[1] | 1 | /* PBN, Paint-By-Numbers Puzzle */ |
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| 2 | |
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| 3 | /* Written in GNU MathProg by Andrew Makhorin <mao@gnu.org> */ |
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| 4 | |
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| 5 | /* A paint-by-number puzzle consists of an m*n grid of pixels (the |
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| 6 | canvas) together with m+n cluster-size sequences, one for each row |
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| 7 | and column. The goal is to paint the canvas with a picture that |
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| 8 | satisfies the following constraints: |
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| 9 | |
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| 10 | 1. Each pixel must be blank or white. |
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| 11 | |
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| 12 | 2. If a row or column has cluster-size sequence s1, s2, ..., sk, |
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| 13 | then it must contain k clusters of black pixels - the first with |
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| 14 | s1 black pixels, the second with s2 black pixels, and so on. |
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| 15 | |
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| 16 | It should be noted that "first" means "leftmost" for rows and |
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| 17 | "topmost" for columns, and that rows and columns need not begin or |
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| 18 | end with black pixels. |
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| 19 | |
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| 20 | Example: |
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| 21 | 1 1 |
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| 22 | 1 1 |
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| 23 | 2 1 1 1 1 1 2 3 |
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| 24 | 3 2 1 2 1 2 3 4 8 9 |
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| 25 | |
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| 26 | 3 6 # # # . # # # # # # |
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| 27 | 1 4 # . . . . . # # # # |
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| 28 | 1 1 3 . . # . # . . # # # |
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| 29 | 2 . . . . . . . . # # |
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| 30 | 3 3 . . # # # . . # # # |
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| 31 | 1 4 # . . . . . # # # # |
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| 32 | 2 5 # # . . . # # # # # |
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| 33 | 2 5 # # . . . # # # # # |
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| 34 | 1 1 . . . # . . . . . # |
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| 35 | 3 . . # # # . . . . . |
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| 36 | |
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| 37 | (In Russia this sort of puzzles is known as "Japanese crossword".) |
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| 38 | |
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| 39 | References: |
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| 40 | Robert A. Bosch, "Painting by Numbers", 2000. |
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| 41 | <http://www.oberlin.edu/~math/faculty/bosch/pbn-page.html> */ |
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| 42 | |
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| 43 | param m, integer, >= 1; |
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| 44 | /* the number of rows */ |
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| 45 | |
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| 46 | param n, integer, >= 1; |
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| 47 | /* the number of columns */ |
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| 48 | |
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| 49 | param row{i in 1..m, 1..n div 2}, integer, >= 0, default 0; |
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| 50 | /* the cluster-size sequence for row i (raw data) */ |
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| 51 | |
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| 52 | param col{j in 1..n, 1..m div 2}, integer, >= 0, default 0; |
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| 53 | /* the cluster-size sequence for column j (raw data) */ |
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| 54 | |
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| 55 | param kr{i in 1..m} := sum{t in 1..n div 2: row[i,t] > 0} 1; |
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| 56 | /* the number of clusters in row i */ |
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| 57 | |
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| 58 | param kc{j in 1..n} := sum{t in 1..m div 2: col[j,t] > 0} 1; |
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| 59 | /* the number of clusters in column j */ |
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| 60 | |
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| 61 | param sr{i in 1..m, t in 1..kr[i]} := row[i,t], integer, >= 1; |
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| 62 | /* the cluster-size sequence for row i */ |
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| 63 | |
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| 64 | param sc{j in 1..n, t in 1..kc[j]} := col[j,t], integer, >= 1; |
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| 65 | /* the cluster-size sequence for column j */ |
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| 66 | |
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| 67 | check{i in 1..m}: sum{t in 1..kr[i]} sr[i,t] <= n - (kr[i] - 1); |
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| 68 | /* check that the sum of the cluster sizes in each row is valid */ |
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| 69 | |
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| 70 | check{j in 1..n}: sum{t in 1..kc[j]} sc[j,t] <= m - (kc[j] - 1); |
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| 71 | /* check that the sum of the cluster sizes in each column is valid */ |
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| 72 | |
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| 73 | check: sum{i in 1..m, t in 1..kr[i]} sr[i,t] = |
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| 74 | sum{j in 1..n, t in 1..kc[j]} sc[j,t]; |
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| 75 | /* check that the sum of the cluster sizes in all rows is equal to the |
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| 76 | sum of the cluster sizes in all columns */ |
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| 77 | |
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| 78 | param er{i in 1..m, t in 1..kr[i]} := |
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| 79 | if t = 1 then 1 else er[i,t-1] + sr[i,t-1] + 1; |
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| 80 | /* the smallest value of j such that row i's t-th cluster can be |
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| 81 | placed in row i with its leftmost pixel occupying pixel j */ |
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| 82 | |
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| 83 | param lr{i in 1..m, t in 1..kr[i]} := |
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| 84 | if t = kr[i] then n + 1 - sr[i,t] else lr[i,t+1] - sr[i,t] - 1; |
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| 85 | /* the largest value of j such that row i's t-th cluster can be |
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| 86 | placed in row i with its leftmost pixel occupying pixel j */ |
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| 87 | |
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| 88 | param ec{j in 1..n, t in 1..kc[j]} := |
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| 89 | if t = 1 then 1 else ec[j,t-1] + sc[j,t-1] + 1; |
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| 90 | /* the smallest value of i such that column j's t-th cluster can be |
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| 91 | placed in column j with its topmost pixel occupying pixel i */ |
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| 92 | |
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| 93 | param lc{j in 1..n, t in 1..kc[j]} := |
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| 94 | if t = kc[j] then m + 1 - sc[j,t] else lc[j,t+1] - sc[j,t] - 1; |
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| 95 | /* the largest value of i such that column j's t-th cluster can be |
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| 96 | placed in column j with its topmost pixel occupying pixel i */ |
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| 97 | |
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| 98 | var z{i in 1..m, j in 1..n}, binary; |
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| 99 | /* z[i,j] = 1, if row i's j-th pixel is painted black |
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| 100 | z[i,j] = 0, if row i's j-th pixel is painted white */ |
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| 101 | |
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| 102 | var y{i in 1..m, t in 1..kr[i], j in er[i,t]..lr[i,t]}, binary; |
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| 103 | /* y[i,t,j] = 1, if row i's t-th cluster is placed in row i with its |
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| 104 | leftmost pixel occupying pixel j |
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| 105 | y[i,t,j] = 0, if not */ |
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| 106 | |
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| 107 | var x{j in 1..n, t in 1..kc[j], i in ec[j,t]..lc[j,t]}, binary; |
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| 108 | /* x[j,t,i] = 1, if column j's t-th cluster is placed in column j with |
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| 109 | its topmost pixel occupying pixel i |
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| 110 | x[j,t,i] = 0, if not */ |
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| 111 | |
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| 112 | s.t. fa{i in 1..m, t in 1..kr[i]}: |
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| 113 | sum{j in er[i,t]..lr[i,t]} y[i,t,j] = 1; |
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| 114 | /* row i's t-th cluster must appear in row i exactly once */ |
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| 115 | |
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| 116 | s.t. fb{i in 1..m, t in 1..kr[i]-1, j in er[i,t]..lr[i,t]}: |
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| 117 | y[i,t,j] <= sum{jp in j+sr[i,t]+1..lr[i,t+1]} y[i,t+1,jp]; |
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| 118 | /* row i's (t+1)-th cluster must be placed to the right of its t-th |
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| 119 | cluster */ |
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| 120 | |
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| 121 | s.t. fc{j in 1..n, t in 1..kc[j]}: |
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| 122 | sum{i in ec[j,t]..lc[j,t]} x[j,t,i] = 1; |
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| 123 | /* column j's t-th cluster must appear in column j exactly once */ |
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| 124 | |
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| 125 | s.t. fd{j in 1..n, t in 1..kc[j]-1, i in ec[j,t]..lc[j,t]}: |
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| 126 | x[j,t,i] <= sum{ip in i+sc[j,t]+1..lc[j,t+1]} x[j,t+1,ip]; |
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| 127 | /* column j's (t+1)-th cluster must be placed below its t-th cluster */ |
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| 128 | |
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| 129 | s.t. fe{i in 1..m, j in 1..n}: |
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| 130 | z[i,j] <= sum{t in 1..kr[i], jp in er[i,t]..lr[i,t]: |
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| 131 | j-sr[i,t]+1 <= jp and jp <= j} y[i,t,jp]; |
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| 132 | /* the double coverage constraint stating that if row i's j-th pixel |
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| 133 | is painted black, then at least one of row i's clusters must be |
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| 134 | placed in such a way that it covers row i's j-th pixel */ |
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| 135 | |
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| 136 | s.t. ff{i in 1..m, j in 1..n}: |
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| 137 | z[i,j] <= sum{t in 1..kc[j], ip in ec[j,t]..lc[j,t]: |
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| 138 | i-sc[j,t]+1 <= ip and ip <= i} x[j,t,ip]; |
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| 139 | /* the double coverage constraint making sure that if row i's j-th |
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| 140 | pixel is painted black, then at least one of column j's clusters |
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| 141 | covers it */ |
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| 142 | |
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| 143 | s.t. fg{i in 1..m, j in 1..n, t in 1..kr[i], jp in er[i,t]..lr[i,t]: |
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| 144 | j-sr[i,t]+1 <= jp and jp <= j}: z[i,j] >= y[i,t,jp]; |
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| 145 | /* the constraint to prevent white pixels from being covered by the |
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| 146 | row clusters */ |
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| 147 | |
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| 148 | s.t. fh{i in 1..m, j in 1..n, t in 1..kc[j], ip in ec[j,t]..lc[j,t]: |
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| 149 | i-sc[j,t]+1 <= ip and ip <= i}: z[i,j] >= x[j,t,ip]; |
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| 150 | /* the constraint to prevent white pixels from being covered by the |
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| 151 | column clusters */ |
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| 152 | |
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| 153 | /* there is no need for an objective function here */ |
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| 154 | |
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| 155 | solve; |
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| 156 | |
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| 157 | for {i in 1..m} |
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| 158 | { printf{j in 1..n} " %s", if z[i,j] then "#" else "."; |
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| 159 | printf "\n"; |
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| 160 | } |
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| 161 | |
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| 162 | data; |
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| 163 | |
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| 164 | /* These data correspond to the example above. */ |
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| 165 | |
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| 166 | param m := 10; |
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| 167 | |
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| 168 | param n := 10; |
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| 169 | |
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| 170 | param row : 1 2 3 4 := |
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| 171 | 1 3 6 . . |
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| 172 | 2 1 4 . . |
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| 173 | 3 1 1 3 . |
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| 174 | 4 2 . . . |
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| 175 | 5 3 3 . . |
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| 176 | 6 1 4 . . |
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| 177 | 7 2 5 . . |
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| 178 | 8 2 5 . . |
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| 179 | 9 1 1 . . |
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| 180 | 10 3 . . . ; |
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| 181 | |
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| 182 | param col : 1 2 3 4 := |
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| 183 | 1 2 3 . . |
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| 184 | 2 1 2 . . |
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| 185 | 3 1 1 1 1 |
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| 186 | 4 1 2 . . |
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| 187 | 5 1 1 1 1 |
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| 188 | 6 1 2 . . |
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| 189 | 7 2 3 . . |
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| 190 | 8 3 4 . . |
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| 191 | 9 8 . . . |
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| 192 | 10 9 . . . ; |
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| 193 | |
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| 194 | end; |
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