adjmatrix = xmalloc(sizeof(*adjmatrix)*n);
}
+static AdjWord one_adj_bit(int bitnum) {
+ return (AdjWord)1 << j;
+}
+
static int count_set_adj_bits(AdjWord w) {
int j, total;
for (j=0, total=0; j<m; j++)
- total += !!(w & ((AdjWord)1 << j));
+ total += !!(w & one_adj_bit(j));
return total;
}
static void optimise(void) {
- int i;
- for (i=0; i<n; i++) {
+ int i, totalfrags;
+ for (i=0, totalfrags=0; i<n; i++) {
+ int frags = count_set_adj_bits(adjmatrix[i]);
+ totalfrags += frags;
printf("%"PRADJ" ", adjmatrix[i]);
- double maxminsize = (double)m / count_set_adj_bits(adjmatrix[i]);
+ double maxminsize = (double)m / frags;
if (maxminsize < best) {
printf(" too fine\n");
return;
* fragment from old match i and making it part of new match j.
*
* The structural variables (columns) are:
- * x_fragsz_i_j the size of that fragment
- * x_minimum minimum size of any fragment
+ * x_minimum minimum size of any fragment (bounded below by 0)
+ * x_morefrag_i_j the amount by which the size of the fragment
+ * i,j exceeds the minimum size (bounded below by 0)
*
- * The auxiliary variables (rows, constraints) are:
+ * The auxiliary variables (rows) are:
* x_total_i total length for each input match (fixed variable)
* x_total_j total length for each output match (fixed variable)
- * x_fragmin_i_j amount by which fragment is > minimum (lower bound 0)
*
- * The objective function is simply to maximise x_minimum
+ * The objective function is simply
+ * maximise x_minimum
+ *
+ * We use X_ and Y_ to refer to GLPK's (1-based) column and row indices.
+ * ME_ refers to entries in the list of constraint matrix elements
+ * which we build up as we go.
*/
+ glp_prob *prob = glp_create_prob();
+
+ int Y_totals_i = glp_add_rows(prob, i);
+ int Y_totals_j = glp_add_rows(prob, j);
+ int X_minimum = glp_add_cols(prob, 1);
+ int rows = glp_get_num_rows(prob);
+ int cols = glp_get_num_rows(cols);
+
+ int next_matrix_entry = 1; /* wtf GLPK! */
+ int matrix_entries_size = next_matrix_entry + i + j + totalfrags*2;
+ double matrix_entries[matrix_entries_size];
+ int matrix_entries_XY[2][matrix_entries_size];
+
+#define ADD_MATRIX_ENTRY(Y,X) ({ \
+ assert(matrix_entries_size < next_matrix_entry); \
+ matrix_entries_XY[0][next_matrix_entry] = X; \
+ matrix_entries_XY[1][next_matrix_entry] = Y; \
+ matrix_entries[next_matrix_entry] = 0; \
+ next_matrix_entry++; \
+ })
+
+ int ME_totals_i__minimum = next_matrix_entry;
+ for (i=0; i<n; i++) ADD_MATRIX_ENTRY(Y_totals_i+i, X_minimum);
+
+ int ME_totals_j__minimum = next_matrix_entry;
+ for (j=0; j<m; j++) ADD_MATRIX_ENTRY(Y_totals_j+j, X_minimum);
+
+ /* \forall_i x_totals_i = m */
+ /* \forall_i x_totals_j = n */
+ for (i=0; i<n; i++) glp_set_row_bounds(prob, Y_totals_i+i, GLP_FX, m,m);
+ for (j=0; j<m; j++) glp_set_row_bounds(prob, Y_totals_j+j, GLP_FX, n,n);
+
+ /* x_minimum >= 0 */
+ glp_set_col_bounds(prob, X_minimum, GLP_LB, 0, 0);
+
+ /* objective is maximising x_minimum */
+ glp_set_obj_dir(prob, GLP_MAX);
+ glp_set_obj_coef(prob, X_minimum, 1);
+
+ for (i=0; i<n; j++) {
+ for (j=0; j<m; j++) {
+ if (!(adjmatrix[i] & one_adj_bit(j)))
+ continue;
+ /* x_total_i += x_minimum */
+ /* x_total_j += x_minimum */
+ matrix_entries[ ME_totals_i__minimum + i ] ++;
+ matrix_entries[ ME_totals_j__minimum + j ] ++;
+
+ /* x_morefrag_i_j >= 0 */
+ int X_morefrag_i_j = glp_add_cols(prob, 1);
+ glp_set_col_bnds(prob, X_morefrag_i_j, GLP_LO, 0, 0);
+
+ /* x_total_i += x_morefrag_i_j */
+ /* x_total_j += x_morefrag_i_j */
+ int ME_totals_i__mf_i_j = ADD_MATRIX_ENTRY(Y_totals_i+i, X_morefrag_i_j);
+ int ME_totals_j__mf_i_j = ADD_MATRIX_ENTRY(Y_totals_j+j, X_morefrag_i_j);
+ matrix_entries[ME_totals_i__mf_i_j] = 1;
+ matrix_entries[ME_totals_j__mf_i_j] = 1;
+ }
+ }
+
+ assert(next_matrix_entry == matrix_entries_size);
+
+ for (row=1; row<=rows; row++) {
+ glp_load_matrix(prob, next_matrix_entry,
+ matrix_entries_XY[1], matrix_entries_XY[0],
+ matrix_entries);
+
printf("nyi\n");
}