R/waterseries.R
In NCRN/NCRNWater: Data analysis and visualization for NPS I&M water monitoring
#' @include NCRNWater_NCRNWaterObj_Class_def.R
#' @include getWData.R
#' @importFrom dplyr arrange filter mutate pull slice
#' @importFrom ggplot2 aes facet_wrap geom_hline geom_line geom_point ggplot labs scale_color_manual scale_shape_manual theme element_blank theme_bw
#' @importFrom lubridate month year
#' @importFrom magrittr %>%
#' @importFrom plotly config ggplotly
#' @importFrom purrr map_chr
#' @importFrom viridis scale_color_viridis
#' @importFrom methods callGeneric
#'
#' @title waterseries
#'
#' @description Produces a time series plot from water data.
#'
#' @inheritParams getChars
#'
#' @param object Either a \code{data.frame} that is the output of \code{getWData}, a \code{Characteristic} object, a \code{Site} object, a \code{Park} object or a \code{list} of such objects.
#'
#' @param charname Required if \code{object} is not a \code{data.frame}. Name(s), in quotes, of one or more \code{Characteristic}s
#' whose data should be graphed.
#' @param by Indicates how the data for the plot should be grouped. A text variable in quotes. Choices are:
#' \describe{
#' \item{"park"}{If more than one park is included in the graph, this will produce a different line for each park.}
#' \item{"site}{If more than one site is included in the graph, this will produce a different line for each site.}
#' \item{"category"}{If more than one category is included in the graph, this will prodice a different line for each category.}
#' \item{"char"}{The default. If more than one characteristic is included in the graph, this will produce a different line for
#' each one.}
#' }
#'
#' @param assessment Vector indicating if assessment lines will be marked on the graph. See details below.
#' @param layers Defaults to c("points","line") Indicates which layers you wish to see on the plot.
#' @param yname Text, defaults to \code{NA}. A label for the y-axis. If an \code{Characteristic}, \code{Site}, or \code{Park} object
#' is passed to \code{object}, then the y-label will default to the Display Name and Units for the Characteristic, unless overwritten by the
#' \code{yname} argument. If a \code{data.frame} is passed then the y-label will either be the text from \code{yname} or blank
#' if \code{yname} is left as \code{NA}.
#' @param xname Text, defaults to \code{NA}. A label for the x-axis. If a \code{Characteristic}, \code{Site}, or \code{Park}
#' object is passed to \code{object}, then the x-label will default to whatever is indicated in \code{by},
#' unless overwritten by the \code{xname} argument. If a \code{data.frame} is passed then the x-label will either be the text
#' from \code{xname} or blank if \code{xname} is left as \code{NA}.
#'
#' @param censored If \code{FALSE} assumes all data points are true measurements. If \code{TRUE} plots the minimum or maximum
#' quantification limit and color codes to distinguish true measurements from detection limits. Defaults to \code{FALSE}.
#'
#' @param deseason If \code{FALSE} will plot all data points on the same figure. If \code{TRUE} will split plots by month.
#' Defaults to \code{FALSE}.
#'
#' @param labels A character vector indicating the labels for the data series, defaults to \code{NA}. If labels are provided
#' (one for each series) they will be printed. If \code{object} is a \code{data.frame} and \code{labels} is \code{NA} then no labels
#' will be printed. If \code{object} is a \code{Characteristic}, \code{Site}, or \code{Park} object, and \code{labels} is \code{NA}
#' then the default will depend on the \code{by} argument. "site" will be labeled with the site name from the \code{Site}'s
#' \code{Display Name} slot and "park" with the \code{Park}'s short name from the \code{ShortName} slot.
#' @param title A title in the graph in quotes. Defaults to \code{NULL}, which indicates no title should be used.
#' @param colors a character vector with the colors for the points and lines.
#' @param assesscolor a length one character vector with the color for the assessment lines.
#' @param sizes a length 3 numeric vector with the sizes for the points, line connecting the points and assessment lines.
