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terminus_picker_v3_15nov2017.R
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terminus_picker_v3_15nov2017.R
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########################################################################################################
## script: terminus_picker_v3.R
#
## Author: Steve Foga
## Contact: [email protected] OR [email protected]
## Creation Date: 10 APR 2013
## Modification Date: 05 MAY 2014
#
#
## Purpose: A semi-automated method of detecting the glacier terminus position on
## remotely-sensed imagery. Uses difference in brigthness of adjacent pixels
## in order to do guess the terminus location.
#
#
## Recent updates: 1) Added "black to white" and "white to blue" color palettes for picker.
## 2) Corrected MODIS naming conventions
## 3) Added "previous good pick" to plot window
## 4) Added binary "good image (1)/bad image (0) column to output CSV file
##
##
#
## Known issues: 1) (Minor) The "picked" pixel indicators are sometimes not easy to see, or change colors during a picking session.
## 2) (Minor) The first preview image comes up as rainbow colors on the first run.
#
#
## Proposed updates: 1) (DONE) Add multiple color schemes for "Interactive Mode" (Currently Earth tones only.)
## 2) (DONE) Adding separate digitization tool for sediment plumes (i.e. Rink Isbrae). DONE
## 3) Allowing the picker to handle more than one row value per column of data. (not necessary if picked correctly)
#
##
#
## Picker tools: A) "Interactive Mode" Allows the user to edit and/or add picks. Close window by clicking the Windows "X" when finished.
## 1) "Left-click" = add picks.
## 2) "Right-click" = revert to previous pick. Can be done for multiple undos.
## B) "Plume Dileniation" Pick the border of a sediment plume. Tool then calculates the area and adds it to the output CSV.
## 1) "Left-click" = add points.
## 2) "Right-click" = delete points.
## C) "Melange Dileniation" Pick the border of an ice melange. Tool works the same as the "plume dileniation" tool.
## D) "SAVE Image and Continue" If the picks are satisfactory, then continue to the next image.
## E) "DISCARD Image" If image is cloudy and/or has systematic errors, discard from terminus area calculation. Sets all picks to NA.
## F) "Refresh" Click to re-generate points on preview raster.
## G) "List" Shows picks and their index number. For informational use only.
#
#
########## Load libraries ##########
library(sp) # Base GIS package
library(raster) # For raster I/O, algebra
library(rgdal) # For additional GIS features not covered by 'sp' or 'raster'
#tclRequire("Tktable") # For loading table functionality
library(tkrplot) # For plotting interactive point grid
library(tcltk2) # Tcl/tk GUI
########## User input ##########
## Specify year
#year <- 2009
year <- 2014
## Specify location: "east" or "west" Greenland?
## (west = Rink, KG, Jakobshavn; east = Helheim, Kangerdlugssuaq)
region <- "east"
#region <- "west"
## Input directory
dir_in = "/home/chrx/Downloads/picker/images/"
#dir_in <- "C:/Users/fogaste/Desktop/2008_hhg_test/"
#dir_in <- "C:/Users/fogaste/Documents/Projects/2012_08_21_Helheim_Sea_Ice_Cover/helheim_geotiff/2008_terra_merge_8bit3/"
#dir_in <- 'C:/Users/fogaste/Documents/Projects/rink_isbrae/2012_terra_rink/'
## Output directory (dir. does not have to exist)
#dir_out <- "C:/Users/fogaste/Documents/Projects/2012_08_21_Helheim_Sea_Ice_Cover/helheim_geotiff/2009_terra_terminus_area_test/"
dir_out <- '/home/chrx/Downloads/picker/out/'
## Input shapefile (bouding box for area calculation)
#shp_in <- "C:/Users/fogaste/Documents/Projects/rink_isbrae/shapefiles/rink_term_bound.shp"
shp_in <- "/home/chrx/Downloads/picker/kgl_term_box.shp"
## OPTIONAL: Use a mask to further clip down melange raster extent
#mel_shp_in <- "C:/Users/fogaste/Documents/Projects/rink_isbrae/shapefiles/rink_boundary.shp"
#mel_shp_in <- "C:/Users/fogaste/Documents/Projects/2012_08_21_Helheim_Sea_Ice_Cover/helheim_geotiff/Shapefiles/helheim_boundary_main.shp"
######################### Automated section #########################
## determine OS (for plotting)
ptf = .Platform$OS.type
## Check if output folder exists, if not, create it.
dir.create(dir_out,showWarnings=FALSE)
shp <- shapefile(shp_in)
if (exists("mel_shp_in")){
mel_shp <- shapefile(mel_shp_in)
}
## Get files
fn_in <- list.files(path = dir_in, pattern = ".tif", full.names=TRUE) # Entire path + file names
## Find dates, slope and resulting terminus position of each image
im_date <- terminus <- term_y <- rep(NA,length(fn_in))
## Make NULL variable to dynamically store values
true_ct <- NULL
## Create an empty list to fill with x coordinates
xs <- fit <- xs_final <- rep(list(list()),length(fn_in))
## Define focal matrix
#kern <- matrix(c(6,6,6,0,0,0,-1,-1,-1),nrow=3)
#kern <- matrix(c(0,-1,0,-1,5,-1,0,-1,0),nrow=3)
#sobel_x <- matrix(c(-1,-2,-1,0,0,0,1,2,1),nrow=3)
#sobel_y <- matrix(c(1,0,-1,2,0,-2,1,0,-1),nrow=3)
#sharp <- matrix(c(0,-1,0,-1,8,-1,0,-1,0),nrow=3)
#emboss <- matrix(c(-2,-1,0,-1,1,1,0,1,2),nrow=3)
#hipass <- matrix(c(-0.7,-1,-0.7,-1,4,-1,-0.7,-1,-0.7),nrow=3)
for (idx in 1:length(fn_in)){
## Find julian date of each image (YYYYDDD)
im_name <- strsplit(fn_in[idx],split="/")
im_name <- im_name[[1]][length(im_name[[1]])]
## Find the date string and write to new variable
strng <- regexpr(year,im_name)
im_date[idx] <- substr(im_name,strng[1]+nchar(year),strng[1]+nchar(year)+2)
## Read in raster
print(fn_in[idx])
rin <- raster(fn_in[idx],band=1)
## make sure raster is 8 bit, else do conversion
#if (dataType(rin) != "INT1U"){
# rin <- calc(rin, fun=function(x){((x - min(x)) * 255)/(max(x)- min(x)) + 0})
#}
## Store original spatial resolution (for later calculations)\
orig_sp_res <- res(rin)[1]
## Store dynamic spatial resolution (used for re-sampling; this value will change)
sp_res <- res(rin)[1]
## If the raster resolution is finer than MODIS, then resample the pixels. Otherwise picking takes too long & images load too slowly.
