xval-noise-models: The main routine

xval-noise-models-p4.r

execute.tests <- function(n) {
  # A place-holder for the test results 
  result.df <- data.frame()
  # Initial values for snr model optimization
  param.init <- c(2, 0.4, 5e-06)
  
  # Iterate n times
  for (n in 1:n) {
    split.data()
    # Model each channel per iteration
    for (sel.channel in imgnoiser.option('RGGB.channel.labels')) {
      solve <- fit.optim.snr(sel.channel, param.init)
      wv <- test.error.weighted.var(sel.channel, solve$par)
      se <- test.error.snr(sel.channel, solve$par)
      result.df <- rbind(result.df,
                         data.frame(
                         'model' = 'optim.snr',
                         'channel' = sel.channel,
                         'w.var.error' = wv$w.var,
                         'w.mean.error' = wv$w.mean,
                         'snr.error' = se,
                         'coeff1' = solve$par[1],
                         'coeff2' = solve$par[2],
                         'coeff3' = solve$par[3]
                         ))
      
      lfit <- fit.w.robust(sel.channel)
      wv <- test.error.weighted.var(sel.channel, lfit$coefficients)
      se <- test.error.snr(sel.channel, lfit$coefficients)
      result.df <- rbind(result.df,
                         data.frame(
                         'model' = 'w.robust',
                         'channel' = sel.channel,
                         'w.var.error' = wv$w.var,
                         'w.mean.error' = wv$w.mean,
                         'snr.error' = se,
                         'coeff1' = lfit$coefficients[1],
                         'coeff2' = lfit$coefficients[2],
                         'coeff3' = lfit$coefficients[3]
                         ))
    
    }
  }
  # Summarize the results per model an channel
  result.df <-
    tbl_df(result.df) %>%
      group_by(method, channel) %>%
      summarize(var.weighted.avg = mean(var.weighted),
                mean.weighted.avg = mean(mean.weighted),
                SNR.error.avg = mean(SNR.Error),
                coeff1.avg = mean(coeff1),
                coeff2.avg = mean(coeff2),
                coeff3.avg = mean(coeff3)
                )
  # return the result
  result.df;
}