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# Get the LR tifs var data
tif.var.zero <- vvm.tif$var.df
# Rename 'mean' and 'var' columns to avoid later name colision in merging
names(tif.var.zero)[3:4] <- paste0('tif.', names(tif.var.zero)[3:4])
# Remove sample file name extension to make possible the merge by picture file name
tif.var.zero$pict <- substr(tif.var.zero$pict, 1, 8)

# Compute the linear sRGB values
vvm.rgb.lin <- convert.to.rgb(target.space = 'sRGB', use.camera.tc = FALSE, target.tc = 'linear')
# Get the sRGB linear wide var data

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# Read the selected 'good' image sample file names
sel.pics <- read.csv('sel-pict.csv')
vvm.sel <- vvm$new(has.RGGB.pattern = TRUE)

# 'Digest' the samples computing noise related statistics
vvm.sel$digest(
    file.name.from = sel.pics$pict,
    file.path      = 'ISO100/Selection/crops'
)

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hvm.all <- hvdvm$new(has.RGGB.pattern = TRUE)
hvm.all$digest(photo.conds.file = 'ISO100/crops/full-set.csv',
               crop.files.path  = 'ISO100/crops',
               min.raw          = 4,
               max.raw          = c(16379, 15774, 15774 ,16379))

# Fit a quadratic model
hvm.all$fit.model(model.name   = 'weighted',
                  model.family = 'lmrob',
                  degree       = 2,

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# Convert selected raw images to a given destinations space
# without demosaicing
convert.to.rgb <- function(target.space, 
                          use.camera.tc, 
                          target.tc, 
                          cam.coldata = imgnoiser::nikon.d7000.ISO100.colmap,
                          dest.scale = 255
) {
  
  library(imgnoiser)

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library(imgnoiser)
vvm.all <- vvm$new(has.RGGB.pattern = TRUE)
vvm.all$digest(file.name.from = '_ODL0387s4',
               file.name.to   = '_ODL1671s6',
               file.name.ext  = '.pgm',
               file.path      = 'ISO100/crops',
               min.raw        = 4, # <= Raising this limit to avoid the funny red tail
               max.raw        = c(16379, 15776, 15776 ,16379))

# Fit a quadratic, weighted, robust model

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# 1) Read and digest the channels with valid values
vvm.all <- vvm$new(has.RGGB.pattern = TRUE)
vvm.all$digest(
    file.name.from = '_ODL0387s4',
    file.name.to   = '_ODL1671s6',
    file.name.ext  = '.pgm', 
    file.path      = 'ISO100/crops',
    min.raw        = 4, 
    max.raw        = c(16379, 15774, 15774 ,16379))
    

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MenuHandler.prototype.buildMenu = function(menuObj, MaxLevels, currLevel, basePath) {
    var menu = "", menuItem, className, extraTitle;

    for (var childMenuKey in menuObj) {
        menuItem = '';
        className = '';
        extraTitle = "";

        if ( !/[^\-—–\s]/.test( menuObj[childMenuKey].menu ) )
            menuItem = '---';