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1 ;******************************************************** |
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2 ; histogram normalized by rain and compute correleration |
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3 ;******************************************************** |
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4 load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_code.ncl" |
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5 load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/gsn_csm.ncl" |
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6 load "$NCARG_ROOT/lib/ncarg/nclscripts/csm/contributed.ncl" |
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7 |
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8 procedure pminmax(data:numeric,name:string) |
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9 begin |
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10 print ("min/max " + name + " = " + min(data) + "/" + max(data)) |
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11 if(isatt(data,"units")) then |
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12 print (name + " units = " + data@units) |
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13 end if |
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14 end |
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15 |
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16 ; |
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17 ; Main code. |
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18 ; |
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19 begin |
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20 |
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21 ;nclass = 18 |
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22 nclass = 20 |
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23 |
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24 ;************************************************ |
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25 ; read in data: observed |
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26 ;************************************************ |
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27 diri1 = "/fis/cgd/cseg/people/jeff/clamp_data/lai/" |
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28 ;fili1 = "land_class_T42.nc" |
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29 fili1 = "land_class_T42_new.nc" |
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30 fili2 = "LAI_2000-2005_mean_T42.nc" |
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31 data_file_ob1 = addfile(diri1+fili1,"r") |
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32 data_file_ob2 = addfile(diri1+fili2,"r") |
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33 |
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34 RAIN1 = tofloat(data_file_ob1->LAND_CLASS) |
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35 NPP1 = data_file_ob2->LAI |
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36 ;************************************************ |
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37 ; read in data: model |
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38 ;************************************************ |
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39 diri2 = "/fis/cgd/cseg/people/jeff/clamp_data/model/" |
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40 ;fili3 = "i01.03cn_1545-1569_ANN_climo.nc" |
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41 fili3 = "i01.04casa_1605-1629_ANN_climo.nc" |
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42 data_file_model = addfile(diri2+fili3,"r") |
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43 |
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44 NPP2 = data_file_model->TLAI |
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45 ;************************************************ |
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46 ; print min/max and unit |
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47 ;************************************************ |
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48 pminmax(RAIN1,"RAIN1") |
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49 pminmax(NPP1,"NPP1") |
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50 pminmax(NPP2,"NPP2") |
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51 |
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52 RAIN1_1D = ndtooned(RAIN1) |
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53 NPP1_1D = ndtooned(NPP1) |
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54 NPP2_1D = ndtooned(NPP2) |
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55 ; |
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56 ; Calculate some "nice" bins for binning the data in equally spaced |
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57 ; ranges. |
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58 ; |
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59 |
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60 ; nbins = nclass + 1 ; Number of bins to use. |
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61 ; nicevals = nice_mnmxintvl(min(RAIN1_1D),max(RAIN1_1D),nbins,False) |
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62 ; nvals = floattoint((nicevals(1) - nicevals(0))/nicevals(2) + 1) |
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63 ; range = fspan(nicevals(0),nicevals(1),nvals) |
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64 |
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65 nclassn = nclass + 1 |
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66 range = fspan(0,nclassn-1,nclassn) |
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67 |
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68 ; print (nicevals) |
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69 ; print (nvals) |
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70 print (range) |
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71 ; exit |
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72 |
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73 ; |
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74 ; Use this range information to grab all the values in a |
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75 ; particular range, and then take an average. |
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76 ; |
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77 nr = dimsizes(range) |
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78 nx = nr-1 |
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79 xvalues = new((/2,nx/),typeof(RAIN1_1D)) |
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80 xvalues(0,:) = range(0:nr-2) + (range(1:)-range(0:nr-2))/2. |
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81 dx = xvalues(0,1) - xvalues(0,0) ; range width |
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82 dx4 = dx/4 ; 1/4 of the range |
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83 xvalues(1,:) = xvalues(0,:) - dx/5. |
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84 yvalues = new((/2,nx/),typeof(RAIN1_1D)) |
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85 mn_yvalues = new((/2,nx/),typeof(RAIN1_1D)) |
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86 mx_yvalues = new((/2,nx/),typeof(RAIN1_1D)) |
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87 |
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88 do nd=0,1 |
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89 ; |
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90 ; See if we are doing model or observational data. |
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91 ; |
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92 if(nd.eq.0) then |
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93 data = RAIN1_1D |
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94 npp_data = NPP1_1D |
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95 else |
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96 data = RAIN1_1D |