#' @param legend a vector indicating where the legend position. Can be: "none","left","right","top","bottom" or a two element
#' numeric vector.
#' @param webplot If TRUE, the plot is produced using ggploty from the ploty package. Will produce a html plot with interactive
#' features.
#' @param ... Additional arguments used to select and filter data passed to \code{\link{getWData}}
#'
#' @return Creates a time series plot.
#'
#' @details The \code{assessment} argument determines if lines representing the assessment values should be drawn on the graph.
#' If \code{FALSE} then no lines will be drawn. If \code{TRUE}, the default, then the upper and lower points indicated in
#' \code{object}'s \code{Character} objects will be used to draw the lines. Note that if there are multiple assessment points,
#' for example if different parks have different points, or if there is both an upper and lower point, they will all be drawn.
#' If a \code{vector} of numbers is passed to \code{assessment} instead then those will serve as the assessment values and lines will
#' be drawn accordingly. Note that if \code{object} is a \code{data.frame} then the only way to draw assessment lines is by passing a
#' numeric \code{vector} to \code{assessment}.
#'
#' @export
setGeneric(name="waterseries",function(object, parkcode=NA, sitecode=NA,charname=NA, category=NA, by="char",
assessment=TRUE,
layers=c("points","line"), xname=NA, yname=NA, labels=NA, title=NULL, colors=NA, assesscolor="red",
sizes=c(3, 0.8, 1.1), censored = FALSE, deseason = FALSE,
legend="bottom", webplot=FALSE,...)
{standardGeneric("waterseries")},signature=c("object") )
setMethod(f="waterseries", signature=c(object="NCRNWaterObj"),
function(object, parkcode, sitecode, charname, category, by, assessment, layers, xname, yname,
labels, title, colors, assesscolor, sizes, censored, deseason, legend, webplot,...){
try(PlotData<-getWData(object=object,parkcode=parkcode, sitecode=sitecode,
charname=charname, category=category, ...))
if(!exists("PlotData") || nrow(PlotData)==0)stop("Function arguments did not return a data frame with records.")
# Add months and censored info for later filter for plotting
PlotData <- PlotData %>% mutate(year.dec = as.numeric(julian(Date)/365),
month = lubridate::month(Date, label = TRUE, abbr = FALSE)) %>% arrange(Date)
PlotData <- PlotData %>% group_by(Category, Characteristic, Site, Park, month) %>%
mutate(num_meas = ifelse(censored, sum(!is.na(ValueCen)),sum(!is.na(Value))),
pct_true = sum(ifelse(!censored, 1, 0))/num_meas, #sum(!is.na(ValueCen)),
adjValueCen = ifelse(censored == TRUE, max(ValueCen, na.rm = TRUE), Value)) %>%
ungroup() %>% arrange(month)
if(is.na(yname)) yname<-paste0(getCharInfo(object=object, charname=charname, category=category, info="CategoryDisplay")," (",
getCharInfo(object=object, charname=charname, category=category, info="Units"),")") %>% unique()
if(is.na(xname)) xname<-"Date"
if(all(is.na(labels))) labels<-switch(by,
none="",
char=unique(PlotData$Characteristic) %>% map_chr( ~unique(getCharInfo(object,charname=.x,info="DisplayName"))) %>%
factor(.,levels=unique(.)),
park=unique(PlotData$Park) %>% map_chr(~unique(getParkInfo(object, parkcode=.x, info="ParkShortName"))) %>%
`[`(order(unique(PlotData$Site))) %>% factor(.,levels=unique(.)),
site=unique(PlotData$Site) %>% map_chr(~unique(getSiteInfo(object, sitecode=.x, info="SiteName"))) %>%
`[`(order(unique(PlotData$Site))) %>% factor(.,levels=unique(.)),
category=unique(PlotData$Category) %>% map_chr(~unique(getCharInfo(object, category=.x, info="CategoryDisplay"))) %>%
`[`(order(unique(PlotData$Category))) %>% factor(.,levels=unique(.))
