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1 ;******************************************************** |
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2 ; using model biome |
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3 ; |
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4 ; required command line input parameters: |
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5 ; ncl 'model_name="10cn" model_grid="T42" dirm="/.../ film="..."' 01.npp.ncl |
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6 ; |
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7 ;************************************************************** |
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8 load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_code.ncl" |
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9 load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_csm.ncl" |
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10 load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/contributed.ncl" |
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11 ;************************************************************** |
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12 procedure set_line(lines:string,nline:integer,newlines:string) |
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13 begin |
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14 ; add line to ascci/html file |
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15 |
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16 nnewlines = dimsizes(newlines) |
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17 if(nline+nnewlines-1.ge.dimsizes(lines)) |
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18 print("set_line: bad index, not setting anything.") |
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19 return |
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20 end if |
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21 lines(nline:nline+nnewlines-1) = newlines |
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22 ; print ("lines = " + lines(nline:nline+nnewlines-1)) |
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23 nline = nline + nnewlines |
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24 return |
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25 end |
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26 ;************************************************************** |
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27 ; Main code. |
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28 begin |
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29 |
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30 plot_type = "ps" |
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31 plot_type_new = "png" |
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32 |
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33 ;************************************************ |
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34 ; read data: model |
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35 ;************************************************ |
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36 co2_i = 283.1878 |
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37 co2_f = 364.1252 |
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38 |
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39 model_grid = "T42" |
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40 |
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41 ;model_name_i = "i01.07cn" |
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42 ;model_name_f = "i01.10cn" |
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43 |
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44 model_name_i = "i01.07casa" |
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45 model_name_f = "i01.10casa" |
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46 |
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47 model_name = model_name_f |
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48 |
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49 dirm = "/fis/cgd/cseg/people/jeff/clamp_data/model/" |
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50 film_i = model_name_i + "_1990-2004_ANN_climo.nc" |
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51 film_f = model_name_f + "_1990-2004_ANN_climo.nc" |
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52 |
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53 fm_i = addfile (dirm+film_i,"r") |
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54 fm_f = addfile (dirm+film_f,"r") |
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55 |
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56 xm = fm_f->lon |
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57 ym = fm_f->lat |
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58 |
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59 npp_i = fm_i->NPP |
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60 npp_f = fm_f->NPP |
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61 |
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62 delete (fm_i) |
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63 delete (fm_f) |
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64 |
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65 ;Units for these variables are: |
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66 ;npp_i: g C/m^2/s |
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67 |
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68 nsec_per_year = 60*60*24*365 |
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69 |
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70 npp_i = npp_i * nsec_per_year |
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71 npp_f = npp_f * nsec_per_year |
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72 |
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73 ;=================================================== |
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74 ; read data: observed at stations |
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75 ;=================================================== |
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76 |
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77 station = (/"DukeFACE" \ |
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78 ,"AspenFACE" \ |
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79 ,"ORNL-FACE" \ |
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80 ,"POP-EUROFACE" \ |
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81 /) |
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82 |
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83 lat_ob = (/ 35.58, 45.40, 35.54, 42.22/) |
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84 lon_ob = (/-79.05, -89.37, -84.20, 11.48/) |
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85 lon_ob = where(lon_ob.lt.0.,lon_ob+360.,lon_ob) |
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86 ;print (lon_ob) |
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87 |
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88 n_sta = dimsizes(station) |
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89 beta_4_ob = new((/n_sta/),float) |
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90 beta_4_ob = 0.60 |
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91 |
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92 ;=================================================== |
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93 ; get model data at station |
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94 ;=================================================== |
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95 |
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96 npp_i_4 =linint2_points(xm,ym,npp_i,True,lon_ob,lat_ob,0) |
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97 |
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98 npp_f_4 =linint2_points(xm,ym,npp_f,True,lon_ob,lat_ob,0) |
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99 |
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100 ;print (npp_i_4) |
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101 ;print (npp_f_4) |
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102 |
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103 ;============================ |
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104 ;compute beta_4 |
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105 ;============================ |
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106 |
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107 beta_4 = new((/n_sta/),float) |
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108 |
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109 beta_4 = ((npp_f_4/npp_i_4) - 1.)/log(co2_f/co2_i) |
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110 |
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111 beta_4_avg = avg(beta_4) |
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112 |
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113 ;print (beta_4) |
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114 ;print (beta_4_avg) |
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115 |
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116 ;M_beta = abs((beta_4_avg/beta_4_ob) - 1.)* 3. |
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117 |
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118 bias = sum(abs(beta_4-beta_4_ob)/(abs(beta_4)+abs(beta_4_ob))) |
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119 M_beta = (1. - (bias/n_sta))*3. |
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120 |
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121 print (M_beta) |
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122 |
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123 ;========================= |
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124 ; for html table - station |
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125 ;========================= |
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126 |
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127 output_html = "table_station.html" |
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128 |
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129 ; column (not including header column) |
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130 |
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131 col_head = (/"Latitude","Longitude","CO2_i","CO2_f","NPP_i","NPP_f","Beta_model","Beta_ob"/) |
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132 |
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133 ncol = dimsizes(col_head) |
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134 |
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135 ; row (not including header row) |
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136 row_head = (/"DukeFACE" \ |
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137 ,"AspenFACE" \ |
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138 ,"ORNL-FACE" \ |
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139 ,"POP-EUROFACE" \ |
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140 ,"All Station" \ |
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141 /) |
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142 nrow = dimsizes(row_head) |
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143 |
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144 ; arrays to be passed to table. |
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145 text4 = new ((/nrow, ncol/),string ) |
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146 |
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147 do i=0,nrow-2 |
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148 text4(i,0) = sprintf("%.1f",lat_ob(i)) |
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149 text4(i,1) = sprintf("%.1f",lon_ob(i)) |
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150 text4(i,2) = sprintf("%.1f",co2_i) |
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151 text4(i,3) = sprintf("%.1f",co2_f) |
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152 text4(i,4) = sprintf("%.1f",npp_i_4(0,i)) |
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153 text4(i,5) = sprintf("%.1f",npp_f_4(0,i)) |
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154 text4(i,6) = sprintf("%.2f",beta_4(i)) |
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155 text4(i,7) = "-" |
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156 end do |
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157 text4(nrow-1,0) = "-" |
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158 text4(nrow-1,1) = "-" |
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159 text4(nrow-1,2) = "-" |
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160 text4(nrow-1,3) = "-" |
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161 text4(nrow-1,4) = "-" |
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162 text4(nrow-1,5) = "-" |
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163 text4(nrow-1,6) = sprintf("%.2f",beta_4_avg) |
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164 text4(nrow-1,7) = sprintf("%.2f",avg(beta_4_ob)) |
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165 |
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166 ;----------- |
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167 ; html table |
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168 ;----------- |
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169 |
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170 header_text = "<H1>Beta Factor: Model "+model_name+"</H1>" |
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171 |
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172 header = (/"<HTML>" \ |
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173 ,"<HEAD>" \ |
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174 ,"<TITLE>CLAMP metrics</TITLE>" \ |
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175 ,"</HEAD>" \ |
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176 ,header_text \ |
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177 /) |
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178 footer = "</HTML>" |
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179 |
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180 table_header = (/ \ |
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181 "<table border=1 cellspacing=0 cellpadding=3 width=80%>" \ |
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182 ,"<tr>" \ |
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183 ," <th bgcolor=DDDDDD >Station</th>" \ |
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184 ," <th bgcolor=DDDDDD >"+col_head(0)+"</th>" \ |
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185 ," <th bgcolor=DDDDDD >"+col_head(1)+"</th>" \ |
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186 ," <th bgcolor=DDDDDD >"+col_head(2)+"</th>" \ |
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187 ," <th bgcolor=DDDDDD >"+col_head(3)+"</th>" \ |
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188 ," <th bgcolor=DDDDDD >"+col_head(4)+"</th>" \ |
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189 ," <th bgcolor=DDDDDD >"+col_head(5)+"</th>" \ |
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190 ," <th bgcolor=DDDDDD >"+col_head(6)+"</th>" \ |
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191 ," <th bgcolor=DDDDDD >"+col_head(7)+"</th>" \ |
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192 ,"</tr>" \ |
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193 /) |
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194 table_footer = "</table>" |
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195 row_header = "<tr>" |
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196 row_footer = "</tr>" |
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197 |
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198 lines = new(50000,string) |
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199 nline = 0 |
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200 |
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201 set_line(lines,nline,header) |
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202 set_line(lines,nline,table_header) |
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203 ;----------------------------------------------- |
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204 ;row of table |
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205 |
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206 do n = 0,nrow-1 |
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207 set_line(lines,nline,row_header) |
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208 |
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209 txt1 = row_head(n) |
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210 txt2 = text4(n,0) |
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211 txt3 = text4(n,1) |
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212 txt4 = text4(n,2) |
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213 txt5 = text4(n,3) |
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214 txt6 = text4(n,4) |
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215 txt7 = text4(n,5) |
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216 txt8 = text4(n,6) |
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217 txt9 = text4(n,7) |
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218 |
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219 set_line(lines,nline,"<th>"+txt1+"</th>") |
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220 set_line(lines,nline,"<th>"+txt2+"</th>") |
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221 set_line(lines,nline,"<th>"+txt3+"</th>") |
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222 set_line(lines,nline,"<th>"+txt4+"</th>") |
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223 set_line(lines,nline,"<th>"+txt5+"</th>") |
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224 set_line(lines,nline,"<th>"+txt6+"</th>") |
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225 set_line(lines,nline,"<th>"+txt7+"</th>") |
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226 set_line(lines,nline,"<th>"+txt8+"</th>") |
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227 set_line(lines,nline,"<th>"+txt9+"</th>") |
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228 |
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229 set_line(lines,nline,row_footer) |
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230 end do |
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231 ;----------------------------------------------- |
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232 set_line(lines,nline,table_footer) |
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233 set_line(lines,nline,footer) |
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234 |
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235 ; Now write to an HTML file. |
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236 idx = ind(.not.ismissing(lines)) |
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237 if(.not.any(ismissing(idx))) then |
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238 asciiwrite(output_html,lines(idx)) |
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239 else |
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240 print ("error?") |
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241 end if |
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242 |
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243 delete (col_head) |
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244 delete (row_head) |
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245 delete (text4) |
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246 delete (table_header) |
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247 delete (idx) |
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248 |
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249 ;------------------------------------------------ |
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250 ; read biome data: model |
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251 |
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252 biome_name_mod = "Model PFT Class" |
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253 |
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254 dirm = "/fis/cgd/cseg/people/jeff/clamp_data/model/" |
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255 film = "class_pft_"+model_grid+".nc" |
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256 |
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257 fm = addfile(dirm+film,"r") |
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258 |
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259 classmod = fm->CLASS_PFT |
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260 |
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261 delete (fm) |
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262 |
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263 ; model data has 17 land-type classes |
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264 |
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265 nclass_mod = 17 |
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266 |
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267 ;------------------------------------------------ |
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268 ; read biome data: observed |
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269 |
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270 biome_name_ob = "MODIS LandCover" |
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271 |
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272 diro = "/fis/cgd/cseg/people/jeff/clamp_data/lai/ob/" |
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273 filo = "land_class_"+model_grid+".nc" |
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274 |
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275 fo = addfile(diro+filo,"r") |
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276 |
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277 classob = tofloat(fo->LAND_CLASS) |
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278 |
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279 delete (fo) |
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280 |
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281 ; input observed data has 20 land-type classes |
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282 |
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283 nclass_ob = 20 |
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284 |
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285 ;******************************************************************** |
