From 5ce5c5d8ced4f50e2ce51b80425775141802c4ab Mon Sep 17 00:00:00 2001 From: Alex Grigorievskiy Date: Fri, 19 Aug 2016 16:38:56 +0100 Subject: [PATCH 01/48] TEST: Correcting message for test skipping. This is normal that this test does not work and hence skipped. --- GPy/testing/gpy_kernels_state_space_tests.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/testing/gpy_kernels_state_space_tests.py b/GPy/testing/gpy_kernels_state_space_tests.py index f39eb9d05..4714dda3e 100644 --- a/GPy/testing/gpy_kernels_state_space_tests.py +++ b/GPy/testing/gpy_kernels_state_space_tests.py @@ -267,7 +267,7 @@ def get_new_kernels(): gp_kernel=gp_kernel, mean_compare_decimal=2, var_compare_decimal=2) except AssertionError: - raise SkipTest("Skipping Regular kalman filter for kernel addition, as it seems to be bugged for some python versions") + raise SkipTest("Skipping Regular kalman filter for kernel addition, because it is not stable (normal situation) for this data.") def test_kernel_multiplication(self,): From dfe32266b6e781158b14d3bdea2306a6fd7fa607 Mon Sep 17 00:00:00 2001 From: Alex Grigorievskiy Date: Thu, 6 Apr 2017 11:59:13 +0300 Subject: [PATCH 02/48] STATE-SPACE: Recent modifications to state-space inference, including bug fixes in state-space kernels. --- GPy/kern/src/sde_standard_periodic.py | 105 +++++-- GPy/kern/src/sde_stationary.py | 90 ++++-- GPy/models/state_space_cython.pyx | 51 +++- GPy/models/state_space_main.py | 299 +++++++++++++++++-- GPy/models/state_space_model.py | 85 ++++-- GPy/testing/gpy_kernels_state_space_tests.py | 6 +- 6 files changed, 539 insertions(+), 97 deletions(-) diff --git a/GPy/kern/src/sde_standard_periodic.py b/GPy/kern/src/sde_standard_periodic.py index 3729bf57d..be32f7b2c 100644 --- a/GPy/kern/src/sde_standard_periodic.py +++ b/GPy/kern/src/sde_standard_periodic.py @@ -9,6 +9,7 @@ import numpy as np import scipy as sp +import warnings from scipy import special as special @@ -26,6 +27,38 @@ class sde_StdPeriodic(StdPeriodic): \left( \frac{\sin(\frac{\pi}{\lambda_i} (x_i - y_i) )}{l_i} \right)^2 \right] } """ + # TODO: write comment to the constructor arguments + def __init__(self, *args, **kwargs): + """ + Init constructior. + + Two optinal extra parameters are added in addition to the ones in + StdPeriodic kernel. + + :param approx_order: approximation order for the RBF covariance. (Default 7) + :type approx_order: int + + :param balance: Whether to balance this kernel separately. (Defaulf False). Model has a separate parameter for balancing. + :type balance: bool + """ + + #import pdb; pdb.set_trace() + + if 'approx_order' in kwargs: + self.approx_order = kwargs.get('approx_order') + del kwargs['approx_order'] + else: + self.approx_order = 7 + + + if 'balance' in kwargs: + self.balance = bool( kwargs.get('balance') ) + del kwargs['balance'] + else: + self.balance = False + + super(sde_StdPeriodic, self).__init__(*args, **kwargs) + def sde_update_gradient_full(self, gradients): """ Update gradient in the order in which parameters are represented in the @@ -38,41 +71,48 @@ def sde_update_gradient_full(self, gradients): def sde(self): """ - Return the state space representation of the covariance. + Return the state space representation of the standard periodic covariance. - ! Note: one must constrain lengthscale not to drop below 0.25. - After this bessel functions of the first kind grows to very high. + ! Note: one must constrain lengthscale not to drop below 0.2. (independently of approximation order) + After this Bessel functions of the first becomes NaN. Rescaling + time variable might help. - ! Note: one must keep wevelength also not very low. Because then + ! Note: one must keep period also not very low. Because then the gradients wrt wavelength become ustable. However this might depend on the data. For test example with - 300 data points the low limit is 0.15. + 300 data points the low limit is 0.15. """ + #import pdb; pdb.set_trace() # Params to use: (in that order) #self.variance #self.period #self.lengthscale - N = 7 # approximation order - - - w0 = 2*np.pi/self.period # frequency - lengthscale = 2*self.lengthscale - - [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: - - dq2l = 2*dq2l - - if np.any( np.isfinite(q2) == False): - raise ValueError("SDE periodic covariance error 1") - - if np.any( np.isfinite(dq2l) == False): - raise ValueError("SDE periodic covariance error 2") - + if self.approx_order is not None: + N = int(self.approx_order) + else: + N = 7 # approximation order + + p_period = float(self.period) + p_lengthscale = 2*float(self.lengthscale) + p_variance = float(self.variance) + + w0 = 2*np.pi/p_period # frequency + # lengthscale is multiplied by 2 because of different definition of lengthscale + + [q2,dq2l] = seriescoeff(N, p_lengthscale, p_variance) + + dq2l = 2*dq2l # This is because the lengthscale if multiplied by 2. + + eps = 1e-12 + if np.any( np.isfinite(q2) == False) or np.any( np.abs(q2) > 1.0/eps) or np.any( np.abs(q2) < eps): + warnings.warn("sde_Periodic: Infinite, too small, or too large (eps={0:e}) values in q2 :".format(eps) + q2.__format__("") ) + + if np.any( np.isfinite(dq2l) == False) or np.any( np.abs(dq2l) > 1.0/eps) or np.any( np.abs(dq2l) < eps): + warnings.warn("sde_Periodic: Infinite, too small, or too large (eps={0:e}) values in dq2l :".format(eps) + q2.__format__("") ) + + F = np.kron(np.diag(range(0,N+1)),np.array( ((0, -w0), (w0, 0)) ) ) L = np.eye(2*(N+1)) Qc = np.zeros((2*(N+1), 2*(N+1))) @@ -88,10 +128,10 @@ def sde(self): # Derivatives wrt self.variance dF[:,:,0] = np.zeros(F.shape) dQc[:,:,0] = np.zeros(Qc.shape) - dP_inf[:,:,0] = P_inf / self.variance + dP_inf[:,:,0] = P_inf / p_variance # Derivatives self.period - dF[:,:,1] = np.kron(np.diag(range(0,N+1)),np.array( ((0, w0), (-w0, 0)) ) / self.period ); + dF[:,:,1] = np.kron(np.diag(range(0,N+1)),np.array( ((0, w0), (-w0, 0)) ) / p_period ); dQc[:,:,1] = np.zeros(Qc.shape) dP_inf[:,:,1] = np.zeros(P_inf.shape) @@ -100,7 +140,12 @@ def sde(self): dQc[:,:,2] = np.zeros(Qc.shape) dP_inf[:,:,2] = np.kron(np.diag(dq2l),np.eye(2)) dP0 = dP_inf.copy() - + + if self.balance: + # Benefits of this are not very sound. + import GPy.models.state_space_main as ssm + (F, L, Qc, H, P_inf, P0, dF, dQc, dP_inf,dP0) = ssm.balance_ss_model(F, L, Qc, H, P_inf, P0, dF, dQc, dP_inf, dP0 ) + return (F, L, Qc, H, P_inf, P0, dF, dQc, dP_inf, dP0) @@ -164,9 +209,9 @@ def seriescoeff(m=6,lengthScale=1.0,magnSigma2=1.0, true_covariance=False): coeffs = 2*magnSigma2*sp.exp( -lengthScale**(-2) ) * special.iv(range(0,m+1),1.0/lengthScale**(2)) if np.any( np.isfinite(coeffs) == False): raise ValueError("sde_standard_periodic: Coefficients are not finite!") - #import pdb; pdb.set_trace() + #import pdb; pdb.set_trace() coeffs[0] = 0.5*coeffs[0] - + #print(coeffs) # Derivatives wrt (lengthScale) coeffs_dl = np.zeros(m+1) coeffs_dl[1:] = magnSigma2*lengthScale**(-3) * sp.exp(-lengthScale**(-2))*\ @@ -177,4 +222,4 @@ def seriescoeff(m=6,lengthScale=1.0,magnSigma2=1.0, true_covariance=False): (2*special.iv(0,lengthScale**(-2)) - 2*special.iv(1,lengthScale**(-2)) ) - return coeffs, coeffs_dl + return coeffs.squeeze(), coeffs_dl.squeeze() diff --git a/GPy/kern/src/sde_stationary.py b/GPy/kern/src/sde_stationary.py index 3ac5f402d..d7c61d6bd 100644 --- a/GPy/kern/src/sde_stationary.py +++ b/GPy/kern/src/sde_stationary.py @@ -11,6 +11,7 @@ import numpy as np import scipy as sp +import warnings class sde_RBF(RBF): """ @@ -25,6 +26,37 @@ class sde_RBF(RBF): k(r) = \sigma^2 \exp \\bigg(- \\frac{1}{2} r^2 \\bigg) \\ \\ \\ \\ \text{ where } r = \sqrt{\sum_{i=1}^{input dim} \frac{(x_i-y_i)^2}{\ell_i^2} } """ + def __init__(self, *args, **kwargs): + """ + Init constructior. + + Two optinal extra parameters are added in addition to the ones in + RBF kernel. + + :param approx_order: approximation order for the RBF covariance. (Default 10) + :type approx_order: int + + :param balance: Whether to balance this kernel separately. (Defaulf True). Model has a separate parameter for balancing. + :type balance: bool + """ + + if 'balance' in kwargs: + self.balance = bool( kwargs.get('balance') ) + del kwargs['balance'] + else: + self.balance = True + + + if 'approx_order' in kwargs: + self.approx_order = kwargs.get('approx_order') + del kwargs['approx_order'] + else: + self.approx_order = 6 + + + + super(sde_RBF, self).__init__(*args, **kwargs) + def sde_update_gradient_full(self, gradients): """ Update gradient in the order in which parameters are represented in the @@ -37,23 +69,43 @@ def sde_update_gradient_full(self, gradients): def sde(self): """ Return the state space representation of the covariance. + + Note! For Sparse GP inference too small or two high values of lengthscale + lead to instabilities. This is because Qc are too high or too low + and P_inf are not full rank. This effect depends on approximatio order. + For N = 10. lengthscale must be in (0.8,8). For other N tests must be conducted. + N=6: (0.06,31) + Variance should be within reasonable bounds as well, but its dependence is linear. + + The above facts do not take into accout regularization. """ - - N = 10# approximation order ( number of terms in exponent series expansion) + #import pdb; pdb.set_trace() + if self.approx_order is not None: + N = self.approx_order + else: + N = 10# approximation order ( number of terms in exponent series expansion) + roots_rounding_decimals = 6 fn = np.math.factorial(N) - kappa = 1.0/2.0/self.lengthscale**2 + p_lengthscale = float( self.lengthscale ) + p_variance = float(self.variance) + kappa = 1.0/2.0/p_lengthscale**2 - Qc = np.array((self.variance*np.sqrt(np.pi/kappa)*fn*(4*kappa)**N,),) + Qc = np.array( ((p_variance*np.sqrt(np.pi/kappa)*fn*(4*kappa)**N,),) ) + + eps = 1e-12 + if (float(Qc) > 1.0/eps) or (float(Qc) < eps): + warnings.warn("""sde_RBF kernel: the noise variance Qc is either very large or very small. + It influece conditioning of P_inf: {0:e}""".format(float(Qc)) ) - pp = np.zeros((2*N+1,)) # array of polynomial coefficients from higher power to lower + pp1 = np.zeros((2*N+1,)) # array of polynomial coefficients from higher power to lower for n in range(0, N+1): # (2N+1) - number of polynomial coefficients - pp[2*(N-n)] = fn*(4.0*kappa)**(N-n)/np.math.factorial(n)*(-1)**n - - pp = sp.poly1d(pp) + pp1[2*(N-n)] = fn*(4.0*kappa)**(N-n)/np.math.factorial(n)*(-1)**n + + pp = sp.poly1d(pp1) roots = sp.roots(pp) neg_real_part_roots = roots[np.round(np.real(roots) ,roots_rounding_decimals) < 0] @@ -69,6 +121,7 @@ def sde(self): H[0,0] = 1 # Infinite covariance: + #import pdb; pdb.set_trace() Pinf = sp.linalg.solve_lyapunov(F, -np.dot(L,np.dot( Qc[0,0],L.T))) Pinf = 0.5*(Pinf + Pinf.T) # Allocating space for derivatives @@ -79,17 +132,17 @@ def sde(self): # Derivatives: dFvariance = np.zeros(F.shape) dFlengthscale = np.zeros(F.shape) - dFlengthscale[-1,:] = -aa[-1:0:-1]/self.lengthscale * np.arange(-N,0,1) - - dQcvariance = Qc/self.variance - dQclengthscale = np.array(((self.variance*np.sqrt(2*np.pi)*fn*2**N*self.lengthscale**(-2*N)*(1-2*N,),))) + dFlengthscale[-1,:] = -aa[-1:0:-1]/p_lengthscale * np.arange(-N,0,1) - dPinf_variance = Pinf/self.variance + dQcvariance = Qc/p_variance + dQclengthscale = np.array(( (p_variance*np.sqrt(2*np.pi)*fn*2**N*p_lengthscale**(-2*N)*(1-2*N),),)) + + dPinf_variance = Pinf/p_variance lp = Pinf.shape[0] coeff = np.arange(1,lp+1).reshape(lp,1) + np.arange(1,lp+1).reshape(1,lp) - 2 coeff[np.mod(coeff,2) != 0] = 0 - dPinf_lengthscale = -1/self.lengthscale*Pinf*coeff + dPinf_lengthscale = -1/p_lengthscale*Pinf*coeff dF[:,:,0] = dFvariance dF[:,:,1] = dFlengthscale @@ -101,10 +154,11 @@ def sde(self): P0 = Pinf.copy() dP0 = dPinf.copy() - # Benefits of this are not very sound. Helps only in one case: - # SVD Kalman + RBF kernel - import GPy.models.state_space_main as ssm - (F, L, Qc, H, Pinf, P0, dF, dQc, dPinf,dP0, T) = ssm.balance_ss_model(F, L, Qc, H, Pinf, P0, dF, dQc, dPinf, dP0 ) + if self.balance: + # Benefits of this are not very sound. Helps only in one case: + # SVD Kalman + RBF kernel + import GPy.models.state_space_main as ssm + (F, L, Qc, H, Pinf, P0, dF, dQc, dPinf,dP0) = ssm.balance_ss_model(F, L, Qc, H, Pinf, P0, dF, dQc, dPinf, dP0 ) return (F, L, Qc, H, Pinf, P0, dF, dQc, dPinf, dP0) diff --git a/GPy/models/state_space_cython.pyx b/GPy/models/state_space_cython.pyx index ae09d1cd2..2626b9e70 100644 --- a/GPy/models/state_space_cython.pyx +++ b/GPy/models/state_space_cython.pyx @@ -432,6 +432,8 @@ cdef class AQcompute_batch_Cython(Q_handling_Cython): (self.reconstruct_indices.nbytes if (self.reconstruct_indices is not None) else 0) self.Q_svd_dict = {} + self.Q_square_root_dict = {} + self.Q_inverse_dict = {} self.last_k = 0 # !!!Print statistics! Which object is created # !!!Print statistics! Print sizes of matrices @@ -477,19 +479,54 @@ cdef class AQcompute_batch_Cython(Q_handling_Cython): cdef np.ndarray[DTYPE_t, ndim=2] U cdef np.ndarray[DTYPE_t, ndim=1] S cdef np.ndarray[DTYPE_t, ndim=2] Vh + - if matrix_index in self.Q_svd_dict: - square_root = self.Q_svd_dict[matrix_index] + if matrix_index in self.Q_square_root_dict: + square_root = self.Q_square_root_dict[matrix_index] else: - U,S,Vh = sp.linalg.svd( self.Qs[:,:, matrix_index], + if matrix_index not in self.Q_svd_dict + U,S,Vh = sp.linalg.svd( self.Qs[:,:, matrix_index], full_matrices=False, compute_uv=True, - overwrite_a=False, check_finite=False) - + overwrite_a=False, check_finite=False) + self.Q_svd_dict[matrix_index] = (U,S,Vh) + else: + U,S,Vh = self.Q_svd_dict[matrix_index] + square_root = U * np.sqrt(S) - self.Q_svd_dict[matrix_index] = square_root + self.Q_suqare_root_dict[matrix_index] = square_root return square_root - + + + cpdef Q_inverse(self, int k, float jitter=0.0): + """ + Square root of the noise matrix Q + """ + + cdef int matrix_index = self.reconstruct_indices[k] + cdef np.ndarray[DTYPE_t, ndim=2] square_root + + cdef np.ndarray[DTYPE_t, ndim=2] U + cdef np.ndarray[DTYPE_t, ndim=1] S + cdef np.ndarray[DTYPE_t, ndim=2] Vh + + + if matrix_index in self.Q_inverse_dict: + Q_inverse = self.Q_inverse_dict[matrix_index] + else: + if matrix_index not in self.Q_svd_dict + U,S,Vh = sp.linalg.svd( self.Qs[:,:, matrix_index], + full_matrices=False, compute_uv=True, + overwrite_a=False, check_finite=False) + self.Q_svd_dict[matrix_index] = (U,S,Vh) + else: + U,S,Vh = self.Q_svd_dict[matrix_index] + + Q_inverse = Q_inverse = np.dot( Vh.T * ( 1.0/(S + jitter)) , U.T ) + self.Q_inverse_dict[matrix_index] = Q_inverse + + return Q_inverse + # def return_last(self): # """ # Function returns last available matrices. diff --git a/GPy/models/state_space_main.py b/GPy/models/state_space_main.py index 65763a058..dd639ad06 100644 --- a/GPy/models/state_space_main.py +++ b/GPy/models/state_space_main.py @@ -12,6 +12,8 @@ import scipy as sp import scipy.linalg as linalg +import warnings + try: from . import state_space_setup setup_available = True @@ -41,6 +43,10 @@ else: print("state_space: cython is NOT used") +# When debugging external module can set some value to this variable (e.g.) +# 'model' and in this module this variable can be seen.s +tmp_buffer = None + class Dynamic_Callables_Python(object): @@ -227,7 +233,7 @@ def __init__(self, R, index, R_time_var_index, unique_R_number, dR=None): self.R_square_root = {} def Rk(self, k): - return self.R[:, :, self.index[self.R_time_var_index, k]] + return self.R[:, :, int(self.index[self.R_time_var_index, k])] def dRk(self, k): if self.dR is None: @@ -305,7 +311,7 @@ def Hk(self, k, m_pred, P_pred): # returns state iteration matrix P: parameter for Jacobian, usually covariance matrix. """ - return self.H[:, :, self.index[self.H_time_var_index, k]] + return self.H[:, :, int(self.index[self.H_time_var_index, k])] def dHk(self, k): if self.dH is None: @@ -2303,6 +2309,8 @@ def __init__(self, F,L,Qc,dt,compute_derivatives=False, grad_params_no=None, P_i self.v_dQk = None self.square_root_computed = False + self.Q_inverse_computed = False + self.Q_svd_computed = False # !!!Print statistics! Which object is created def f_a(self, k,m,A): @@ -2337,7 +2345,10 @@ def _recompute_for_new_k(self,k): self.v_Qk = v_Qk self.v_dAk = v_dAk self.v_dQk = v_dQk + self.Q_square_root_computed = False + self.Q_inverse_computed = False + self.Q_svd_computed = False else: v_Ak = self.v_Ak v_Qk = self.v_Qk @@ -2359,8 +2370,11 @@ def reset(self, compute_derivatives): self.last_k = 0 self.last_k_computed = False self.compute_derivatives = compute_derivatives + self.Q_square_root_computed = False - + self.Q_inverse_computed = False + self.Q_svd_computed = False + self.Q_eigen_computed = False return self def Ak(self,k,m,P): @@ -2381,12 +2395,19 @@ def dQk(self, k): def Q_srk(self,k): """ + Check square root, maybe rewriting for Spectral decomposition is needed. Square root of the noise matrix Q """ if ((self.last_k == k) and (self.last_k_computed == True)): if not self.Q_square_root_computed: - (U, S, Vh) = sp.linalg.svd( self.v_Qk, full_matrices=False, compute_uv=True, overwrite_a=False, check_finite=False) + if not self.Q_svd_computed: + (U, S, Vh) = sp.linalg.svd( self.v_Qk, full_matrices=False, compute_uv=True, overwrite_a=False, check_finite=False) + self.Q_svd = (U, S, Vh) + self.Q_svd_computed = True + else: + (U, S, Vh) = self.Q_svd + square_root = U * np.sqrt(S) self.square_root_computed = True self.Q_square_root = square_root @@ -2396,7 +2417,56 @@ def Q_srk(self,k): raise ValueError("Square root of Q can not be computed") return square_root + + def Q_inverse(self, k, p_largest_cond_num, p_regularization_type): + """ + Function inverts Q matrix and regularizes the inverse. + Regularization is useful when original matrix is badly conditioned. + Function is currently used only in SparseGP code. + + Inputs: + ------------------------------ + k: int + Iteration number. + + p_largest_cond_num: float + Largest condition value for the inverted matrix. If cond. number is smaller than that + no regularization happen. + + regularization_type: 1 or 2 + Regularization type. + + regularization_type: int (1 or 2) + + type 1: 1/(S[k] + regularizer) regularizer is computed + type 2: S[k]/(S^2[k] + regularizer) regularizer is computed + """ + + #import pdb; pdb.set_trace() + + if ((self.last_k == k) and (self.last_k_computed == True)): + if not self.Q_inverse_computed: + if not self.Q_svd_computed: + (U, S, Vh) = sp.linalg.svd( self.v_Qk, full_matrices=False, compute_uv=True, overwrite_a=False, check_finite=False) + self.Q_svd = (U, S, Vh) + self.Q_svd_computed = True + else: + (U, S, Vh) = self.Q_svd + + Q_inverse_r = psd_matrix_inverse(k, 0.5*(self.v_Qk + self.v_Qk.T), U,S, p_largest_cond_num, p_regularization_type) + + self.Q_inverse_computed = True + self.Q_inverse_r = Q_inverse_r + + else: + Q_inverse_r = self.Q_inverse_r + else: + raise ValueError("""Inverse of Q can not be computed, because Q has not been computed. + This requires some programming""") + return Q_inverse_r + + def return_last(self): """ Function returns last computed matrices. @@ -2463,6 +2533,9 @@ def __init__(self, F,L,Qc,dt,compute_derivatives=False, grad_params_no=None, P_i (self.reconstruct_indices.nbytes if (self.reconstruct_indices is not None) else 0) self.Q_svd_dict = {} + self.Q_square_root_dict = {} + self.Q_inverse_dict = {} + self.last_k = None # !!!Print statistics! Which object is created # !!!Print statistics! Print sizes of matrices @@ -2503,17 +2576,66 @@ def Q_srk(self,k): Square root of the noise matrix Q """ matrix_index = self.reconstruct_indices[k] - if matrix_index in