;**************************************************************

load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_code.ncl"

load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_csm.ncl"

load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/contributed.ncl"

;**************************************************************

procedure set_line(lines:string,nline:integer,newlines:string) 

begin

; add line to ascci/html file

  nnewlines = dimsizes(newlines)

  if(nline+nnewlines-1.ge.dimsizes(lines))

    print("set_line: bad index, not setting anything.") 

    return

  end if 

  lines(nline:nline+nnewlines-1) = newlines

;  print ("lines = " + lines(nline:nline+nnewlines-1))

  nline = nline + nnewlines

  return 

end

;**************************************************************

; Main code.

begin

  plot_type     = "ps"

  plot_type_new = "png"

;-----------------------------------------------------

; edit table.html of current model for movel1_vs_model2

  if (isvar("compare")) then

     html_name2 = compare+"/table.html"  

     html_new2  = html_name2 +".new"

  end if

;------------------------------------------------------

; edit table.html for current model

  html_name = model_name+"/table.html"  

  html_new  = html_name +".new"

;------------------------------------------------------

; read data: model       

  fm = addfile(dirm+film10,"r")      

  laimod = fm->TLAI

  delete (fm)

  dsizes = dimsizes(laimod)

  ntime  = dsizes(0)

  nlat   = dsizes(1)

  nlon   = dsizes(2)

;-----------------------------------

; get landfrac data

 film_l   = "lnd_"+ model_grid + ".nc"

 fm_l     = addfile (dirs+film_l,"r")  

 landfrac = fm_l->landfrac

 delete (fm_l)

;----------------------------------

; read biome data: model

  biome_name_mod = "Model PFT Class"

  film_c   = "class_pft_"+model_grid+".nc"

  fm_c     = addfile(dirs+film_c,"r") 

  classmod = fm_c->CLASS_PFT               

  delete (fm_c)

; model data has 17 land-type classes

  nclass_mod = 17

;----------------------------------------------------------

; read data: ob       

;----------------------------------

; read biome data: observed

  biome_name_ob = "MODIS LandCover"

  dir_c = diro + "lai/"

  filo_c = "land_class_"+model_grid+".nc"

  fo = addfile(dir_c+filo_c,"r")

  classob = tofloat(fo->LAND_CLASS)               

  delete (fo)

; input observed data has 20 land-type classes

  nclass_ob = 20

;---------------------------------

; read lai data: observed

  ;ob_name = "MODIS MOD 15A2 2000-2005"

  ob_name = "MODIS MOD 15A2 2000-2004"

  dir_l = diro + "lai/"

  ;filo = "LAI_2000-2005_MONS_"+model_grid+".nc"

  filo = "LAI_2000-2004_MONS_"+model_grid+".nc"

  fo = addfile(dir_l+filo,"r")                

  laiob = fo->LAI

  delete (fo)

;-------------------------------------------------

; take into account landfrac

  laimod = laimod * conform(laimod,landfrac,(/1,2/))

  laiob  = laiob  * conform(laiob ,landfrac,(/1,2/))

  delete (landfrac)

;************************************************

; global res

;************************************************

  resg                      = True             ; Use plot options

  resg@cnFillOn             = True             ; Turn on color fill

  resg@gsnSpreadColors      = True             ; use full colormap

  resg@cnLinesOn            = False            ; Turn off contourn lines

  resg@mpFillOn             = False            ; Turn off map fill

  resg@cnLevelSelectionMode = "ManualLevels"   ; Manual contour invtervals

;************************************************

; plot global biome class: (1) observed

;************************************************

  resg@cnMinLevelValF       = 1.              ; Min level

  resg@cnMaxLevelValF       = 19.             ; Max level

  resg@cnLevelSpacingF      = 1.              ; interval

  classob@_FillValue = 1.e+36

  classob = where(classob.eq.0,classob@_FillValue,classob)

  plot_name = "global_class_ob"

  title     = biome_name_ob

  resg@tiMainString  = title

  wks = gsn_open_wks (plot_type,plot_name)   ; open workstation

  gsn_define_colormap(wks,"gui_default")     ; choose colormap

  plot = gsn_csm_contour_map_ce(wks,classob,resg)   

  delete (wks)

  system("convert "+plot_name+"."+plot_type+" "+plot_name+"."+plot_type_new+";"+ \

         "rm "+plot_name+"."+plot_type)