if (sp_res <= 10){
resamp_grid <- raster(nrow=(nrow(rin)/10),ncol=(ncol(rin)/10),crs=crs(rin),xmn=xmin(rin),xmx=xmax(rin),ymn=ymin(rin),ymx=ymax(rin))
rin <- resample(rin,resamp_grid, method='ngb')
} else if (sp_res < 30 & sp_res >= 15){
resamp_grid <- raster(nrow=(nrow(rin)/5),ncol=(ncol(rin)/5),crs=crs(rin),xmn=xmin(rin),xmx=xmax(rin),ymn=ymin(rin),ymx=ymax(rin))
rin <- resample(rin,resamp_grid,method='ngb')
} else if (sp_res <= 50 & sp_res >= 30) {
resamp_grid <- raster(nrow=(nrow(rin)/3),ncol=(ncol(rin)/3),crs=crs(rin),xmn=xmin(rin),xmx=xmax(rin),ymn=ymin(rin),ymx=ymax(rin))
rin <- resample(rin,resamp_grid,method='ngb')
}
## Crop image to fjord shapefile
#rin <- crop(rin,mel_shp)
#rin <- mask(rin,mel_shp,snap='in')
## Determinine its spatial resolution
#sp_res <- res(rin)[1]
## Set display rasters for the picker
rast <- crop(rin,shp,snap='in')
#rast <- mask(rast,shp)
#rast <- rast^2
## Convert original raster into a matrix
rast_mat <- matrix(rast[],nrow=rast@nrows,ncol=rast@ncols,byrow=TRUE)
## Find center of study area
x_start_idx <- length(rast_mat[,1])
## Add column names to terminus position matrix
name_col <- rep(NA,x_start_idx)
for (cidx in 1:x_start_idx){
name_col[cidx] <- paste("c",cidx,sep="")
}
ys <- 1:x_start_idx
# Fill all of variable 'xs' with NA values
xs[[idx]] <- rep(NA,length(ys))
for (i in 1:length(ys)){
## If there is no max (NA values only) then pass through an NA...
if (length(which.max(diff(rast_mat[i,1:dim(rast_mat)[2]]))) == 0){
xs[[idx]][i] <- NA
## ...else, replace the index with the maximum value in the row
}else{
xs[[idx]][i] <- (which.max(diff(rast_mat[i,1:dim(rast_mat)[2]]))+1)
}
}
## Find median xs value
med <- median(sort(xs[[idx]]))
## Eliminate any values that are 10 pixels or more away from the median
xs[[idx]][which(xs[[idx]] <= med-15 | xs[[idx]] >= med+15)] <- NA
## Output count of values with NAs
cat("Image ",im_date[idx],": ",length(xs[[idx]][is.na(xs[[idx]])])," NA values.\n",sep="")
######################### Picker section #########################
## Initialize bomb (counter that tells the for loop to break)
bomb <- 0
## Initialize undo count (so multiple undos can be performed by user)
undo_ct <- 0
## Create empty vectors for area calculations
area_sq_km <- plume_sq_km <- melange_sq_km <- Pl.XX <- Pl.YY <- Me.XX <- Me.YY <- rep(NA,length(fn_in))
bomb3_ct <- 0
## Initialize previous value variable (storage container for undo function & plume digitization)
prev_value_x <- prev_value_y <- Pl.X <- Pl.Y <- Me.X <- Me.Y <- prev_value_plx <- prev_value_ply <- NULL
if (length(which(is.na(xs[[idx]])==TRUE)) == length(ys)) { ## If all values are NA
next
} else {
rplot <- brick(rin)
#rplot_c <- crop(rplot,shp,snap='in')
#rplot_c <- mask(rplot_c,shp)
tmp_rast <- rast <- rplot_c <- crop(rin,shp,snap='in')
#tmp_rast <- rast <- mask(tmp_rast,shp)
## Re-create ys to match clipped raster
ys <- 1:dim(rast)[1]
const_rast_mat <- matrix(tmp_rast[],nrow=tmp_rast@nrows,ncol=tmp_rast@ncols,byrow=TRUE)
## For each xs value, ask if the user wants to change the value
for (pidx in 1:length(xs[[idx]])+bomb3_ct){
## LEGACY: If the "back" command was called, load all data from previous iteration
if (bomb == 3){ pidx <<- pidx-2 }
if (bomb3_ct > 0){ pidx <- pidx-bomb3_ct }
pt_mat <- pt_mat_disp <- matrix(data=NA,nrow=dim(rast)[1],ncol=dim(rast)[2])
## LEGACY: move rows manually; highlight row with different values
for (ridx in 1:length(xs[[idx]])){
if (pidx==ridx){
pt_mat_disp[ys[ridx],xs[[idx]][ridx]] <- 201
pt_mat[ys[ridx],xs[[idx]][ridx]] <- 0
}else{
pt_mat_disp[ys[ridx],xs[[idx]][ridx]] <- 200
pt_mat[ys[ridx],xs[[idx]][ridx]] <- 255
}
}
pt_rast <- raster(pt_mat,crs=rast@crs, xmn=rast@extent@xmin, ymn=rast@extent@ymin,
xmx=rast@extent@xmax, ymx=rast@extent@ymax)
pt_rast_disp <- raster(pt_mat_disp,crs=rast@crs, xmn=rast@extent@xmin, ymn=rast@extent@ymin,
xmx=rast@extent@xmax, ymx=rast@extent@ymax)
