma
#' \item \bold{DNS}: Distance to Nearest Specification Limit in Simga Units
#' \item \bold{Cp}: Cp (Within)
#' \item \bold{Cpk}: Cpk (Within)
#' \item \bold{Pp}: Pp (Between)
#' \item \bold{Ppk}: Ppk (Between)
#' \item \bold{LCL}: Lower Control Limit
#' \item \bold{X}: Process Center
#' \item \bold{UCL}: Upper Control Limit
#' \item \bold{Sig}: Sigma from control charts
#' }
#' @param px numeric, x position for table. Use Inf to force label to x-limit.
#' @param py numeric, y position for table. Use Inf to force label to y-limits. May also need vjust parameter.
#' @param digits integer, how many digits to report.
#' @inheritParams ggplot2::stat_identity
#' @return horizontal lines for histogram and density plots.
#' @inherit stat_QC_CAPA examples
stat_QC_cap_summary <- function(
LSL, USL, method="xBar.rBar", px=Inf, py= -Inf,
show = c("Cp", "Cpk", "Pp", "Ppk"),
digits=8,
mapping = NULL, data = NULL,
inherit.aes = TRUE, ...){
stat_QC_CAPA(
LSL=LSL, USL=USL, method=method,
digits=digits,
mapping = mapping, data = data,
geom = "label",
position = "identity", na.rm = FALSE,
show.legend = NA, inherit.aes = inherit.aes,
show = show, direction=NA,
type = "table", px=px, py=py, ...)
}
#' @export
#' @title Auto QC Capability Stat Function
#' @description Draws lines, lables and summary statistics. Works best with histogram and density plots.
#' @inheritParams stat_QC_CAPA
#' @param show.lines vector, indicating which lines to draw ie., c("LCL", "LSL", "X", "USL", "UCL")
#' \itemize{
#' \item \bold{LCL}: Lower Control Limit
#' \item \bold{LSL}: Lower Specification Limit
#' \item \bold{X}: Process Center
#' \item \bold{USL}: Upper Specification Limit
#' \item \bold{UCL}: Upper Control Limit
#' }
#' @param line.direction string "v" or "h", specifies which direction to draw lines.
#' @param show.line.labels boolean, if TRUE then draw.
#' @param line.label.size numeric, control the size of the line labels.
#' @param show.cap.summary vector, indicating which lines to draw ie.,
#' c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk", "LCL", "X", "UCL", "Sig").
#' The order given in the vector is the order presented in the graph.
#' \itemize{
#' \item \bold{TOL}: Tolerance in Sigma Units (USL-LSL)/sigma
#' \item \bold{DNS}: Distance to Nearest Specification Limit in Simga Units
#' \item \bold{Cp}: Cp (Within)
#' \item \bold{Cpk}: Cpk (Within)
#' \item \bold{Pp}: Pp (Between)
#' \item \bold{Ppk}: Ppk (Between)
#' \item \bold{LCL}: Lower Control Limit
#' \item \bold{X}: Process Center
#' \item \bold{UCL}: Upper Control Limit
#' \item \bold{Sig}: Sigma from control charts
#' }
#' @param cap.summary.size numeric, control the size/scale of the summary text box.
#' @param px numeric, x position for summary text box. Use Inf to force label to x-limit.
#' @param py numeric, y position for summary text box. Use Inf to force label to y-limits. May also need vjust parameter.
#' @param digits integer, how many digits to report.
#' @inheritParams ggplot2::stat_identity
#' @return capability layer for histogram and density plots.