;************************************************

; plot global biome class: (2) model

;************************************************

  resg@cnMinLevelValF       = 0.              ; Min level

  resg@cnMaxLevelValF       = 16.             ; Max level

  resg@cnLevelSpacingF      = 1.              ; interval

  plot_name = "global_class_model"

  title     = biome_name_mod

  resg@tiMainString  = title

  wks = gsn_open_wks (plot_type,plot_name)   ; open workstation

  gsn_define_colormap(wks,"gui_default")     ; choose colormap

  plot = gsn_csm_contour_map_ce(wks,classmod,resg)   

  delete (wks)

  system("convert "+plot_name+"."+plot_type+" "+plot_name+"."+plot_type_new+";"+ \

         "rm "+plot_name+"."+plot_type)

;*******************************************************************

; for html table : all 3 components (Mean, Max, Phase)

;*******************************************************************

; column (not including header column)

  component = (/"Mean","Max","Phase"/)

  col_head  = (/"observed",model_name,"M_score" \

               ,"observed",model_name,"M_score" \

               ,"observed",model_name,"M_score" \

               /)

  n_comp = dimsizes(component) 

  ncol   = dimsizes(col_head )

; row (not including header row)

;----------------------------------------------------

; using model biome class:  

  row_head  = (/"Not Vegetated" \

               ,"Needleleaf Evergreen Temperate Tree" \

               ,"Needleleaf Evergreen Boreal Tree" \

;              ,"Needleleaf Deciduous Boreal Tree" \

               ,"Broadleaf Evergreen Tropical Tree" \

               ,"Broadleaf Evergreen Temperate Tree" \

               ,"Broadleaf Deciduous Tropical Tree" \

               ,"Broadleaf Deciduous Temperate Tree" \

;              ,"Broadleaf Deciduous Boreal Tree" \

;              ,"Broadleaf Evergreen Shrub" \

               ,"Broadleaf Deciduous Temperate Shrub" \

               ,"Broadleaf Deciduous Boreal Shrub" \

               ,"C3 Arctic Grass" \

               ,"C3 Non-Arctic Grass" \

               ,"C4 Grass" \

               ,"Corn" \

;              ,"Wheat" \                      

               ,"All Biomes" \                

               /)  

  nrow = dimsizes(row_head)                  

; arrays to be passed to table. 

  text = new ((/nrow, ncol/),string ) 

; total M_score

  M_total = 0.

;********************************************************************

; use land-type class to bin the data in equally spaced ranges

;********************************************************************

; using model biome class

  nclass = nclass_mod

  range  = fspan(0,nclass,nclass+1)

; Use this range information to grab all the values in a

; particular range, and then take an average.

  nx = dimsizes(range) - 1

; for 2 data: model and observed

  data_n = 2

; using model biome class

  base = ndtooned(classmod)

; output

  yvalues = new((/data_n,nx/),float)

  count   = new((/data_n,nx/),float)

;************************************************************************

; go through all components

;************************************************************************

 do m = 0,n_comp-1

;===================

; get data:

;===================

; (A) Mean

  if (m .eq. 0) then

     data_ob  = dim_avg_Wrap(laiob (lat|:,lon|:,time|:))

     data_mod = dim_avg_Wrap(laimod(lat|:,lon|:,time|:))

  end if

; (B) Max

  if (m .eq. 1) then

;    observed  

     data_ob = laiob(0,:,:)

     data_ob@long_name = "Leaf Area Index Max"

     do j = 0,nlat-1

     do i = 0,nlon-1

        data_ob(j,i) = max(laiob(:,j,i))

     end do

     end do          

;    model  

     data_mod = laimod(0,:,:)

     data_mod@long_name = "Leaf Area Index Max"

     do j = 0,nlat-1

     do i = 0,nlon-1

        data_mod(j,i) = max(laimod(:,j,i))

     end do

     end do

  end if

; (C) phase

  if (m .eq. 2) then  

;    observed

     data_ob = laiob(0,:,:)

     data_ob@long_name = "Leaf Area Index Max Month"

     do j = 0,nlat-1

     do i = 0,nlon-1 

        data_ob(j,i) = maxind(laiob(:,j,i)) + 1

     end do

     end do          

;    model

     data_mod = laimod(0,:,:)

     data_mod@long_name = "Leaf Area Index Max Month"