## Display plume data (if available)
pl_pt_mat <- matrix(data=NA,nrow=dim(rast)[1],ncol=dim(rast)[2])
if (length(Pl.X) > 0){
# Remove NA values
if (any(is.na(Pl.X))){
Pl.X <- Pl.X[-which(is.na(Pl.X))]
Pl.Y <- Pl.Y[-which(is.na(Pl.Y))]
}
for (ridx in 1:length(Pl.X)){
pl_pt_mat[Pl.Y[ridx],Pl.X[ridx]] <- 201
}
}
pl_pt_rast <- raster(pl_pt_mat,crs=rast@crs, xmn=rast@extent@xmin, ymn=rast@extent@ymin,
xmx=rast@extent@xmax, ymx=rast@extent@ymax)
## Display melange data (if available)
me_pt_mat <- matrix(data=NA,nrow=dim(rin)[1],ncol=dim(rin)[2])
if (length(Me.X) > 0){
if (any(is.na(Me.X))){
Me.X <- Me.X[-which(is.na(Me.X))]
Me.Y <- Me.Y[-which(is.na(Me.Y))]
}
for (ridx in 1:length(Me.X)){
me_pt_mat[Me.Y[ridx],Me.X[ridx]] <- 50
}
}
me_pt_rast <- raster(me_pt_mat,crs=rin@crs, xmn=rin@extent@xmin, ymn=rin@extent@ymin,
xmx=rin@extent@xmax, ymx=rin@extent@ymax)
## Re-plot the data
graphics.off()
## Plot the entire study area
if (ptf == "windows"){
windows(xpos=1000,ypos=0)
plot(rplot,stretch="hist")
plot(shp,add=TRUE)
## Plot the high-contrast raster + the terminus points
windows(xpos=1000,ypos=400)
} else {
x11(xpos=1000,ypos=0)
plot(rplot,stretch="hist")
plot(shp,add=TRUE)
x11(xpos=1000,ypos=400)
}
plot(rast,col=palette(gray(0:255/255)),xaxt='n',yaxt='n')
bkpts <- c(0,50,200,201,250)
colors <- c("black","yellow","green","red","black")
plot(pt_rast_disp,breaks=bkpts,col=colors,legend=FALSE,add=TRUE)
plot(t(pl_pt_rast),breaks=bkpts,col=colors,legend=FALSE,add=TRUE)
#axis(1,at=seq(xmin(rast),xmax(rast)-sp_res,sp_res),cex.axis=0.8,las=2,tck=1,pos=ymin(rast),labels=1:dim(rast)[2])
#axis(2,at=seq(ymin(rast),ymax(rast),sp_res),cex.axis=0.7,tck=1,las=2,labels=(dim(rast)[1]+1):1)
## Set to break loop if it is changed to 1
if (bomb == 2 & idx == 2){
xs[[1]] <- rep(NA,length(xs[[1]]))
} else if (bomb == 2){
xs[[idx]] <- rep(NA,x_start_idx)
}
## Reset bomb to 0
bomb <- 0
## Find all the rows that still have NA values
na_rows <- which(is.na(xs[[idx]]))
## "Interactive" button: move to interactive menu, and l-click to change point position
on.int <- function(){
plotFxn <- function(){
## Set RGB palette for digitized points
rgb.palette <- colorRampPalette(c("blue", "yellow"))
test.pal <- colorRampPalette(c("#660000","#FF4D4D"))
## Turn digitized points into a raster
for (pidx in 1:length(xs[[idx]])){
pt_mat <- pt_mat_disp <- matrix(data=NA,nrow=dim(rast)[1],ncol=dim(rast)[2])
for (ridx in 1:length(xs[[idx]])){
if (pidx==ridx){
pt_mat_disp[ys[ridx],xs[[idx]][ridx]] <- 201
pt_mat[ys[ridx],xs[[idx]][ridx]] <- 0
}else{
pt_mat_disp[ys[ridx],xs[[idx]][ridx]] <- 200
pt_mat[ys[ridx],xs[[idx]][ridx]] <- 255
}
}
}
pt_rast <- raster(pt_mat,crs=rast@crs, xmn=rast@extent@xmin, ymn=rast@extent@ymin,
xmx=rast@extent@xmax, ymx=rast@extent@ymax)
## Plot raster + digitized points
par(mar=c(0,0,0,0))
## Plot image with terrain colors
## Plot image with black-and-white colors
bw.pal <- colorRampPalette(c("black","white"))
image(rast,main="",axes=FALSE,col=bw.pal(500))
par(new=TRUE)
image(pt_rast,main="",axes=FALSE)
bkpts <- c(0,50,200,201,250)
colors <- c("black","yellow","green","red","black")
}
require(tcltk2)
tt2 <- tktoplevel()
img <- tkrplot(tt2,fun=plotFxn,hscale=1,vscale=1)
tkpack(img)
tkgrid(img)
## Find dimensions of tk plot image (this is different than the raster dimensions)
img_wid <- as.numeric(tclvalue(tkwinfo("reqwidth",img)))
img_hei <- as.numeric(tclvalue(tkwinfo("reqheight",img)))
## Find dimensions of raster image
ras_wid <- dim(rast)[2]
ras_hei <- dim(rast)[1]
## If pixel dimensions are not square (i.e. rectangular), find the dimensions of each one to adjust pixel count
pix_hei <- res(rast)[2]
pix_wid <- res(rast)[1]
pix_wid <- pix_hei <- 1
## Find pixel size of tk image based upon raster dimensions. Use this to adjust all input clicks
w_x_factor <- (img_wid/ras_wid)*pix_wid
h_y_factor <- (img_hei/ras_hei)*pix_hei
#cat("wx factor:",w_x_factor,'\n')
#cat("hy factor:",h_y_factor,'\n')
