R/studentGrowthPlot.R
In CenterForAssessment/SGP: Student Growth Percentiles & Percentile Growth Trajectories
Defines functions
`studentGrowthPlot`
`studentGrowthPlot` <-
function(Scale_Scores, ## Vector of Scale Scores
Plotting_Scale_Scores, ## Score used for plotting, if missing, then Scale_Scores are used
## for plotting, if supplied Scale_Scores used for text
Achievement_Levels, ## NOTE: Achievement_Levels must/should be supplied as factors with appropriate level codings
SGP, ## Vector of SGPs
SGP_Levels, ## Vector of SGP Levels
Grades, ## Vector of Grade levels for student
Content_Areas, ## Vector of Content Areas for student
Cuts, ## Vector of NY1, NY2, and NY3 cutscores
Plotting_Cuts, ## Vector of NY1, NY2, and NY3 cutscores used for plotting (transformed if non-vertical/equated scale)
SGP_Targets, ## Vector of CUKU, CUKU_Current, MUSU, MUSU_Current (multi) year targets
SGP_Scale_Score_Targets, ## Vector of CUKU, CUKU_Current, MUSU, MUSU_Current scale score targets
Plotting_SGP_Scale_Score_Targets, ## Vector of CUKU, CUKU_Current, MUSU, MUSU_Current scale score targets for plotting (transformed if non-vertical/equated scale)
Cutscores, ## data.frame of long formatted achievement level cutscores
Years, ## Vector of years corresponding to Scale_Scores, Content_Areas, ... arguments supplied
Report_Parameters) { ## list containing Current_Year, Content_Area, Content_Area_Title, State, Denote_Content_Area, SGP_Targets,
## Configuration, Language, Assessment_Transition, Fan
############################################
### Create relevant variables
############################################
YEAR <- CONTENT_AREA <- GRADE <- GRADE_NUMERIC <- CUTSCORES <- CUTLEVEL <- level_1_1_curve <- level_2_1_curve <- NULL ## To prevent R CMD check warnings
CUTSCORES_EQUATED <- CUTSCORES_TRANSFORMED <- NULL
number.growth.levels <- length(SGP::SGPstateData[[Report_Parameters$State]][["Growth"]][["Levels"]])
if (!is.null(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Growth_Level_Labels"]])) {
growth.level.labels <- as.character(unlist(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Growth_Level_Labels"]]))
growth.level.labels.shortened <- names(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Growth_Level_Labels"]])
} else {
growth.level.labels <- growth.level.labels.shortened <- SGP::SGPstateData[[Report_Parameters$State]][["Growth"]][["Levels"]]
}
growth.level.cutscores <- SGP::SGPstateData[[Report_Parameters$State]][["Growth"]][["Cutscores"]][["Cuts"]]
growth.level.cutscores.text <- SGP::SGPstateData[[Report_Parameters$State]][["Growth"]][["Cutscores"]][["Labels"]]
content.area.label <- SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Content_Areas_Labels"]][[Report_Parameters$Content_Area_Title]]
if (!is.null(SGP::SGPstateData[[Report_Parameters$State]][["SGP_Configuration"]][["content_area.projection.sequence"]][[Report_Parameters$Content_Area]])) {
grades.content_areas.reported.in.state <- data.frame(
GRADE=SGP::SGPstateData[[Report_Parameters$State]][["SGP_Configuration"]][["grade.projection.sequence"]][[Report_Parameters$Content_Area]],
YEAR_LAG=c(1, SGP::SGPstateData[[Report_Parameters$State]][["SGP_Configuration"]][["year_lags.projection.sequence"]][[Report_Parameters$Content_Area]]),
CONTENT_AREA=SGP::SGPstateData[[Report_Parameters$State]][["SGP_Configuration"]][["content_area.projection.sequence"]][[Report_Parameters$Content_Area]],
stringsAsFactors=FALSE
)
} else {
grades.content_areas.reported.in.state <- data.frame(
GRADE=SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Grades_Reported"]][[Report_Parameters$Content_Area]],
YEAR_LAG=c(1, diff(as.numeric(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Grades_Reported"]][[Report_Parameters$Content_Area]]))),
CONTENT_AREA=Report_Parameters$Content_Area,
stringsAsFactors=FALSE
)
}
grades.content_areas.reported.in.state <- subset(grades.content_areas.reported.in.state, !(is.na(GRADE) & is.na(CONTENT_AREA)))
grades.content_areas.reported.in.state$GRADE_NUMERIC <- (as.numeric(grades.content_areas.reported.in.state$GRADE[2])-1)+c(0, cumsum(tail(grades.content_areas.reported.in.state$YEAR_LAG, -1)))
grade.rpt.index <- intersect(grep(paste0("^", Grades[1], "$"), grades.content_areas.reported.in.state$GRADE), grep(paste0("^", Content_Areas[1], "$"), grades.content_areas.reported.in.state$CONTENT_AREA)) # needed when transition grade is the same - e.g. Grade 9 ELA to Grade 9 PSAT (not 9 to EOCT)
if (length(grade.rpt.index)==0) {
if (max(Grades, na.rm = TRUE) == "EOCT") {
grade.rpt.index <- min(grep(max(Grades, na.rm = TRUE), grades.content_areas.reported.in.state$GRADE))
} else grade.rpt.index <- min(nrow(grades.content_areas.reported.in.state), (max(grep(max(Grades, na.rm = TRUE), grades.content_areas.reported.in.state$GRADE)) + min(which(!is.na(Grades))) - 1))
}
grades.content_areas.reported.in.state$YEAR <- Report_Parameters$Current_Year
for (y in (grade.rpt.index-1):1) grades.content_areas.reported.in.state$YEAR[y] <- yearIncrement(grades.content_areas.reported.in.state$YEAR[y+1], 0, grades.content_areas.reported.in.state$YEAR_LAG[y+1])
if (grade.rpt.index != nrow(grades.content_areas.reported.in.state)) {
for (y in (grade.rpt.index+1):max((grade.rpt.index+1),(nrow(grades.content_areas.reported.in.state)))) { # -1))) {
grades.content_areas.reported.in.state$YEAR[y] <-
yearIncrement(grades.content_areas.reported.in.state$YEAR[y-1], 0, -grades.content_areas.reported.in.state$YEAR_LAG[y]) # YEAR_LAG[y] not YEAR_LAG[y-1] because YEAR_LAG= above is offset by 1 w/ c(1, SGP::...)
}
}
if (!is.null(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Earliest_Year_Reported"]])) {
grade.rpt.tf <- sapply(1:nrow(grades.content_areas.reported.in.state), function(y) grades.content_areas.reported.in.state$YEAR[y] >=
SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Earliest_Year_Reported"]][[grades.content_areas.reported.in.state$CONTENT_AREA[y]]])
if (!all(grade.rpt.tf)) {
grades.content_areas.reported.in.state <- grades.content_areas.reported.in.state[-which(!grade.rpt.tf),]
}
}
if (!is.null(transition.grade <- SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][["Grade"]])) {
post.trans.content_areas <- names(SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][[paste0('Content_Areas_Labels.', transition.grade)]])
transition.grade.numeric <- suppressWarnings(min(as.data.table(grades.content_areas.reported.in.state)[as.numeric(GRADE) >= as.numeric(transition.grade) & CONTENT_AREA %in% post.trans.content_areas, GRADE_NUMERIC]))
grades.content_areas.reported.in.state <- grades.content_areas.reported.in.state[union(sort(c(
which(grades.content_areas.reported.in.state$CONTENT_AREA %in% c(Content_Areas, post.trans.content_areas)))),
max(grep(paste0("^", Grades[!is.na(Grades)][1], "$"), grades.content_areas.reported.in.state$GRADE)):nrow(grades.content_areas.reported.in.state)),]
max.year.index <- max(grep(Report_Parameters$Current_Year, grades.content_areas.reported.in.state$YEAR))
if (transition.grade.numeric %in% grades.content_areas.reported.in.state$GRADE_NUMERIC[1:max.year.index]) {
tmp.gcar <- subset(grades.content_areas.reported.in.state,
!(YEAR >= Report_Parameters$Current_Year & !CONTENT_AREA %in% post.trans.content_areas))
if (all(Content_Areas[!is.na(Grades)] %in% tmp.gcar$CONTENT_AREA)) {
grades.content_areas.reported.in.state <- tmp.gcar
if (!all(diff(grades.content_areas.reported.in.state$GRADE_NUMERIC)==1)) {
grades.content_areas.reported.in.state$GRADE_NUMERIC <- (as.numeric(grades.content_areas.reported.in.state$GRADE_NUMERIC[2])-1)+c(0, cumsum(tail(grades.content_areas.reported.in.state$YEAR_LAG, -1)))
}
} else {
if (Grades[!is.na(Grades)][1] == transition.grade) {
grd.trans.index <- intersect(grep(paste0("^", Grades[!is.na(Grades)][1], "$"), grades.content_areas.reported.in.state$GRADE), grep(paste0("^", Content_Areas[1], "$"), grades.content_areas.reported.in.state$CONTENT_AREA)) # needed when transition grade is the same - e.g. Grade 9 ELA to Grade 9 PSAT (not 9 to EOCT)
end <- nrow(grades.content_areas.reported.in.state)
grades.content_areas.reported.in.state$YEAR[grd.trans.index:1] <- as.numeric(grades.content_areas.reported.in.state$YEAR[grd.trans.index]) - c(0, cumsum(rep(1, length(grades.content_areas.reported.in.state$YEAR_LAG[grd.trans.index:1])-1)))
grades.content_areas.reported.in.state$GRADE_NUMERIC[grd.trans.index:end] <- grades.content_areas.reported.in.state$GRADE_NUMERIC[grd.trans.index] + cumsum(c(1, tail(grades.content_areas.reported.in.state$YEAR_LAG[grd.trans.index:end], -1)))
}
}
}
}
test.abbreviation <- SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Abbreviation"]]
if (identical(SGP::SGPstateData[[Report_Parameters$State]][['Assessment_Program_Information']][['Test_Season']], "Fall")) {
test.season <- SGP::SGPstateData[[Report_Parameters$State]][['Assessment_Program_Information']][['Test_Season']]
} else {
test.season <- NULL
}
if (!is.null(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Use_EOCT_Label"]])) {
print.eoct.content.area <- FALSE
} else print.eoct.content.area <- TRUE
border.color <- "grey25"
if (is.null(SGP::SGPstateData[[Report_Parameters$State]][["SGP_Configuration"]][["arrow.legend.color"]])) {
arrow.legend.color <- rev(diverge_hcl(number.growth.levels, h = c(180, 40), c = 255, l = c(20, 100)))
} else {
arrow.legend.color <- SGP::SGPstateData[[Report_Parameters$State]][["SGP_Configuration"]][["arrow.legend.color"]]
}
if (is.null(SGP::SGPstateData[[Report_Parameters$State]][["SGP_Configuration"]][["sgp.target.types"]])) {
sgp.target.types <- c("Scale_Score_Targets_CUKU", "Scale_Score_Targets_MUSU", "Scale_Score_Targets_Current_CUKU", "Scale_Score_Targets_Current_MUSU")
} else {
sgp.target.types <- SGP::SGPstateData[[Report_Parameters$State]][["SGP_Configuration"]][["sgp.target.types"]]
}
missing.data.symbol <- "--"
if (!is.null(my.year.span <- SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["sgPlot.year.span"]])) {
studentGrowthPlot.year.span <- my.year.span
} else studentGrowthPlot.year.span <- 5
if (is.null(Report_Parameters[['Denote_Content_Area']]) || Report_Parameters[['Denote_Content_Area']]==FALSE) {
legend.fill.color <- "white"
} else {
legend.fill.color <- rgb(0,0,1,0.25)
}
if (is.null(Report_Parameters[['Configuration']][['Connect_Points']])) {
connect.points <- "Arrows"
} else {
connect.points <- Report_Parameters[['Configuration']][['Connect_Points']]
}
if (!is.null(Report_Parameters[['SGP_Targets']])) {
if (all(c("sgp.projections", "sgp.projections.lagged") %in% Report_Parameters[['SGP_Targets']]) | all(c("sgp.projections.baseline", "sgp.projections.lagged.baseline") %in% Report_Parameters[['SGP_Targets']])) tmp.target.types <- names(unlist(SGP_Targets)[!is.na(unlist(SGP_Targets))])
if (identical("sgp.projections", Report_Parameters[['SGP_Targets']]) | identical("sgp.projections.baseline", Report_Parameters[['SGP_Targets']])) tmp.target.types <- grep("Current", names(unlist(SGP_Targets)[!is.na(unlist(SGP_Targets))]), value=TRUE)
if (identical("sgp.projections.lagged", Report_Parameters[['SGP_Targets']]) | identical("sgp.projections.lagged.baseline", Report_Parameters[['SGP_Targets']])) tmp.target.types <- grep("Current", names(unlist(SGP_Targets)[!is.na(unlist(SGP_Targets))]), value=TRUE, invert=TRUE)
if (identical("CUSTOM", Report_Parameters[['SGP_Targets']])) tmp.target.types <- grep("CUSTOM", names(unlist(SGP_Targets)[!is.na(unlist(SGP_Targets))]), value=TRUE)
}
if (!is.null(SGP::SGPstateData[[Report_Parameters$State]][['SGP_Configuration']][['sgPlot.show.content_area.progression']]) |
!is.null(Report_Parameters[['Configuration']][['Assessment_Transition']])) {
sgPlot.show.content_area.progression <- SGP::SGPstateData[[Report_Parameters$State]][['SGP_Configuration']][['sgPlot.show.content_area.progression']]
} else {
if (is.null(Report_Parameters[['Configuration']][['Show_Content_Area_Progression']])) {
sgPlot.show.content_area.progression <- FALSE
} else {
sgPlot.show.content_area.progression <- Report_Parameters[['Configuration']][['Show_Content_Area_Progression']]
}
}
if (sgPlot.show.content_area.progression) print.eoct.content.area <- FALSE else print.eoct.content.area <- TRUE
if (is.null(SGP::SGPstateData[[Report_Parameters$State]][['SGP_Configuration']][['Show_Fan_Cut_Scores']])) {
show.fan.cutscores <- FALSE
} else {
show.fan.cutscores <- TRUE
}
if (is.null(SGP::SGPstateData[[Report_Parameters$State]][['SGP_Configuration']][['Show_Fan_Growth_Labels']])) {
show.fan.growth.labels <- TRUE
} else {
show.fan.growth.labels <- FALSE
}
if (is.null(Report_Parameters[['Configuration']][['Font_Size']])) {
title.ca.size <- 1.8
legend.size <- 0.5
legend.lheight <- 1
left.vp.size <- 0.85
bottom.right.vp.size <- 1.2
bottom.left.vp.size <- 0.7
} else {
if (!is.null(Report_Parameters[['Configuration']][['Font_Size']][['title.ca.size']])) {
title.ca.size <- Report_Parameters[["Configuration"]][["Font_Size"]][["title.ca.size"]]
} else title.ca.size <- 1.8
if (!is.null(Report_Parameters[['Configuration']][['Font_Size']][['legend.size']])) {
legend.size <- Report_Parameters[['Configuration']][['Font_Size']][['legend.size']]
} else legend.size <- 0.5
if (!is.null(Report_Parameters[['Configuration']][['Font_Size']][['legend.lheight']])) {
legend.lheight <- Report_Parameters[['Configuration']][['Font_Size']][['legend.lheight']]
} else legend.lheight <- 1
if (!is.null(Report_Parameters[['Configuration']][['Font_Size']][['left.vp.size']])) {
left.vp.size <- Report_Parameters[['Configuration']][['Font_Size']][['left.vp.size']]
} else left.vp.size <- 0.85
if (!is.null(Report_Parameters[['Configuration']][['Font_Size']][['bottom.right.vp.size']])) {
bottom.right.vp.size <- Report_Parameters[["Configuration"]][["Font_Size"]][["bottom.right.vp.size"]]
} else bottom.right.vp.size <- 1.2
if (!is.null(Report_Parameters[['Configuration']][['Font_Size']][['bottom.left.vp.size']])) {
bottom.left.vp.size <- Report_Parameters[['Configuration']][['Font_Size']][['bottom.left.vp.size']]
} else bottom.left.vp.size <- 0.7
}
if (!is.null(Report_Parameters[['Configuration']][['Font_Family']])) {
font.fam <- Report_Parameters[['Configuration']][['Font_Family']]
} else font.fam <- "Helvetica-Narrow"
if (is.null(Report_Parameters[['Configuration']][['Language']])) {
achievement.label <- "Achievement"
achievement_level.label <- "Achievement Level"
achievement_target.label <- "Achievement Target"
growth.label <- "Growth"
growth_percentile.label <- "Growth Percentile"
growth_level.label <- "Growth Level"
growth_target.label <- "Growth Target"
level.label <- "Level"
percentiles.label <- "Percentiles"
scale_score.label <- "Scale Score"
grade.label <- "Grade"
CU.label <- "Catch Up"
KU.label <- "Keep Up"
MU.label <- "Move Up"
SU.label <- "Stay Up"
target.label <- "Target"
}
if (identical(toupper(Report_Parameters[['Configuration']][['Language']]), "SPANISH")) { # WIDA_CO and NH
achievement.label <- "Resultado"
achievement_level.label <- "Nivel de Capacitaci\uF3n" # unicode for accented o is \uF3 - http://www.ascii.cl/htmlcodes.htm
achievement_target.label <- "Meta de Capacitaci\uF3n"
growth.label <- "Crecimiento"
growth_percentile.label <- "Porcentaje de Crecimiento"
growth_level.label <- "Nivel de Crecimiento"
growth_target.label <- "Meta de Crecimiento"
level.label <- "Niveles"
percentiles.label <- "El Percentil"
scale_score.label <- "Escala"
grade.label <- "Grado"
CU.label <- "Alcanzar"
KU.label <- "Guadar"
MU.label <- "Avanzar"
SU.label <- "Mantener"
target.label <- "Meta"
SGP_Levels <- SGP::SGPstateData[[Report_Parameters$State]][["Growth"]][["Levels"]][match(SGP_Levels, SGP::SGPstateData[[paste(head(unlist(strsplit(Report_Parameters$State, "_")), -1), collapse="_")]][["Growth"]][["Levels"]])]
}
if (is.list(Report_Parameters[["Configuration"]][["Language"]])) { # See WIDA_GA for example
achievement.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["achievement.label"]]
achievement_level.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["achievement_level.label"]]
achievement_target.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["achievement_target.label"]]
growth.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["growth.label"]]
growth_percentile.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["growth_percentile.label"]]
growth_level.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["growth_level.label"]]
growth_target.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["growth_target.label"]]
level.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["level.label"]]
percentiles.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["percentiles.label"]]
scale_score.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["scale_score.label"]]
grade.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["grade.label"]]
CU.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["CU.label"]]
KU.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["KU.label"]]
MU.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["MU.label"]]
SU.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["SU.label"]]
target.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["target.label"]]
SGP_Levels <- SGP::SGPstateData[[Report_Parameters$State]][["Growth"]][["Levels"]][match(SGP_Levels, SGP::SGPstateData[[paste(head(unlist(strsplit(Report_Parameters$State, "_")), -1), collapse = "_")]][["Growth"]][["Levels"]])]
}
if (!is.null(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Content_Area_in_Legend"]])) {
content.area.in.legend <- SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Content_Area_in_Legend"]]
} else content.area.in.legend <- TRUE
if (!is.null(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Legend_Extra"]])) {
extra.legend.element <- TRUE
extra.legend.elements <- SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Legend_Extra"]]
} else extra.legend.element <- FALSE
if (is.null(Report_Parameters[['Fan']])) {
show.fan <- TRUE
} else {
show.fan <- eval(parse(text=Report_Parameters[['Fan']]))
}
if (!is.null(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Fan_Extra"]])) {
fan.extra <- TRUE
fan.extras <- SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Fan_Extra"]]
} else fan.extra <- FALSE
Cutscores <- copy(Cutscores)
if (!is.null(Report_Parameters[['Assessment_Transition']])) Cutscores[,CUTSCORES:=CUTSCORES_EQUATED]
if (is.null(Report_Parameters[['Assessment_Transition']]) &&
Report_Parameters$Current_Year %in% SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Transformed_Achievement_Level_Cutscores"]][[Report_Parameters$Content_Area_Title]]) {
Cutscores[,CUTSCORES:=CUTSCORES_TRANSFORMED]
}
##############################
### Utility functions
##############################
`%w/o%` <- function(x, y) x[!x %in% y]
ach.level.labels <- function(perlevel){
tmp <- unlist(sapply(achievement.level.labels, names), use.names=FALSE)[match(perlevel, unlist(achievement.level.labels))]
tmp[is.na(tmp) & !is.na(perlevel)] <- perlevel[is.na(tmp) & !is.na(perlevel)]
tmp[is.na(tmp)] <- missing.data.symbol
return(tmp)
}
sgp.level.labels <- function(sgp_level){
sgp_level[is.na(sgp_level)] <- missing.data.symbol
return(sgp_level)
}
arrow.color <- function(sgp){
arrow.legend.color[findInterval(sgp, growth.level.cutscores)+1]
}
get.my.cutscore.year <- function(state, content_area, year, cutlevel) {
year <- tail(sort(c(SGP::SGPstateData[[state]][["Student_Report_Information"]][["Earliest_Year_Reported"]][[content_area]], year)), 1)
tmp.index <- grep(content_area, names(SGP::SGPstateData[[state]][["Achievement"]][["Cutscores"]]))
tmp.cutlevels <- sapply(tmp.index, function(x) length(SGP::SGPstateData[[state]][["Achievement"]][["Cutscores"]][[x]][[1]]))
tmp.cutscore.years <- unique(sapply(strsplit(names(SGP::SGPstateData[[state]][["Achievement"]][["Cutscores"]])[tmp.index], "[.]"), '[', 2))
