R/canopy.profile.R

In gshideler/mangroveStructure: tools for calculating mangrove forest structure

#' Mangrove Canopy Plot for Point-Centered Quarter Method
#'
#' This function allows you to calculate the Holdridge Complexity Index and Mean Stand Diameter for pcqm data.
#' @param samplingpoint Column name for sampling points (numerical). Default name is "samplingpoint". First sampling point must be 1.
#' @param height Column name for height. Default name is "height". Values must be in meters.
#' @param interval10 Logical argument for distance between PCQM sampling points. If interval10=TRUE (Default), the canopy plot assumes equidistant 10-meter spacing between all sampling points. If interval10=FALSE, a unique column must exist in the dataframe with distance from the previous sampling point.
#' @param interval Column name for the distances between sampling points (required if interval10=FALSE). Default name is "interval". The first row (samplingpoint 1) must be a value of 0. Each successive sampling point number represents the distance from the previous sampling point, NOT the additive distance from sampling point 1.
#' @param ymax Optional argument for specifying the maximum extent of the y axis. If not specified (Default), ymax is estimated based on dataframe values.
#' @param xmax Optional argument for specifying the maximum extent of the x axis. If not specified (Default), xmax is estimated based on dataframe values.
#' @keywords mangrove structure, pcqm, canopy profile
#' @examples
#' canopy.profile(mangrove_data)
#' canopy.profile(mangrove_data, ymax = 50, samplingpoint = "Sampling_Point", interval10=FALSE)
#' @export

# Function to plot canopy height across distance from Point-Centered Quarter Method transect
canopy.profile<-function(x, 
                      samplingpoint = 'samplingpoint',
                      height = 'height',
                      interval10 = TRUE,
                      interval = 'interval',
                      ymax = NULL,
                      xmax = NULL){
  
    #Confirm it is a data frame
     x <- as.data.frame(x)
  
    #Load columns
    x$SamplingPoint <- x[,samplingpoint]
    x$height <- x[,height]
  
  #Check for NA cells
  if(any(is.na(x)) == TRUE) stop("Data frame cannot contain missing values (NAs).")

  #Preference for y axis maximum value display
    null_yMax <- max(x$height)+mean(sd(x$height))
    yMax <- if(is.null(ymax)) null_yMax else ymax
      
    

  
  # Get the summarize and transform functions from the plyr namespace
  summarize = get("summarize", asNamespace('plyr'))

  # RUN if interval is standard 10 m for entire data set
  if(interval10==TRUE){
      if(min(x$SamplingPoint>1)){
      stop("Please check that Sampling Points begin at 1.")
            }
    else{
      plotcan <- plyr::ddply(x, "SamplingPoint", summarize, Avg_Height = mean(height), SD = sd(height))
      plotcan[, 3][plotcan[, 3] == 0] <- NA
      plotcan$SamplingPoint <- (plotcan$SamplingPoint*10)-10
      
      null_xMax <- max(plotcan$SamplingPoint)
      xMax <- if(is.null(xmax)) null_xMax else xmax
       
      par(ask=FALSE)
      plot(plotcan$SamplingPoint, plotcan$Avg_Height, pch=20, ylab="Mean canopy height (SD)", xlab="Distance from starting point", ylim=range(c(0, yMax)), xlim=range(c(0, xMax)))
      lines(plotcan$SamplingPoint, plotcan$Avg_Height)
      arrows(plotcan$SamplingPoint, plotcan$Avg_Height-plotcan$SD, plotcan$SamplingPoint, plotcan$Avg_Height+plotcan$SD, length=0.05, angle=90, code=3)
    }
  }
  
  # RUN if interval has unique distances
   else{
    x$Interval <- x[,interval]
    plotcan <- plyr::ddply(x, "samplingpoint", summarize, Avg_Height = mean(height), SD = sd(height), Interval=max(interval), SamplingPoint=0)
    for (i in 1:nrow(plotcan)) {
      ifelse(plotcan$samplingpoint[i]==1, plotcan$SamplingPoint[i]<-0, plotcan$SamplingPoint[i] <- plotcan$Interval[i] + plotcan$SamplingPoint[i-1])
      }
     
    null_xMax <- max(plotcan$SamplingPoint)
    xMax <- if(is.null(xmax)) null_xMax else xmax
      
    plotcan[, 3][plotcan[, 3] == 0] <- NA
    par(ask=FALSE)
    plot(plotcan$SamplingPoint, plotcan$Avg_Height, pch=20, ylab="Mean canopy height (SD)", xlab="Distance from starting point", ylim=range(c(0, yMax)), xlim=range(c(0, xMax)))
    lines(plotcan$SamplingPoint, plotcan$Avg_Height)
    arrows(plotcan$SamplingPoint, plotcan$Avg_Height-plotcan$SD, plotcan$SamplingPoint, plotcan$Avg_Height+plotcan$SD, length=0.05, angle=90, code=3)
   
  }
  
  }