mvPoint <- function(xClick,yClick){
## All x and y-clicks are divided by a fixed factor, since each pixel is stretched to fit a coordinate grid.
## Store original value in variable (for undo function)
if (length(prev_value_x) == 0){
## Rounding
prev_value_x <<- xs[[idx]][ceiling((as.numeric(yClick))/h_y_factor)]
prev_value_y <<- ceiling(as.numeric(yClick)/h_y_factor)
} else {
prev_value_x <<- append(prev_value_x,xs[[idx]][ceiling((as.numeric(yClick))/h_y_factor)])
prev_value_y <<- append(prev_value_y,ceiling(as.numeric(yClick)/h_y_factor))
}
## Rounding
xs[[idx]][ceiling((as.numeric(yClick))/h_y_factor)] <<- ceiling(as.numeric(xClick)/w_x_factor)
cat("x click:",xClick)
cat("y click:",yClick)
## No rounding
#xs[[idx]][(as.numeric(yClick)/h_y_factor)] <<- as.numeric(xClick)/w_x_factor
cat("X var:",ceiling((as.numeric(xClick))/w_x_factor),'\n')
cat("Y var:",ceiling((as.numeric(yClick))/h_y_factor),'\n')
}
## Function to add points
OnLeftClick <- function(x,y){
xClick <- x
yClick <- y
## Call the move point function
mvPoint(xClick,yClick)
## Print the new coordinates in the console window
print(xClick)
print(yClick)
## Set the undo count back to zero
undo_ct <<- 0
## Re-plot data after each click
tkrreplot(img)
}
## Function to undo last l-click action
OnRightClick <- function(){
if (length(prev_value_x) > 0){
if (is.na(prev_value_y[length(prev_value_y)-undo_ct])){
## If the point didn't exist previously, make it disappear when 'undo' is called
xs[[idx]][prev_value_y[length(prev_value_y)-undo_ct]] <<- NA
}else{
## Replace the xs[[idx]] value with the previous value
xs[[idx]][prev_value_y[length(prev_value_y)-undo_ct]] <<- prev_value_x[length(prev_value_x)-undo_ct]
}
## Advance the undo count
undo_ct <<- undo_ct + 1
cat(paste("Undo count:",undo_ct,"\n"))
cat(paste("X move to:",prev_value_x[length(prev_value_x)-undo_ct],"\n"))
cat(paste("Y move to:",prev_value_y[length(prev_value_y)-undo_ct],"\n"))
}
tkrreplot(img)
}
## Assign function to l-click mouse button
tkbind(img,"<Button-1>",OnLeftClick)
## Assign undo function to r-click mouse button
tkbind(img,"<Button-3>",OnRightClick)
tkconfigure(img,cursor="hand2")
if (exists("tt2")){ tkwait.window(tt2) }
}
## "Interactive - previous picks" button: plot previous picks instead of predictive picks
on.int.prev <- function(){
plotFxn <- function(){
## Set RGB palette for digitized points
#rgb.palette <- colorRampPalette(c("white", "black"))
#test.pal <- colorRampPalette(c("#660000","#FF4D4D"))
## If any, determine which good previous picks to load
if (length(true_ct) > 0 & any(true_ct == 1)){
one_idx <- which(true_ct == 1)
last_idx <- one_idx[length(one_idx)]
xs[[idx]] <<- xs[[last_idx]]
for (pidx in 1:length(xs[[last_idx]])){
pt_mat <- pt_mat_disp <- matrix(data=NA,nrow=dim(rast)[1],ncol=dim(rast)[2])
for (ridx in 1:length(xs[[last_idx]])){
if (pidx==ridx){
pt_mat_disp[ys[ridx],xs[[last_idx]][ridx]] <- 201
pt_mat[ys[ridx],xs[[last_idx]][ridx]] <- 0
}else{
pt_mat_disp[ys[ridx],xs[[last_idx]][ridx]] <- 200
pt_mat[ys[ridx],xs[[last_idx]][ridx]] <- 255
}
}
}
} else {## Else, load predicted picks as normal
for (pidx in 1:length(xs[[idx]])){
pt_mat <- pt_mat_disp <- matrix(data=NA,nrow=dim(rast)[1],ncol=dim(rast)[2])
for (ridx in 1:length(xs[[idx]])){
if (pidx==ridx){
pt_mat_disp[ys[ridx],xs[[idx]][ridx]] <- 201
pt_mat[ys[ridx],xs[[idx]][ridx]] <- 0
}else{
pt_mat_disp[ys[ridx],xs[[idx]][ridx]] <- 200
pt_mat[ys[ridx],xs[[idx]][ridx]] <- 255
}
}
}
}
## Turn digitized points into a raster
pt_rast <- raster(pt_mat,crs=rast@crs, xmn=rast@extent@xmin, ymn=rast@extent@ymin,
xmx=rast@extent@xmax, ymx=rast@extent@ymax)
## Plot raster + digitized points
par(mar=c(0,0,0,0))
## Plot image with black-and-white colors
white.black.pal <- colorRampPalette(c("white","black"))
image(rast,main="",axes=FALSE,col=white.black.pal(500))
par(new=TRUE)
image(pt_rast,main="",axes=FALSE)
bkpts <- c(0,50,200,201,250)
colors <- c("black","yellow","green","red","black")
}
require(tcltk2)
tt2 <- tktoplevel()
img <- tkrplot(tt2,fun=plotFxn,hscale=2,vscale=2)
tkpack(img)
tkgrid(img)
## Find dimensions of tk plot image (this is different than the raster dimensions)
img_wid <- as.numeric(tclvalue(tkwinfo("reqwidth",img)))
img_hei <- as.numeric(tclvalue(tkwinfo("reqheight",img)))
## Find dimensions of raster image
ras_wid <- dim(rast)[2]
ras_hei <- dim(rast)[1]
## If pixel dimensions are not square (i.e. rectangular), find the dimensions of each one to adjust pixel count
pix_hei <- res(rast)[2]
pix_wid <- res(rast)[1]
pix_wid <- pix_hei <- 1
## Find pixel size of tk image based upon raster dimensions. Use this to adjust all input clicks
w_x_factor <- (img_wid/ras_wid)*pix_wid
h_y_factor <- (img_hei/ras_hei)*pix_hei
mvPoint <- function(xClick,yClick){
## All x and y-clicks are divided by a fixed factor, since each pixel is stretched to fit a coordinate grid.
## Store original value in variable (for undo function)
if (length(prev_value_x) == 0){
prev_value_x <<- xs[[idx]][ceiling((as.numeric(yClick))/h_y_factor)]
prev_value_y <<- ceiling(as.numeric(yClick)/h_y_factor)
} else {
prev_value_x <<- append(prev_value_x,xs[[idx]][ceiling((as.numeric(yClick))/h_y_factor)])
prev_value_y <<- append(prev_value_y,ceiling(as.numeric(yClick)/h_y_factor))
}
xs[[idx]][ceiling((as.numeric(yClick))/h_y_factor)] <<- ceiling(as.numeric(xClick)/w_x_factor)
cat("x click:",xClick)
cat("y click:",yClick)
cat("X var:",ceiling((as.numeric(xClick))/w_x_factor),'\n')
cat("Y var:",ceiling((as.numeric(yClick))/h_y_factor),'\n')
}
## Function to add points
OnLeftClick <- function(x,y){
xClick <- x
yClick <- y
## Call the move point function
mvPoint(xClick,yClick)
## Print the new coordinates in the console window
print(xClick)
print(yClick)
## Set the undo count back to zero
undo_ct <<- 0
## Re-plot data after each click
tkrreplot(img)
}
## Function to undo last l-click action
OnRightClick <- function(){
if (length(prev_value_x) > 0){
if (is.na(prev_value_y[length(prev_value_y)-undo_ct])){
## If the point didn't exist previously, make it disappear when 'undo' is called
xs[[idx]][prev_value_y[length(prev_value_y)-undo_ct]] <<- NA
}else{
## Replace the xs[[idx]] value with the previous value
xs[[idx]][prev_value_y[length(prev_value_y)-undo_ct]] <<- prev_value_x[length(prev_value_x)-undo_ct]
}
## Advance the undo count
undo_ct <<- undo_ct + 1
cat(paste("Undo count:",undo_ct,"\n"))
cat(paste("X move to:",prev_value_x[length(prev_value_x)-undo_ct],"\n"))
cat(paste("Y move to:",prev_value_y[length(prev_value_y)-undo_ct],"\n"))
}
tkrreplot(img)
}
## Assign function to l-click mouse button
tkbind(img,"<Button-1>",OnLeftClick)
## Assign undo function to r-click mouse button
tkbind(img,"<Button-3>",OnRightClick)
tkconfigure(img,cursor="hand2")
if (exists("tt2")){ tkwait.window(tt2) }
}
## "Interactive - Blue to white" button: move to interactive menu, and l-click to change point position
on.int.blue <- function(){
plotFxn <- function(){
## Set RGB palette for digitized points
rgb.palette <- colorRampPalette(c("blue", "yellow"))
test.pal <- colorRampPalette(c("#660000","#FF4D4D"))
## Turn digitized points into a raster
for (pidx in 1:length(xs[[idx]])){
pt_mat <- pt_mat_disp <- matrix(data=NA,nrow=dim(rast)[1],ncol=dim(rast)[2])
for (ridx in 1:length(xs[[idx]])){
if (pidx==ridx){
pt_mat_disp[ys[ridx],xs[[idx]][ridx]] <- 201
pt_mat[ys[ridx],xs[[idx]][ridx]] <- 0
}else{
pt_mat_disp[ys[ridx],xs[[idx]][ridx]] <- 200
pt_mat[ys[ridx],xs[[idx]][ridx]] <- 255
}
}
}
pt_rast <- raster(pt_mat,crs=rast@crs, xmn=rast@extent@xmin, ymn=rast@extent@ymin,
xmx=rast@extent@xmax, ymx=rast@extent@ymax)
## Plot raster + digitized points
par(mar=c(0,0,0,0))
## Plot image with terrain colors
## Plot image with black-and-white colors
blue.white.pal <- colorRampPalette(c("blue","white"))
image(rast,main="",axes=FALSE,col=blue.white.pal(500))
par(new=TRUE)
image(pt_rast,main="",axes=FALSE)
bkpts <- c(0,50,200,201,250)
colors <- c("black","yellow","green","red","black")
}
require(tcltk2)
tt2 <- tktoplevel()
img <- tkrplot(tt2,fun=plotFxn,hscale=2,vscale=2)
tkpack(img)
tkgrid(img)
## Find dimensions of tk plot image (this is different than the raster dimensions)
img_wid <- as.numeric(tclvalue(tkwinfo("reqwidth",img)))
img_hei <- as.numeric(tclvalue(tkwinfo("reqheight",img)))
## Find dimensions of raster image
ras_wid <- dim(rast)[2]
ras_hei <- dim(rast)[1]
## If pixel dimensions are not square (i.e. rectangular), find the dimensions of each one to adjust pixel count
pix_hei <- res(rast)[2]
pix_wid <- res(rast)[1]