     do j = 0,nlat-1

     do i = 0,nlon-1 

        data_mod(j,i) = maxind(laimod(:,j,i)) + 1

     end do

     end do

  end if

;==============================

; put data into bins

;==============================

; Loop through each range, using base

  do i=0,nx-1

     if (i.ne.(nx-1)) then

        idx = ind((base.ge.range(i)).and.(base.lt.range(i+1)))

     else

        idx = ind(base.ge.range(i))

     end if

;    loop through each dataset

     do n = 0,data_n-1

        if (n .eq. 0) then

           data = ndtooned(data_ob)

        end if

        if (n .eq. 1) then

           data = ndtooned(data_mod)

        end if

;       Calculate average 

        if (.not.any(ismissing(idx))) then

           yvalues(n,i) = avg(data(idx))

           count(n,i)   = dimsizes(idx)

        else

           yvalues(n,i) = yvalues@_FillValue

           count(n,i)   = 0

        end if

;#############################################################

; using model biome class:

;

;     set the following 4 classes to _FillValue:

;     (3)Needleleaf Deciduous Boreal Tree,

;     (8)Broadleaf Deciduous Boreal Tree,

;     (9)Broadleaf Evergreen Shrub,

;     (16)Wheat

      if (i.eq.3 .or. i.eq.8 .or. i.eq.9 .or. i.eq.16) then

         yvalues(n,i) = yvalues@_FillValue

         count(n,i)   = 0

      end if

;############################################################# 

      delete(data)

    end do                 ; n-loop

    delete(idx)

  end do                   ; i-loop

;=====================================

; compute correlation coef and M score 

;=====================================

  score_max = 5.0

  u       = yvalues(0,:)

  v       = yvalues(1,:)

  u_count = count(0,:)

  v_count = count(1,:)

  good = ind(.not.ismissing(u) .and. .not.ismissing(v))

  uu = u(good)

  vv = v(good)

  uu_count = u_count(good)

  vv_count = v_count(good)

; compute correlation coef

  cc = esccr(uu,vv,0)

  if (n .eq. 2) then

     bias   = avg(abs(vv-uu))

     bias   = where((bias.gt. 6.),12.-bias,bias)

     Mscore = ((6. - bias)/6.)*score_max

  else

     bias  = sum(abs(vv-uu)/abs(vv+uu))

     Mscore = (1.- (bias/dimsizes(uu)))*score_max

  end if

  M_score = sprintf("%.2f", Mscore)

; compute M_total

  M_total = M_total + Mscore

;================================

; output M_score to score sheet

;===============================

  if (isvar("compare")) then

     system("sed -e '1,/M_lai_"+component(m)+"/s/M_lai_"+component(m)+"/"+M_score+"/' "+html_name2+" > "+html_new2+";"+ \

            "mv -f "+html_new2+" "+html_name2)

  end if

  system("sed s#M_lai_"+component(m)+"#"+M_score+"# "+html_name+" > "+html_new+";"+ \

         "mv -f "+html_new+" "+html_name)

;==============================

; output M_score to html table

;==============================

  n = m*3

  do i=0,nrow-2

     text(i,n)   = sprintf("%.1f",uu(i))

     text(i,n+1) = sprintf("%.1f",vv(i))

     text(i,n+2) = "-"

  end do

  text(nrow-1,n)   = sprintf("%.1f",sum(uu*uu_count)/sum(uu_count))

  text(nrow-1,n+1) = sprintf("%.1f",sum(vv*vv_count)/sum(vv_count))

  text(nrow-1,n+2) = M_score

  delete (u)

  delete (v)

  delete (uu)

  delete (vv)

  delete (u_count)

  delete (v_count)

  delete (uu_count)

  delete (vv_count)

  delete (good)

;======================================== 

; global res changes for each component

;========================================

  delta = 0.00001  

  if (m .eq. 0) then

     resg@cnMinLevelValF       = 0.             

     resg@cnMaxLevelValF       = 10.             

     resg@cnLevelSpacingF      = 1.

     data_ob = where(ismissing(data_ob).and.(ismissing(data_mod).or.(data_mod.lt.delta)),0.,data_ob)

  end if

  if (m .eq. 1) then

     resg@cnMinLevelValF       = 0.             

     resg@cnMaxLevelValF       = 10.             

