Fix _NOSCAL algo typos in the man (#70)

diff --git a/api/nlopt.3 b/api/nlopt.3
index 3234093af8921fbeebf60a5cf2a5dc047843e571..709d48b3ff12dddbd66a0df7afd7281d5e486829 100644 (file)
--- a/api/nlopt.3
+++ b/api/nlopt.3
@@ -316,15 +316,15 @@ DIRECT-L search algorithm by Jones et al. as modified by Gablonsky et
 al. to be more weighted towards local search.  Does not support
 unconstrainted optimization.  There are also several other variants of
 the DIRECT algorithm that are supported:
-.BR NLOPT_GLOBAL_DIRECT ,
+.BR NLOPT_GN_DIRECT ,
 which is the original DIRECT algorithm;
-.BR NLOPT_GLOBAL_DIRECT_L_RAND ,
+.BR NLOPT_GN_DIRECT_L_RAND ,
 a slightly randomized version of DIRECT-L that may be better in
 high-dimensional search spaces;
-.BR NLOPT_GLOBAL_DIRECT_NOSCAL ,
-.BR NLOPT_GLOBAL_DIRECT_L_NOSCAL ,
+.BR NLOPT_GN_DIRECT_NOSCAL ,
+.BR NLOPT_GN_DIRECT_L_NOSCAL ,
 and
-.BR NLOPT_GLOBAL_DIRECT_L_RAND_NOSCAL ,
+.BR NLOPT_GN_DIRECT_L_RAND_NOSCAL ,
 which are versions of DIRECT where the dimensions are not rescaled to
 a unit hypercube (which means that dimensions with larger bounds are
 given more weight).

diff --git a/api/nlopt_minimize.3 b/api/nlopt_minimize.3
index 1d30d0f2b08749033d44b9304376301c2b2f1459..6c1c10863606fd7b0d6702d8e8f91689d03ce6cd 100644 (file)
--- a/api/nlopt_minimize.3
+++ b/api/nlopt_minimize.3
@@ -204,15 +204,15 @@ DIRECT-L search algorithm by Jones et al. as modified by Gablonsky et
 al. to be more weighted towards local search.  Does not support
 unconstrainted optimization.  There are also several other variants of
 the DIRECT algorithm that are supported:
-.BR NLOPT_GLOBAL_DIRECT ,
+.BR NLOPT_GN_DIRECT ,
 which is the original DIRECT algorithm;
-.BR NLOPT_GLOBAL_DIRECT_L_RAND ,
+.BR NLOPT_GN_DIRECT_L_RAND ,
 a slightly randomized version of DIRECT-L that may be better in
 high-dimensional search spaces;
-.BR NLOPT_GLOBAL_DIRECT_NOSCAL ,
-.BR NLOPT_GLOBAL_DIRECT_L_NOSCAL ,
+.BR NLOPT_GN_DIRECT_NOSCAL ,
+.BR NLOPT_GN_DIRECT_L_NOSCAL ,
 and
-.BR NLOPT_GLOBAL_DIRECT_L_RAND_NOSCAL ,
+.BR NLOPT_GN_DIRECT_L_RAND_NOSCAL ,
 which are versions of DIRECT where the dimensions are not rescaled to
 a unit hypercube (which means that dimensions with larger bounds are
 given more weight).

diff --git a/api/nlopt_minimize_constrained.3 b/api/nlopt_minimize_constrained.3
index b4c9f229b547f553534701604c4ef149a41d20f5..09eb205d93077824ce64c26d57ccea2ca9af5846 100644 (file)
--- a/api/nlopt_minimize_constrained.3
+++ b/api/nlopt_minimize_constrained.3
@@ -306,15 +306,15 @@ DIRECT-L search algorithm by Jones et al. as modified by Gablonsky et
 al. to be more weighted towards local search.  Does not support
 unconstrainted optimization.  There are also several other variants of
 the DIRECT algorithm that are supported:
-.BR NLOPT_GLOBAL_DIRECT ,
+.BR NLOPT_GN_DIRECT ,
 which is the original DIRECT algorithm;
-.BR NLOPT_GLOBAL_DIRECT_L_RAND ,
+.BR NLOPT_GN_DIRECT_L_RAND ,
 a slightly randomized version of DIRECT-L that may be better in
 high-dimensional search spaces;
-.BR NLOPT_GLOBAL_DIRECT_NOSCAL ,
-.BR NLOPT_GLOBAL_DIRECT_L_NOSCAL ,
+.BR NLOPT_GN_DIRECT_NOSCAL ,
+.BR NLOPT_GN_DIRECT_L_NOSCAL ,
 and
-.BR NLOPT_GLOBAL_DIRECT_L_RAND_NOSCAL ,
+.BR NLOPT_GN_DIRECT_L_RAND_NOSCAL ,
 which are versions of DIRECT where the dimensions are not rescaled to
 a unit hypercube (which means that dimensions with larger bounds are
 given more weight).

diff --git a/direct/README b/direct/README
index 785fb0328e0c4ca2cfb6904acce3220d2e6f7ddd..49464121ea4447bcae5d1378f48965e4862e10e4 100644 (file)
--- a/direct/README
+++ b/direct/README
@@ -21,8 +21,8 @@ algorithm, as described in:
        of the DIRECT algorithm," J. Global Optimization 21 (1),
        p. 27-37 (2001).
 
-Both the original Jones algorithm (NLOPT_GLOBAL_DIRECT) and the
-Gablonsky modified version (NLOPT_GLOBAL_DIRECT_L) are implemented
+Both the original Jones algorithm (NLOPT_GN_DIRECT) and the
+Gablonsky modified version (NLOPT_GN_DIRECT_L) are implemented
 and available from the NLopt interface.  The Gablonsky version
 makes the algorithm "more biased towards local search" so that it
 is more efficient for functions without too many local minima.