tmp.cutscore.years <- tmp.cutscore.years[cutlevel <= tmp.cutlevels]
if (year %in% tmp.cutscore.years) {
return(year)
} else {
if (year==sort(c(year, tmp.cutscore.years))[1]) {
return(NA)
} else {
return(sort(tmp.cutscore.years)[which(year==sort(c(year, tmp.cutscore.years)))-1])
}
}
}
interpolate.grades <- function(grades, content_areas, data.year.span, scale_scores) {
last.number <- function (x) {
if (sum(!is.na(x)) > 0) return(max(which(!is.na(x)))) else return (0)
}
first.number <- function (x) {
if (sum(!is.na(x)) > 0 ) return(min(which(!is.na(x)))) else return (0)
}
convert.grades <- function(grades, content_areas, to="GRADE_NUMERIC", lookup=grades.content_areas.reported.in.state) {
if (to=="GRADE_NUMERIC") {
return(as.numeric(lookup$GRADE_NUMERIC[match(paste(grades, content_areas), paste(lookup$GRADE, lookup$CONTENT_AREA))]))
}
if (to=="GRADE") {
return(as.character(lookup$GRADE[match(grades, lookup$GRADE_NUMERIC)]))
}
}
extend.grades <- function (x, content_areas) {
tmp.grades.numeric <- x
tmp.content_areas <- grades.content_areas.reported.in.state$CONTENT_AREA[match(x, grades.content_areas.reported.in.state$GRADE_NUMERIC)]
if ((length(tmp.content_areas) > length(x)) & any(duplicated(grades.content_areas.reported.in.state$GRADE_NUMERIC))) {
tmp.dups <- grades.content_areas.reported.in.state$CONTENT_AREA[duplicated(grades.content_areas.reported.in.state$GRADE_NUMERIC)]
tmp.content_areas <- tmp.content_areas[!tmp.content_areas %in% tmp.dups]
}
tmp.grades <- convert.grades(x, to="GRADE")
tmp.head <- min(which(x[!is.na(x)][1] <= grades.content_areas.reported.in.state$GRADE_NUMERIC), na.rm=TRUE)
tmp.tail <- min(which(tail(x[!is.na(x)], 1) <= grades.content_areas.reported.in.state$GRADE_NUMERIC), na.rm=TRUE)
if (tmp.head==1) {
tmp.grades <- c("GRADE_LOWER", tmp.grades); tmp.content_areas <- c("PLACEHOLDER", tmp.content_areas); tmp.grades.numeric <- c(NA, tmp.grades.numeric)
} else {
tmp.grades <- c(grades.content_areas.reported.in.state$GRADE[tmp.head-1], tmp.grades)
tmp.content_areas <- c(grades.content_areas.reported.in.state$CONTENT_AREA[tmp.head-1], tmp.content_areas)
tmp.grades.numeric <- c(grades.content_areas.reported.in.state$GRADE_NUMERIC[tmp.head-1], tmp.grades.numeric)
}
if (tmp.tail==dim(grades.content_areas.reported.in.state)[1]) {
tmp.grades <- c(tmp.grades, "GRADE_UPPER");
tmp.content_areas <- c(tmp.content_areas, "PLACEHOLDER");
tmp.grades.numeric <- c(tmp.grades.numeric, NA)
} else {
tmp.grades <- c(tmp.grades, grades.content_areas.reported.in.state$GRADE[tmp.tail+1])
tmp.content_areas <- c(tmp.content_areas, grades.content_areas.reported.in.state$CONTENT_AREA[tmp.tail+1])
tmp.grades.numeric <- c(tmp.grades.numeric, grades.content_areas.reported.in.state$GRADE_NUMERIC[tmp.tail+1])
}
tmp.grades[is.na(tmp.grades)] <- tmp.grades.numeric[is.na(tmp.grades)]
return(data.frame(GRADE=tmp.grades, GRADE_NUMERIC=tmp.grades.numeric, CONTENT_AREA=tmp.content_areas, stringsAsFactors=FALSE))
}
first.scale.score <- first.number(head(grades, data.year.span))
last.scale.score <- last.number(grades)
any.scale.scores <- any(!is.na(scale_scores))
grades <- convert.grades(grades, content_areas)
if (last.scale.score < data.year.span) {
grades[(last.scale.score+1):data.year.span] <- (grades[last.scale.score]-1):(grades[last.scale.score] - (data.year.span - last.scale.score))
grades[grades < min(grades.content_areas.reported.in.state$GRADE_NUMERIC)] <- min(grades.content_areas.reported.in.state$GRADE_NUMERIC)
}
if (first.scale.score > 1) {
grades[1:(first.scale.score-1)] <- (grades[first.scale.score] + (first.scale.score - 1)):(grades[first.scale.score]+1)
grades[grades > max(grades.content_areas.reported.in.state$GRADE_NUMERIC)] <- max(grades.content_areas.reported.in.state$GRADE_NUMERIC)
if (any(is.na(grades))) {
if (1 %in% which(is.na(grades))) grades[1] <- grades[min(which(!is.na(grades)))]+(min(which(!is.na(grades)))-1) # `approx` doesn't work when first value is NA
if (length(grades) %in% which(is.na(grades))) grades[length(grades)] <- grades[min(which(!is.na(grades)))]-(length(grades)-min(which(!is.na(grades)))) # `approx` doesn't work when last value is NA
grades[which(is.na(grades))] <- approx(grades, xout=which(is.na(grades)))$y
grades <- as.integer(grades)
}
if (!grades[1] %in% grades.content_areas.reported.in.state$GRADE_NUMERIC) {
grades[1] <- grades.content_areas.reported.in.state$GRADE_NUMERIC[which.min(grades[1] > grades.content_areas.reported.in.state$GRADE_NUMERIC)-1]
}
if (any(!grades %in% grades.content_areas.reported.in.state$GRADE_NUMERIC)) {
for (tmp.missing.grades in which(!grades %in% grades.content_areas.reported.in.state$GRADE_NUMERIC)) {
grades[tmp.missing.grades] <-
grades.content_areas.reported.in.state$GRADE_NUMERIC[which.max(grades[tmp.missing.grades] < grades.content_areas.reported.in.state$GRADE_NUMERIC)]
}
}
}
if (any(is.na(grades))) {
tmp.na <- which(is.na(grades))
tmp.not.na <- max(which(!is.na(grades)))
while (any(is.na(grades))) {
nearest.not.na <- tmp.na[which.min(abs(tmp.na-tmp.not.na))]; tmp.dif <- (tmp.not.na-nearest.not.na)
tmp.index <- match(grades[tmp.not.na], grades.content_areas.reported.in.state$GRADE_NUMERIC)+tmp.dif
if (tmp.index <= 0L) tmp.index <- 1
if (tmp.index > nrow(grades.content_areas.reported.in.state)) tmp.index <- nrow(grades.content_areas.reported.in.state)
grades[tmp.not.na-tmp.dif] <- grades.content_areas.reported.in.state$GRADE_NUMERIC[tmp.index]
tmp.na <- which(is.na(grades)); tmp.not.na <- min(which(!is.na(grades)))
}
if (!length(grades) %in% tmp.na && length(intersect(tmp.na, which(!is.na(grades)))) > 0) {
tmp.indices <- intersect(tmp.na, which(!is.na(grades)))
grades[tmp.indices] <- NA
grades[tmp.indices] <- round(approx(grades, xout=tmp.indices)$y)
}
}
if (grades[1]==max(grades.content_areas.reported.in.state$GRADE_NUMERIC)) {
year_span <- data.year.span
temp.grades.content_areas <- extend.grades(rev(grades), content_areas)
return(list(
interp.df = temp.grades.content_areas,
year_span=year_span,
any_scale_scores=any.scale.scores,
increment_for_projection_current=0,
years=yearIncrement(Report_Parameters$Current_Year, seq(1-max(which(grades[1]==temp.grades.content_areas$GRADE_NUMERIC)), length=dim(temp.grades.content_areas)[1]))))
} else {
year.increment.for.projection.current <- grades.content_areas.reported.in.state$YEAR_LAG[which(grades[1]==grades.content_areas.reported.in.state$GRADE_NUMERIC)+1]
year_span <- max(min(last.scale.score, data.year.span-1), min(grades[1]-min(grades.content_areas.reported.in.state$GRADE_NUMERIC)+1, data.year.span-1)) - (year.increment.for.projection.current-1)
temp.grades <- c(rev(head(grades, year_span)),
head(seq(grades.content_areas.reported.in.state$GRADE_NUMERIC[match(grades[1], grades.content_areas.reported.in.state$GRADE_NUMERIC)]+1, length=data.year.span),
data.year.span-year_span))
temp.grades.content_areas <- extend.grades(temp.grades, content_areas)
return(list(
interp.df = temp.grades.content_areas,
year_span=year_span,
any_scale_scores=any.scale.scores,
increment_for_projection_current=year.increment.for.projection.current,
years=yearIncrement(Report_Parameters$Current_Year, seq(1-max(which(grades[1]==temp.grades.content_areas$GRADE_NUMERIC)), length=dim(temp.grades.content_areas)[1]))))
}
} ### END interpolate.grades function
year.function <- function(year, add.sub, vec.length, output.type="numeric", season=NULL) {
if (is.null(season)) {
if (grepl("_", year)) {
tmp <- as.numeric(unlist(strsplit(strsplit(as.character(year), "[.]")[[1]][1], "_")))+add.sub
if (output.type=="numeric") {
return(seq(from=tmp[2], length=vec.length))
} else {
return(paste0(seq(from=tmp[1], length=vec.length), "-", seq(from=tmp[2], length=vec.length)))
}
} else {
return(seq(from=as.numeric(strsplit(as.character(year), "[.]")[[1]][1])+add.sub, length=vec.length))
}
} else {
if (length(grep("_", year) > 0)) {
tmp <- as.numeric(unlist(strsplit(strsplit(as.character(year), "[.]")[[1]][1], "_")))+add.sub
if (output.type=="numeric") {
return(seq(from=tmp[2], length=vec.length))
} else {
return(paste(season, seq(from=tmp[1], length=vec.length)))
}
} else {
return(paste(season, seq(from=as.numeric(strsplit(as.character(year), "[.]")[[1]][1])+add.sub, length=vec.length)))
}
}
}
stextGrob <- function (label, r=0.1, x = x, y = y,
just = "centre", hjust = NULL, vjust = NULL, rot = 0, check.overlap = FALSE,
default.units = "native", name = NULL, gp = gpar(), vp = NULL){
# http://stackoverflow.com/questions/7734535/control-font-thickness-without-changing-font-size
let <- textGrob("a", gp=gp, vp=vp)
wlet <- grobWidth(let)
hlet <- grobHeight(let)
tg <- textGrob(label=label, x=x, y=y, gp=gpar(col="white"), just = just, hjust = hjust, vjust = vjust, rot = rot,
check.overlap = check.overlap, default.units = default.units)
tgl <- c(lapply(seq(0, 2*pi, length=36), function(theta){
textGrob(label=label,x=x+cos(theta)*r*wlet, y=y+sin(theta)*r*hlet, gp=gpar(col="black"),
just = just, hjust = hjust, vjust = vjust, rot = rot, check.overlap = check.overlap, default.units = default.units)
}), list(tg))
g <- gTree(children=do.call(gList, tgl), vp=vp, name=name, gp=gp)
}
grid.stext <- function(...){
g <- stextGrob(...)
grid.draw(g)
invisible(g)
}
labelSplit <- function(label, force.split.nchar=9) {
label.split <- unlist(strsplit(label, " "))
label.word.nchar <- cumsum(nchar(label.split))
if (length(label.word.nchar) > 1 & tail(label.word.nchar, 1) > force.split.nchar) {
if (any(label.word.nchar <= force.split.nchar)) {
label.split.position <- max(which(label.word.nchar <= force.split.nchar))
tmp.label <- paste(label.split[1:label.split.position], collapse=" ")
tmp.label[2] <- paste(label.split[(label.split.position+1):length(label.split)], collapse=" ")
tmp.cex <- c(title.ca.size - 0.25 - max(0, nchar(tmp.label[1])-force.split.nchar)*0.1, title.ca.size - 0.25 - max(0, nchar(tmp.label[2])-force.split.nchar)*0.1)
} else {
tmp.label <- label.split
tmp.cex <- rep(title.ca.size - 0.25 - (max(nchar(tmp.label))-force.split.nchar)*0.1, length(tmp.label))
}
return(list(content_area.label.pieces=tmp.label, cex=tmp.cex))
} else {
return(list(content_area.label.pieces=label, cex=title.ca.size - max(0, nchar(label)-force.split.nchar)*0.1))
}
}
###
### END Utility functions
###
grade.values <- interpolate.grades(Grades, Content_Areas, studentGrowthPlot.year.span, Scale_Scores)
if (any(duplicated(grade.values$interp.df))) {
grade.values$interp.df <- unique(grade.values$interp.df) # needed when transition grade is the same - e.g. Grade 9 ELA to Grade 9 PSAT (not 9 to EOCT)
}
grade.values$interp.df <- subset(grade.values$interp.df, !(is.na(GRADE) & is.na(GRADE_NUMERIC) & is.na(CONTENT_AREA)))
grade.values$years <- tail(grade.values$years, nrow(grade.values$interp.df))
if (!is.null(Report_Parameters[['Assessment_Transition']]) && grade.values$years[2] >= Report_Parameters[['Assessment_Transition']][['Year']]) Report_Parameters[['Assessment_Transition']] <- NULL
if (!is.null(transition.grade)) {
grade.rpt.index <- intersect(grep(paste0("^", Grades[!is.na(Grades)][1], "$"), grades.content_areas.reported.in.state$GRADE), grep(paste0("^", Content_Areas[1], "$"), grades.content_areas.reported.in.state$CONTENT_AREA)) # needed when transition grade is the same - e.g. Grade 9 ELA to Grade 9 PSAT (not 9 to EOCT)
if (length(grade.rpt.index)==0) grade.rpt.index <- (max(grep(max(Grades, na.rm = TRUE), grades.content_areas.reported.in.state$GRADE)) + min(which(!is.na(Grades))) - 1)
if (any(grades.content_areas.reported.in.state$CONTENT_AREA[grade.rpt.index:nrow(grades.content_areas.reported.in.state)] %in% post.trans.content_areas)) {
if (!is.list(Report_Parameters[['Assessment_Transition']])) {
Report_Parameters[['Assessment_Transition']] <- list(Grade = transition.grade)
} else Report_Parameters[['Assessment_Transition']][['Grade']] <- transition.grade
Report_Parameters[['Assessment_Transition']][['Assessment_Transition_Type']] <- c(
SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][['Vertical_Scale']],
SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][[paste('Vertical_Scale', transition.grade, sep=".")]])
grd.index <- grep(paste(SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][[paste0('Grades_Tested.', transition.grade)]], collapse="|"), grade.values$interp.df$GRADE)
sbj.index <- grep(paste(names(SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][[paste0('Content_Areas_Labels.', transition.grade)]]), collapse="|"), grade.values$interp.df$CONTENT_AREA)
if (length(sbj.index) > 0 & length(grd.index) > 0) {
Report_Parameters[['Assessment_Transition']][['Year']] <- as.data.table(grades.content_areas.reported.in.state)[
GRADE == grade.values$interp.df[min(intersect(grd.index, sbj.index)),]$GRADE &
CONTENT_AREA == grade.values$interp.df[min(intersect(grd.index, sbj.index)),]$CONTENT_AREA, YEAR]
} else Report_Parameters[['Assessment_Transition']][['Year']] <- grade.values$years[length(Grades)]
if (!is.na(grade.values$years[length(Grades)]) & grade.values$years[length(Grades)] < Report_Parameters[['Assessment_Transition']][['Year']]) Report_Parameters[['Assessment_Transition']][['Year']] <- grade.values$years[length(Grades)]
}
# if (!transition.grade %in% grades.content_areas.reported.in.state$GRADE[1:(grade.rpt.index+1)] & !any(grade.values$interp.df$GRADE_NUMERIC > transition.grade.numeric, na.rm = TRUE)) Report_Parameters[['Assessment_Transition']] <- NULL
}
if (is.null(Report_Parameters[['Assessment_Transition']])) {
achievement.level.labels <- list(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Achievement_Level_Labels"]])
number.achievement.level.regions <- sapply(achievement.level.labels, length)
level.to.get.cuku <- list(which.max(SGP::SGPstateData[[Report_Parameters$State]][["Achievement"]][["Levels"]][["Proficient"]]=="Proficient")-1)
level.to.get.musu <- list(which.max(SGP::SGPstateData[[Report_Parameters$State]][["Achievement"]][["Levels"]][["Proficient"]]=="Proficient"))
} else {
achievement.level.labels <- SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][
grep("Achievement_Level_Labels", names(SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]]))]
number.achievement.level.regions <- sapply(achievement.level.labels, length)
achievement.levels.proficiency <- SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][
grep("Achievement_Levels", names(SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]]))]
level.to.get.cuku <- sapply(achievement.levels.proficiency, function(x) which.max(x[['Proficient']]=="Proficient")-1)
level.to.get.musu <- sapply(achievement.levels.proficiency, function(x) which.max(x[['Proficient']]=="Proficient"))
}
achievement.level.region.colors <- lapply(number.achievement.level.regions, function(x) paste0("grey", round(seq(62, 91, length=x))))
if (!is.null(Report_Parameters[['Assessment_Transition']][['Assessment_Transition_Type']])) {
if (identical(toupper(Report_Parameters[['Assessment_Transition']][['Assessment_Transition_Type']][1]), "NO")) {
tmp.cutscore.year <- tail(head(sort(unique(Cutscores[['YEAR']]), na.last=FALSE), -1), 1)
if (!is.null(transition.grade)) tmp.cutscore.year <- NA
tmp.cutscore.grade <- grade.values[['interp.df']][['GRADE']][which(grade.values[['years']]==Report_Parameters[['Assessment_Transition']][['Year']])]
if (!tmp.cutscore.grade %in% Cutscores[['GRADE']]) {
tmp.grades.reported <- SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Grades_Reported"]][[Report_Parameters$Content_Area]]
tmp.cutscore.grade <-
tmp.grades.reported[which.max(as.numeric(grade.values[['interp.df']][['GRADE']][which(grade.values[['years']]==Report_Parameters[['Assessment_Transition']][['Year']])]) < tmp.grades.reported)-1]
}
if (is.na(tmp.cutscore.year)) {
Cutscores[is.na(YEAR), CUTSCORES:=Cutscores[GRADE==tmp.cutscore.grade & is.na(YEAR)][['CUTSCORES']]]
} else {
Cutscores[is.na(YEAR) | YEAR < Report_Parameters$Assessment_Transition$Year,
CUTSCORES:=Cutscores[GRADE==tmp.cutscore.grade & YEAR==tmp.cutscore.year][['CUTSCORES']]]
}
}
if (identical(toupper(Report_Parameters[['Assessment_Transition']][['Assessment_Transition_Type']][2]), "NO")) {
tmp.cutscore.grade <- Grades[which(Years==Report_Parameters[['Assessment_Transition']][['Year']])]
if (length(tmp.cutscore.grade)==0) tmp.cutscore.grade <- NA
if (is.na(tmp.cutscore.grade)) {
tmp.cutscore.grade <- grade.values[['interp.df']][['GRADE']][which(grade.values[['years']]==Report_Parameters[['Assessment_Transition']][['Year']])]
}
Cutscores[!is.na(YEAR) & YEAR >= Report_Parameters$Assessment_Transition$Year,
CUTSCORES:=Cutscores[GRADE==tmp.cutscore.grade & YEAR >= Report_Parameters$Assessment_Transition$Year][['CUTSCORES']]]
}
}
if (grade.values[['any_scale_scores']]) {
low.year <- year.function(Report_Parameters$Current_Year, (1-grade.values$year_span), 1)
high.year <- year.function(Report_Parameters$Current_Year, studentGrowthPlot.year.span-grade.values$year_span, 1)
year.text <- c(year.function(Report_Parameters$Current_Year, (1-grade.values$year_span), grade.values$year_span+grade.values$increment_for_projection_current, "character", test.season),
rep(" ", studentGrowthPlot.year.span))
year.text <- head(year.text, studentGrowthPlot.year.span)
content_area.text <- grade.values$interp.df$CONTENT_AREA[match(gsub("-", "_", year.text), sapply(grade.values$years, function(f) strsplit(f, "[.]")[[1]][1]))]
content_area.text[is.na(content_area.text)] <- " "
for (i in which(content_area.text %in% names(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Content_Areas_Labels"]]))) {
content_area.text[i] <- SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Content_Areas_Labels"]][[content_area.text[i]]]
}
if (grade.values$increment_for_projection_current > 0) {
grades.text.numbers <- c(Grades[grade.values$year_span:1],
grades.content_areas.reported.in.state$GRADE[match(Grades[1], grades.content_areas.reported.in.state$GRADE)+seq(grade.values$increment_for_projection_current)])
tmp.grades.text.numbers <- head(grade.values$interp.df$GRADE[-1], studentGrowthPlot.year.span)
} else {
grades.text.numbers <- Grades[grade.values$year_span:1]
tmp.grades.text.numbers <- head(grade.values$interp.df$GRADE[-1], studentGrowthPlot.year.span)
}
if (!is.null(Report_Parameters[['Configuration']][['Zero_to_K']])) {
if (is.character(Report_Parameters[['Configuration']][['Zero_to_K']])) {
grades.text.numbers[which(grades.text.numbers==0)] <- Report_Parameters[['Configuration']][['Zero_to_K']]
} else grades.text.numbers[which(grades.text.numbers==0)] <- "K"
}
grades.text.numbers.missing <- which(is.na(grades.text.numbers))
grades.text.numbers.non.tested <- which(!tmp.grades.text.numbers %in% grades.content_areas.reported.in.state$GRADE)
grades.text.eoct <- which(grades.text.numbers=="EOCT")
grades.text <- c(paste(grade.label, grades.text.numbers), rep(" ", studentGrowthPlot.year.span))
grades.text[grades.text.numbers.missing] <- missing.data.symbol
grades.text[grades.text.numbers.non.tested] <- "Non-tested Grade"
if (print.eoct.content.area) {
grades.text[grades.text.eoct] <- content_area.text[grades.text.eoct]
} else grades.text[grades.text.eoct] <- "EOCT"
grades.text <- head(grades.text, studentGrowthPlot.year.span)
if (missing(Plotting_Scale_Scores)) Plotting_Scale_Scores <- Scale_Scores
scale.scores.values <- c(Plotting_Scale_Scores[grade.values$year_span:1], rep(NA, studentGrowthPlot.year.span))
scale.scores.values <- head(scale.scores.values, studentGrowthPlot.year.span)
scale.scores.text <- c(Scale_Scores[grade.values$year_span:1], rep(" ", studentGrowthPlot.year.span))
scale.scores.text[which(is.na(Scale_Scores[grade.values$year_span:1]))] <- missing.data.symbol
scale.scores.text <- head(scale.scores.text, studentGrowthPlot.year.span)
ach.levels.text <- c(ach.level.labels(Achievement_Levels[grade.values$year_span:1]), rep(" ", studentGrowthPlot.year.span))
ach.levels.text <- head(ach.levels.text, studentGrowthPlot.year.span)