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286 ; use land-type class to bin the data in equally spaced ranges |
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287 ;******************************************************************** |
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288 |
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289 ; using observed biome class |
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290 ; nclass = nclass_ob |
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291 ; using model biome class |
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292 nclass = nclass_mod |
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293 |
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294 nclassn = nclass + 1 |
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295 range = fspan(0,nclassn-1,nclassn) |
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296 ; print (range) |
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297 |
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298 ; Use this range information to grab all the values in a |
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299 ; particular range, and then take an average. |
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300 |
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301 nr = dimsizes(range) |
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302 nx = nr-1 |
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303 xvalues = new((/2,nx/),float) |
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304 xvalues(0,:) = range(0:nr-2) + (range(1:)-range(0:nr-2))/2. |
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305 dx = xvalues(0,1) - xvalues(0,0) ; range width |
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306 dx4 = dx/4 ; 1/4 of the range |
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307 xvalues(1,:) = xvalues(0,:) - dx/5. |
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308 |
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309 ;============================== |
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310 ; put data into bins |
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311 ;============================== |
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312 |
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313 ; using observed biome class |
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314 ; base_1D = ndtooned(classob) |
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315 ; using model biome class |
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316 base_1D = ndtooned(classmod) |
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317 |
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318 data1_1D = ndtooned(npp_i) |
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319 data2_1D = ndtooned(npp_f) |
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320 |
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321 ; output |
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322 |
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323 yvalues = new((/2,nx/),float) |
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324 count = new((/2,nx/),float) |
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325 |
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326 do nd=0,1 |
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327 |
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328 ; See if we are doing data1 (nd=0) or data2 (nd=1). |
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329 |
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330 base = base_1D |
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331 |
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332 if(nd.eq.0) then |
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333 data = data1_1D |
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334 else |
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335 data = data2_1D |
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336 end if |
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337 |
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338 ; Loop through each range, using base. |
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339 |
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340 do i=0,nr-2 |
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341 if (i.ne.(nr-2)) then |
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342 ; print("") |
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343 ; print("In range ["+range(i)+","+range(i+1)+")") |
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344 idx = ind((base.ge.range(i)).and.(base.lt.range(i+1))) |
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345 else |
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346 ; print("") |
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347 ; print("In range ["+range(i)+",)") |
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348 idx = ind(base.ge.range(i)) |
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349 end if |
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350 |
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351 ; Calculate average |
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352 |
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353 if(.not.any(ismissing(idx))) then |
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354 yvalues(nd,i) = avg(data(idx)) |
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355 count(nd,i) = dimsizes(idx) |
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356 else |
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357 yvalues(nd,i) = yvalues@_FillValue |
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358 count(nd,i) = 0 |
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359 end if |
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360 |
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361 ;############################################################# |
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362 ;using observed biome class: |
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363 ; |
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364 ; set the following 4 classes to _FillValue: |
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365 ; Water Bodies(0), Urban and Build-Up(13), |
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366 ; Permenant Snow and Ice(15), Unclassified(17) |
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367 |
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368 ; if (i.eq.0 .or. i.eq.13 .or. i.eq.15 .or. i.eq.17) then |
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369 ; yvalues(nd,i) = yvalues@_FillValue |
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370 ; count(nd,i) = 0 |
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371 ; end if |
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372 ;############################################################# |
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373 |
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374 ;############################################################# |
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375 ;using model biome class: |
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376 ; |
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377 ; set the following 4 classes to _FillValue: |
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378 ; (3)Needleleaf Deciduous Boreal Tree, |
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379 ; (8)Broadleaf Deciduous Boreal Tree, |
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380 ; (9)Broadleaf Evergreen Shrub, |
