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all the product_orthogonal have been changed to prod_orthogonal for consistency

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This commit is contained in:
Nicolas 2013-03-11 10:33:29 +00:00
parent f881e65761
commit ec748e2d6b
5 changed files with 13 additions and 13 deletions
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2
GPy/kern/__init__.py
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@ -2,5 +2,5 @@
# Licensed under the BSD 3-clause license (see LICENSE.txt) # Licensed under the BSD 3-clause license (see LICENSE.txt)
from constructors import rbf, Matern32, Matern52, exponential, linear, white, bias, finite_dimensional, spline, Brownian, rbf_sympy, sympykern, periodic_exponential, periodic_Matern32, periodic_Matern52, product, product_orthogonal, symmetric, coregionalise from constructors import rbf, Matern32, Matern52, exponential, linear, white, bias, finite_dimensional, spline, Brownian, rbf_sympy, sympykern, periodic_exponential, periodic_Matern32, periodic_Matern52, prod, prod_orthogonal, symmetric, coregionalise
from kern import kern from kern import kern

12
GPy/kern/constructors.py
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@ -18,8 +18,8 @@ from Brownian import Brownian as Brownianpart
from periodic_exponential import periodic_exponential as periodic_exponentialpart from periodic_exponential import periodic_exponential as periodic_exponentialpart
from periodic_Matern32 import periodic_Matern32 as periodic_Matern32part from periodic_Matern32 import periodic_Matern32 as periodic_Matern32part
from periodic_Matern52 import periodic_Matern52 as periodic_Matern52part from periodic_Matern52 import periodic_Matern52 as periodic_Matern52part
from product import product as productpart from prod import prod as prodpart
from product_orthogonal import product_orthogonal as product_orthogonalpart from prod_orthogonal import prod_orthogonal as prod_orthogonalpart
from symmetric import symmetric as symmetric_part from symmetric import symmetric as symmetric_part
from coregionalise import coregionalise as coregionalise_part from coregionalise import coregionalise as coregionalise_part
#TODO these s=constructors are not as clean as we'd like. Tidy the code up #TODO these s=constructors are not as clean as we'd like. Tidy the code up
@ -245,7 +245,7 @@ def periodic_Matern52(D,variance=1., lengthscale=None, period=2*np.pi,n_freq=10,
part = periodic_Matern52part(D,variance, lengthscale, period, n_freq, lower, upper) part = periodic_Matern52part(D,variance, lengthscale, period, n_freq, lower, upper)
return kern(D, [part]) return kern(D, [part])
def product(k1,k2): def prod(k1,k2):
""" """
Construct a product kernel over D from two kernels over D Construct a product kernel over D from two kernels over D
@ -253,10 +253,10 @@ def product(k1,k2):
:type k1, k2: kernpart :type k1, k2: kernpart
:rtype: kernel object :rtype: kernel object
""" """
part = productpart(k1,k2) part = prodpart(k1,k2)
return kern(k1.D, [part]) return kern(k1.D, [part])
def product_orthogonal(k1,k2): def prod_orthogonal(k1,k2):
""" """
Construct a product kernel over D1 x D2 from a kernel over D1 and another over D2. Construct a product kernel over D1 x D2 from a kernel over D1 and another over D2.
@ -264,7 +264,7 @@ def product_orthogonal(k1,k2):
:type k1, k2: kernpart :type k1, k2: kernpart
:rtype: kernel object :rtype: kernel object
""" """
part = product_orthogonalpart(k1,k2) part = prod_orthogonalpart(k1,k2)
return kern(k1.D+k2.D, [part]) return kern(k1.D+k2.D, [part])
def symmetric(k): def symmetric(k):

8
GPy/kern/kern.py
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@ -7,8 +7,8 @@ import pylab as pb
from ..core.parameterised import parameterised from ..core.parameterised import parameterised
from kernpart import kernpart from kernpart import kernpart
import itertools import itertools
from product_orthogonal import product_orthogonal from prod_orthogonal import prod_orthogonal
from product import product from prod import prod
class kern(parameterised): class kern(parameterised):
def __init__(self,D,parts=[], input_slices=None): def __init__(self,D,parts=[], input_slices=None):
@ -161,7 +161,7 @@ class kern(parameterised):
K1 = self.copy() K1 = self.copy()
K2 = other.copy() K2 = other.copy()
newkernparts = [product(k1,k2) for k1, k2 in itertools.product(K1.parts,K2.parts)] newkernparts = [prod(k1,k2) for k1, k2 in itertools.product(K1.parts,K2.parts)]
slices = [] slices = []
for sl1, sl2 in itertools.product(K1.input_slices,K2.input_slices): for sl1, sl2 in itertools.product(K1.input_slices,K2.input_slices):
@ -183,7 +183,7 @@ class kern(parameterised):
K1 = self.copy() K1 = self.copy()
K2 = other.copy() K2 = other.copy()
newkernparts = [product_orthogonal(k1,k2) for k1, k2 in itertools.product(K1.parts,K2.parts)] newkernparts = [prod_orthogonal(k1,k2) for k1, k2 in itertools.product(K1.parts,K2.parts)]
slices = [] slices = []
for sl1, sl2 in itertools.product(K1.input_slices,K2.input_slices): for sl1, sl2 in itertools.product(K1.input_slices,K2.input_slices):

2
GPy/kern/product.py → GPy/kern/prod.py
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@ -6,7 +6,7 @@ import numpy as np
import hashlib import hashlib
#from scipy import integrate # This may not be necessary (Nicolas, 20th Feb) #from scipy import integrate # This may not be necessary (Nicolas, 20th Feb)
class product(kernpart): class prod(kernpart):
""" """
Computes the product of 2 kernels that are defined on the same space Computes the product of 2 kernels that are defined on the same space

2
GPy/kern/product_orthogonal.py → GPy/kern/prod_orthogonal.py
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@ -6,7 +6,7 @@ import numpy as np
import hashlib import hashlib
#from scipy import integrate # This may not be necessary (Nicolas, 20th Feb) #from scipy import integrate # This may not be necessary (Nicolas, 20th Feb)
class product_orthogonal(kernpart): class prod_orthogonal(kernpart):
""" """
Computes the product of 2 kernels Computes the product of 2 kernels