apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-05-09 12:02:38 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

domain and trtansformations namespace prettyfying

Browse source
This commit is contained in:
Max Zwiessele 2013-10-11 17:26:04 +01:00
parent 780daac03e
commit 2018368d8d
5 changed files with 36 additions and 41 deletions
Download patch file Download diff file Expand all files Collapse all files

26
GPy/core/transformations.py
View file

@ -3,10 +3,10 @@
import numpy as np
from GPy.core.domains import POSITIVE, NEGATIVE, BOUNDED
from GPy.core.domains import _POSITIVE,_NEGATIVE, _BOUNDED
import sys
import weakref
lim_val = -np.log(sys.float_info.epsilon)
_lim_val = -np.log(sys.float_info.epsilon)
class Transformation(object):
domain = None
@ -29,13 +29,13 @@ class Transformation(object):
raise NotImplementedError
class Logexp(Transformation):
domain = POSITIVE
domain = _POSITIVE
def f(self, x):
return np.where(x>lim_val, x, np.log(1. + np.exp(x)))
return np.where(x>_lim_val, x, np.log(1. + np.exp(x)))
def finv(self, f):
return np.where(f>lim_val, f, np.log(np.exp(f) - 1.))
return np.where(f>_lim_val, f, np.log(np.exp(f) - 1.))
def gradfactor(self, f):
return np.where(f>lim_val, 1., 1 - np.exp(-f))
return np.where(f>_lim_val, 1., 1 - np.exp(-f))
def initialize(self, f):
if np.any(f < 0.):
print "Warning: changing parameters to satisfy constraints"
@ -44,7 +44,7 @@ class Logexp(Transformation):
return '+ve'
class NegativeLogexp(Transformation):
domain = NEGATIVE
domain = _NEGATIVE
logexp = Logexp()
def f(self, x):
return -self.logexp.f(x) # np.log(1. + np.exp(x))
@ -62,7 +62,7 @@ class LogexpClipped(Logexp):
min_bound = 1e-10
log_max_bound = np.log(max_bound)
log_min_bound = np.log(min_bound)
domain = POSITIVE
domain = _POSITIVE
_instances = []
def __new__(cls, lower=1e-6, *args, **kwargs):
if cls._instances:
@ -97,9 +97,9 @@ class LogexpClipped(Logexp):
class Exponent(Transformation):
# TODO: can't allow this to go to zero, need to set a lower bound. Similar with negative Exponent below. See old MATLAB code.
domain = POSITIVE
domain = _POSITIVE
def f(self, x):
return np.where(x<lim_val, np.where(x>-lim_val, np.exp(x), np.exp(-lim_val)), np.exp(lim_val))
return np.where(x<_lim_val, np.where(x>-_lim_val, np.exp(x), np.exp(-_lim_val)), np.exp(_lim_val))
def finv(self, x):
return np.log(x)
def gradfactor(self, f):
@ -112,7 +112,7 @@ class Exponent(Transformation):
return '+ve'
class NegativeExponent(Exponent):
domain = NEGATIVE
domain = _NEGATIVE
def f(self, x):
return -Exponent.f(x)
def finv(self, f):
@ -125,7 +125,7 @@ class NegativeExponent(Exponent):
return '-ve'
class Square(Transformation):
domain = POSITIVE
domain = _POSITIVE
def f(self, x):
return x ** 2
def finv(self, x):
@ -138,7 +138,7 @@ class Square(Transformation):
return '+sq'
class Logistic(Transformation):
domain = BOUNDED
domain = _BOUNDED
_instances = []
def __new__(cls, lower=1e-6, upper=1e-6, *args, **kwargs):
if cls._instances: