Commit eb9a2b34 authored by Alexander Wiebel's avatar Alexander Wiebel

[DOC] typos (grep and sed are so cool)

parent 245fc164
......@@ -80,7 +80,7 @@ const std::string WDataSetGP::getName() const
const std::string WDataSetGP::getDescription() const
{
return "Contains gaussian processes representing deterministic tracks.";
return "Contains Gaussian processes representing deterministic tracks.";
}
boost::shared_ptr< WPrototyped > WDataSetGP::getPrototype()
......
......@@ -50,7 +50,7 @@ public:
WDataSetGP();
/**
* Assembles a dataset of gaussian processes out of the deterministic tracts as well the
* Assembles a dataset of Gaussian processes out of the deterministic tracts as well the
* underlying tensor field.
*
* \param tracts The dataset containing the deterministic tracts
......@@ -71,7 +71,7 @@ public:
virtual ~WDataSetGP();
/**
* Defines a new mean function over the mean functions of all gaussian processes.
* Defines a new mean function over the mean functions of all Gaussian processes.
*
* \param p The position where to evaluate all mean functions
*
......
......@@ -36,8 +36,8 @@
class WFiber;
/**
* Represents a basic gaussian process with its mean- and covariance function. Basically this aims
* to implement a part of the gaussian process framework as presented by Wasserman et. al:
* Represents a basic Gaussian process with its mean- and covariance function. Basically this aims
* to implement a part of the Gaussian process framework as presented by Wasserman et. al:
* http://dx.doi.org/10.1016/j.neuroimage.2010.01.004
*/
class WGaussProcess
......@@ -45,7 +45,7 @@ class WGaussProcess
friend class WGaussProcessTest;
public:
/**
* Constructs a gaussian process out of a fiber with the help of underlying diffusion tensor
* Constructs a Gaussian process out of a fiber with the help of underlying diffusion tensor
* information.
*
* \param tractID One deterministic tractogram ID
......@@ -69,7 +69,7 @@ public:
*
* \param p The point where to evaluate the Gauss process.
*
* \return The mean value of this gaussian process at the point \e p.
* \return The mean value of this Gaussian process at the point \e p.
*/
double mean( const WPosition& p ) const;
......@@ -91,8 +91,8 @@ public:
WFiber generateTract() const;
/**
* As each gaussian process is associated with a WFiber it also hat the maximal segment length,
* used as width for the gaussian kernels around the base points.
* As each Gaussian process is associated with a WFiber it also hat the maximal segment length,
* used as width for the Gaussian kernels around the base points.
*
* \return Copy of the maximal segment length this Gauss process is associated with.
*/
......@@ -150,7 +150,7 @@ private:
double cov_d( const WPosition& p1, const WPosition& p2 ) const;
/**
* Covariance function of this gaussian process.
* Covariance function of this Gaussian process.
*
* \note The reason why this isn't realized as member is just simplicity. Maybe we have time to
* change this!
......@@ -163,7 +163,7 @@ private:
double cov( const WPosition& p1, const WPosition& p2 ) const;
/**
* The id of the tract inside the \ref WDataSetFibers this gaussian process is representing.
* The id of the tract inside the \ref WDataSetFibers this Gaussian process is representing.
* This is needed since the sample points of a tract will be needed for mean computation. (\f$
* S_f(p) \f$ will need all \f$ f_i \f$i)
*
......@@ -242,10 +242,10 @@ inline const Eigen::VectorXd& WGaussProcess::getCff1lProduct() const
namespace gauss
{
/**
* The inner product of two gaussian processes. See appendix A.3 of the Demian Wassermann paper.
* The inner product of two Gaussian processes. See appendix A.3 of the Demian Wassermann paper.
*
* \param p1 First gaussian process
* \param p2 Second gaussian process
* \param p1 First Gaussian process
* \param p2 Second Gaussian process
*
* \return The similarity of those two processes, aka inner product.
*/
......
......@@ -53,7 +53,7 @@ const std::string WMDetTract2GPConvert::getName() const
const std::string WMDetTract2GPConvert::getDescription() const
{
return "Converts deterministic tracts to gaussian processes as described in the paper of Wassermann: "
return "Converts deterministic tracts to Gaussian processes as described in the paper of Wassermann: "
"http://dx.doi.org/10.1016/j.neuroimage.2010.01.004";
}
......@@ -96,7 +96,7 @@ void WMDetTract2GPConvert::moduleMain()
{
continue;
}
boost::shared_ptr< WProgress > progress1 = boost::shared_ptr< WProgress >( new WProgress( "Converting tracts into gaussian processes.", tracts->size() ) ); // NOLINT line length
boost::shared_ptr< WProgress > progress1 = boost::shared_ptr< WProgress >( new WProgress( "Converting tracts into Gaussian processes.", tracts->size() ) ); // NOLINT line length
m_progress->addSubProgress( progress1 );
m_gpOC->updateData( boost::shared_ptr< WDataSetGP >( new WDataSetGP( tracts, tensors, m_shutdownFlag, progress1 ) ) );
progress1->finish();
......
