Class for data visualization. More...

#include <Visualization.hpp>

Public Member Functions
	Visualization (bool shared_session=true, bool keep_temp_files=false)

	Visualization (Data< T > &sample, bool shared_session=true, bool keep_temp_files=false)

void	setTerminal (const std::string &terminal)

void	setSample (Data< T > &sample)
	Set sample to be visualized. More...

void	setTitle (std::string title)
	Set plot title. More...

void	setStyle (std::string style)
	Set plot style. (points, lines, etc.) More...

std::string	execute_command (const std::string &cmd, bool fetch_configs=true)

std::string	plot1DRegresion (int x=0, bool save=false, double scale=1.0, const std::string &title="", const std::string &format="svg", const std::string &x_label="x", const std::string &y_label="y")
	Plot the data as a regression dataset with points values in the y-axis. More...

std::string	plot1DRegresionHyperplane (int x, Solution s, bool save=false, double scale=1.0, const std::string &title="", const std::string &format="svg", const std::string &x_label="x", const std::string &y_label="y")
	Plot the data as a regression dataset with points values in the y-axis alongside with a regressor solution. More...

std::string	plot2D (int x=0, int y=1, bool save=false, double scale=1.0, const std::string &title="", const std::string &format="svg", const std::string &x_label="x", const std::string &y_label="y")
	Plot the selected features in 2D. More...

std::string	plot2D (mltk::Point< double > x, mltk::Point< double > y, bool save=false, double scale=1.0, const std::string &title="", const std::string &format="svg", const std::string &x_label="x", const std::string &y_label="y")

std::string	plot2DwithHyperplane (int x, int y, Solution w, bool save=false, double scale=1.0, const std::string &title="", const std::string &format="svg", const std::string &x_label="x", const std::string &y_label="y")
	Plot the data in 2D with the hyperplane in solution generated by a classifier. More...

std::string	plot2DRegresion (int x=0, int y=1, bool save=false, double scale=1.0, const std::string &title="", const std::string &format="svg", const std::string &x_label="x", const std::string &y_label="y", const std::string &z_label="z")
	Plot the data as a regression dataset with points values in the z-axis. More...

std::string	plot2DRegresionHyperplane (int x, int y, Solution s, bool save=false, double scale=1.0, const std::string &title="", const std::string &format="svg", const std::string &x_label="x", const std::string &y_label="y", const std::string &z_label="z")
	Plot the data as a regression dataset with points values in the z-axis alongside with a regressor solution. More...

std::string	plot3D (int x=0, int y=1, int z=2, bool save=false, double scale=1.0, const std::string &title="", const std::string &format="svg", const std::string &x_label="x", const std::string &y_label="y", const std::string &z_label="z")
	Plot the selected features in 3D. More...

std::string	plot3D (mltk::Point< double > x, mltk::Point< double > y, mltk::Point< double > z, bool save=false, double scale=1.0, const std::string &title="", const std::string &format="svg", const std::string &x_label="x", const std::string &y_label="y", const std::string &z_label="z")

std::string	plot3DwithHyperplane (int x, int y, int z, Solution w, bool save=false, double scale=1.0, const std::string &title="", const std::string &format="svg", const std::string &x_label="x", const std::string &y_label="y", const std::string &z_label="z")
	Plot the data in 2D with separated by the hyperplane in the solution. More...

template<class Learner >
std::string	plotDecisionSurface2D (Learner &learner, int x=0, int y=1, bool is_trained=true, size_t grid_dim=50, bool save=false, double scale=1.0, const std::string &title="", const std::string &format="svg", const std::string &x_label="x", const std::string &y_label="y")
	Plot the decision boundary of a classifier with the data points above it. More...

Static Public Member Functions
static void	cmd (const std::string &command)
	Execute a script on gnuplot. More...

Detailed Description

template<typename T = double>
class mltk::visualize::Visualization< T >

Class for data visualization.

Member Function Documentation

◆ cmd()

template<typename T >

void mltk::visualize::Visualization< T >::cmd ( const std::string & command )

static

Execute a script on gnuplot.

Parameters

command script to be executed.

◆ plot1DRegresion()

template<typename T >

std::string mltk::visualize::Visualization< T >::plot1DRegresion	(	int	x = `0`,
		bool	save = `false`,
		double	scale = `1.0`,
		const std::string &	title = `""`,
		const std::string &	format = `"svg"`,
		const std::string &	x_label = `"x"`,
		const std::string &	y_label = `"y"`
	)

Plot the data as a regression dataset with points values in the y-axis.