)
if(is.logical(assessment) & assessment) assessment<-c(getCharInfo(object=object,parkcode=parkcode, sitecode=sitecode,
charname=charname, category = category, info="LowerPoint"),getCharInfo(object=object,parkcode=parkcode, sitecode=sitecode,
charname=charname, category=category, info="UpperPoint")) %>% unlist %>% unique
assessment<-assessment[!is.na(assessment)] # needed if there is no upper or lower assessment.
callGeneric(object=PlotData, by=by, assessment=assessment, layers=layers, xname=xname, yname=yname,labels=labels,
title=title,colors=colors, assesscolor=assesscolor, sizes=sizes, censored = censored, deseason = deseason,
legend=legend, webplot=webplot)
})
setMethod(f="waterseries", signature=c(object="data.frame"),
function(object, by, assessment, layers, xname, yname, labels, title, colors, assesscolor,
sizes, censored, deseason, legend, webplot){
Grouper<-switch(by,
char=object %>% pull(Characteristic) %>% factor(., levels=unique(.)),
site=object %>% pull(Site) %>% factor(., levels=unique(sort(.))),
park=object %>% pull(Park) %>% factor(., levels=unique(sort(.))),
category=object %>% pull(Category) %>% factor(., levels=unique(sort(.)))
)
if(all(is.na(yname))) yname<-""
if(all(is.na(xname))) xname<-""
if(all(is.na(labels))) labels<-switch(by,
char=object$Characteristic %>% unique,
site=object$Site %>% unique,
park=object$Park %>% unique)
Xaxis <- object$Date
OutPlot<-
if(censored == TRUE){
if(deseason == FALSE){
ggplot(object, aes(x = Xaxis, y = adjValueCen, color = censored, group = censored))+
{if ("points" %in% layers) geom_point(size = sizes[1]) }+
{if (is.numeric(assessment)) geom_hline(yintercept = assessment, color = assesscolor,
linetype = "dashed", size = sizes[3])} +
labs(title = title, y = yname, x = xname) +
scale_color_manual(values = c("FALSE" = "blue", "TRUE" = "red"),
labels = c("FALSE" = "True Value", "TRUE"= "Censored"))+
theme_bw() +
theme(panel.grid = element_blank(), legend.title = element_blank(), legend.position = legend)
} else if(deseason == TRUE){
df_mon <- object %>% filter(num_meas>=6) %>% droplevels() %>% arrange(month)
if(nrow(df_mon)==0)stop("Too few data points to plot.")
ggplot(df_mon, aes(x = Date, y = adjValueCen, color = censored, group = censored))+
geom_point(size = sizes[1])+
labs(title = title, y = yname, x = xname) +
scale_color_manual(values = c("FALSE" = "blue", "TRUE" = "red"),
labels = c("FALSE" = "True Value", "TRUE"= "Censored"))+
theme_bw() +
theme(panel.grid = element_blank(), legend.title = element_blank(), legend.position = legend)+
facet_wrap(~month)+
{if (is.numeric(assessment)) geom_hline(yintercept = assessment, color = assesscolor,
linetype = "dashed", size = sizes[3])}
} # End of deseason = TRUE
} else if (censored == FALSE){
if(deseason == FALSE){
ggplot(object, aes(x = Xaxis, y = Value))+
{if ("points" %in% layers) geom_point(aes(color = Grouper, shape = Grouper), size = sizes[1]) }+
{if ("line" %in% layers) geom_line(aes(color = Grouper), size = sizes[2])} +
{if (is.na(colors)) viridis::scale_color_viridis(name = "legend", labels = labels,
discrete = T)}+
{if (!is.na(colors)) scale_color_manual(name = "legend", labels = labels, values = colors)}+
scale_shape_manual(name = "legend", labels = labels,
values = c(16, 15, 17, 18, 1, 0, 2, 5, 6, 3, 4, 8, 13, 9, 12)[1:nlevels(Grouper)]) +
{if (is.numeric(assessment)) geom_hline(yintercept = assessment, color = assesscolor,
linetype = "dashed", size = sizes[3])} +
labs(title = title, y = yname, x = xname) +
theme_bw() +
theme(panel.grid = element_blank(), legend.title = element_blank(), legend.position = legend)#+
} else if(deseason == TRUE){
df_mon2 <- object %>% filter(num_meas>=6) %>% droplevels() %>% arrange(month)
if(nrow(df_mon2)==0)stop("Too few data points to plot.")