self.Q_svd_dict: - square_root = self.Q_svd_dict[matrix_index] + if matrix_index in self.Q_square_root_dict: + square_root = self.Q_square_root_dict[matrix_index] else: - (U, S, Vh) = sp.linalg.svd( self.Qs[:,:, matrix_index], + if matrix_index in self.Q_svd_dict: + (U, S, Vh) = self.Q_svd_dict[matrix_index] + else: + (U, S, Vh) = sp.linalg.svd( self.Qs[:,:, matrix_index], full_matrices=False, compute_uv=True, overwrite_a=False, check_finite=False) + self.Q_svd_dict[matrix_index] = (U,S,Vh) + square_root = U * np.sqrt(S) - self.Q_svd_dict[matrix_index] = square_root + self.Q_square_root_dict[matrix_index] = square_root return square_root - + + def Q_inverse(self, k, p_largest_cond_num, p_regularization_type): + """ + Function inverts Q matrix and regularizes the inverse. + Regularization is useful when original matrix is badly conditioned. + Function is currently used only in SparseGP code. + + Inputs: + ------------------------------ + k: int + Iteration number. + + p_largest_cond_num: float + Largest condition value for the inverted matrix. If cond. number is smaller than that + no regularization happen. + + regularization_type: 1 or 2 + Regularization type. + + regularization_type: int (1 or 2) + + type 1: 1/(S[k] + regularizer) regularizer is computed + type 2: S[k]/(S^2[k] + regularizer) regularizer is computed + """ + #import pdb; pdb.set_trace() + + matrix_index = self.reconstruct_indices[k] + if matrix_index in self.Q_inverse_dict: + Q_inverse_r = self.Q_inverse_dict[matrix_index] + else: + + if matrix_index in self.Q_svd_dict: + (U, S, Vh) = self.Q_svd_dict[matrix_index] + else: + (U, S, Vh) = sp.linalg.svd( self.Qs[:,:, matrix_index], + full_matrices=False, compute_uv=True, + overwrite_a=False, check_finite=False) + self.Q_svd_dict[matrix_index] = (U,S,Vh) + + Q_inverse_r = psd_matrix_inverse(k, 0.5*(self.Qs[:,:, matrix_index] + self.Qs[:,:, matrix_index].T), U,S, p_largest_cond_num, p_regularization_type) + self.Q_inverse_dict[matrix_index] = Q_inverse_r + + return Q_inverse_r + + def return_last(self): """ Function returns last available matrices. @@ -3073,7 +3195,8 @@ def cont_discr_rts_smoother(cls,state_dim, filter_means, filter_covars, @classmethod def _cont_to_discrete_object(cls, X, F, L, Qc, compute_derivatives=False, grad_params_no=None, - P_inf=None, dP_inf=None, dF = None, dQc=None): + P_inf=None, dP_inf=None, dF = None, dQc=None, + dt0=None): """ Function return the object which is used in Kalman filter and/or smoother to obtain matrices A, Q and their derivatives for discrete model @@ -3110,7 +3233,14 @@ def _cont_to_discrete_object(cls, X, F, L, Qc, compute_derivatives=False, threshold_number_of_unique_time_steps = 20 # above which matrices are separately each time dt = np.empty((X.shape[0],)) dt[1:] = np.diff(X[:,0],axis=0) - dt[0] = 0#dt[1] + if dt0 is None: + dt[0] = 0#dt[1] + else: + if isinstance(dt0,str): + dt = dt[1:] + else: + dt[0] = dt0 + unique_indices = np.unique(np.round(dt, decimals=unique_round_decimals)) number_unique_indices = len(unique_indices) @@ -3161,7 +3291,10 @@ def lti_sde_to_descrete(F,L,Qc,dt,compute_derivatives=False, x_{k} = A_{k} * x_{k-1} + q_{k-1}; q_{k-1} ~ N(0, Q_{k-1}) - + TODO: this function can be redone to "preprocess dataset", when + close time points are handeled properly (with rounding parameter) and + values are averaged accordingly. + Input: -------------- F,L: LTI SDE matrices of corresponding dimensions @@ -3222,11 +3355,9 @@ def lti_sde_to_descrete(F,L,Qc,dt,compute_derivatives=False, n = F.shape[0] if not isinstance(dt, collections.Iterable): # not iterable, scalar - + #import pdb; pdb.set_trace() # The dynamical model A = matrix_exponent(F*dt) - if np.any( np.isnan(A)): - A = linalg.expm3(F*dt) # The covariance matrix Q by matrix fraction decomposition -> Phi = np.zeros((2*n,2*n)) @@ -3265,15 +3396,17 @@ def lti_sde_to_descrete(F,L,Qc,dt,compute_derivatives=False, # The discrete-time dynamical model* if p==0: A = AA[:n,:n,p] - Q_noise_2 = P_inf - A.dot(P_inf).dot(A.T) - Q_noise = Q_noise_2 + Q_noise_3 = P_inf - A.dot(P_inf).dot(A.T) + Q_noise = Q_noise_3 #PP = A.dot(P).dot(A.T) + Q_noise_2 # The derivatives of A and Q dA[:,:,p] = AA[n:,:n,p] - dQ[:,:,p] = dP_inf[:,:,p] - dA[:,:,p].dot(P_inf).dot(A.T) \ - - A.dot(dP_inf[:,:,p]).dot(A.T) - A.dot(P_inf).dot(dA[:,:,p].T) # Rewrite not ro multiply two times - + tmp = dA[:,:,p].dot(P_inf).dot(A.T) + dQ[:,:,p] = dP_inf[:,:,p] - tmp \ + - A.dot(dP_inf[:,:,p]).dot(A.T) - tmp.T + + dQ[:,:,p] = 0.5*(dQ[:,:,p] + dQ[:,:,p].T) # Symmetrize else: dA = None dQ = None @@ -3283,6 +3416,10 @@ def lti_sde_to_descrete(F,L,Qc,dt,compute_derivatives=False, #Q_noise = Q_noise_1 # Return + #import pdb; pdb.set_trace() + #if dt != 0: + # Q_noise = Q_noise + np.eye(Q_noise.shape[0])*1e-8 + Q_noise = 0.5*(Q_noise + Q_noise.T) # Symmetrize return A, Q_noise,None, dA, dQ else: # iterable, array @@ -3486,4 +3623,124 @@ def balance_ss_model(F,L,Qc,H,Pinf,P0,dF=None,dQc=None,dPinf=None,dP0=None): # (F,L,Qc,H,Pinf,P0,dF,dQc,dPinf,dP0) - return bF, bL, bQc, bH, bPinf, bP0, bdF, bdQc, bdPinf, bdP0, T + return bF, bL, bQc, bH, bPinf, bP0, bdF, bdQc, bdPinf, bdP0 + +#def psd_matrix_inverse(k,Q, U=None,S=None, p_largest_cond_num=None, regularization_type=2): +# """ +# Function inverts positive definite matrix and regularizes the inverse. +# Regularization is useful when original matrix is badly conditioned. +# Function is currently used only in SparseGP code. +# +# Inputs: +# ------------------------------ +# k: int +# Iteration umber. Used for information only. Value -1 corresponds to P_inf_inv. +# +# Q: matrix +# To be inverted +# +# U,S: matrix. vector +# SVD components of Q +# +# p_largest_cond_num: float +# Largest condition value for the inverted matrix. If cond. number is smaller than that +# no regularization happen. +# +# regularization_type: 1 or 2 +# Regularization type. +# """ +# #import pdb; pdb.set_trace() +## if (k == 0) or (k == -1): # -1 - P_inf_inv computation +## import pdb; pdb.set_trace() +# +# if p_largest_cond_num is None: +# raise ValueError("psd_matrix_inverse: None p_largest_cond_num") +# +# if U is None or S is None: +# (U, S, Vh) = sp.linalg.svd( Q, full_matrices=False, compute_uv=True, overwrite_a=False, check_finite=False) +# if S[0] < (1e-4): +# #import pdb; pdb.set_trace() +# warnings.warn("""state_space_main psd_matrix_inverse: largest singular value is too small {0:e}. +# condition number is {1:e} Maybe somethigng is wrong +# """.format(S[0], S[0]/S[-1])) +# S = S + (1e-4 - S[0]) # make the S[0] at least 1e-4 +# +# current_conditional_number = S[0]/S[-1] +# if (current_conditional_number > p_largest_cond_num): +# if (regularization_type == 1): +# regularizer = S[0] / p_largest_cond_num +# # the second computation of SVD is done to compute more precisely singular +# # vectors of small singular values, since small singular values become large. +# # It is not very clear how this step is useful but test is here. +# (U, S, Vh) = sp.linalg.svd( Q + regularizer*np.eye(Q.shape[0]), +# full_matrices=False, compute_uv=True, overwrite_a=False, check_finite=False) +# +# Q_inverse_r = np.dot( U * 1.0/S , U.T ) # Assume Q_inv is positive definite +# +# # In this case, RBF kernel we get complx eigenvalues. Probably +# # for small eigenvalue corresponding eigenvectors are not very orthogonal. +# ##########Q_inverse = np.dot( Vh.T * ( 1.0/(S + regularizer)) , U.T ) +# elif (regularization_type == 2): +# +# new_border_value = np.sqrt(current_conditional_number)/2 +# if p_largest_cond_num >= new_border_value: # this type of regularization works +# regularizer = ( S[0] / p_largest_cond_num / 2.0 )**2 +# +# Q_inverse_r = np.dot( U * ( S/(S**2 + regularizer)) , U.T ) # Assume Q_inv is positive definite +# else: +# +# better_curr_cond_num = new_border_value +# warnings.warn("""state_space_main psd_matrix_inverse: reg_type = 2 can't be done completely. +# Current conditionakl number {0:e} is reduced to {1:e} by reg_type = 1""".format(current_conditional_number, better_curr_cond_num)) +# +# regularizer = S[0] / better_curr_cond_num +# # the second computation of SVD is done to compute more precisely singular +# # vectors of small singular values, since small singular values become large. +# # It is not very clear how this step is useful but test is here. +# (U, S, Vh) = sp.linalg.svd( Q + regularizer*np.eye(Q.shape[0]), +# full_matrices=False, compute_uv=True, overwrite_a=False, check_finite=False) +# +# regularizer = ( S[0] / p_largest_cond_num / 2.0 )**2 +# +# Q_inverse_r = np.dot( U * ( S/(S**2 + regularizer)) , U.T ) # Assume Q_inv is positive definite +# +# assert regularizer*10 < S[0], "regularizer is not << S[0]" +# assert regularizer > 10*S[-1], "regularizer is not >> S[-1]" +# +## Old version -> +## lamda_star = np.sqrt(current_conditional_number) +## if 2*p_largest_cond_num >= lamda_star: +## lamda = current_conditional_number / 2 / p_largest_cond_num +## +## regularizer = (S[-1] * lamda)**2 +## +## Q_inverse_r = np.dot( U * ( S/(S**2 + regularizer)) , U.T ) # Assume Q_inv is positive definite +## else: +## better_curr_cond_num = (2*p_largest_cond_num)**2 / 2 # division by 2 just in case here +## warnings.warn("""state_space_main psd_matrix_inverse: reg_type = 2 can't be done completely. +## Current conditionakl number {0:e} is reduced to {1:e} by reg_type = 1""".format(current_conditional_number, better_curr_cond_num)) +## +## regularizer = S[0] / better_curr_cond_num +## # the second computation of SVD is done to compute more precisely singular +## # vectors of small singular values, since small singular values become large. +## # It is not very clear how this step is useful but test is here. +## (U, S, Vh) = sp.linalg.svd( Q + regularizer*np.eye(Q.shape[0]), +## full_matrices=False, compute_uv=True, overwrite_a=False, check_finite=False) +## +## lamda = better_curr_cond_num / 2 / p_largest_cond_num +## +## regularizer = (S[-1] * lamda)**2 +## +## Q_inverse_r = np.dot( U * ( S/(S**2 + regularizer)) , U.T ) # Assume Q_inv is positive definite +## +## assert lamda > 10, "Some assumptions are incorrect if this is not satisfied." +## Old version <- +# else: +# raise ValueError("AQcompute_batch_Python:Q_inverse: Invalid regularization type") +# +# else: +# Q_inverse_r = np.dot( U * 1.0/S , U.T ) # Assume Q_inv is positive definite +# # When checking conditional number 2 times difference is ok. +# Q_inverse_r = 0.5*(Q_inverse_r + Q_inverse_r.T) +# +# return Q_inverse_r \ No newline at end of file diff --git a/GPy/models/state_space_model.py b/GPy/models/state_space_model.py index 5d22c0fcc..c74a25f2a 100644 --- a/GPy/models/state_space_model.py +++ b/GPy/models/state_space_model.py @@ -1,6 +1,6 @@ # Copyright (c) 2013, Arno Solin. # Licensed under the BSD 3-clause license (see LICENSE.txt) -# +# # This implementation of converting GPs to state space models is based on the article: # # @article{Sarkka+Solin+Hartikainen:2013, @@ -23,7 +23,16 @@ from . import state_space_setup as ss_setup class StateSpace(Model): - def __init__(self, X, Y, kernel=None, noise_var=1.0, kalman_filter_type = 'regular', use_cython = False, name='StateSpace'): + def __init__(self, X, Y, kernel=None, noise_var=1.0, kalman_filter_type = 'regular', use_cython = False, balance=False, name='StateSpace'): + """ + Inputs: + ------------------ + + balance: bool + Whether to balance or not the model as a whole + + """ + super(StateSpace, self).__init__(name=name) if len(X.shape) == 1: @@ -51,15 +60,16 @@ def __init__(self, X, Y, kernel=None, noise_var=1.0, kalman_filter_type = 'regul ss_setup.use_cython = use_cython #import pdb; pdb.set_trace() - + self.balance = balance + global ssm #from . import state_space_main as ssm if (ssm.cython_code_available) and (ssm.use_cython != ss_setup.use_cython): reload(ssm) # Make sure the observations are ordered in time sort_index = np.argsort(X[:,0]) - self.X = X[sort_index] - self.Y = Y[sort_index] + self.X = X[sort_index,:] + self.Y = Y[sort_index,:] # Noise variance self.likelihood = likelihoods.Gaussian(variance=noise_var) @@ -86,11 +96,12 @@ def parameters_changed(self): #np.set_printoptions(16) #print(self.param_array) - #import pdb; pdb.set_trace() + # Get the model matrices from the kernel (F,L,Qc,H,P_inf, P0, dFt,dQct,dP_inft, dP0t) = self.kern.sde() - + #Qc = Qc + np.eye(Qc.shape[0]) * 1e-8 + #import pdb; pdb.set_trace() # necessary parameters measurement_dim = self.output_dim grad_params_no = dFt.shape[2]+1 # we also add measurement noise as a parameter @@ -112,8 +123,9 @@ def parameters_changed(self): dR[:,:,-1] = np.eye(measurement_dim) # Balancing - #(F,L,Qc,H,P_inf,P0, dF,dQc,dP_inf,dP0) = ssm.balance_ss_model(F,L,Qc,H,P_inf,P0, dF,dQc,dP_inf, dP0) - + if self.balance: + (F,L,Qc,H,P_inf,P0, dF,dQc,dP_inf,dP0) = ssm.balance_ss_model(F,L,Qc,H,P_inf,P0, dF,dQc,dP_inf, dP0) + print("SSM parameters_changed balancing!") # Use the Kalman filter to evaluate the likelihood grad_calc_params = {} grad_calc_params['dP_inf'] = dP_inf @@ -125,7 +137,7 @@ def parameters_changed(self): kalman_filter_type = self.kalman_filter_type # The following code is required because sometimes the shapes of self.Y - # becomes 3D even though is must be 2D. The reason is undescovered. + # becomes 3D even though is must be 2D. The reason is undiscovered. Y = self.Y if self.ts_number is None: Y.shape = (self.num_data,1) @@ -146,7 +158,7 @@ def parameters_changed(self): if np.any( np.isfinite(grad_log_likelihood) == False): #import pdb; pdb.set_trace() - print("State-Space: NaN valkues in the grad_log_likelihood") + print("State-Space: NaN values in the grad_log_likelihood") #print(grad_log_likelihood) grad_log_likelihood_sum = np.sum(grad_log_likelihood,axis=1) @@ -159,7 +171,7 @@ def parameters_changed(self): def log_likelihood(self): return self._log_marginal_likelihood - def _raw_predict(self, Xnew=None, Ynew=None, filteronly=False, **kw): + def _raw_predict(self, Xnew=None, Ynew=None, filteronly=False, p_balance=False, **kw): """ Performs the actual prediction for new X points. Inner function. It is called only from inside this class. @@ -177,7 +189,10 @@ def _raw_predict(self, Xnew=None, Ynew=None, filteronly=False, **kw): filteronly: bool Use only Kalman Filter for prediction. In this case the output does not coincide with corresponding Gaussian process. - + + balance: bool + Whether to balance or not the model as a whole + Output: -------------------- @@ -210,7 +225,12 @@ def _raw_predict(self, Xnew=None, Ynew=None, filteronly=False, **kw): # Get the model matrices from the kernel (F,L,Qc,H,P_inf, P0, dF,dQc,dP_inf,dP0) = self.kern.sde() state_dim = F.shape[0] - + + # Balancing + if (p_balance==True): + (F,L,Qc,H,P_inf,P0, dF,dQc,dP_inf,dP0) = ssm.balance_ss_model(F,L,Qc,H,P_inf,P0, dF,dQc,dP_inf, dP0) + print("SSM _raw_predict balancing!") + #Y = self.Y[:, 0,0] # Run the Kalman filter #import pdb; pdb.set_trace() @@ -261,10 +281,23 @@ def _raw_predict(self, Xnew=None, Ynew=None, filteronly=False, **kw): # Return the posterior of the state return (m, V) - def predict(self, Xnew=None, filteronly=False, include_likelihood=True, **kw): - + def predict(self, Xnew=None, filteronly=False, include_likelihood=True, balance=None, **kw): + """ + Inputs: + ------------------ + + balance: bool + Whether to balance or not the model as a whole + + """ + + if balance is None: + p_balance = self.balance + else: + p_balance = balance + # Run the Kalman filter to get the state - (m, V) = self._raw_predict(Xnew,filteronly=filteronly) + (m, V) = self._raw_predict(Xnew,filteronly=filteronly, p_balance=p_balance) # Add the noise variance to the state variance if include_likelihood: @@ -277,8 +310,22 @@ def predict(self, Xnew=None, filteronly=False, include_likelihood=True, **kw): # Return mean and variance return m, V - def predict_quantiles(self, Xnew=None, quantiles=(2.5, 97.5), **kw): - mu, var = self._raw_predict(Xnew) + def predict_quantiles(self, Xnew=None, quantiles=(2.5, 97.5), balance=None, **kw): + """ + Inputs: + ------------------ + + balance: bool + Whether to balance or not the model as a whole + + """ + if balance is None: + p_balance = self.balance + else: + p_balance = balance + + + mu, var = self._raw_predict(Xnew, p_balance=p_balance) #import pdb; pdb.set_trace() return [stats.norm.ppf(q/100.)*np.sqrt(var + float(self.Gaussian_noise.variance)) + mu for q in quantiles] diff --git a/GPy/testing/gpy_kernels_state_space_tests.py b/GPy/testing/gpy_kernels_state_space_tests.py index 4714dda3e..1ce495839 100644 --- a/GPy/testing/gpy_kernels_state_space_tests.py +++ b/GPy/testing/gpy_kernels_state_space_tests.py @@ -91,12 +91,14 @@ def test_Matern52_kernel(self,): mean_compare_decimal=5, var_compare_decimal=5) def test_RBF_kernel(self,): + #import pdb;pdb.set_trace() + np.random.seed(234) # seed the random number generator (X,Y) = generate_sine_data(x_points=None, sin_period=5.0, sin_ampl=10.0, noise_var=2.0, plot = False, points_num=50, x_interval = (0, 20), random=True) X.shape = (X.shape[0],1); Y.shape = (Y.shape[0],1) - ss_kernel = GPy.kern.sde_RBF(1, 110., 1.5, active_dims=[0,]) + ss_kernel = GPy.kern.sde_RBF(1, 110., 1.5, active_dims=[0,], balance=True, approx_order=10) gp_kernel = GPy.kern.RBF(1, 110., 1.5, active_dims=[0,]) self.run_for_model(X, Y, ss_kernel, check_gradients=True, @@ -375,7 +377,7 @@ def get_new_kernels(): print("Running state-space inference tests...") unittest.main() - #tt = StateSpaceKernelsTests('test_periodic_kernel') + #tt = StateSpaceKernelsTests('test_RBF_kernel') #import pdb; pdb.set_trace() #tt.test_Matern32_kernel() #tt.test_Matern52_kernel() From 9824e02a78f56af89f11193165edfaa1f4c9e7dd Mon Sep 17 00:00:00 2001 From: Alex Grigorievskiy Date: Tue, 13 Jun 2017 16:07:41 +0300 Subject: [PATCH 03/48] SDE: Remove sde kernels from the _src folder. --- GPy/kern/_src/sde_brownian.py | 57 -------- GPy/kern/_src/sde_linear.py | 64 --------- GPy/kern/_src/sde_matern.py | 135 ------------------ GPy/kern/_src/sde_standard_periodic.py | 178 ----------------------- GPy/kern/_src/sde_static.py | 101 ------------- GPy/kern/_src/sde_stationary.py | 190 ------------------------- 6 files changed, 725 deletions(-) delete mode 100644 GPy/kern/_src/sde_brownian.py delete mode 100644 GPy/kern/_src/sde_linear.py delete mode 100644 GPy/kern/_src/sde_matern.py delete mode 100644 GPy/kern/_src/sde_standard_periodic.py delete mode 100644 GPy/kern/_src/sde_static.py delete mode 100644 GPy/kern/_src/sde_stationary.py diff --git a/GPy/kern/_src/sde_brownian.py b/GPy/kern/_src/sde_brownian.py deleted file mode 100644 index 559501437..000000000 --- a/GPy/kern/_src/sde_brownian.py +++ /dev/null @@ -1,57 +0,0 @@ -# -*- coding: utf-8 -*- -""" -Classes in this module enhance Brownian motion covariance function with the -Stochastic Differential Equation (SDE) functionality. -""" - -from .brownian import Brownian - -import numpy as np - -class sde_Brownian(Brownian): - """ - - Class provide extra functionality to transfer this covariance function into - SDE form. - - Linear kernel: - - .. math:: - - k(x,y) = \sigma^2 min(x,y) - - """ - - def sde_update_gradient_full(self, gradients): - """ - Update gradient in the order in which parameters are represented in the - kernel - """ - - self.variance.gradient = gradients[0] - - def sde(self): - """ - Return the state space representation of the covariance. - """ - - variance = float(self.variance.values) # this is initial variancve in Bayesian linear regression - - F = np.array( ((0,1.0),(0,0) )) - L = np.array( ((1.0,),(0,)) ) - Qc = np.array( ((variance,),) ) - H = np.array( ((1.0,0),) ) - - Pinf = np.array( ( (0, -0.5*variance ), (-0.5*variance, 0) ) ) - #P0 = Pinf.copy() - P0 = np.zeros((2,2)) - #Pinf = np.array( ( (t0, 1.0), (1.0, 1.0/t0) ) ) * variance - dF = np.zeros((2,2,1)) - dQc = np.ones( (1,1,1) ) - - dPinf = np.zeros((2,2,1)) - dPinf[:,:,0] = np.array( ( (0, -0.5), (-0.5, 0) ) ) - #dP0 = dPinf.copy() - dP0 = np.zeros((2,2,1)) - - return (F, L, Qc, H, Pinf, P0, dF, dQc, dPinf, dP0) diff --git a/GPy/kern/_src/sde_linear.py b/GPy/kern/_src/sde_linear.py deleted file mode 100644 index 031f0f5f7..000000000 --- a/GPy/kern/_src/sde_linear.py +++ /dev/null @@ -1,64 +0,0 @@ -# -*- coding: utf-8 -*- -""" -Classes in this module enhance Linear covariance function with the -Stochastic Differential Equation (SDE) functionality. -""" -from .linear import Linear - -import numpy as np - -class sde_Linear(Linear): - """ - - Class provide extra functionality to transfer this covariance function into - SDE form. - - Linear kernel: - - .. math:: - - k(x,y) = \sum_{i=1}^{input dim} \sigma^2_i x_iy_i - - """ - def __init__(self, input_dim, X, variances=None, ARD=False, active_dims=None, name='linear'): - """ - Modify the init method, because one extra parameter is required. X - points - on the X axis. - """ - - super(sde_Linear, self).__init__(input_dim, variances, ARD, active_dims, name) - - self.t0 = np.min(X) - - - def sde_update_gradient_full(self, gradients): - """ - Update gradient in the order in which parameters are represented in the - kernel - """ - - self.variances.gradient = gradients[0] - - def sde(self): - """ - Return the state space representation of the covariance. - """ - - variance = float(self.variances.values) # this is initial variancve in Bayesian linear regression - t0 = float(self.t0) - - F = np.array( ((0,1.0),(0,0) )) - L = np.array( ((0,),(1.0,)) ) - Qc = np.zeros((1,1)) - H = np.array( ((1.0,0),) ) - - Pinf = np.zeros((2,2)) - P0 = np.array( ( (t0**2, t0), (t0, 1) ) ) * variance - dF = np.zeros((2,2,1)) - dQc = np.zeros( (1,1,1) ) - - dPinf = np.zeros((2,2,1)) - dP0 = np.zeros((2,2,1)) - dP0[:,:,0] = P0 / variance - - return (F, L, Qc, H, Pinf, P0, dF, dQc, dPinf, dP0) diff --git a/GPy/kern/_src/sde_matern.py b/GPy/kern/_src/sde_matern.py deleted file mode 100644 index 0ce1cf98e..000000000 --- a/GPy/kern/_src/sde_matern.py +++ /dev/null @@ -1,135 +0,0 @@ -# -*- coding: utf-8 -*- -""" -Classes in this module enhance Matern covariance functions with the -Stochastic Differential Equation (SDE) functionality. -""" -from .stationary import Matern32 -from .stationary import Matern52 -import numpy as np - -class sde_Matern32(Matern32): - """ - - Class provide extra functionality to transfer this covariance function into - SDE forrm. - - Matern 3/2 kernel: - - .. math:: - - k(r) = \sigma^2 (1 + \sqrt{3} r) \exp(- \sqrt{3} r) \\ \\ \\ \\ \text{ where } r = \sqrt{\sum_{i=1}^{input dim} \frac{(x_i-y_i)^2}{\ell_i^2} } - - """ - def sde_update_gradient_full(self, gradients): - """ - Update gradient in the order in which parameters are represented in the - kernel - """ - - self.variance.gradient = gradients[0] - self.lengthscale.gradient = gradients[1] - - def sde(self): - """ - Return the state space representation of the covariance. - """ - - variance = float(self.variance.values) - lengthscale = float(self.lengthscale.values) - - foo = np.sqrt(3.)/lengthscale - F = np.array(((0, 1.0), (-foo**2, -2*foo))) - L = np.array(( (0,), (1.0,) )) - Qc = np.array(((12.*np.sqrt(3) / lengthscale**3 * variance,),)) - H = np.array(((1.0, 0),)) - Pinf = np.array(((variance, 0.0), (0.0, 3.*variance/(lengthscale**2)))) - P0 = Pinf.copy() - - # Allocate space for the derivatives - dF = np.empty([F.shape[0],F.shape[1],2]) - dQc = np.empty([Qc.shape[0],Qc.shape[1],2]) - dPinf = np.empty([Pinf.shape[0],Pinf.shape[1],2]) - # The partial derivatives - dFvariance = np.zeros((2,2)) - dFlengthscale = np.array(((0,0), (6./lengthscale**3,2*np.sqrt(3)/lengthscale**2))) - dQcvariance = np.array((12.*np.sqrt(3)/lengthscale**3)) - dQclengthscale = np.array((-3*12*np.sqrt(3)/lengthscale**4*variance)) - dPinfvariance = np.array(((1,0),(0,3./lengthscale**2))) - dPinflengthscale = np.array(((0,0), (0,-6*variance/lengthscale**3))) - # Combine the derivatives - dF[:,:,0] = dFvariance - dF[:,:,1] = dFlengthscale - dQc[:,:,0] = dQcvariance - dQc[:,:,1] = dQclengthscale - dPinf[:,:,0] = dPinfvariance - dPinf[:,:,1] = dPinflengthscale - dP0 = dPinf.copy() - - return (F, L, Qc, H, Pinf, P0, dF, dQc, dPinf, dP0) - -class sde_Matern52(Matern52): - """ - - Class provide extra functionality to transfer this covariance function into - SDE forrm. - - Matern 5/2 kernel: - - .. math:: - - k(r) = \sigma^2 (1 + \sqrt{5} r + \frac{5}{3}r^2) \exp(- \sqrt{5} r) \\ \\ \\ \\ \text{ where } r = \sqrt{\sum_{i=1}^{input dim} \frac{(x_i-y_i)^2}{\ell_i^2} } - - """ - def sde_update_gradient_full(self, gradients): - """ - Update gradient in the order in which parameters are represented in the - kernel - """ - - self.variance.gradient = gradients[0] - self.lengthscale.gradient = gradients[1] - - def sde(self): - """ - Return the state space representation of the covariance. - """ - - variance = float(self.variance.values) - lengthscale = float(self.lengthscale.values) - - lamda = np.sqrt(5.0)/lengthscale - kappa = 5.0/3.0*variance/lengthscale**2 - - F = np.array(((0, 1,0), (0, 0, 1), (-lamda**3, -3.0*lamda**2, -3*lamda))) - L = np.array(((0,),(0,),(1,))) - Qc = np.array((((variance*400.0*np.sqrt(5.0)/3.0/lengthscale**5),),)) - H = np.array(((1,0,0),)) - - Pinf = np.array(((variance,0,-kappa), (0, kappa, 0), (-kappa, 0, 25.0*variance/lengthscale**4))) - P0 = Pinf.copy() - # Allocate space for the derivatives - dF = np.empty((3,3,2)) - dQc = np.empty((1,1,2)) - dPinf = np.empty((3,3,2)) - - # The partial derivatives - dFvariance = np.zeros((3,3)) - dFlengthscale = np.array(((0,0,0),(0,0,0),(15.0*np.sqrt(5.0)/lengthscale**4, - 30.0/lengthscale**3, 3*np.sqrt(5.0)/lengthscale**2))) - dQcvariance = np.array((((400*np.sqrt(5)/3/lengthscale**5,),))) - dQclengthscale = np.array((((-variance*2000*np.sqrt(5)/3/lengthscale**6,),))) - - dPinf_variance = Pinf/variance - kappa2 = -2.0*kappa/lengthscale - dPinf_lengthscale = np.array(((0,0,-kappa2),(0,kappa2,0),(-kappa2, - 0,-100*variance/lengthscale**5))) - # Combine the derivatives - dF[:,:,0] = dFvariance - dF[:,:,1] = dFlengthscale - dQc[:,:,0] = dQcvariance - dQc[:,:,1] = dQclengthscale - dPinf[:,:,0] = dPinf_variance - dPinf[:,:,1] = dPinf_lengthscale - dP0 = dPinf.copy() - - return (F, L, Qc, H, Pinf, P0, dF, dQc, dPinf, dP0) \ No newline at end of file diff --git a/GPy/kern/_src/sde_standard_periodic.py b/GPy/kern/_src/sde_standard_periodic.py deleted file mode 100644 index c3df7d923..000000000 --- a/GPy/kern/_src/sde_standard_periodic.py +++ /dev/null @@ -1,178 +0,0 @@ -# -*- coding: utf-8 -*- -""" -Classes in this module enhance Matern covariance functions with the -Stochastic Differential Equation (SDE) functionality. -""" -from .standard_periodic import StdPeriodic - -import numpy as np -import scipy as sp - -from scipy import special as special - -class sde_StdPeriodic(StdPeriodic): - """ - - Class provide extra functionality to transfer this covariance function into - SDE form. - - Standard Periodic kernel: - - .. math:: - - k(x,y) = \theta_1 \exp \left[ - \frac{1}{2} {}\sum_{i=1}^{input\_dim} - \left( \frac{\sin(\frac{\pi}{\lambda_i} (x_i - y_i) )}{l_i} \right)^2 \right] } - - """ - def sde_update_gradient_full(self, gradients): - """ - Update gradient in the order in which parameters are represented in the - kernel - """ - - self.variance.gradient = gradients[0] - self.wavelengths.gradient = gradients[1] - self.lengthscales.gradient = gradients[2] - - def sde(self): - """ - Return the state space representation of the covariance. - - - ! Note: one must constrain lengthscale not to drop below 0.25. - After this bessel functions of the first kind grows to very high. - - ! Note: one must keep wevelength also not very low. Because then - the gradients wrt wavelength become ustable. - However this might depend on the data. For test example with - 300 data points the low limit is 0.15. - """ - - # Params to use: (in that order) - #self.variance - #self.wavelengths - #self.lengthscales - N = 7 # approximation order - - - w0 = 2*np.pi/self.wavelengths # frequency - lengthscales = 2*self.lengthscales - - [q2,dq2l] = seriescoeff(N,lengthscales,self.variance) - # lengthscale is multiplied by 2 because of slightly different - # formula for periodic covariance function. - # For the same reason: - - dq2l = 2*dq2l - - if np.any( np.isfinite(q2) == False): - raise ValueError("SDE periodic covariance error 1") - - if np.any( np.isfinite(dq2l) == False): - raise ValueError("SDE periodic covariance error 2") - - F = np.kron(np.diag(range(0,N+1)),np.array( ((0, -w0), (w0, 0)) ) ) - L = np.eye(2*(N+1)) - Qc = np.zeros((2*(N+1), 2*(N+1))) - P_inf = np.kron(np.diag(q2),np.eye(2)) - H = np.kron(np.ones((1,N+1)),np.array((1,0)) ) - P0 = P_inf.copy() - - # Derivatives - dF = np.empty((F.shape[0], F.shape[1], 3)) - dQc = np.empty((Qc.shape[0], Qc.shape[1], 3)) - dP_inf = np.empty((P_inf.shape[0], P_inf.shape[1], 3)) - - # Derivatives wrt self.variance - dF[:,:,0] = np.zeros(F.shape) - 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 ); - dQc[:,:,1] = np.zeros(Qc.shape) - dP_inf[:,:,1] = np.zeros(P_inf.shape) - - # Derivatives self.lengthscales - dF[:,:,2] = np.zeros(F.shape) - dQc[:,:,2] = np.zeros(Qc.shape) - dP_inf[:,:,2] = np.kron(np.diag(dq2l),np.eye(2)) - dP0 = dP_inf.copy() - - return (F, L, Qc, H, P_inf, P0, dF, dQc, dP_inf, dP0) - - - - -def seriescoeff(m=6,lengthScale=1.0,magnSigma2=1.0, true_covariance=False): - """ - Calculate the coefficients q_j^2 for the covariance function - approximation: - - k(\tau) = \sum_{j=0}^{+\infty} q_j^2 \cos(j\omega_0 \tau) - - Reference is: - - [1] Arno Solin and Simo Särkkä (2014). Explicit link between periodic - covariance functions and state space models. In Proceedings of the - Seventeenth International Conference on Artifcial Intelligence and - Statistics (AISTATS 2014). JMLR: W&CP, volume 33. - - Note! Only the infinite approximation (through Bessel function) - is currently implemented. - - Input: - ---------------- - - m: int - Degree of approximation. Default 6. - lengthScale: float - Length scale parameter in the kerenl - magnSigma2:float - Multiplier in front of the kernel. - - - Output: - ----------------- - - coeffs: array(m+1) - Covariance series coefficients - - coeffs_dl: array(m+1) - Derivatives of the coefficients with respect to lengthscale. - - """ - - if true_covariance: - - bb = lambda j,m: (1.0 + np.array((j != 0), dtype=np.float64) ) / (2**(j)) *\ - sp.special.binom(j, sp.floor( (j-m)/2.0 * np.array(m<=j, dtype=np.float64) ))*\ - np.array(m<=j, dtype=np.float64) *np.array(sp.mod(j-m,2)==0, dtype=np.float64) - - M,J = np.meshgrid(range(0,m+1),range(0,m+1)) - - coeffs = bb(J,M) / sp.misc.factorial(J) * sp.exp( -lengthScale**(-2) ) *\ - (lengthScale**(-2))**J *magnSigma2 - - coeffs_dl = np.sum( coeffs*lengthScale**(-3)*(2.0-2.0*J*lengthScale**2),0) - - coeffs = np.sum(coeffs,0) - - else: - coeffs = 2*magnSigma2*sp.exp( -lengthScale**(-2) ) * special.iv(range(0,m+1),1.0/lengthScale**(2)) - if np.any( np.isfinite(coeffs) == False): - raise ValueError("sde_standard_periodic: Coefficients are not finite!") - #import pdb; pdb.set_trace() - coeffs[0] = 0.5*coeffs[0] - - # Derivatives wrt (lengthScale) - coeffs_dl = np.zeros(m+1) - coeffs_dl[1:] = magnSigma2*lengthScale**(-3) * sp.exp(-lengthScale**(-2))*\ - (-4*special.iv(range(0,m),lengthScale**(-2)) + 4*(1+np.arange(1,m+1)*lengthScale**(2))*special.iv(range(1,m+1),lengthScale**(-2)) ) - - # The first element - coeffs_dl[0] = magnSigma2*lengthScale**(-3) * np.exp(-lengthScale**(-2))*\ - (2*special.iv(0,lengthScale**(-2)) - 2*special.iv(1,lengthScale**(-2)) ) - - - return coeffs, coeffs_dl diff --git a/GPy/kern/_src/sde_static.py b/GPy/kern/_src/sde_static.py deleted file mode 100644 index ae8ed194d..000000000 --- a/GPy/kern/_src/sde_static.py +++ /dev/null @@ -1,101 +0,0 @@ -# -*- coding: utf-8 -*- -""" -Classes in this module enhance Static covariance functions with the -Stochastic Differential Equation (SDE) functionality. -""" -from .static import White -from .static import Bias - -import numpy as np - -class sde_White(White): - """ - - Class provide extra functionality to transfer this covariance function into - SDE forrm. - - White kernel: - - .. math:: - - k(x,y) = \alpha*\delta(x-y) - - """ - - def sde_update_gradient_full(self, gradients): - """ - Update gradient in the order in which parameters are represented in the - kernel - """ - - self.variance.gradient = gradients[0] - - def sde(self): - """ - Return the state space representation of the covariance. - """ - - variance = float(self.variance.values) - - F = np.array( ((-np.inf,),) ) - L = np.array( ((1.0,),) ) - Qc = np.array( ((variance,),) ) - H = np.array( ((1.0,),) ) - - Pinf = np.array( ((variance,),) ) - P0 = Pinf.copy() - - dF = np.zeros((1,1,1)) - dQc = np.zeros((1,1,1)) - dQc[:,:,0] = np.array( ((1.0,),) ) - - dPinf = np.zeros((1,1,1)) - dPinf[:,:,0] = np.array( ((1.0,),) ) - dP0 = dPinf.copy() - - return (F, L, Qc, H, Pinf, P0, dF, dQc, dPinf, dP0) - - -class sde_Bias(Bias): - """ - - Class provide extra functionality to transfer this covariance function into - SDE forrm. - - Bias kernel: - - .. math:: - - k(x,y) = \alpha - - """ - def sde_update_gradient_full(self, gradients): - """ - Update gradient in the order in which parameters are represented in the - kernel - """ - - self.variance.gradient = gradients[0] - - def sde(self): - """ - Return the state space representation of the covariance. - """ - variance = float(self.variance.values) - - F = np.array( ((0.0,),)) - L = np.array( ((1.0,),)) - Qc = np.zeros((1,1)) - H = np.array( ((1.0,),)) - - Pinf = np.zeros((1,1)) - P0 = np.array( ((variance,),) ) - - dF = np.zeros((1,1,1)) - dQc = np.zeros((1,1,1)) - - dPinf = np.zeros((1,1,1)) - dP0 = np.zeros((1,1,1)) - dP0[:,:,0] = np.array( ((1.0,),) ) - - return (F, L, Qc, H, Pinf, P0, dF, dQc, dPinf, dP0) \ No newline at end of file diff --git a/GPy/kern/_src/sde_stationary.py b/GPy/kern/_src/sde_stationary.py deleted file mode 100644 index 9504c5c37..000000000 --- a/GPy/kern/_src/sde_stationary.py +++ /dev/null @@ -1,190 +0,0 @@ -# -*- coding: utf-8 -*- -""" -Classes in this module enhance several stationary covariance functions with the -Stochastic Differential Equation (SDE) functionality. -""" -from .rbf import RBF -from .stationary import Exponential -from .stationary import RatQuad - -import numpy as np -import scipy as sp - -class sde_RBF(RBF): - """ - - Class provide extra functionality to transfer this covariance function into - SDE form. - - Radial Basis Function kernel: - - .. math:: - - k(r) = \sigma^2 \exp \\bigg(- \\frac{1}{2} r^2 \\bigg) \\ \\ \\ \\ \text{ where } r = \sqrt{\sum_{i=1}^{input dim} \frac{(x_i-y_i)^2}{\ell_i^2} } - - """ - def sde_update_gradient_full(self, gradients): - """ - Update gradient in the order in which parameters are represented in the - kernel - """ - - self.variance.gradient = gradients[0] - self.lengthscale.gradient = gradients[1] - - def sde(self): - """ - Return the state space representation of the covariance. - """ - - N = 10# approximation order ( number of terms in exponent series expansion) - roots_rounding_decimals = 6 - - fn = np.math.factorial(N) - - kappa = 1.0/2.0/self.lengthscale**2 - - Qc = np.array((self.variance*np.sqrt(np.pi/kappa)*fn*(4*kappa)**N,),) - - pp = np.zeros((2*N+1,)) # array of polynomial coefficients from higher power to lower - - for n in range(0, N+1): # (2N+1) - number of polynomial coefficients - pp[2*(N-n)] = fn*(4.0*kappa)**(N-n)/np.math.factorial(n)*(-1)**n - - pp = sp.poly1d(pp) - roots = sp.roots(pp) - - neg_real_part_roots = roots[np.round(np.real(roots) ,roots_rounding_decimals) < 0] - aa = sp.poly1d(neg_real_part_roots, r=True).coeffs - - F = np.diag(np.ones((N-1,)),1) - F[-1,:] = -aa[-1:0:-1] - - L= np.zeros((N,1)) - L[N-1,0] = 1 - - H = np.zeros((1,N)) - H[0,0] = 1 - - # Infinite covariance: - Pinf = sp.linalg.solve_lyapunov(F, -np.dot(L,np.dot( Qc[0,0],L.T))) - Pinf = 0.5*(Pinf + Pinf.T) - # Allocating space for derivatives - dF = np.empty([F.shape[0],F.shape[1],2]) - dQc = np.empty([Qc.shape[0],Qc.shape[1],2]) - dPinf = np.empty([Pinf.shape[0],Pinf.shape[1],2]) - - # Derivatives: - dFvariance = np.zeros(F.shape) - dFlengthscale = np.zeros(F.shape) - dFlengthscale[-1,:] = -aa[-1:0:-1]/self.lengthscale * np.arange(-N,0,1) - - dQcvariance = Qc/self.variance - dQclengthscale = np.array(((self.variance*np.sqrt(2*np.pi)*fn*2**N*self.lengthscale**(-2*N)*(1-2*N,),))) - - dPinf_variance = Pinf/self.variance - - lp = Pinf.shape[0] - coeff = np.arange(1,lp+1).reshape(lp,1) + np.arange(1,lp+1).reshape(1,lp) - 2 - coeff[np.mod(coeff,2) != 0] = 0 - dPinf_lengthscale = -1/self.lengthscale*Pinf*coeff - - dF[:,:,0] = dFvariance - dF[:,:,1] = dFlengthscale - dQc[:,:,0] = dQcvariance - dQc[:,:,1] = dQclengthscale - dPinf[:,:,0] = dPinf_variance - dPinf[:,:,1] = dPinf_lengthscale - - P0 = Pinf.copy() - dP0 = dPinf.copy() - - # Benefits of this are not very sound. Helps only in one case: - # SVD Kalman + RBF kernel - import GPy.models.state_space_main as ssm - (F, L, Qc, H, Pinf, P0, dF, dQc, dPinf,dP0, T) = ssm.balance_ss_model(F, L, Qc, H, Pinf, P0, dF, dQc, dPinf, dP0 ) - - return (F, L, Qc, H, Pinf, P0, dF, dQc, dPinf, dP0) - -class sde_Exponential(Exponential): - """ - - Class provide extra functionality to transfer this covariance function into - SDE form. - - Exponential kernel: - - .. math:: - - k(r) = \sigma^2 \exp \\bigg(- \\frac{1}{2} r \\bigg) \\ \\ \\ \\ \text{ where } r = \sqrt{\sum_{i=1}^{input dim} \frac{(x_i-y_i)^2}{\ell_i^2} } - - """ - - def sde_update_gradient_full(self, gradients): - """ - Update gradient in the order in which parameters are represented in the - kernel - """ - - self.variance.gradient = gradients[0] - self.lengthscale.gradient = gradients[1] - - def sde(self): - """ - Return the state space representation of the covariance. - """ - variance = float(self.variance.values) - lengthscale = float(self.lengthscale) - - F = np.array(((-1.0/lengthscale,),)) - L = np.array(((1.0,),)) - Qc = np.array( ((2.0*variance/lengthscale,),) ) - H = np.array(((1.0,),)) - Pinf = np.array(((variance,),)) - P0 = Pinf.copy() - - dF = np.zeros((1,1,2)); - dQc = np.zeros((1,1,2)); - dPinf = np.zeros((1,1,2)); - - dF[:,:,0] = 0.0 - dF[:,:,1] = 1.0/lengthscale**2 - - dQc[:,:,0] = 2.0/lengthscale - dQc[:,:,1] = -2.0*variance/lengthscale**2 - - dPinf[:,:,0] = 1.0 - dPinf[:,:,1] = 0.0 - - dP0 = dPinf.copy() - - return (F, L, Qc, H, Pinf, P0, dF, dQc, dPinf, dP0) - -class sde_RatQuad(RatQuad): - """ - - Class provide extra functionality to transfer this covariance function into - SDE form. - - Rational Quadratic kernel: - - .. math:: - - k(r) = \sigma^2 \\bigg( 1 + \\frac{r^2}{2} \\bigg)^{- \alpha} \\ \\ \\ \\ \text{ where } r = \sqrt{\sum_{i=1}^{input dim} \frac{(x_i-y_i)^2}{\ell_i^2} } - - """ - - def sde(self): - """ - Return the state space representation of the covariance. - """ - - assert False, 'Not Implemented' - - # Params to use: - - # self.lengthscale - # self.variance - #self.power - - #return (F, L, Qc, H, Pinf, dF, dQc, dPinf) From 6af11edb6db4411cc30159fce4dd56d3e1fd4d40 Mon Sep 17 00:00:00 2001 From: Alex Grigorievskiy Date: Tue, 13 Jun 2017 22:55:04 +0300 Subject: [PATCH 04/48] SDE: removed some unnecessary