     resg@cnLevelSpacingF      = 1.

     data_ob = where(ismissing(data_ob).and.(ismissing(data_mod).or.(data_mod.lt.delta)),0.,data_ob)

  end if

  if (m .eq. 2) then

     resg@cnMinLevelValF       = 1.             

     resg@cnMaxLevelValF       = 12.             

     resg@cnLevelSpacingF      = 1.

     data_mod = where(ismissing(data_ob).or.(data_mod.lt.delta),data_mod@_FillValue,data_mod)

     data_ob = where(ismissing(data_ob).and.(ismissing(data_mod).or.(data_mod.lt.delta)),0.,data_ob)

  end if

;=========================

; global contour : ob

;=========================

  plot_name = "global_"+component(m)+"_ob"

  title     = ob_name

  resg@tiMainString  = title

  wks = gsn_open_wks (plot_type,plot_name)   ; open workstation

  gsn_define_colormap(wks,"gui_default")     ; choose colormap

  plot = gsn_csm_contour_map_ce(wks,data_ob,resg)   

  delete (wks)

  delete (plot)

  system("convert "+plot_name+"."+plot_type+" "+plot_name+"."+plot_type_new+";"+ \

         "rm "+plot_name+"."+plot_type)

;============================

; global contour : model

;============================

  plot_name = "global_"+component(m)+"_model"  

  title     = "Model " + model_name

  resg@tiMainString  = title

  wks = gsn_open_wks (plot_type,plot_name)

  gsn_define_colormap(wks,"gui_default")     

  plot = gsn_csm_contour_map_ce(wks,data_mod,resg)   

  delete (wks)

  delete (plot)

  system("convert "+plot_name+"."+plot_type+" "+plot_name+"."+plot_type_new+";"+ \

         "rm "+plot_name+"."+plot_type)

;================================

; global contour: model vs ob

;================================

  plot_name = "global_"+component(m)+"_model_vs_ob"

  wks = gsn_open_wks (plot_type,plot_name)   

  gsn_define_colormap(wks,"gui_default")     

  plot=new(3,graphic)                        ; create graphic array

  resg@gsnFrame             = False          ; Do not draw plot 

  resg@gsnDraw              = False          ; Do not advance frame

; plot correlation coef

  gRes               = True

  gRes@txFontHeightF = 0.02

  gRes@txAngleF      = 90

  correlation_text = "(correlation coef = "+sprintf("%.2f", cc)+")"

  gsn_text_ndc(wks,correlation_text,0.20,0.50,gRes)

; plot ob

  title     = ob_name

  resg@tiMainString  = title

  plot(0) = gsn_csm_contour_map_ce(wks,data_ob,resg)       

; plot model

  title     = "Model "+ model_name

  resg@tiMainString  = title

  plot(1) = gsn_csm_contour_map_ce(wks,data_mod,resg) 

; plot model-ob

  if (m .eq. 0) then

     resg@cnMinLevelValF  = -2.           

     resg@cnMaxLevelValF  =  2.            

     resg@cnLevelSpacingF =  0.4

  end if

  if (m .eq. 1) then

     resg@cnMinLevelValF  = -6.           

     resg@cnMaxLevelValF  =  6.            

     resg@cnLevelSpacingF =  1.

  end if

  if (m .eq. 2) then

     resg@cnMinLevelValF  = -6.           

     resg@cnMaxLevelValF  =  6.            

     resg@cnLevelSpacingF =  1.

  end if

  zz = data_mod

  zz = data_mod - data_ob

  title = "Model_"+model_name+" - Observed"

  resg@tiMainString    = title

  plot(2) = gsn_csm_contour_map_ce(wks,zz,resg) 

; plot panel

  pres                            = True        ; panel plot mods desired

  pres@gsnMaximize                = True        ; fill the page

  gsn_panel(wks,plot,(/3,1/),pres)              ; create panel plot

  delete (wks)

  delete (plot)

  system("convert "+plot_name+"."+plot_type+" "+plot_name+"."+plot_type_new+";"+ \

         "rm "+plot_name+"."+plot_type)

  delete (data_ob)

  delete (data_mod)

  resg@gsnFrame             = True          ; Do advance frame 

  resg@gsnDraw              = True          ; Do draw plot

 end do    ; m-loop

;**************************************************

; html table

;**************************************************

  output_html = "table_model_vs_ob.html"