Grouper2<-switch(by,
char = df_mon2 %>% pull(Characteristic) %>% factor(., levels=unique(.)),
site = df_mon2 %>% pull(Site) %>% factor(., levels=unique(sort(.))),
park = df_mon2 %>% pull(Park) %>% factor(., levels=unique(sort(.))),
category = df_mon2 %>% pull(Category) %>% factor(., levels=unique(sort(.)))
)
ggplot(df_mon2, aes(x = Date, y = Value))+
geom_point(aes(color = Grouper2, shape = Grouper2), size = sizes[1])+
#geom_point(size = sizes[1])+
{if (is.na(colors)) viridis::scale_color_viridis(name = "legend", labels = labels, discrete = T)}+
{if (!is.na(colors)) scale_color_manual(name = "legend", labels = labels, values = colors)}+
scale_shape_manual(name = "legend", labels = labels,
values = c(16, 15, 17, 18, 1, 0, 2, 5, 6, 3, 4, 8, 13, 9, 12)[1:nlevels(Grouper)]) +
{if (is.numeric(assessment)) geom_hline(yintercept = assessment, color = assesscolor,
linetype = "dashed", size = sizes[3])} +
labs(title = title, y = yname, x = xname) +
theme_bw() +
theme(panel.grid = element_blank(), legend.title = element_blank(), legend.position = legend)+
facet_wrap(~month)
}
}# End of censored == FALSE
ifelse(webplot, return(ggplotly(OutPlot) %>% plotly::config(displaylogo=F)),return(OutPlot))
})
NCRN/NCRNWater documentation built on May 15, 2023, 9:50 p.m.
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#' @include NCRNWater_NCRNWaterObj_Class_def.R
#' @include getWData.R
#' @importFrom dplyr arrange filter mutate pull slice
#' @importFrom ggplot2 aes facet_wrap geom_hline geom_line geom_point ggplot labs scale_color_manual scale_shape_manual theme element_blank theme_bw
#' @importFrom lubridate month year
#' @importFrom magrittr %>%
#' @importFrom plotly config ggplotly
#' @importFrom purrr map_chr
#' @importFrom viridis scale_color_viridis
#' @importFrom methods callGeneric
#'
#' @title waterseries
#'
#' @description Produces a time series plot from water data.
#'
#' @inheritParams getChars
#'
#' @param object Either a \code{data.frame} that is the output of \code{getWData}, a \code{Characteristic} object, a \code{Site} object, a \code{Park} object or a \code{list} of such objects.
#'
#' @param charname Required if \code{object} is not a \code{data.frame}. Name(s), in quotes, of one or more \code{Characteristic}s
#' whose data should be graphed.
#' @param by Indicates how the data for the plot should be grouped. A text variable in quotes. Choices are:
#' \describe{
#' \item{"park"}{If more than one park is included in the graph, this will produce a different line for each park.}
#' \item{"site}{If more than one site is included in the graph, this will produce a different line for each site.}
#' \item{"category"}{If more than one category is included in the graph, this will prodice a different line for each category.}
#' \item{"char"}{The default. If more than one characteristic is included in the graph, this will produce a different line for
#' each one.}
#' }
#'
#' @param assessment Vector indicating if assessment lines will be marked on the graph. See details below.
#' @param layers Defaults to c("points","line") Indicates which layers you wish to see on the plot.
