Source code for GPy.core.mapping

# Copyright (c) 2013,2014, GPy authors (see AUTHORS.txt).
# Copyright (c) 2015, James Hensman
# Licensed under the BSD 3-clause license (see LICENSE.txt)

import sys
from .parameterization import Parameterized
import numpy as np

[docs]class Mapping(Parameterized): """ Base model for shared mapping behaviours """ def __init__(self, input_dim, output_dim, name='mapping'): self.input_dim = input_dim self.output_dim = output_dim super(Mapping, self).__init__(name=name)
[docs] def f(self, X): raise NotImplementedError
[docs] def gradients_X(self, dL_dF, X): raise NotImplementedError
[docs] def update_gradients(self, dL_dF, X): raise NotImplementedError
[docs] def to_dict(self): raise NotImplementedError
def _save_to_input_dict(self): input_dict = {} input_dict["input_dim"] = self.input_dim input_dict["output_dim"] = self.output_dim input_dict["name"] = self.name return input_dict
[docs] @staticmethod def from_dict(input_dict): """ Instantiate an object of a derived class using the information in input_dict (built by the to_dict method of the derived class). More specifically, after reading the derived class from input_dict, it calls the method _build_from_input_dict of the derived class. Note: This method should not be overrided in the derived class. In case it is needed, please override _build_from_input_dict instate. :param dict input_dict: Dictionary with all the information needed to instantiate the object. """ import copy input_dict = copy.deepcopy(input_dict) mapping_class = input_dict.pop('class') input_dict["name"] = str(input_dict["name"]) import GPy mapping_class = eval(mapping_class) return mapping_class._build_from_input_dict(mapping_class, input_dict)
@staticmethod def _build_from_input_dict(mapping_class, input_dict): return mapping_class(**input_dict)
[docs]class Bijective_mapping(Mapping): """ This is a mapping that is bijective, i.e. you can go from X to f and also back from f to X. The inverse mapping is called g(). """ def __init__(self, input_dim, output_dim, name='bijective_mapping'): super(Bijective_mapping, self).__init__(name=name)
[docs] def g(self, f): """Inverse mapping from output domain of the function to the inputs.""" raise NotImplementedError