  header_text = "<H1>LAI: Model "+model_name+" vs. MODIS observations</H1>" 

  header = (/"<HTML>" \

            ,"<HEAD>" \

            ,"<TITLE>CLAMP metrics</TITLE>" \

            ,"</HEAD>" \

            ,header_text \

            /) 

  footer = "</HTML>"

  table_header = (/ \

        "<table border=1 cellspacing=0 cellpadding=3 width=100%>" \

       ,"<tr>" \

       ,"   <th bgcolor=DDDDDD rowspan=2>Biome Class</th>" \

       ,"   <th bgcolor=DDDDDD colspan=3>"+component(0)+" (m2/m2)</th>" \

       ,"   <th bgcolor=DDDDDD colspan=3>"+component(1)+" (m2/m2)</th>" \

       ,"   <th bgcolor=DDDDDD colspan=3>"+component(2)+" (months)</th>" \

       ,"   <th bgcolor=DDDDDD rowspan=2>Annual Plot</th>" \

       ,"</tr>" \

       ,"<tr>" \

       ,"   <th bgcolor=DDDDDD >observed</th>" \

       ,"   <th bgcolor=DDDDDD >"+model_name+"</th>" \

       ,"   <th bgcolor=DDDDDD >M_score</th>" \

       ,"   <th bgcolor=DDDDDD >observed</th>" \

       ,"   <th bgcolor=DDDDDD >"+model_name+"</th>" \

       ,"   <th bgcolor=DDDDDD >M_score</th>" \

       ,"   <th bgcolor=DDDDDD >observed</th>" \

       ,"   <th bgcolor=DDDDDD >"+model_name+"</th>" \

       ,"   <th bgcolor=DDDDDD >M_score</th>" \

       ,"</tr>" \

       /)

  table_footer = "</table>"

  row_header = "<tr>"

  row_footer = "</tr>"

  lines = new(50000,string)

  nline = 0

  set_line(lines,nline,header)

  set_line(lines,nline,table_header)

;-----------------------------------------------

;row of table

  do n = 0,nrow-1

     set_line(lines,nline,row_header)

     txt1  = row_head(n)

     txt2  = text(n,0)

     txt3  = text(n,1)

     txt4  = text(n,2)

     txt5  = text(n,3)

     txt6  = text(n,4)

     txt7  = text(n,5)

     txt8  = text(n,6)

     txt9  = text(n,7)

     txt10 = text(n,8)

     txt11 = "<a href=./annual_biome_"+n+".png>model_vs_ob</a>" 

     set_line(lines,nline,"<th>"+txt1+"</th>")

     set_line(lines,nline,"<th>"+txt2+"</th>")

     set_line(lines,nline,"<th>"+txt3+"</th>")

     set_line(lines,nline,"<th>"+txt4+"</th>")

     set_line(lines,nline,"<th>"+txt5+"</th>")

     set_line(lines,nline,"<th>"+txt6+"</th>")

     set_line(lines,nline,"<th>"+txt7+"</th>")

     set_line(lines,nline,"<th>"+txt8+"</th>")

     set_line(lines,nline,"<th>"+txt9+"</th>")

     set_line(lines,nline,"<th>"+txt10+"</th>")

     set_line(lines,nline,"<th>"+txt11+"</th>")

     set_line(lines,nline,row_footer)

  end do

;-----------------------------------------------

  set_line(lines,nline,table_footer)

  set_line(lines,nline,footer) 

; Now write to an HTML file

  idx = ind(.not.ismissing(lines))

  if(.not.any(ismissing(idx))) then

    asciiwrite(output_html,lines(idx))

  else

   print ("error?")

  end if

  delete (yvalues)

  delete (count)

  delete (idx)

;************************************************************************

; go through all ntime

;************************************************************************

; for 2 data: model and observed

  data_n = 2

; using model biome class

  base = ndtooned(classmod)

; output

  yvalues = new((/data_n,nx,ntime/),float)