comments. --- GPy/models/state_space_main.py | 124 -------------------------------- GPy/models/state_space_model.py | 4 +- 2 files changed, 2 insertions(+), 126 deletions(-) diff --git a/GPy/models/state_space_main.py b/GPy/models/state_space_main.py index dd639ad06..6ed2fbeb7 100644 --- a/GPy/models/state_space_main.py +++ b/GPy/models/state_space_main.py @@ -3415,10 +3415,6 @@ def lti_sde_to_descrete(F,L,Qc,dt,compute_derivatives=False, #Q_noise = Q_noise_1 - # Return - #import pdb; pdb.set_trace() - #if dt != 0: - # Q_noise = Q_noise + np.eye(Q_noise.shape[0])*1e-8 Q_noise = 0.5*(Q_noise + Q_noise.T) # Symmetrize return A, Q_noise,None, dA, dQ @@ -3624,123 +3620,3 @@ def balance_ss_model(F,L,Qc,H,Pinf,P0,dF=None,dQc=None,dPinf=None,dP0=None): # (F,L,Qc,H,Pinf,P0,dF,dQc,dPinf,dP0) return bF, bL, bQc, bH, bPinf, bP0, bdF, bdQc, bdPinf, bdP0 - -#def psd_matrix_inverse(k,Q, U=None,S=None, p_largest_cond_num=None, regularization_type=2): -# """ -# Function inverts positive definite matrix and regularizes the inverse. -# Regularization is useful when original matrix is badly conditioned. -# Function is currently used only in SparseGP code. -# -# Inputs: -# ------------------------------ -# k: int -# Iteration umber. Used for information only. Value -1 corresponds to P_inf_inv. -# -# Q: matrix -# To be inverted -# -# U,S: matrix. vector -# SVD components of Q -# -# p_largest_cond_num: float -# Largest condition value for the inverted matrix. If cond. number is smaller than that -# no regularization happen. -# -# regularization_type: 1 or 2 -# Regularization type. -# """ -# #import pdb; pdb.set_trace() -## if (k == 0) or (k == -1): # -1 - P_inf_inv computation -## import pdb; pdb.set_trace() -# -# if p_largest_cond_num is None: -# raise ValueError("psd_matrix_inverse: None p_largest_cond_num") -# -# if U is None or S is None: -# (U, S, Vh) = sp.linalg.svd( Q, full_matrices=False, compute_uv=True, overwrite_a=False, check_finite=False) -# if S[0] < (1e-4): -# #import pdb; pdb.set_trace() -# warnings.warn("""state_space_main psd_matrix_inverse: largest singular value is too small {0:e}. -# condition number is {1:e} Maybe somethigng is wrong -# """.format(S[0], S[0]/S[-1])) -# S = S + (1e-4 - S[0]) # make the S[0] at least 1e-4 -# -# current_conditional_number = S[0]/S[-1] -# if (current_conditional_number > p_largest_cond_num): -# if (regularization_type == 1): -# regularizer = S[0] / p_largest_cond_num -# # the second computation of SVD is done to compute more precisely singular -# # vectors of small singular values, since small singular values become large. -# # It is not very clear how this step is useful but test is here. -# (U, S, Vh) = sp.linalg.svd( Q + regularizer*np.eye(Q.shape[0]), -# full_matrices=False, compute_uv=True, overwrite_a=False, check_finite=False) -# -# Q_inverse_r = np.dot( U * 1.0/S , U.T ) # Assume Q_inv is positive definite -# -# # In this case, RBF kernel we get complx eigenvalues. Probably -# # for small eigenvalue corresponding eigenvectors are not very orthogonal. -# ##########Q_inverse = np.dot( Vh.T * ( 1.0/(S + regularizer)) , U.T ) -# elif (regularization_type == 2): -# -# new_border_value = np.sqrt(current_conditional_number)/2 -# if p_largest_cond_num >= new_border_value: # this type of regularization works -# regularizer = ( S[0] / p_largest_cond_num / 2.0 )**2 -# -# Q_inverse_r = np.dot( U * ( S/(S**2 + regularizer)) , U.T ) # Assume Q_inv is positive definite -# else: -# -# better_curr_cond_num = new_border_value -# warnings.warn("""state_space_main psd_matrix_inverse: reg_type = 2 can't be done completely. -# Current conditionakl number {0:e} is reduced to {1:e} by reg_type = 1""".format(current_conditional_number, better_curr_cond_num)) -# -# regularizer = S[0] / better_curr_cond_num -# # the second computation of SVD is done to compute more precisely singular -# # vectors of small singular values, since small singular values become large. -# # It is not very clear how this step is useful but test is here. -# (U, S, Vh) = sp.linalg.svd( Q + regularizer*np.eye(Q.shape[0]), -# full_matrices=False, compute_uv=True, overwrite_a=False, check_finite=False) -# -# regularizer = ( S[0] / p_largest_cond_num / 2.0 )**2 -# -# Q_inverse_r = np.dot( U * ( S/(S**2 + regularizer)) , U.T ) # Assume Q_inv is positive definite -# -# assert regularizer*10 < S[0], "regularizer is not << S[0]" -# assert regularizer > 10*S[-1], "regularizer is not >> S[-1]" -# -## Old version -> -## lamda_star = np.sqrt(current_conditional_number) -## if 2*p_largest_cond_num >= lamda_star: -## lamda = current_conditional_number / 2 / p_largest_cond_num -## -## regularizer = (S[-1] * lamda)**2 -## -## Q_inverse_r = np.dot( U * ( S/(S**2 + regularizer)) , U.T ) # Assume Q_inv is positive definite -## else: -## better_curr_cond_num = (2*p_largest_cond_num)**2 / 2 # division by 2 just in case here -## warnings.warn("""state_space_main psd_matrix_inverse: reg_type = 2 can't be done completely. -## Current conditionakl number {0:e} is reduced to {1:e} by reg_type = 1""".format(current_conditional_number, better_curr_cond_num)) -## -## regularizer = S[0] / better_curr_cond_num -## # the second computation of SVD is done to compute more precisely singular -## # vectors of small singular values, since small singular values become large. -## # It is not very clear how this step is useful but test is here. -## (U, S, Vh) = sp.linalg.svd( Q + regularizer*np.eye(Q.shape[0]), -## full_matrices=False, compute_uv=True, overwrite_a=False, check_finite=False) -## -## lamda = better_curr_cond_num / 2 / p_largest_cond_num -## -## regularizer = (S[-1] * lamda)**2 -## -## Q_inverse_r = np.dot( U * ( S/(S**2 + regularizer)) , U.T ) # Assume Q_inv is positive definite -## -## assert lamda > 10, "Some assumptions are incorrect if this is not satisfied." -## Old version <- -# else: -# raise ValueError("AQcompute_batch_Python:Q_inverse: Invalid regularization type") -# -# else: -# Q_inverse_r = np.dot( U * 1.0/S , U.T ) # Assume Q_inv is positive definite -# # When checking conditional number 2 times difference is ok. -# Q_inverse_r = 0.5*(Q_inverse_r + Q_inverse_r.T) -# -# return Q_inverse_r \ No newline at end of file diff --git a/GPy/models/state_space_model.py b/GPy/models/state_space_model.py index c74a25f2a..d16b5adc7 100644 --- a/GPy/models/state_space_model.py +++ b/GPy/models/state_space_model.py @@ -100,8 +100,8 @@ def parameters_changed(self): # Get the model matrices from the kernel (F,L,Qc,H,P_inf, P0, dFt,dQct,dP_inft, dP0t) = self.kern.sde() - #Qc = Qc + np.eye(Qc.shape[0]) * 1e-8 - #import pdb; pdb.set_trace() + + # necessary parameters measurement_dim = self.output_dim grad_params_no = dFt.shape[2]+1 # we also add measurement noise as a parameter From 7950b88bf987ee3ef2c3d7ede6b866f22e773068 Mon Sep 17 00:00:00 2001 From: Joachim van der Herten Date: Fri, 14 Jul 2017 23:22:31 +0200 Subject: [PATCH 05/48] Implementation of student-t processes --- .../latent_function_inference/__init__.py | 1 + .../exact_studentt_inference.py | 49 +++ .../latent_function_inference/posterior.py | 147 +++++---- GPy/models/__init__.py | 1 + GPy/models/tp_regression.py | 298 ++++++++++++++++++ GPy/plotting/__init__.py | 13 + GPy/testing/gp_tests.py | 1 + GPy/testing/model_tests.py | 39 +++ GPy/testing/tp_tests.py | 145 +++++++++ 9 files changed, 630 insertions(+), 64 deletions(-) create mode 100644 GPy/inference/latent_function_inference/exact_studentt_inference.py create mode 100644 GPy/models/tp_regression.py create mode 100644 GPy/testing/tp_tests.py diff --git a/GPy/inference/latent_function_inference/__init__.py b/GPy/inference/latent_function_inference/__init__.py index 3938a6a48..91a4d261a 100644 --- a/GPy/inference/latent_function_inference/__init__.py +++ b/GPy/inference/latent_function_inference/__init__.py @@ -62,6 +62,7 @@ def __setstate__(self, state): self.append(inf) from .exact_gaussian_inference import ExactGaussianInference +from .exact_studentt_inference import ExactStudentTInference from .laplace import Laplace,LaplaceBlock from GPy.inference.latent_function_inference.var_dtc import VarDTC from .expectation_propagation import EP, EPDTC diff --git a/GPy/inference/latent_function_inference/exact_studentt_inference.py b/GPy/inference/latent_function_inference/exact_studentt_inference.py new file mode 100644 index 000000000..161dd289c --- /dev/null +++ b/GPy/inference/latent_function_inference/exact_studentt_inference.py @@ -0,0 +1,49 @@ +# Copyright (c) 2017, GPy authors (see AUTHORS.txt). +# Licensed under the BSD 3-clause license (see LICENSE.txt) + +from . import LatentFunctionInference +from .posterior import StudentTPosterior +from ...util.linalg import pdinv, dpotrs, tdot +from ...util import diag + +import numpy as np +from scipy.special import gammaln, digamma + + +class ExactStudentTInference(LatentFunctionInference): + """ + An object for inference of student-t processes (not for GP with student-t likelihood!). + + The function self.inference returns a StudentTPosterior object, which summarizes + the posterior. + """ + + def inference(self, kern, X, Y, nu, mean_function=None, K=None): + m = 0 if mean_function is None else mean_function.f(X) + K = kern.K(X) if K is None else K + + YYT_factor = Y - m + Ky = K.copy() + diag.add(Ky, 1e-8) + + # Posterior representation + Wi, LW, LWi, W_logdet = pdinv(Ky) + alpha, _ = dpotrs(LW, YYT_factor, lower=1) + beta = np.sum(alpha * YYT_factor) + posterior = StudentTPosterior(nu, woodbury_chol=LW, woodbury_vector=alpha, K=K) + + # Log marginal + N = Y.shape[0] + D = Y.shape[1] + log_marginal = 0.5 * (-N * np.log((nu - 2) * np.pi) - W_logdet - (nu + N) * np.log(1 + beta / (nu - 2))) + log_marginal += gammaln((nu + N) / 2) - gammaln(nu / 2) + + # Gradients + dL_dK = 0.5 * ((nu + N) / (nu + beta - 2) * tdot(alpha) - D * Wi) + dL_dnu = -N / (nu - 2.) + digamma(0.5 * (nu + N)) - digamma(0.5 * nu) + dL_dnu -= np.log(1 + beta / (nu - 2.)) + dL_dnu += ((nu + N) * beta) / ((nu - 2) * (beta + nu - 2)) + dL_dnu *= 0.5 + gradients = {'dL_dK': dL_dK, 'dL_dnu': dL_dnu, 'dL_dm': alpha} + + return posterior, log_marginal, gradients diff --git a/GPy/inference/latent_function_inference/posterior.py b/GPy/inference/latent_function_inference/posterior.py index 40ea5c738..964ead7af 100644 --- a/GPy/inference/latent_function_inference/posterior.py +++ b/GPy/inference/latent_function_inference/posterior.py @@ -5,6 +5,7 @@ from ...util.linalg import pdinv, dpotrs, dpotri, symmetrify, jitchol, dtrtrs, tdot from GPy.core.parameterization.variational import VariationalPosterior + class Posterior(object): """ An object to represent a Gaussian posterior over latent function values, p(f|D). @@ -16,7 +17,9 @@ class Posterior(object): the function at any new point x_* by integrating over this posterior. """ - def __init__(self, woodbury_chol=None, woodbury_vector=None, K=None, mean=None, cov=None, K_chol=None, woodbury_inv=None, prior_mean=0): + + def __init__(self, woodbury_chol=None, woodbury_vector=None, K=None, mean=None, cov=None, K_chol=None, + woodbury_inv=None, prior_mean=0): """ woodbury_chol : a lower triangular matrix L that satisfies posterior_covariance = K - K L^{-T} L^{-1} K woodbury_vector : a matrix (or vector, as Nx1 matrix) M which satisfies posterior_mean = K M @@ -44,33 +47,33 @@ def __init__(self, woodbury_chol=None, woodbury_vector=None, K=None, mean=None, compute all other quantites on demand. """ - #obligatory + # obligatory self._K = K - if ((woodbury_chol is not None) and (woodbury_vector is not None))\ - or ((woodbury_inv is not None) and (woodbury_vector is not None))\ - or ((woodbury_inv is not None) and (mean is not None))\ + if ((woodbury_chol is not None) and (woodbury_vector is not None)) \ + or ((woodbury_inv is not None) and (woodbury_vector is not None)) \ + or ((woodbury_inv is not None) and (mean is not None)) \ or ((mean is not None) and (cov is not None)): - pass # we have sufficient to compute the posterior + pass # we have sufficient to compute the posterior else: raise ValueError("insufficient information to compute the posterior") self._K_chol = K_chol self._K = K - #option 1: + # option 1: self._woodbury_chol = woodbury_chol self._woodbury_vector = woodbury_vector - #option 2. + # option 2. self._woodbury_inv = woodbury_inv - #and woodbury vector + # and woodbury vector - #option 2: + # option 2: self._mean = mean self._covariance = cov self._prior_mean = prior_mean - #compute this lazily + # compute this lazily self._precision = None @property @@ -96,9 +99,11 @@ def covariance(self): $$ """ if self._covariance is None: - #LiK, _ = dtrtrs(self.woodbury_chol, self._K, lower=1) - self._covariance = (np.atleast_3d(self._K) - np.tensordot(np.dot(np.atleast_3d(self.woodbury_inv).T, self._K), self._K, [1,0]).T).squeeze() - #self._covariance = self._K - self._K.dot(self.woodbury_inv).dot(self._K) + # LiK, _ = dtrtrs(self.woodbury_chol, self._K, lower=1) + self._covariance = ( + np.atleast_3d(self._K) - np.tensordot(np.dot(np.atleast_3d(self.woodbury_inv).T, self._K), self._K, + [1, 0]).T).squeeze() + # self._covariance = self._K - self._K.dot(self.woodbury_inv).dot(self._K) return self._covariance @property @@ -108,9 +113,9 @@ def precision(self): """ if self._precision is None: cov = np.atleast_3d(self.covariance) - self._precision = np.zeros(cov.shape) # if one covariance per dimension + self._precision = np.zeros(cov.shape) # if one covariance per dimension for p in range(cov.shape[-1]): - self._precision[:,:,p] = pdinv(cov[:,:,p])[0] + self._precision[:, :, p] = pdinv(cov[:, :, p])[0] return self._precision @property @@ -123,18 +128,18 @@ def woodbury_chol(self): $$ """ if self._woodbury_chol is None: - #compute woodbury chol from + # compute woodbury chol from if self._woodbury_inv is not None: winv = np.atleast_3d(self._woodbury_inv) self._woodbury_chol = np.zeros(winv.shape) for p in range(winv.shape[-1]): - self._woodbury_chol[:,:,p] = pdinv(winv[:,:,p])[2] - #Li = jitchol(self._woodbury_inv) - #self._woodbury_chol, _ = dtrtri(Li) - #W, _, _, _, = pdinv(self._woodbury_inv) - #symmetrify(W) - #self._woodbury_chol = jitchol(W) - #try computing woodbury chol from cov + self._woodbury_chol[:, :, p] = pdinv(winv[:, :, p])[2] + # Li = jitchol(self._woodbury_inv) + # self._woodbury_chol, _ = dtrtri(Li) + # W, _, _, _, = pdinv(self._woodbury_inv) + # symmetrify(W) + # self._woodbury_chol = jitchol(W) + # try computing woodbury chol from cov elif self._covariance is not None: raise NotImplementedError("TODO: check code here") B = self._K - self._covariance @@ -157,14 +162,14 @@ def woodbury_inv(self): if self._woodbury_inv is None: if self._woodbury_chol is not None: self._woodbury_inv, _ = dpotri(self._woodbury_chol, lower=1) - #self._woodbury_inv, _ = dpotrs(self.woodbury_chol, np.eye(self.woodbury_chol.shape[0]), lower=1) + # self._woodbury_inv, _ = dpotrs(self.woodbury_chol, np.eye(self.woodbury_chol.shape[0]), lower=1) symmetrify(self._woodbury_inv) elif self._covariance is not None: B = np.atleast_3d(self._K) - np.atleast_3d(self._covariance) self._woodbury_inv = np.empty_like(B) for i in range(B.shape[-1]): - tmp, _ = dpotrs(self.K_chol, B[:,:,i]) - self._woodbury_inv[:,:,i], _ = dpotrs(self.K_chol, tmp.T) + tmp, _ = dpotrs(self.K_chol, B[:, :, i]) + self._woodbury_inv[:, :, i], _ = dpotrs(self.K_chol, tmp.T) return self._woodbury_inv @property @@ -196,14 +201,14 @@ def _raw_predict(self, kern, Xnew, pred_var, full_cov=False): if not isinstance(Xnew, VariationalPosterior): Kx = kern.K(pred_var, Xnew) mu = np.dot(Kx.T, woodbury_vector) - if len(mu.shape)==1: - mu = mu.reshape(-1,1) + if len(mu.shape) == 1: + mu = mu.reshape(-1, 1) if full_cov: Kxx = kern.K(Xnew) if woodbury_inv.ndim == 2: var = Kxx - np.dot(Kx.T, np.dot(woodbury_inv, Kx)) - elif woodbury_inv.ndim == 3: # Missing data - var = np.empty((Kxx.shape[0],Kxx.shape[1],woodbury_inv.shape[2])) + elif woodbury_inv.ndim == 3: # Missing data + var = np.empty((Kxx.shape[0], Kxx.shape[1], woodbury_inv.shape[2])) from ...util.linalg import mdot for i in range(var.shape[2]): var[:, :, i] = (Kxx - mdot(Kx.T, woodbury_inv[:, :, i], Kx)) @@ -211,9 +216,9 @@ def _raw_predict(self, kern, Xnew, pred_var, full_cov=False): else: Kxx = kern.Kdiag(Xnew) if woodbury_inv.ndim == 2: - var = (Kxx - np.sum(np.dot(woodbury_inv.T, Kx) * Kx, 0))[:,None] - elif woodbury_inv.ndim == 3: # Missing data - var = np.empty((Kxx.shape[0],woodbury_inv.shape[2])) + var = (Kxx - np.sum(np.dot(woodbury_inv.T, Kx) * Kx, 0))[:, None] + elif woodbury_inv.ndim == 3: # Missing data + var = np.empty((Kxx.shape[0], woodbury_inv.shape[2])) for i in range(var.shape[1]): var[:, i] = (Kxx - (np.sum(np.dot(woodbury_inv[:, :, i].T, Kx) * Kx, 0))) var = var @@ -222,86 +227,100 @@ def _raw_predict(self, kern, Xnew, pred_var, full_cov=False): psi1_star = kern.psi1(pred_var, Xnew) psi2_star = kern.psi2n(pred_var, Xnew) la = woodbury_vector - mu = np.dot(psi1_star, la) # TODO: dimensions? - N,M,D = psi0_star.shape[0],psi1_star.shape[1], la.shape[1] + mu = np.dot(psi1_star, la) # TODO: dimensions? + N, M, D = psi0_star.shape[0], psi1_star.shape[1], la.shape[1] if full_cov: - raise NotImplementedError("Full covariance for Sparse GP predicted with uncertain inputs not implemented yet.") + raise NotImplementedError( + "Full covariance for Sparse GP predicted with uncertain inputs not implemented yet.") var = np.zeros((Xnew.shape[0], la.shape[1], la.shape[1])) di = np.diag_indices(la.shape[1]) else: - tmp = psi2_star - psi1_star[:,:,None]*psi1_star[:,None,:] - var = (tmp.reshape(-1,M).dot(la).reshape(N,M,D)*la[None,:,:]).sum(1) + psi0_star[:,None] - if woodbury_inv.ndim==2: - var += -psi2_star.reshape(N,-1).dot(woodbury_inv.flat)[:,None] + tmp = psi2_star - psi1_star[:, :, None] * psi1_star[:, None, :] + var = (tmp.reshape(-1, M).dot(la).reshape(N, M, D) * la[None, :, :]).sum(1) + psi0_star[:, None] + if woodbury_inv.ndim == 2: + var += -psi2_star.reshape(N, -1).dot(woodbury_inv.flat)[:, None] else: - var += -psi2_star.reshape(N,-1).dot(woodbury_inv.reshape(-1,D)) - var = np.clip(var,1e-15,np.inf) + var += -psi2_star.reshape(N, -1).dot(woodbury_inv.reshape(-1, D)) + var = np.clip(var, 1e-15, np.inf) return mu, var class PosteriorExact(Posterior): - def _raw_predict(self, kern, Xnew, pred_var, full_cov=False): Kx = kern.K(pred_var, Xnew) mu = np.dot(Kx.T, self.woodbury_vector) - if len(mu.shape)==1: - mu = mu.reshape(-1,1) + if len(mu.shape) == 1: + mu = mu.reshape(-1, 1) if full_cov: Kxx = kern.K(Xnew) if self._woodbury_chol.ndim == 2: tmp = dtrtrs(self._woodbury_chol, Kx)[0] var = Kxx - tdot(tmp.T) - elif self._woodbury_chol.ndim == 3: # Missing data - var = np.empty((Kxx.shape[0],Kxx.shape[1],self._woodbury_chol.shape[2])) + elif self._woodbury_chol.ndim == 3: # Missing data + var = np.empty((Kxx.shape[0], Kxx.shape[1], self._woodbury_chol.shape[2])) for i in range(var.shape[2]): - tmp = dtrtrs(self._woodbury_chol[:,:,i], Kx)[0] + tmp = dtrtrs(self._woodbury_chol[:, :, i], Kx)[0] var[:, :, i] = (Kxx - tdot(tmp.T)) var = var else: Kxx = kern.Kdiag(Xnew) if self._woodbury_chol.ndim == 2: tmp = dtrtrs(self._woodbury_chol, Kx)[0] - var = (Kxx - np.square(tmp).sum(0))[:,None] - elif self._woodbury_chol.ndim == 3: # Missing data - var = np.empty((Kxx.shape[0],self._woodbury_chol.shape[2])) + var = (Kxx - np.square(tmp).sum(0))[:, None] + elif self._woodbury_chol.ndim == 3: # Missing data + var = np.empty((Kxx.shape[0], self._woodbury_chol.shape[2])) for i in range(var.shape[1]): - tmp = dtrtrs(self._woodbury_chol[:,:,i], Kx)[0] + tmp = dtrtrs(self._woodbury_chol[:, :, i], Kx)[0] var[:, i] = (Kxx - np.square(tmp).sum(0)) var = var return mu, var -class PosteriorEP(Posterior): +class PosteriorEP(Posterior): def _raw_predict(self, kern, Xnew, pred_var, full_cov=False): Kx = kern.K(pred_var, Xnew) mu = np.dot(Kx.T, self.woodbury_vector) - if len(mu.shape)==1: - mu = mu.reshape(-1,1) + if len(mu.shape) == 1: + mu = mu.reshape(-1, 1) if full_cov: Kxx = kern.K(Xnew) if self._woodbury_inv.ndim == 2: - tmp = np.dot(Kx.T,np.dot(self._woodbury_inv, Kx)) + tmp = np.dot(Kx.T, np.dot(self._woodbury_inv, Kx)) var = Kxx - tmp - elif self._woodbury_inv.ndim == 3: # Missing data - var = np.empty((Kxx.shape[0],Kxx.shape[1],self._woodbury_inv.shape[2])) + elif self._woodbury_inv.ndim == 3: # Missing data + var = np.empty((Kxx.shape[0], Kxx.shape[1], self._woodbury_inv.shape[2])) for i in range(var.shape[2]): - tmp = np.dot(Kx.T,np.dot(self._woodbury_inv[:,:,i], Kx)) + tmp = np.dot(Kx.T, np.dot(self._woodbury_inv[:, :, i], Kx)) var[:, :, i] = (Kxx - tmp) var = var else: Kxx = kern.Kdiag(Xnew) if self._woodbury_inv.ndim == 2: tmp = (np.dot(self._woodbury_inv, Kx) * Kx).sum(0) - var = (Kxx - tmp)[:,None] - elif self._woodbury_inv.ndim == 3: # Missing data - var = np.empty((Kxx.shape[0],self._woodbury_inv.shape[2])) + var = (Kxx - tmp)[:, None] + elif self._woodbury_inv.ndim == 3: # Missing data + var = np.empty((Kxx.shape[0], self._woodbury_inv.shape[2])) for i in range(var.shape[1]): - tmp = (Kx * np.dot(self._woodbury_inv[:,:,i], Kx)).sum(0) + tmp = (Kx * np.dot(self._woodbury_inv[:, :, i], Kx)).sum(0) var[:, i] = (Kxx - tmp) var = var return mu, var + + +class StudentTPosterior(PosteriorExact): + def __init__(self, deg_free, **kwargs): + super(StudentTPosterior, self).