gpflow.mean_functions

gpflow.mean_functions.Additive

class gpflow.mean_functions.Additive(*args: Any, **kwargs: Any)[source]

Bases: gpflow.mean_functions.MeanFunction

Attributes
parameters
trainable_parameters

Methods

__call__(X)

Call self as a function.

gpflow.mean_functions.Constant

class gpflow.mean_functions.Constant(*args: Any, **kwargs: Any)[source]

Bases: gpflow.mean_functions.MeanFunction

Attributes
parameters
trainable_parameters

Methods

__call__(X)

Call self as a function.

gpflow.mean_functions.Identity

class gpflow.mean_functions.Identity(*args: Any, **kwargs: Any)[source]

Bases: gpflow.mean_functions.Linear

y_i = x_i

Attributes
A
b
parameters
trainable_parameters

Methods

__call__(X)

Call self as a function.

gpflow.mean_functions.Linear

class gpflow.mean_functions.Linear(*args: Any, **kwargs: Any)[source]

Bases: gpflow.mean_functions.MeanFunction

y_i = A x_i + b

Attributes
parameters
trainable_parameters

Methods

__call__(X)

Call self as a function.

__init__(A=None, b=None)[source]

A is a matrix which maps each element of X to Y, b is an additive constant.

If X has N rows and D columns, and Y is intended to have Q columns, then A must be [D, Q], b must be a vector of length Q.

gpflow.mean_functions.MeanFunction

class gpflow.mean_functions.MeanFunction(*args, **kwargs)[source]

Bases: gpflow.base.Module

The base mean function class. To implement a mean function, write the __call__ method. This takes a tensor X and returns a tensor m(X). In accordance with the GPflow standard, each row of X represents one datum, and each row of Y is computed independently for each row of X.

MeanFunction classes can have parameters, see the Linear class for an example.

Attributes
parameters
trainable_parameters

Methods

__call__(X)

Call self as a function.

Parameters
  • args (Any) –

  • kwargs (Any) –

gpflow.mean_functions.Product

class gpflow.mean_functions.Product(*args: Any, **kwargs: Any)[source]

Bases: gpflow.mean_functions.MeanFunction

Attributes
parameters
trainable_parameters

Methods

__call__(X)

Call self as a function.

gpflow.mean_functions.SwitchedMeanFunction

class gpflow.mean_functions.SwitchedMeanFunction(*args: Any, **kwargs: Any)[source]

Bases: gpflow.mean_functions.MeanFunction

This class enables to use different (independent) mean_functions respective to the data ‘label’. We assume the ‘label’ is stored in the extra column of X.

Attributes
parameters
trainable_parameters

Methods

__call__(X)

Call self as a function.

gpflow.mean_functions.Zero

class gpflow.mean_functions.Zero(*args: Any, **kwargs: Any)[source]

Bases: gpflow.mean_functions.Constant

Attributes
parameters
trainable_parameters

Methods

__call__(X)

Call self as a function.