if (grade.values[['year_span']] > 1) {
gp.values <- c(SGP[(grade.values$year_span-1):1], rep(NA, studentGrowthPlot.year.span))
gp.values <- head(gp.values, studentGrowthPlot.year.span-1)
gp.text <- c(SGP[(grade.values$year_span-1):1], rep(" ", studentGrowthPlot.year.span))
gp.text[which(is.na(SGP[(grade.values$year_span-1):1]))] <- missing.data.symbol
gp.text <- head(gp.text, studentGrowthPlot.year.span-1)
gp.levels.text <- c(sgp.level.labels(SGP_Levels[(grade.values$year_span-1):1]), rep(" ", studentGrowthPlot.year.span))
gp.levels.text <- head(gp.levels.text, studentGrowthPlot.year.span-1)
} else {
gp.values <- rep(NA, studentGrowthPlot.year.span-1)
gp.text <- rep(" ", studentGrowthPlot.year.span-1)
gp.levels.text <- rep(" ", studentGrowthPlot.year.span-1)
}
if (grade.values[['increment_for_projection_current']]==0) {
cuts.ny1 <- rep(NA, number.growth.levels+1)
cuts.ny1.text <- rep(NA, number.growth.levels+1)
} else {
cuts.ny1 <- Plotting_Cuts[["NY1"]]
cuts.ny1.text <- Cuts[["NY1"]]
}
} else {
low.year <- year.function(Report_Parameters$Current_Year, (1-grade.values$year_span), 1)
high.year <- year.function(Report_Parameters$Current_Year, studentGrowthPlot.year.span-grade.values$year_span, 1)
year.text <- rep(" ", studentGrowthPlot.year.span)
content_area.text <- rep(" ", studentGrowthPlot.year.span)
grades.text <- rep(" ", studentGrowthPlot.year.span)
scale.scores.values <- rep(NA, studentGrowthPlot.year.span)
scale.scores.text <- rep(" ", studentGrowthPlot.year.span)
ach.levels.text <- rep(" ", studentGrowthPlot.year.span)
gp.values <- rep(NA, studentGrowthPlot.year.span-1)
gp.text <- rep(" ", studentGrowthPlot.year.span-1)
gp.levels.text <- rep(" ", studentGrowthPlot.year.span-1)
cuts.ny1 <- rep(NA, number.growth.levels+1)
cuts.ny1.text <- rep(NA, number.growth.levels+1)
}
current.year <- year.function(Report_Parameters$Current_Year, 0, 1)
xscale.range <- range(low.year,high.year) + c(-0.075, 0.1)*diff(range(low.year,high.year))
if (is.null(Report_Parameters$Assessment_Transition)) {
tmp.year.cut <- NULL
xscale.range.list <- list(xscale.range)
} else {
tmp.year.cut <- year.function(Report_Parameters$Assessment_Transition$Year, 0, 1)-0.5
if (tmp.year.cut <= xscale.range[1]) xscale.range[1] <- tmp.year.cut-0.9
xscale.range.list <- list(c(xscale.range[1], tmp.year.cut-0.025), c(tmp.year.cut+0.025, xscale.range[2]))
}
low.score <- min(cuts.ny1, Plotting_Scale_Scores, Cutscores[GRADE==data.table(grade.values[['interp.df']])[!is.na(CONTENT_AREA)][['GRADE']][1] & CUTLEVEL==1][['CUTSCORES']], na.rm=TRUE)
high.score <- max(cuts.ny1, Plotting_Scale_Scores, Cutscores[GRADE==tail(data.table(grade.values[['interp.df']])[!is.na(CONTENT_AREA)][['GRADE']], 1) & CUTLEVEL %in% (number.achievement.level.regions-1)][['CUTSCORES']], na.rm=TRUE)
yscale.range <- extendrange(c(low.score,high.score), f=0.15)
content_area.label.pieces <- labelSplit(content.area.label)
if (length(content_area.label.pieces[[1]])==1) split.content_area.tf <- FALSE else split.content_area.tf <- TRUE
### Create viewports
if (is.null(Report_Parameters$Assessment_Transition)) {
subject.report.vp <- viewport(layout = grid.layout(2, 3, widths = unit(c(1.15, 5.4, 1.5)/8.05, rep("npc", 3)),
heights = unit(c(2.45, 0.9)/3.35, rep("npc", 2))), gp=gpar(fill="transparent"))
} else {
subject.report.vp <- viewport(layout = grid.layout(2, 3, widths = unit(c(1.15, 5.65, 1.25)/8.05, rep("npc", 3)),
heights = unit(c(2.45, 0.9)/3.35, rep("npc", 2))), gp=gpar(fill="transparent"))
}
growth.chart.vp <- viewport(name="growth.chart.vp",
layout.pos.row=1, layout.pos.col=2,
xscale=xscale.range,
yscale=yscale.range,
gp=gpar(fill="transparent"))
if (is.null(Report_Parameters$Assessment_Transition)) {
right.vp <- viewport(name="right.vp",
layout.pos.row=1, layout.pos.col=3,
xscale=c(0,1),
yscale=c(0,1),
gp=gpar(fill="transparent"))
} else {
right.vp <- viewport(name="right.vp",
layout.pos.row=1, layout.pos.col=3,
xscale=c(0,1),
yscale=yscale.range,
gp=gpar(fill="transparent"))
}
left.vp <- viewport(name="left.vp",
layout.pos.row=1, layout.pos.col=1,
xscale=c(0, 1),
yscale=yscale.range,
gp=gpar(fill="transparent"))
if (is.null(Report_Parameters$Assessment_Transition)) {
growth.and.margins.vp <- viewport(name="growth.and.margins.vp",
layout.pos.row=1, layout.pos.col=1:2)
} else {
growth.and.margins.vp <- viewport(name="growth.and.margins.vp",
layout.pos.row=1, layout.pos.col=1:3)
bottom.right.vp.size <- 1.05
}
bottom.vp <- viewport(name="bottom.vp",
layout.pos.row=2, layout.pos.col=2,
xscale=xscale.range,
yscale=c(0,3),
gp=gpar(fill="transparent"))
bottom.left.right.vp <- viewport(name="bottom.left.right.vp",
layout.pos.row=2, layout.pos.col=1:3,
xscale=c(0,1),
yscale=c(0,3),
gp=gpar(fill="transparent"))
bottom.right.vp <- viewport(name="bottom.right.vp",
layout.pos.row=2, layout.pos.col=3,
xscale=c(0,1),
yscale=c(0,3),
gp=gpar(fill="transparent"))
bottom.left.vp <- viewport(name="bottom.left.vp",
layout.pos.row=2, layout.pos.col=1,
xscale=c(0,1),
yscale=c(0,3),
gp=gpar(fill="transparent"))
no.data.vp <- viewport(name="no.data.vp",
layout.pos.row=1, layout.pos.col=1:3,
xscale=c(0,1),
yscale=c(0,1),
gp=gpar(fill="transparent"))
pushViewport(subject.report.vp)
#############################################
### Growth.Chart Viewport
#############################################
pushViewport(growth.chart.vp)
if (is.null(tmp.year.cut)) {
tmp.year.sequence <- list(as.character((low.year-1):(high.year+1)))
} else {
tmp.year.sequence <- list(as.character((low.year-1):tmp.year.cut), as.character(rev((high.year+1):tmp.year.cut)))
}
for (j in seq(length(Report_Parameters$Assessment_Transition[['Year']])+1)) {
for (i in seq(number.achievement.level.regions[[j]]-1)) {
temp <- data.table(temp_id=seq_len(nrow(grade.values$interp.df)), grade.values$interp.df, YEAR=sapply(strsplit(sapply(strsplit(grade.values$years, "_"), tail, 1), "[.]"), head, 1), key="YEAR")[tmp.year.sequence[[j]]]
temp[,YEAR:=get.my.cutscore.year(Report_Parameters$State, Report_Parameters$Content_Area, YEAR, i)]
if (class(temp$YEAR) != class(Cutscores$YEAR)) class(temp$YEAR) <- class(Cutscores$YEAR)
temp <- merge(temp, Cutscores[CUTLEVEL==i], all.x=TRUE, by=c("YEAR", "CONTENT_AREA", "GRADE"))
temp <- temp[order(temp$temp_id),][['CUTSCORES']]
if (length(temp[which(!is.na(temp))])==1) {
temp[which(is.na(temp))] <- temp[which(!is.na(temp))]
} else {
temp[which(is.na(temp))] <- approx(temp, xout=which(is.na(temp)), rule=2)$y
}
assign(paste0("level_", j, "_", i, "_curve"), splinefun(as.numeric(tmp.year.sequence[[j]]), temp, method="monoH.FC"))
}
tmp.x.points <- seq(xscale.range.list[[j]][1], xscale.range.list[[j]][2], length=round(diff(xscale.range.list[[j]])/diff(xscale.range)*40))
x.boundary.values.1 <- c(xscale.range.list[[j]][1], tmp.x.points, xscale.range.list[[j]][2])
y.boundary.values.1 <- c(yscale.range[1], eval(parse(text=paste0("level_", j, "_1_curve(tmp.x.points)"))), yscale.range[1])
assign(paste0("x.boundary.values.", number.achievement.level.regions[[j]]),
c(xscale.range.list[[j]][1], tmp.x.points, xscale.range.list[[j]][2]))
assign(paste0("y.boundary.values.", number.achievement.level.regions[[j]]),
c(yscale.range[2], eval(parse(text=paste0("level_", j, "_", number.achievement.level.regions[[j]]-1, "_curve(tmp.x.points)"))), yscale.range[2]))
if (number.achievement.level.regions[[j]] > 2) {
for (i in 2:(number.achievement.level.regions[[j]]-1)) {
assign(paste0("x.boundary.values.", i),
c(tmp.x.points, rev(tmp.x.points)))
assign(paste0("y.boundary.values.", i),
eval(parse(text=paste0("c(level_", j, "_", i, "_curve(tmp.x.points), level_", j, "_", i-1, "_curve(rev(tmp.x.points)))"))))
}
}
## Keep achievement level bands from extending outside of chart box
eval(parse(text=paste0("y.boundary.values.", seq(number.achievement.level.regions[[j]]), "[y.boundary.values.", seq(number.achievement.level.regions[[j]]), " > max(yscale.range)] <- max(yscale.range)")))
eval(parse(text=paste0("y.boundary.values.", seq(number.achievement.level.regions[[j]]), "[y.boundary.values.", seq(number.achievement.level.regions[[j]]), " < min(yscale.range)] <- min(yscale.range)")))
for (i in seq(number.achievement.level.regions[[j]])) {
grid.polygon(x=get(paste0("x.boundary.values.", i)),
y=get(paste0("y.boundary.values.", i)),
default.units="native",
gp=gpar(fill=achievement.level.region.colors[[j]][i], lwd=0.8, col="white"))
}
}
if (!is.null(Report_Parameters$Assessment_Transition)) {
grid.lines(x=tmp.year.cut, y=yscale.range, default.units="native", gp=gpar(lwd=1.8, col=border.color))
grid.lines(x=tmp.year.cut+0.028, y=yscale.range, default.units="native", gp=gpar(lwd=0.4, col=border.color))
grid.lines(x=tmp.year.cut-0.028, y=yscale.range, default.units="native", gp=gpar(lwd=0.4, col=border.color))
if (grade.values[['any_scale_scores']]) {
tmp.transition.names <- names(SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]])
tmp.test.abbreviation <-
unlist(SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][grep('Assessment_Abbreviation', tmp.transition.names)])
tmp.test.abbreviation.text <- rep(" ", length(year.text))
tmp.test.abbreviation.text[which((low.year:high.year < Report_Parameters$Assessment_Transition$Year)[which(year.text!=" ")])] <-
tmp.test.abbreviation[1]
tmp.test.abbreviation.text[which((low.year:high.year >= Report_Parameters$Assessment_Transition$Year)[which(year.text!=" ")])] <-
tmp.test.abbreviation[2]
tmp.test.abbreviation.text[which(content_area.text==" ")] <- " "
grid.stext(tmp.test.abbreviation.text, x=unit(low.year:high.year, "native"), y=convertHeight(unit(0.07, "npc"), "native"), gp=gpar(cex=0.7))
grid.stext(sapply(content_area.text, capwords), x=unit(low.year:high.year, "native"), y=convertHeight(unit(0.03, "npc"), "native"), gp=gpar(cex=0.7))
}
}
if (is.null(Report_Parameters$Assessment_Transition) && sgPlot.show.content_area.progression) {
grid.stext(sapply(content_area.text, capwords), x=unit(low.year:high.year, "native"), y=convertHeight(unit(0.05, "npc"), "native"), gp=gpar(cex=0.75))
# grid.text(x=low.year:high.year, y=convertHeight(unit(0.05, "npc"), "native"), sapply(content_area.text, capwords), gp=gpar(col="white", cex=0.75), default.units="native")
}
if (connect.points=="Arrows") {
growth.arrow.coors.x <- c(.05, .85, .8, 1, .8, .85, .05, .053, .0555, .0575, .0585, .059, .0585, .0575, .0555, .053, .05)
growth.arrow.coors.y <- c(-.2, -.2, -.5, 0, .5, .2, seq(.2, -.2, length=11))
for (i in 1:length(gp.values)) {
tmp.lag <- which(is.na(rev(scale.scores.values[1:i]))==FALSE)
if (!is.na(gp.values[i]) & length(tmp.lag) > 0) {
lag.to.prior.score <- min(tmp.lag, na.rm=TRUE)
if (lag.to.prior.score == 1) my.lty <- 1 else my.lty <- 2
arrow.rise <- convertHeight(unit(scale.scores.values[i+1], "native") - unit(scale.scores.values[i+1-lag.to.prior.score], "native"), "inches")
arrow.run <- convertWidth(unit(lag.to.prior.score, "native") - unit(0, "native"), "inches")
arrow.angle <- atan2(as.numeric(arrow.rise),as.numeric(arrow.run))*180/pi
## Arrows connecting achievement scores
if (!is.na(arrow.angle)) {
pushViewport(viewport(x=unit(low.year+i-lag.to.prior.score, "native"), y=unit(scale.scores.values[i+1-lag.to.prior.score], "native"),
width=unit((lag.to.prior.score-0.08)/cos(arrow.angle*pi/180), "native"), height=unit(0.05, "npc"), angle=arrow.angle, just=c("left", "center"),
xscale=c(0, 1), yscale=c(-0.5, 0.5)))
grid.polygon(x=growth.arrow.coors.x, y=growth.arrow.coors.y, default.units="native",
gp=gpar(lwd=0.3, lty=my.lty, col=border.color, fill=arrow.color(as.numeric(gp.values[i]))))
grid.curve(0.05, -0.2, 0.05, 0.2, curvature=0.3, ncp=11, square=FALSE, default.units="native", gp=gpar(lwd=0.3, col=border.color))
popViewport()
}
}
}
} ## END Report_Parameters[['Configuration']][['Connect_Points']]=="Arrows"
if (paste(Grades[1], Content_Areas[1]) != tail(with(grades.content_areas.reported.in.state, paste(GRADE, CONTENT_AREA)), 1) & !is.na(cuts.ny1[1]) & show.fan){
for (i in seq(number.growth.levels)) {
grid.polygon(x=c(current.year, rep(current.year+grade.values$increment_for_projection_current, 2), current.year),
y=c(scale.scores.values[which(current.year==low.year:high.year)], max(yscale.range[1], cuts.ny1[i]),
min(yscale.range[2], cuts.ny1[i+1]), scale.scores.values[which(current.year==low.year:high.year)]),
default.units="native", gp=gpar(col=NA, lwd=0, fill=arrow.legend.color[i], alpha=0.45))
if (fan.extra) {
fan.extra.col <- arrow.legend.color[i]
fan.extra.x <- c(current.year, rep(current.year+grade.values$increment_for_projection_current, 2), current.year)
fan.extra.y <- c(scale.scores.values[which(current.year==low.year:high.year)], max(yscale.range[1], cuts.ny1[i]),
min(yscale.range[2], cuts.ny1[i+1]), scale.scores.values[which(current.year==low.year:high.year)])
eval(parse(text = fan.extras[i]))
}
grid.roundrect(x=unit(current.year+grade.values$increment_for_projection_current, "native"),
y=unit((max(yscale.range[1], cuts.ny1[i])+min(yscale.range[2], cuts.ny1[i+1]))/2, "native"),
height=unit(min(yscale.range[2], as.numeric(cuts.ny1[i+1])) - max(yscale.range[1], as.numeric(cuts.ny1[i])), "native"),
width=unit(0.04, "native"), r=unit(0.45, "snpc"), gp=gpar(lwd=0.3, col=border.color, fill=arrow.legend.color[i]))
if (show.fan.growth.labels && is.null(Report_Parameters[['SGP_Targets']])) {
grid.text(x=current.year+grade.values$increment_for_projection_current+0.05,
y=(max(yscale.range[1], cuts.ny1[i])+min(yscale.range[2], cuts.ny1[i+1]))/2, growth.level.labels[i],
default.units="native", just="left", gp=gpar(cex=0.4, col=border.color))
}
if (i != 1 & show.fan.cutscores) {
grid.text(x=current.year+grade.values$increment_for_projection_current+0.05, y=cuts.ny1[i], as.character(cuts.ny1.text[i]),
default.units="native", just="left", gp=gpar(cex=0.4, col=border.color))
}
}
}
if (!is.null(Report_Parameters[['SGP_Targets']])) {
for (i in tmp.target.types) {
if (length(grep("Current", i))==0) {
current.year.x.coor <- current.year
current.year.x.coor.lag <- min(which(!is.na(tail(Scale_Scores, -1))), na.rm=TRUE)
x.coor.label.adjustment <- -0.075; label.position <- "right"; tmp.index <- 1
if (is.null(Report_Parameters$Assessment_Transition)) {
tmp.achievement.level <- which(tail(head(Achievement_Levels, current.year.x.coor.lag+1), 1)==achievement.level.labels[[tmp.index]])
} else {
if (year.function(Report_Parameters$Assessment_Transition$Year, 0, 1) <= current.year.x.coor-current.year.x.coor.lag) tmp.index <- 2
tmp.achievement.level <- which(tail(head(Achievement_Levels, current.year.x.coor.lag+1), 1)==achievement.level.labels[[tmp.index]])
}
show.targets <- TRUE
} else {
current.year.x.coor <- current.year+grade.values$increment_for_projection_current
current.year.x.coor.lag <- grade.values$increment_for_projection_current
x.coor.label.adjustment <- 0.075; label.position <- "left"; tmp.index <- 1; show.targets <- show.fan
if (is.null(Report_Parameters$Assessment_Transition)) {
tmp.achievement.level <- which(head(Achievement_Levels, 1)==achievement.level.labels[[tmp.index]])
} else {
if (year.function(Report_Parameters$Assessment_Transition$Year, 0, 1) <= current.year.x.coor) tmp.index <- 2
tmp.achievement.level <- which(head(Achievement_Levels, 1)==achievement.level.labels[[tmp.index]])
}
}
if (show.targets) {
if (length(grep("CUKU", i))>0 & tmp.achievement.level <= level.to.get.cuku[[tmp.index]]) {
label.position <- c(label.position, "center")
tmp.target.label <- c(CU.label, target.label)
y.coordinates <- c(as.numeric(convertHeight(convertHeight(unit(Plotting_SGP_Scale_Score_Targets[[i]][['NY1']], "native"), "inches")+unit(0.0375, "inches"), "native")),
as.numeric(convertHeight(convertHeight(unit(Plotting_SGP_Scale_Score_Targets[[i]][['NY1']], "native"), "inches")-unit(0.0375, "inches"), "native")))
}
if (length(grep("CUKU", i))>0 & tmp.achievement.level > level.to.get.cuku[[tmp.index]]) {
label.position <- c(label.position, "top")
tmp.target.label <- c(KU.label, target.label)
y.coordinates <- c(Plotting_SGP_Scale_Score_Targets[[i]][['NY1']],
as.numeric(convertHeight(convertHeight(unit(Plotting_SGP_Scale_Score_Targets[[i]][['NY1']], "native"), "inches")-unit(0.1, "inches"), "native")))
}
if (length(grep("MUSU", i))>0 & tmp.achievement.level <= level.to.get.musu[[tmp.index]]) {
label.position <- c(label.position, "bottom")
tmp.target.label <- c(MU.label, target.label)
y.coordinates <- c(as.numeric(convertHeight(convertHeight(unit(Plotting_SGP_Scale_Score_Targets[[i]][['NY1']], "native"), "inches")+unit(0.1, "inches"), "native")),
Plotting_SGP_Scale_Score_Targets[[i]][['NY1']])
}
if (length(grep("MUSU", i))>0 & tmp.achievement.level > level.to.get.musu[[tmp.index]]) {
label.position <- c(label.position, "bottom")
tmp.target.label <- c(SU.label, target.label)
y.coordinates <- c(as.numeric(convertHeight(convertHeight(unit(Plotting_SGP_Scale_Score_Targets[[i]][['NY1']], "native"), "inches")+unit(0.1, "inches"), "native")),
Plotting_SGP_Scale_Score_Targets[[i]][['NY1']])
}
if (length(grep("CUSTOM", i))>0) {
label.position <- c(label.position, "bottom")
tmp.target.label <- NULL
y.coordinates <- c(as.numeric(convertHeight(convertHeight(unit(Plotting_SGP_Scale_Score_Targets[[i]][['NY1']], "native"), "inches")+unit(0.1, "inches"), "native")),
Plotting_SGP_Scale_Score_Targets[[i]][['NY1']])
}
grid.lines(x=c(current.year.x.coor-current.year.x.coor.lag, current.year.x.coor),
y=c(scale.scores.values[which(current.year.x.coor-current.year.x.coor.lag==low.year:high.year)], Plotting_SGP_Scale_Score_Targets[[i]][['NY1']]),
gp=gpar(lwd=0.8, col=border.color), default.units="native")
grid.circle(x=current.year.x.coor, y=Plotting_SGP_Scale_Score_Targets[[i]][['NY1']], r=unit(c(0.05, 0.04, 0.025, 0.0125), "inches"),
gp=gpar(col=c("black", "white", "black", "white"), lwd=0.01, fill=c("black", "white", "black", "white")), default.units="native")
if (!is.null(tmp.target.label)) grid.text(x=current.year.x.coor+x.coor.label.adjustment, y=y.coordinates, tmp.target.label, default.units="native", just=label.position, gp=gpar(cex=0.5, col=border.color))
}
}
}
grid.circle(x=low.year:high.year, y=scale.scores.values, r=unit(0.04, "inches"), gp=gpar(col=border.color, lwd=0.7, fill="white"), default.units="native")
# popViewport() Don't pop until after next section - extra mid-level distinction may be needed (first code chunk in 'Left Viewport')
#################################
### Left Viewport
#################################
unq.labels <- names(achievement.level.labels[[1]])
if (length(unique(unq.labels)) != number.achievement.level.regions[[1]]) {
# WIDA_GA for example - extra "mid-level" used for state exit criteria cut
tmp.n.achlev.regions <- length(unique(unq.labels))
dup.levels <- which(duplicated(unq.labels))
unq.levels <- which(!duplicated(unq.labels))
unq.levels <- unq.levels + c(diff(unq.levels) - 1, 0) # use (last) duplicate level for boundaries
max.level <- max(unq.levels)
mid.levels <- unq.levels %w/o% c(1, max.level)
for (k in dup.levels) {
tmp_fun <- get(paste0("level_1_", k - 1, "_curve"))
y.dup.points <- tmp_fun(tmp.x.points)
grid.lines(x = tmp.x.points, y = y.dup.points, default.units = "native",
gp = gpar(lwd = 1.4, lty = "dashed", col = "black"))
}
} else {
tmp.n.achlev.regions <- max.level <- number.achievement.level.regions[[1]]
unq.levels <- seq(tmp.n.achlev.regions)
mid.levels <- 2:(tmp.n.achlev.regions - 1)
}
popViewport() # growth.chart.vp
pushViewport(left.vp)
y.boundary.legend.1 <- c(yscale.range[1], yscale.range[1], rep(level_1_1_curve(xscale.range[1]), 2))
assign(paste0("y.boundary.legend.", max.level),
c(yscale.range[2], yscale.range[2], rep(eval(parse(text = paste0("level_1", "_", max.level-1, "_curve(xscale.range[1])"))), 2)))
if (tmp.n.achlev.regions > 2) {
for (i in mid.levels) {
ii <- unq.levels[which(unq.levels == i) - 1]
assign(paste0("y.boundary.legend.", i), eval(parse(text =
paste0("c(rep(level_1", "_", ii, "_curve(xscale.range[1]), 2), rep(level_1",