;==============================

; put data into bins

;==============================

; Loop through each range, using base

  do i=0,nx-1

     if (i.ne.(nx-1)) then

        idx = ind((base.ge.range(i)).and.(base.lt.range(i+1)))

     else

        idx = ind(base.ge.range(i))

     end if

;    loop through each dataset

     do n = 0,data_n-1

        do m = 0,ntime-1

        if (n .eq. 0) then

           data = ndtooned(laiob (m,:,:))

        end if

        if (n .eq. 1) then

           data = ndtooned(laimod(m,:,:))

        end if

;       Calculate average 

        if (.not.any(ismissing(idx))) then

           yvalues(n,i,m) = avg(data(idx))

        else

           yvalues(n,i,m) = yvalues@_FillValue

        end if

;#############################################################

; using model biome class:

;

;     set the following 4 classes to _FillValue:

;     (3)Needleleaf Deciduous Boreal Tree,

;     (8)Broadleaf Deciduous Boreal Tree,

;     (9)Broadleaf Evergreen Shrub,

;     (16)Wheat

      if (i.eq.3 .or. i.eq.8 .or. i.eq.9 .or. i.eq.16) then

         yvalues(n,i,m) = yvalues@_FillValue

      end if

;############################################################# 

      end do               ; m-loop

      delete(data)

    end do                 ; n-loop

    delete(idx)

  end do                   ; i-loop

  good = ind(.not.ismissing(yvalues(0,:,0)))  

  n_biome = dimsizes(good)

;----------------------------------------------------------------

; data for tseries plot

  yvalues_g = new((/data_n,n_biome,ntime/),float)

  yvalues_g@units = ""

  yvalues_g = yvalues(:,good,:)

  delete (good)

;*******************************************************************

; res for line plot

;*******************************************************************

; for x-axis in xyplot

  mon = ispan(1,12,1)

  mon@long_name = "month"

  res                   = True                      ; plot mods desired

  res@xyLineThicknesses = (/2.0,2.0,2.0/)           ; make 2nd lines thicker

  res@xyLineColors      = (/"blue","red"/)         ; change line color

; res@tiMainFontHeightF = 0.025                     ; size of title 

; Add a boxed legend using the more simple method

  res@pmLegendDisplayMode    = "Always"

; res@pmLegendWidthF         = 0.1

  res@pmLegendWidthF         = 0.08

  res@pmLegendHeightF        = 0.06

; res@pmLegendOrthogonalPosF = -1.17

; res@pmLegendOrthogonalPosF = -1.00  ;(downward)

  res@pmLegendOrthogonalPosF = -0.30  ;(downward)

; res@pmLegendParallelPosF   =  0.18

  res@pmLegendParallelPosF   =  0.23  ;(rightward)

; res@lgPerimOn             = False

  res@lgLabelFontHeightF     = 0.015

  res@xyExplicitLegendLabels = (/"observed",model_name/)

;************************************************************

  plot_data = new((/2,ntime/),float)

  plot_data@long_name = "Leaf Area Index"

;----------------------------------------------

; time series plot : per biome

  do m = 0, n_biome-1

     plot_name = "annual_biome_"+ m

     wks = gsn_open_wks (plot_type,plot_name) 

     title = "LAI : "+ row_head(m)

     res@tiMainString = title

     plot_data(0,:) = yvalues_g(0,m,:)

     plot_data(1,:) = yvalues_g(1,m,:)

     plot = gsn_csm_xy(wks,mon,plot_data,res)

     delete (wks)

     delete (plot)

     system("convert "+plot_name+"."+plot_type+" "+plot_name+"."+plot_type_new+";"+ \

            "rm "+plot_name+"."+plot_type)

  end do

;--------------------------------------------

; time series plot: all biome

     plot_name = "annual_biome_"+ n_biome

     wks = gsn_open_wks (plot_type,plot_name)   

     title = "LAI : "+ row_head(n_biome)

     res@tiMainString = title

     do k = 0,ntime-1

        plot_data(0,k) = avg(yvalues_g(0,:,k))

        plot_data(1,k) = avg(yvalues_g(1,:,k))

     end do

     plot = gsn_csm_xy(wks,mon,plot_data,res)

     delete (wks)

     delete (plot)

     system("convert "+plot_name+"."+plot_type+" "+plot_name+"."+plot_type_new+";"+ \

            "rm "+plot_name+"."+plot_type)

  delete (plot_data)

;***************************************************************************

; write total score to file

;***************************************************************************

  asciiwrite("M_save.lai", M_total)

;***************************************************************************

; output plots

;***************************************************************************

  output_dir = model_name+"/lai"

  system("mv *.png *.html " + output_dir) 

;***************************************************************************

end