X-Git-Url: http://info.iut-bm.univ-fcomte.fr/pub/gitweb/simgrid.git/blobdiff_plain/85e1d2c205ca99512b48bceca0f16677a401e233..2558c8c0eb206ff353cb88672f5a90cd0e2562d3:/src/kernel/lmm/lagrange.cpp

diff --git a/src/kernel/lmm/lagrange.cpp b/src/kernel/lmm/lagrange.cpp
index 8d6cb06ae6..fdab111a34 100644
--- a/src/kernel/lmm/lagrange.cpp
+++ b/src/kernel/lmm/lagrange.cpp
@@ -1,4 +1,4 @@
-/* Copyright (c) 2007-2018. The SimGrid Team. All rights reserved.          */
+/* Copyright (c) 2007-2019. The SimGrid Team. All rights reserved.          */
 
 /* This program is free software; you can redistribute it and/or modify it
  * under the terms of the license (GNU LGPL) which comes with this package. */
@@ -8,6 +8,7 @@
  * "ssh://username@scm.gforge.inria.fr/svn/memo/people/pvelho/lagrange/ppf.ps".
  */
 #include "src/kernel/lmm/maxmin.hpp"
+#include "src/surf/surf_interface.hpp"
 #include "xbt/log.h"
 #include "xbt/sysdep.h"
 
@@ -206,7 +207,7 @@ void Lagrange::lagrange_solve()
     /* Improve the value of lambda_i */
     for (Constraint& cnst : active_constraint_set) {
       XBT_DEBUG("Working on cnst (%p)", &cnst);
-      cnst.new_lambda = dichotomy(cnst.lambda, partial_diff_lambda, cnst, dichotomy_min_error);
+      cnst.new_lambda = dichotomy(cnst.lambda, cnst, dichotomy_min_error);
       XBT_DEBUG("Updating lambda : cnst->lambda (%p) : %1.20f -> %1.20f", &cnst, cnst.lambda, cnst.new_lambda);
       cnst.lambda = cnst.new_lambda;
 
@@ -216,7 +217,7 @@ void Lagrange::lagrange_solve()
       obj = new_obj;
     }
 
-    /* Now computes the values of each variable (\rho) based on the values of \lambda and \mu. */
+    /* Now computes the values of each variable (@rho) based on the values of @lambda and @mu. */
     XBT_DEBUG("-------------- Check convergence ----------");
     overall_modification = 0;
     for (Variable& var : variable_set) {
@@ -254,17 +255,16 @@ void Lagrange::lagrange_solve()
 
 /*
  * Returns a double value corresponding to the result of a dichotomy process 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.
+ * 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 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 minimum error tolerated
  *
  * @return a double corresponding to the result of the dichotomy process
  */
-double Lagrange::dichotomy(double init, double diff(double, const Constraint&), const Constraint& cnst,
-                           double min_error)
+double Lagrange::dichotomy(double init, const Constraint& cnst, double min_error)
 {
   double min = init;
   double max = init;
@@ -282,15 +282,15 @@ double Lagrange::dichotomy(double init, double diff(double, const Constraint&),
 
   overall_error = 1;
 
-  diff_0 = diff(1e-16, cnst);
+  diff_0 = partial_diff_lambda(1e-16, cnst);
   if (diff_0 >= 0) {
     XBT_CDEBUG(surf_lagrange_dichotomy, "returning 0.0 (diff = %e)", diff_0);
     XBT_OUT();
     return 0.0;
   }
 
-  double min_diff = diff(min, cnst);
-  double max_diff = diff(max, cnst);
+  double min_diff = partial_diff_lambda(min, cnst);
+  double max_diff = partial_diff_lambda(max, cnst);
 
   while (overall_error > min_error) {
     XBT_CDEBUG(surf_lagrange_dichotomy, "[min, max] = [%1.20f, %1.20f] || diffmin, diffmax = %1.20f, %1.20f", min, max,
@@ -300,7 +300,7 @@ double Lagrange::dichotomy(double init, double diff(double, const Constraint&),
       if (min == max) {
         XBT_CDEBUG(surf_lagrange_dichotomy, "Decreasing min");
         min      = min / 2.0;
-        min_diff = diff(min, cnst);
+        min_diff = partial_diff_lambda(min, cnst);
       } else {
         XBT_CDEBUG(surf_lagrange_dichotomy, "Decreasing max");
         max      = min;
@@ -310,7 +310,7 @@ double Lagrange::dichotomy(double init, double diff(double, const Constraint&),
       if (min == max) {
         XBT_CDEBUG(surf_lagrange_dichotomy, "Increasing max");
         max      = max * 2.0;
-        max_diff = diff(max, cnst);
+        max_diff = partial_diff_lambda(max, cnst);
       } else {
         XBT_CDEBUG(surf_lagrange_dichotomy, "Increasing min");
         min      = max;
@@ -327,7 +327,7 @@ double Lagrange::dichotomy(double init, double diff(double, const Constraint&),
                   min, max - min, min_diff, max_diff);
         break;
       }
-      middle_diff = diff(middle, cnst);
+      middle_diff = partial_diff_lambda(middle, cnst);
 
       if (middle_diff < 0) {
         XBT_CDEBUG(surf_lagrange_dichotomy, "Increasing min");
@@ -400,19 +400,21 @@ double Lagrange::partial_diff_lambda(double lambda, const Constraint& cnst)
   return diff;
 }
 
-/** \brief Attribute the value bound to var->bound.
+/** @brief Attribute the value bound to var->bound.
  *
- *  \param func_fpi  inverse of the partial differential of f (f prime inverse, (f')^{-1})
+ *  @param f    function (f)
+ *  @param fp   partial differential of f (f prime, (f'))
+ *  @param fpi  inverse of the partial differential of f (f prime inverse, (f')^{-1})
  *
  *  Set default functions to the ones passed as parameters.
  */
-void Lagrange::set_default_protocol_function(double (*func_f)(const Variable& var, double x),
-                                             double (*func_fp)(const Variable& var, double x),
-                                             double (*func_fpi)(const Variable& var, double x))
+void Lagrange::set_default_protocol_function(double (*f)(const Variable& var, double x),
+                                             double (*fp)(const Variable& var, double x),
+                                             double (*fpi)(const Variable& var, double x))
 {
-  Lagrange::func_f   = func_f;
-  Lagrange::func_fp  = func_fp;
-  Lagrange::func_fpi = func_fpi;
+  func_f   = f;
+  func_fp  = fp;
+  func_fpi = fpi;
 }
 
 double (*Lagrange::func_f)(const Variable&, double);
@@ -423,9 +425,9 @@ double (*Lagrange::func_fpi)(const Variable&, double);
 /* NOTE for Reno: all functions consider the network coefficient (alpha) equal to 1. */
 
 /*
- * For Vegas: $f(x) = \alpha D_f\ln(x)$
- * Therefore: $fp(x) = \frac{\alpha D_f}{x}$
- * Therefore: $fpi(x) = \frac{\alpha D_f}{x}$
+ * For Vegas: $f(x) = @alpha D_f@ln(x)$
+ * Therefore: $fp(x) = @frac{@alpha D_f}{x}$
+ * Therefore: $fpi(x) = @frac{@alpha D_f}{x}$
  */
 double func_vegas_f(const Variable& var, double x)
 {
@@ -446,9 +448,9 @@ double func_vegas_fpi(const Variable& var, double x)
 }
 
 /*
- * For Reno:  $f(x) = \frac{\sqrt{3/2}}{D_f} atan(\sqrt{3/2}D_f x)$
- * Therefore: $fp(x)  = \frac{3}{3 D_f^2 x^2+2}$
- * Therefore: $fpi(x)  = \sqrt{\frac{1}{{D_f}^2 x} - \frac{2}{3{D_f}^2}}$
+ * For Reno:  $f(x) = @frac{@sqrt{3/2}}{D_f} atan(@sqrt{3/2}D_f x)$
+ * Therefore: $fp(x)  = @frac{3}{3 D_f^2 x^2+2}$
+ * Therefore: $fpi(x)  = @sqrt{@frac{1}{{D_f}^2 x} - @frac{2}{3{D_f}^2}}$
  */
 double func_reno_f(const Variable& var, double x)
 {
@@ -477,7 +479,7 @@ double func_reno_fpi(const Variable& var, double x)
 }
 
 /* Implementing new Reno-2
- * For Reno-2:  $f(x)   = U_f(x_f) = \frac{{2}{D_f}}*ln(2+x*D_f)$
+ * For Reno-2:  $f(x)   = U_f(x_f) = @frac{{2}{D_f}}*ln(2+x*D_f)$
  * Therefore:   $fp(x)  = 2/(Weight*x + 2)
  * Therefore:   $fpi(x) = (2*Weight)/x - 4
  */