"_", i, "_curve(xscale.range[1]), 2))"))))
}
}
for (i in unq.levels){
grid.polygon(x = c(0,1,1,0), y = get(paste0("y.boundary.legend.", i)),
default.units = "native",
gp = gpar(fill = achievement.level.region.colors[[1]][i], lwd = 0.5, col = border.color, alpha = 0.7))
}
grid.text(x = 0.94, y = (level_1_1_curve(xscale.range[1]) + yscale.range[1])/2,
label = unq.labels[1], default.units = "native", just = "right",
gp = gpar(col = border.color, fontface = 2, fontfamily = font.fam, cex = left.vp.size, lineheight = legend.lheight))
grid.text(x = 0.94, y = (eval(parse(text = paste0("level_1", "_", max.level-1, "_curve(xscale.range[1])"))) + yscale.range[2])/2,
label = unq.labels[max.level], default.units = "native", just = "right",
gp = gpar(col = border.color, fontface = 2, fontfamily = font.fam, cex = left.vp.size, lineheight = legend.lheight))
if (tmp.n.achlev.regions > 2) {
for (i in mid.levels) {
ii <- unq.levels[which(unq.levels == i) - 1]
grid.text(x = .94,
y = (eval(parse(text = paste0("(level_1", "_", ii, "_curve(xscale.range[1]) + level_1",
"_", i, "_curve(xscale.range[1]))/2")))),
label = unq.labels[i],
gp = gpar(col = border.color, fontface = 2, fontfamily = font.fam, cex = left.vp.size, lineheight = legend.lheight),
default.units = "native", just = "right")
}
}
grid.lines(0, c(yscale.range[1], yscale.range[2]), gp = gpar(lwd = 0.8, col = border.color), default.units = "native")
popViewport()
############################################
### Growth and Margins Viewport
############################################
pushViewport(growth.and.margins.vp)
if (grade.values$year_span == 0) {
grid.roundrect(r=unit(.01, "snpc"), gp=gpar(lwd=1.8, col=border.color, clip=TRUE, fill=rgb(1, 1, 1, 0.5)))
} else {
grid.roundrect(r=unit(.01, "snpc"), gp=gpar(lwd=1.8, col=border.color, clip=TRUE))
}
popViewport()
##############################################
### Bottom Viewport
##############################################
pushViewport(bottom.vp)
if (is.null(Report_Parameters[['SGP_Targets']])) {
grid.text(x=low.year:high.year, y=2.67, grades.text, gp=gpar(col=border.color, cex=.75), default.units="native")
grid.text(x=low.year:high.year, y=2.3, year.text, gp=gpar(col=border.color, cex=.6), default.units="native")
grid.text(x=low.year:high.year, y=1.7, scale.scores.text, gp=gpar(col=border.color, cex=.65), default.units="native")
grid.text(x=low.year:high.year, y=1.3, ach.levels.text, gp=gpar(col=border.color, cex=.6), default.units="native")
grid.text(x=(low.year+1):high.year-0.5, y=0.7, gp.text, gp=gpar(col=border.color, cex=.65), default.units="native")
grid.text(x=(low.year+1):high.year-0.5, y=0.3, gp.levels.text, gp=gpar(col=border.color, cex=.6), default.units="native")
} else {
grid.text(x=low.year:high.year, y=2.75, grades.text, gp=gpar(col=border.color, cex=.6), default.units="native")
grid.text(x=low.year:high.year, y=2.45, year.text, gp=gpar(col=border.color, cex=.5), default.units="native")
grid.text(x=low.year:high.year, y=1.95, scale.scores.text, gp=gpar(col=border.color, cex=.5), default.units="native")
grid.text(x=low.year:high.year, y=1.65, ach.levels.text, gp=gpar(col=border.color, cex=.5), default.units="native")
grid.text(x=(low.year+1):high.year-0.5, y=0.85, gp.text, gp=gpar(col=border.color, cex=.5), default.units="native")
grid.text(x=(low.year+1):high.year-0.5, y=0.55, gp.levels.text, gp=gpar(col=border.color, cex=.5), default.units="native")
tmp.projection.names.list <- list()
if (length(grep("Current", tmp.target.types)) > 0) {
tmp.projection.names.list[["Current"]] <- grep("Current", tmp.target.types, value=TRUE)
}
if (length(grep("Current", tmp.target.types, invert=TRUE)) > 0) {
tmp.projection.names.list[["Lagged"]] <- grep("Current", tmp.target.types, value=TRUE, invert=TRUE)
}
for (i in seq_along(tmp.projection.names.list)) {
if (length(grep("Current", tmp.projection.names.list[[i]])) > 0) {
tmp.projection.names <- tmp.projection.names.list[[i]]
tmp.projection.year.from <- current.year
tmp.projection.year.to <- current.year+grade.values$increment_for_projection_current
if (!is.null(Report_Parameters$Assessment_Transition) && year.function(Report_Parameters$Assessment_Transition$Year, 0, 1) <= tmp.projection.year.from) {
achievement.level.label.index.from <- 2
} else {
achievement.level.label.index.from <- 1
}
if (!is.null(Report_Parameters$Assessment_Transition) && year.function(Report_Parameters$Assessment_Transition$Year, 0, 1) <= tmp.projection.year.to) {
achievement.level.label.index.to <- 2
} else {
achievement.level.label.index.to <- 1
}
tmp.achievement.level <- which(head(Achievement_Levels, 1)==achievement.level.labels[[achievement.level.label.index.from]])
} else {
tmp.projection.names <- tmp.projection.names.list[[i]]
tmp.projection.year.lag <- min(which(!is.na(tail(Scale_Scores, -1))), na.rm=TRUE)
tmp.projection.year.from <- current.year-tmp.projection.year.lag
tmp.projection.year.to <- current.year
if (!is.null(Report_Parameters$Assessment_Transition) && year.function(Report_Parameters$Assessment_Transition$Year, 0, 1) <= tmp.projection.year.from) {
achievement.level.label.index.from <- 2
} else {
achievement.level.label.index.from <- 1
}
if (!is.null(Report_Parameters$Assessment_Transition) && year.function(Report_Parameters$Assessment_Transition$Year, 0, 1) <= tmp.projection.year.to) {
achievement.level.label.index.to <- 2
} else {
achievement.level.label.index.to <- 1
}
tmp.achievement.level <- which(tail(head(Achievement_Levels, tmp.projection.year.lag+1), 1)==achievement.level.labels[[achievement.level.label.index.from]])
}
if (length(grep("CUSTOM", tmp.projection.names))==0) { ### Achievement/Growth Target Text associated with CUKU/MUSU targets
if ((length(grep("CUKU", tmp.projection.names)) > 0 & tmp.achievement.level <= level.to.get.cuku[[achievement.level.label.index.from]]) |
length(grep("MUSU", tmp.projection.names))==0) {
level.to.get.cuku.label <- names(achievement.level.labels[[achievement.level.label.index.to]])[level.to.get.cuku[[achievement.level.label.index.to]]+1]
grid.text(x=tmp.projection.year.to-0.5, y=1.35,
paste0(level.to.get.cuku.label, " (", SGP_Scale_Score_Targets[[grep("CUKU", tmp.projection.names, value=TRUE)]][['NY1']], ")"),
gp=gpar(col=border.color, cex=.4), default.units="native")
grid.text(x=tmp.projection.year.to-0.5, y=0.25,
paste0(CU.label, " (", SGP_Targets[[grep("CUKU", tmp.projection.names, value=TRUE)]], ")"),
gp=gpar(col=border.color, cex=.4), default.units="native")
} else {
level.to.get.cuku.label <- names(achievement.level.labels[[achievement.level.label.index.to]])[level.to.get.cuku[[achievement.level.label.index.to]]+1]
level.to.get.musu.label <- names(achievement.level.labels[[achievement.level.label.index.to]])[level.to.get.musu[[achievement.level.label.index.to]]+1]
grid.text(x=tmp.projection.year.to-0.5, y=1.35,
paste0(level.to.get.cuku.label, " (", SGP_Scale_Score_Targets[[grep("CUKU", tmp.projection.names, value=TRUE)]][['NY1']], ")/", level.to.get.musu.label, " (", SGP_Scale_Score_Targets[[grep("MUSU", tmp.projection.names, value=TRUE)]][['NY1']], ")"),
gp=gpar(col=border.color, cex=.4), default.units="native")
if (tmp.achievement.level <= level.to.get.musu[[achievement.level.label.index.from]]) {
grid.text(x=tmp.projection.year.to-0.5, y=0.25,
paste0(KU.label, " (", SGP_Targets[[grep('CUKU', tmp.projection.names, value=TRUE)]], ")/Move Up (", SGP_Targets[[grep('MUSU', tmp.projection.names, value=TRUE)]], ")"),
gp=gpar(col=border.color, cex=.4), default.units="native")
}
if (tmp.achievement.level > level.to.get.musu[[achievement.level.label.index.from]]) {
grid.text(x=tmp.projection.year.to-0.5, y=0.25,
paste0(KU.label, " (", SGP_Targets[[grep('CUKU', tmp.projection.names, value=TRUE)]], ")/Stay Up (", SGP_Targets[[grep('MUSU', tmp.projection.names, value=TRUE)]], ")"),
gp=gpar(col=border.color, cex=.4), default.units="native")
}
}
} else { ### Achievement/Growth Target text associated with CUSTOM plotting
level.to.get.cuku.label <- names(achievement.level.labels[[achievement.level.label.index.to]])[level.to.get.cuku[[achievement.level.label.index.to]]+1]
grid.text(x=tmp.projection.year.to-0.5, y=1.35,
paste0(level.to.get.cuku.label, " (", SGP_Scale_Score_Targets[[grep("CUSTOM", tmp.projection.names, value=TRUE)]][['NY1']], ")"),
gp=gpar(col=border.color, cex=.4), default.units="native")
grid.text(x=tmp.projection.year.to-0.5, y=0.25,
paste0(CU.label, " (", SGP_Targets[[grep("CUSTOM", tmp.projection.names, value=TRUE)]], ")"),
gp=gpar(col=border.color, cex=.4), default.units="native")
}
}
}
popViewport()
##############################
### Bottom Left.Right Viewport
##############################
pushViewport(bottom.left.right.vp)
if (is.null(Report_Parameters[['SGP_Targets']])) {
grid.lines(x=c(0,1), y=2, gp=gpar(lwd=1.8, col=border.color), default.units="native")
grid.lines(x=c(0,1), y=1, gp=gpar(lwd=1, col=border.color), default.units="native")
grid.lines(x=c(0,1), y=0, gp=gpar(lwd=1.8, col=border.color), default.units="native")
} else {
grid.lines(x=c(0,1), y=2.2, gp=gpar(lwd=1.8, col=border.color), default.units="native")
grid.lines(x=c(0,1), y=1.1, gp=gpar(lwd=1, col=border.color), default.units="native")
grid.lines(x=c(0,1), y=0, gp=gpar(lwd=1.8, col=border.color), default.units="native")
}
popViewport()
################################
### Bottom Right Viewport
################################
pushViewport(bottom.right.vp)
if (is.null(Report_Parameters[['SGP_Targets']])) {
grid.text(x=0.1, y=1.5, achievement.label, gp=gpar(col=border.color, cex=bottom.right.vp.size), just="left", default.units="native")
grid.text(x=0.1, y=.5, growth.label, gp=gpar(col=border.color, cex=bottom.right.vp.size), just="left", default.units="native")
} else {
grid.text(x=0.1, y=1.65, achievement.label, gp=gpar(col=border.color, cex=bottom.right.vp.size+0.1), just="left", default.units="native")
grid.text(x=0.1, y=0.55, growth.label, gp=gpar(col=border.color, cex=bottom.right.vp.size+0.1), just="left", default.units="native")
}
popViewport()
###########################
### Bottom Left Viewport
###########################
pushViewport(bottom.left.vp)
if (is.null(Report_Parameters[['SGP_Targets']])) {
grid.text(x=0.9, y=1.7, gsub("\\n", " ", scale_score.label), gp=gpar(col=border.color, cex=bottom.left.vp.size), just="right", default.units="native")
grid.text(x=0.9, y=1.3, achievement_level.label, gp=gpar(col=border.color, cex=bottom.left.vp.size), just="right", default.units="native")
grid.text(x=0.9, y=0.7, growth_percentile.label, gp=gpar(col=border.color, cex=bottom.left.vp.size), just="right", default.units="native")
grid.text(x=0.9, y=0.3, growth_level.label, gp=gpar(col=border.color, cex=bottom.left.vp.size), just="right", default.units="native")
} else {
grid.text(x=0.9, y=1.95, scale_score.label, gp=gpar(col=border.color, cex=bottom.left.vp.size-0.125), just="right", default.units="native")
grid.text(x=0.9, y=1.65, achievement_level.label, gp=gpar(col=border.color, cex=bottom.left.vp.size-0.125), just="right", default.units="native")
grid.text(x=0.9, y=1.35, achievement_target.label, gp=gpar(col=border.color, cex=bottom.left.vp.size-0.125), just="right", default.units="native")
grid.text(x=0.9, y=0.85, growth_percentile.label, gp=gpar(col=border.color, cex=bottom.left.vp.size-0.125), just="right", default.units="native")
grid.text(x=0.9, y=0.55, growth_level.label, gp=gpar(col=border.color, cex=bottom.left.vp.size-0.125), just="right", default.units="native")
grid.text(x=0.9, y=0.25, growth_target.label, gp=gpar(col=border.color, cex=bottom.left.vp.size-0.125), just="right", default.units="native")
}
popViewport()
###################################
### Right Viewport
###################################
if (is.null(Report_Parameters$Assessment_Transition)) { ## right.vp without ASSESSMENT_TRANSITION
pushViewport(right.vp)
grid.roundrect(width = unit(0.95, "native"), r = unit(.02, "snpc"),
gp = gpar(lwd = 1.8, col = border.color, fill = legend.fill.color), just = "center")
if (content.area.in.legend) {
if (!split.content_area.tf) {
grid.text(x = 0.5, y = 0.875,
label = content_area.label.pieces[[1]][1], default.units = "native",
gp = gpar(col = border.color, cex = content_area.label.pieces[[2]][1],
fontface = 2, fontfamily = font.fam))
} else {
grid.text(x = 0.5, y = 0.92,
label = content_area.label.pieces[[1]][1], default.units = "native",
gp = gpar(col = border.color, cex = content_area.label.pieces[[2]][1],
fontface = 2, fontfamily = font.fam))
grid.text(x = 0.5, y = 0.83,
label = content_area.label.pieces[[1]][2], default.units = "native",
gp = gpar(col = border.color, cex = content_area.label.pieces[[2]][2],
fontface = 2, fontfamily = font.fam))
}
top.offset <- 0
} else top.offset <- 0.175
grid.text(x = 0.08, y = (0.75 + top.offset),
label = achievement.label, default.units = "native", just = "left",
gp = gpar(col = border.color, cex = 0.85, fontface = 2, fontfamily = font.fam))
grid.text(x = 0.08, y = 0.525,
label = growth.label, default.units = "native", just = "left",
gp = gpar(col = border.color, cex = 0.75, fontface = 2, fontfamily = font.fam))
grid.text(x = 0.275, y = 0.455,
label = level.label, default.units = "native", just = "center",
gp = gpar(col = border.color, cex = 0.6))
grid.text(x = 0.75, y = 0.455,
label = percentiles.label, default.units = "native", just = "center",
gp = gpar(col = border.color, cex = 0.6))
grid.roundrect(x = unit(0.3, "native"), y = unit((0.64 + top.offset), "native"),
width = unit(0.3, "native"), height = unit(0.1, "native"), r = unit(0.06, "char"),
gp = gpar(col = "grey72", lwd = 0.4, fill = "grey72"))
grid.circle(x = 0.3, y = (0.64 + top.offset), r = unit(0.04, "inches"),
gp = gpar(col = border.color, lwd = 0.7, fill = "white"), default.units = "native")
if (!split.content_area.tf) {
grid.text(x = 0.7, y = (0.675 + top.offset), # just = "top",
label = paste(test.abbreviation, content.area.label), default.units = "native",
gp = gpar(col = border.color, cex = legend.size, lineheight = 1/legend.lheight))
grid.text(x = 0.7, y = (0.625 + top.offset),
label = scale_score.label, default.units = "native",
gp = gpar(col = border.color, cex = legend.size, lineheight = legend.lheight))
} else {
grid.text(x = 0.7, y = (0.7 + top.offset), label = test.abbreviation,
gp = gpar(col = border.color, cex = legend.size), default.units = "native")
grid.text(x = 0.7, y = (0.665 + top.offset), label = content_area.label.pieces[[1]][1],
gp = gpar(col = border.color, cex = legend.size), default.units = "native")
grid.text(x = 0.7, y = (0.63 + top.offset), label = content_area.label.pieces[[1]][2],
gp = gpar(col = border.color, cex = legend.size), default.units = "native")
grid.text(x = 0.7, y = (0.595 + top.offset), label = scale_score.label,
gp = gpar(col = border.color, cex = legend.size, lineheight = legend.lheight), default.units = "native")
}
if (extra.legend.element) {
for (ele in extra.legend.elements) {
eval(parse(text = ele))
}
}
y.center <- seq(0.05, 0.4, length = number.growth.levels+1)
arrow.legend.coors.x <- c(0.25, 0.75, 0.75, 1, 0.5, 0, 0.25)
arrow.legend.coors.y <- c(0, 0, 1.3, 1.1, 2, 1.1, 1.3)
growth.label.cex <- (0.5 - max(0, max(nchar(growth.level.labels.shortened))-9)*0.01) ### OLD multipler = 0.042
for (i in seq(number.growth.levels)) {
pushViewport(
viewport(x=unit(0.3, "native"), y=unit(y.center[i], "native"),
width=unit(0.07, "native"), height=unit(y.center[2]-y.center[1], "npc"),
just=c("center", "bottom"), xscale=c(0, 1), yscale=c(0, 2))
)
grid.polygon(x=arrow.legend.coors.x, y=arrow.legend.coors.y, default.units="native",
gp=gpar(lwd=0.3, col=border.color, fill=arrow.legend.color[i]))
popViewport()
grid.polygon(x=c(0.05, rep(0.1875, 2)),
y=c((head(y.center,1)+tail(y.center,1))/2, y.center[i], y.center[i]+y.center[2]-y.center[1]),
gp=gpar(col=NA, lwd=0, fill=arrow.legend.color[i], alpha=0.45), default.units="native")
if (fan.extra) {
fan.extra.col <- arrow.legend.color[i]
fan.extra.x <- c(0.05, rep(0.1875, 2))
fan.extra.y <- c((head(y.center,1)+tail(y.center,1))/2, y.center[i], y.center[i]+y.center[2]-y.center[1])
eval(parse(text = fan.extras[i]))
}
pushViewport(
viewport(x=unit(0.2, "native"), y=unit(y.center[i], "native"),
width=unit(0.04, "native"), height=unit(y.center[2]-y.center[1], "npc"),
just=c("center", "bottom"))
)
grid.roundrect(x=0.5, y=0.5, width=1, height=1, r=unit(.45, "snpc"),
gp=gpar(lwd=0.3, col=border.color, fill=arrow.legend.color[i]))
popViewport()
grid.text(x=0.36,
y=((y.center[1]+y.center[2])/2)+(i-1)*(y.center[2]-y.center[1]),
label = growth.level.labels.shortened[i], default.units="native",
gp=gpar(col=border.color, cex=growth.label.cex), just="left")
grid.text(x=0.925, y=((y.center[1]+y.center[2])/2)+(i-1)*(y.center[2]-y.center[1]),
label = growth.level.cutscores.text[i], default.units="native",
gp=gpar(col=border.color, cex=growth.label.cex), just="right")
}
} else { ### right.vp with ASSESSMENT_TRANSITION
pushViewport(right.vp)
y.boundary.legend.1 <- c(yscale.range[1], yscale.range[1], rep(level_2_1_curve(xscale.range[2]), 2))
assign(paste0("y.boundary.legend.", number.achievement.level.regions[[2]]),
c(yscale.range[2], yscale.range[2], rep(eval(parse(text=paste0("level_2", "_", number.achievement.level.regions[[2]]-1, "_curve(xscale.range[2])"))), 2)))
if (number.achievement.level.regions[[2]] > 2) {
for (i in 2:(number.achievement.level.regions[[2]]-1)) {
assign(paste0("y.boundary.legend.", i),
eval(parse(text=paste0("c(rep(level_2", "_", i-1, "_curve(xscale.range[2]), 2), rep(level_2", "_", i, "_curve(xscale.range[2]), 2))"))))
}
}
for (i in seq(number.achievement.level.regions[[2]])){
grid.polygon(x = c(0,1,1,0), y = get(paste0("y.boundary.legend.", i)), default.units = "native",
gp = gpar(fill = achievement.level.region.colors[[2]][i], lwd = 0.5, col = border.color, alpha = 0.7))
}
grid.text(label = names(achievement.level.labels[[2]])[1],
x = 0.06, y = (level_2_1_curve(xscale.range[2]) + yscale.range[1])/2,
gp = gpar(col = border.color, fontface = 2, fontfamily = font.fam, cex = .85),
default.units = "native", just = "left")
grid.text(label = names(achievement.level.labels[[2]])[number.achievement.level.regions[[2]]],
x = 0.06,
y = (eval(parse(text = paste0("level_2", "_", number.achievement.level.regions[[2]]-1, "_curve(xscale.range[2])"))) + yscale.range[2])/2,
gp = gpar(col = border.color, fontface = 2, fontfamily = font.fam, cex = .85),
default.units = "native", just = "left")
if (number.achievement.level.regions[[2]] > 2) {
for (i in 2:(number.achievement.level.regions[[2]]-1)) {
grid.text(label = names(achievement.level.labels[[2]])[i],
x = 0.06,
y = (eval(parse(text = paste0("(level_2", "_", i-1, "_curve(xscale.range[2]) + level_2", "_", i, "_curve(xscale.range[2]))/2")))),
gp = gpar(col = border.color, fontface = 2, fontfamily = font.fam, cex = .85),
default.units = "native", just = "left")
}
}
grid.lines(0, c(yscale.range[1], yscale.range[2]), gp = gpar(lwd = 0.8, col = border.color), default.units = "native")
}
popViewport()
####################################
### No Data Viewport
####################################
if (!grade.values[['any_scale_scores']]) {
pushViewport(no.data.vp)
no.data.text <- paste("No", test.abbreviation, content.area.label, "Data")
no.data.text.pieces <- labelSplit(no.data.text)
if (length(no.data.text.pieces[[1]])==1) {
grid.text(x=0.5, y=0.5, no.data.text.pieces[[1]][1], gp=gpar(col="grey40", cex=3.5))
} else {
grid.text(x=0.475, y=0.575, no.data.text.pieces[[1]][1], gp=gpar(col="grey40", cex=2.25))
grid.text(x=0.475, y=0.425, no.data.text.pieces[[1]][2], gp=gpar(col="grey40", cex=2.25))
}
grid.roundrect(r=unit(0.02, "snpc"), gp=gpar(fill="white", lwd=0, col="white", alpha=0.5))
popViewport()
}
popViewport()
} ## END studentGrowthPlot Function
CenterForAssessment/SGP documentation built on April 22, 2024, 3:16 p.m.