#' @param yname Text, defaults to \code{NA}. A label for the y-axis. If an \code{Characteristic}, \code{Site}, or \code{Park} object
#' is passed to \code{object}, then the y-label will default to the Display Name and Units for the Characteristic, unless overwritten by the
#' \code{yname} argument. If a \code{data.frame} is passed then the y-label will either be the text from \code{yname} or blank
#' if \code{yname} is left as \code{NA}.
#' @param xname Text, defaults to \code{NA}. A label for the x-axis. If a \code{Characteristic}, \code{Site}, or \code{Park}
#' object is passed to \code{object}, then the x-label will default to whatever is indicated in \code{by},
#' unless overwritten by the \code{xname} argument. If a \code{data.frame} is passed then the x-label will either be the text
#' from \code{xname} or blank if \code{xname} is left as \code{NA}.
#'
#' @param censored If \code{FALSE} assumes all data points are true measurements. If \code{TRUE} plots the minimum or maximum
#' quantification limit and color codes to distinguish true measurements from detection limits. Defaults to \code{FALSE}.
#'
#' @param deseason If \code{FALSE} will plot all data points on the same figure. If \code{TRUE} will split plots by month.
#' Defaults to \code{FALSE}.
#'
#' @param labels A character vector indicating the labels for the data series, defaults to \code{NA}. If labels are provided
#' (one for each series) they will be printed. If \code{object} is a \code{data.frame} and \code{labels} is \code{NA} then no labels
#' will be printed. If \code{object} is a \code{Characteristic}, \code{Site}, or \code{Park} object, and \code{labels} is \code{NA}
#' then the default will depend on the \code{by} argument. "site" will be labeled with the site name from the \code{Site}'s
#' \code{Display Name} slot and "park" with the \code{Park}'s short name from the \code{ShortName} slot.
#' @param title A title in the graph in quotes. Defaults to \code{NULL}, which indicates no title should be used.
#' @param colors a character vector with the colors for the points and lines.
#' @param assesscolor a length one character vector with the color for the assessment lines.
#' @param sizes a length 3 numeric vector with the sizes for the points, line connecting the points and assessment lines.
#' @param legend a vector indicating where the legend position. Can be: "none","left","right","top","bottom" or a two element
#' numeric vector.
#' @param webplot If TRUE, the plot is produced using ggploty from the ploty package. Will produce a html plot with interactive
#' features.
#' @param ... Additional arguments used to select and filter data passed to \code{\link{getWData}}
#'
#' @return Creates a time series plot.
#'
#' @details The \code{assessment} argument determines if lines representing the assessment values should be drawn on the graph.
#' If \code{FALSE} then no lines will be drawn. If \code{TRUE}, the default, then the upper and lower points indicated in
#' \code{object}'s \code{Character} objects will be used to draw the lines. Note that if there are multiple assessment points,
#' for example if different parks have different points, or if there is both an upper and lower point, they will all be drawn.
#' If a \code{vector} of numbers is passed to \code{assessment} instead then those will serve as the assessment values and lines will
#' be drawn accordingly. Note that if \code{object} is a \code{data.frame} then the only way to draw assessment lines is by passing a
#' numeric \code{vector} to \code{assessment}.
#'
#' @export
setGeneric(name="waterseries",function(object, parkcode=NA, sitecode=NA,charname=NA, category=NA, by="char",
assessment=TRUE,
layers=c("points","line"), xname=NA, yname=NA, labels=NA, title=NULL, colors=NA, assesscolor="red",
sizes=c(3, 0.8, 1.1), censored = FALSE, deseason = FALSE,
legend="bottom", webplot=FALSE,...)
{standardGeneric("waterseries")},signature=c("object") )
setMethod(f="waterseries", signature=c(object="NCRNWaterObj"),
function(object, parkcode, sitecode, charname, category, by, assessment, layers, xname, yname,
labels, title, colors, assesscolor, sizes, censored, deseason, legend, webplot,...){
try(PlotData<-getWData(object=object,parkcode=parkcode, sitecode=sitecode,
charname=charname, category=category, ...))
if(!exists("PlotData") || nrow(PlotData)==0)stop("Function arguments did not return a data frame with records.")
