GridLAB-D: Random number generators

enum RANDOMTYPE

Enumerator:

RT_INVALID	used to flag bad random types
RT_DEGENERATE	degenerate distribution (Dirac delta function); double only_value
RT_UNIFORM	uniform distribution; double minimum_value, double maximum_value
RT_NORMAL	normal distribution; double arithmetic_mean, double arithmetic_stdev
RT_LOGNORMAL	log-normal distribution; double geometric_mean, double geometric_stdev
RT_BERNOULLI	Bernoulli distribution; double probability_of_observing_1.
RT_PARETO	Pareto distribution; double minimum_value, double gamma_scale.
RT_EXPONENTIAL	exponential distribution; double coefficient, double k_scale
RT_SAMPLED	sampled distribution; unsigned number_of_samples, double samples[n_samples]

Definition at line 13 of file random.h.

int random_apply	(	char *	group_expression,
		char *	property,
		RANDOMTYPE	type,
			...
	)

Apply a random number to property of a group of objects.

Returns:: the number of objects changed

Parameters:

group_expression	the group definition; see find_objects()
property	the property to update
type	the distribution type

Definition at line 295 of file random.c.

References find_first(), find_next(), find_objects(), FL_GROUP, and object_set_double_by_name().

double random_bernoulli ( double p )

Generate a Bernoulli distributed random number.

The probability density function for the Bernoulli distribution is

$Prob\left\{x=1\right\} = 1-Prob\left\{x=0\right\} = p$

Note that the Bernoulli distribution is a discrete distribution.

Parameters:

p	the probability of generating a 1

Definition at line 152 of file random.c.

References output_warning(), and randunit().

Referenced by random_test().

double random_degenerate ( double a )

Generate the same number always.

This is the Dirac delta function:

The probability density function for the Dirac delta function

$\varphi\left(a\right) = 1.0$

Definition at line 76 of file random.c.

References output_warning().

Referenced by random_test().

double random_exponential ( double lambda )

Generate an exponentially distributed random number.

The exponential probability density function is

$\varphi\left(x\right) = \left\{ \begin{array}{c c} \lambda e^{-\lambda x} & x \geq o \\ 0 & x < 0 \end{array} \right\}$

Parameters:

lambda

the rate parameter lambda

Definition at line 237 of file random.c.

References output_warning(), randunit(), and throw_exception().

Referenced by random_test().

double random_lognormal	(	double	gmu,
		double	gsigma
	)

Generate a log Gaussian distributed random number.

The log-normal probability density function is

$\varphi\left(x\right) = \frac{1}{\sqrt{2\pi}x\sigma}e^{\frac{\left(\ln x-\mu\right)^2}{2\sigma^2}}$

Parameters:

gmu	the geometric mean
gsigma	the geometric standard deviation

Definition at line 220 of file random.c.

References random_normal().

Referenced by random_test().

double random_normal	(	double	m,
		double	s
	)

Generate a Gaussian distributed random number.

The probability density function for the Gaussian (normal) distribution is

$\varphi\left(x\right) = \frac{1}{\sqrt{2\pi}\sigma}e^{\frac{\left(x-\mu\right)^2}{2\sigma^2}}$

Normally distributed random numbers are generated using the Box-Muller method:

    double random_normal(double m, double s)
    {
        double r, a, b;
        do { 
            a = 2*randunit()-1;
            b = 2*randunit()-1;
            r = a*a+b*b;
        } while (r>=1);
        return sqrt(-2*log(r)/r)*a*r*s+m;
    }

Parameters:

m	the mean of the distribution
s	the standard deviation of the distribution

Definition at line 133 of file random.c.

References output_warning(), PI, and randunit().

Referenced by random_lognormal(), and random_test().

double random_pareto	(	double	m,
		double	k
	)

Generate a Pareto distributed random number.

The Pareto distribution is one in which the probability of drawing a number less than x is proportional to x^k. The probability density function of the Pareto distribution is

$\varphi\left( x<k \right) = k \frac{m^k}{x^{k+1}} x \geq m$

The cumulative density function is

$\varphi\left( x<k \right) = 1-(\frac{m}{x})^k$

.