pix_wid <- pix_hei <- 1
## Find pixel size of tk image based upon raster dimensions. Use this to adjust all input clicks
w_x_factor <- (img_wid/ras_wid)*pix_wid
h_y_factor <- (img_hei/ras_hei)*pix_hei
mvPoint <- function(xClick,yClick){
## All x and y-clicks are divided by a fixed factor, since each pixel is stretched to fit a coordinate grid.
## Store original value in variable (for undo function)
if (length(prev_value_x) == 0){
prev_value_x <<- xs[[idx]][ceiling((as.numeric(yClick))/h_y_factor)]
prev_value_y <<- ceiling(as.numeric(yClick)/h_y_factor)
} else {
prev_value_x <<- append(prev_value_x,xs[[idx]][ceiling((as.numeric(yClick))/h_y_factor)])
prev_value_y <<- append(prev_value_y,ceiling(as.numeric(yClick)/h_y_factor))
}
xs[[idx]][ceiling((as.numeric(yClick))/h_y_factor)] <<- ceiling(as.numeric(xClick)/w_x_factor)
cat("x click:",xClick)
cat("y click:",yClick)
cat("X var:",ceiling((as.numeric(xClick))/w_x_factor),'\n')
cat("Y var:",ceiling((as.numeric(yClick))/h_y_factor),'\n')
}
## Function to add points
OnLeftClick <- function(x,y){
xClick <- x
yClick <- y
## Call the move point function
mvPoint(xClick,yClick)
## Print the new coordinates in the console window
print(xClick)
print(yClick)
## Set the undo count back to zero
undo_ct <<- 0
## Re-plot data after each click
tkrreplot(img)
}
## Function to undo last l-click action
OnRightClick <- function(){
if (length(prev_value_x) > 0){
if (is.na(prev_value_y[length(prev_value_y)-undo_ct])){
## If the point didn't exist previously, make it disappear when 'undo' is called
xs[[idx]][prev_value_y[length(prev_value_y)-undo_ct]] <<- NA
}else{
## Replace the xs[[idx]] value with the previous value
xs[[idx]][prev_value_y[length(prev_value_y)-undo_ct]] <<- prev_value_x[length(prev_value_x)-undo_ct]
}
## Advance the undo count
undo_ct <<- undo_ct + 1
cat(paste("Undo count:",undo_ct,"\n"))
cat(paste("X move to:",prev_value_x[length(prev_value_x)-undo_ct],"\n"))
cat(paste("Y move to:",prev_value_y[length(prev_value_y)-undo_ct],"\n"))
}
tkrreplot(img)
}
## Assign function to l-click mouse button
tkbind(img,"<Button-1>",OnLeftClick)
## Assign undo function to r-click mouse button
tkbind(img,"<Button-3>",OnRightClick)
tkconfigure(img,cursor="hand2")
if (exists("tt2")){ tkwait.window(tt2) }
}
## Plot shape around sediment plume area
on.plume <- function(){
plotFxn <- function(){
## Set RGB palette for digitized points
rgb.palette <- colorRampPalette(c("blue", "yellow"))
test.pal <- colorRampPalette(c("#660000","#FF4D4D"))
## Turn digitized points into a raster
pl_pt_mat <- matrix(data=NA,nrow=dim(rast)[1],ncol=dim(rast)[2])
if (length(Pl.X) > 0){
if (any(is.na(Pl.X))){
Pl.X <- Pl.X[-which(is.na(Pl.X))]
Pl.Y <- Pl.Y[-which(is.na(Pl.Y))]
}
for (ridx in 1:length(Pl.X)){
pl_pt_mat[Pl.Y[ridx],Pl.X[ridx]] <- 201
}
}
pl_pt_rast <- raster(pl_pt_mat,crs=rast@crs, xmn=rast@extent@xmin, ymn=rast@extent@ymin,
xmx=rast@extent@xmax, ymx=rast@extent@ymax)
pl_pt_rast <- t(pl_pt_rast)
## Plot raster + digitized points
par(mar=c(0,0,0,0))
image(rast,main="",axes=FALSE,col=terrain.colors(500))
par(new=TRUE)
if (length(Pl.X) > 0){
image(t(pl_pt_rast),main="",axes=FALSE)
bkpts <- c(0,50,200,201,250)
colors <- c("black","yellow","green","red","black")
}
}
require(tcltk2)
tt2 <- tktoplevel()
img <- tkrplot(tt2,fun=plotFxn,hscale=2,vscale=2)
tkpack(img)
tkgrid(img)
## Find dimensions of tk plot image (this is different than the raster dimensions)
img_wid <- as.numeric(tclvalue(tkwinfo("reqwidth",img)))
img_hei <- as.numeric(tclvalue(tkwinfo("reqheight",img)))
## Find dimensions of raster image
ras_wid <- dim(rast)[2]
ras_hei <- dim(rast)[1]
## If pixel dimensions are not square (i.e. rectangular), find the dimensions of each one to adjust pixel count
pix_hei <- res(rast)[2]
pix_wid <- res(rast)[1]
