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132 lines
2.5 KiB
Python
132 lines
2.5 KiB
Python
# Copyright (c) 2012, 2013 Ricardo Andrade
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# Licensed under the BSD 3-clause license (see LICENSE.txt)
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import numpy as np
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from scipy import stats
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import scipy as sp
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import pylab as pb
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from GPy.util.univariate_Gaussian import std_norm_pdf,std_norm_cdf,inv_std_norm_cdf
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class GPTransformation(object):
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"""
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Link function class for doing non-Gaussian likelihoods approximation
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:param Y: observed output (Nx1 numpy.darray)
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.. note:: Y values allowed depend on the likelihood_function used
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"""
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def __init__(self):
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pass
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class Identity(GPTransformation):
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"""
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.. math::
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g(f) = f
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"""
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#def transf(self,mu):
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# return mu
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def transf(self,f):
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return f
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def dtransf_df(self,f):
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return 1.
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def d2transf_df2(self,f):
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return 0
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class Probit(GPTransformation):
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"""
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.. math::
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g(f) = \\Phi^{-1} (mu)
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"""
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#def transf(self,mu):
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# return inv_std_norm_cdf(mu)
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def transf(self,f):
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return std_norm_cdf(f)
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def dtransf_df(self,f):
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return std_norm_pdf(f)
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def d2transf_df2(self,f):
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return -f * std_norm_pdf(f)
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class Log(GPTransformation):
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"""
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.. math::
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g(f) = \\log(\\mu)
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"""
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#def transf(self,mu):
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# return np.log(mu)
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def transf(self,f):
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return np.exp(f)
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def dtransf_df(self,f):
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return np.exp(f)
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def d2transf_df2(self,f):
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return np.exp(f)
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class Log_ex_1(GPTransformation):
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"""
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.. math::
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g(f) = \\log(\\exp(\\mu) - 1)
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"""
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#def transf(self,mu):
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# """
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# function: output space -> latent space
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# """
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# return np.log(np.exp(mu) - 1)
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def transf(self,f):
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"""
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function: latent space -> output space
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"""
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return np.log(1.+np.exp(f))
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def dtransf_df(self,f):
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return np.exp(f)/(1.+np.exp(f))
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def d2transf_df2(self,f):
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aux = np.exp(f)/(1.+np.exp(f))
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return aux*(1.-aux)
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class Reciprocal(GPTransformation):
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def transf(sefl,f):
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return 1./f
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def dtransf_df(self,f):
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return -1./f**2
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def d2transf_df2(self,f):
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return 2./f**3
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class Heaviside(GPTransformation):
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"""
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.. math::
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g(f) = I_{x \\in A}
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"""
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def transf(self,f):
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#transformation goes here
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return np.where(f>0, 1, 0)
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def dtransf_df(self,f):
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raise NotImplementedError, "This function is not differentiable!"
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def d2transf_df2(self,f):
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raise NotImplementedError, "This function is not differentiable!"
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