__init__(**kwargs) + self.nu = deg_free + + def _raw_predict(self, kern, Xnew, pred_var, full_cov=False): + print(self.nu) + mu, var = super(StudentTPosterior, self)._raw_predict(kern, Xnew, pred_var, full_cov) + beta = np.sum(self.woodbury_vector * self.mean) + N = self.woodbury_vector.shape[0] + tp_var_scale = (self.nu + beta - 2) / (self.nu + N - 2) + return mu, tp_var_scale * var diff --git a/GPy/models/__init__.py b/GPy/models/__init__.py index ce7ba50ba..f0c00cf92 100644 --- a/GPy/models/__init__.py +++ b/GPy/models/__init__.py @@ -26,3 +26,4 @@ from .ibp_lfm import IBPLFM from .gp_offset_regression import GPOffsetRegression from .gp_grid_regression import GPRegressionGrid +from .tp_regression import TPRegression \ No newline at end of file diff --git a/GPy/models/tp_regression.py b/GPy/models/tp_regression.py new file mode 100644 index 000000000..9fa26a5f3 --- /dev/null +++ b/GPy/models/tp_regression.py @@ -0,0 +1,298 @@ +# Copyright (c) 2017 the GPy Austhors (see AUTHORS.txt) +# Licensed under the BSD 3-clause license (see LICENSE.txt) + +from ..core import Model +from ..core.parameterization import Param +from ..core import Mapping +from ..kern import Kern, RBF +from ..inference.latent_function_inference import ExactStudentTInference +from ..util.normalizer import Standardize + +import numpy as np +from scipy import stats +from paramz import ObsAr +from paramz.transformations import Logistic, Logexp, LogexpClipped + +import warnings + + +class TPRegression(Model): + """ + Student-t Process model for regression, as presented in + + Shah, A., Wilson, A. and Ghahramani, Z., 2014, April. Student-t processes as alternatives to Gaussian processes. + In Artificial Intelligence and Statistics (pp. 877-885). + + :param X: input observations + :param Y: observed values + :param kernel: a GPy kernel, defaults to rbf + :param deg_free: initial value for the degrees of freedom hyperparameter + :param Norm normalizer: [False] + + Normalize Y with the norm given. + If normalizer is False, no normalization will be done + If it is None, we use GaussianNorm(alization) + + .. Note:: Multiple independent outputs are allowed using columns of Y + + """ + + def __init__(self, X, Y, kernel=None, deg_free=5., normalizer=None, mean_function=None, name='TP regression'): + super(TPRegression, self).__init__(name=name) + # X + assert X.ndim == 2 + self.set_X(X) + self.num_data, self.input_dim = self.X.shape + + # Y + assert Y.ndim == 2 + if normalizer is True: + self.normalizer = Standardize() + elif normalizer is False: + self.normalizer = None + else: + self.normalizer = normalizer + + self.set_Y(Y) + + if Y.shape[0] != self.num_data: + # There can be cases where we want inputs than outputs, for example if we have multiple latent + # function values + warnings.warn("There are more rows in your input data X, \ + than in your output data Y, be VERY sure this is what you want") + self.output_dim = self.Y.shape[1] + + # Kernel + kernel = kernel or RBF(self.X.shape[1]) + assert isinstance(kernel, Kern) + self.kern = kernel + self.link_parameter(self.kern) + + if self.kern._effective_input_dim != self.X.shape[1]: + warnings.warn( + "Your kernel has a different input dimension {} then the given X dimension {}. Be very sure this is " + "what you want and you have not forgotten to set the right input dimenion in your kernel".format( + self.kern._effective_input_dim, self.X.shape[1])) + + # Mean function + self.mean_function = mean_function + if mean_function is not None: + assert isinstance(self.mean_function, Mapping) + assert mean_function.input_dim == self.input_dim + assert mean_function.output_dim == self.output_dim + self.link_parameter(mean_function) + + # Degrees of freedom + # self.nu = Param('deg_free', float(deg_free), LogexpClipped(lower=2.)) + self.nu = Param('deg_free', float(deg_free), Logexp()) + # self.nu = Param('deg_free', float(deg_free), Logistic(2., np.inf)) + self.link_parameter(self.nu) + + # Inference + self.inference_method = ExactStudentTInference() + self.posterior = None + self._log_marginal_likelihood = None + + # Insert property for plotting (not used) + self.Y_metadata = None + + def _update_posterior_dof(self, dof, which): + if self.posterior is not None: + print(dof) + self.posterior.nu = dof + print(self.posterior.nu) + + @property + def _predictive_variable(self): + return self.X + + def set_XY(self, X, Y): + """ + Set the input / output data of the model + This is useful if we wish to change our existing data but maintain the same model + + :param X: input observations + :type X: np.ndarray + :param Y: output observations + :type Y: np.ndarray or ObsAr + """ + self.update_model(False) + self.set_Y(Y) + self.set_X(X) + self.update_model(True) + + def set_X(self, X): + """ + Set the input data of the model + + :param X: input observations + :type X: np.ndarray + """ + assert isinstance(X, np.ndarray) + state = self.update_model() + self.update_model(False) + self.X = ObsAr(X) + self.update_model(state) + + def set_Y(self, Y): + """ + Set the output data of the model + + :param Y: output observations + :type Y: np.ndarray or ObsArray + """ + assert isinstance(Y, (np.ndarray, ObsAr)) + state = self.update_model() + self.update_model(False) + if self.normalizer is not None: + self.normalizer.scale_by(Y) + self.Y_normalized = ObsAr(self.normalizer.normalize(Y)) + self.Y = Y + else: + self.Y = ObsAr(Y) if isinstance(Y, np.ndarray) else Y + self.Y_normalized = self.Y + self.update_model(state) + + def parameters_changed(self): + """ + Method that is called upon any changes to :class:`~GPy.core.parameterization.param.Param` variables within the model. + In particular in this class this method re-performs inference, recalculating the posterior, log marginal likelihood and gradients of the model + + .. warning:: + This method is not designed to be called manually, the framework is set up to automatically call this method upon changes to parameters, if you call + this method yourself, there may be unexpected consequences. + """ + self.posterior, self._log_marginal_likelihood, grad_dict = self.inference_method.inference(self.kern, + self.X, + self.Y_normalized, + self.nu + 2 + np.finfo( + float).eps, + self.mean_function) + self.kern.update_gradients_full(grad_dict['dL_dK'], self.X) + if self.mean_function is not None: + self.mean_function.update_gradients(grad_dict['dL_dm'], self.X) + self.nu.gradient = grad_dict['dL_dnu'] + + def log_likelihood(self): + """ + The log marginal likelihood of the model, :math:`p(\mathbf{y})`, this is the objective function of the model being optimised + """ + return self._log_marginal_likelihood or self.inference()[1] + + def _raw_predict(self, Xnew, full_cov=False, kern=None): + """ + For making predictions, does not account for normalization or likelihood + + full_cov is a boolean which defines whether the full covariance matrix + of the prediction is computed. If full_cov is False (default), only the + diagonal of the covariance is returned. + + .. math:: + p(f*|X*, X, Y) = \int^{\inf}_{\inf} p(f*|f,X*)p(f|X,Y) df + = MVN\left(\nu + N,f*| K_{x*x}(K_{xx})^{-1}Y, + \frac{\nu + \beta - 2}{\nu + N - 2}K_{x*x*} - K_{xx*}(K_{xx})^{-1}K_{xx*}\right) + \nu := \texttt{Degrees of freedom} + """ + mu, var = self.posterior._raw_predict(kern=self.kern if kern is None else kern, Xnew=Xnew, + pred_var=self._predictive_variable, full_cov=full_cov) + if self.mean_function is not None: + mu += self.mean_function.f(Xnew) + return mu, var + + def predict(self, Xnew, full_cov=False, kern=None, **kwargs): + """ + Predict the function(s) at the new point(s) Xnew. For Student-t processes, this method is equivalent to + predict_noiseless as no likelihood is included in the model. + """ + return self.predict_noiseless(Xnew, full_cov=full_cov, kern=kern) + + def predict_noiseless(self, Xnew, full_cov=False, kern=None): + """ + Predict the underlying function f at the new point(s) Xnew. + + :param Xnew: The points at which to make a prediction + :type Xnew: np.ndarray (Nnew x self.input_dim) + :param full_cov: whether to return the full covariance matrix, or just the diagonal + :type full_cov: bool + :param kern: The kernel to use for prediction (defaults to the model kern). + + :returns: (mean, var): + mean: posterior mean, a Numpy array, Nnew x self.input_dim + var: posterior variance, a Numpy array, Nnew x 1 if full_cov=False, Nnew x Nnew otherwise + + If full_cov and self.input_dim > 1, the return shape of var is Nnew x Nnew x self.input_dim. + If self.input_dim == 1, the return shape is Nnew x Nnew. + This is to allow for different normalizations of the output dimensions. + """ + # Predict the latent function values + mu, var = self._raw_predict(Xnew, full_cov=full_cov, kern=kern) + + # Un-apply normalization + if self.normalizer is not None: + mu, var = self.normalizer.inverse_mean(mu), self.normalizer.inverse_variance(var) + + return mu, var + + def predict_quantiles(self, X, quantiles=(2.5, 97.5), kern=None, **kwargs): + """ + Get the predictive quantiles around the prediction at X + + :param X: The points at which to make a prediction + :type X: np.ndarray (Xnew x self.input_dim) + :param quantiles: tuple of quantiles, default is (2.5, 97.5) which is the 95% interval + :type quantiles: tuple + :param kern: optional kernel to use for prediction + :type predict_kw: dict + :returns: list of quantiles for each X and predictive quantiles for interval combination + :rtype: [np.ndarray (Xnew x self.output_dim), np.ndarray (Xnew x self.output_dim)] + """ + mu, var = self._raw_predict(X, full_cov=False, kern=kern) + quantiles = [stats.t.ppf(q / 100., self.nu + self.num_data) * np.sqrt(var) + mu for q in quantiles] + + if self.normalizer is not None: + quantiles = [self.normalizer.inverse_mean(q) for q in quantiles] + + return quantiles + + def posterior_samples(self, X, size=10, full_cov=False, Y_metadata=None, likelihood=None, **predict_kwargs): + """ + Samples the posterior GP at the points X, equivalent to posterior_samples_f due to the absence of a likelihood. + """ + return self.posterior_samples_f(X, size, full_cov=full_cov, **predict_kwargs) + + def posterior_samples_f(self, X, size=10, full_cov=True, **predict_kwargs): + """ + Samples the posterior TP at the points X. + + :param X: The points at which to take the samples. + :type X: np.ndarray (Nnew x self.input_dim) + :param size: the number of a posteriori samples. + :type size: int. + :param full_cov: whether to return the full covariance matrix, or just the diagonal. + :type full_cov: bool. + :returns: fsim: set of simulations + :rtype: np.ndarray (D x N x samples) (if D==1 we flatten out the first dimension) + """ + mu, var = self._raw_predict(X, full_cov=full_cov, **predict_kwargs) + if self.normalizer is not None: + mu, var = self.normalizer.inverse_mean(mu), self.normalizer.inverse_variance(var) + + def sim_one_dim(m, v): + nu = self.nu + self.num_data + v = np.diag(v.flatten()) if not full_cov else v + Z = np.random.multivariate_normal(np.zeros(X.shape[0]), v, size).T + g = np.tile(np.random.gamma(nu / 2., 2. / nu, size), (X.shape[0], 1)) + return m + Z / np.sqrt(g) + + if self.output_dim == 1: + return sim_one_dim(mu, var) + else: + fsim = np.empty((self.output_dim, self.num_data, size)) + for d in range(self.output_dim): + if full_cov and var.ndim == 3: + fsim[d] = sim_one_dim(mu[:, d], var[:, :, d]) + elif (not full_cov) and var.ndim == 2: + fsim[d] = sim_one_dim(mu[:, d], var[:, d]) + else: + fsim[d] = sim_one_dim(mu[:, d], var) + return fsim diff --git a/GPy/plotting/__init__.py b/GPy/plotting/__init__.py index ad62a00fb..8c680caf4 100644 --- a/GPy/plotting/__init__.py +++ b/GPy/plotting/__init__.py @@ -92,6 +92,19 @@ def inject_plotting(): SSGPLVM.plot_inducing = gpy_plot.latent_plots.plot_latent_inducing SSGPLVM.plot_steepest_gradient_map = gpy_plot.latent_plots.plot_steepest_gradient_map + from ..models import TPRegression + TPRegression.plot_data = gpy_plot.data_plots.plot_data + TPRegression.plot = gpy_plot.gp_plots.plot + TPRegression.plot_data_error = gpy_plot.data_plots.plot_data_error + TPRegression.plot_errorbars_trainset = gpy_plot.data_plots.plot_errorbars_trainset + TPRegression.plot_mean = gpy_plot.gp_plots.plot_mean + TPRegression.plot_confidence = gpy_plot.gp_plots.plot_confidence + TPRegression.plot_density = gpy_plot.gp_plots.plot_density + TPRegression.plot_samples = gpy_plot.gp_plots.plot_samples + TPRegression.plot_f = gpy_plot.gp_plots.plot_f + TPRegression.plot_latent = gpy_plot.gp_plots.plot_f + TPRegression.plot_noiseless = gpy_plot.gp_plots.plot_f + from ..kern import Kern Kern.plot_covariance = gpy_plot.kernel_plots.plot_covariance def deprecate_plot(self, *args, **kwargs): diff --git a/GPy/testing/gp_tests.py b/GPy/testing/gp_tests.py index 97e3718d5..54f24feda 100644 --- a/GPy/testing/gp_tests.py +++ b/GPy/testing/gp_tests.py @@ -92,6 +92,7 @@ def update_gradients(self, dL_dF, X): Y = p.f(X) + np.random.multivariate_normal(np.zeros(X.shape[0]), k.K(X)+np.eye(X.shape[0])*1e-8)[:,None] + np.random.normal(0, .1, (X.shape[0], 1)) m = GPy.models.GPRegression(X, Y, mean_function=p) m.randomize() + print(m) assert(m.checkgrad()) _ = m.predict(m.X) diff --git a/GPy/testing/model_tests.py b/GPy/testing/model_tests.py index c6dc50f10..2250567c0 100644 --- a/GPy/testing/model_tests.py +++ b/GPy/testing/model_tests.py @@ -716,6 +716,45 @@ def test_SparseGPRegression_rbf_white_kern_1D_uncertain_inputs(self): rbflin = GPy.kern.RBF(1) + GPy.kern.White(1) self.check_model(rbflin, model_type='SparseGPRegression', dimension=1, uncertain_inputs=1) + def test_TPRegression_matern52_1D(self): + ''' Testing the TP regression with matern52 kernel on 1d data ''' + matern52 = GPy.kern.Matern52(1) + GPy.kern.White(1) + self.check_model(matern52, model_type='TPRegression', dimension=1) + + def test_TPRegression_rbf_2D(self): + ''' Testing the TP regression with rbf kernel on 2d data ''' + rbf = GPy.kern.RBF(2) + self.check_model(rbf, model_type='TPRegression', dimension=2) + + def test_TPRegression_rbf_ARD_2D(self): + ''' Testing the GP regression with rbf kernel on 2d data ''' + k = GPy.kern.RBF(2, ARD=True) + self.check_model(k, model_type='TPRegression', dimension=2) + + def test_TPRegression_matern52_2D(self): + ''' Testing the TP regression with matern52 kernel on 2d data ''' + matern52 = GPy.kern.Matern52(2) + self.check_model(matern52, model_type='TPRegression', dimension=2) + + def test_TPRegression_matern52_ARD_2D(self): + ''' Testing the TP regression with matern52 kernel on 2d data ''' + matern52 = GPy.kern.Matern52(2, ARD=True) + self.check_model(matern52, model_type='TPRegression', dimension=2) + + def test_TPRegression_matern32_1D(self): + ''' Testing the TP regression with matern32 kernel on 1d data ''' + matern32 = GPy.kern.Matern32(1) + self.check_model(matern32, model_type='TPRegression', dimension=1) + + def test_TPRegression_matern32_2D(self): + ''' Testing the TP regression with matern32 kernel on 2d data ''' + matern32 = GPy.kern.Matern32(2) + self.check_model(matern32, model_type='TPRegression', dimension=2) + + def test_TPRegression_matern32_ARD_2D(self): + ''' Testing the TP regression with matern32 kernel on 2d data ''' + matern32 = GPy.kern.Matern32(2, ARD=True) + self.check_model(matern32, model_type='TPRegression', dimension=2) def test_GPLVM_rbf_bias_white_kern_2D(self): """ Testing GPLVM with rbf + bias kernel """ diff --git a/GPy/testing/tp_tests.py b/GPy/testing/tp_tests.py new file mode 100644 index 000000000..620ae7911 --- /dev/null +++ b/GPy/testing/tp_tests.py @@ -0,0 +1,145 @@ +''' +Created on 14 Jul 2017, based on gp_tests + +@author: javdrher +''' +import unittest +import numpy as np, GPy + + +class Test(unittest.TestCase): + def setUp(self): + np.random.seed(12345) + self.N = 20 + self.N_new = 50 + self.D = 1 + self.X = np.random.uniform(-3., 3., (self.N, 1)) + self.Y = np.sin(self.X) + np.random.randn(self.N, self.D) * 0.05 + self.X_new = np.random.uniform(-3., 3., (self.N_new, 1)) + + def test_setxy_gp(self): + k = GPy.kern.RBF(1) + GPy.kern.White(1) + m = GPy.models.TPRegression(self.X, self.Y, kernel=k) + mu, var = m.predict(m.X) + X = m.X.copy() + m.set_XY(m.X[:10], m.Y[:10]) + assert (m.checkgrad(tolerance=1e-2)) + m.set_XY(X, self.Y) + mu2, var2 = m.predict(m.X) + np.testing.assert_allclose(mu, mu2) + np.testing.assert_allclose(var, var2) + + def test_mean_function(self): + from GPy.core.parameterization.param import Param + from GPy.core.mapping import Mapping + + class Parabola(Mapping): + def __init__(self, variance, degree=2, name='parabola'): + super(Parabola, self).