R Package Documentation
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Defines functions `studentGrowthPlot`
`studentGrowthPlot` <-
function(Scale_Scores, ## Vector of Scale Scores
Plotting_Scale_Scores, ## Score used for plotting, if missing, then Scale_Scores are used
## for plotting, if supplied Scale_Scores used for text
Achievement_Levels, ## NOTE: Achievement_Levels must/should be supplied as factors with appropriate level codings
SGP, ## Vector of SGPs
SGP_Levels, ## Vector of SGP Levels
Grades, ## Vector of Grade levels for student
Content_Areas, ## Vector of Content Areas for student
Cuts, ## Vector of NY1, NY2, and NY3 cutscores
Plotting_Cuts, ## Vector of NY1, NY2, and NY3 cutscores used for plotting (transformed if non-vertical/equated scale)
SGP_Targets, ## Vector of CUKU, CUKU_Current, MUSU, MUSU_Current (multi) year targets
SGP_Scale_Score_Targets, ## Vector of CUKU, CUKU_Current, MUSU, MUSU_Current scale score targets
Plotting_SGP_Scale_Score_Targets, ## Vector of CUKU, CUKU_Current, MUSU, MUSU_Current scale score targets for plotting (transformed if non-vertical/equated scale)
Cutscores, ## data.frame of long formatted achievement level cutscores
Years, ## Vector of years corresponding to Scale_Scores, Content_Areas, ... arguments supplied
Report_Parameters) { ## list containing Current_Year, Content_Area, Content_Area_Title, State, Denote_Content_Area, SGP_Targets,
## Configuration, Language, Assessment_Transition, Fan
############################################
### Create relevant variables
############################################
YEAR <- CONTENT_AREA <- GRADE <- GRADE_NUMERIC <- CUTSCORES <- CUTLEVEL <- level_1_1_curve <- level_2_1_curve <- NULL ## To prevent R CMD check warnings
CUTSCORES_EQUATED <- CUTSCORES_TRANSFORMED <- NULL
number.growth.levels <- length(SGP::SGPstateData[[Report_Parameters$State]][["Growth"]][["Levels"]])
if (!is.null(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Growth_Level_Labels"]])) {
growth.level.labels <- as.character(unlist(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Growth_Level_Labels"]]))
growth.level.labels.shortened <- names(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Growth_Level_Labels"]])
} else {
growth.level.labels <- growth.level.labels.shortened <- SGP::SGPstateData[[Report_Parameters$State]][["Growth"]][["Levels"]]
}
growth.level.cutscores <- SGP::SGPstateData[[Report_Parameters$State]][["Growth"]][["Cutscores"]][["Cuts"]]
growth.level.cutscores.text <- SGP::SGPstateData[[Report_Parameters$State]][["Growth"]][["Cutscores"]][["Labels"]]
content.area.label <- SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Content_Areas_Labels"]][[Report_Parameters$Content_Area_Title]]
if (!is.null(SGP::SGPstateData[[Report_Parameters$State]][["SGP_Configuration"]][["content_area.projection.sequence"]][[Report_Parameters$Content_Area]])) {
grades.content_areas.reported.in.state <- data.frame(
GRADE=SGP::SGPstateData[[Report_Parameters$State]][["SGP_Configuration"]][["grade.projection.sequence"]][[Report_Parameters$Content_Area]],
YEAR_LAG=c(1, SGP::SGPstateData[[Report_Parameters$State]][["SGP_Configuration"]][["year_lags.projection.sequence"]][[Report_Parameters$Content_Area]]),
CONTENT_AREA=SGP::SGPstateData[[Report_Parameters$State]][["SGP_Configuration"]][["content_area.projection.sequence"]][[Report_Parameters$Content_Area]],
stringsAsFactors=FALSE
)
} else {
grades.content_areas.reported.in.state <- data.frame(
GRADE=SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Grades_Reported"]][[Report_Parameters$Content_Area]],
YEAR_LAG=c(1, diff(as.numeric(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Grades_Reported"]][[Report_Parameters$Content_Area]]))),
CONTENT_AREA=Report_Parameters$Content_Area,
stringsAsFactors=FALSE
)
}
grades.content_areas.reported.in.state <- subset(grades.content_areas.reported.in.state, !(is.na(GRADE) & is.na(CONTENT_AREA)))
grades.content_areas.reported.in.state$GRADE_NUMERIC <- (as.numeric(grades.content_areas.reported.in.state$GRADE[2])-1)+c(0, cumsum(tail(grades.content_areas.reported.in.state$YEAR_LAG, -1)))
grade.rpt.index <- intersect(grep(paste0("^", Grades[1], "$"), grades.content_areas.reported.in.state$GRADE), grep(paste0("^", Content_Areas[1], "$"), grades.content_areas.reported.in.state$CONTENT_AREA)) # needed when transition grade is the same - e.g. Grade 9 ELA to Grade 9 PSAT (not 9 to EOCT)
if (length(grade.rpt.index)==0) {
if (max(Grades, na.rm = TRUE) == "EOCT") {
grade.rpt.index <- min(grep(max(Grades, na.rm = TRUE), grades.content_areas.reported.in.state$GRADE))
} else grade.rpt.index <- min(nrow(grades.content_areas.reported.in.state), (max(grep(max(Grades, na.rm = TRUE), grades.content_areas.reported.in.state$GRADE)) + min(which(!is.na(Grades))) - 1))
}
grades.content_areas.reported.in.state$YEAR <- Report_Parameters$Current_Year
for (y in (grade.rpt.index-1):1) grades.content_areas.reported.in.state$YEAR[y] <- yearIncrement(grades.content_areas.reported.in.state$YEAR[y+1], 0, grades.content_areas.reported.in.state$YEAR_LAG[y+1])
if (grade.rpt.index != nrow(grades.content_areas.reported.in.state)) {
for (y in (grade.rpt.index+1):max((grade.rpt.index+1),(nrow(grades.content_areas.reported.in.state)))) { # -1))) {
grades.content_areas.reported.in.state$YEAR[y] <-
yearIncrement(grades.content_areas.reported.in.state$YEAR[y-1], 0, -grades.content_areas.reported.in.state$YEAR_LAG[y]) # YEAR_LAG[y] not YEAR_LAG[y-1] because YEAR_LAG= above is offset by 1 w/ c(1, SGP::...)
}
}
if (!is.null(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Earliest_Year_Reported"]])) {
grade.rpt.tf <- sapply(1:nrow(grades.content_areas.reported.in.state), function(y) grades.content_areas.reported.in.state$YEAR[y] >=
SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Earliest_Year_Reported"]][[grades.content_areas.reported.in.state$CONTENT_AREA[y]]])
if (!all(grade.rpt.tf)) {
grades.content_areas.reported.in.state <- grades.content_areas.reported.in.state[-which(!grade.rpt.tf),]
}
}
if (!is.null(transition.grade <- SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][["Grade"]])) {
post.trans.content_areas <- names(SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][[paste0('Content_Areas_Labels.', transition.grade)]])
transition.grade.numeric <- suppressWarnings(min(as.data.table(grades.content_areas.reported.in.state)[as.numeric(GRADE) >= as.numeric(transition.grade) & CONTENT_AREA %in% post.trans.content_areas, GRADE_NUMERIC]))
grades.content_areas.reported.in.state <- grades.content_areas.reported.in.state[union(sort(c(
which(grades.content_areas.reported.in.state$CONTENT_AREA %in% c(Content_Areas, post.trans.content_areas)))),
max(grep(paste0("^", Grades[!is.na(Grades)][1], "$"), grades.content_areas.reported.in.state$GRADE)):nrow(grades.content_areas.reported.in.state)),]
max.year.index <- max(grep(Report_Parameters$Current_Year, grades.content_areas.reported.in.state$YEAR))
if (transition.grade.numeric %in% grades.content_areas.reported.in.state$GRADE_NUMERIC[1:max.year.index]) {
tmp.gcar <- subset(grades.content_areas.reported.in.state,
!(YEAR >= Report_Parameters$Current_Year & !CONTENT_AREA %in% post.trans.content_areas))
if (all(Content_Areas[!is.na(Grades)] %in% tmp.gcar$CONTENT_AREA)) {
grades.content_areas.reported.in.state <- tmp.gcar
if (!all(diff(grades.content_areas.reported.in.state$GRADE_NUMERIC)==1)) {
grades.content_areas.reported.in.state$GRADE_NUMERIC <- (as.numeric(grades.content_areas.reported.in.state$GRADE_NUMERIC[2])-1)+c(0, cumsum(tail(grades.content_areas.reported.in.state$YEAR_LAG, -1)))
}
} else {
if (Grades[!is.na(Grades)][1] == transition.grade) {
grd.trans.index <- intersect(grep(paste0("^", Grades[!is.na(Grades)][1], "$"), grades.content_areas.reported.in.state$GRADE), grep(paste0("^", Content_Areas[1], "$"), grades.content_areas.reported.in.state$CONTENT_AREA)) # needed when transition grade is the same - e.g. Grade 9 ELA to Grade 9 PSAT (not 9 to EOCT)
end <- nrow(grades.content_areas.reported.in.state)
grades.content_areas.reported.in.state$YEAR[grd.trans.index:1] <- as.numeric(grades.content_areas.reported.in.state$YEAR[grd.trans.index]) - c(0, cumsum(rep(1, length(grades.content_areas.reported.in.state$YEAR_LAG[grd.trans.index:1])-1)))
grades.content_areas.reported.in.state$GRADE_NUMERIC[grd.trans.index:end] <- grades.content_areas.reported.in.state$GRADE_NUMERIC[grd.trans.index] + cumsum(c(1, tail(grades.content_areas.reported.in.state$YEAR_LAG[grd.trans.index:end], -1)))
}
}
}
}
test.abbreviation <- SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Abbreviation"]]
if (identical(SGP::SGPstateData[[Report_Parameters$State]][['Assessment_Program_Information']][['Test_Season']], "Fall")) {
test.season <- SGP::SGPstateData[[Report_Parameters$State]][['Assessment_Program_Information']][['Test_Season']]
} else {
test.season <- NULL
}
if (!is.null(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Use_EOCT_Label"]])) {
print.eoct.content.area <- FALSE
} else print.eoct.content.area <- TRUE
border.color <- "grey25"
if (is.null(SGP::SGPstateData[[Report_Parameters$State]][["SGP_Configuration"]][["arrow.legend.color"]])) {
arrow.legend.color <- rev(diverge_hcl(number.growth.levels, h = c(180, 40), c = 255, l = c(20, 100)))
} else {
arrow.legend.color <- SGP::SGPstateData[[Report_Parameters$State]][["SGP_Configuration"]][["arrow.legend.color"]]
}
if (is.null(SGP::SGPstateData[[Report_Parameters$State]][["SGP_Configuration"]][["sgp.target.types"]])) {
sgp.target.types <- c("Scale_Score_Targets_CUKU", "Scale_Score_Targets_MUSU", "Scale_Score_Targets_Current_CUKU", "Scale_Score_Targets_Current_MUSU")
} else {
sgp.target.types <- SGP::SGPstateData[[Report_Parameters$State]][["SGP_Configuration"]][["sgp.target.types"]]
}
missing.data.symbol <- "--"
if (!is.null(my.year.span <- SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["sgPlot.year.span"]])) {
studentGrowthPlot.year.span <- my.year.span
} else studentGrowthPlot.year.span <- 5
if (is.null(Report_Parameters[['Denote_Content_Area']]) || Report_Parameters[['Denote_Content_Area']]==FALSE) {
legend.fill.color <- "white"
} else {
legend.fill.color <- rgb(0,0,1,0.25)
}
if (is.null(Report_Parameters[['Configuration']][['Connect_Points']])) {
connect.points <- "Arrows"
} else {
connect.points <- Report_Parameters[['Configuration']][['Connect_Points']]
}
if (!is.null(Report_Parameters[['SGP_Targets']])) {
if (all(c("sgp.projections", "sgp.projections.lagged") %in% Report_Parameters[['SGP_Targets']]) | all(c("sgp.projections.baseline", "sgp.projections.lagged.baseline") %in% Report_Parameters[['SGP_Targets']])) tmp.target.types <- names(unlist(SGP_Targets)[!is.na(unlist(SGP_Targets))])
if (identical("sgp.projections", Report_Parameters[['SGP_Targets']]) | identical("sgp.projections.baseline", Report_Parameters[['SGP_Targets']])) tmp.target.types <- grep("Current", names(unlist(SGP_Targets)[!is.na(unlist(SGP_Targets))]), value=TRUE)
if (identical("sgp.projections.lagged", Report_Parameters[['SGP_Targets']]) | identical("sgp.projections.lagged.baseline", Report_Parameters[['SGP_Targets']])) tmp.target.types <- grep("Current", names(unlist(SGP_Targets)[!is.na(unlist(SGP_Targets))]), value=TRUE, invert=TRUE)
if (identical("CUSTOM", Report_Parameters[['SGP_Targets']])) tmp.target.types <- grep("CUSTOM", names(unlist(SGP_Targets)[!is.na(unlist(SGP_Targets))]), value=TRUE)
}
if (!is.null(SGP::SGPstateData[[Report_Parameters$State]][['SGP_Configuration']][['sgPlot.show.content_area.progression']]) |
!is.null(Report_Parameters[['Configuration']][['Assessment_Transition']])) {
sgPlot.show.content_area.progression <- SGP::SGPstateData[[Report_Parameters$State]][['SGP_Configuration']][['sgPlot.show.content_area.progression']]
} else {
if (is.null(Report_Parameters[['Configuration']][['Show_Content_Area_Progression']])) {
sgPlot.show.content_area.progression <- FALSE
} else {
sgPlot.show.content_area.progression <- Report_Parameters[['Configuration']][['Show_Content_Area_Progression']]
}
}
if (sgPlot.show.content_area.progression) print.eoct.content.area <- FALSE else print.eoct.content.area <- TRUE
if (is.null(SGP::SGPstateData[[Report_Parameters$State]][['SGP_Configuration']][['Show_Fan_Cut_Scores']])) {
show.fan.cutscores <- FALSE
} else {
show.fan.cutscores <- TRUE
}
if (is.null(SGP::SGPstateData[[Report_Parameters$State]][['SGP_Configuration']][['Show_Fan_Growth_Labels']])) {
show.fan.growth.labels <- TRUE
} else {
show.fan.growth.labels <- FALSE
}
if (is.null(Report_Parameters[['Configuration']][['Font_Size']])) {
title.ca.size <- 1.8
legend.size <- 0.5
legend.lheight <- 1
left.vp.size <- 0.85
bottom.right.vp.size <- 1.2
bottom.left.vp.size <- 0.7
} else {
if (!is.null(Report_Parameters[['Configuration']][['Font_Size']][['title.ca.size']])) {
title.ca.size <- Report_Parameters[["Configuration"]][["Font_Size"]][["title.ca.size"]]
} else title.ca.size <- 1.8
if (!is.null(Report_Parameters[['Configuration']][['Font_Size']][['legend.size']])) {
legend.size <- Report_Parameters[['Configuration']][['Font_Size']][['legend.size']]
} else legend.size <- 0.5
if (!is.null(Report_Parameters[['Configuration']][['Font_Size']][['legend.lheight']])) {
legend.lheight <- Report_Parameters[['Configuration']][['Font_Size']][['legend.lheight']]
} else legend.lheight <- 1
if (!is.null(Report_Parameters[['Configuration']][['Font_Size']][['left.vp.size']])) {
left.vp.size <- Report_Parameters[['Configuration']][['Font_Size']][['left.vp.size']]
} else left.vp.size <- 0.85
if (!is.null(Report_Parameters[['Configuration']][['Font_Size']][['bottom.right.vp.size']])) {
bottom.right.vp.size <- Report_Parameters[["Configuration"]][["Font_Size"]][["bottom.right.vp.size"]]
} else bottom.right.vp.size <- 1.2
if (!is.null(Report_Parameters[['Configuration']][['Font_Size']][['bottom.left.vp.size']])) {
bottom.left.vp.size <- Report_Parameters[['Configuration']][['Font_Size']][['bottom.left.vp.size']]
} else bottom.left.vp.size <- 0.7
}
if (!is.null(Report_Parameters[['Configuration']][['Font_Family']])) {
font.fam <- Report_Parameters[['Configuration']][['Font_Family']]
} else font.fam <- "Helvetica-Narrow"
if (is.null(Report_Parameters[['Configuration']][['Language']])) {
achievement.label <- "Achievement"
achievement_level.label <- "Achievement Level"
achievement_target.label <- "Achievement Target"
growth.label <- "Growth"
growth_percentile.label <- "Growth Percentile"
growth_level.label <- "Growth Level"
growth_target.label <- "Growth Target"
level.label <- "Level"
percentiles.label <- "Percentiles"
scale_score.label <- "Scale Score"
grade.label <- "Grade"
CU.label <- "Catch Up"
KU.label <- "Keep Up"
MU.label <- "Move Up"
SU.label <- "Stay Up"
target.label <- "Target"
}
if (identical(toupper(Report_Parameters[['Configuration']][['Language']]), "SPANISH")) { # WIDA_CO and NH
achievement.label <- "Resultado"
achievement_level.label <- "Nivel de Capacitaci\uF3n" # unicode for accented o is \uF3 - http://www.ascii.cl/htmlcodes.htm
achievement_target.label <- "Meta de Capacitaci\uF3n"
growth.label <- "Crecimiento"
growth_percentile.label <- "Porcentaje de Crecimiento"
growth_level.label <- "Nivel de Crecimiento"
growth_target.label <- "Meta de Crecimiento"
level.label <- "Niveles"
percentiles.label <- "El Percentil"
scale_score.label <- "Escala"
grade.label <- "Grado"
CU.label <- "Alcanzar"
KU.label <- "Guadar"
MU.label <- "Avanzar"
SU.label <- "Mantener"
target.label <- "Meta"
SGP_Levels <- SGP::SGPstateData[[Report_Parameters$State]][["Growth"]][["Levels"]][match(SGP_Levels, SGP::SGPstateData[[paste(head(unlist(strsplit(Report_Parameters$State, "_")), -1), collapse="_")]][["Growth"]][["Levels"]])]
}
if (is.list(Report_Parameters[["Configuration"]][["Language"]])) { # See WIDA_GA for example
achievement.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["achievement.label"]]
achievement_level.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["achievement_level.label"]]
achievement_target.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["achievement_target.label"]]
growth.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["growth.label"]]
growth_percentile.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["growth_percentile.label"]]
growth_level.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["growth_level.label"]]
growth_target.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["growth_target.label"]]
level.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["level.label"]]
percentiles.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["percentiles.label"]]
scale_score.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["scale_score.label"]]
grade.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["grade.label"]]
CU.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["CU.label"]]
KU.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["KU.label"]]
MU.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["MU.label"]]
SU.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["SU.label"]]
target.label <- Report_Parameters[["Configuration"]][["Language"]][["Custom"]][["target.label"]]
SGP_Levels <- SGP::SGPstateData[[Report_Parameters$State]][["Growth"]][["Levels"]][match(SGP_Levels, SGP::SGPstateData[[paste(head(unlist(strsplit(Report_Parameters$State, "_")), -1), collapse = "_")]][["Growth"]][["Levels"]])]
}
if (!is.null(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Content_Area_in_Legend"]])) {
content.area.in.legend <- SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Content_Area_in_Legend"]]
} else content.area.in.legend <- TRUE
if (!is.null(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Legend_Extra"]])) {
extra.legend.element <- TRUE
extra.legend.elements <- SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Legend_Extra"]]
} else extra.legend.element <- FALSE
if (is.null(Report_Parameters[['Fan']])) {
show.fan <- TRUE
} else {
show.fan <- eval(parse(text=Report_Parameters[['Fan']]))
}
if (!is.null(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Fan_Extra"]])) {
fan.extra <- TRUE
fan.extras <- SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Fan_Extra"]]
} else fan.extra <- FALSE
Cutscores <- copy(Cutscores)
if (!is.null(Report_Parameters[['Assessment_Transition']])) Cutscores[,CUTSCORES:=CUTSCORES_EQUATED]
if (is.null(Report_Parameters[['Assessment_Transition']]) &&
Report_Parameters$Current_Year %in% SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Transformed_Achievement_Level_Cutscores"]][[Report_Parameters$Content_Area_Title]]) {
Cutscores[,CUTSCORES:=CUTSCORES_TRANSFORMED]
}
##############################
### Utility functions
##############################
`%w/o%` <- function(x, y) x[!x %in% y]
ach.level.labels <- function(perlevel){
tmp <- unlist(sapply(achievement.level.labels, names), use.names=FALSE)[match(perlevel, unlist(achievement.level.labels))]
tmp[is.na(tmp) & !is.na(perlevel)] <- perlevel[is.na(tmp) & !is.na(perlevel)]
tmp[is.na(tmp)] <- missing.data.symbol
return(tmp)
}
sgp.level.labels <- function(sgp_level){
sgp_level[is.na(sgp_level)] <- missing.data.symbol
return(sgp_level)
}
arrow.color <- function(sgp){
arrow.legend.color[findInterval(sgp, growth.level.cutscores)+1]
}
get.my.cutscore.year <- function(state, content_area, year, cutlevel) {
year <- tail(sort(c(SGP::SGPstateData[[state]][["Student_Report_Information"]][["Earliest_Year_Reported"]][[content_area]], year)), 1)
tmp.index <- grep(content_area, names(SGP::SGPstateData[[state]][["Achievement"]][["Cutscores"]]))
tmp.cutlevels <- sapply(tmp.index, function(x) length(SGP::SGPstateData[[state]][["Achievement"]][["Cutscores"]][[x]][[1]]))
tmp.cutscore.years <- unique(sapply(strsplit(names(SGP::SGPstateData[[state]][["Achievement"]][["Cutscores"]])[tmp.index], "[.]"), '[', 2))
tmp.cutscore.years <- tmp.cutscore.years[cutlevel <= tmp.cutlevels]