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381 ; (16)Wheat |
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382 |
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383 if (i.eq.3 .or. i.eq.8 .or. i.eq.9 .or. i.eq.16) then |
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384 yvalues(nd,i) = yvalues@_FillValue |
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385 count(nd,i) = 0 |
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386 end if |
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387 ;############################################################# |
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388 |
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389 ; print(nd + ": " + count(nd,i) + " points, avg = " + yvalues(nd,i)) |
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390 |
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391 ; Clean up for next time in loop. |
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392 |
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393 delete(idx) |
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394 end do |
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395 |
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396 delete(data) |
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397 end do |
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398 |
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399 ;============================ |
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400 ;compute beta |
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401 ;============================ |
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402 |
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403 u = yvalues(0,:) |
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404 v = yvalues(1,:) |
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405 u_count = count(0,:) |
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406 v_count = count(1,:) |
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407 |
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408 good = ind(.not.ismissing(u) .and. .not.ismissing(v)) |
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409 |
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410 uu = u(good) |
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411 vv = v(good) |
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412 uu_count = u_count(good) |
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413 vv_count = v_count(good) |
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414 |
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415 n_biome = dimsizes(uu) |
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416 beta_biome = new((/n_biome/),float) |
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417 |
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418 beta_biome = ((vv/uu) - 1.)/log(co2_f/co2_i) |
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419 |
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420 ;beta_biome_avg = avg(beta_biome) |
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421 beta_biome_avg = (sum(vv*vv_count)/sum(uu*uu_count) - 1.)/log(co2_f/co2_i) |
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422 |
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423 ;print (beta_biome_avg) |
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424 |
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425 ;=========================== |
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426 ; for html table - biome |
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427 ;=========================== |
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428 |
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429 output_html = "table_biome.html" |
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430 |
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431 ; column (not including header column) |
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432 |
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433 col_head = (/"CO2_i","CO2_f","NPP_i","NPP_f","Beta_model"/) |
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434 |
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435 ncol = dimsizes(col_head) |
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436 |
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437 ; row (not including header row) |
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438 |
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439 ;---------------------------------------------------- |
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440 ; using observed biome class: |
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441 ; |
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442 ; row_head = (/"Evergreen Needleleaf Forests" \ |
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443 ; ,"Evergreen Broadleaf Forests" \ |
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444 ; ,"Deciduous Needleleaf Forest" \ |
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445 ; ,"Deciduous Broadleaf Forests" \ |
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446 ; ,"Mixed Forests" \ |
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447 ; ,"Closed Bushlands" \ |
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448 ; ,"Open Bushlands" \ |
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449 ; ,"Woody Savannas (S. Hem.)" \ |
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450 ; ,"Savannas (S. Hem.)" \ |
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451 ; ,"Grasslands" \ |
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452 ; ,"Permanent Wetlands" \ |
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453 ; ,"Croplands" \ |
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454 ; ,"Cropland/Natural Vegetation Mosaic" \ |
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455 ; ,"Barren or Sparsely Vegetated" \ |
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456 ; ,"Woody Savannas (N. Hem.)" \ |
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457 ; ,"Savannas (N. Hem.)" \ |
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458 ; ,"All Biome" \ |
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459 ; /) |
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460 |
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461 ;---------------------------------------------------- |
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462 ; using model biome class: |
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463 ; |
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464 row_head = (/"Not Vegetated" \ |
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465 ,"Needleleaf Evergreen Temperate Tree" \ |
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466 ,"Needleleaf Evergreen Boreal Tree" \ |
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467 ; ,"Needleleaf Deciduous Boreal Tree" \ |
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468 ,"Broadleaf Evergreen Tropical Tree" \ |
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469 ,"Broadleaf Evergreen Temperate Tree" \ |
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470 ,"Broadleaf Deciduous Tropical Tree" \ |
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471 ,"Broadleaf Deciduous Temperate Tree" \ |
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472 ; ,"Broadleaf Deciduous Boreal Tree" \ |
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473 ; ,"Broadleaf Evergreen Shrub" \ |
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474 ,"Broadleaf Deciduous Temperate Shrub" \ |