__init__(1, 1, name) + self.variance = Param('variance', np.ones(degree + 1) * variance) + self.degree = degree + self.link_parameter(self.variance) + + def f(self, X): + p = self.variance[0] * np.ones(X.shape) + for i in range(1, self.degree + 1): + p += self.variance[i] * X ** (i) + return p + + def gradients_X(self, dL_dF, X): + grad = np.zeros(X.shape) + for i in range(1, self.degree + 1): + grad += (i) * self.variance[i] * X ** (i - 1) + return grad + + def update_gradients(self, dL_dF, X): + for i in range(self.degree + 1): + self.variance.gradient[i] = (dL_dF * X ** (i)).sum(0) + + X = np.linspace(-2, 2, 100)[:, None] + k = GPy.kern.RBF(1) + GPy.kern.White(1) + k.randomize() + p = Parabola(.3) + p.randomize() + Y = p.f(X) + np.random.multivariate_normal(np.zeros(X.shape[0]), k.K(X) + np.eye(X.shape[0]) * 1e-8)[:, + None] + np.random.normal(0, .1, (X.shape[0], 1)) + m = GPy.models.TPRegression(X, Y, kernel=k, mean_function=p) + assert (m.checkgrad(tolerance=2e-1)) + _ = m.predict(m.X) + + def test_normalizer(self): + k = GPy.kern.RBF(1) + GPy.kern.White(1) + Y = self.Y + mu, std = Y.mean(0), Y.std(0) + m = GPy.models.TPRegression(self.X, Y, kernel=k, normalizer=True) + m.optimize() + assert (m.checkgrad()) + k = GPy.kern.RBF(1) + GPy.kern.White(1) + m2 = GPy.models.TPRegression(self.X, (Y - mu) / std, kernel=k, normalizer=False) + m2[:] = m[:] + + mu1, var1 = m.predict(m.X, full_cov=True) + mu2, var2 = m2.predict(m2.X, full_cov=True) + np.testing.assert_allclose(mu1, (mu2 * std) + mu) + np.testing.assert_allclose(var1, var2 * std ** 2) + + mu1, var1 = m.predict(m.X, full_cov=False) + mu2, var2 = m2.predict(m2.X, full_cov=False) + + np.testing.assert_allclose(mu1, (mu2 * std) + mu) + np.testing.assert_allclose(var1, var2 * std ** 2) + + q50n = m.predict_quantiles(m.X, (50,)) + q50 = m2.predict_quantiles(m2.X, (50,)) + + np.testing.assert_allclose(q50n[0], (q50[0] * std) + mu) + + # Test variance component: + qs = np.array([2.5, 97.5]) + # The quantiles get computed before unormalization + # And transformed using the mean transformation: + c = np.random.choice(self.X.shape[0]) + q95 = m2.predict_quantiles(self.X[[c]], qs) + mu, var = m2.predict(self.X[[c]]) + from scipy.stats import t + np.testing.assert_allclose((mu + (t.ppf(qs / 100., m2.nu + m2.num_data) * np.sqrt(var))).flatten(), + np.array(q95).flatten()) + + def test_predict_equivalence(self): + k = GPy.kern.RBF(1) + GPy.kern.White(1) + m = GPy.models.TPRegression(self.X, self.Y, kernel=k) + m.optimize() + mu1, var1 = m.predict(m.X) + mu2, var2 = m.predict_noiseless(m.X) + mu3, var3 = m._raw_predict(m.X) + np.testing.assert_allclose(mu1, mu2) + np.testing.assert_allclose(var1, var2) + np.testing.assert_allclose(mu1, mu3) + np.testing.assert_allclose(var1, var3) + + m2 = GPy.models.TPRegression(self.X, self.Y, kernel=k, normalizer=True) + m2.optimize() + mu1, var1 = m2.predict(m.X) + mu2, var2 = m2.predict_noiseless(m.X) + mu3, var3 = m2._raw_predict(m.X) + np.testing.assert_allclose(mu1, mu2) + np.testing.assert_allclose(var1, var2) + self.assertFalse(np.allclose(mu1, mu3)) + self.assertFalse(np.allclose(var1, var3)) + + def test_gp_equivalence(self): + k = GPy.kern.RBF(1) + m = GPy.models.GPRegression(self.X, self.Y, kernel=k) + m.optimize() + + k1 = GPy.kern.RBF(1, variance=k.variance, lengthscale=k.lengthscale) + k2 = GPy.kern.White(1, variance=m.likelihood.variance) + m2 = GPy.models.TPRegression(self.X, self.Y, kernel=k1 + k2, deg_free=1e6) + mu1, var1 = m.predict(self.X) + mu2, var2 = m2.predict(self.X) + np.testing.assert_allclose(mu1, mu2) + np.testing.assert_allclose(var1, var2) + + +if __name__ == "__main__": + unittest.main() From 5bb17f21d28117ccff300c9e738e73c985b96c4c Mon Sep 17 00:00:00 2001 From: Joachim van der Herten Date: Fri, 14 Jul 2017 23:26:02 +0200 Subject: [PATCH 06/48] Removal of print statements --- GPy/models/tp_regression.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/GPy/models/tp_regression.py b/GPy/models/tp_regression.py index 9fa26a5f3..fef08bb49 100644 --- a/GPy/models/tp_regression.py +++ b/GPy/models/tp_regression.py @@ -98,9 +98,7 @@ def __init__(self, X, Y, kernel=None, deg_free=5., normalizer=None, mean_functio def _update_posterior_dof(self, dof, which): if self.posterior is not None: - print(dof) self.posterior.nu = dof - print(self.posterior.nu) @property def _predictive_variable(self): From 394d3ea23659de49a8ff492775c9ae99ae6fcec6 Mon Sep 17 00:00:00 2001 From: Joachim van der Herten Date: Fri, 14 Jul 2017 23:48:24 +0200 Subject: [PATCH 07/48] Added some shifts to the degrees of freedom parameter. --- GPy/models/tp_regression.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/GPy/models/tp_regression.py b/GPy/models/tp_regression.py index fef08bb49..3ed102a6c 100644 --- a/GPy/models/tp_regression.py +++ b/GPy/models/tp_regression.py @@ -83,9 +83,7 @@ def __init__(self, X, Y, kernel=None, deg_free=5., normalizer=None, mean_functio self.link_parameter(mean_function) # Degrees of freedom - # self.nu = Param('deg_free', float(deg_free), LogexpClipped(lower=2.)) self.nu = Param('deg_free', float(deg_free), Logexp()) - # self.nu = Param('deg_free', float(deg_free), Logistic(2., np.inf)) self.link_parameter(self.nu) # Inference @@ -245,7 +243,7 @@ def predict_quantiles(self, X, quantiles=(2.5, 97.5), kern=None, **kwargs): :rtype: [np.ndarray (Xnew x self.output_dim), np.ndarray (Xnew x self.output_dim)] """ mu, var = self._raw_predict(X, full_cov=False, kern=kern) - quantiles = [stats.t.ppf(q / 100., self.nu + self.num_data) * np.sqrt(var) + mu for q in quantiles] + quantiles = [stats.t.ppf(q / 100., self.nu + 2 + self.num_data) * np.sqrt(var) + mu for q in quantiles] if self.normalizer is not None: quantiles = [self.normalizer.inverse_mean(q) for q in quantiles] @@ -276,7 +274,7 @@ def posterior_samples_f(self, X, size=10, full_cov=True, **predict_kwargs): mu, var = self.normalizer.inverse_mean(mu), self.normalizer.inverse_variance(var) def sim_one_dim(m, v): - nu = self.nu + self.num_data + nu = self.nu + 2 + self.num_data v = np.diag(v.flatten()) if not full_cov else v Z = np.random.multivariate_normal(np.zeros(X.shape[0]), v, size).T g = np.tile(np.random.gamma(nu / 2., 2. / nu, size), (X.shape[0], 1)) From 4af1f017ec9ea7cb9fc70a914810e0670c7e7070 Mon Sep 17 00:00:00 2001 From: Joachim van der Herten Date: Sat, 15 Jul 2017 00:35:39 +0200 Subject: [PATCH 08/48] Solved incorrect parameter assignments (causing test faillure) --- GPy/inference/latent_function_inference/posterior.py | 1 - GPy/testing/gp_tests.py | 1 - GPy/testing/tp_tests.py | 6 +++--- 3 files changed, 3 insertions(+), 5 deletions(-) diff --git a/GPy/inference/latent_function_inference/posterior.py b/GPy/inference/latent_function_inference/posterior.py index 964ead7af..96042c6f3 100644 --- a/GPy/inference/latent_function_inference/posterior.py +++ b/GPy/inference/latent_function_inference/posterior.py @@ -318,7 +318,6 @@ def __init__(self, deg_free, **kwargs): self.nu = deg_free def _raw_predict(self, kern, Xnew, pred_var, full_cov=False): - print(self.nu) mu, var = super(StudentTPosterior, self)._raw_predict(kern, Xnew, pred_var, full_cov) beta = np.sum(self.woodbury_vector * self.mean) N = self.woodbury_vector.shape[0] diff --git a/GPy/testing/gp_tests.py b/GPy/testing/gp_tests.py index 54f24feda..97e3718d5 100644 --- a/GPy/testing/gp_tests.py +++ b/GPy/testing/gp_tests.py @@ -92,7 +92,6 @@ def update_gradients(self, dL_dF, X): Y = p.f(X) + np.random.multivariate_normal(np.zeros(X.shape[0]), k.K(X)+np.eye(X.shape[0])*1e-8)[:,None] + np.random.normal(0, .1, (X.shape[0], 1)) m = GPy.models.GPRegression(X, Y, mean_function=p) m.randomize() - print(m) assert(m.checkgrad()) _ = m.predict(m.X) diff --git a/GPy/testing/tp_tests.py b/GPy/testing/tp_tests.py index 620ae7911..643d67e0b 100644 --- a/GPy/testing/tp_tests.py +++ b/GPy/testing/tp_tests.py @@ -131,11 +131,11 @@ def test_gp_equivalence(self): k = GPy.kern.RBF(1) m = GPy.models.GPRegression(self.X, self.Y, kernel=k) m.optimize() - - k1 = GPy.kern.RBF(1, variance=k.variance, lengthscale=k.lengthscale) + mu1, var1 = m.predict(self.X) + k1 = GPy.kern.RBF(1) + k1[:] = k[:] k2 = GPy.kern.White(1, variance=m.likelihood.variance) m2 = GPy.models.TPRegression(self.X, self.Y, kernel=k1 + k2, deg_free=1e6) - mu1, var1 = m.predict(self.X) mu2, var2 = m2.predict(self.X) np.testing.assert_allclose(mu1, mu2) np.testing.assert_allclose(var1, var2) From a7af12e6ea9bbe3c240bb512c96494573c785904 Mon Sep 17 00:00:00 2001 From: Jayanth Koushik Date: Mon, 23 Oct 2017 15:58:17 -0400 Subject: [PATCH 09/48] fix: dev: cython import errors This commit fixes issues observed in Windows where some cython modules are successfully imported, and some are not. This causes the global config cython.working to be inconsistent, which causes import errors when unavailable cython modules are tried to be imported (example https://github.com/SheffieldML/GPy/issues/266). This commit uses a separate flag for each module to fix the issue. --- GPy/kern/src/coregionalize.py | 11 +++++++---- GPy/kern/src/stationary.py | 7 ++++--- GPy/testing/cython_tests.py | 18 +++++++++++------- GPy/testing/kernel_tests.py | 8 ++++---- GPy/util/choleskies.py | 9 ++++++--- 5 files changed, 32 insertions(+), 21 deletions(-) diff --git a/GPy/kern/src/coregionalize.py b/GPy/kern/src/coregionalize.py index 197d7ece0..704d03703 100644 --- a/GPy/kern/src/coregionalize.py +++ b/GPy/kern/src/coregionalize.py @@ -6,11 +6,14 @@ from ...core.parameterization import Param from paramz.transformations import Logexp from ...util.config import config # for assesing whether to use cython + try: from . import coregionalize_cython - config.set('cython', 'working', 'True') + cython_coregionalize_working = True except ImportError: - config.set('cython', 'working', 'False') + print('warning in coregionalize: failed to import cython module: falling back to numpy') + cython_coregionalize_working = False + class Coregionalize(Kern): """ @@ -61,7 +64,7 @@ def parameters_changed(self): self.B = np.dot(self.W, self.W.T) + np.diag(self.kappa) def K(self, X, X2=None): - if config.getboolean('cython', 'working'): + if cython_coregionalize_working and config.getboolean('cython', 'working'): return self._K_cython(X, X2) else: return self._K_numpy(X, X2) @@ -92,7 +95,7 @@ def update_gradients_full(self, dL_dK, X, X2=None): index2 = np.asarray(X2, dtype=np.int) #attempt to use cython for a nasty double indexing loop: fall back to numpy - if config.getboolean('cython', 'working'): + if cython_coregionalize_working and config.getboolean('cython', 'working'): dL_dK_small = self._gradient_reduce_cython(dL_dK, index, index2) else: dL_dK_small = self._gradient_reduce_numpy(dL_dK, index, index2) diff --git a/GPy/kern/src/stationary.py b/GPy/kern/src/stationary.py index 4e8ddb779..81681d604 100644 --- a/GPy/kern/src/stationary.py +++ b/GPy/kern/src/stationary.py @@ -14,9 +14,10 @@ try: from . import stationary_cython + cython_stationary_working = True except ImportError: print('warning in stationary: failed to import cython module: falling back to numpy') - config.set('cython', 'working', 'false') + cython_stationary_working = False class Stationary(Kern): @@ -196,7 +197,7 @@ def update_gradients_full(self, dL_dK, X, X2=None): tmp = dL_dr*self._inv_dist(X, X2) if X2 is None: X2 = X - if config.getboolean('cython', 'working'): + if cython_stationary_working and config.getboolean('cython', 'working'): self.lengthscale.gradient = self._lengthscale_grads_cython(tmp, X, X2) else: self.lengthscale.gradient = self._lengthscale_grads_pure(tmp, X, X2) @@ -239,7 +240,7 @@ def gradients_X(self, dL_dK, X, X2=None): """ Given the derivative of the objective wrt K (dL_dK), compute the derivative wrt X """ - if config.getboolean('cython', 'working'): + if cython_stationary_working and config.getboolean('cython', 'working'): return self._gradients_X_cython(dL_dK, X, X2) else: return self._gradients_X_pure(dL_dK, X, X2) diff --git a/GPy/testing/cython_tests.py b/GPy/testing/cython_tests.py index c4bca5cd3..c777aae05 100644 --- a/GPy/testing/cython_tests.py +++ b/GPy/testing/cython_tests.py @@ -2,21 +2,25 @@ import scipy as sp from GPy.util import choleskies import GPy -from ..util.config import config import unittest try: - from ..util import linalg_cython from ..util import choleskies_cython - config.set('cython', 'working', 'True') + choleskies_cython_working = True except ImportError: - config.set('cython', 'working', 'False') + choleskies_cython_working = False + +try: + from ..kern.src import stationary_cython + stationary_cython_working = True +except ImportError: + stationary_cython_working = False """ These tests make sure that the pure python and cython codes work the same """ -@unittest.skipIf(not config.getboolean('cython', 'working'),"Cython modules have not been built on this machine") +@unittest.skipIf(not choleskies_cython_working,"Cython cholesky module has not been built on this machine") class CythonTestChols(np.testing.TestCase): def setUp(self): self.flat = np.random.randn(45,5) @@ -30,7 +34,7 @@ def test_triang_to_flat(self): A2 = choleskies._triang_to_flat_cython(self.triang) np.testing.assert_allclose(A1, A2) -@unittest.skipIf(not config.getboolean('cython', 'working'),"Cython modules have not been built on this machine") +@unittest.skipIf(not stationary_cython_working,"Cython stationary module has not been built on this machine") class test_stationary(np.testing.TestCase): def setUp(self): self.k = GPy.kern.RBF(10) @@ -60,7 +64,7 @@ def test_rect_lengthscales(self): g2 = self.k._lengthscale_grads_cython(self.dKxz, self.X, self.Z) np.testing.assert_allclose(g1, g2) -@unittest.skipIf(not config.getboolean('cython', 'working'),"Cython modules have not been built on this machine") +@unittest.skipIf(not choleskies_cython_working,"Cython cholesky module has not been built on this machine") class test_choleskies_backprop(np.testing.TestCase): def setUp(self): a =np.random.randn(10,12) diff --git a/GPy/testing/kernel_tests.py b/GPy/testing/kernel_tests.py index 053fce357..e5bc5683e 100644 --- a/GPy/testing/kernel_tests.py +++ b/GPy/testing/kernel_tests.py @@ -14,10 +14,10 @@ verbose = 0 try: - from ..util import linalg_cython - config.set('cython', 'working', 'True') + from ..util import choleskies_cython + cython_choleskies_working = True except ImportError: - config.set('cython', 'working', 'False') + cython_choleskies_working = False class Kern_check_model(GPy.core.Model): @@ -618,7 +618,7 @@ def test_Coregionalize(self): kern = GPy.kern.Coregionalize(1, output_dim=3, active_dims=[-1]) self.assertTrue(check_kernel_gradient_functions(kern, X=self.X, X2=self.X2, verbose=verbose, fixed_X_dims=-1)) -@unittest.skipIf(not config.getboolean('cython', 'working'),"Cython modules have not been built on this machine") +@unittest.skipIf(not cython_choleskies_working,"Cython choleskies module has not been built on this machine") class Coregionalize_cython_test(unittest.TestCase): """ Make sure that the coregionalize kernel work with and without cython enabled diff --git a/GPy/util/choleskies.py b/GPy/util/choleskies.py index 2676b6e63..54a7ea74b 100644 --- a/GPy/util/choleskies.py +++ b/GPy/util/choleskies.py @@ -4,11 +4,14 @@ import numpy as np from . import linalg from .config import config + try: from . import choleskies_cython - config.set('cython', 'working', 'True') + cython_choleskies_working = True except ImportError: - config.set('cython', 'working', 'False') + print('warning in choleskies: failed to import cython module: falling back to numpy') + cython_choleskies_working = False + def safe_root(N): i = np.sqrt(N) @@ -100,7 +103,7 @@ def indexes_to_fix_for_low_rank(rank, size): return np.setdiff1d(np.arange((size**2+size)/2), keep) -if config.getboolean('cython', 'working'): +if cython_choleskies_working and config.getboolean('cython', 'working'): triang_to_flat = _triang_to_flat_cython flat_to_triang = _flat_to_triang_cython backprop_gradient = choleskies_cython.backprop_gradient_par_c From 6605b736d8231b495c10ce3210ac7d92d6cf4313 Mon Sep 17 00:00:00 2001 From: Jayanth Koushik Date: Mon, 23 Oct 2017 16:22:42 -0400 Subject: [PATCH 10/48] Use correct cython check in kernel_tests.py --- GPy/testing/kernel_tests.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/GPy/testing/kernel_tests.py b/GPy/testing/kernel_tests.py index e5bc5683e..5f418674e 100644 --- a/GPy/testing/kernel_tests.py +++ b/GPy/testing/kernel_tests.py @@ -14,10 +14,10 @@ verbose = 0 try: - from ..util import choleskies_cython - cython_choleskies_working = True + from ..kern.src import coregionalize_cython + cython_coregionalize_working = True except ImportError: - cython_choleskies_working = False + cython_coregionalize_working = False class Kern_check_model(GPy.core.Model): @@ -618,7 +618,7 @@ def test_Coregionalize(self): kern = GPy.kern.Coregionalize(1, output_dim=3, active_dims=[-1]) self.assertTrue(check_kernel_gradient_functions(kern, X=self.X, X2=self.X2, verbose=verbose, fixed_X_dims=-1)) -@unittest.skipIf(not cython_choleskies_working,"Cython choleskies module has not been built on this machine") +@unittest.skipIf(not cython_coregionalize_working,"Cython coregionalize module has not been built on this machine") class Coregionalize_cython_test(unittest.TestCase): """ Make sure that the coregionalize kernel work with and without cython enabled From 928559216cdb2d7e2261fab8e89bc929502069c9 Mon Sep 17 00:00:00 2001 From: Jayanth Koushik Date: Thu, 16 Nov 2017 20:29:49 -0500 Subject: [PATCH 11/48] Refactor checking for cython availability --- GPy/kern/src/coregionalize.py | 8 ++++---- GPy/kern/src/stationary.py | 8 ++++---- GPy/util/choleskies.py | 6 +++--- 3 files changed, 11 insertions(+), 11 deletions(-) diff --git a/GPy/kern/src/coregionalize.py b/GPy/kern/src/coregionalize.py index 704d03703..0c471cb34 100644 --- a/GPy/kern/src/coregionalize.py +++ b/GPy/kern/src/coregionalize.py @@ -9,10 +9,10 @@ try: from . import coregionalize_cython - cython_coregionalize_working = True + use_coregionalize_cython = config.getboolean('cython', 'working') except ImportError: print('warning in coregionalize: failed to import cython module: falling back to numpy') - cython_coregionalize_working = False + use_coregionalize_cython = False class Coregionalize(Kern): @@ -64,7 +64,7 @@ def parameters_changed(self): self.B = np.dot(self.W, self.W.T) + np.diag(self.kappa) def K(self, X, X2=None): - if cython_coregionalize_working and config.getboolean('cython', 'working'): + if use_coregionalize_cython: return self._K_cython(X, X2) else: return self._K_numpy(X, X2) @@ -95,7 +95,7 @@ def update_gradients_full(self, dL_dK, X, X2=None): index2 = np.asarray(X2, dtype=np.int) #attempt to use cython for a nasty double indexing loop: fall back to numpy - if cython_coregionalize_working and config.getboolean('cython', 'working'): + if use_coregionalize_cython: dL_dK_small = self._gradient_reduce_cython(dL_dK, index, index2) else: dL_dK_small = self._gradient_reduce_numpy(dL_dK, index, index2) diff --git a/GPy/kern/src/stationary.py b/GPy/kern/src/stationary.py index 81681d604..901720498 100644 --- a/GPy/kern/src/stationary.py +++ b/GPy/kern/src/stationary.py @@ -14,10 +14,10 @@ try: from . import stationary_cython - cython_stationary_working = True + use_stationary_cython = config.getboolean('cython', 'working') except ImportError: print('warning in stationary: failed to import cython module: falling back to numpy') - cython_stationary_working = False + use_stationary_cython = False class Stationary(Kern): @@ -197,7 +197,7 @@ def update_gradients_full(self, dL_dK, X, X2=None): tmp = dL_dr*self._inv_dist(X, X2) if X2 is None: X2 = X - if cython_stationary_working and config.getboolean('cython', 'working'): + if use_stationary_cython: self.lengthscale.gradient = self._lengthscale_grads_cython(tmp, X, X2) else: self.lengthscale.gradient = self._lengthscale_grads_pure(tmp, X, X2) @@ -240,7 +240,7 @@ def gradients_X(self, dL_dK, X, X2=None): """ Given the derivative of the objective wrt K (dL_dK), compute the derivative wrt X """ - if cython_stationary_working and config.getboolean('cython', 'working'): + if use_stationary_cython: return self._gradients_X_cython(dL_dK, X, X2) else: return self._gradients_X_pure(dL_dK, X, X2) diff --git a/GPy/util/choleskies.py b/GPy/util/choleskies.py index 54a7ea74b..acc4ad7a7 100644 --- a/GPy/util/choleskies.py +++ b/GPy/util/choleskies.py @@ -7,10 +7,10 @@ try: from . import choleskies_cython - cython_choleskies_working = True + use_choleskies_cython = config.getboolean('cython', 'working') except ImportError: print('warning in choleskies: failed to import cython module: falling back to numpy') - cython_choleskies_working = False + use_choleskies_cython = False def safe_root(N): @@ -103,7 +103,7 @@ def indexes_to_fix_for_low_rank(rank, size): return np.setdiff1d(np.arange((size**2+size)/2), keep) -if cython_choleskies_working and config.getboolean('cython', 'working'): +if use_choleskies_cython: triang_to_flat = _triang_to_flat_cython flat_to_triang = _flat_to_triang_cython backprop_gradient = choleskies_cython.backprop_gradient_par_c From cb1ab89d8a5eebca414284ef35d635ccafffe516 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Sun, 31 Dec 2017 22:54:43 +0100 Subject: [PATCH 12/48] Update gp.py Sample return seemed to have been based on number of training data, not number of posterior samples requested. --- GPy/core/gp.