From 25ba3d5ec8b5991f51743bfa0b9349806b2bbae4 Mon Sep 17 00:00:00 2001 From: Alexander Grigorievskiy Date: Tue, 15 Mar 2016 18:58:38 +0200 Subject: [PATCH] KERN: sde_standard_periodic kernel change parameters names. --- GPy/kern/src/sde_standard_periodic.py | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/GPy/kern/src/sde_standard_periodic.py b/GPy/kern/src/sde_standard_periodic.py index ed9d8cee..3729bf57 100644 --- a/GPy/kern/src/sde_standard_periodic.py +++ b/GPy/kern/src/sde_standard_periodic.py @@ -33,8 +33,8 @@ class sde_StdPeriodic(StdPeriodic): """ self.variance.gradient = gradients[0] - self.wavelengths.gradient = gradients[1] - self.lengthscales.gradient = gradients[2] + self.period.gradient = gradients[1] + self.lengthscale.gradient = gradients[2] def sde(self): """ @@ -52,15 +52,15 @@ class sde_StdPeriodic(StdPeriodic): # Params to use: (in that order) #self.variance - #self.wavelengths - #self.lengthscales + #self.period + #self.lengthscale N = 7 # approximation order - w0 = 2*np.pi/self.wavelengths # frequency - lengthscales = 2*self.lengthscales + w0 = 2*np.pi/self.period # frequency + lengthscale = 2*self.lengthscale - [q2,dq2l] = seriescoeff(N,lengthscales,self.variance) + [q2,dq2l] = seriescoeff(N,lengthscale,self.variance) # lengthscale is multiplied by 2 because of slightly different # formula for periodic covariance function. # For the same reason: @@ -90,8 +90,8 @@ class sde_StdPeriodic(StdPeriodic): dQc[:,:,0] = np.zeros(Qc.shape) dP_inf[:,:,0] = P_inf / self.variance - # Derivatives self.wavelengths - dF[:,:,1] = np.kron(np.diag(range(0,N+1)),np.array( ((0, w0), (-w0, 0)) ) / self.wavelengths ); + # Derivatives self.period + dF[:,:,1] = np.kron(np.diag(range(0,N+1)),np.array( ((0, w0), (-w0, 0)) ) / self.period ); dQc[:,:,1] = np.zeros(Qc.shape) dP_inf[:,:,1] = np.zeros(P_inf.shape)