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475 ,"Broadleaf Deciduous Boreal Shrub" \ |
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476 ,"C3 Arctic Grass" \ |
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477 ,"C3 Non-Arctic Grass" \ |
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478 ,"C4 Grass" \ |
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479 ,"Corn" \ |
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480 ; ,"Wheat" \ |
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481 ,"All Biome" \ |
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482 /) |
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483 |
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484 nrow = dimsizes(row_head) |
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485 |
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486 ; arrays to be passed to table. |
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487 text4 = new ((/nrow, ncol/),string ) |
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488 |
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489 do i=0,nrow-2 |
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490 text4(i,0) = sprintf("%.1f",co2_i) |
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491 text4(i,1) = sprintf("%.1f",co2_f) |
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492 text4(i,2) = sprintf("%.1f",uu(i)) |
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493 text4(i,3) = sprintf("%.1f",vv(i)) |
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494 text4(i,4) = sprintf("%.2f",beta_biome(i)) |
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495 end do |
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496 text4(nrow-1,0) = "-" |
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497 text4(nrow-1,1) = "-" |
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498 text4(nrow-1,2) = "-" |
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499 text4(nrow-1,3) = "-" |
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500 text4(nrow-1,4) = sprintf("%.2f",beta_biome_avg) |
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501 |
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502 ;************************************************** |
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503 ; html table |
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504 ;************************************************** |
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505 |
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506 header_text = "<H1>Beta Factor: Model "+model_name+"</H1>" |
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507 |
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508 header = (/"<HTML>" \ |
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509 ,"<HEAD>" \ |
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510 ,"<TITLE>CLAMP metrics</TITLE>" \ |
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511 ,"</HEAD>" \ |
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512 ,header_text \ |
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513 /) |
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514 footer = "</HTML>" |
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515 |
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516 table_header = (/ \ |
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517 "<table border=1 cellspacing=0 cellpadding=3 width=80%>" \ |
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518 ,"<tr>" \ |
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519 ," <th bgcolor=DDDDDD >Biome Class</th>" \ |
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520 ," <th bgcolor=DDDDDD >"+col_head(0)+"</th>" \ |
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521 ," <th bgcolor=DDDDDD >"+col_head(1)+"</th>" \ |
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522 ," <th bgcolor=DDDDDD >"+col_head(2)+"</th>" \ |
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523 ," <th bgcolor=DDDDDD >"+col_head(3)+"</th>" \ |
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524 ," <th bgcolor=DDDDDD >"+col_head(4)+"</th>" \ |
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525 ,"</tr>" \ |
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526 /) |
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527 table_footer = "</table>" |
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528 row_header = "<tr>" |
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529 row_footer = "</tr>" |
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530 |
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531 lines = new(50000,string) |
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532 nline = 0 |
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533 |
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534 set_line(lines,nline,header) |
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535 set_line(lines,nline,table_header) |
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536 ;----------------------------------------------- |
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537 ;row of table |
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538 |
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539 do n = 0,nrow-1 |
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540 set_line(lines,nline,row_header) |
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541 |
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542 txt1 = row_head(n) |
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543 txt2 = text4(n,0) |
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544 txt3 = text4(n,1) |
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545 txt4 = text4(n,2) |
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546 txt5 = text4(n,3) |
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547 txt6 = text4(n,4) |
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548 |
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549 set_line(lines,nline,"<th>"+txt1+"</th>") |
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550 set_line(lines,nline,"<th>"+txt2+"</th>") |
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551 set_line(lines,nline,"<th>"+txt3+"</th>") |
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552 set_line(lines,nline,"<th>"+txt4+"</th>") |
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553 set_line(lines,nline,"<th>"+txt5+"</th>") |
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554 set_line(lines,nline,"<th>"+txt6+"</th>") |
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555 |
|
556 set_line(lines,nline,row_footer) |
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557 end do |
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558 ;----------------------------------------------- |
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559 set_line(lines,nline,table_footer) |
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560 set_line(lines,nline,footer) |
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561 |
|
562 ; Now write to an HTML file. |
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563 idx = ind(.not.ismissing(lines)) |
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564 if(.not.any(ismissing(idx))) then |
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565 asciiwrite(output_html,lines(idx)) |
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566 else |
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567 print ("error?") |
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568 end if |
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569 |
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570 end |
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571 |