R/disp.plot.R

In tjconstant/disp.plot: plotting of irregular spaced matrix data with aribitary transformations

#' Plotting of irregular spaced matrix data with aribitary transformations.
#'
#' @description Polygon 2D plotting of irregular spaced matrix data with aribitary transformations.
#'
#' @param x x vector
#' @param y y vector
#' @param z z vector
#' @param fx function of x and y returning the functional transformation of the x-axis
#' @param fy function of x and y returning the functional transformation of the y-axis
#' @param nx,ny The square image will be constructed from nx by ny polygons. If nx and ny are equal to the defaults, length(unique(x)) and length(unique(y)), the plot produced will be a standard (uninterpolated) colorplot. Higher values of nx and ny will produce smoother plots.
#' @param method Specifies the interpolation method to use. Default is 'bilinear' using akima::interp, you can also use 'bicubic' (from akima::bicubic.grid).
#' @param return_data Returns a list of the three matricies used for image.plot
#' @param ... The usual arguments to the image function as x,y,or z or as a list with x,y,z as components. One can also include a breaks argument for an unequal color scale with color scale boundaries at the breaks (see example in the image.plot documentation).
#'
#' @return
#' Returns an image plot of the data
#' @details
#' In this function fx and fy are passed as functions, not raw vectors. See the examples for how to use this method to plot dispersion.
#' nothing_x(x,y) and nothing_y(x,y) are the default functions for transformations, and do nothing (i.e. return x and y respectivley)
#'
#' @author Tom Constant
#' @export
#'
#' @seealso
#' \code{\link[fields]{image.plot}},
#' \code{\link[akima]{interp}},
#' \code{\link[akima]{bicubic.grid}}
#'
#' @examples
#'
#' data(SPPdispersion)
#'
#' x<-SPPdispersion$wavelength*1e9
#' y<-SPPdispersion$angle
#' z<-SPPdispersion$reflection
#'
#' kx<-function(x,y) (2*pi/(x*1e-9))*sin(y*pi/180)
#' omega<-function(x,y) 2*pi*3e8/(x*1e-9)
#'
#' disp.plot(x,y,z)
#'
#' disp.plot(x,y,z,fx=kx,fy=omega,nx=200,ny=200,method="bicubic")
#'
#' # Polar Coordinates example
#'
#' # Edit SPPdisperison to vary from wavelength from 0 to 400 and angle 0 to 360 degrees
#' # Note, apart from the example, theres absolutley no reason to do this
#'
#' x <- SPPdispersion$wavelength*1e9-400
#' y <- 359*(SPPdispersion$angle-min(SPPdispersion$angle))/(max(SPPdispersion$angle)-min(SPPdispersion$angle))
#' z <- SPPdispersion$reflection
#'
#' # Polar Coordinate Transform
#' fx <- function(x,y) x*sin(y*pi/180)
#' fy <- function(x,y) x*cos(y*pi/180)
#'
#' disp.plot(x,y,z,fx,fy,nx=300,ny=300,method = "bicubic")

disp.plot<-function( x,
                     y,
                     z,
                     fx=nothing_x,
                     fy=nothing_y,
                     nx=length(unique(x)),
                     ny=length(unique(y)),
                     method="bilinear",
                     return_data=F,
                     ...){

  interp_grid<-disp.grid(x,y,z,nx,ny,method)

  x<-interp_grid$x
  y<-interp_grid$y
  z<-interp_grid$z

  if(return_data){
    return(list(fx=fx(x,y),fy=fy(x,y),z=z))
  }else{
    image.plot<-fields::image.plot
    image.plot(fx(x,y),fy(x,y),z,xaxs='i',yaxs='i',...)
  }

}


nothing_x<-function(x,y) return(x)
nothing_y<-function(x,y) return(y)