#include <toolkits/ml_data_2/row_slicing_utilities.hpp>

Public Member Functions
	row_slicer (const std::shared_ptr< ml_metadata > &metadata, const std::vector< size_t > &columns_to_pick)

void	slice (sparse_vector &dest, const std::vector< ml_data_entry > &x_t, const std::vector< flexible_type > &x_u) const

void	slice (dense_vector &dest, const std::vector< ml_data_entry > &x_t, const std::vector< flexible_type > &x_u) const

void	slice (std::vector< flexible_type > &dest, const std::vector< ml_data_entry > &x_t, const std::vector< flexible_type > &x_u) const

size_t	num_dimensions ()

void	save (turi::oarchive &oarc) const

void	load (turi::iarchive &iarc)

Detailed Description

A slicer class that allows taking a row and splitting it up by columns.

Definition at line 25 of file row_slicing_utilities.hpp.

Constructor & Destructor Documentation

◆ row_slicer()

turi::v2::row_slicer::row_slicer	(	const std::shared_ptr< ml_metadata > &	metadata,
		const std::vector< size_t > &	columns_to_pick
	)

Constructor – provide ml_metadata class and a subset of column indices to use in this particular row. the columns_to_pick must be in sorted order.

If the chosen columns are from untranslated columns, then they must be all untranslated columns. In this case, only the flexible_type slice method below can be used. Otherwise, none of the columns must be untranslated, and either the sparse or dense slicing methods must be used.

Example:

sframe X = make_integer_testing_sframe( {"C0", "C1", "C2"}, { {1,2,3}, {4,5,6} } );

v2::ml_data data;

data.fill(X);

std::vector<v2::ml_data_entry> x_t; std::vector<flexible_type> x_u;

// Select that we want columns 1 and 2, but drop 0. v2::row_slicer s_c1_c2(data.metadata(), {1, 2} );

v2::dense_vector vd; v2::sparse_vector vs; std::vector<flexible_type> vu;

////////////////////////////////////////

auto it = data.get_iterator();

it.fill_observation(x_t); it.fill_untranslated_values(x_u);

s_c1_c2.slice(vd, x_t, x_u);

// There are 2 numerical columns included in this test ASSERT_EQ(vd.size(), 2); ASSERT_EQ(size_t(vd[0]), 2); // First row, 2nd column, by the slicer ASSERT_EQ(size_t(vd[1]), 3); // First row, 3nd column, by the slicer

s_c1_c2.slice(vs, x_t, x_u);

ASSERT_EQ(vd.nonZeros(), 2); ASSERT_EQ(size_t(vd.coeffRef(0)), 2); // First row, 2nd column, by the slicer ASSERT_EQ(size_t(vd.coeffRef(1)), 3); // First row, 2nd column, by the slicer

Example with untranslated columns: sframe X = make_integer_testing_sframe( {"C0", "C1", "C2"}, { {1,2,3}, {4,5,6} } );

v2::ml_data data;

// Set column C1 and C2 to be untranslated. data.set_data(X, "", {}, { {"C1", v2::ml_column_mode::UNTRANSLATED}, {"C2", v2::ml_column_mode::UNTRANSLATED} });

data.fill();

std::vector<v2::ml_data_entry> x_t; std::vector<flexible_type> x_u;

// Take the second and third columns v2::row_slicer s_c1_c2(data.metadata(), {1, 2} );

std::vector<flexible_type> vu;

auto it = data.get_iterator();

it.fill_observation(x_t); it.fill_untranslated_values(x_u);

s_c1_c2.slice(vu, x_t, x_u);

// There are 2 numerical columns included in this test ASSERT_EQ(vu.size(), 2); ASSERT_EQ(size_t(vu[0]), 2); // First row, 2nd column, by the slicer ASSERT_EQ(size_t(vu[1]), 3); // First row, 3nd column, by the slicer

++it;

Member Function Documentation

◆ load()

void turi::v2::row_slicer::load ( turi::iarchive & iarc )

Serialization – load.

◆ num_dimensions()

size_t turi::v2::row_slicer::num_dimensions ( )

inline

For translated row types, this returns the number of dimensions present. The eigen dense vectors will have this size after a call to slice above.

Definition at line 144 of file row_slicing_utilities.hpp.

◆ save()

void turi::v2::row_slicer::save ( turi::oarchive & oarc ) const

Serialization – save.

◆ slice() [1/3]

void turi::v2::row_slicer::slice	(	sparse_vector &	dest,
		const std::vector< ml_data_entry > &	x_t,
		const std::vector< flexible_type > &	x_u
	)		const

Take a row, represented by a pair of translated and untranslated columns (either of which may be empty), and use it to fill an eigen sparse vector with the result.

◆ slice() [2/3]

void turi::v2::row_slicer::slice	(	dense_vector &	dest,
		const std::vector< ml_data_entry > &	x_t,
		const std::vector< flexible_type > &	x_u
	)		const

Take a row, represented by a pair of translated and untranslated columns (either of which may be empty), and use it to fill an eigen dense vector with the result.

◆ slice() [3/3]

void turi::v2::row_slicer::slice	(	std::vector< flexible_type > &	dest,
		const std::vector< ml_data_entry > &	x_t,
		const std::vector< flexible_type > &	x_u
	)		const

Take a row, represented by a pair of translated and untranslated columns (either of which may be empty), and use it to fill an untranslated row with the result.

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

toolkits/ml_data_2/row_slicing_utilities.hpp

Public Member Functions