#' @seealso for more control over lines, labels, and capability data see the following functions:
#'\itemize{
#' \item \code{\link{stat_QC_cap_vlabels}}
#' \item \code{\link{stat_QC_cap_hlabels}}
#' \item \code{\link{stat_QC_cap_vlines}}
#' \item \code{\link{stat_QC_cap_hlines}}
#' \item \code{\link{stat_QC_cap_summary}}
#'}
#' @examples
#' # Load Libraries ----------------------------------------------------------
#' require(ggQC)
#' require(ggplot2)
#' # Setup Data --------------------------------------------------------------
#' set.seed(5555)
#' Process1 <- data.frame(ProcessID = as.factor(rep(1,100)),
#' Value = rnorm(100,10,1),
#' Subgroup = rep(1:20, each=5),
#' Process_run_id = 1:100)
#' set.seed(5556)
#' Process2 <- data.frame(ProcessID = as.factor(rep(2,100)),
#' Value = rnorm(100,20, 1),
#' Subgroup = rep(1:10, each=10),
#' Process_run_id = 101:200)
#' df <- rbind(Process1, Process2)
#'
#' ######################
#' ## Example 1 XmR ##
#' ######################
#'
#' ##You may need to use the r-studio Zoom for these plots or make the size of the
#' ##stat_QC_cap_summary smaller with size = some number"
#'
#' # Normal Histogram XmR --------------------------------------------------------
#' EX1.1 <- ggplot(df[df$ProcessID == 1,], aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_histogram(binwidth = 1, color="purple") +
#' geom_hline(yintercept=0, color="grey") +
#' stat_QC_Capability(LSL=5, USL=15, show.cap.summary = "all", method="XmR") +
#' scale_x_continuous(expand = expand_scale(mult = c(0.15,.8))) +
#' ylim(0,45)
#' #Ex1.1
#'
#' # Facet Histogram XmR -----------------------------------------------------
#' EX1.2 <- ggplot(df[order(df$Process_run_id),],
#' aes(x=Value, QC.Subgroup=Subgroup, color=ProcessID)) +
#' geom_histogram(binwidth = 1) +
#' geom_hline(yintercept=0, color="grey") +
#' stat_QC_Capability(LSL=5, USL=15, show.cap.summary = "all", method="XmR") +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8))) +
#' facet_grid(.~ProcessID, scales = "free_x") + ylim(0,45)
#' #EX1.2
#'
#' # Normal Density XmR --------------------------------------------------------
#' EX1.3 <- ggplot(df[df$ProcessID == 1,], aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_density(bw = .4, fill="purple", trim=TRUE) +
#' geom_hline(yintercept=0, color="grey") +
#' stat_QC_Capability(LSL=5, USL=15, show.cap.summary = "all", method="XmR") +
#' scale_x_continuous(expand = expand_scale(mult = c(0.15,.8))) + ylim(0,.5)
#' #EX1.3
#'
#' ########################################
#' ## Example 2: xBar.rBar or xBar.sBar ##
#' ########################################
#' # Single Histogram xBar.rBar ----------------------------------------------
#' EX2.1 <- ggplot(df[df$ProcessID==1,], aes(x=Value, QC.Subgroup=Subgroup)) +
#' geom_histogram(binwidth = 1) +
#' stat_QC_Capability(LSL=5, USL=15, method="xBar.rBar") +
#' scale_x_continuous(expand = ggplot2::expand_scale(mult = c(0.15,.8))) #+
#' #EX2.1
stat_QC_Capability <- function(
LSL, USL, method = "xBar.rBar",
show.lines = c("LSL","USL"),
line.direction = "v",
show.line.labels = TRUE,
line.label.size = 3,
show.cap.summary = c("Cp", "Cpk", "Pp", "Ppk"),
cap.summary.size = 4,
px=Inf, py= -Inf,
digits = 3){
if(!method %in% c("xBar.rBar", "xBar.rMedian", "xBar.sBar",
"xMedian.rBar", "xMedian.rMedian", "XmR")){
stop("Error: This feature only works with the following methods
xBar.rBar, xBar.rMedian, xBar.sBar xMedian.rBar, xMedian.rMedian, XmR")
}
if(line.direction == "v"){
theLines <- stat_QC_cap_vlines(LSL = LSL, USL=USL, method = method,
show=show.lines)
theLabels <- stat_QC_cap_vlabels(LSL = LSL, USL=USL, method = method,
show=show.lines, size=line.label.size)
}else if(line.direction == "h"){
theLines <- stat_QC_cap_hlines(LSL = LSL, USL=USL, method = method,
show=show.lines)
theLabels <- stat_QC_cap_hlabels(LSL = LSL, USL=USL, method = method,
show=show.lines, size=line.label.size)
}
if(any(show.cap.summary %in% c("TOL","DNS", "Cp", "Cpk", "Pp", "Ppk", "LCL", "X", "UCL", "Sig", "all", "ALL"))){
theSUMMARY <- stat_QC_cap_summary(LSL = LSL, USL = USL, method = method,
show = show.cap.summary, digits = digits,
px = px, py=py, size=cap.summary.size)
}else{
theSUMMARY <- NULL
}
if(!show.line.labels){
theLabels <- NULL
}
return(list(theLines, theLabels, theSUMMARY))
}
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