if (year %in% tmp.cutscore.years) {
return(year)
} else {
if (year==sort(c(year, tmp.cutscore.years))[1]) {
return(NA)
} else {
return(sort(tmp.cutscore.years)[which(year==sort(c(year, tmp.cutscore.years)))-1])
}
}
}
interpolate.grades <- function(grades, content_areas, data.year.span, scale_scores) {
last.number <- function (x) {
if (sum(!is.na(x)) > 0) return(max(which(!is.na(x)))) else return (0)
}
first.number <- function (x) {
if (sum(!is.na(x)) > 0 ) return(min(which(!is.na(x)))) else return (0)
}
convert.grades <- function(grades, content_areas, to="GRADE_NUMERIC", lookup=grades.content_areas.reported.in.state) {
if (to=="GRADE_NUMERIC") {
return(as.numeric(lookup$GRADE_NUMERIC[match(paste(grades, content_areas), paste(lookup$GRADE, lookup$CONTENT_AREA))]))
}
if (to=="GRADE") {
return(as.character(lookup$GRADE[match(grades, lookup$GRADE_NUMERIC)]))
}
}
extend.grades <- function (x, content_areas) {
tmp.grades.numeric <- x
tmp.content_areas <- grades.content_areas.reported.in.state$CONTENT_AREA[match(x, grades.content_areas.reported.in.state$GRADE_NUMERIC)]
if ((length(tmp.content_areas) > length(x)) & any(duplicated(grades.content_areas.reported.in.state$GRADE_NUMERIC))) {
tmp.dups <- grades.content_areas.reported.in.state$CONTENT_AREA[duplicated(grades.content_areas.reported.in.state$GRADE_NUMERIC)]
tmp.content_areas <- tmp.content_areas[!tmp.content_areas %in% tmp.dups]
}
tmp.grades <- convert.grades(x, to="GRADE")
tmp.head <- min(which(x[!is.na(x)][1] <= grades.content_areas.reported.in.state$GRADE_NUMERIC), na.rm=TRUE)
tmp.tail <- min(which(tail(x[!is.na(x)], 1) <= grades.content_areas.reported.in.state$GRADE_NUMERIC), na.rm=TRUE)
if (tmp.head==1) {
tmp.grades <- c("GRADE_LOWER", tmp.grades); tmp.content_areas <- c("PLACEHOLDER", tmp.content_areas); tmp.grades.numeric <- c(NA, tmp.grades.numeric)
} else {
tmp.grades <- c(grades.content_areas.reported.in.state$GRADE[tmp.head-1], tmp.grades)
tmp.content_areas <- c(grades.content_areas.reported.in.state$CONTENT_AREA[tmp.head-1], tmp.content_areas)
tmp.grades.numeric <- c(grades.content_areas.reported.in.state$GRADE_NUMERIC[tmp.head-1], tmp.grades.numeric)
}
if (tmp.tail==dim(grades.content_areas.reported.in.state)[1]) {
tmp.grades <- c(tmp.grades, "GRADE_UPPER");
tmp.content_areas <- c(tmp.content_areas, "PLACEHOLDER");
tmp.grades.numeric <- c(tmp.grades.numeric, NA)
} else {
tmp.grades <- c(tmp.grades, grades.content_areas.reported.in.state$GRADE[tmp.tail+1])
tmp.content_areas <- c(tmp.content_areas, grades.content_areas.reported.in.state$CONTENT_AREA[tmp.tail+1])
tmp.grades.numeric <- c(tmp.grades.numeric, grades.content_areas.reported.in.state$GRADE_NUMERIC[tmp.tail+1])
}
tmp.grades[is.na(tmp.grades)] <- tmp.grades.numeric[is.na(tmp.grades)]
return(data.frame(GRADE=tmp.grades, GRADE_NUMERIC=tmp.grades.numeric, CONTENT_AREA=tmp.content_areas, stringsAsFactors=FALSE))
}
first.scale.score <- first.number(head(grades, data.year.span))
last.scale.score <- last.number(grades)
any.scale.scores <- any(!is.na(scale_scores))
grades <- convert.grades(grades, content_areas)
if (last.scale.score < data.year.span) {
grades[(last.scale.score+1):data.year.span] <- (grades[last.scale.score]-1):(grades[last.scale.score] - (data.year.span - last.scale.score))
grades[grades < min(grades.content_areas.reported.in.state$GRADE_NUMERIC)] <- min(grades.content_areas.reported.in.state$GRADE_NUMERIC)
}
if (first.scale.score > 1) {
grades[1:(first.scale.score-1)] <- (grades[first.scale.score] + (first.scale.score - 1)):(grades[first.scale.score]+1)
grades[grades > max(grades.content_areas.reported.in.state$GRADE_NUMERIC)] <- max(grades.content_areas.reported.in.state$GRADE_NUMERIC)
if (any(is.na(grades))) {
if (1 %in% which(is.na(grades))) grades[1] <- grades[min(which(!is.na(grades)))]+(min(which(!is.na(grades)))-1) # `approx` doesn't work when first value is NA
if (length(grades) %in% which(is.na(grades))) grades[length(grades)] <- grades[min(which(!is.na(grades)))]-(length(grades)-min(which(!is.na(grades)))) # `approx` doesn't work when last value is NA
grades[which(is.na(grades))] <- approx(grades, xout=which(is.na(grades)))$y
grades <- as.integer(grades)
}
if (!grades[1] %in% grades.content_areas.reported.in.state$GRADE_NUMERIC) {
grades[1] <- grades.content_areas.reported.in.state$GRADE_NUMERIC[which.min(grades[1] > grades.content_areas.reported.in.state$GRADE_NUMERIC)-1]
}
if (any(!grades %in% grades.content_areas.reported.in.state$GRADE_NUMERIC)) {
for (tmp.missing.grades in which(!grades %in% grades.content_areas.reported.in.state$GRADE_NUMERIC)) {
grades[tmp.missing.grades] <-
grades.content_areas.reported.in.state$GRADE_NUMERIC[which.max(grades[tmp.missing.grades] < grades.content_areas.reported.in.state$GRADE_NUMERIC)]
}
}
}
if (any(is.na(grades))) {
tmp.na <- which(is.na(grades))
tmp.not.na <- max(which(!is.na(grades)))
while (any(is.na(grades))) {
nearest.not.na <- tmp.na[which.min(abs(tmp.na-tmp.not.na))]; tmp.dif <- (tmp.not.na-nearest.not.na)
tmp.index <- match(grades[tmp.not.na], grades.content_areas.reported.in.state$GRADE_NUMERIC)+tmp.dif
if (tmp.index <= 0L) tmp.index <- 1
if (tmp.index > nrow(grades.content_areas.reported.in.state)) tmp.index <- nrow(grades.content_areas.reported.in.state)
grades[tmp.not.na-tmp.dif] <- grades.content_areas.reported.in.state$GRADE_NUMERIC[tmp.index]
tmp.na <- which(is.na(grades)); tmp.not.na <- min(which(!is.na(grades)))
}
if (!length(grades) %in% tmp.na && length(intersect(tmp.na, which(!is.na(grades)))) > 0) {
tmp.indices <- intersect(tmp.na, which(!is.na(grades)))
grades[tmp.indices] <- NA
grades[tmp.indices] <- round(approx(grades, xout=tmp.indices)$y)
}
}
if (grades[1]==max(grades.content_areas.reported.in.state$GRADE_NUMERIC)) {
year_span <- data.year.span
temp.grades.content_areas <- extend.grades(rev(grades), content_areas)
return(list(
interp.df = temp.grades.content_areas,
year_span=year_span,
any_scale_scores=any.scale.scores,
increment_for_projection_current=0,
years=yearIncrement(Report_Parameters$Current_Year, seq(1-max(which(grades[1]==temp.grades.content_areas$GRADE_NUMERIC)), length=dim(temp.grades.content_areas)[1]))))
} else {
year.increment.for.projection.current <- grades.content_areas.reported.in.state$YEAR_LAG[which(grades[1]==grades.content_areas.reported.in.state$GRADE_NUMERIC)+1]
year_span <- max(min(last.scale.score, data.year.span-1), min(grades[1]-min(grades.content_areas.reported.in.state$GRADE_NUMERIC)+1, data.year.span-1)) - (year.increment.for.projection.current-1)
temp.grades <- c(rev(head(grades, year_span)),
head(seq(grades.content_areas.reported.in.state$GRADE_NUMERIC[match(grades[1], grades.content_areas.reported.in.state$GRADE_NUMERIC)]+1, length=data.year.span),
data.year.span-year_span))
temp.grades.content_areas <- extend.grades(temp.grades, content_areas)
return(list(
interp.df = temp.grades.content_areas,
year_span=year_span,
any_scale_scores=any.scale.scores,
increment_for_projection_current=year.increment.for.projection.current,
years=yearIncrement(Report_Parameters$Current_Year, seq(1-max(which(grades[1]==temp.grades.content_areas$GRADE_NUMERIC)), length=dim(temp.grades.content_areas)[1]))))
}
} ### END interpolate.grades function
year.function <- function(year, add.sub, vec.length, output.type="numeric", season=NULL) {
if (is.null(season)) {
if (grepl("_", year)) {
tmp <- as.numeric(unlist(strsplit(strsplit(as.character(year), "[.]")[[1]][1], "_")))+add.sub
if (output.type=="numeric") {
return(seq(from=tmp[2], length=vec.length))
} else {
return(paste0(seq(from=tmp[1], length=vec.length), "-", seq(from=tmp[2], length=vec.length)))
}
} else {
return(seq(from=as.numeric(strsplit(as.character(year), "[.]")[[1]][1])+add.sub, length=vec.length))
}
} else {
if (length(grep("_", year) > 0)) {
tmp <- as.numeric(unlist(strsplit(strsplit(as.character(year), "[.]")[[1]][1], "_")))+add.sub
if (output.type=="numeric") {
return(seq(from=tmp[2], length=vec.length))
} else {
return(paste(season, seq(from=tmp[1], length=vec.length)))
}
} else {
return(paste(season, seq(from=as.numeric(strsplit(as.character(year), "[.]")[[1]][1])+add.sub, length=vec.length)))
}
}
}
stextGrob <- function (label, r=0.1, x = x, y = y,
just = "centre", hjust = NULL, vjust = NULL, rot = 0, check.overlap = FALSE,
default.units = "native", name = NULL, gp = gpar(), vp = NULL){
# http://stackoverflow.com/questions/7734535/control-font-thickness-without-changing-font-size
let <- textGrob("a", gp=gp, vp=vp)
wlet <- grobWidth(let)
hlet <- grobHeight(let)
tg <- textGrob(label=label, x=x, y=y, gp=gpar(col="white"), just = just, hjust = hjust, vjust = vjust, rot = rot,
check.overlap = check.overlap, default.units = default.units)
tgl <- c(lapply(seq(0, 2*pi, length=36), function(theta){
textGrob(label=label,x=x+cos(theta)*r*wlet, y=y+sin(theta)*r*hlet, gp=gpar(col="black"),
just = just, hjust = hjust, vjust = vjust, rot = rot, check.overlap = check.overlap, default.units = default.units)
}), list(tg))
g <- gTree(children=do.call(gList, tgl), vp=vp, name=name, gp=gp)
}
grid.stext <- function(...){
g <- stextGrob(...)
grid.draw(g)
invisible(g)
}
labelSplit <- function(label, force.split.nchar=9) {
label.split <- unlist(strsplit(label, " "))
label.word.nchar <- cumsum(nchar(label.split))
if (length(label.word.nchar) > 1 & tail(label.word.nchar, 1) > force.split.nchar) {
if (any(label.word.nchar <= force.split.nchar)) {
label.split.position <- max(which(label.word.nchar <= force.split.nchar))
tmp.label <- paste(label.split[1:label.split.position], collapse=" ")
tmp.label[2] <- paste(label.split[(label.split.position+1):length(label.split)], collapse=" ")
tmp.cex <- c(title.ca.size - 0.25 - max(0, nchar(tmp.label[1])-force.split.nchar)*0.1, title.ca.size - 0.25 - max(0, nchar(tmp.label[2])-force.split.nchar)*0.1)
} else {
tmp.label <- label.split
tmp.cex <- rep(title.ca.size - 0.25 - (max(nchar(tmp.label))-force.split.nchar)*0.1, length(tmp.label))
}
return(list(content_area.label.pieces=tmp.label, cex=tmp.cex))
} else {
return(list(content_area.label.pieces=label, cex=title.ca.size - max(0, nchar(label)-force.split.nchar)*0.1))
}
}
###
### END Utility functions
###
grade.values <- interpolate.grades(Grades, Content_Areas, studentGrowthPlot.year.span, Scale_Scores)
if (any(duplicated(grade.values$interp.df))) {
grade.values$interp.df <- unique(grade.values$interp.df) # needed when transition grade is the same - e.g. Grade 9 ELA to Grade 9 PSAT (not 9 to EOCT)
}
grade.values$interp.df <- subset(grade.values$interp.df, !(is.na(GRADE) & is.na(GRADE_NUMERIC) & is.na(CONTENT_AREA)))
grade.values$years <- tail(grade.values$years, nrow(grade.values$interp.df))
if (!is.null(Report_Parameters[['Assessment_Transition']]) && grade.values$years[2] >= Report_Parameters[['Assessment_Transition']][['Year']]) Report_Parameters[['Assessment_Transition']] <- NULL
if (!is.null(transition.grade)) {
grade.rpt.index <- intersect(grep(paste0("^", Grades[!is.na(Grades)][1], "$"), grades.content_areas.reported.in.state$GRADE), grep(paste0("^", Content_Areas[1], "$"), grades.content_areas.reported.in.state$CONTENT_AREA)) # needed when transition grade is the same - e.g. Grade 9 ELA to Grade 9 PSAT (not 9 to EOCT)
if (length(grade.rpt.index)==0) grade.rpt.index <- (max(grep(max(Grades, na.rm = TRUE), grades.content_areas.reported.in.state$GRADE)) + min(which(!is.na(Grades))) - 1)
if (any(grades.content_areas.reported.in.state$CONTENT_AREA[grade.rpt.index:nrow(grades.content_areas.reported.in.state)] %in% post.trans.content_areas)) {
if (!is.list(Report_Parameters[['Assessment_Transition']])) {
Report_Parameters[['Assessment_Transition']] <- list(Grade = transition.grade)
} else Report_Parameters[['Assessment_Transition']][['Grade']] <- transition.grade
Report_Parameters[['Assessment_Transition']][['Assessment_Transition_Type']] <- c(
SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][['Vertical_Scale']],
SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][[paste('Vertical_Scale', transition.grade, sep=".")]])
grd.index <- grep(paste(SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][[paste0('Grades_Tested.', transition.grade)]], collapse="|"), grade.values$interp.df$GRADE)
sbj.index <- grep(paste(names(SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][[paste0('Content_Areas_Labels.', transition.grade)]]), collapse="|"), grade.values$interp.df$CONTENT_AREA)
if (length(sbj.index) > 0 & length(grd.index) > 0) {
Report_Parameters[['Assessment_Transition']][['Year']] <- as.data.table(grades.content_areas.reported.in.state)[
GRADE == grade.values$interp.df[min(intersect(grd.index, sbj.index)),]$GRADE &
CONTENT_AREA == grade.values$interp.df[min(intersect(grd.index, sbj.index)),]$CONTENT_AREA, YEAR]
} else Report_Parameters[['Assessment_Transition']][['Year']] <- grade.values$years[length(Grades)]
if (!is.na(grade.values$years[length(Grades)]) & grade.values$years[length(Grades)] < Report_Parameters[['Assessment_Transition']][['Year']]) Report_Parameters[['Assessment_Transition']][['Year']] <- grade.values$years[length(Grades)]
}
# if (!transition.grade %in% grades.content_areas.reported.in.state$GRADE[1:(grade.rpt.index+1)] & !any(grade.values$interp.df$GRADE_NUMERIC > transition.grade.numeric, na.rm = TRUE)) Report_Parameters[['Assessment_Transition']] <- NULL
}
if (is.null(Report_Parameters[['Assessment_Transition']])) {
achievement.level.labels <- list(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Achievement_Level_Labels"]])
number.achievement.level.regions <- sapply(achievement.level.labels, length)
level.to.get.cuku <- list(which.max(SGP::SGPstateData[[Report_Parameters$State]][["Achievement"]][["Levels"]][["Proficient"]]=="Proficient")-1)
level.to.get.musu <- list(which.max(SGP::SGPstateData[[Report_Parameters$State]][["Achievement"]][["Levels"]][["Proficient"]]=="Proficient"))
} else {
achievement.level.labels <- SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][
grep("Achievement_Level_Labels", names(SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]]))]
number.achievement.level.regions <- sapply(achievement.level.labels, length)
achievement.levels.proficiency <- SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][
grep("Achievement_Levels", names(SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]]))]
level.to.get.cuku <- sapply(achievement.levels.proficiency, function(x) which.max(x[['Proficient']]=="Proficient")-1)
level.to.get.musu <- sapply(achievement.levels.proficiency, function(x) which.max(x[['Proficient']]=="Proficient"))
}
achievement.level.region.colors <- lapply(number.achievement.level.regions, function(x) paste0("grey", round(seq(62, 91, length=x))))
if (!is.null(Report_Parameters[['Assessment_Transition']][['Assessment_Transition_Type']])) {
if (identical(toupper(Report_Parameters[['Assessment_Transition']][['Assessment_Transition_Type']][1]), "NO")) {
tmp.cutscore.year <- tail(head(sort(unique(Cutscores[['YEAR']]), na.last=FALSE), -1), 1)
if (!is.null(transition.grade)) tmp.cutscore.year <- NA
tmp.cutscore.grade <- grade.values[['interp.df']][['GRADE']][which(grade.values[['years']]==Report_Parameters[['Assessment_Transition']][['Year']])]
if (!tmp.cutscore.grade %in% Cutscores[['GRADE']]) {
tmp.grades.reported <- SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Grades_Reported"]][[Report_Parameters$Content_Area]]
tmp.cutscore.grade <-
tmp.grades.reported[which.max(as.numeric(grade.values[['interp.df']][['GRADE']][which(grade.values[['years']]==Report_Parameters[['Assessment_Transition']][['Year']])]) < tmp.grades.reported)-1]
}
if (is.na(tmp.cutscore.year)) {
Cutscores[is.na(YEAR), CUTSCORES:=Cutscores[GRADE==tmp.cutscore.grade & is.na(YEAR)][['CUTSCORES']]]
} else {
Cutscores[is.na(YEAR) | YEAR < Report_Parameters$Assessment_Transition$Year,
CUTSCORES:=Cutscores[GRADE==tmp.cutscore.grade & YEAR==tmp.cutscore.year][['CUTSCORES']]]
}
}
if (identical(toupper(Report_Parameters[['Assessment_Transition']][['Assessment_Transition_Type']][2]), "NO")) {
tmp.cutscore.grade <- Grades[which(Years==Report_Parameters[['Assessment_Transition']][['Year']])]
if (length(tmp.cutscore.grade)==0) tmp.cutscore.grade <- NA
if (is.na(tmp.cutscore.grade)) {
tmp.cutscore.grade <- grade.values[['interp.df']][['GRADE']][which(grade.values[['years']]==Report_Parameters[['Assessment_Transition']][['Year']])]
}
Cutscores[!is.na(YEAR) & YEAR >= Report_Parameters$Assessment_Transition$Year,
CUTSCORES:=Cutscores[GRADE==tmp.cutscore.grade & YEAR >= Report_Parameters$Assessment_Transition$Year][['CUTSCORES']]]
}
}
if (grade.values[['any_scale_scores']]) {
low.year <- year.function(Report_Parameters$Current_Year, (1-grade.values$year_span), 1)
high.year <- year.function(Report_Parameters$Current_Year, studentGrowthPlot.year.span-grade.values$year_span, 1)
year.text <- c(year.function(Report_Parameters$Current_Year, (1-grade.values$year_span), grade.values$year_span+grade.values$increment_for_projection_current, "character", test.season),
rep(" ", studentGrowthPlot.year.span))
year.text <- head(year.text, studentGrowthPlot.year.span)
content_area.text <- grade.values$interp.df$CONTENT_AREA[match(gsub("-", "_", year.text), sapply(grade.values$years, function(f) strsplit(f, "[.]")[[1]][1]))]
content_area.text[is.na(content_area.text)] <- " "
for (i in which(content_area.text %in% names(SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Content_Areas_Labels"]]))) {
content_area.text[i] <- SGP::SGPstateData[[Report_Parameters$State]][["Student_Report_Information"]][["Content_Areas_Labels"]][[content_area.text[i]]]
}
if (grade.values$increment_for_projection_current > 0) {
grades.text.numbers <- c(Grades[grade.values$year_span:1],
grades.content_areas.reported.in.state$GRADE[match(Grades[1], grades.content_areas.reported.in.state$GRADE)+seq(grade.values$increment_for_projection_current)])
tmp.grades.text.numbers <- head(grade.values$interp.df$GRADE[-1], studentGrowthPlot.year.span)
} else {
grades.text.numbers <- Grades[grade.values$year_span:1]
tmp.grades.text.numbers <- head(grade.values$interp.df$GRADE[-1], studentGrowthPlot.year.span)
}
if (!is.null(Report_Parameters[['Configuration']][['Zero_to_K']])) {
if (is.character(Report_Parameters[['Configuration']][['Zero_to_K']])) {
grades.text.numbers[which(grades.text.numbers==0)] <- Report_Parameters[['Configuration']][['Zero_to_K']]
} else grades.text.numbers[which(grades.text.numbers==0)] <- "K"
}
grades.text.numbers.missing <- which(is.na(grades.text.numbers))
grades.text.numbers.non.tested <- which(!tmp.grades.text.numbers %in% grades.content_areas.reported.in.state$GRADE)
grades.text.eoct <- which(grades.text.numbers=="EOCT")
grades.text <- c(paste(grade.label, grades.text.numbers), rep(" ", studentGrowthPlot.year.span))
grades.text[grades.text.numbers.missing] <- missing.data.symbol
grades.text[grades.text.numbers.non.tested] <- "Non-tested Grade"
if (print.eoct.content.area) {
grades.text[grades.text.eoct] <- content_area.text[grades.text.eoct]
} else grades.text[grades.text.eoct] <- "EOCT"
grades.text <- head(grades.text, studentGrowthPlot.year.span)
if (missing(Plotting_Scale_Scores)) Plotting_Scale_Scores <- Scale_Scores
scale.scores.values <- c(Plotting_Scale_Scores[grade.values$year_span:1], rep(NA, studentGrowthPlot.year.span))
scale.scores.values <- head(scale.scores.values, studentGrowthPlot.year.span)
scale.scores.text <- c(Scale_Scores[grade.values$year_span:1], rep(" ", studentGrowthPlot.year.span))
scale.scores.text[which(is.na(Scale_Scores[grade.values$year_span:1]))] <- missing.data.symbol
scale.scores.text <- head(scale.scores.text, studentGrowthPlot.year.span)
ach.levels.text <- c(ach.level.labels(Achievement_Levels[grade.values$year_span:1]), rep(" ", studentGrowthPlot.year.span))
ach.levels.text <- head(ach.levels.text, studentGrowthPlot.year.span)
