*
* Invoke as ./main n m
*
- * The algorithm is faster if the arguments are ordered so that n > m.
+ * The arguments must be ordered so that n > m:
+ * n is the number of (more, shorter) input matches of length m
+ * m is the number of (fewer, longer) output matches of length n
+ *
+ * Options:
+ * -j<jobs> run in parallel on <jobs> cores
+ * -b<best> search only for better than <best>
*/
/*
*
* We search all possible adjacency matrices, and for each one we run
* GLPK's simplex solver. We represent the adjacency matrix as an
- * array of bitmaps.
+ * array of bitmaps: one word per input stick, with one bit per output
+ * stick.
*
* However, there are a couple of wrinkles:
*
* nondecreasing in array order.
*
* Once we have a solution, we also avoid considering any candidate
- * which involves dividing one of the output sticks into so many
+ * which involves dividing one of the input sticks into so many
* fragment that the smallest fragment would necessarily be no bigger
* than our best solution. That is, we reject candidates where any of
* the hamming weights of the adjacency bitmap words are too large.
*
+ * We further winnow the set of possible adjacency matrices, by
+ * ensuring the same bit is not set in too many entries of adjmatrix
+ * (ie, as above, only considering output sticks); and by ensuring
+ * that it is not set in too few: each output stick must consist
+ * of at least two fragments since the output sticks are longer than
+ * the input ones.
+ *
* And, we want to do the search in order of increasing maximum
* hamming weight. This is because in practice optimal solutions tend
* to have low hamming weight, and having found a reasonable solution
static glp_prob *best_prob;
static AdjWord *best_adjmatrix;
-static int n_over_best, m_over_best;
+static int n_max_frags=INT_MAX, m_max_frags=INT_MAX;
static int *weight;
static unsigned printcounter;
static void set_best(double new_best) {
best = new_best;
- n_over_best = floor(n / best);
- m_over_best = floor(m / best);
+ /*
+ * When computing n_max_frags, we want to set a value that will skip
+ * anything that won't provide strictly better solutions. So we
+ * want
+ * frags < n / best
+ * _ _
+ * <=> frags < | n / best |
+ * _ _
+ * <=> frags <= | n / best | - 1
+ *
+ * But best values from glpk are slightly approximate, so we
+ * subtract a fudge factor from our target.
+ */
+ double near_best = best * 0.98 - 0.02;
+ if (near_best > 0) {
+ n_max_frags = ceil(n / near_best) - 1;
+ m_max_frags = ceil(m / near_best) - 1;
+ }
}
/*----- multicore support -----*/
}
static void mc_iterate_worker(void) {
+ static time_t lastprint;
+
for (;;) {
mc_rwvsetup_outer();
ssize_t r = readv(mc_work[0], mc_iov, mc_niovs);
bool ok = maxhamweight_ok();
if (!ok) continue;
- ok = preconsider_ok(multicore_iteration_boundary, 1);
- progress_eol();
+ time_t now = time(0);
+ bool doprint = now != lastprint;
+ lastprint = now;
+
+ ok = preconsider_ok(multicore_iteration_boundary, doprint);
+ if (doprint) progress_eol();
if (!ok) continue;
/* stop iterate_recurse from trying to run multicore_outer_iteration */
glp_term_out(GLP_OFF);
setlinebuf(stderr);
weight = calloc(sizeof(*weight), m); assert(weight);
- n_over_best = INT_MAX;
- m_over_best = INT_MAX;
}
#if 0
static int totalfrags;
static bool maxhamweight_ok(void) {
- return maxhamweight <= m_over_best;
+ return maxhamweight <= m_max_frags;
}
static bool preconsider_ok(int nwords, bool doprint) {
for (i=0, totalfrags=0; i<nwords; i++) {
int frags = count_set_adj_bits(adjmatrix[i]);
PRINTF("%"PRADJ" ", adjmatrix[i]);
- if (frags > m_over_best) {
+ if (frags > m_max_frags) {
PRINTF(" too fine");
goto out;
}
glp_set_obj_coef(prob, X_minimum, 1);
for (i=0; i<n; i++) {
- for (j=0, jbit=1; j<m; j++, jbit<<=1) {
+ FOR_BITS(j,m) {
if (!(adjmatrix[i] & jbit))
continue;
/* x_total_i += x_minimum */
AdjWord jbit;
if (i >= n) {
+ for (j=0; j<m; j++)
+ if (weight[j] < 2)
+ return;
+
printcounter++;
optimise(!(printcounter & 0xfff));
return;
if (adjmatrix[i] & jbit)
weight[j]++;
for (int j = 0; j < m; j++)
- if (weight[j] >= n_over_best)
+ if (weight[j] > n_max_frags)
goto takeout;
iterate_recurse(i+1, adjmatrix[i]);
}
}
+static int gcd(int a, int b)
+{
+ assert(a>0);
+ assert(b>0);
+ while (b) {
+ int t = a % b;
+ a = b;
+ b = t;
+ }
+ return a;
+}
+
+static void print_rational(int n, int d)
+{
+ int g = gcd(n, d);
+ n /= g;
+ d /= g;
+ printf("%d", n);
+ if (d > 1)
+ printf("/%d", d);
+}
+
+#define MAKE_INT_VECTOR_COMPARATOR(thing) \
+ static int compare_ints_##thing(const void *av, const void *bv) \
+ { \
+ const int *a = (const int *)av; \
+ const int *b = (const int *)bv; \
+ int i; \
+ for (i = 0; i < (thing); i++) \
+ if (a[i] != b[i]) \
+ return a[i] > b[i] ? -1 : +1; \
+ return 0; \
+ }
+/* Good grief, if only qsort let me pass a context parameter */
+MAKE_INT_VECTOR_COMPARATOR(1)
+MAKE_INT_VECTOR_COMPARATOR(m)
+MAKE_INT_VECTOR_COMPARATOR(n)
+
static void report(void) {
fprintf(stderr, "\n");
+ if (best_adjmatrix) {
+ int i;
+ fprintf(stderr," ");
+ for (i=0; i<n; i++) fprintf(stderr, " %"PRADJ, best_adjmatrix[i]);
+ }
+ fprintf(stderr, " best=%-12.8f nf<=%d mf<=%d\n",
+ best, n_max_frags, m_max_frags);
+ printf("%d into %d: ", n, m);
if (best_prob) {
double min = glp_get_obj_val(best_prob);
double a[n][m];
- int i, j, cols;
+ int ai[n][m];
+ int i, j, k, d, cols, imin;
for (i = 0; i < n; i++)
for (j = 0; j < m; j++)
a[i][j] = 0;
continue;
a[x][y] = min + glp_get_col_prim(best_prob, i);
}
- printf("%d into %d: min fragment %g [%s]\n", n, m, min, VERSION);
- for (i = 0; i < n; i++) {
+
+ /*
+ * Try to find a denominator over which all these numbers turn
+ * sensibly into rationals.
+ */
+ for (d = 1;; d++) {
+ /*
+ * Round everything to the nearest multiple of d.
+ */
+ for (i = 0; i < n; i++)
+ for (j = 0; j < m; j++)
+ ai[i][j] = a[i][j] * d + 0.5;
+
+ /*
+ * Ensure the rows and columns add up correctly.
+ */
+ for (i = 0; i < n; i++) {
+ int total = 0;
+ for (j = 0; j < m; j++)
+ total += ai[i][j];
+ if (total != d*m)
+ goto next_d;
+ }
for (j = 0; j < m; j++) {
- if (a[i][j])
- printf(" %9.3f", a[i][j]);
- else
- printf(" ");
+ int total = 0;
+ for (i = 0; i < n; i++)
+ total += ai[i][j];
+ if (total != d*n)
+ goto next_d;
+ }
+
+ /*
+ * Ensure we haven't rounded a good solution to a worse one, by
+ * finding the new minimum fragment and making sure it's at
+ * least the one we previously had.
+ */
+ imin = d*n;
+ for (i = 0; i < n; i++)
+ for (j = 0; j < m; j++)
+ if (ai[i][j] > 0 && ai[i][j] < imin)
+ imin = ai[i][j];
+
+ if (abs((double)imin / d - min) > 1e-10)
+ goto next_d;
+
+ /*
+ * Got it! We've found a rational-valued dissection.
+ */
+ printf("min fragment ");
+ print_rational(imin, d);
+ printf(" [%s]\n", VERSION);
+
+ /*
+ * We don't really want to output the matrix, so instead let's
+ * output the ways in which the sticks are cut up.
+ */
+ {
+ int ai2[m][n];
+ for (i = 0; i < n; i++) {
+ for (j = 0; j < m; j++)
+ ai2[j][i] = ai[i][j];
+ }
+ for (i = 0; i < n; i++)
+ qsort(ai+i, m, sizeof(int), compare_ints_1);
+ qsort(ai, n, m*sizeof(int), compare_ints_m);
+ printf(" Cut up %d sticks of length %d like this:\n", n, m);
+ for (i = 0; i < n ;) {
+ for (j = 1; i+j < n && compare_ints_m(ai+i, ai+i+j) == 0; j++);
+ printf(" %d x (", j);
+ for (k = 0; k < m && ai[i][k] > 0; k++) {
+ if (k > 0) printf(" + ");
+ print_rational(ai[i][k], d);
+ }
+ printf(")\n");
+ i += j;
+ }
+
+ for (j = 0; j < m; j++)
+ qsort(ai2+j, n, sizeof(int), compare_ints_1);
+ qsort(ai2, m, n*sizeof(int), compare_ints_n);
+ printf(" Reassemble as %d sticks of length %d like this:\n", m, n);
+ for (j = 0; j < m ;) {
+ for (i = 1; i+j < m && compare_ints_n(ai2+j, ai2+j+i) == 0; i++);
+ printf(" %d x (", i);
+ for (k = 0; k < n && ai2[j][k] > 0; k++) {
+ if (k > 0) printf(" + ");
+ print_rational(ai2[j][k], d);
+ }
+ printf(")\n");
+ j += i;
+ }
}
- printf("\n");
+ return;
+
+ next_d:;
}
+ } else {
+ printf(" none better than %9.3f [%s]\n", best, VERSION);
}
if (ferror(stdout) || fclose(stdout)) { perror("stdout"); exit(-1); }
}
int main(int argc, char **argv) {
int opt;
- while ((opt = getopt(argc,argv,"j:")) >= 0) {
+ double best_to_set = -1.0; /* means 'don't' */
+ while ((opt = getopt(argc,argv,"j:b:")) >= 0) {
switch (opt) {
case 'j': ncpus = atoi(optarg); break;
+ case 'b': best_to_set = atof(optarg); break;
case '+': assert(!"bad option");
default: abort();
}
assert(argc==3);
n = atoi(argv[1]);
m = atoi(argv[2]);
+ assert(n > m);
+ if (best_to_set > 0) set_best(best_to_set);
prep();