# Add months and censored info for later filter for plotting
PlotData <- PlotData %>% mutate(year.dec = as.numeric(julian(Date)/365),
month = lubridate::month(Date, label = TRUE, abbr = FALSE)) %>% arrange(Date)
PlotData <- PlotData %>% group_by(Category, Characteristic, Site, Park, month) %>%
mutate(num_meas = ifelse(censored, sum(!is.na(ValueCen)),sum(!is.na(Value))),
pct_true = sum(ifelse(!censored, 1, 0))/num_meas, #sum(!is.na(ValueCen)),
adjValueCen = ifelse(censored == TRUE, max(ValueCen, na.rm = TRUE), Value)) %>%
ungroup() %>% arrange(month)
if(is.na(yname)) yname<-paste0(getCharInfo(object=object, charname=charname, category=category, info="CategoryDisplay")," (",
getCharInfo(object=object, charname=charname, category=category, info="Units"),")") %>% unique()
if(is.na(xname)) xname<-"Date"
if(all(is.na(labels))) labels<-switch(by,
none="",
char=unique(PlotData$Characteristic) %>% map_chr( ~unique(getCharInfo(object,charname=.x,info="DisplayName"))) %>%
factor(.,levels=unique(.)),
park=unique(PlotData$Park) %>% map_chr(~unique(getParkInfo(object, parkcode=.x, info="ParkShortName"))) %>%
`[`(order(unique(PlotData$Site))) %>% factor(.,levels=unique(.)),
site=unique(PlotData$Site) %>% map_chr(~unique(getSiteInfo(object, sitecode=.x, info="SiteName"))) %>%
`[`(order(unique(PlotData$Site))) %>% factor(.,levels=unique(.)),
category=unique(PlotData$Category) %>% map_chr(~unique(getCharInfo(object, category=.x, info="CategoryDisplay"))) %>%
`[`(order(unique(PlotData$Category))) %>% factor(.,levels=unique(.))
)
if(is.logical(assessment) & assessment) assessment<-c(getCharInfo(object=object,parkcode=parkcode, sitecode=sitecode,
charname=charname, category = category, info="LowerPoint"),getCharInfo(object=object,parkcode=parkcode, sitecode=sitecode,
charname=charname, category=category, info="UpperPoint")) %>% unlist %>% unique
assessment<-assessment[!is.na(assessment)] # needed if there is no upper or lower assessment.
callGeneric(object=PlotData, by=by, assessment=assessment, layers=layers, xname=xname, yname=yname,labels=labels,
title=title,colors=colors, assesscolor=assesscolor, sizes=sizes, censored = censored, deseason = deseason,
legend=legend, webplot=webplot)
})
setMethod(f="waterseries", signature=c(object="data.frame"),
function(object, by, assessment, layers, xname, yname, labels, title, colors, assesscolor,
sizes, censored, deseason, legend, webplot){
Grouper<-switch(by,
char=object %>% pull(Characteristic) %>% factor(., levels=unique(.)),
site=object %>% pull(Site) %>% factor(., levels=unique(sort(.))),
park=object %>% pull(Park) %>% factor(., levels=unique(sort(.))),
category=object %>% pull(Category) %>% factor(., levels=unique(sort(.)))
)
if(all(is.na(yname))) yname<-""
if(all(is.na(xname))) xname<-""
if(all(is.na(labels))) labels<-switch(by,
char=object$Characteristic %>% unique,
site=object$Site %>% unique,
park=object$Park %>% unique)
Xaxis <- object$Date
OutPlot<-
if(censored == TRUE){
if(deseason == FALSE){
ggplot(object, aes(x = Xaxis, y = adjValueCen, color = censored, group = censored))+
{if ("points" %in% layers) geom_point(size = sizes[1]) }+
{if (is.numeric(assessment)) geom_hline(yintercept = assessment, color = assesscolor,
linetype = "dashed", size = sizes[3])} +
labs(title = title, y = yname, x = xname) +
scale_color_manual(values = c("FALSE" = "blue", "TRUE" = "red"),
labels = c("FALSE" = "True Value", "TRUE"= "Censored"))+
theme_bw() +
theme(panel.grid = element_blank(), legend.title = element_blank(), legend.position = legend)
} else if(deseason == TRUE){
df_mon <- object %>% filter(num_meas>=6) %>% droplevels() %>% arrange(month)
if(nrow(df_mon)==0)stop("Too few data points to plot.")
