qdtsne::Status< num_dim_, Index_, Float_ > Class Template Reference

Status of the t-SNE iterations. More...

#include <Status.hpp>

Public Member Functions
int	iteration () const
int	max_iterations () const
size_t	num_observations () const
void	run (Float_ *Y, int limit)
void	run (Float_ *Y)

Detailed Description

template<int num_dim_, typename Index_, typename Float_>
class qdtsne::Status< num_dim_, Index_, Float_ >

Status of the t-SNE iterations.

Template Parameters

num_dim_	Number of dimensions in the t-SNE embedding.
Index_	Integer type for the neighbor indices.
Float_	Floating-point type for the distances.

This class holds the precomputed structures required to perform the t-SNE iterations. Instances should not be constructed directly but instead created by initialize().

Member Function Documentation

iteration()

template<int num_dim_, typename Index_ , typename Float_ >

int qdtsne::Status< num_dim_, Index_, Float_ >::iteration ( ) const

inline

Returns

The number of iterations performed on this object so far.

max_iterations()

template<int num_dim_, typename Index_ , typename Float_ >

int qdtsne::Status< num_dim_, Index_, Float_ >::max_iterations ( ) const

inline

Returns

The maximum number of iterations. This can be modified to run() the algorithm for more iterations.

num_observations()

template<int num_dim_, typename Index_ , typename Float_ >

size_t qdtsne::Status< num_dim_, Index_, Float_ >::num_observations ( ) const

inline

Returns

The number of observations in the dataset.

run() [1/2]

template<int num_dim_, typename Index_ , typename Float_ >

void qdtsne::Status< num_dim_, Index_, Float_ >::run ( Float_ *  Y )

inline

Run the algorithm to the maximum number of iterations. If run() has already been invoked with an iteration limit, this method will only perform the remaining iterations required for iteration() to reach max_iter(). If iteration() is already greater than max_iter(), this method is a no-op.

Parameters

[in,out]

Y

Pointer to a array containing a column-major matrix with number of rows and columns equal to num_dim_ and num_observations(), respectively. Each row corresponds to a dimension of the embedding while each column corresponds to an observation. On input, this should contain the initial location of each observation; on output, it is updated to the t-SNE location at the specified number of iterations.

run() [2/2]

template<int num_dim_, typename Index_ , typename Float_ >

void qdtsne::Status< num_dim_, Index_, Float_ >::run ( Float_ *  Y, int  limit  )

inline

Run the algorithm to the specified number of iterations. This can be invoked repeatedly with increasing limit to run the algorithm incrementally.

Parameters

[in,out]	Y	Pointer to a array containing a column-major matrix with number of rows and columns equal to num_dim_ and num_observations(), respectively. Each row corresponds to a dimension of the embedding while each column corresponds to an observation. On input, this should contain the initial location of each observation; on output, it is updated to the t-SNE location at the specified number of iterations.
	limit	Number of iterations to run up to. The actual number of iterations performed will be the difference between limit and iteration(), i.e., iteration() will be equal to limit on completion. limit may be greater than max_iterations(), to run the algorithm for more iterations than specified during construction of this Status object.

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The documentation for this class was generated from the following file:

• qdtsne/Status.hpp