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97 npp_data = NPP2_1D |
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98 end if |
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99 ; |
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100 ; Loop through each range and check for values. |
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101 ; |
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102 do i=0,nr-2 |
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103 if (i.ne.(nr-2)) then |
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104 print("") |
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105 print("In range ["+range(i)+","+range(i+1)+")") |
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106 idx = ind((range(i).le.data).and.(data.lt.range(i+1))) |
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107 else |
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108 print("") |
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109 print("In range ["+range(i)+",)") |
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110 idx = ind(range(i).le.data) |
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111 end if |
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112 ; |
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113 ; Calculate average, and get min and max. |
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114 ; |
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115 if(.not.any(ismissing(idx))) then |
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116 yvalues(nd,i) = avg(npp_data(idx)) |
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117 mn_yvalues(nd,i) = min(npp_data(idx)) |
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118 mx_yvalues(nd,i) = max(npp_data(idx)) |
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119 count = dimsizes(idx) |
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120 else |
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121 count = 0 |
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122 yvalues(nd,i) = yvalues@_FillValue |
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123 mn_yvalues(nd,i) = yvalues@_FillValue |
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124 mx_yvalues(nd,i) = yvalues@_FillValue |
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125 end if |
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126 ; |
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127 ; Print out information. |
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128 ; |
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129 print(nd + ": " + count + " points, avg = " + yvalues(nd,i)) |
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130 print("Min/Max: " + mn_yvalues(nd,i) + "/" + mx_yvalues(nd,i)) |
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131 |
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132 ; |
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133 ; Clean up for next time in loop. |
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134 ; |
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135 delete(idx) |
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136 end do |
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137 delete(data) |
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138 delete(npp_data) |
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139 end do |
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140 |
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141 ; |
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142 ; Start the graphics. |
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143 ; |
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144 wks = gsn_open_wks("ps","xy") |
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145 |
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146 res = True |
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147 res@gsnMaximize = True |
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148 res@gsnDraw = False |
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149 res@gsnFrame = False |
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150 res@xyMarkLineMode = "Markers" |
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151 res@xyMarkerSizeF = 0.014 |
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152 res@xyMarker = 16 |
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153 res@xyMarkerColors = (/"Brown","Blue"/) |
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154 ; res@trYMinF = min(mn_yvalues) - 10. |
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155 ; res@trYMaxF = max(mx_yvalues) + 10. |
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156 res@trYMinF = min(mn_yvalues) - 2 |
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157 res@trYMaxF = max(mx_yvalues) + 4 |
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158 |
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159 ; res@tiMainString = "Observed vs i01.03cn" |
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160 res@tiMainString = "Observed vs i01.04casa" |
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161 |
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162 res@tiYAxisString = "Mean LAI (Leaf Area Index)" |
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163 res@tiXAxisString = "Land Cover Type" |
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164 ; |
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165 ; Add a boxed legend using the more simple method, which won't have |
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166 ; vertical lines going through the markers. |
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167 ; |
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168 res@pmLegendDisplayMode = "Always" |
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169 ; res@pmLegendWidthF = 0.1 |
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170 res@pmLegendWidthF = 0.08 |
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171 res@pmLegendHeightF = 0.05 |
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172 res@pmLegendOrthogonalPosF = -1.17 |
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173 ; res@pmLegendOrthogonalPosF = -1.00 ;(downward) |
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174 ; res@pmLegendParallelPosF = 0.18 |
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175 res@pmLegendParallelPosF = 0.23 ;(rightward) |
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176 |
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177 ; res@lgPerimOn = False |
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178 res@lgLabelFontHeightF = 0.015 |
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179 ; res@xyExplicitLegendLabels = (/"observed","model_i01.03cn"/) |
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180 res@xyExplicitLegendLabels = (/"observed","model_i01.04casa"/) |
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181 |
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182 xy = gsn_csm_xy(wks,xvalues,yvalues,res) |
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183 |
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184 max_bar = new((/2,nx/),graphic) |
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185 min_bar = new((/2,nx/),graphic) |
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186 max_cap = new((/2,nx/),graphic) |
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187 min_cap = new((/2,nx/),graphic) |
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188 |
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189 lnres = True |
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190 |
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191 line_colors = (/"brown","blue"/) |
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192 do nd=0,1 |
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193 lnres@gsLineColor = line_colors(nd) |
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194 do i=0,nx-1 |
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195 |
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196 if(.not.ismissing(mn_yvalues(nd,i)).and. \ |