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 7bad76485..4481d3bcc 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -564,7 +564,7 @@ def sim_one_dim(m, v): if self.output_dim == 1: return sim_one_dim(m, v) else: - fsim = np.empty((self.output_dim, self.num_data, size)) + fsim = np.empty((self.output_dim, X.shape[1], size)) for d in range(self.output_dim): if full_cov and v.ndim == 3: fsim[d] = sim_one_dim(m[:, d], v[:, :, d]) From ff4f861fcb021054fb5acf3d99039b80e8cc1777 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Sun, 31 Dec 2017 23:22:23 +0100 Subject: [PATCH 13/48] Testing for dims should be checking whether 2nd dim is greater than 1 --- GPy/core/gp.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 4481d3bcc..5d99f0cf5 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -568,7 +568,7 @@ def sim_one_dim(m, v): for d in range(self.output_dim): if full_cov and v.ndim == 3: fsim[d] = sim_one_dim(m[:, d], v[:, :, d]) - elif (not full_cov) and v.ndim == 2: + elif (not full_cov) and v.shape[1]>1: fsim[d] = sim_one_dim(m[:, d], v[:, d]) else: fsim[d] = sim_one_dim(m[:, d], v) From 0d26609b15d589ca4da878fb38c561e568f7ba73 Mon Sep 17 00:00:00 2001 From: Neil Lawrence Date: Mon, 1 Jan 2018 01:18:08 +0100 Subject: [PATCH 14/48] Rewrite poster_samples_f to return NxDxsize --- GPy/core/gp.py | 37 ++++++++++++++----------------------- 1 file changed, 14 insertions(+), 23 deletions(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 5d99f0cf5..d546bf0e8 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -538,7 +538,7 @@ def predict_magnification(self, Xnew, kern=None, mean=True, covariance=True, dim mag[n] = np.sqrt(np.linalg.det(G[n, :, :])) return mag - def posterior_samples_f(self,X, size=10, full_cov=True, **predict_kwargs): + def posterior_samples_f(self,X, size=10, **predict_kwargs): """ Samples the posterior GP at the points X. @@ -546,35 +546,28 @@ def posterior_samples_f(self,X, size=10, full_cov=True, **predict_kwargs): :type X: np.ndarray (Nnew x self.input_dim) :param size: the number of a posteriori samples. :type size: int. - :param full_cov: whether to return the full covariance matrix, or just the diagonal. - :type full_cov: bool. - :returns: fsim: set of simulations - :rtype: np.ndarray (D x N x samples) (if D==1 we flatten out the first dimension) + :returns: set of simulations + :rtype: np.ndarray (Nnew x D x samples) """ - m, v = self._raw_predict(X, full_cov=full_cov, **predict_kwargs) + m, v = self._raw_predict(X, full_cov=True, **predict_kwargs) if self.normalizer is not None: m, v = self.normalizer.inverse_mean(m), self.normalizer.inverse_variance(v) def sim_one_dim(m, v): - if not full_cov: - return np.random.multivariate_normal(m.flatten(), np.diag(v.flatten()), size).T - else: - return np.random.multivariate_normal(m.flatten(), v, size).T + return np.random.multivariate_normal(m, v, size).T if self.output_dim == 1: - return sim_one_dim(m, v) + return sim_one_dim(m.flatten(), v)[:, np.newaxis, :] else: - fsim = np.empty((self.output_dim, X.shape[1], size)) + fsim = np.empty((X.shape[0], self.output_dim, size)) for d in range(self.output_dim): - if full_cov and v.ndim == 3: - fsim[d] = sim_one_dim(m[:, d], v[:, :, d]) - elif (not full_cov) and v.shape[1]>1: - fsim[d] = sim_one_dim(m[:, d], v[:, d]) + if v.ndim == 3: + fsim[:, d, :] = sim_one_dim(m[:, d], v[:, :, d]) else: - fsim[d] = sim_one_dim(m[:, d], v) + fsim[:, d, :] = sim_one_dim(m[:, d], v) return fsim - def posterior_samples(self, X, size=10, full_cov=False, Y_metadata=None, likelihood=None, **predict_kwargs): + def posterior_samples(self, X, size=10, Y_metadata=None, likelihood=None, **predict_kwargs): """ Samples the posterior GP at the points X. @@ -582,19 +575,17 @@ def posterior_samples(self, X, size=10, full_cov=False, Y_metadata=None, likelih :type X: np.ndarray (Nnew x self.input_dim.) :param size: the number of a posteriori samples. :type size: int. - :param full_cov: whether to return the full covariance matrix, or just the diagonal. - :type full_cov: bool. :param noise_model: for mixed noise likelihood, the noise model to use in the samples. :type noise_model: integer. :returns: Ysim: set of simulations, :rtype: np.ndarray (D x N x samples) (if D==1 we flatten out the first dimension) """ - fsim = self.posterior_samples_f(X, size, full_cov=full_cov, **predict_kwargs) + fsim = self.posterior_samples_f(X, size, **predict_kwargs) if likelihood is None: likelihood = self.likelihood if fsim.ndim == 3: - for d in range(fsim.shape[0]): - fsim[d] = likelihood.samples(fsim[d], Y_metadata=Y_metadata) + for d in range(fsim.shape[1]): + fsim[:, d] = likelihood.samples(fsim[:, d], Y_metadata=Y_metadata) else: fsim = likelihood.samples(fsim, Y_metadata=Y_metadata) return fsim From 7da9536f31af1884dcd949e2f5fb15f2965aea17 Mon Sep 17 00:00:00 2001 From: Siivola Eero Date: Thu, 1 Feb 2018 10:40:20 +0200 Subject: [PATCH 15/48] Added a new class that enables using multiple likelihoods for multioutput case (previously, Mixed noise only allowed use of multiple gaussians) --- GPy/likelihoods/__init__.py | 1 + GPy/likelihoods/multioutput_likelihood.py | 229 ++++++++++++++++++++++ GPy/testing/likelihood_tests.py | 11 +- 3 files changed, 240 insertions(+), 1 deletion(-) create mode 100644 GPy/likelihoods/multioutput_likelihood.py diff --git a/GPy/likelihoods/__init__.py b/GPy/likelihoods/__init__.py index 83941093c..7ec8092b2 100644 --- a/GPy/likelihoods/__init__.py +++ b/GPy/likelihoods/__init__.py @@ -9,3 +9,4 @@ from .binomial import Binomial from .weibull import Weibull from .loglogistic import LogLogistic +from .multioutput_likelihood import MultioutputLikelihood \ No newline at end of file diff --git a/GPy/likelihoods/multioutput_likelihood.py b/GPy/likelihoods/multioutput_likelihood.py new file mode 100644 index 000000000..7b201d600 --- /dev/null +++ b/GPy/likelihoods/multioutput_likelihood.py @@ -0,0 +1,229 @@ +# Copyright (c) 2012-2014 The GPy authors (see AUTHORS.txt) +# Licensed under the BSD 3-clause license (see LICENSE.txt) + +import numpy as np +from scipy import stats, special +from . import link_functions +from .likelihood import Likelihood +from .mixed_noise import MixedNoise +from .gaussian import Gaussian +from ..core.parameterization import Param +from paramz.transformations import Logexp +from ..core.parameterization import Parameterized +from ..kern.src.independent_outputs import index_to_slices +import itertools + +class MultioutputLikelihood(MixedNoise): + ''' + CombinedLikelihood is used to combine different likelihoods for + multioutput models, where different outputs have different observation models. + + As input the likelihood takes a list of likelihoods used. The likelihood + uses "output_index" in Y_metadata to connect observations to likelihoods. + ''' + def __init__(self, likelihoods_list, name='multioutput_likelihood'): + super(Likelihood, self).__init__(name=name) + + indices, inverse = self._unique_likelihoods(likelihoods_list) + self.link_parameters(*[likelihoods_list[i] for i in indices]) + + self.index_map = [indices[i] for i in inverse] + self.inverse = inverse + + self.gradient_sizes = [likelihoods_list[i].size for i in indices] + self.gradient_index = np.cumsum(self.gradient_sizes) - self.gradient_sizes[0] + + self.likelihoods_list = likelihoods_list + + self.gp_link = None + self.log_concave = False + self.not_block_really = False + + def _unique_likelihoods(self, likelihoods_list): + indices = [] + inverse = [] + for i in range(len(likelihoods_list)): + for j in indices: + if likelihoods_list[i] is likelihoods_list[j]: + inverse += [j] + break + if len(inverse) <= i: + indices += [i] + inverse += [i] + return indices, inverse + + def moments_match_ep(self, data_i, tau_i, v_i, Y_metadata_i): + return self.likelihoods_list[Y_metadata_i["output_index"][0]].moments_match_ep(data_i, tau_i, v_i, Y_metadata_i) + + def exact_inference_gradients(self, dL_dKdiag, Y_metadata): + assert all([isinstance(l, Gaussian) for l in self.likelihoods_list]) + ind = [self.index_map[i] for i in Y_metadata['output_index'].flatten()] + return np.array([dL_dKdiag[ind==i].sum() for i in np.unique(self.index_map)]) + + def ep_gradients(self, Y, cav_tau, cav_v, dL_dKdiag, Y_metadata=None, quad_mode='gk', boost_grad=1.): + ind = [self.index_map[i] for i in Y_metadata['output_index'].flatten()] + slices = index_to_slices(ind) + grads = np.zeros((self.size)) + for i in range(len(slices)): + if self.likelihoods_list[i].size > 0: + ii = self.inverse[i] ## index in our gradient_sizes and gradient_index -lists + for j in range(len(slices[i])): + grads[self.gradient_index[ii]:self.gradient_index[ii]+self.gradient_sizes[ii]] += self.likelihoods_list[i].ep_gradients(Y[slices[i][j],:], cav_tau[slices[i][j]], cav_v[slices[i][j]], dL_dKdiag = dL_dKdiag[slices[i][j]], Y_metadata=Y_metadata, quad_mode=quad_mode, boost_grad=boost_grad) + return grads + + def predictive_values(self, mu, var, full_cov=False, Y_metadata=None): + ind = Y_metadata['output_index'].flatten() + outputs = np.unique(ind) + mu_new = np.zeros(mu.shape ) + var_new = np.zeros(var.shape ) + for j in outputs: + m, v = self.likelihoods_list[j].predictive_values(mu[ind==j,:], var[ind==j,:], full_cov, Y_metadata=None) + mu_new[ind==j,:] = m + var_new[ind==j,:] = v + return mu_new, var_new + + def predictive_variance(self, mu, sigma, Y_metadata): + ind = Y_metadata['output_index'].flatten() + outputs = np.unique(ind) + var = np.zeros( (sigma.size) ) + for j in outputs: + v = self.likelihoods_list[j].predictive_variance(mu[ind==j,:], + sigma[ind==j,:],Y_metadata=None) + var[ind==j,:] = np.hstack(v) + return [v[:,None] for v in var.T] + + def pdf(self, f, y, Y_metadata=None): + ind = Y_metadata['output_index'].flatten() + outputs = np.unique(ind) + pdf = np.zeros(y.shape) + for j in outputs: + pdf[ind==j,:] = self.likelihoods_list[j].pdf(f[ind==j,:], y[ind==j,:], Y_metadata=None) + return pdf + + def pdf_link(self, inv_link_f, y, Y_metadata=None): + ind = Y_metadata['output_index'].flatten() + outputs = np.unique(ind) + pdf_link = np.zeros(y.shape) + for j in outputs: + pdf_link[ind==j,:] = self.likelihoods_list[j].pdf_link(inv_link_f[ind==j,:], y[ind==j,:], Y_metadata=None) + return pdf_link + + def logpdf(self, f, y, Y_metadata=None): + ind = Y_metadata['output_index'].flatten() + outputs = np.unique(ind) + if ind.shape[0]==1: + ind = ind[0]*np.ones(f.shape[0]) + y = y*np.ones(f.shape) + lpdf = np.zeros(f.shape) + for j in outputs: + lpdf[np.where(ind==j)[0],:] = self.likelihoods_list[j].logpdf(f[np.where(ind==j)[0],:], y[np.where(ind==j)[0],:], Y_metadata=None) + return lpdf + + def logpdf_link(self, inv_link_f, y, Y_metadata=None): + ind = Y_metadata['output_index'].flatten() + outputs = np.unique(ind) + logpdf_link = np.zeros(y.shape) + for j in outputs: + logpdf_link[ind==j,:] = self.likelihoods_list[j].logpdf_link(inv_link_f[ind==j,:], y[ind==j,:], Y_metadata=None) + return logpdf_link + + def dlogpdf_dlink(self, inv_link_f, y, Y_metadata=None): + ind = Y_metadata['output_index'].flatten() + outputs = np.unique(ind) + dlogpdf_dlink = np.zeros(y.shape) + for j in outputs: + dlogpdf_dlink[ind==j,:] = self.likelihoods_list[j].dlogpdf_dlink(inv_link_f[ind==j,:], y[ind==j,:], Y_metadata=None) + return dlogpdf_dlink + + def d2logpdf_dlink2(self, inv_link_f, y, Y_metadata=None): + ind = Y_metadata['output_index'].flatten() + outputs = np.unique(ind) + d2logpdf_dlink2 = np.zeros(y.shape) + for j in outputs: + d2logpdf_dlink2[ind==j,:] = self.likelihoods_list[j].d2logpdf_dlink2(inv_link_f[ind==j,:], y[ind==j,:], Y_metadata=None) + return d2logpdf_dlink2 + + def d3logpdf_dlink3(self, inv_link_f, y, Y_metadata=None): + ind = Y_metadata['output_index'].flatten() + outputs = np.unique(ind) + d3logpdf_dlink3 = np.zeros(y.shape) + for j in outputs: + d3logpdf_dlink3[ind==j,:] = self.likelihoods_list[j].d3logpdf_dlink3(inv_link_f[ind==j,:], y[ind==j,:], Y_metadata=None) + return d3logpdf_dlink3 + + def log_predictive_density(self, y_test, mu_star, var_star, Y_metadata=None): + ind = Y_metadata['output_index'].flatten() + outputs = np.unique(ind) + log_pred = np.zeros(y_test.shape) + for j in outputs: + log_pred[ind==j,:] = self.likelihoods_list[j].log_predictive_density(y_test[ind==j,:], mu_star[ind==j,:], var_star[ind==j,:], Y_metadata=None) + return log_pred + + def dlogpdf_dtheta(self, f, y, Y_metadata=None): + ind = Y_metadata['output_index'].flatten() + if ind.shape[0]==1: + ind = ind[0]*np.ones(f.shape[0]) + y = y*np.ones(f.shape) + slices = index_to_slices(ind) + pdf = np.zeros((self.size, f.shape[0], f.shape[1]) ) + for i in range(len(slices)): + if self.likelihoods_list[i].size > 0: + ii = self.inverse[i] + for j in range(len(slices[i])): + pdf[self.gradient_index[ii]:self.gradient_index[ii]+self.gradient_sizes[ii], slices[i][j],:] = self.likelihoods_list[i].dlogpdf_dtheta(f[slices[i][j],:], y[slices[i][j],:], Y_metadata=None) + return pdf + + def d2logpdf_df2(self, f, y, Y_metadata): + ind = Y_metadata['output_index'].flatten() + outputs = np.unique(ind) + Q = np.zeros(f.shape) + for j in outputs: + Q[ind==j,:] = self.likelihoods_list[j].d2logpdf_df2(f[ind==j,:], + y[ind==j,:],Y_metadata=None) + return Q + + def dlogpdf_df(self, f, y, Y_metadata): + ind = Y_metadata['output_index'].flatten() + outputs = np.unique(ind) + Q = np.zeros(f.shape) + for j in outputs: + Q[ind==j,:] = self.likelihoods_list[j].dlogpdf_df(f[ind==j,:], + y[ind==j,:],Y_metadata=None) + return Q + + def d3logpdf_df3(self, f, y, Y_metadata=None): + ind = Y_metadata['output_index'].flatten() + outputs = np.unique(ind) + Q = np.zeros(f.shape) + for j in outputs: + Q[ind==j,:] = self.likelihoods_list[j].d3logpdf_df3(f[ind==j,:], + y[ind==j,:],Y_metadata=None) + return Q + + def dlogpdf_df_dtheta(self, f, y, Y_metadata=None): + ind = Y_metadata['output_index'].flatten() + if ind.shape[0]==1: + ind = ind[0]*np.ones(f.shape[0]) + y = y*np.ones(f.shape) + slices = index_to_slices(ind) + pdf = np.zeros((self.size, f.shape[0], f.shape[1]) ) + for i in range(len(slices)): + if self.likelihoods_list[i].size > 0: + ii = self.inverse[i] + for j in range(len(slices[i])): + pdf[self.gradient_index[ii]:self.gradient_index[ii]+self.gradient_sizes[ii], slices[i][j],:] = self.likelihoods_list[i].dlogpdf_df_dtheta(f[slices[i][j],:], y[slices[i][j],:], Y_metadata=None) + return pdf + + def d2logpdf_df2_dtheta(self, f, y, Y_metadata=None): + ind = Y_metadata['output_index'].flatten() + if ind.shape[0]==1: + ind = ind[0]*np.ones(f.shape[0]) + y = y*np.ones(f.shape) + slices = index_to_slices(ind) + pdf = np.zeros((self.size, f.shape[0], f.shape[1]) ) + for i in range(len(slices)): + if self.likelihoods_list[i].size > 0: + ii = self.inverse[i] + for j in range(len(slices[i])): + pdf[self.gradient_index[ii]:self.gradient_index[ii]+self.gradient_sizes[ii], slices[i][j],:] = self.likelihoods_list[i].d2logpdf_df2_dtheta(f[slices[i][j],:], y[slices[i][j],:], Y_metadata=None) + return pdf \ No newline at end of file diff --git a/GPy/testing/likelihood_tests.py b/GPy/testing/likelihood_tests.py index ac681ecc7..2c1a6e245 100644 --- a/GPy/testing/likelihood_tests.py +++ b/GPy/testing/likelihood_tests.py @@ -128,7 +128,7 @@ def setUp(self): censored[random_inds] = 1 self.Y_metadata = dict() self.Y_metadata['censored'] = censored - + self.Y_metadata['output_index'] = np.zeros((self.N,1), dtype=int) #Make a bigger step as lower bound can be quite curved self.step = 1e-4 @@ -292,6 +292,15 @@ def setUp(self): "Y": self.positive_Y, "Y_metadata": self.Y_metadata, "laplace": True + }, + "multioutput_default": { + "model": GPy.likelihoods.MultioutputLikelihood([GPy.likelihoods.Bernoulli()]), + "link_f_constraints": [partial(self.constrain_bounded, lower=0, upper=1)], + "laplace": True, + "Y": self.binary_Y, + "Y_metadata": self.Y_metadata, + "ep": True, + "variational_expectations": True, } #, #GAMMA needs some work!"Gamma_default": { From 46d3b6ce5ce9e23d0f2d2b942d36b3c84acb8e61 Mon Sep 17 00:00:00 2001 From: Jayanth Koushik Date: Thu, 15 Feb 2018 14:04:47 -0500 Subject: [PATCH 16/48] Don't override global cython config in tests --- GPy/testing/cython_tests.py | 6 ++++-- GPy/testing/kernel_tests.py | 2 +- 2 files changed, 5 insertions(+), 3 deletions(-) diff --git a/GPy/testing/cython_tests.py b/GPy/testing/cython_tests.py index c777aae05..dc41c44a7 100644 --- a/GPy/testing/cython_tests.py +++ b/GPy/testing/cython_tests.py @@ -4,15 +4,17 @@ import GPy import unittest +from ..util.config import config + try: from ..util import choleskies_cython - choleskies_cython_working = True + choleskies_cython_working = config.getboolean('cython', 'working') except ImportError: choleskies_cython_working = False try: from ..kern.src import stationary_cython - stationary_cython_working = True + stationary_cython_working = config.getboolean('cython', 'working') except ImportError: stationary_cython_working = False diff --git a/GPy/testing/kernel_tests.py b/GPy/testing/kernel_tests.py index 5f418674e..7f89ae4e1 100644 --- a/GPy/testing/kernel_tests.py +++ b/GPy/testing/kernel_tests.py @@ -15,7 +15,7 @@ try: from ..kern.src import coregionalize_cython - cython_coregionalize_working = True + cython_coregionalize_working = config.getboolean('cython', 'working') except ImportError: cython_coregionalize_working = False From 1aab04188566f658d417b0531ae6a306ff492189 Mon Sep 17 00:00:00 2001 From: Jayanth Koushik Date: Thu, 15 Feb 2018 17:17:25 -0500 Subject: [PATCH 17/48] Fix cython check in linalg --- GPy/util/linalg.