Parameters

x	Feature to be used in the x-axis.
save	If true, save the plot to disk, otherwise it shows the plot on the screen.
scale	Scale factor for all axis of the plot.
title	Plot title.
format	Plot output format if is set to save to disk.
x_label	x-axis label.
y_label	y-axis label.

Returns: string containing the gnuplot script generated by the plot function.

◆ plot1DRegresionHyperplane()

template<typename T >

std::string mltk::visualize::Visualization< T >::plot1DRegresionHyperplane	(	int	x,
		Solution	s,
		bool	save = `false`,
		double	scale = `1.0`,
		const std::string &	title = `""`,
		const std::string &	format = `"svg"`,
		const std::string &	x_label = `"x"`,
		const std::string &	y_label = `"y"`
	)

Plot the data as a regression dataset with points values in the y-axis alongside with a regressor solution.

Parameters

x	Feature to be used in the x-axis.
s	Learner solution with the hyperplane to be plotted.
save	If true, save the plot to disk, otherwise it shows the plot on the screen.
scale	Scale factor for all axis of the plot.
title	Plot title.
format	Plot output format if is set to save to disk.
x_label	x-axis label.
y_label	y-axis label.

Returns: string containing the gnuplot script generated by the plot function.

◆ plot2D()

template<typename T >

std::string mltk::visualize::Visualization< T >::plot2D	(	int	x = `0`,
		int	y = `1`,
		bool	save = `false`,
		double	scale = `1.0`,
		const std::string &	title = `""`,
		const std::string &	format = `"svg"`,
		const std::string &	x_label = `"x"`,
		const std::string &	y_label = `"y"`
	)

Plot the selected features in 2D.

Parameters

x	Feature to be used in the x-axis.
y	Feature to be used in the y-axis.
save	If true, save the plot to disk, otherwise it shows the plot on the screen.
scale	Scale factor for all axis of the plot.
title	Plot title.
format	Plot output format if is set to save to disk.
x_label	x-axis label.
y_label	y-axis label.

Returns: string containing the gnuplot script generated by the plot function.

◆ plot2DRegresion()

template<typename T >

std::string mltk::visualize::Visualization< T >::plot2DRegresion	(	int	x = `0`,
		int	y = `1`,
		bool	save = `false`,
		double	scale = `1.0`,
		const std::string &	title = `""`,
		const std::string &	format = `"svg"`,
		const std::string &	x_label = `"x"`,
		const std::string &	y_label = `"y"`,
		const std::string &	z_label = `"z"`
	)

Plot the data as a regression dataset with points values in the z-axis.

Parameters

x	Feature to be used in the x-axis.
y	Feature to be used in the y-axis.
save	If true, save the plot to disk, otherwise it shows the plot on the screen.
scale	Scale factor for all axis of the plot.
title	Plot title.
format	Plot output format if is set to save to disk.
x_label	x-axis label.
y_label	y-axis label.
z_label	z-axis label.

Returns: string containing the gnuplot script generated by the plot function.

◆ plot2DRegresionHyperplane()

template<typename T >

std::string mltk::visualize::Visualization< T >::plot2DRegresionHyperplane	(	int	x,
		int	y,
		Solution	s,
		bool	save = `false`,
		double	scale = `1.0`,
		const std::string &	title = `""`,
		const std::string &	format = `"svg"`,
		const std::string &	x_label = `"x"`,
		const std::string &	y_label = `"y"`,
		const std::string &	z_label = `"z"`
	)

Plot the data as a regression dataset with points values in the z-axis alongside with a regressor solution.

Parameters

x	Feature to be used in the x-axis.
y	Feature to be used in the y-axis.
s	Learner solution with the hyperplane to be plotted.
save	If true, save the plot to disk, otherwise it shows the plot on the screen.
scale	Scale factor for all axis of the plot.
title	Plot title.
format	Plot output format if is set to save to disk.
x_label	x-axis label.
y_label	y-axis label.
z_label	z-axis label.

Returns: string containing the gnuplot script generated by the plot function.

◆ plot2DwithHyperplane()

template<typename T >

std::string mltk::visualize::Visualization< T >::plot2DwithHyperplane	(	int	x,
		int	y,
		Solution	w,
		bool	save = `false`,
		double	scale = `1.0`,
		const std::string &	title = `""`,
		const std::string &	format = `"svg"`,
		const std::string &	x_label = `"x"`,
		const std::string &	y_label = `"y"`
	)

Plot the data in 2D with the hyperplane in solution generated by a classifier.

Parameters

x	Feature to be used in the x-axis.
y	Feature to be used in the y-axis.
w	Learner solution with the hyperplane to be plotted.
save	If true, save the plot to disk, otherwise it shows the plot on the screen.
scale	Scale factor for all axis of the plot.
title	Plot title.
format	Plot output format if is set to save to disk.
x_label	x-axis label.
y_label	y-axis label.

Returns: string containing the gnuplot script generated by the plot function.

◆ plot3D()

template<typename T >

std::string mltk::visualize::Visualization< T >::plot3D	(	int	x = `0`,
		int	y = `1`,
		int	z = `2`,
		bool	save = `false`,
		double	scale = `1.0`,
		const std::string &	title = `""`,
		const std::string &	format = `"svg"`,
		const std::string &	x_label = `"x"`,
		const std::string &	y_label = `"y"`,
		const std::string &	z_label = `"z"`
	)

Plot the selected features in 3D.

Parameters

x	Feature to be used in the x-axis.
y	Feature to be used in the y-axis.
z	Feature to be used in the z-axis.
save	If true, save the plot to disk, otherwise it shows the plot on the screen.
scale	Scale factor for all axis of the plot.
title	Plot title.
format	Plot output format if is set to save to disk.
x_label	x-axis label.
y_label	y-axis label.
z_label	z-axis label.

Returns: string containing the gnuplot script generated by the plot function.

◆ plot3DwithHyperplane()

template<typename T >

std::string mltk::visualize::Visualization< T >::plot3DwithHyperplane	(	int	x,
		int	y,
		int	z,
		Solution	w,
		bool	save = `false`,
		double	scale = `1.0`,
		const std::string &	title = `""`,
		const std::string &	format = `"svg"`,
		const std::string &	x_label = `"x"`,
		const std::string &	y_label = `"y"`,
		const std::string &	z_label = `"z"`
	)

Plot the data in 2D with separated by the hyperplane in the solution.

Parameters

x	Feature to be used in the x-axis.
y	Feature to be used in the y-axis.
z	Feature to be used in the z-axis.
w	Learner solution with the hyperplane to be plotted.
save	If true, save the plot to disk, otherwise it shows the plot on the screen.
scale	Scale factor for all axis of the plot.
title	Plot title.
format	Plot output format if is set to save to disk.
x_label	x-axis label.
y_label	y-axis label.
z_label	z-axis label.

Returns: string containing the gnuplot script generated by the plot function.

◆ plotDecisionSurface2D()

template<typename T >

template<class Learner >

std::string mltk::visualize::Visualization< T >::plotDecisionSurface2D	(	Learner &	learner,
		int	x = `0`,
		int	y = `1`,
		bool	is_trained = `true`,
		size_t	grid_dim = `50`,
		bool	save = `false`,
		double	scale = `1.0`,
		const std::string &	title = `""`,
		const std::string &	format = `"svg"`,
		const std::string &	x_label = `"x"`,
		const std::string &	y_label = `"y"`
	)

Plot the decision boundary of a classifier with the data points above it.

Template Parameters

Learner Classifier wrapper type.

Parameters

learner	Classifier for decision boundary generation.
x	Feature to be used in the x-axis.
y	Feature to be used in the y-axis.
is_trained	If the classifier is not trained, the method will call the train method.
grid_dim	Dimensions for the decision boundary grid. The plot has better resolution with bigger values, but it takes more time to generate the plot.
save	If true, save the plot to disk, otherwise it shows the plot on the screen.
scale	Scale factor for all axis of the plot.
title	Plot title.
format	Plot output format if is set to save to disk.
x_label	x-axis label.
y_label	y-axis label.

Returns: string containing the gnuplot script generated by the plot function.

◆ setSample()

template<typename T >

void mltk::visualize::Visualization< T >::setSample ( Data< T > & sample )

Set sample to be visualized.

Parameters

sample samples for visualization.

Returns: void

◆ setStyle()

template<typename T >

void mltk::visualize::Visualization< T >::setStyle ( std::string style )

Set plot style. (points, lines, etc.)

Parameters

style Style to be set.

Returns: void

◆ setTitle()

template<typename T >

void mltk::visualize::Visualization< T >::setTitle ( std::string title )

Set plot title.

Parameters

title Plot title.

Returns: void

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

Visualization.hpp

Public Member Functions

Static Public Member Functions

Detailed Description

template<typename T = double> class mltk::visualize::Visualization< T >

Member Function Documentation

◆ cmd()

◆ plot1DRegresion()

◆ plot1DRegresionHyperplane()

◆ plot2D()

◆ plot2DRegresion()

◆ plot2DRegresionHyperplane()

◆ plot2DwithHyperplane()

◆ plot3D()

◆ plot3DwithHyperplane()

◆ plotDecisionSurface2D()

◆ setSample()

◆ setStyle()

◆ setTitle()

template<typename T = double>
class mltk::visualize::Visualization< T >