From: franklin.jonathan_at_[hidden]
Date: 2008-05-15 00:29:21
Author: jfranklin
Date: 2008-05-15 00:29:19 EDT (Thu, 15 May 2008)
New Revision: 45381
URL: http://svn.boost.org/trac/boost/changeset/45381
Log:
Changed size_t to std::size_t.
Text files modified:
sandbox/cluster/boost/algorithm/cluster/cluster_data.hpp | 2 +-
sandbox/cluster/boost/algorithm/cluster/dbscan.hpp | 8 ++++----
sandbox/cluster/boost/algorithm/cluster/k_means.hpp | 6 +++---
3 files changed, 8 insertions(+), 8 deletions(-)
Modified: sandbox/cluster/boost/algorithm/cluster/cluster_data.hpp
==============================================================================
--- sandbox/cluster/boost/algorithm/cluster/cluster_data.hpp (original)
+++ sandbox/cluster/boost/algorithm/cluster/cluster_data.hpp 2008-05-15 00:29:19 EDT (Thu, 15 May 2008)
@@ -52,7 +52,7 @@
value_type & back() { return m_pClusters->back(); }
value_type const & back() const { return m_pClusters->back(); }
- size_t size() const { return m_pClusters->size(); }
+ std::size_t size() const { return m_pClusters->size(); }
bool empty() const { return m_pClusters->empty(); }
private:
Modified: sandbox/cluster/boost/algorithm/cluster/dbscan.hpp
==============================================================================
--- sandbox/cluster/boost/algorithm/cluster/dbscan.hpp (original)
+++ sandbox/cluster/boost/algorithm/cluster/dbscan.hpp 2008-05-15 00:29:19 EDT (Thu, 15 May 2008)
@@ -52,7 +52,7 @@
dbscan(NTupleIterT const & begin,
NTupleIterT const & end,
DistanceT const & eps,
- size_t min_points,
+ std::size_t min_points,
DistFunT const & d)
{
// Concept check.
@@ -68,7 +68,7 @@
ntuple_nodes tuples;
// Initialize algorithm.
- //size_t num_elems = 0;
+ //std::size_t num_elems = 0;
for(NTupleIterT it = begin; it != end; ++it)
{
//++num_elems;
@@ -106,7 +106,7 @@
// Mark entire neighborhood as part of the current cluster.
it->cluster = cluster_num;
cur_cluster.push_back(it->tuple);
- for (size_t n = 0; n < seeds.size(); ++n)
+ for (std::size_t n = 0; n < seeds.size(); ++n)
{
seeds[n]->cluster = cluster_num;
cur_cluster.push_back(seeds[n]->tuple);
@@ -124,7 +124,7 @@
if (results.size() >= min_points)
{
- for (size_t n = 0; n < results.size(); ++n)
+ for (std::size_t n = 0; n < results.size(); ++n)
{
if (results[n]->cluster < 1) // Not assigned to cluster yet.
{
Modified: sandbox/cluster/boost/algorithm/cluster/k_means.hpp
==============================================================================
--- sandbox/cluster/boost/algorithm/cluster/k_means.hpp (original)
+++ sandbox/cluster/boost/algorithm/cluster/k_means.hpp 2008-05-15 00:29:19 EDT (Thu, 15 May 2008)
@@ -136,12 +136,12 @@
typedef NTupleIter::value_type PointType;
typedef PointType::value_type AttributeType; //For the c funtion test, it will be a double type
const DistanceType knumOfPoints = last - first; //The n variable in the C function
- const size_t knDimension = PointType::size(); //The m variable in the C function
+ const std::size_t knDimension = PointType::size(); //The m variable in the C function
AttributeType** ppData = new AttributeType* [knumOfPoints];
AttributeType** centroids = new AttributeType* [k];
//Pre-allocate the result array
- for(size_t nCentroid = 0; nCentroid < k; nCentroid++)
+ for(std::size_t nCentroid = 0; nCentroid < k; nCentroid++)
{
centroids[nCentroid] = new AttributeType[knDimension];
}
@@ -161,7 +161,7 @@
typedef KMeansCluster<PointType> KMeansClusterType;
KMeansClustering< KMeansClusterType > clustering;
- for(size_t nCentroid = 0; nCentroid < k; nCentroid++)
+ for(std::size_t nCentroid = 0; nCentroid < k; nCentroid++)
{
KMeansClusterType cluster;