#if (pix_wid == pix_hei){
pix_wid <- pix_hei <- 1
#}
## Find pixel size of tk image based upon raster dimensions. Use this to adjust all input clicks
w_x_factor <- (img_wid/ras_wid)*pix_wid
h_y_factor <- (img_hei/ras_hei)*pix_hei
mvPoint <- function(xClick,yClick){
## All x and y-clicks are divided by a fixed factor, since each pixel is stretched to fit a coordinate grid.
## Store original value in variable (for undo function)
if (length(prev_value_plx) == 0){
prev_value_plx <<- ceiling(as.numeric(xClick)/w_x_factor)
prev_value_ply <<- ceiling(as.numeric(yClick)/h_y_factor)
} else {
prev_value_plx <<- append(prev_value_plx,ceiling(as.numeric(xClick)/w_x_factor))
prev_value_ply <<- append(prev_value_ply,ceiling(as.numeric(yClick)/h_y_factor))
}
if (length(Pl.X) != 0){
Pl.X <<- append(Pl.X,ceiling(as.numeric(xClick)/w_x_factor))
Pl.Y <<- append(Pl.Y,ceiling((as.numeric(yClick))/h_y_factor))
} else {
Pl.X <<- ceiling(as.numeric(xClick)/w_x_factor)
Pl.Y <<- ceiling((as.numeric(yClick))/h_y_factor)
}
cat("X var:",ceiling((as.numeric(xClick))/w_x_factor),'\n')
cat("Y var:",ceiling((as.numeric(yClick))/h_y_factor),'\n')
}
## Function to add points
OnLeftClick <- function(x,y){
xClick <- x
yClick <- y
## Call the move point function
mvPoint(xClick,yClick)
## Print the new coordinates in the console window
print(xClick)
print(yClick)
## Set the undo count back to zero
undo_ct <<- 0
## Re-plot data after each click
tkrreplot(img)
}
## Function to undo last l-click action
OnRightClick <- function(){
if (length(prev_value_plx) > 0){
Pl.X[length(Pl.X)-undo_ct] <<- NA
Pl.Y[length(Pl.Y)-undo_ct] <<- NA
## Advance the undo count
undo_ct <<- undo_ct + 1
cat(paste("Undo count:",undo_ct,"\n"))
}
tkrreplot(img)
}
## Assign function to l-click mouse button
tkbind(img,"<Button-1>",OnLeftClick)
## Assign undo function to r-click mouse button
tkbind(img,"<Button-3>",OnRightClick)
tkconfigure(img,cursor="hand2")
if (exists("tt2")){ tkwait.window(tt2) }
}
## Plot shape around ice melange area
on.melange <- function(){
plotFxn <- function(){
## Set RGB palette for digitized points
rgb.palette <- colorRampPalette(c("blue", "yellow"))
test.pal <- colorRampPalette(c("#660000","#FF4D4D"))
## Turn digitized points into a raster
me_pt_mat <- matrix(data=NA,nrow=dim(rin)[1],ncol=dim(rin)[2])
if (length(Me.X) > 0){
if (any(is.na(Me.X))){
Me.X <- Me.X[-which(is.na(Me.X))]
Me.Y <- Me.Y[-which(is.na(Me.Y))]
}
for (ridx in 1:length(Me.X)){
me_pt_mat[Me.Y[ridx],Me.X[ridx]] <- 201
}
}
# Create a plottable raster from the resulting matrix
me_pt_rast <- raster(me_pt_mat,crs=rin@crs, xmn=rin@extent@xmin, ymn=rin@extent@ymin,
xmx=rin@extent@xmax, ymx=rin@extent@ymax)
# Transpose the raster
me_pt_rast <- t(me_pt_rast)
## Plot raster + digitized points
par(mar=c(0,0,0,0))
image(rin,main="",axes=FALSE,col=terrain.colors(500))
par(new=TRUE)
if (length(Me.X) > 0){
image(t(me_pt_rast),main="",axes=FALSE)
bkpts <- c(0,50,200,201,250)
colors <- c("black","yellow","green","red","black")
}
}
require(tcltk2)
# Plot up the images on a new tk window
tt2 <- tktoplevel()
img <- tkrplot(tt2,fun=plotFxn,hscale=2,vscale=2)
tkpack(img)
tkgrid(img)
## Find dimensions of tk plot image (this is different than the raster dimensions)
img_wid <- as.numeric(tclvalue(tkwinfo("reqwidth",img)))
img_hei <- as.numeric(tclvalue(tkwinfo("reqheight",img)))
## Find dimensions of raster image
ras_wid <- dim(rin)[2]
ras_hei <- dim(rin)[1]
## If pixel dimensions are not square (i.e. rectangular), find the dimensions of each one to adjust pixel count
pix_hei <- res(rin)[2]
pix_wid <- res(rin)[1]
pix_wid <- pix_hei <- 1
## Find pixel size of tk image based upon raster dimensions. Use this to adjust all input clicks
w_x_factor <- (img_wid/ras_wid)*pix_wid
h_y_factor <- (img_hei/ras_hei)*pix_hei
mvPoint <- function(xClick,yClick){
## All x and y-clicks are divided by a fixed factor, since each pixel is stretched to fit a coordinate grid.
## Store original value in variable (for undo function)
if (length(prev_value_plx) == 0){
## Rounding
prev_value_plx <<- ceiling(as.numeric(xClick)/w_x_factor)
prev_value_ply <<- ceiling(as.numeric(yClick)/h_y_factor)
} else {
## Rounding
prev_value_plx <<- append(prev_value_plx,ceiling(as.numeric(xClick)/w_x_factor))
prev_value_ply <<- append(prev_value_ply,ceiling(as.numeric(yClick)/h_y_factor))
}
## Rounding
if (length(Me.X) != 0){
Me.X <<- append(Me.X,ceiling(as.numeric(xClick)/w_x_factor))
Me.Y <<- append(Me.Y,ceiling((as.numeric(yClick))/h_y_factor))
} else {
Me.X <<- ceiling(as.numeric(xClick)/w_x_factor)
Me.Y <<- ceiling((as.numeric(yClick))/h_y_factor)
}
cat("X var:",ceiling((as.numeric(xClick))/w_x_factor),'\n')
cat("Y var:",ceiling((as.numeric(yClick))/h_y_factor),'\n')
}
## Function to add points
OnLeftClick <- function(x,y){
xClick <- x
yClick <- y
## Call the move point function
mvPoint(xClick,yClick)
## Print the new coordinates in the console window
print(xClick)
print(yClick)
## Set the undo count back to zero
undo_ct <<- 0
## Re-plot data after each click
tkrreplot(img)
}
## Function to undo last l-click action
OnRightClick <- function(){
if (length(prev_value_plx) > 0){
Me.X[length(Me.X)-undo_ct] <<- NA
Me.Y[length(Me.Y)-undo_ct] <<- NA
## Advance the undo count
undo_ct <<- undo_ct + 1
cat(paste("Undo count:",undo_ct,"\n"))
#cat(paste("X move to:",prev_value_plx[length(prev_value_plx)-undo_ct],"\n"))
#cat(paste("Y move to:",prev_value_ply[length(prev_value_ply)-undo_ct],"\n"))
}
tkrreplot(img)
}
## Assign function to l-click mouse button
tkbind(img,"<Button-1>",OnLeftClick)
## Assign undo function to r-click mouse button
tkbind(img,"<Button-3>",OnRightClick)
tkconfigure(img,cursor="hand2")
if (exists("tt2")){ tkwait.window(tt2) }
}
## "Refresh" button: re-load current images
on.ref <- function(){
## Close the tcltk window
tkdestroy(tt)
}
## "Save & Next Image" button: skips entire image (everything looks OK)
on.skipall <- function(){
## Close the tcltk window
tkdestroy(tt)