if (grade.values[['year_span']] > 1) {
gp.values <- c(SGP[(grade.values$year_span-1):1], rep(NA, studentGrowthPlot.year.span))
gp.values <- head(gp.values, studentGrowthPlot.year.span-1)
gp.text <- c(SGP[(grade.values$year_span-1):1], rep(" ", studentGrowthPlot.year.span))
gp.text[which(is.na(SGP[(grade.values$year_span-1):1]))] <- missing.data.symbol
gp.text <- head(gp.text, studentGrowthPlot.year.span-1)
gp.levels.text <- c(sgp.level.labels(SGP_Levels[(grade.values$year_span-1):1]), rep(" ", studentGrowthPlot.year.span))
gp.levels.text <- head(gp.levels.text, studentGrowthPlot.year.span-1)
} else {
gp.values <- rep(NA, studentGrowthPlot.year.span-1)
gp.text <- rep(" ", studentGrowthPlot.year.span-1)
gp.levels.text <- rep(" ", studentGrowthPlot.year.span-1)
}
if (grade.values[['increment_for_projection_current']]==0) {
cuts.ny1 <- rep(NA, number.growth.levels+1)
cuts.ny1.text <- rep(NA, number.growth.levels+1)
} else {
cuts.ny1 <- Plotting_Cuts[["NY1"]]
cuts.ny1.text <- Cuts[["NY1"]]
}
} else {
low.year <- year.function(Report_Parameters$Current_Year, (1-grade.values$year_span), 1)
high.year <- year.function(Report_Parameters$Current_Year, studentGrowthPlot.year.span-grade.values$year_span, 1)
year.text <- rep(" ", studentGrowthPlot.year.span)
content_area.text <- rep(" ", studentGrowthPlot.year.span)
grades.text <- rep(" ", studentGrowthPlot.year.span)
scale.scores.values <- rep(NA, studentGrowthPlot.year.span)
scale.scores.text <- rep(" ", studentGrowthPlot.year.span)
ach.levels.text <- rep(" ", studentGrowthPlot.year.span)
gp.values <- rep(NA, studentGrowthPlot.year.span-1)
gp.text <- rep(" ", studentGrowthPlot.year.span-1)
gp.levels.text <- rep(" ", studentGrowthPlot.year.span-1)
cuts.ny1 <- rep(NA, number.growth.levels+1)
cuts.ny1.text <- rep(NA, number.growth.levels+1)
}
current.year <- year.function(Report_Parameters$Current_Year, 0, 1)
xscale.range <- range(low.year,high.year) + c(-0.075, 0.1)*diff(range(low.year,high.year))
if (is.null(Report_Parameters$Assessment_Transition)) {
tmp.year.cut <- NULL
xscale.range.list <- list(xscale.range)
} else {
tmp.year.cut <- year.function(Report_Parameters$Assessment_Transition$Year, 0, 1)-0.5
if (tmp.year.cut <= xscale.range[1]) xscale.range[1] <- tmp.year.cut-0.9
xscale.range.list <- list(c(xscale.range[1], tmp.year.cut-0.025), c(tmp.year.cut+0.025, xscale.range[2]))
}
low.score <- min(cuts.ny1, Plotting_Scale_Scores, Cutscores[GRADE==data.table(grade.values[['interp.df']])[!is.na(CONTENT_AREA)][['GRADE']][1] & CUTLEVEL==1][['CUTSCORES']], na.rm=TRUE)
high.score <- max(cuts.ny1, Plotting_Scale_Scores, Cutscores[GRADE==tail(data.table(grade.values[['interp.df']])[!is.na(CONTENT_AREA)][['GRADE']], 1) & CUTLEVEL %in% (number.achievement.level.regions-1)][['CUTSCORES']], na.rm=TRUE)
yscale.range <- extendrange(c(low.score,high.score), f=0.15)
content_area.label.pieces <- labelSplit(content.area.label)
if (length(content_area.label.pieces[[1]])==1) split.content_area.tf <- FALSE else split.content_area.tf <- TRUE
### Create viewports
if (is.null(Report_Parameters$Assessment_Transition)) {
subject.report.vp <- viewport(layout = grid.layout(2, 3, widths = unit(c(1.15, 5.4, 1.5)/8.05, rep("npc", 3)),
heights = unit(c(2.45, 0.9)/3.35, rep("npc", 2))), gp=gpar(fill="transparent"))
} else {
subject.report.vp <- viewport(layout = grid.layout(2, 3, widths = unit(c(1.15, 5.65, 1.25)/8.05, rep("npc", 3)),
heights = unit(c(2.45, 0.9)/3.35, rep("npc", 2))), gp=gpar(fill="transparent"))
}
growth.chart.vp <- viewport(name="growth.chart.vp",
layout.pos.row=1, layout.pos.col=2,
xscale=xscale.range,
yscale=yscale.range,
gp=gpar(fill="transparent"))
if (is.null(Report_Parameters$Assessment_Transition)) {
right.vp <- viewport(name="right.vp",
layout.pos.row=1, layout.pos.col=3,
xscale=c(0,1),
yscale=c(0,1),
gp=gpar(fill="transparent"))
} else {
right.vp <- viewport(name="right.vp",
layout.pos.row=1, layout.pos.col=3,
xscale=c(0,1),
yscale=yscale.range,
gp=gpar(fill="transparent"))
}
left.vp <- viewport(name="left.vp",
layout.pos.row=1, layout.pos.col=1,
xscale=c(0, 1),
yscale=yscale.range,
gp=gpar(fill="transparent"))
if (is.null(Report_Parameters$Assessment_Transition)) {
growth.and.margins.vp <- viewport(name="growth.and.margins.vp",
layout.pos.row=1, layout.pos.col=1:2)
} else {
growth.and.margins.vp <- viewport(name="growth.and.margins.vp",
layout.pos.row=1, layout.pos.col=1:3)
bottom.right.vp.size <- 1.05
}
bottom.vp <- viewport(name="bottom.vp",
layout.pos.row=2, layout.pos.col=2,
xscale=xscale.range,
yscale=c(0,3),
gp=gpar(fill="transparent"))
bottom.left.right.vp <- viewport(name="bottom.left.right.vp",
layout.pos.row=2, layout.pos.col=1:3,
xscale=c(0,1),
yscale=c(0,3),
gp=gpar(fill="transparent"))
bottom.right.vp <- viewport(name="bottom.right.vp",
layout.pos.row=2, layout.pos.col=3,
xscale=c(0,1),
yscale=c(0,3),
gp=gpar(fill="transparent"))
bottom.left.vp <- viewport(name="bottom.left.vp",
layout.pos.row=2, layout.pos.col=1,
xscale=c(0,1),
yscale=c(0,3),
gp=gpar(fill="transparent"))
no.data.vp <- viewport(name="no.data.vp",
layout.pos.row=1, layout.pos.col=1:3,
xscale=c(0,1),
yscale=c(0,1),
gp=gpar(fill="transparent"))
pushViewport(subject.report.vp)
#############################################
### Growth.Chart Viewport
#############################################
pushViewport(growth.chart.vp)
if (is.null(tmp.year.cut)) {
tmp.year.sequence <- list(as.character((low.year-1):(high.year+1)))
} else {
tmp.year.sequence <- list(as.character((low.year-1):tmp.year.cut), as.character(rev((high.year+1):tmp.year.cut)))
}
for (j in seq(length(Report_Parameters$Assessment_Transition[['Year']])+1)) {
for (i in seq(number.achievement.level.regions[[j]]-1)) {
temp <- data.table(temp_id=seq_len(nrow(grade.values$interp.df)), grade.values$interp.df, YEAR=sapply(strsplit(sapply(strsplit(grade.values$years, "_"), tail, 1), "[.]"), head, 1), key="YEAR")[tmp.year.sequence[[j]]]
temp[,YEAR:=get.my.cutscore.year(Report_Parameters$State, Report_Parameters$Content_Area, YEAR, i)]
if (class(temp$YEAR) != class(Cutscores$YEAR)) class(temp$YEAR) <- class(Cutscores$YEAR)
temp <- merge(temp, Cutscores[CUTLEVEL==i], all.x=TRUE, by=c("YEAR", "CONTENT_AREA", "GRADE"))
temp <- temp[order(temp$temp_id),][['CUTSCORES']]
if (length(temp[which(!is.na(temp))])==1) {
temp[which(is.na(temp))] <- temp[which(!is.na(temp))]
} else {
temp[which(is.na(temp))] <- approx(temp, xout=which(is.na(temp)), rule=2)$y
}
assign(paste0("level_", j, "_", i, "_curve"), splinefun(as.numeric(tmp.year.sequence[[j]]), temp, method="monoH.FC"))
}
tmp.x.points <- seq(xscale.range.list[[j]][1], xscale.range.list[[j]][2], length=round(diff(xscale.range.list[[j]])/diff(xscale.range)*40))
x.boundary.values.1 <- c(xscale.range.list[[j]][1], tmp.x.points, xscale.range.list[[j]][2])
y.boundary.values.1 <- c(yscale.range[1], eval(parse(text=paste0("level_", j, "_1_curve(tmp.x.points)"))), yscale.range[1])
assign(paste0("x.boundary.values.", number.achievement.level.regions[[j]]),
c(xscale.range.list[[j]][1], tmp.x.points, xscale.range.list[[j]][2]))
assign(paste0("y.boundary.values.", number.achievement.level.regions[[j]]),
c(yscale.range[2], eval(parse(text=paste0("level_", j, "_", number.achievement.level.regions[[j]]-1, "_curve(tmp.x.points)"))), yscale.range[2]))
if (number.achievement.level.regions[[j]] > 2) {
for (i in 2:(number.achievement.level.regions[[j]]-1)) {
assign(paste0("x.boundary.values.", i),
c(tmp.x.points, rev(tmp.x.points)))
assign(paste0("y.boundary.values.", i),
eval(parse(text=paste0("c(level_", j, "_", i, "_curve(tmp.x.points), level_", j, "_", i-1, "_curve(rev(tmp.x.points)))"))))
}
}
## Keep achievement level bands from extending outside of chart box
eval(parse(text=paste0("y.boundary.values.", seq(number.achievement.level.regions[[j]]), "[y.boundary.values.", seq(number.achievement.level.regions[[j]]), " > max(yscale.range)] <- max(yscale.range)")))
eval(parse(text=paste0("y.boundary.values.", seq(number.achievement.level.regions[[j]]), "[y.boundary.values.", seq(number.achievement.level.regions[[j]]), " < min(yscale.range)] <- min(yscale.range)")))
for (i in seq(number.achievement.level.regions[[j]])) {
grid.polygon(x=get(paste0("x.boundary.values.", i)),
y=get(paste0("y.boundary.values.", i)),
default.units="native",
gp=gpar(fill=achievement.level.region.colors[[j]][i], lwd=0.8, col="white"))
}
}
if (!is.null(Report_Parameters$Assessment_Transition)) {
grid.lines(x=tmp.year.cut, y=yscale.range, default.units="native", gp=gpar(lwd=1.8, col=border.color))
grid.lines(x=tmp.year.cut+0.028, y=yscale.range, default.units="native", gp=gpar(lwd=0.4, col=border.color))
grid.lines(x=tmp.year.cut-0.028, y=yscale.range, default.units="native", gp=gpar(lwd=0.4, col=border.color))
if (grade.values[['any_scale_scores']]) {
tmp.transition.names <- names(SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]])
tmp.test.abbreviation <-
unlist(SGP::SGPstateData[[Report_Parameters$State]][["Assessment_Program_Information"]][["Assessment_Transition"]][grep('Assessment_Abbreviation', tmp.transition.names)])
tmp.test.abbreviation.text <- rep(" ", length(year.text))
tmp.test.abbreviation.text[which((low.year:high.year < Report_Parameters$Assessment_Transition$Year)[which(year.text!=" ")])] <-
tmp.test.abbreviation[1]
tmp.test.abbreviation.text[which((low.year:high.year >= Report_Parameters$Assessment_Transition$Year)[which(year.text!=" ")])] <-
tmp.test.abbreviation[2]
tmp.test.abbreviation.text[which(content_area.text==" ")] <- " "
grid.stext(tmp.test.abbreviation.text, x=unit(low.year:high.year, "native"), y=convertHeight(unit(0.07, "npc"), "native"), gp=gpar(cex=0.7))
grid.stext(sapply(content_area.text, capwords), x=unit(low.year:high.year, "native"), y=convertHeight(unit(0.03, "npc"), "native"), gp=gpar(cex=0.7))
}
}
if (is.null(Report_Parameters$Assessment_Transition) && sgPlot.show.content_area.progression) {
grid.stext(sapply(content_area.text, capwords), x=unit(low.year:high.year, "native"), y=convertHeight(unit(0.05, "npc"), "native"), gp=gpar(cex=0.75))
# grid.text(x=low.year:high.year, y=convertHeight(unit(0.05, "npc"), "native"), sapply(content_area.text, capwords), gp=gpar(col="white", cex=0.75), default.units="native")
}
if (connect.points=="Arrows") {
growth.arrow.coors.x <- c(.05, .85, .8, 1, .8, .85, .05, .053, .0555, .0575, .0585, .059, .0585, .0575, .0555, .053, .05)
growth.arrow.coors.y <- c(-.2, -.2, -.5, 0, .5, .2, seq(.2, -.2, length=11))
for (i in 1:length(gp.values)) {
tmp.lag <- which(is.na(rev(scale.scores.values[1:i]))==FALSE)
if (!is.na(gp.values[i]) & length(tmp.lag) > 0) {
lag.to.prior.score <- min(tmp.lag, na.rm=TRUE)
if (lag.to.prior.score == 1) my.lty <- 1 else my.lty <- 2
arrow.rise <- convertHeight(unit(scale.scores.values[i+1], "native") - unit(scale.scores.values[i+1-lag.to.prior.score], "native"), "inches")
arrow.run <- convertWidth(unit(lag.to.prior.score, "native") - unit(0, "native"), "inches")
arrow.angle <- atan2(as.numeric(arrow.rise),as.numeric(arrow.run))*180/pi
## Arrows connecting achievement scores
if (!is.na(arrow.angle)) {
pushViewport(viewport(x=unit(low.year+i-lag.to.prior.score, "native"), y=unit(scale.scores.values[i+1-lag.to.prior.score], "native"),
width=unit((lag.to.prior.score-0.08)/cos(arrow.angle*pi/180), "native"), height=unit(0.05, "npc"), angle=arrow.angle, just=c("left", "center"),
xscale=c(0, 1), yscale=c(-0.5, 0.5)))
grid.polygon(x=growth.arrow.coors.x, y=growth.arrow.coors.y, default.units="native",
gp=gpar(lwd=0.3, lty=my.lty, col=border.color, fill=arrow.color(as.numeric(gp.values[i]))))
grid.curve(0.05, -0.2, 0.05, 0.2, curvature=0.3, ncp=11, square=FALSE, default.units="native", gp=gpar(lwd=0.3, col=border.color))
popViewport()
}
}
}
} ## END Report_Parameters[['Configuration']][['Connect_Points']]=="Arrows"
if (paste(Grades[1], Content_Areas[1]) != tail(with(grades.content_areas.reported.in.state, paste(GRADE, CONTENT_AREA)), 1) & !is.na(cuts.ny1[1]) & show.fan){
for (i in seq(number.growth.levels)) {
grid.polygon(x=c(current.year, rep(current.year+grade.values$increment_for_projection_current, 2), current.year),
y=c(scale.scores.values[which(current.year==low.year:high.year)], max(yscale.range[1], cuts.ny1[i]),
min(yscale.range[2], cuts.ny1[i+1]), scale.scores.values[which(current.year==low.year:high.year)]),
default.units="native", gp=gpar(col=NA, lwd=0, fill=arrow.legend.color[i], alpha=0.45))
if (fan.extra) {
fan.extra.col <- arrow.legend.color[i]
fan.extra.x <- c(current.year, rep(current.year+grade.values$increment_for_projection_current, 2), current.year)
fan.extra.y <- c(scale.scores.values[which(current.year==low.year:high.year)], max(yscale.range[1], cuts.ny1[i]),
min(yscale.range[2], cuts.ny1[i+1]), scale.scores.values[which(current.year==low.year:high.year)])
eval(parse(text = fan.extras[i]))
}
grid.roundrect(x=unit(current.year+grade.values$increment_for_projection_current, "native"),
y=unit((max(yscale.range[1], cuts.ny1[i])+min(yscale.range[2], cuts.ny1[i+1]))/2, "native"),
height=unit(min(yscale.range[2], as.numeric(cuts.ny1[i+1])) - max(yscale.range[1], as.numeric(cuts.ny1[i])), "native"),
width=unit(0.04, "native"), r=unit(0.45, "snpc"), gp=gpar(lwd=0.3, col=border.color, fill=arrow.legend.color[i]))
if (show.fan.growth.labels && is.null(Report_Parameters[['SGP_Targets']])) {
grid.text(x=current.year+grade.values$increment_for_projection_current+0.05,
y=(max(yscale.range[1], cuts.ny1[i])+min(yscale.range[2], cuts.ny1[i+1]))/2, growth.level.labels[i],
default.units="native", just="left", gp=gpar(cex=0.4, col=border.color))
}
if (i != 1 & show.fan.cutscores) {
grid.text(x=current.year+grade.values$increment_for_projection_current+0.05, y=cuts.ny1[i], as.character(cuts.ny1.text[i]),
default.units="native", just="left", gp=gpar(cex=0.4, col=border.color))
}
}
}
if (!is.null(Report_Parameters[['SGP_Targets']])) {
for (i in tmp.target.types) {
if (length(grep("Current", i))==0) {
current.year.x.coor <- current.year
current.year.x.coor.lag <- min(which(!is.na(tail(Scale_Scores, -1))), na.rm=TRUE)
x.coor.label.adjustment <- -0.075; label.position <- "right"; tmp.index <- 1
if (is.null(Report_Parameters$Assessment_Transition)) {
tmp.achievement.level <- which(tail(head(Achievement_Levels, current.year.x.coor.lag+1), 1)==achievement.level.labels[[tmp.index]])
} else {
if (year.function(Report_Parameters$Assessment_Transition$Year, 0, 1) <= current.year.x.coor-current.year.x.coor.lag) tmp.index <- 2
tmp.achievement.level <- which(tail(head(Achievement_Levels, current.year.x.coor.lag+1), 1)==achievement.level.labels[[tmp.index]])
}
show.targets <- TRUE
} else {
current.year.x.coor <- current.year+grade.values$increment_for_projection_current
current.year.x.coor.lag <- grade.values$increment_for_projection_current
x.coor.label.adjustment <- 0.075; label.position <- "left"; tmp.index <- 1; show.targets <- show.fan
if (is.null(Report_Parameters$Assessment_Transition)) {
tmp.achievement.level <- which(head(Achievement_Levels, 1)==achievement.level.labels[[tmp.index]])
} else {
if (year.function(Report_Parameters$Assessment_Transition$Year, 0, 1) <= current.year.x.coor) tmp.index <- 2
tmp.achievement.level <- which(head(Achievement_Levels, 1)==achievement.level.labels[[tmp.index]])
}
}
if (show.targets) {
if (length(grep("CUKU", i))>0 & tmp.achievement.level <= level.to.get.cuku[[tmp.index]]) {
label.position <- c(label.position, "center")
tmp.target.label <- c(CU.label, target.label)
y.coordinates <- c(as.numeric(convertHeight(convertHeight(unit(Plotting_SGP_Scale_Score_Targets[[i]][['NY1']], "native"), "inches")+unit(0.0375, "inches"), "native")),
as.numeric(convertHeight(convertHeight(unit(Plotting_SGP_Scale_Score_Targets[[i]][['NY1']], "native"), "inches")-unit(0.0375, "inches"), "native")))
}
if (length(grep("CUKU", i))>0 & tmp.achievement.level > level.to.get.cuku[[tmp.index]]) {
label.position <- c(label.position, "top")
tmp.target.label <- c(KU.label, target.label)
y.coordinates <- c(Plotting_SGP_Scale_Score_Targets[[i]][['NY1']],
as.numeric(convertHeight(convertHeight(unit(Plotting_SGP_Scale_Score_Targets[[i]][['NY1']], "native"), "inches")-unit(0.1, "inches"), "native")))
}
if (length(grep("MUSU", i))>0 & tmp.achievement.level <= level.to.get.musu[[tmp.index]]) {
label.position <- c(label.position, "bottom")
tmp.target.label <- c(MU.label, target.label)
y.coordinates <- c(as.numeric(convertHeight(convertHeight(unit(Plotting_SGP_Scale_Score_Targets[[i]][['NY1']], "native"), "inches")+unit(0.1, "inches"), "native")),
Plotting_SGP_Scale_Score_Targets[[i]][['NY1']])
}
if (length(grep("MUSU", i))>0 & tmp.achievement.level > level.to.get.musu[[tmp.index]]) {
label.position <- c(label.position, "bottom")
tmp.target.label <- c(SU.label, target.label)
y.coordinates <- c(as.numeric(convertHeight(convertHeight(unit(Plotting_SGP_Scale_Score_Targets[[i]][['NY1']], "native"), "inches")+unit(0.1, "inches"), "native")),
Plotting_SGP_Scale_Score_Targets[[i]][['NY1']])
}
if (length(grep("CUSTOM", i))>0) {
label.position <- c(label.position, "bottom")
tmp.target.label <- NULL
y.coordinates <- c(as.numeric(convertHeight(convertHeight(unit(Plotting_SGP_Scale_Score_Targets[[i]][['NY1']], "native"), "inches")+unit(0.1, "inches"), "native")),
Plotting_SGP_Scale_Score_Targets[[i]][['NY1']])
}
grid.lines(x=c(current.year.x.coor-current.year.x.coor.lag, current.year.x.coor),
y=c(scale.scores.values[which(current.year.x.coor-current.year.x.coor.lag==low.year:high.year)], Plotting_SGP_Scale_Score_Targets[[i]][['NY1']]),
gp=gpar(lwd=0.8, col=border.color), default.units="native")
grid.circle(x=current.year.x.coor, y=Plotting_SGP_Scale_Score_Targets[[i]][['NY1']], r=unit(c(0.05, 0.04, 0.025, 0.0125), "inches"),
gp=gpar(col=c("black", "white", "black", "white"), lwd=0.01, fill=c("black", "white", "black", "white")), default.units="native")
if (!is.null(tmp.target.label)) grid.text(x=current.year.x.coor+x.coor.label.adjustment, y=y.coordinates, tmp.target.label, default.units="native", just=label.position, gp=gpar(cex=0.5, col=border.color))
}
}
}
grid.circle(x=low.year:high.year, y=scale.scores.values, r=unit(0.04, "inches"), gp=gpar(col=border.color, lwd=0.7, fill="white"), default.units="native")
# popViewport() Don't pop until after next section - extra mid-level distinction may be needed (first code chunk in 'Left Viewport')
#################################
### Left Viewport
#################################
unq.labels <- names(achievement.level.labels[[1]])
if (length(unique(unq.labels)) != number.achievement.level.regions[[1]]) {
# WIDA_GA for example - extra "mid-level" used for state exit criteria cut
tmp.n.achlev.regions <- length(unique(unq.labels))
dup.levels <- which(duplicated(unq.labels))
unq.levels <- which(!duplicated(unq.labels))
unq.levels <- unq.levels + c(diff(unq.levels) - 1, 0) # use (last) duplicate level for boundaries
max.level <- max(unq.levels)
mid.levels <- unq.levels %w/o% c(1, max.level)
for (k in dup.levels) {
tmp_fun <- get(paste0("level_1_", k - 1, "_curve"))
y.dup.points <- tmp_fun(tmp.x.points)
grid.lines(x = tmp.x.points, y = y.dup.points, default.units = "native",
gp = gpar(lwd = 1.4, lty = "dashed", col = "black"))
}
} else {
tmp.n.achlev.regions <- max.level <- number.achievement.level.regions[[1]]
unq.levels <- seq(tmp.n.achlev.regions)
mid.levels <- 2:(tmp.n.achlev.regions - 1)
}
popViewport() # growth.chart.vp
pushViewport(left.vp)
y.boundary.legend.1 <- c(yscale.range[1], yscale.range[1], rep(level_1_1_curve(xscale.range[1]), 2))
assign(paste0("y.boundary.legend.", max.level),
c(yscale.range[2], yscale.range[2], rep(eval(parse(text = paste0("level_1", "_", max.level-1, "_curve(xscale.range[1])"))), 2)))
if (tmp.n.achlev.regions > 2) {
for (i in mid.levels) {
ii <- unq.levels[which(unq.levels == i) - 1]
assign(paste0("y.boundary.legend.", i), eval(parse(text =