ggplot(df_mon, aes(x = Date, y = adjValueCen, color = censored, group = censored))+
geom_point(size = sizes[1])+
labs(title = title, y = yname, x = xname) +
scale_color_manual(values = c("FALSE" = "blue", "TRUE" = "red"),
labels = c("FALSE" = "True Value", "TRUE"= "Censored"))+
theme_bw() +
theme(panel.grid = element_blank(), legend.title = element_blank(), legend.position = legend)+
facet_wrap(~month)+
{if (is.numeric(assessment)) geom_hline(yintercept = assessment, color = assesscolor,
linetype = "dashed", size = sizes[3])}
} # End of deseason = TRUE
} else if (censored == FALSE){
if(deseason == FALSE){
ggplot(object, aes(x = Xaxis, y = Value))+
{if ("points" %in% layers) geom_point(aes(color = Grouper, shape = Grouper), size = sizes[1]) }+
{if ("line" %in% layers) geom_line(aes(color = Grouper), size = sizes[2])} +
{if (is.na(colors)) viridis::scale_color_viridis(name = "legend", labels = labels,
discrete = T)}+
{if (!is.na(colors)) scale_color_manual(name = "legend", labels = labels, values = colors)}+
scale_shape_manual(name = "legend", labels = labels,
values = c(16, 15, 17, 18, 1, 0, 2, 5, 6, 3, 4, 8, 13, 9, 12)[1:nlevels(Grouper)]) +
{if (is.numeric(assessment)) geom_hline(yintercept = assessment, color = assesscolor,
linetype = "dashed", size = sizes[3])} +
labs(title = title, y = yname, x = xname) +
theme_bw() +
theme(panel.grid = element_blank(), legend.title = element_blank(), legend.position = legend)#+
} else if(deseason == TRUE){
df_mon2 <- object %>% filter(num_meas>=6) %>% droplevels() %>% arrange(month)
if(nrow(df_mon2)==0)stop("Too few data points to plot.")
Grouper2<-switch(by,
char = df_mon2 %>% pull(Characteristic) %>% factor(., levels=unique(.)),
site = df_mon2 %>% pull(Site) %>% factor(., levels=unique(sort(.))),
park = df_mon2 %>% pull(Park) %>% factor(., levels=unique(sort(.))),
category = df_mon2 %>% pull(Category) %>% factor(., levels=unique(sort(.)))
)
ggplot(df_mon2, aes(x = Date, y = Value))+
geom_point(aes(color = Grouper2, shape = Grouper2), size = sizes[1])+
#geom_point(size = sizes[1])+
{if (is.na(colors)) viridis::scale_color_viridis(name = "legend", labels = labels, discrete = T)}+
{if (!is.na(colors)) scale_color_manual(name = "legend", labels = labels, values = colors)}+
scale_shape_manual(name = "legend", labels = labels,
values = c(16, 15, 17, 18, 1, 0, 2, 5, 6, 3, 4, 8, 13, 9, 12)[1:nlevels(Grouper)]) +
{if (is.numeric(assessment)) geom_hline(yintercept = assessment, color = assesscolor,
linetype = "dashed", size = sizes[3])} +
labs(title = title, y = yname, x = xname) +
theme_bw() +
theme(panel.grid = element_blank(), legend.title = element_blank(), legend.position = legend)+
facet_wrap(~month)
}
}# End of censored == FALSE
ifelse(webplot, return(ggplotly(OutPlot) %>% plotly::config(displaylogo=F)),return(OutPlot))
})
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