test12.cpp File Reference

---

Detailed Description

Test of indii::ml::aux::selfTreeDensity.

This test:

• creates a random multivariate Gaussian mixture,
• samples from this mixture and constructs kernel density approximation,
• calculates the density at the support points of the kernel density approximation, comparing the results of indii::ml::aux::selfTreeDensity and indii::ml::aux::dualTreeDensity.

Results are as follows:

Mixture mean
[2](0.0981163,-0.732858)
Mixture covariance
[2,2]((0.837146,-0.470933),(-0.470933,2.16876))
Sample mean
[2](0.0862835,-0.705297)
Sample covariance
[2,2]((0.799899,-0.368035),(-0.368035,1.88599))
Kernel density mixture mean
[2](0.0862835,-0.705297)
Kernel density mixture covariance
[2,2]((0.799899,-0.368035),(-0.368035,1.88599))
Kernel density mixture sample mean
[2](0.123679,-0.728515)
Kernel density mixture sample covariance
[2,2]((0.758673,-0.382827),(-0.382827,1.89692))
Kernel density mixture importance sample mean
[2](0.129972,-0.710245)
Kernel density mixture importance sample covariance
[2,2]((0.730353,-0.300594),(-0.300594,1.51821))

Definition in file test12.cpp.

Go to the source code of this file.

Functions
aux::GaussianPdf	createRandomGaussian (const unsigned int M, const double minMean=-1.0, const double maxMean=1.0, const double minCov=-1.0, const double maxCov=1.0)
	Create random Gaussian distribution.
int	main (int argc, char *argv[])
	Run tests.
Variables
unsigned int	M = 2
	Dimensionality of the distribution.
unsigned int	COMPONENTS = 4
	Number of components in the Gaussian mixture.
unsigned int	P = 5000
	Number of samples to take.
unsigned int	RES = 200
	Resolution of plots.
double	H = 0.25 * aux::hopt(M,P)
	Bandwidth.

---

Function Documentation

aux::GaussianPdf createRandomGaussian	(	const unsigned int	M,
		const double	minMean = -1.0,
		const double	maxMean = 1.0,
		const double	minCov = -1.0,
		const double	maxCov = 1.0
	)

Create random Gaussian distribution.

Parameters:

	M	Dimensionality of the Gaussian.
	minMean	Minimum value of any component of the mean.
	maxMean	Maximum value of any component of the mean.
	minCov	Minimum value of any component of the covariance.
	maxCov	Maximum value of any component of the covariance.

Returns:

Gaussian with given dimensionality, with mean and covariance randomly generated uniformly from within the given bounds.

Definition at line 75 of file test12.cpp.

int main	(	int	argc,
		char *	argv[]
	)

Run tests.

Definition at line 104 of file test12.cpp.

---

Variable Documentation

unsigned int COMPONENTS = 4

Number of components in the Gaussian mixture.

Definition at line 45 of file test12.cpp.

double H = 0.25 * aux::hopt(M,P)

Bandwidth.

Definition at line 60 of file test12.cpp.

unsigned int M = 2

Dimensionality of the distribution.

Definition at line 40 of file test12.cpp.

unsigned int P = 5000

Number of samples to take.

Definition at line 50 of file test12.cpp.

unsigned int RES = 200

Resolution of plots.

Definition at line 55 of file test12.cpp.

---