## Leave the loop and start the next iteration on the outer loop
## This is not recommended programming practice, but it works!
bomb <<- 1
}
## "DISCARD" button: removes raster from final output plot
on.discard <- function(){
## Close the tcltk window
tkdestroy(tt)
if (exists("tt2")){ tkdestroy("tt2")}
## Leave the loop using the bomb (see above)
bomb <<- 2
}
## Initialize window
tt<-tktoplevel()
## First window
Name <- tclVar(xs[[idx]][pidx])
entry.Name <-tkentry(tt,width="20",textvariable=Name)
## Set heading for options window
fn_split <- strsplit(fn_in[idx],split="/")
fn_split <- strsplit(fn_split[[1]][length(fn_split[[1]])],split="_")
if (year <= 2008){
## Split values that are separated by a period, then select the first part of the split value
fn_nums <- strsplit(fn_split[[1]],split="\\.")[[1]][1]
} else {
fn_num <- as.numeric(fn_split[[1]])
## Eliminate any values which are not numeric
fn_nums <- fn_num[which(!is.na(fn_num))]
## If applicable, eliminate any values that are the year string
fn_nums <- fn_nums[which(fn_nums != year)]
}
tkgrid(tklabel(tt,text=paste("Day ",im_date[idx],sep=" ")))
tkgrid(tklabel(tt,text=paste("Row",pidx,": Enter new column value:")))
tkgrid(tklabel(tt,text=paste("Rows with NA values:",paste(length(na_rows)),sep=" ")))
tkgrid(entry.Name)
## Set button names and appearance
int.but <- tkbutton(tt,text=" TERMINUS Digitization Mode (White to Black) ",command=on.int)
int.blu.but <- tkbutton(tt,text=" TERMINUS Digitization Mode (Blue to White) ",command=on.int.blue)
int.prev.but <- tkbutton(tt,text=" APPLY Previous Good TERMINUS Position (White to Black) ",command=on.int.prev)
plu.but <- tkbutton(tt,text=" Plume Delineation ",command=on.plume)
mel.but <- tkbutton(tt,text=" Melange Delineation ",command=on.melange)
#back.but <- tkbutton(tt,text=" Back ",command=on.back)
ref.but <- tkbutton(tt,text=" Refresh Window ",command=on.ref)
skipall.but <- tkbutton(tt,text=" SAVE Image & Continue ",command=on.skipall)
discard.but <- tkbutton(tt,text=" **DISCARD Image** ",command=on.discard)
## Set original xs value to a different variable
xs_old <- xs[[idx]][pidx]
##### Set buttons #####
## List edit button
#tkbind(entry.Name,on.list)
#tkgrid(list.but)
## Interactive previous button
tkbind(entry.Name,on.int.prev)
tkgrid(int.prev.but)
## Interactive Menu button (white to black)
tkbind(entry.Name,on.int)
tkgrid(int.but)
## Interactive Menu button (blue to white)
tkbind(entry.Name,on.int.blue)
tkgrid(int.blu.but)
## Plume digitizer button
tkbind(entry.Name,on.plume)
tkgrid(plu.but)
## Melange digitizer button
tkbind(entry.Name,on.melange)
tkgrid(mel.but)
## Skip button
tkbind(entry.Name,"<s>",on.ref)
tkgrid(ref.but)
## Skip All button
tkbind(entry.Name,"<q>",on.skipall)
tkgrid(skipall.but)
## Discard button
tkbind(entry.Name,on.discard)
tkgrid(discard.but)
#tkbind(entry.Name, "<Return>",OnOK)
tkfocus(tt)
## Bring window to front of screen
tkraise(tt)
## Stop the loop until the options window is closed
tkwait.window(tt)
## Break program if bomb was set to 1
if (bomb == 1) { ## Bomb 1 is SAVE
true_ct <<- append(true_ct,1)
break
} else if (bomb == 2){ ## Bomb 2 is DISCARD
## If the 'discard' bomb flag was set, then make all the digitized values NA.
xs[[idx]] <- rep(NA,x_start_idx)
true_ct <<- append(true_ct,0)
#area_sq_km[idx] <<- NA
break
} else if (bomb == 3){ ## Bomb 3 is LEGACY
next
bomb3_ct <- bomb3_ct + 1
}
}
##### Define area of glacier #####
## If the raster was not discarded...
if (!all(is.na(xs[[idx]]))){
## Create a dynamic vector for counting NA pixels
pixel_ct <- rep(NA,length(xs[[idx]]))
for (nidx in 1:length(xs[[idx]])){
## If the current data value isn't already NA...
if (!is.na(xs[[idx]][nidx])){
## ...count up the number of NA values in the given row...
na_idx <- which(is.na(rast[nidx,]))
## If pick exists within an NA range already, set the value to NA.
if (any(na_idx==xs[[idx]][nidx])){
pixel_ct[nidx] <- NA
} else {
## ...and count the number of non-NA pixels in that given row (from that column index to the beginning/end of the raster,
## depending on region selected.)
if (region == "east"){
pixel_ct[nidx] <- xs[[idx]][nidx] - length(which(na_idx <= xs[[idx]][nidx]))
} else if (region == "west"){
pixel_ct[nidx] <- xs[[idx]][nidx] - length(which(na_idx >= xs[[idx]][nidx]))
} else {
cat("Incorrect region selected! Area cannot be calculated!\n\n\n\n")
break
}
}
}
}
if (length(pixel_ct) == length(xs[[idx]])){
temp <- xs[[idx]]
xs_final[[idx]] <- pixel_ct
}
area_sq_km[idx] <- (sum(pixel_ct[!is.na(pixel_ct)])*sp_res*sp_res)/1000000
}
##### Find area of plume and/or melange #####
if (length(Pl.X) == 0){
plume_sq_km[idx] <- NA
} else {
## Points must be in clockwise order to create whole polygon for area calculation
## Solution found at: http://stackoverflow.com/questions/2855189/sort-latitude-and-longitude-coordinates-into-clockwise-ordered-quadrilateral
plume_area <- function(Pl.X,Pl.Y){
# Put input vars into new variables (so they can be manipulated later)
xx <- Pl.X
yy <- Pl.Y
# Find max y value
ymi <- which.max(yy)
# Put top point into coordinate pair