paste0("c(rep(level_1", "_", ii, "_curve(xscale.range[1]), 2), rep(level_1",
"_", i, "_curve(xscale.range[1]), 2))"))))
}
}
for (i in unq.levels){
grid.polygon(x = c(0,1,1,0), y = get(paste0("y.boundary.legend.", i)),
default.units = "native",
gp = gpar(fill = achievement.level.region.colors[[1]][i], lwd = 0.5, col = border.color, alpha = 0.7))
}
grid.text(x = 0.94, y = (level_1_1_curve(xscale.range[1]) + yscale.range[1])/2,
label = unq.labels[1], default.units = "native", just = "right",
gp = gpar(col = border.color, fontface = 2, fontfamily = font.fam, cex = left.vp.size, lineheight = legend.lheight))
grid.text(x = 0.94, y = (eval(parse(text = paste0("level_1", "_", max.level-1, "_curve(xscale.range[1])"))) + yscale.range[2])/2,
label = unq.labels[max.level], default.units = "native", just = "right",
gp = gpar(col = border.color, fontface = 2, fontfamily = font.fam, cex = left.vp.size, lineheight = legend.lheight))
if (tmp.n.achlev.regions > 2) {
for (i in mid.levels) {
ii <- unq.levels[which(unq.levels == i) - 1]
grid.text(x = .94,
y = (eval(parse(text = paste0("(level_1", "_", ii, "_curve(xscale.range[1]) + level_1",
"_", i, "_curve(xscale.range[1]))/2")))),
label = unq.labels[i],
gp = gpar(col = border.color, fontface = 2, fontfamily = font.fam, cex = left.vp.size, lineheight = legend.lheight),
default.units = "native", just = "right")
}
}
grid.lines(0, c(yscale.range[1], yscale.range[2]), gp = gpar(lwd = 0.8, col = border.color), default.units = "native")
popViewport()
############################################
### Growth and Margins Viewport
############################################
pushViewport(growth.and.margins.vp)
if (grade.values$year_span == 0) {
grid.roundrect(r=unit(.01, "snpc"), gp=gpar(lwd=1.8, col=border.color, clip=TRUE, fill=rgb(1, 1, 1, 0.5)))
} else {
grid.roundrect(r=unit(.01, "snpc"), gp=gpar(lwd=1.8, col=border.color, clip=TRUE))
}
popViewport()
##############################################
### Bottom Viewport
##############################################
pushViewport(bottom.vp)
if (is.null(Report_Parameters[['SGP_Targets']])) {
grid.text(x=low.year:high.year, y=2.67, grades.text, gp=gpar(col=border.color, cex=.75), default.units="native")
grid.text(x=low.year:high.year, y=2.3, year.text, gp=gpar(col=border.color, cex=.6), default.units="native")
grid.text(x=low.year:high.year, y=1.7, scale.scores.text, gp=gpar(col=border.color, cex=.65), default.units="native")
grid.text(x=low.year:high.year, y=1.3, ach.levels.text, gp=gpar(col=border.color, cex=.6), default.units="native")
grid.text(x=(low.year+1):high.year-0.5, y=0.7, gp.text, gp=gpar(col=border.color, cex=.65), default.units="native")
grid.text(x=(low.year+1):high.year-0.5, y=0.3, gp.levels.text, gp=gpar(col=border.color, cex=.6), default.units="native")
} else {
grid.text(x=low.year:high.year, y=2.75, grades.text, gp=gpar(col=border.color, cex=.6), default.units="native")
grid.text(x=low.year:high.year, y=2.45, year.text, gp=gpar(col=border.color, cex=.5), default.units="native")
grid.text(x=low.year:high.year, y=1.95, scale.scores.text, gp=gpar(col=border.color, cex=.5), default.units="native")
grid.text(x=low.year:high.year, y=1.65, ach.levels.text, gp=gpar(col=border.color, cex=.5), default.units="native")
grid.text(x=(low.year+1):high.year-0.5, y=0.85, gp.text, gp=gpar(col=border.color, cex=.5), default.units="native")
grid.text(x=(low.year+1):high.year-0.5, y=0.55, gp.levels.text, gp=gpar(col=border.color, cex=.5), default.units="native")
tmp.projection.names.list <- list()
if (length(grep("Current", tmp.target.types)) > 0) {
tmp.projection.names.list[["Current"]] <- grep("Current", tmp.target.types, value=TRUE)
}
if (length(grep("Current", tmp.target.types, invert=TRUE)) > 0) {
tmp.projection.names.list[["Lagged"]] <- grep("Current", tmp.target.types, value=TRUE, invert=TRUE)
}
for (i in seq_along(tmp.projection.names.list)) {
if (length(grep("Current", tmp.projection.names.list[[i]])) > 0) {
tmp.projection.names <- tmp.projection.names.list[[i]]
tmp.projection.year.from <- current.year
tmp.projection.year.to <- current.year+grade.values$increment_for_projection_current
if (!is.null(Report_Parameters$Assessment_Transition) && year.function(Report_Parameters$Assessment_Transition$Year, 0, 1) <= tmp.projection.year.from) {
achievement.level.label.index.from <- 2
} else {
achievement.level.label.index.from <- 1
}
if (!is.null(Report_Parameters$Assessment_Transition) && year.function(Report_Parameters$Assessment_Transition$Year, 0, 1) <= tmp.projection.year.to) {
achievement.level.label.index.to <- 2
} else {
achievement.level.label.index.to <- 1
}
tmp.achievement.level <- which(head(Achievement_Levels, 1)==achievement.level.labels[[achievement.level.label.index.from]])
} else {
tmp.projection.names <- tmp.projection.names.list[[i]]
tmp.projection.year.lag <- min(which(!is.na(tail(Scale_Scores, -1))), na.rm=TRUE)
tmp.projection.year.from <- current.year-tmp.projection.year.lag
tmp.projection.year.to <- current.year
if (!is.null(Report_Parameters$Assessment_Transition) && year.function(Report_Parameters$Assessment_Transition$Year, 0, 1) <= tmp.projection.year.from) {
achievement.level.label.index.from <- 2
} else {
achievement.level.label.index.from <- 1
}
if (!is.null(Report_Parameters$Assessment_Transition) && year.function(Report_Parameters$Assessment_Transition$Year, 0, 1) <= tmp.projection.year.to) {
achievement.level.label.index.to <- 2
} else {
achievement.level.label.index.to <- 1
}
tmp.achievement.level <- which(tail(head(Achievement_Levels, tmp.projection.year.lag+1), 1)==achievement.level.labels[[achievement.level.label.index.from]])
}
if (length(grep("CUSTOM", tmp.projection.names))==0) { ### Achievement/Growth Target Text associated with CUKU/MUSU targets
if ((length(grep("CUKU", tmp.projection.names)) > 0 & tmp.achievement.level <= level.to.get.cuku[[achievement.level.label.index.from]]) |
length(grep("MUSU", tmp.projection.names))==0) {
level.to.get.cuku.label <- names(achievement.level.labels[[achievement.level.label.index.to]])[level.to.get.cuku[[achievement.level.label.index.to]]+1]
grid.text(x=tmp.projection.year.to-0.5, y=1.35,
paste0(level.to.get.cuku.label, " (", SGP_Scale_Score_Targets[[grep("CUKU", tmp.projection.names, value=TRUE)]][['NY1']], ")"),
gp=gpar(col=border.color, cex=.4), default.units="native")
grid.text(x=tmp.projection.year.to-0.5, y=0.25,
paste0(CU.label, " (", SGP_Targets[[grep("CUKU", tmp.projection.names, value=TRUE)]], ")"),
gp=gpar(col=border.color, cex=.4), default.units="native")
} else {
level.to.get.cuku.label <- names(achievement.level.labels[[achievement.level.label.index.to]])[level.to.get.cuku[[achievement.level.label.index.to]]+1]
level.to.get.musu.label <- names(achievement.level.labels[[achievement.level.label.index.to]])[level.to.get.musu[[achievement.level.label.index.to]]+1]
grid.text(x=tmp.projection.year.to-0.5, y=1.35,
paste0(level.to.get.cuku.label, " (", SGP_Scale_Score_Targets[[grep("CUKU", tmp.projection.names, value=TRUE)]][['NY1']], ")/", level.to.get.musu.label, " (", SGP_Scale_Score_Targets[[grep("MUSU", tmp.projection.names, value=TRUE)]][['NY1']], ")"),
gp=gpar(col=border.color, cex=.4), default.units="native")
if (tmp.achievement.level <= level.to.get.musu[[achievement.level.label.index.from]]) {
grid.text(x=tmp.projection.year.to-0.5, y=0.25,
paste0(KU.label, " (", SGP_Targets[[grep('CUKU', tmp.projection.names, value=TRUE)]], ")/Move Up (", SGP_Targets[[grep('MUSU', tmp.projection.names, value=TRUE)]], ")"),
gp=gpar(col=border.color, cex=.4), default.units="native")
}
if (tmp.achievement.level > level.to.get.musu[[achievement.level.label.index.from]]) {
grid.text(x=tmp.projection.year.to-0.5, y=0.25,
paste0(KU.label, " (", SGP_Targets[[grep('CUKU', tmp.projection.names, value=TRUE)]], ")/Stay Up (", SGP_Targets[[grep('MUSU', tmp.projection.names, value=TRUE)]], ")"),
gp=gpar(col=border.color, cex=.4), default.units="native")
}
}
} else { ### Achievement/Growth Target text associated with CUSTOM plotting
level.to.get.cuku.label <- names(achievement.level.labels[[achievement.level.label.index.to]])[level.to.get.cuku[[achievement.level.label.index.to]]+1]
grid.text(x=tmp.projection.year.to-0.5, y=1.35,
paste0(level.to.get.cuku.label, " (", SGP_Scale_Score_Targets[[grep("CUSTOM", tmp.projection.names, value=TRUE)]][['NY1']], ")"),
gp=gpar(col=border.color, cex=.4), default.units="native")
grid.text(x=tmp.projection.year.to-0.5, y=0.25,
paste0(CU.label, " (", SGP_Targets[[grep("CUSTOM", tmp.projection.names, value=TRUE)]], ")"),
gp=gpar(col=border.color, cex=.4), default.units="native")
}
}
}
popViewport()
##############################
### Bottom Left.Right Viewport
##############################
pushViewport(bottom.left.right.vp)
if (is.null(Report_Parameters[['SGP_Targets']])) {
grid.lines(x=c(0,1), y=2, gp=gpar(lwd=1.8, col=border.color), default.units="native")
grid.lines(x=c(0,1), y=1, gp=gpar(lwd=1, col=border.color), default.units="native")
grid.lines(x=c(0,1), y=0, gp=gpar(lwd=1.8, col=border.color), default.units="native")
} else {
grid.lines(x=c(0,1), y=2.2, gp=gpar(lwd=1.8, col=border.color), default.units="native")
grid.lines(x=c(0,1), y=1.1, gp=gpar(lwd=1, col=border.color), default.units="native")
grid.lines(x=c(0,1), y=0, gp=gpar(lwd=1.8, col=border.color), default.units="native")
}
popViewport()
################################
### Bottom Right Viewport
################################
pushViewport(bottom.right.vp)
if (is.null(Report_Parameters[['SGP_Targets']])) {
grid.text(x=0.1, y=1.5, achievement.label, gp=gpar(col=border.color, cex=bottom.right.vp.size), just="left", default.units="native")
grid.text(x=0.1, y=.5, growth.label, gp=gpar(col=border.color, cex=bottom.right.vp.size), just="left", default.units="native")
} else {
grid.text(x=0.1, y=1.65, achievement.label, gp=gpar(col=border.color, cex=bottom.right.vp.size+0.1), just="left", default.units="native")
grid.text(x=0.1, y=0.55, growth.label, gp=gpar(col=border.color, cex=bottom.right.vp.size+0.1), just="left", default.units="native")
}
popViewport()
###########################
### Bottom Left Viewport
###########################
pushViewport(bottom.left.vp)
if (is.null(Report_Parameters[['SGP_Targets']])) {
grid.text(x=0.9, y=1.7, gsub("\\n", " ", scale_score.label), gp=gpar(col=border.color, cex=bottom.left.vp.size), just="right", default.units="native")
grid.text(x=0.9, y=1.3, achievement_level.label, gp=gpar(col=border.color, cex=bottom.left.vp.size), just="right", default.units="native")
grid.text(x=0.9, y=0.7, growth_percentile.label, gp=gpar(col=border.color, cex=bottom.left.vp.size), just="right", default.units="native")
grid.text(x=0.9, y=0.3, growth_level.label, gp=gpar(col=border.color, cex=bottom.left.vp.size), just="right", default.units="native")
} else {
grid.text(x=0.9, y=1.95, scale_score.label, gp=gpar(col=border.color, cex=bottom.left.vp.size-0.125), just="right", default.units="native")
grid.text(x=0.9, y=1.65, achievement_level.label, gp=gpar(col=border.color, cex=bottom.left.vp.size-0.125), just="right", default.units="native")
grid.text(x=0.9, y=1.35, achievement_target.label, gp=gpar(col=border.color, cex=bottom.left.vp.size-0.125), just="right", default.units="native")
grid.text(x=0.9, y=0.85, growth_percentile.label, gp=gpar(col=border.color, cex=bottom.left.vp.size-0.125), just="right", default.units="native")
grid.text(x=0.9, y=0.55, growth_level.label, gp=gpar(col=border.color, cex=bottom.left.vp.size-0.125), just="right", default.units="native")
grid.text(x=0.9, y=0.25, growth_target.label, gp=gpar(col=border.color, cex=bottom.left.vp.size-0.125), just="right", default.units="native")
}
popViewport()
###################################
### Right Viewport
###################################
if (is.null(Report_Parameters$Assessment_Transition)) { ## right.vp without ASSESSMENT_TRANSITION
pushViewport(right.vp)
grid.roundrect(width = unit(0.95, "native"), r = unit(.02, "snpc"),
gp = gpar(lwd = 1.8, col = border.color, fill = legend.fill.color), just = "center")
if (content.area.in.legend) {
if (!split.content_area.tf) {
grid.text(x = 0.5, y = 0.875,
label = content_area.label.pieces[[1]][1], default.units = "native",
gp = gpar(col = border.color, cex = content_area.label.pieces[[2]][1],
fontface = 2, fontfamily = font.fam))
} else {
grid.text(x = 0.5, y = 0.92,
label = content_area.label.pieces[[1]][1], default.units = "native",
gp = gpar(col = border.color, cex = content_area.label.pieces[[2]][1],
fontface = 2, fontfamily = font.fam))
grid.text(x = 0.5, y = 0.83,
label = content_area.label.pieces[[1]][2], default.units = "native",
gp = gpar(col = border.color, cex = content_area.label.pieces[[2]][2],
fontface = 2, fontfamily = font.fam))
}
top.offset <- 0
} else top.offset <- 0.175
grid.text(x = 0.08, y = (0.75 + top.offset),
label = achievement.label, default.units = "native", just = "left",
gp = gpar(col = border.color, cex = 0.85, fontface = 2, fontfamily = font.fam))
grid.text(x = 0.08, y = 0.525,
label = growth.label, default.units = "native", just = "left",
gp = gpar(col = border.color, cex = 0.75, fontface = 2, fontfamily = font.fam))
grid.text(x = 0.275, y = 0.455,
label = level.label, default.units = "native", just = "center",
gp = gpar(col = border.color, cex = 0.6))
grid.text(x = 0.75, y = 0.455,
label = percentiles.label, default.units = "native", just = "center",
gp = gpar(col = border.color, cex = 0.6))
grid.roundrect(x = unit(0.3, "native"), y = unit((0.64 + top.offset), "native"),
width = unit(0.3, "native"), height = unit(0.1, "native"), r = unit(0.06, "char"),
gp = gpar(col = "grey72", lwd = 0.4, fill = "grey72"))
grid.circle(x = 0.3, y = (0.64 + top.offset), r = unit(0.04, "inches"),
gp = gpar(col = border.color, lwd = 0.7, fill = "white"), default.units = "native")
if (!split.content_area.tf) {
grid.text(x = 0.7, y = (0.675 + top.offset), # just = "top",
label = paste(test.abbreviation, content.area.label), default.units = "native",
gp = gpar(col = border.color, cex = legend.size, lineheight = 1/legend.lheight))
grid.text(x = 0.7, y = (0.625 + top.offset),
label = scale_score.label, default.units = "native",
gp = gpar(col = border.color, cex = legend.size, lineheight = legend.lheight))
} else {
grid.text(x = 0.7, y = (0.7 + top.offset), label = test.abbreviation,
gp = gpar(col = border.color, cex = legend.size), default.units = "native")
grid.text(x = 0.7, y = (0.665 + top.offset), label = content_area.label.pieces[[1]][1],
gp = gpar(col = border.color, cex = legend.size), default.units = "native")
grid.text(x = 0.7, y = (0.63 + top.offset), label = content_area.label.pieces[[1]][2],
gp = gpar(col = border.color, cex = legend.size), default.units = "native")
grid.text(x = 0.7, y = (0.595 + top.offset), label = scale_score.label,
gp = gpar(col = border.color, cex = legend.size, lineheight = legend.lheight), default.units = "native")
}
if (extra.legend.element) {
for (ele in extra.legend.elements) {
eval(parse(text = ele))
}
}
y.center <- seq(0.05, 0.4, length = number.growth.levels+1)
arrow.legend.coors.x <- c(0.25, 0.75, 0.75, 1, 0.5, 0, 0.25)
arrow.legend.coors.y <- c(0, 0, 1.3, 1.1, 2, 1.1, 1.3)
growth.label.cex <- (0.5 - max(0, max(nchar(growth.level.labels.shortened))-9)*0.01) ### OLD multipler = 0.042
for (i in seq(number.growth.levels)) {
pushViewport(
viewport(x=unit(0.3, "native"), y=unit(y.center[i], "native"),
width=unit(0.07, "native"), height=unit(y.center[2]-y.center[1], "npc"),
just=c("center", "bottom"), xscale=c(0, 1), yscale=c(0, 2))
)
grid.polygon(x=arrow.legend.coors.x, y=arrow.legend.coors.y, default.units="native",
gp=gpar(lwd=0.3, col=border.color, fill=arrow.legend.color[i]))
popViewport()
grid.polygon(x=c(0.05, rep(0.1875, 2)),
y=c((head(y.center,1)+tail(y.center,1))/2, y.center[i], y.center[i]+y.center[2]-y.center[1]),
gp=gpar(col=NA, lwd=0, fill=arrow.legend.color[i], alpha=0.45), default.units="native")
if (fan.extra) {
fan.extra.col <- arrow.legend.color[i]
fan.extra.x <- c(0.05, rep(0.1875, 2))
fan.extra.y <- c((head(y.center,1)+tail(y.center,1))/2, y.center[i], y.center[i]+y.center[2]-y.center[1])
eval(parse(text = fan.extras[i]))
}
pushViewport(
viewport(x=unit(0.2, "native"), y=unit(y.center[i], "native"),
width=unit(0.04, "native"), height=unit(y.center[2]-y.center[1], "npc"),
just=c("center", "bottom"))
)
grid.roundrect(x=0.5, y=0.5, width=1, height=1, r=unit(.45, "snpc"),
gp=gpar(lwd=0.3, col=border.color, fill=arrow.legend.color[i]))
popViewport()
grid.text(x=0.36,
y=((y.center[1]+y.center[2])/2)+(i-1)*(y.center[2]-y.center[1]),
label = growth.level.labels.shortened[i], default.units="native",
gp=gpar(col=border.color, cex=growth.label.cex), just="left")
grid.text(x=0.925, y=((y.center[1]+y.center[2])/2)+(i-1)*(y.center[2]-y.center[1]),
label = growth.level.cutscores.text[i], default.units="native",
gp=gpar(col=border.color, cex=growth.label.cex), just="right")
}
} else { ### right.vp with ASSESSMENT_TRANSITION
pushViewport(right.vp)
y.boundary.legend.1 <- c(yscale.range[1], yscale.range[1], rep(level_2_1_curve(xscale.range[2]), 2))
assign(paste0("y.boundary.legend.", number.achievement.level.regions[[2]]),
c(yscale.range[2], yscale.range[2], rep(eval(parse(text=paste0("level_2", "_", number.achievement.level.regions[[2]]-1, "_curve(xscale.range[2])"))), 2)))
if (number.achievement.level.regions[[2]] > 2) {
for (i in 2:(number.achievement.level.regions[[2]]-1)) {
assign(paste0("y.boundary.legend.", i),
eval(parse(text=paste0("c(rep(level_2", "_", i-1, "_curve(xscale.range[2]), 2), rep(level_2", "_", i, "_curve(xscale.range[2]), 2))"))))
}
}
for (i in seq(number.achievement.level.regions[[2]])){
grid.polygon(x = c(0,1,1,0), y = get(paste0("y.boundary.legend.", i)), default.units = "native",
gp = gpar(fill = achievement.level.region.colors[[2]][i], lwd = 0.5, col = border.color, alpha = 0.7))
}
grid.text(label = names(achievement.level.labels[[2]])[1],
x = 0.06, y = (level_2_1_curve(xscale.range[2]) + yscale.range[1])/2,
gp = gpar(col = border.color, fontface = 2, fontfamily = font.fam, cex = .85),
default.units = "native", just = "left")
grid.text(label = names(achievement.level.labels[[2]])[number.achievement.level.regions[[2]]],
x = 0.06,
y = (eval(parse(text = paste0("level_2", "_", number.achievement.level.regions[[2]]-1, "_curve(xscale.range[2])"))) + yscale.range[2])/2,
gp = gpar(col = border.color, fontface = 2, fontfamily = font.fam, cex = .85),
default.units = "native", just = "left")
if (number.achievement.level.regions[[2]] > 2) {
for (i in 2:(number.achievement.level.regions[[2]]-1)) {
grid.text(label = names(achievement.level.labels[[2]])[i],
x = 0.06,
y = (eval(parse(text = paste0("(level_2", "_", i-1, "_curve(xscale.range[2]) + level_2", "_", i, "_curve(xscale.range[2]))/2")))),
gp = gpar(col = border.color, fontface = 2, fontfamily = font.fam, cex = .85),
default.units = "native", just = "left")
}
}
grid.lines(0, c(yscale.range[1], yscale.range[2]), gp = gpar(lwd = 0.8, col = border.color), default.units = "native")
}
popViewport()
####################################
### No Data Viewport
####################################
if (!grade.values[['any_scale_scores']]) {
pushViewport(no.data.vp)
no.data.text <- paste("No", test.abbreviation, content.area.label, "Data")
no.data.text.pieces <- labelSplit(no.data.text)
if (length(no.data.text.pieces[[1]])==1) {
grid.text(x=0.5, y=0.5, no.data.text.pieces[[1]][1], gp=gpar(col="grey40", cex=3.5))
} else {
grid.text(x=0.475, y=0.575, no.data.text.pieces[[1]][1], gp=gpar(col="grey40", cex=2.25))
grid.text(x=0.475, y=0.425, no.data.text.pieces[[1]][2], gp=gpar(col="grey40", cex=2.25))
}
grid.roundrect(r=unit(0.02, "snpc"), gp=gpar(fill="white", lwd=0, col="white", alpha=0.5))
popViewport()
}
popViewport()
} ## END studentGrowthPlot Function
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