Privugger Distributions¶

continuous module¶

class privugger.distributions.continuous.Beta(name, alpha=1, beta=1, num_elements=- 1, is_hyper_param=False)[source]¶

Bases: privugger.distributions.continuous.Continuous

Class for the Beta distribution

name¶

Type: String of the name of the random variable

alpha¶

Type: value for the alpha parameter. Default: 1

beta¶

Type: value for the beta parameter. Default: 1

num_elements¶

Type: int specifying number of RV’s

is_hyper_param¶

Type: Boolean specifying if this RV is used as a hyper parameter. Default: False

get_params()[source]¶

pymc3_dist(name, hypers)[source]¶

scipy_dist(name)[source]¶

class privugger.distributions.continuous.Exponential(name, lam=1, num_elements=- 1, is_hyper_param=False)[source]¶

Bases: privugger.distributions.continuous.Continuous

Class for the Exponential distribution

name¶

Type: String of the name of the random variable

lam¶

Type: value for the lambda parameter. Default: 1

num_elements¶

Type: int specifying number of RV’s

is_hyper_param¶

Type: Boolean specifying if this RV is used as a hyper parameter. Default: False

get_params()[source]¶

pymc3_dist(name, hypers)[source]¶

scipy_dist(name)[source]¶

class privugger.distributions.continuous.Normal(name, mu=0, std=1, num_elements=- 1, is_hyper_param=False)[source]¶

Bases: privugger.distributions.continuous.Continuous

Class for the Gaussian distribution

name¶

Type: String of the name of the random variable

mu¶

Type: value for the mean of the distribution. Default: 0

std¶

Type: value for the standard deviation. Default: 1

num_elements¶

Type: int specifying number of RV’s

is_hyper_param¶

Type: Boolean specifying if this RV is used as a hyper parameter. Default: False

get_params()[source]¶

pymc3_dist(name, hypers)[source]¶

scipy_dist(name)[source]¶

class privugger.distributions.continuous.Uniform(name, lower=0, upper=1, num_elements=- 1, is_hyper_param=False)[source]¶

Bases: privugger.distributions.continuous.Continuous

Class for the Uniform distribution

name¶

Type: String of the name of the random variable

lower¶

Type: int for the lower bound. Default: 0

upper¶

Type: int for the upper bound. Default: 1

num_elements¶

Type: int specifying number of RV’s

is_hyper_param¶

Type: Boolean specifying if this RV is used as a hyper parameter. Default: False

get_params()[source]¶

pymc3_dist(name, hypers)[source]¶

scipy_dist(name)[source]¶

discrete module¶

class privugger.distributions.discrete.Bernoulli(name, p=0.5, num_elements=- 1, is_hyper_param=False)[source]¶

Bases: privugger.distributions.discrete.Discrete

Class for the Bernoulli distribution

name¶

Type: String of the name of the random variable

p¶

Type: float value [0,1] giving the probability. Default: 0.5

num_elements¶

Type: int specifying number of RV’s

is_hyper_param¶

Type: Boolean specifying if this RV is used as a hyper parameter. Default: False

get_params()[source]¶

pymc3_dist(name, hypers)[source]¶

scipy_dist(name)[source]¶

class privugger.distributions.discrete.Binomial(name, n=2, p=0.5, num_elements=- 1, is_hyper_param=False)[source]¶

Bases: privugger.distributions.discrete.Discrete

Class for the Binomial distribution

name¶

Type: String of the name of the random variable

n¶

Type: int specifying the number of trials. Default: 2

p¶

Type: float value [0,1] giving the probability. Default: 0.5

num_elements¶

Type: int specifying number of RV’s

is_hyper_param¶

Type: Boolean specifying if this RV is used as a hyper parameter. Default: False

get_params()[source]¶

pymc3_dist(name, hypers)[source]¶

scipy_dist(name)[source]¶

class privugger.distributions.discrete.Categorical(name, p=None, num_elements=- 1, is_hyper_param=False)[source]¶

Bases: privugger.distributions.discrete.Discrete

Class for the Categorical distribution

name¶

Type: String of the name of the random variable

p¶

Type: Float list of probabilities

num_elements¶

Type: int specifying number of RV’s

is_hyper_param¶

Type: Boolean specifying if this RV is used as a hyper parameter. Default: False

get_params()[source]¶

pymc3_dist(name, hypers)[source]¶

scipy_dist(name)[source]¶

class privugger.distributions.discrete.Constant(name, val, num_elements=- 1, is_hyper_param=False)[source]¶

Bases: privugger.distributions.discrete.Discrete

Class for the Constant distribution

name¶

Type: String of the name of the random variable

val¶

Type: The constant value

num_elements¶

Type: int specifying number of RV’s

is_hyper_param¶

Type: Boolean specifying if this RV is used as a hyper parameter. Default: False

get_params()[source]¶

pymc3_dist(name, hypers)[source]¶

scipy_dist(name)[source]¶

class privugger.distributions.discrete.DiscreteUniform(name, lower=0, upper=1, num_elements=- 1, is_hyper_param=False)[source]¶

Bases: privugger.distributions.discrete.Discrete

Class for the Discrete Uniform distribution

name¶

Type: String of the name of the random variable

lower¶

Type: int value giving the lower bound of the values. Default: 0

upper¶

Type: ine value giving the upper bound of the values. Default: 1

num_elements¶

Type: int specifying number of RV’s

is_hyper_param¶

Type: Boolean specifying if this RV is used as a hyper parameter. Default: False

get_params()[source]¶

pymc3_dist(name, hypers)[source]¶

scipy_dist(name)[source]¶

class privugger.distributions.discrete.Geometric(p=0.5, num_elements=- 1, is_hyper_param=False)[source]¶

Bases: privugger.distributions.discrete.Discrete

Class for the Geometric distribution

name¶

Type: String of the name of the random variable

p¶

Type: float value [0,1] giving the probability. Default: 0.5

num_elements¶

Type: int specifying number of RV’s

is_hyper_param¶

Type: Boolean specifying if this RV is used as a hyper parameter. Default: False

get_params()[source]¶

pymc3_dist(name, hypers)[source]¶

scipy_dist(name)[source]¶