......@@ -36,7 +36,7 @@
#include "../WDataSetGP.h"
/**
* Converts each deterministic tract to a gaussian process using the DTI information.
* Converts each deterministic tract to a Gaussian process using the DTI information.
* \ingroup modules
*/
class WMDetTract2GPConvert: public WModule
......@@ -99,7 +99,7 @@ protected:
private:
/**
* Input connector for the deterministic tract dataset which is going to be converted into
* gaussian processes.
* Gaussian processes.
*/
boost::shared_ptr< WModuleInputData< WDataSetFibers > > m_tractIC;
......
......@@ -64,7 +64,7 @@ const std::string WMDetTractClusteringGP::getDescription() const
void WMDetTractClusteringGP::connectors()
{
m_gpIC = WModuleInputData< WDataSetGP >::createAndAdd( shared_from_this(), "gpInput", "WDataSetGP providing the gaussian processes" );
m_gpIC = WModuleInputData< WDataSetGP >::createAndAdd( shared_from_this(), "gpInput", "WDataSetGP providing the Gaussian processes" );
m_dendOC = WModuleOutputData< WDendrogram >::createAndAdd( shared_from_this(), "dendrogramOutput", "WDendrogram as a result of this clustering" );
WModule::connectors();
......
......@@ -40,7 +40,7 @@
class WDendrogram;
/**
* Module for clustering gaussian processes which representing deterministic tracts.
* Module for clustering Gaussian processes which representing deterministic tracts.
*
* \ingroup modules
*/
......@@ -101,11 +101,11 @@ protected:
virtual void properties();
/**
* Computes the distant matrix for all pairs of gaussian processes.
* Computes the distant matrix for all pairs of Gaussian processes.
*
* \warning This function may leave an invalid matrix when the \ref m_shutdownFlag becomes true!
*
* \param dataSet The dataset of gaussian processes.
* \param dataSet The dataset of Gaussian processes.
*
* \return The similarity or also called distant matrix.
*/
......@@ -124,7 +124,7 @@ protected:
boost::shared_ptr< WDendrogram > computeDendrogram( size_t n );
/**
* Input Connector for the gaussian processes which are about to be clustered.
* Input Connector for the Gaussian processes which are about to be clustered.
*/
boost::shared_ptr< WModuleInputData< WDataSetGP > > m_gpIC;
......@@ -134,7 +134,7 @@ protected:
boost::shared_ptr< WModuleOutputData< WDendrogram > > m_dendOC;
/**
* Distant matrix of all pairs of gaussian processes. This is float to save more space!
* Distant matrix of all pairs of Gaussian processes. This is float to save more space!
*/
WMatrixSymFLT m_similarities;
......
......@@ -59,7 +59,7 @@ const std::string WMGpView::getName() const
const std::string WMGpView::getDescription() const
{
return "Displays gaussian processes. It is intended to display espically GP representing deterministic tracts.";
return "Displays Gaussian processes. It is intended to display espically GP representing deterministic tracts.";
}
void WMGpView::connectors()
......
......@@ -132,7 +132,7 @@ protected:
private:
/**
* Input connector for the gaussian proccesses.
* Input connector for the Gaussian proccesses.
*/
boost::shared_ptr< WModuleInputData< WDataSetGP > > m_gpIC;
......
......@@ -36,7 +36,7 @@
#include "../WGaussProcess.h"
/**
* Testsuite for the gaussian process class.
* Testsuite for the Gaussian process class.
*/
class WGaussProcessTest : public CxxTest::TestSuite
{
......@@ -160,7 +160,7 @@ public:
TS_ASSERT_DELTA( overlap, 0.5065, 0.003 );
}
// TODO(math): This is just about to understand what the outcome of small tracts along long tracts in terms of gaussian process similarity is, and
// TODO(math): This is just about to understand what the outcome of small tracts along long tracts in terms of Gaussian process similarity is, and
// can be removed when I understood this to full extent.
//
// void testSmallTractAlongLongTract( void )
......@@ -235,7 +235,7 @@ private:
boost::shared_ptr< WDataSetDTI > m_emptyDTIDataSet;
/**
* Dummy tract dataset for gaussian process generation.
* Dummy tract dataset for Gaussian process generation.
*/
boost::shared_ptr< WDataSetFibers > m_tracts;
......
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