anchor.diff:              train_data(:,1) = 1
               
               
  +            !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
  +            !!
  +            !!  Apply relevant transformations to the input atmospheric data
  +            !!
  +            !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
               do v=1,n_atm_variables
  -                ! does not need to be normalized if it is transformed to match training_atm anyway
                   !$omp do
                   do j=1,size(predictors%variables(v)%data,3)
                       do i=1,size(predictors%variables(v)%data,2)
                           call transform_data(options%prediction%input_Xforms(v), predictors%variables(v)%data(:,i,j), 1, ntimes)
                       enddo
  +                    ! does not need to be normalized if it is transformed to match training_atm anyway
                       if (options%prediction%transformations(v) /= kQUANTILE_MAPPING) then
                           call normalize(predictors%variables(v), j)
                       endif
  
positive.code:                         enddo
                          
                      endif
                      !$omp critical (print_lock)
                      current_completed_gridcells = current_completed_gridcells + 1
                      ! write(*,"(A,f5.1,A)", advance="NO") char(13), current_completed_gridcells/real(total_number_of_gridcells)*100.0, " %"
                      write(*,"(A,f5.1,A$)") char(13), current_completed_gridcells/real(total_number_of_gridcells)*100.0, " %"
                      !$omp end critical (print_lock)
                  enddo
  
negative.code:             endif
              
          end do
      end subroutine allocate_data
  
  end module downscaling_mod
  