+ if (XBT_LOG_ISENABLED(surf_lagrange, xbt_log_priority_debug)) {
+ lmm_print(sys);
+ }
+}
+
+/*
+ * Returns a double value corresponding to the result of a dichotomy proccess with
+ * respect to a given variable/constraint (\mu in the case of a variable or \lambda in
+ * case of a constraint) and a initial value init.
+ *
+ * @param init initial value for \mu or \lambda
+ * @param diff a function that computes the differential of with respect a \mu or \lambda
+ * @param var_cnst a pointer to a variable or constraint
+ * @param min_erro a minimun error tolerated
+ *
+ * @return a double correponding to the result of the dichotomyal process
+ */
+double dichotomy(double init, double diff(double, void *), void *var_cnst,
+ double min_error)
+{
+ double min, max;
+ double overall_error;
+ double middle;
+ double min_diff, max_diff, middle_diff;
+ double diff_0 = 0.0;
+ min = max = init;
+
+ XBT_IN;
+
+ if (init == 0.0) {
+ min = max = 0.5;
+ }
+
+ min_diff = max_diff = middle_diff = 0.0;
+ overall_error = 1;
+
+ if ((diff_0 = diff(1e-16, var_cnst)) >= 0) {
+ CDEBUG1(surf_lagrange_dichotomy, "====> returning 0.0 (diff = %e)",
+ diff_0);
+ return 0.0;
+ }
+
+ CDEBUG1(surf_lagrange_dichotomy,
+ "====> not detected positive diff in 0 (%e)", diff_0);
+
+ while (overall_error > min_error) {
+
+ min_diff = diff(min, var_cnst);
+ max_diff = diff(max, var_cnst);
+
+ CDEBUG2(surf_lagrange_dichotomy,
+ "DICHOTOMY ===> min = %1.20f , max = %1.20f", min, max);
+ CDEBUG2(surf_lagrange_dichotomy,
+ "DICHOTOMY ===> diffmin = %1.20f , diffmax = %1.20f", min_diff,
+ max_diff);
+
+ if (min_diff > 0 && max_diff > 0) {
+ if (min == max) {
+ CDEBUG0(surf_lagrange_dichotomy, "Decreasing min");
+ min = min / 2.0;
+ } else {
+ CDEBUG0(surf_lagrange_dichotomy, "Decreasing max");
+ max = min;
+ }
+ } else if (min_diff < 0 && max_diff < 0) {
+ if (min == max) {
+ CDEBUG0(surf_lagrange_dichotomy, "Increasing max");
+ max = max * 2.0;
+ } else {
+ CDEBUG0(surf_lagrange_dichotomy, "Increasing min");
+ min = max;
+ }
+ } else if (min_diff < 0 && max_diff > 0) {
+ middle = (max + min) / 2.0;
+ middle_diff = diff(middle, var_cnst);
+
+ if (max != 0.0 && min != 0.0) {
+ overall_error = fabs(min - max) / max;
+ }
+
+ if (middle_diff < 0) {
+ min = middle;
+ } else if (middle_diff > 0) {
+ max = middle;
+ } else {
+ CWARN0(surf_lagrange_dichotomy,
+ "Found an optimal solution with 0 error!");
+ overall_error = 0;
+ return middle;
+ }
+
+ } else if (min_diff == 0) {
+ return min;
+ } else if (max_diff == 0) {
+ return max;
+ } else if (min_diff > 0 && max_diff < 0) {
+ CWARN0(surf_lagrange_dichotomy,
+ "The impossible happened, partial_diff(min) > 0 && partial_diff(max) < 0");
+ } else {
+ CWARN2(surf_lagrange_dichotomy,
+ "diffmin (%1.20f) or diffmax (%1.20f) are something I don't know, taking no action.",
+ min_diff, max_diff);
+ abort();
+ }
+ }
+
+ XBT_OUT;
+
+ CDEBUG1(surf_lagrange_dichotomy, "====> returning %e",
+ (min + max) / 2.0);
+ return ((min + max) / 2.0);
+}
+
+/*
+ *
+ */
+double partial_diff_mu(double mu, void *param_var)
+{
+ double mu_partial = 0.0;
+ double sigma_mu = 0.0;
+ lmm_variable_t var = (lmm_variable_t) param_var;
+ int i;
+ XBT_IN;
+ //compute sigma_i
+ for (i = 0; i < var->cnsts_number; i++)
+ sigma_mu += (var->cnsts[i].constraint)->lambda;
+
+ //compute sigma_i + mu_i
+ sigma_mu += mu;
+
+ //use auxiliar function passing (sigma_i + mu_i)
+ mu_partial = diff_aux(var, sigma_mu);
+
+ //add the RTT limit
+ mu_partial += var->bound;
+
+ XBT_OUT;
+ return mu_partial;
+}
+
+/*
+ *
+ */
+double partial_diff_lambda(double lambda, void *param_cnst)
+{
+
+ int i;
+ xbt_swag_t elem_list = NULL;
+ lmm_element_t elem = NULL;
+ lmm_variable_t var = NULL;
+ lmm_constraint_t cnst = (lmm_constraint_t) param_cnst;
+ double lambda_partial = 0.0;
+ double sigma_i = 0.0;
+
+ XBT_IN;
+ elem_list = &(cnst->element_set);
+
+ CDEBUG1(surf_lagrange_dichotomy,"Computting diff of cnst (%p)", cnst);
+
+ xbt_swag_foreach(elem, elem_list) {
+ var = elem->variable;
+ if (var->weight <= 0)
+ continue;
+
+ //initilize de sumation variable
+ sigma_i = 0.0;
+
+ //compute sigma_i of variable var
+ for (i = 0; i < var->cnsts_number; i++) {
+ sigma_i += (var->cnsts[i].constraint)->lambda;