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197 .not.ismissing(mx_yvalues(nd,i))) then |
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198 ; |
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199 ; Attach the vertical bar, both above and below the marker. |
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200 ; |
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201 x1 = xvalues(nd,i) |
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202 y1 = yvalues(nd,i) |
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203 y2 = mn_yvalues(nd,i) |
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204 min_bar(nd,i) = gsn_add_polyline(wks,xy,(/x1,x1/),(/y1,y2/),lnres) |
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205 |
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206 y2 = mx_yvalues(nd,i) |
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207 max_bar(nd,i) = gsn_add_polyline(wks,xy,(/x1,x1/),(/y1,y2/),lnres) |
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208 ; |
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209 ; Attach the horizontal cap line, both above and below the marker. |
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210 ; |
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211 x1 = xvalues(nd,i) - dx4 |
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212 x2 = xvalues(nd,i) + dx4 |
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213 y1 = mn_yvalues(nd,i) |
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214 min_cap(nd,i) = gsn_add_polyline(wks,xy,(/x1,x2/),(/y1,y1/),lnres) |
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215 |
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216 y1 = mx_yvalues(nd,i) |
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217 max_cap(nd,i) = gsn_add_polyline(wks,xy,(/x1,x2/),(/y1,y1/),lnres) |
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218 end if |
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219 end do |
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220 end do |
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221 |
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222 ; |
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223 ; Here's how to do the legend by hand. |
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224 ; |
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225 ; mkres = True ; Marker resources |
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226 ; txres = True ; Text resources |
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227 ; mkres@gsMarkerIndex = 16 |
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228 ; mkres@gsMarkerSizeF = 0.02 |
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229 ; txres@txFontHeightF = 0.02 |
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230 ; txres@txJust = "CenterLeft" |
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231 ; |
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232 ; Change these values if you want to move the marker legend location. |
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233 ; These values are in the same data space as the plot. |
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234 ; |
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235 ; xlg1_cen = 0.2 |
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236 ; ylg1_cen = 900. |
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237 |
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238 ; xlg2_cen = 0.2 |
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239 ; ylg2_cen = 760. |
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240 |
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241 ; mkres@gsMarkerColor = "brown" |
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242 ; lnres@gsLineColor = "brown" |
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243 |
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244 ; lg_mark_legend1 = gsn_add_polymarker(wks,xy,xlg1_cen,ylg1_cen,mkres) |
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245 ; lg_line_legend1 = gsn_add_polyline(wks,xy,(/xlg1_cen,xlg1_cen/), \ |
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246 ; (/ylg1_cen-60,ylg1_cen+60/),lnres) |
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247 ; lg_cap_legend11 = gsn_add_polyline(wks,xy,(/xlg1_cen-0.1,xlg1_cen+0.1/), \ |
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248 ; (/ylg1_cen-60,ylg1_cen-60/),lnres) |
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249 ; lg_cap_legend12 = gsn_add_polyline(wks,xy,(/xlg1_cen-0.1,xlg1_cen+0.1/), \ |
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250 ; (/ylg1_cen+60,ylg1_cen+60/),lnres) |
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251 |
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252 ; tx_legend1 = gsn_add_text(wks,xy,"observed",xlg1_cen+0.15,ylg1_cen,txres) |
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253 |
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254 ; mkres@gsMarkerColor = "blue" |
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255 ; lnres@gsLineColor = "blue" |
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256 |
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257 ; lg_mark_legend2 = gsn_add_polymarker(wks,xy,xlg2_cen,ylg2_cen,mkres) |
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258 ; lg_line_legend2 = gsn_add_polyline(wks,xy,(/xlg2_cen,xlg2_cen/), \ |
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259 ; (/ylg2_cen-60,ylg2_cen+60/),lnres) |
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260 ; lg_cap_legend21 = gsn_add_polyline(wks,xy,(/xlg2_cen-0.1,xlg2_cen+0.1/), \ |
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261 ; (/ylg2_cen-60,ylg2_cen-60/),lnres) |
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262 ; lg_cap_legend22 = gsn_add_polyline(wks,xy,(/xlg2_cen-0.1,xlg2_cen+0.1/), \ |
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263 ; (/ylg2_cen+60,ylg2_cen+60/),lnres) |
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264 ; tx_legend2 = gsn_add_text(wks,xy,"model_i01.03cn",xlg2_cen+0.15,ylg2_cen,txres) |
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265 |
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266 draw(xy) |
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267 frame(wks) |
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268 system("convert xy.ps xy.png") |
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269 |
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270 u = yvalues(0,:) |
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271 v = yvalues(1,:) |
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272 |
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273 good = ind(.not.ismissing(u) .and. .not.ismissing(v)) |
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274 uu = u(good) |
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275 vv = v(good) |
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276 nz = dimsizes(uu) |
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277 print (nz) |
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278 |
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279 ccr = esccr(uu,vv,0) |
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280 print (ccr) |
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281 |
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282 ;old eq |
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283 ;bias = sum(((vv-uu)/uu)^2) |
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284 ;M = (1.- sqrt(bias/nz))*5. |
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285 |
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286 ;new eq |
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287 bias = sum(abs(vv-uu)/(vv+uu)) |
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288 M = (1.- (bias/nz))*5. |
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289 print (bias) |
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290 print (M) |
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291 |
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292 end |
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293 |