Service Distributions

class pyJMT.Cox(lambda0, lambda1, p0)

Bases: object

An Coxian Distribution.

Attributes:

lambda0 (float): The lambda0 of the distribution. lambda1 (float): The lambda1 of the distribution. p0 (float): The p0 of the distribution.

class pyJMT.Det(k)

Bases: object

A Deterministic Distribution.

Attributes:

k (float): The k of the distribution.

class pyJMT.Disabled

Bases: object

A Disabled service distribution.

class pyJMT.Erlang(lambda_value, k)

Bases: object

An Erlang Distribution.

Attributes:

lambda_value (float): The lambda of the distribution. k (int): The k of the distribution.

static fitMeanAndOrder(mean, order)

Fits the parameters of the distribution given the mean and the order.

Parameters:

mean (float): The mean of the distribution. order (int): The order of the distribution.

Returns:

Erlang: An Erlang distribution fitted to the given parameters.

static fitMeanAndSCV(mean, scv)

Fits the parameters of the distribution given the mean and the squared coefficient of variation.

Parameters:

mean (float): The mean of the distribution. scv (float): The squared coefficient of variation of the distribution.

Returns:

Erlang: An Erlang distribution fitted to the given parameters.

class pyJMT.Exp(lambda_value)

Bases: object

An Exponential Distribution.

Attributes:

lambda_value (float): The lambda of the distribution.

class pyJMT.Gamma(alpha, theta)

Bases: object

An Gamma Distribution.

Attributes:

alpha (float): The alpha of the distribution. theta (float): The theta of the distribution.

class pyJMT.HyperExp(p, lambda1, lambda2)

Bases: object

An hyperexponential Distribution.

Attributes:

p (float): The p of the distribution. lambda1 (float): The lambda1 of the distribution. lambda2 (float): The lambda2 of the distribution.

class pyJMT.Lognormal(mu, sigma)

Bases: object

An Lognormal Distribution.

Attributes:

mu (float): The mu of the distribution. sigma (float): The sigma of the distribution.

class pyJMT.Normal(mean, standardDeviation)

Bases: object

A Normal Distribution.

Attributes:

mean (float): The mean of the distribution. standard deviation (float): The standard deviation of the distribution.

class pyJMT.Pareto(alpha, k)

Bases: object

A Pareto Distribution.

Attributes:

mu (float): The mu of the distribution. sigma (float): The sigma of the distribution.

class pyJMT.Replayer(fileName)

Bases: object

A class for replaying data from a file.

Attributes:

fileName (str): The path to the file to replay.

class pyJMT.Uniform(min, max)

Bases: object

A Uniform Distribution.

Attributes:

min (float): The min of the distribution. max (float): The max of the distribution.

class pyJMT.Weibull(lambda_value, k)

Bases: object

A Weibull Distribution.

Attributes:

lambda_value (float): The lambda of the distribution. k (float): The k of the distribution.

class pyJMT.ZeroServiceTime

Bases: object

A Zero Service time service distribution.