[101] | 1 | ;+ |
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[232] | 2 | ; |
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[136] | 3 | ; @file_comments |
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[238] | 4 | ; extrapolate data (zinput) where maskinput equal 0 by filling step by |
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[202] | 5 | ; step the coastline points with the mean value of the 8 neighbourgs |
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| 6 | ; (weighted by their mask value). |
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[101] | 7 | ; |
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[226] | 8 | ; @categories |
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[157] | 9 | ; Interpolation |
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| 10 | ; |
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[202] | 11 | ; @param zinput {in}{required}{type=2d array} |
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[118] | 12 | ; data to be extrapolate |
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| 13 | ; |
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[202] | 14 | ; @param maskinput {in}{required}{type=2d array or -1} |
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| 15 | ; a 2D array, the land-sea mask of the output data (1 on ocean, 0 on land) |
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| 16 | ; put -1 if input data are not masked |
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[118] | 17 | ; |
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[202] | 18 | ; @param nb_iteration {in}{optional}{type=integer scalar}{default=10.E20} |
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[242] | 19 | ; Maximum number of iterations done in the extrapolation process. If there |
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[202] | 20 | ; is no more masked values we exit extrapolate before reaching nb_iteration |
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| 21 | ; (to be sure to fill everything, you can use a very large value) |
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[118] | 22 | ; |
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[261] | 23 | ; @keyword X_PERIODIC {type=scalar, 0 or 1}{default=0} |
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[202] | 24 | ; put 1 to specify that the data are periodic along x axis |
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[118] | 25 | ; |
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[202] | 26 | ; @keyword MINVAL {type=scalar}{default=not used} |
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| 27 | ; to specify a minimum value to the extrapolated values |
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| 28 | ; |
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| 29 | ; @keyword MAXVAL {type=scalar}{default=not used} |
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| 30 | ; to specify a maximum value to the extrapolated values |
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| 31 | ; |
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| 32 | ; @keyword GE0 {type=scalar 0 or 1}{default=0} |
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| 33 | ; put 1 to force the extrapolated values to be larger than 0, same as using minval=0. |
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| 34 | ; |
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[238] | 35 | ; @returns |
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| 36 | ; the extrapolated 2d array |
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[202] | 37 | ; |
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| 38 | ; @examples |
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| 39 | ; IDL> a=extrapolate(dist(jpi,jpj),tmask[*,*,0],/x_periodic) |
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| 40 | ; IDL> tvplus, a |
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| 41 | ; IDL> tvplus, a*(1-tmask[*,*,0]) |
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| 42 | ; get the coastline: |
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| 43 | ; IDL> a=extrapolate(tmask[*,*,0],tmask[*,*,0],1,/x_periodic) |
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| 44 | ; IDL> tvplus, a-tmask[*,*,0] |
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| 45 | ; |
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| 46 | ; @history |
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| 47 | ; Originaly written by G. Roulet |
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| 48 | ; Sebastien Masson (smasson\@lodyc.jussieu.fr) |
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| 49 | ; |
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[226] | 50 | ; @version |
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| 51 | ; $Id$ |
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[118] | 52 | ; |
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[101] | 53 | ;- |
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[231] | 54 | ; |
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[202] | 55 | FUNCTION extrapolate, zinput, maskinput, nb_iteration, x_periodic = x_periodic $ |
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| 56 | , MINVAL = minval, MAXVAL = maxval, GE0 = ge0 |
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[59] | 57 | ; |
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[125] | 58 | compile_opt idl2, strictarrsubs |
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[59] | 59 | ; |
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| 60 | ; check the number of iteration used in the extrapolation. |
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| 61 | IF n_elements(nb_iteration) EQ 0 THEN nb_iteration = 10.E20 |
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| 62 | IF nb_iteration EQ 0 THEN return, zinput |
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| 63 | nx = (size(zinput))[1] |
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| 64 | ny = (size(zinput))[2] |
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| 65 | ; take care of the boundary conditions... |
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[125] | 66 | ; |
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[59] | 67 | ; for the x direction, we put 2 additional columns at the left and |
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[125] | 68 | ; right side of the array. |
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[59] | 69 | ; for the y direction, we put 2 additional lines at the bottom and |
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[125] | 70 | ; top side of the array. |
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[59] | 71 | ; These changes allow us to use shift function without taking care of |
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| 72 | ; the x and y periodicity. |
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| 73 | ; |
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| 74 | ztmp = bytarr(nx+2, ny+2) |
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[202] | 75 | IF n_elements(maskinput) EQ 1 AND maskinput[0] EQ -1 THEN maskinput = replicate(1b, nx, ny) |
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[226] | 76 | IF n_elements(maskinput) NE nx*ny THEN BEGIN |
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[236] | 77 | ras = report('input grid mask do not have the good size') |
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[202] | 78 | return, -1 |
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| 79 | ENDIF |
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[59] | 80 | ztmp[1:nx, 1:ny] = byte(maskinput) |
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| 81 | msk = temporary(ztmp) |
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| 82 | ; |
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| 83 | ztmp = replicate(1.e20, nx+2, ny+2) |
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| 84 | ztmp[1:nx, 1:ny] = zinput |
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| 85 | if keyword_set(x_periodic) then begin |
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| 86 | ztmp[0, 1:ny] = zinput[nx-1, *] |
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| 87 | ztmp[nx+1, 1:ny] = zinput[0, *] |
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| 88 | ENDIF |
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| 89 | ; remove NaN points if there is some... |
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| 90 | nan = where(finite(ztmp) EQ 0, cnt_nan) |
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| 91 | IF cnt_nan NE 0 THEN ztmp[temporary(nan)] = 1.e20 |
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| 92 | z = temporary(ztmp) |
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| 93 | nx2 = nx+2 |
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| 94 | ny2 = ny+2 |
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| 95 | ;--------------------------------------------------------------- |
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| 96 | ;--------------------------------------------------------------- |
