From f961520c4220fc803e5f2416f6f96b92ba5e57cc Mon Sep 17 00:00:00 2001 From: Mike Croucher Date: Thu, 26 Feb 2015 13:38:13 +0000 Subject: [PATCH] Exception fixes for Python 3 compat --- GPy/kern/_src/ODE_UY.py | 2 +- GPy/kern/_src/ODE_UYC.py | 2 +- GPy/kern/_src/ODE_st.py | 2 +- GPy/kern/_src/ODE_t.py | 2 +- GPy/kern/_src/add.py | 2 +- GPy/kern/_src/psi_comp/__init__.py | 8 ++++---- GPy/kern/_src/stationary.py | 4 ++-- GPy/kern/_src/symbolic.py | 2 +- 8 files changed, 12 insertions(+), 12 deletions(-) diff --git a/GPy/kern/_src/ODE_UY.py b/GPy/kern/_src/ODE_UY.py index b4a2b42d..eef8609b 100644 --- a/GPy/kern/_src/ODE_UY.py +++ b/GPy/kern/_src/ODE_UY.py @@ -114,7 +114,7 @@ class ODE_UY(Kern): elif i==1: Kdiag[s1]+= Vu*Vy*(k1+k2+k3) else: - raise ValueError, "invalid input/output index" + raise ValueError("invalid input/output index") #Kdiag[slices[0][0]]+= self.variance_U #matern32 diag #Kdiag[slices[1][0]]+= self.variance_U*self.variance_Y*(k1+k2+k3) # diag return Kdiag diff --git a/GPy/kern/_src/ODE_UYC.py b/GPy/kern/_src/ODE_UYC.py index 1722d2e1..4c39a9c9 100644 --- a/GPy/kern/_src/ODE_UYC.py +++ b/GPy/kern/_src/ODE_UYC.py @@ -115,7 +115,7 @@ class ODE_UYC(Kern): elif i==1: Kdiag[s1]+= Vu*Vy*(k1+k2+k3) else: - raise ValueError, "invalid input/output index" + raise ValueError("invalid input/output index") #Kdiag[slices[0][0]]+= self.variance_U #matern32 diag #Kdiag[slices[1][0]]+= self.variance_U*self.variance_Y*(k1+k2+k3) # diag return Kdiag diff --git a/GPy/kern/_src/ODE_st.py b/GPy/kern/_src/ODE_st.py index 665be230..1c3b661b 100644 --- a/GPy/kern/_src/ODE_st.py +++ b/GPy/kern/_src/ODE_st.py @@ -135,7 +135,7 @@ class ODE_st(Kern): Kdiag[s1]+= b**2*k1 - 2*a*c*k2 + a**2*k3 + c**2*vyt*vyx #Kdiag[s1]+= Vu*Vy*(k1+k2+k3) else: - raise ValueError, "invalid input/output index" + raise ValueError("invalid input/output index") return Kdiag diff --git a/GPy/kern/_src/ODE_t.py b/GPy/kern/_src/ODE_t.py index a470cbec..268917ae 100644 --- a/GPy/kern/_src/ODE_t.py +++ b/GPy/kern/_src/ODE_t.py @@ -85,7 +85,7 @@ class ODE_t(Kern): Kdiag[s1]+= k1 + vyt+self.ubias #Kdiag[s1]+= Vu*Vy*(k1+k2+k3) else: - raise ValueError, "invalid input/output index" + raise ValueError("invalid input/output index") return Kdiag diff --git a/GPy/kern/_src/add.py b/GPy/kern/_src/add.py index 4c72a254..0f612f5b 100644 --- a/GPy/kern/_src/add.py +++ b/GPy/kern/_src/add.py @@ -111,7 +111,7 @@ class Add(CombinationKernel): psi2 += np.einsum('nm,no->mo',tmp1,tmp2)+np.einsum('nm,no->mo',tmp2,tmp1) #(tmp1[:, :, None] * tmp2[:, None, :]) + (tmp2[:, :, None] * tmp1[:, None, :]) else: - raise NotImplementedError, "psi2 cannot be computed for this kernel" + raise NotImplementedError("psi2 cannot be computed for this kernel") return psi2 def update_gradients_expectations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior): diff --git a/GPy/kern/_src/psi_comp/__init__.py b/GPy/kern/_src/psi_comp/__init__.py index a277ff02..74aacd75 100644 --- a/GPy/kern/_src/psi_comp/__init__.py +++ b/GPy/kern/_src/psi_comp/__init__.py @@ -17,7 +17,7 @@ class PSICOMP_RBF(Pickleable): elif isinstance(variational_posterior, variational.SpikeAndSlabPosterior): return