Parameters:

m	the minimum value
k	the k value

Definition at line 198 of file random.c.

References output_warning(), randunit(), and throw_exception().

Referenced by random_test().

double random_sampled	(	unsigned	n,
		double *	x
	)

Generate a number randomly sample uniformly from a list.

The probability that the value a is drawn from the sample is

$Prob\left\{x=a\right\} = \frac{1}{n}$

Note that the sampled distriution is a discrete distribution.

Parameters:

n	the number of samples in the list
x	the sample list

Definition at line 171 of file random.c.

References output_warning(), QNAN, randunit(), and throw_exception().

Referenced by random_test().

int random_test ( void )

Test random distributions.

To run the self-test, use the --randtest command-line argument. The test results are output to the file specified by the global_testoutputfile variable.

Returns:: number of failed tests

Definition at line 404 of file random.c.

References max, min, output_test(), output_warning(), random_bernoulli(), random_degenerate(), random_exponential(), random_lognormal(), random_normal(), random_pareto(), random_sampled(), random_uniform(), and randunit().

Referenced by cmdarg_load().

RANDOMTYPE random_type ( char * name )

Converts a distribution name to a RANDOMTYPE.

Todo:: Add some other distributions (e.g., beta, gamma, Cauchy, Weibull, Laplace) (ticket #56)

Parameters:

name

the name of the distribution

Definition at line 38 of file random.c.

References RT_BERNOULLI, RT_DEGENERATE, RT_EXPONENTIAL, RT_INVALID, RT_LOGNORMAL, RT_NORMAL, RT_PARETO, RT_SAMPLED, and RT_UNIFORM.

double random_uniform	(	double	a,
		double	b
	)

Generate a uniformly distributed random number.

The probability density function for the uniform distribution is

$\varphi\left(x\right) = \left\{ \begin{array}{c c} \frac{1}{b-a} & a \leq x < b \\ 0 & x<a ; x\geq b \end{array} \right\}$

Note that this uniform distribution includes a but does not include b.

Parameters:

a	the minimum number
b	the maximum number

Definition at line 98 of file random.c.

References output_warning(), and randunit().

Referenced by random_test().

double random_value	(	RANDOMTYPE	type,
			...
	)

Generate a random value.

Returns:: a double containing the random number

Parameters:

type

the type of distribution desired

Definition at line 318 of file random.c.

Random number generators
[GridLAB-D Core]

Detailed Description

Defines

Enumerations

Functions

Enumeration Type Documentation

Function Documentation


Defines
#define	QNAN sqrt(-1)
Enumerations
enum	RANDOMTYPE { RT_INVALID = -1, RT_DEGENERATE, RT_UNIFORM, RT_NORMAL, RT_LOGNORMAL, RT_BERNOULLI, RT_PARETO, RT_EXPONENTIAL, RT_SAMPLED }
Functions
int	random_apply (char group_expression, char property, RANDOMTYPE type,...)
	Apply a random number to property of a group of objects.
double	random_bernoulli (double p)
	Generate a Bernoulli distributed random number.
double	random_degenerate (double a)
	Generate the same number always.
double	random_exponential (double lambda)
	Generate an exponentially distributed random number.
int	random_init (void)
double	random_lognormal (double gmu, double gsigma)
	Generate a log Gaussian distributed random number.
double	random_normal (double m, double s)
	Generate a Gaussian distributed random number.
double	random_pareto (double m, double k)
	Generate a Pareto distributed random number.
double	random_sampled (unsigned n, double *x)
	Generate a number randomly sample uniformly from a list.
int	random_test (void)
	Test random distributions.
RANDOMTYPE	random_type (char *name)
	Converts a distribution name to a RANDOMTYPE.
double	random_uniform (double a, double b)
	Generate a uniformly distributed random number.
double	random_value (RANDOMTYPE type,...)
	Generate a random value.
double	randunit (void)

Random number generators [GridLAB-D Core]

Detailed Description

Defines

Enumerations

Functions

Enumeration Type Documentation

Function Documentation

Random number generators
[GridLAB-D Core]