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[125] | 97 | ; extrapolation |
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[59] | 98 | ;--------------------------------------------------------------- |
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| 99 | sqrtinv = 1./sqrt(2) |
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| 100 | ; |
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[69] | 101 | cnt = 1 |
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[226] | 102 | ; When we look for the coastline, we don't want to select the |
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[59] | 103 | ; borderlines of the array. -> we force the value of the mask for |
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| 104 | ; those lines. |
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| 105 | msk[0, *] = 1b |
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| 106 | msk[nx+1, *] = 1b |
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| 107 | msk[*, 0] = 1b |
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| 108 | msk[*, ny+1] = 1b |
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| 109 | ; find the land points |
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| 110 | land = where(msk EQ 0, cnt_land) |
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| 111 | ;--------------------------------------------------------------- |
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| 112 | WHILE cnt LE nb_iteration AND cnt_land NE 0 DO BEGIN |
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| 113 | ;--------------------------------------------------------------- |
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[226] | 114 | ; find the coastline points... |
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[59] | 115 | ;--------------------------------------------------------------- |
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[238] | 116 | ; Once the land points list has been found, we change back the |
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[59] | 117 | ; mask values for the boundary conditions. |
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| 118 | msk[0, *] = 0b |
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| 119 | msk[nx+1, *] = 0b |
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| 120 | msk[*, 0] = 0b |
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| 121 | msk[*, ny+1] = 0b |
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| 122 | if keyword_set(x_periodic) then begin |
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| 123 | msk[0, *] = msk[nx, *] |
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| 124 | msk[nx+1, *] = msk[1, *] |
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| 125 | endif |
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| 126 | ; |
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| 127 | ; we compute the weighted number of sea neighbourgs. |
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| 128 | ; those 4 neighbours have a weight of 1: |
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[125] | 129 | ; * |
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| 130 | ; *+* |
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| 131 | ; * |
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[59] | 132 | ; |
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| 133 | ; those 4 neighbours have a weight of 1/sqrt(2): |
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| 134 | ; |
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| 135 | ; * * |
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[125] | 136 | ; + |
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[59] | 137 | ; * * |
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| 138 | ; |
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| 139 | ; As we make sure that none of the land points are located on the |
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| 140 | ; border of the array, we can compute the weight without shift |
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| 141 | ; (faster). |
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| 142 | ; |
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| 143 | weight = msk[land+1]+msk[land-1]+msk[land+nx2]+msk[land-nx2] $ |
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| 144 | +sqrtinv*(msk[land+nx2+1]+msk[land+nx2-1] $ |
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| 145 | +msk[land-nx2+1]+msk[land-nx2-1]) |
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| 146 | ; list all the points that have sea neighbourgs |
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| 147 | ok = where(weight GT 0) |
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| 148 | ; the coastline points |
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| 149 | coast = land[ok] |
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| 150 | ; their weighted number of sea neighbourgs. |
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| 151 | weight = weight[temporary(ok)] |
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| 152 | ;--------------------------------------------------------------- |
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[226] | 153 | ; fill the coastline points |
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[59] | 154 | ;--------------------------------------------------------------- |
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| 155 | z = temporary(z)*msk |
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| 156 | ; |
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| 157 | zcoast = z[1+coast]+z[-1+coast]+z[nx2+coast]+z[-nx2+coast] $ |
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| 158 | +1./sqrt(2)*(z[nx2+1+coast]+z[nx2-1+coast] $ |
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| 159 | +z[-nx2+1+coast]+z[-nx2-1+coast]) |
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[125] | 160 | ; |
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[199] | 161 | IF keyword_set(ge0) THEN zcoast = 0. > temporary(zcoast) |
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[59] | 162 | IF n_elements(minval) NE 0 THEN zcoast = minval > temporary(zcoast) |
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| 163 | IF n_elements(maxval) NE 0 THEN zcoast = temporary(zcoast) < maxval |
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| 164 | z[coast] = temporary(zcoast)/temporary(weight) |
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[238] | 165 | ; we update the boundary conditions of z |
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[59] | 166 | if keyword_set(x_periodic) then begin |
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| 167 | z[0, *] = z[nx, *] |
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| 168 | z[nx+1, *] = z[1, *] |
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| 169 | endif |
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| 170 | ;--------------------------------------------------------------- |
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| 171 | ; we update the mask |
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| 172 | ;--------------------------------------------------------------- |
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| 173 | msk[temporary(coast)] = 1 |
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| 174 | ; |
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| 175 | cnt = cnt + 1 |
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[125] | 176 | ; When we look for the coast line, we don't want to select the |
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[59] | 177 | ; borderlines of the array. -> we force the value of the mask for |
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| 178 | ; those lines. |
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| 179 | msk[0, *] = 1b |
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| 180 | msk[nx+1, *] = 1b |
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| 181 | msk[*, 0] = 1b |
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| 182 | msk[*, ny+1] = 1b |
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| 183 | ; find the land points |
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| 184 | land = where(msk EQ 0, cnt_land) |
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| 185 | ; |
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| 186 | ENDWHILE |
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| 187 | ;--------------------------------------------------------------- |
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| 188 | ; we return the original size of the array |
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| 189 | ;--------------------------------------------------------------- |
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[125] | 190 | ; |
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[59] | 191 | return, z[1:nx, 1:ny] |
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[125] | 192 | END |
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