added flags for linesearch

3 files changed, 76 insertions, 50 deletions

diff --git a/CGOptimization.lua b/CGOptimization.lua
index 6eee58c..31d5e89 100644
--- a/CGOptimization.lua
+++ b/CGOptimization.lua
@@ -4,22 +4,35 @@ function CG:__init(...)
    require 'liblbfgs'
    parent.__init(self, ...)
    xlua.unpack_class(self, {...},
-      'CGOptimization', nil,
-      {arg='maxEvaluation', type='number', 
-       help='maximum nb of function evaluations per pass (0 = no max)', default=0},
-      {arg='maxIterations', type='number', 
-       help='maximum nb of iterations per pass (0 = no max)', default=0},
-      {arg='maxLineSearch', type='number', 
-       help='maximum nb of steps in line search', default=20},
-      {arg='sparsity', type='number', 
-       help='sparsity coef (Orthantwise C)', default=0},
-      {arg='parallelize', type='number', 
-       help='parallelize onto N cores (experimental!)', default=1}
-   )
+                     'CGOptimization', nil,
+                     {arg='maxEvaluation', type='number',
+                      help='maximum nb of function evaluations per pass (0 = no max)', default=0},
+                     {arg='maxIterations', type='number',
+                      help='maximum nb of iterations per pass (0 = no max)', default=0},
+                     {arg='maxLineSearch', type='number',
+                      help='maximum nb of steps in line search', default=20},
+                     {arg='sparsity', type='number',
+                      help='sparsity coef (Orthantwise C)', default=0},
+                     {arg='linesearch', type='string',
+                      help='type of linesearch used: morethuente, armijo, wolfe, strong_wolfe',
+                      default='wolfe'},
+                     {arg='parallelize', type='number',
+                      help='parallelize onto N cores (experimental!)', default=1}
+                  )
+   local linesearch = 2
+   if not (self.linesearch == 'wolfe') then
+      if self.linesearch == 'morethuente' then
+         linesearch = 0
+      elseif self.linesearch == 'armijo' then
+         linesearch = 1
+      elseif self.linesearch == 'strong_wolfe' then
+         linesearch = 3
+      end
+   end
    -- init CG state
    cg.init(self.parameters, self.gradParameters,
            self.maxEvaluation, self.maxIterations, self.maxLineSearch,
-           self.sparsity, self.verbose)
+           self.sparsity, linesearch, self.verbose)
 end
 
 function CG:optimize()
diff --git a/LBFGSOptimization.lua b/LBFGSOptimization.lua
index 9fd0a3f..53dfe70 100644
--- a/LBFGSOptimization.lua
+++ b/LBFGSOptimization.lua
@@ -4,22 +4,35 @@ function LBFGS:__init(...)
    require 'liblbfgs'
    parent.__init(self, ...)
    xlua.unpack_class(self, {...},
-      'LBFGSOptimization', nil,
-      {arg='maxEvaluation', type='number', 
-       help='maximum nb of function evaluations per pass (0 = no max)', default=0},
-      {arg='maxIterations', type='number', 
-       help='maximum nb of iterations per pass (0 = no max)', default=0},
-      {arg='maxLineSearch', type='number', 
-       help='maximum nb of steps in line search', default=20},
-      {arg='sparsity', type='number', 
-       help='sparsity coef (Orthantwise C)', default=0},
-      {arg='parallelize', type='number', 
-       help='parallelize onto N cores (experimental!)', default=1}
-   )
+                     'LBFGSOptimization', nil,
+                     {arg='maxEvaluation', type='number',
+                      help='maximum nb of function evaluations per pass (0 = no max)', default=0},
+                     {arg='maxIterations', type='number',
+                      help='maximum nb of iterations per pass (0 = no max)', default=0},
+                     {arg='maxLineSearch', type='number',
+                      help='maximum nb of steps in line search', default=20},
+                     {arg='sparsity', type='number',
+                      help='sparsity coef (Orthantwise C)', default=0},
+                     {arg='linesearch', type='string',
+                      help='type of linesearch used: morethuente, armijo, wolfe, strong_wolfe',
+                      default='wolfe'},
+                     {arg='parallelize', type='number',
+                      help='parallelize onto N cores (experimental!)', default=1}
+                  )
+   local linesearch = 2
+   if not (self.linesearch == 'wolfe') then
+      if self.linesearch == 'morethuente' then
+         linesearch = 0
+      elseif self.linesearch == 'armijo' then
+         linesearch = 1
+      elseif self.linesearch == 'strong_wolfe' then
+         linesearch = 3
+      end
+   end
    -- init LBFGS state
    lbfgs.init(self.parameters, self.gradParameters,
               self.maxEvaluation, self.maxIterations, self.maxLineSearch,
-              self.sparsity, self.verbose)
+              self.sparsity, linesearch, self.verbose)
 end
 
