export functions correctly

NAMESPACE

@@ -1,11 +1,11 @@
 # Generated by roxygen2: do not edit by hand
 
-S3method(plot,Grid)
-S3method(plot,Stn)
-S3method(plot,heat)
-S3method(plot,kde2d.hist)
-S3method(plot,ts)
 export(data.agg)
+export(plot.Grid)
+export(plot.Stn)
+export(plot.TimeSeries)
+export(plot.heat)
+export(plot.kde2d.hist)
 import(HeatStress)
 import(MASS)
 import(RColorBrewer)

R/plot.Grid.R

@@ -26,7 +26,7 @@
 #' @param export.format "png" or "pdf" format.
 #' @param lon.points vector of longitudes for grid points to be marked in the map.
 #' @param lat.points vector of latitudes for grid points to be marked in the map.
-#' @export
+#' @export plot.Grid
 #' @details Packages classInt and maps needed.
 #' @import classInt maps
 #' @author Ana Casanueva (24.05.2017)

R/plot.Stn.R

@@ -27,7 +27,7 @@
 #' @param export logical. If TRUE, the figure is exported as pdf file. Default: False.
 #' @param export.path path (including file name) to save the plot.
 #' @param export.format "png" or "pdf" format.
-#' @export
+#' @export plot.Stn
 #' @details Packages classInt and maps needed.
 #' @import classInt maps 
 #' @author Ana Casanueva (17.02.2017)

R/plot.ts.R → R/plot.TimeSeries.R

@@ -11,7 +11,7 @@
 #' @inheritParams plot.ts.orig
 #' @return A time series plot. Plotted data if 'output.data'=TRUE.
 #' @details Plot time series of one vector. It is possible to plot the "raw" series or aggregate it temporarily or display a specific season/month. If the input data is a matrix, by default a separate panel is obtained for each station. 'stn.together' allows to plot all stations together (without subplot).
-#' @export
+#' @export plot.TimeSeries
 #' @import grDevices graphics 
 #' @examples \dontrun{
 #'# Generate some data
@@ -22,30 +22,30 @@
 #'data.day <- array(runif(length(dates.day)*2, -5, 30), dim=c(length(dates.day),2)) 
 #'data.hour <- array(runif(length(dates.hour)*2, -5, 30), dim=c(length(dates.hour),2)) 
 #'# Plot original data
-#'plot.ts(data.day, dates.day, title = c("Original daily data"))
-#'plot.ts(data.day, dates.day, title = c("Original hourly data"), hour=T)
+#'plot.TimeSeries(data.day, dates.day, title = c("Original daily data"))
+#'plot.TimeSeries(data.day, dates.day, title = c("Original hourly data"), hour=T)
 #'# Plot temporarily aggregated data
-#'plot.ts(data.day, dates.day, title = "Yearly data", agg="Y")
-#'plot.ts(data.day, dates.day, title = "Monthly data", agg="M")
-#'plot.ts(data.day, dates.day, title = "Seasonal data", agg="S")
-#'plot.ts(data.hour, dates.hour, hour=T, title = "Daily data", agg="D")
+#'plot.TimeSeries(data.day, dates.day, title = "Yearly data", agg="Y")
+#'plot.TimeSeries(data.day, dates.day, title = "Monthly data", agg="M")
+#'plot.TimeSeries(data.day, dates.day, title = "Seasonal data", agg="S")
+#'plot.TimeSeries(data.hour, dates.hour, hour=T, title = "Daily data", agg="D")
 #'# Plot a specific season or month 
-#'plot.ts(data.day, dates.day, title = "Seasonal data in summer", season = c(6,7,8))
-#'plot.ts(data.day, dates.day, title = c("Monthly data in June A", "Monthly data in June B"), 
+#'plot.TimeSeries(data.day, dates.day, title = "Seasonal data in summer", season = c(6,7,8))
+#'plot.TimeSeries(data.day, dates.day, title = c("Monthly data in June A", "Monthly data in June B"), 
 #'season = 6) # and different subtitles
 #'# Plot all stations together instead of in subplot 
-#'plot.ts(data.day, dates.day, title = "Monthly data in June A", season = 6, stn.together=T)
+#'plot.TimeSeries(data.day, dates.day, title = "Monthly data in June A", season = 6, stn.together=T)
 #'# Plot and save plotted data
-#'res <- plot.ts(data.day, dates.day, title = "Monthly data in June", season = 6, output.data = T)
+#'res <- plot.TimeSeries(data.day, dates.day, title = "Monthly data in June", season = 6, output.data = T)
 #'# Export plot to file
-#'plot.ts(data.day, dates.day, title = "Monthly data in June", season = 6, export = T)
+#'plot.TimeSeries(data.day, dates.day, title = "Monthly data in June", season = 6, export = T)
 #'# Change window size
-#'plot.ts(data.day, dates.day, title = "Monthly data in June", season = 6, 
+#'plot.TimeSeries(data.day, dates.day, title = "Monthly data in June", season = 6, 
 #'window.width = 8, window.height = 4)
 #'}
 
 
-plot.ts <-
+plot.TimeSeries <-
 
   function(data, dates, hour=FALSE, agg=NULL, aggFun="mean", season=NULL, 
             export=FALSE, outDir = "current", outNam = "plot1",outDev = "pdf", title=NULL, input.mch=FALSE,

R/plot.heat.R

@@ -23,7 +23,7 @@
 #' @details The two input variables of the desired index need to be provided, tas and either td or hu. Needed packages: HeatStress, RColorBrewer.
 #' @import HeatStress RColorBrewer
 #' @author Ana Casanueva, 13.12.2018
-#' @export
+#' @export plot.heat
 #' @examples \dontrun{
 #' # Generate data
 #' tas <- rnorm(150, mean=15, sd=2)

R/plot.kde2d.hist.R

@@ -16,7 +16,7 @@
 #' @return Plot with the 2-dimensional kernel densities and historgrams for the input variables.
 #' @details The two-dimensional kernel density estimation is done with the function kde2d in package MASS.
 #' @import MASS RColorBrewer
-#' @export
+#' @export plot.kde2d.hist
 #' @author Ana Casanueva, 13.12.2018
 #' @examples \dontrun{
 #' # Generate data

R/plotFun.R

@@ -13,8 +13,9 @@
 #'  
 #'  \item \code{plot.Stn}: Plot a map of stations.
 #'  \item \code{plot.Grid}: Plot a map of a regular grid.
-#'  \item \code{plot.ts}: Plot time series with or without temporal aggregation.
+#'  \item \code{plot.TimeSeries}: Plot time series with or without temporal aggregation.
 #'  \item \code{plot.kde2d.hist}: Plot a 2D Kernel density plot with the histograms of the marginal distributions.
+#'  \item \code{plot.heat}: Plot heat index as a function of the input variables.
 #'  
 #'  
 #'  Additional functions: