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Matrix
Compression Techniques
These are sparse
parser table compression techniques. I've modified it to be used
in
matrices. These are the pseudocodes ! not the programs!
Graph coloring scheme
for i=0 to m-1 for j =0 to n-1 if T[i][j] == insignificant sigmap[i][j] = 0 else sigmap[i][j] = 1 color = 1 for i=0 to m-1 for i2=0 to m-1 for j=0 to n-1 if T[i][j] == T[i2][j] && T[i][j] != insignificant && T[i2][j] != insignificant f = 1 else f = 0 rowmap[i2] = color if f == 1 if rowmap[i] == color rowmap[i2] = color-1 for j=0 to n-1 newT[rowmap[i2]][j] = T[i][j] else rowmap[i2] = color for j=0 to n-1 newT[rowmap[i2]][j] = T[i][j] else if f == 0 color++ rowmap[i2] = color for j=0 to n-1 newT[rowmap[i2]][j] = T[i][j] for j=0 to n-1 for j2=0 to n-1 for i=0 to m-1 if T[i][j] == T[i][j2] && T[i][j] != insignificant && T[i][j2] != insignificant f = 1 else f = 0 columnmap[j2] = color if f == 1 if columnmap[j] == color columnmap[j2] = color-1 for i=0 to m-1 value[columnmap[i]][j2] = T[i][j] else columnmap[j2] = color  hirschberg/