 function LBFGS:optimize()
diff --git a/lbfgs.c b/lbfgs.c
index d2f22fb..a877c2d 100644
--- a/lbfgs.c
+++ b/lbfgs.c
@@ -945,7 +945,7 @@ int cg(
 
     /* compute 'momentum' term B = (g1'*g1)/(g0'*g0) */
     vecdot(&g1dot, g, g, n);
-    B = g1dot / g0dot; 
+    B = g1dot / g0dot;
     /* store val for next iteration */
     g0dot = g1dot;
 
@@ -956,9 +956,9 @@ int cg(
     /* add the 'momentum' term */
     /* d_1 = -g_1 + B*d_0 */
     vecadd(d, dp, B, n);
-    
+
     /* increment the number of iterations */
-    ++k; 
+    ++k;
 
     /*
       Now the search direction d is ready. We try step = 1 first.
@@ -1787,15 +1787,15 @@ static lbfgsfloatval_t evaluate(void *instance,
 }
 
 static int cg_progress(void *instance,
-                    const lbfgsfloatval_t *x,
-                    const lbfgsfloatval_t *g,
-                    const lbfgsfloatval_t fx,
-                    const lbfgsfloatval_t xnorm,
-                    const lbfgsfloatval_t gnorm,
-                    const lbfgsfloatval_t step,
-                    int n,
-                    int k,
-                    int ls)
+                       const lbfgsfloatval_t *x,
+                       const lbfgsfloatval_t *g,
+                       const lbfgsfloatval_t fx,
+                       const lbfgsfloatval_t xnorm,
+                       const lbfgsfloatval_t gnorm,
+                       const lbfgsfloatval_t step,
+                       int n,
+                       int k,
+                       int ls)
 {
   nIteration = k;
   if (verbose > 1) {
@@ -1808,15 +1808,15 @@ static int cg_progress(void *instance,
 }
 
 static int lbfgs_progress(void *instance,
-                    const lbfgsfloatval_t *x,
-                    const lbfgsfloatval_t *g,
-                    const lbfgsfloatval_t fx,
-                    const lbfgsfloatval_t xnorm,
-                    const lbfgsfloatval_t gnorm,
-                    const lbfgsfloatval_t step,
-                    int n,
-                    int k,
-                    int ls)
+                          const lbfgsfloatval_t *x,
+                          const lbfgsfloatval_t *g,
+                          const lbfgsfloatval_t fx,
+                          const lbfgsfloatval_t xnorm,
+                          const lbfgsfloatval_t gnorm,
+                          const lbfgsfloatval_t step,
+                          int n,
+                          int k,
+                          int ls)
 {
   nIteration = k;
   if (verbose > 1) {
@@ -1884,10 +1884,10 @@ int init(lua_State *L) {
   maxEval = lua_tonumber(L,3);
   lbfgs_param.max_iterations = lua_tonumber(L, 4);
   lbfgs_param.max_linesearch = lua_tonumber(L, 5);
-  lbfgs_param.linesearch = LBFGS_LINESEARCH_BACKTRACKING;
-  lbfgs_param.orthantwise_c = lua_tonumber(L, 6);
+  lbfgs_param.orthantwise_c  = lua_tonumber(L, 6);
+  lbfgs_param.linesearch     = lua_tonumber(L, 7);
   /* get verbose level */
-  verbose = lua_tonumber(L,7);
+  verbose = lua_tonumber(L,8);
 
   /* done */
   return 0;