ssrbf_psi_comp.psicomputations(variance, lengthscale, Z, variational_posterior) else: - raise ValueError, "unknown distriubtion received for psi-statistics" + raise ValueError("unknown distriubtion received for psi-statistics") @Cache_this(limit=2, ignore_args=(0,1,2,3)) def psiDerivativecomputations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, lengthscale, Z, variational_posterior): @@ -26,7 +26,7 @@ class PSICOMP_RBF(Pickleable): elif isinstance(variational_posterior, variational.SpikeAndSlabPosterior): return ssrbf_psi_comp.psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, lengthscale, Z, variational_posterior) else: - raise ValueError, "unknown distriubtion received for psi-statistics" + raise ValueError("unknown distriubtion received for psi-statistics") def _setup_observers(self): pass @@ -40,7 +40,7 @@ class PSICOMP_Linear(Pickleable): elif isinstance(variational_posterior, variational.SpikeAndSlabPosterior): return sslinear_psi_comp.psicomputations(variance, Z, variational_posterior) else: - raise ValueError, "unknown distriubtion received for psi-statistics" + raise ValueError("unknown distriubtion received for psi-statistics") @Cache_this(limit=2, ignore_args=(0,1,2,3)) def psiDerivativecomputations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, Z, variational_posterior): @@ -49,7 +49,7 @@ class PSICOMP_Linear(Pickleable): elif isinstance(variational_posterior, variational.SpikeAndSlabPosterior): return sslinear_psi_comp.psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, Z, variational_posterior) else: - raise ValueError, "unknown distriubtion received for psi-statistics" + raise ValueError("unknown distriubtion received for psi-statistics") def _setup_observers(self): pass \ No newline at end of file diff --git a/GPy/kern/_src/stationary.py b/GPy/kern/_src/stationary.py index 426296f7..0cd85b38 100644 --- a/GPy/kern/_src/stationary.py +++ b/GPy/kern/_src/stationary.py @@ -65,10 +65,10 @@ class Stationary(Kern): self.link_parameters(self.variance, self.lengthscale) def K_of_r(self, r): - raise NotImplementedError, "implement the covariance function as a fn of r to use this class" + raise NotImplementedError("implement the covariance function as a fn of r to use this class") def dK_dr(self, r): - raise NotImplementedError, "implement derivative of the covariance function wrt r to use this class" + raise NotImplementedError("implement derivative of the covariance function wrt r to use this class") @Cache_this(limit=5, ignore_args=()) def K(self, X, X2=None): diff --git a/GPy/kern/_src/symbolic.py b/GPy/kern/_src/symbolic.py index 006af9dc..9ca20ea5 100644 --- a/GPy/kern/_src/symbolic.py +++ b/GPy/kern/_src/symbolic.py @@ -11,7 +11,7 @@ class Symbolic(Kern, Symbolic_core): def __init__(self, input_dim, k=None, output_dim=1, name='symbolic', parameters=None, active_dims=None, operators=None, func_modules=[]): if k is None: - raise ValueError, "You must provide an argument for the covariance function." + raise ValueError("You must provide an argument for the covariance function.") Kern.__init__(self, input_dim, active_dims, name=name) kdiag = k