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/GPy/util/linalg.py b/GPy/util/linalg.py index cad3b352c..406c19a6c 100644 --- a/GPy/util/linalg.py +++ b/GPy/util/linalg.py @@ -11,8 +11,11 @@ from .config import config import logging -if config.getboolean('cython', 'working'): +try: from . import linalg_cython + use_linalg_cython = config.getboolean('cython', 'working') +except ImportError: + use_linalg_cython = False def force_F_ordered_symmetric(A): """ @@ -358,7 +361,7 @@ def symmetrify(A, upper=False): note: tries to use cython, falls back to a slower numpy version """ - if config.getboolean('cython', 'working'): + if use_linalg_cython: _symmetrify_cython(A, upper) else: _symmetrify_numpy(A, upper) From 64c125573ecb5ccb2437ad58b796881b97713874 Mon Sep 17 00:00:00 2001 From: Jayanth Koushik Date: Thu, 15 Feb 2018 17:18:03 -0500 Subject: [PATCH 18/48] Use explicity cython/numpy variants in coregionalize test --- GPy/testing/kernel_tests.py | 18 ++++-------------- 1 file changed, 4 insertions(+), 14 deletions(-) diff --git a/GPy/testing/kernel_tests.py b/GPy/testing/kernel_tests.py index 7f89ae4e1..a0fc5a3d5 100644 --- a/GPy/testing/kernel_tests.py +++ b/GPy/testing/kernel_tests.py @@ -631,32 +631,25 @@ def setUp(self): def test_sym(self): dL_dK = np.random.randn(self.N1, self.N1) - GPy.util.config.config.set('cython', 'working', 'True') - K_cython = self.k.K(self.X) + K_cython = self.k._K_cython(self.X) self.k.update_gradients_full(dL_dK, self.X) grads_cython = self.k.gradient.copy() - GPy.util.config.config.set('cython', 'working', 'False') - K_numpy = self.k.K(self.X) + K_numpy = self.k._K_numpy(self.X) self.k.update_gradients_full(dL_dK, self.X) grads_numpy = self.k.gradient.copy() self.assertTrue(np.allclose(K_numpy, K_cython)) self.assertTrue(np.allclose(grads_numpy, grads_cython)) - #reset the cython state for any other tests - GPy.util.config.config.set('cython', 'working', 'true') - def test_nonsym(self): dL_dK = np.random.randn(self.N1, self.N2) - GPy.util.config.config.set('cython', 'working', 'True') - K_cython = self.k.K(self.X, self.X2) + K_cython = self.k._K_cython(self.X, self.X2) self.k.gradient = 0. self.k.update_gradients_full(dL_dK, self.X, self.X2) grads_cython = self.k.gradient.copy() - GPy.util.config.config.set('cython', 'working', 'False') - K_numpy = self.k.K(self.X, self.X2) + K_numpy = self.k._K_numpy(self.X, self.X2) self.k.gradient = 0. self.k.update_gradients_full(dL_dK, self.X, self.X2) grads_numpy = self.k.gradient.copy() @@ -664,9 +657,6 @@ def test_nonsym(self): self.assertTrue(np.allclose(K_numpy, K_cython)) self.assertTrue(np.allclose(grads_numpy, grads_cython)) - #reset the cython state for any other tests - GPy.util.config.config.set('cython', 'working', 'true') - class KernelTestsProductWithZeroValues(unittest.TestCase): From 08801c555496ed6b6e4da9eb52cb08baf487cf67 Mon Sep 17 00:00:00 2001 From: Jayanth Koushik Date: Thu, 15 Feb 2018 21:26:32 -0500 Subject: [PATCH 19/48] Ensure numpy version is used in coregionalize cython test --- GPy/testing/kernel_tests.py | 12 ++++++++++++ 1 file changed, 12 insertions(+) diff --git a/GPy/testing/kernel_tests.py b/GPy/testing/kernel_tests.py index a0fc5a3d5..a78ef69ac 100644 --- a/GPy/testing/kernel_tests.py +++ b/GPy/testing/kernel_tests.py @@ -636,7 +636,14 @@ def test_sym(self): grads_cython = self.k.gradient.copy() K_numpy = self.k._K_numpy(self.X) + # Nasty hack to ensure the numpy version is used for update_gradients + # If this test is running, cython is working, so override the cython + # function with the numpy function + _gradient_reduce_cython = self.k._gradient_reduce_cython + self.k._gradient_reduce_cython = self.k._gradient_reduce_numpy self.k.update_gradients_full(dL_dK, self.X) + # Undo hack + self.k._gradient_reduce_cython = _gradient_reduce_cython grads_numpy = self.k.gradient.copy() self.assertTrue(np.allclose(K_numpy, K_cython)) @@ -651,7 +658,12 @@ def test_nonsym(self): K_numpy = self.k._K_numpy(self.X, self.X2) self.k.gradient = 0. + # Same hack as in test_sym (Line 639) + _gradient_reduce_cython = self.k._gradient_reduce_cython + self.k._gradient_reduce_cython = self.k._gradient_reduce_numpy self.k.update_gradients_full(dL_dK, self.X, self.X2) + # Undo hack + self.k._gradient_reduce_cython = _gradient_reduce_cython grads_numpy = self.k.gradient.copy() self.assertTrue(np.allclose(K_numpy, K_cython)) From f4ebae742595eff2c95a68d583a44d0920b39b26 Mon Sep 17 00:00:00 2001 From: Moreno Date: Mon, 5 Mar 2018 12:14:31 +0000 Subject: [PATCH 20/48] add serialization functions for EPDTC --- .../expectation_propagation.py | 39 +++++++++++++++++++ GPy/testing/serialization_tests.py | 34 ++++++++++++++++ 2 files changed, 73 insertions(+) diff --git a/GPy/inference/latent_function_inference/expectation_propagation.py b/GPy/inference/latent_function_inference/expectation_propagation.py index e92b58cb9..61d3feff9 100644 --- a/GPy/inference/latent_function_inference/expectation_propagation.py +++ b/GPy/inference/latent_function_inference/expectation_propagation.py @@ -132,6 +132,13 @@ def _update_rank1(self, LLT, Kmn, delta_v, delta_tau, i): self.mu += (delta_v-delta_tau*self.mu[i])*si #mu = np.dot(Sigma, v_tilde) + def to_dict(self): + return { "mu": self.mu.tolist(), "Sigma_diag": self.Sigma_diag.tolist()} + + @staticmethod + def from_dict(input_dict): + return posteriorParamsDTC(np.array(input_dict["mu"]), np.array(input_dict["Sigma_diag"])) + @staticmethod def _recompute(LLT0, Kmn, ga_approx): LLT = LLT0 + np.dot(Kmn*ga_approx.tau[None,:],Kmn.T) @@ -533,3 +540,35 @@ def _local_updates(self, num_data, LLT0, LLT, Kmn, cav_params, post_params, marg #Posterior distribution parameters update if self.parallel_updates == False: post_params._update_rank1(LLT, Kmn, delta_v, delta_tau, i) + + + def to_dict(self): + input_dict = super(EPDTC, self)._to_dict() + input_dict["class"] = "GPy.inference.latent_function_inference.expectation_propagation.EPDTC" + if self.ga_approx_old is not None: + input_dict["ga_approx_old"] = self.ga_approx_old.to_dict() + if self._ep_approximation is not None: + input_dict["_ep_approximation"] = {} + input_dict["_ep_approximation"]["post_params"] = self._ep_approximation[0].to_dict() + input_dict["_ep_approximation"]["ga_approx"] = self._ep_approximation[1].to_dict() + input_dict["_ep_approximation"]["cav_params"] = self._ep_approximation[2].to_dict() + input_dict["_ep_approximation"]["log_Z_tilde"] = self._ep_approximation[3].tolist() + + return input_dict + + @staticmethod + def _from_dict(inference_class, input_dict): + ga_approx_old = input_dict.pop('ga_approx_old', None) + if ga_approx_old is not None: + ga_approx_old = gaussianApproximation.from_dict(ga_approx_old) + _ep_approximation_dict = input_dict.pop('_ep_approximation', None) + _ep_approximation = [] + if _ep_approximation is not None: + _ep_approximation.append(posteriorParamsDTC.from_dict(_ep_approximation_dict["post_params"])) + _ep_approximation.append(gaussianApproximation.from_dict(_ep_approximation_dict["ga_approx"])) + _ep_approximation.append(cavityParams.from_dict(_ep_approximation_dict["cav_params"])) + _ep_approximation.append(np.array(_ep_approximation_dict["log_Z_tilde"])) + ee = EPDTC(**input_dict) + ee.ga_approx_old = ga_approx_old + ee._ep_approximation = _ep_approximation + return ee diff --git a/GPy/testing/serialization_tests.py b/GPy/testing/serialization_tests.py index 80dfd219e..7eb3fe5c0 100644 --- a/GPy/testing/serialization_tests.py +++ b/GPy/testing/serialization_tests.py @@ -116,11 +116,45 @@ def test_serialize_deserialize_inference_methods(self): np.testing.assert_array_equal(e1._ep_approximation[2].v[:], e1_r._ep_approximation[2].v[:]) np.testing.assert_array_equal(e1._ep_approximation[3][:], e1_r._ep_approximation[3][:]) + + e1 = GPy.inference.latent_function_inference.expectation_propagation.EPDTC(ep_mode="nested") + e1.ga_approx_old = GPy.inference.latent_function_inference.expectation_propagation.gaussianApproximation(np.random.rand(10),np.random.rand(10)) + e1._ep_approximation = [] + e1._ep_approximation.append(GPy.inference.latent_function_inference.expectation_propagation.posteriorParamsDTC(np.random.rand(10),np.random.rand(10))) + e1._ep_approximation.append(GPy.inference.latent_function_inference.expectation_propagation.gaussianApproximation(np.random.rand(10),np.random.rand(10))) + e1._ep_approximation.append(GPy.inference.latent_function_inference.expectation_propagation.cavityParams(10)) + e1._ep_approximation[-1].v = np.random.rand(10) + e1._ep_approximation[-1].tau = np.random.rand(10) + e1._ep_approximation.append(np.random.rand(10)) + e1_r = GPy.inference.latent_function_inference.LatentFunctionInference.from_dict(e1.to_dict()) + + + assert type(e1) == type(e1_r) + assert e1.epsilon==e1_r.epsilon + assert e1.eta==e1_r.eta + assert e1.delta==e1_r.delta + assert e1.always_reset==e1_r.always_reset + assert e1.max_iters==e1_r.max_iters + assert e1.ep_mode==e1_r.ep_mode + assert e1.parallel_updates==e1_r.parallel_updates + + np.testing.assert_array_equal(e1.ga_approx_old.tau[:], e1_r.ga_approx_old.tau[:]) + np.testing.assert_array_equal(e1.ga_approx_old.v[:], e1_r.ga_approx_old.v[:]) + np.testing.assert_array_equal(e1._ep_approximation[0].mu[:], e1_r._ep_approximation[0].mu[:]) + np.testing.assert_array_equal(e1._ep_approximation[0].Sigma_diag[:], e1_r._ep_approximation[0].Sigma_diag[:]) + np.testing.assert_array_equal(e1._ep_approximation[1].tau[:], e1_r._ep_approximation[1].tau[:]) + np.testing.assert_array_equal(e1._ep_approximation[1].v[:], e1_r._ep_approximation[1].v[:]) + np.testing.assert_array_equal(e1._ep_approximation[2].tau[:], e1_r._ep_approximation[2].tau[:]) + np.testing.assert_array_equal(e1._ep_approximation[2].v[:], e1_r._ep_approximation[2].v[:]) + np.testing.assert_array_equal(e1._ep_approximation[3][:], e1_r._ep_approximation[3][:]) + + e2 = GPy.inference.latent_function_inference.exact_gaussian_inference.ExactGaussianInference() e2_r = GPy.inference.latent_function_inference.LatentFunctionInference.from_dict(e2.to_dict()) assert type(e2) == type(e2_r) + def test_serialize_deserialize_model(self): np.random.seed(fixed_seed) N = 20 From 90c2912acefaf7d0f595e62f664a2317cea104ec Mon Sep 17 00:00:00 2001 From: Diego Torrejon Date: Wed, 21 Mar 2018 18:00:13 -0400 Subject: [PATCH 21/48] Fixes the dimensions of the samples output --- GPy/core/gp.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 536b2ad47..6c96d2493 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -592,7 +592,7 @@ def sim_one_dim(m, v): if self.output_dim == 1: return sim_one_dim(m, v) else: - fsim = np.empty((self.output_dim, self.num_data, size)) + fsim = np.empty((self.output_dim, len(X), size)) for d in range(self.output_dim): if full_cov and v.ndim == 3: fsim[d] = sim_one_dim(m[:, d], v[:, :, d]) From 69eb888ad1367900ad15f61c7829ad0df11ce0af Mon Sep 17 00:00:00 2001 From: Diego Torrejon Date: Thu, 22 Mar 2018 16:32:05 -0400 Subject: [PATCH 22/48] Maintains consistency with numpy arrays --- GPy/core/gp.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 6c96d2493..453de4078 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -592,7 +592,7 @@ def sim_one_dim(m, v): if self.output_dim == 1: return sim_one_dim(m, v) else: - fsim = np.empty((self.output_dim, len(X), size)) + fsim = np.empty((self.output_dim, X.shape[0], size)) for d in range(self.output_dim): if full_cov and v.ndim == 3: fsim[d] = sim_one_dim(m[:, d], v[:, :, d]) From 7b2af57aee34e6e09dfdc32fd95736786c5738e1 Mon Sep 17 00:00:00 2001 From: Moreno Date: Wed, 16 May 2018 08:53:55 +0100 Subject: [PATCH 23/48] Sparse GP serialization --- GPy/core/sparse_gp.py | 39 ++++++ .../expectation_propagation.py | 14 +-- GPy/models/sparse_gp_classification.py | 27 +++- GPy/testing/serialization_tests.py | 116 ++++++++++++------ 4 files changed, 145 insertions(+), 51 deletions(-) diff --git a/GPy/core/sparse_gp.py b/GPy/core/sparse_gp.py index 4c7e98c41..820b16e7c 100644 --- a/GPy/core/sparse_gp.py +++ b/GPy/core/sparse_gp.py @@ -117,3 +117,42 @@ def _update_gradients(self): self.Z.gradient = self.kern.gradients_X(self.grad_dict['dL_dKmm'], self.Z) self.Z.gradient += self.kern.gradients_X(self.grad_dict['dL_dKnm'].T, self.Z, self.X) self._Zgrad = self.Z.gradient.copy() + + def to_dict(self, save_data=True): + input_dict = super(SparseGP, self).to_dict(save_data) + input_dict["class"] = "GPy.core.SparseGP" + input_dict["Z"] = self.Z.tolist() + return input_dict + + @staticmethod + def _from_dict(input_dict, data=None): + import GPy + if (input_dict['X'] is None) or (input_dict['Y'] is None): + assert(data is not None) + input_dict["X"], input_dict["Y"] = np.array(data[0]), np.array(data[1]) + elif data is not None: + print("WARNING: The model has been saved with X,Y! The original values are being overriden!") + input_dict["X"], input_dict["Y"] = np.array(data[0]), np.array(data[1]) + else: + input_dict["X"], input_dict["Y"] = np.array(input_dict['X']), np.array(input_dict['Y']) + + input_dict["Z"] = np.array(input_dict['Z']) + input_dict["kernel"] = GPy.kern.Kern.from_dict(input_dict["kernel"]) + input_dict["likelihood"] = GPy.likelihoods.likelihood.Likelihood.from_dict(input_dict["likelihood"]) + mean_function = input_dict.get("mean_function") + if mean_function is not None: + input_dict["mean_function"] = GPy.core.mapping.Mapping.from_dict(mean_function) + else: + input_dict["mean_function"] = mean_function + input_dict["inference_method"] = GPy.inference.latent_function_inference.LatentFunctionInference.from_dict(input_dict["inference_method"]) + + #FIXME: Assumes the Y_metadata is serializable. We should create a Metadata class + Y_metadata = input_dict.get("Y_metadata") + input_dict["Y_metadata"] = Y_metadata + + normalizer = input_dict.get("normalizer") + if normalizer is not None: + input_dict["normalizer"] = GPy.util.normalizer._Norm.from_dict(normalizer) + else: + input_dict["normalizer"] = normalizer + return SparseGP(**input_dict) diff --git a/GPy/inference/latent_function_inference/expectation_propagation.py b/GPy/inference/latent_function_inference/expectation_propagation.py index 61d3feff9..635a1bbd8 100644 --- a/GPy/inference/latent_function_inference/expectation_propagation.py +++ b/GPy/inference/latent_function_inference/expectation_propagation.py @@ -402,7 +402,7 @@ def _from_dict(inference_class, input_dict): class EPDTC(EPBase, VarDTC): def inference(self, kern, X, Z, likelihood, Y, mean_function=None, Y_metadata=None, Lm=None, dL_dKmm=None, psi0=None, psi1=None, psi2=None): - if self.always_reset: + if self.always_reset and not self.loading: self.reset() num_data, output_dim = Y.shape @@ -420,11 +420,11 @@ def inference(self, kern, X, Z, likelihood, Y, mean_function=None, Y_metadata=No else: Kmn = psi1.T - if self.ep_mode=="nested": + if self.ep_mode=="nested" and not self.loading: #Force EP at each step of the optimization self._ep_approximation = None post_params, ga_approx, log_Z_tilde = self._ep_approximation = self.expectation_propagation(Kmm, Kmn, Y, likelihood, Y_metadata) - elif self.ep_mode=="alternated": + elif self.ep_mode=="alternated" or self.loading: if getattr(self, '_ep_approximation', None) is None: #if we don't yet have the results of runnign EP, run EP and store the computed factors in self._ep_approximation post_params, ga_approx, log_Z_tilde = self._ep_approximation = self.expectation_propagation(Kmm, Kmn, Y, likelihood, Y_metadata) @@ -434,6 +434,8 @@ def inference(self, kern, X, Z, likelihood, Y, mean_function=None, Y_metadata=No else: raise ValueError("ep_mode value not valid") + self.loading = False + mu_tilde = ga_approx.v / ga_approx.tau.astype(float) return super(EPDTC, self).inference(kern, X, Z, likelihood, ObsAr(mu_tilde[:,None]), @@ -551,8 +553,7 @@ def to_dict(self): input_dict["_ep_approximation"] = {} input_dict["_ep_approximation"]["post_params"] = self._ep_approximation[0].to_dict() input_dict["_ep_approximation"]["ga_approx"] = self._ep_approximation[1].to_dict() - input_dict["_ep_approximation"]["cav_params"] = self._ep_approximation[2].to_dict() - input_dict["_ep_approximation"]["log_Z_tilde"] = self._ep_approximation[3].tolist() + input_dict["_ep_approximation"]["log_Z_tilde"] = self._ep_approximation[2] return input_dict @@ -566,8 +567,7 @@ def _from_dict(inference_class, input_dict): if _ep_approximation is not None: _ep_approximation.append(posteriorParamsDTC.from_dict(_ep_approximation_dict["post_params"])) _ep_approximation.append(gaussianApproximation.from_dict(_ep_approximation_dict["ga_approx"])) - _ep_approximation.append(cavityParams.from_dict(_ep_approximation_dict["cav_params"])) - _ep_approximation.append(np.array(_ep_approximation_dict["log_Z_tilde"])) + _ep_approximation.append(_ep_approximation_dict["log_Z_tilde"]) ee = EPDTC(**input_dict) ee.ga_approx_old = ga_approx_old ee._ep_approximation = _ep_approximation diff --git a/GPy/models/sparse_gp_classification.py b/GPy/models/sparse_gp_classification.py index a996732a5..7a86e1d5a 100644 --- a/GPy/models/sparse_gp_classification.py +++ b/GPy/models/sparse_gp_classification.py @@ -7,6 +7,7 @@ from .. import likelihoods from .. import kern from ..inference.latent_function_inference import EPDTC +from copy import deepcopy class SparseGPClassification(SparseGP): """ @@ -40,6 +41,27 @@ def __init__(self, X, Y=None, likelihood=None, kernel=None, Z=None, num_inducing SparseGP.__init__(self, X, Y, Z, kernel, likelihood, inference_method=EPDTC(), name='SparseGPClassification',Y_metadata=Y_metadata) + @staticmethod + def from_sparse_gp(sparse_gp): + from copy import deepcopy + sparse_gp = deepcopy(sparse_gp) + SparseGPClassification(sparse_gp.X, sparse_gp.Y, sparse_gp.Z, sparse_gp.kern, sparse_gp.likelihood, sparse_gp.inference_method, sparse_gp.mean_function, name='sparse_gp_classification') + + def to_dict(self, save_data=True): + model_dict = super(SparseGPClassification,self).to_dict(save_data) + model_dict["class"] = "GPy.models.SparseGPClassification" + return model_dict + + @staticmethod + def from_dict(input_dict, data=None): + import GPy + m = GPy.core.model.Model.from_dict(input_dict, data) + return GPClassification.from_sparse_gp(m) + + def save_model(self, output_filename, compress=True, save_data=True): + self._save_model(output_filename, compress=True, save_data=True) + + class SparseGPClassificationUncertainInput(SparseGP): """ Sparse Gaussian Process model for classification with uncertain inputs. @@ -87,8 +109,3 @@ def parameters_changed(self): self.psi2 = self.kern.psi2n(self.Z, self.X) self.posterior, self._log_marginal_likelihood, self.grad_dict = self.inference_method.inference(self.kern, self.X, self.Z, self.likelihood, self.Y, self.Y_metadata, psi0=self.psi0, psi1=self.psi1, psi2=self.psi2) self._update_gradients() - - - - - diff --git a/GPy/testing/serialization_tests.py b/GPy/testing/serialization_tests.py index 7eb3fe5c0..57781bf32 100644 --- a/GPy/testing/serialization_tests.py +++ b/GPy/testing/serialization_tests.py @@ -11,6 +11,7 @@ import GPy from nose import SkipTest import numpy as np +import os fixed_seed = 11 @@ -116,46 +117,38 @@ def test_serialize_deserialize_inference_methods(self): np.testing.assert_array_equal(e1._ep_approximation[2].v[:], e1_r._ep_approximation[2].v[:]) np.testing.assert_array_equal(e1._ep_approximation[3][:], e1_r._ep_approximation[3][:]) + e2 = GPy.inference.latent_function_inference.expectation_propagation.EPDTC(ep_mode="nested") + e2.ga_approx_old = GPy.inference.latent_function_inference.expectation_propagation.gaussianApproximation(np.random.rand(10),np.random.rand(10)) + e2._ep_approximation = [] + e2._ep_approximation.append(GPy.inference.latent_function_inference.expectation_propagation.posteriorParamsDTC(np.random.rand(10),np.random.rand(10))) + e2._ep_approximation.append(GPy.inference.latent_function_inference.expectation_propagation.gaussianApproximation(np.random.rand(10),np.random.rand(10))) + e2._ep_approximation.append(100.0) + e2_r = GPy.inference.latent_function_inference.LatentFunctionInference.from_dict(e2.to_dict()) - e1 = GPy.inference.latent_function_inference.expectation_propagation.EPDTC(ep_mode="nested") - e1.ga_approx_old = GPy.inference.latent_function_inference.expectation_propagation.gaussianApproximation(np.random.rand(10),np.random.rand(10)) - e1._ep_approximation = [] - e1._ep_approximation.append(GPy.inference.latent_function_inference.expectation_propagation.posteriorParamsDTC(np.random.rand(10),np.random.rand(10))) - e1._ep_approximation.append(GPy.inference.latent_function_inference.expectation_propagation.gaussianApproximation(np.random.rand(10),np.random.rand(10))) - e1._ep_approximation.append(GPy.inference.latent_function_inference.expectation_propagation.cavityParams(10)) - e1._ep_approximation[-1].v = np.random.rand(10) - e1._ep_approximation[-1].tau = np.random.rand(10) - e1._ep_approximation.append(np.random.rand(10)) - e1_r = GPy.inference.latent_function_inference.LatentFunctionInference.from_dict(e1.to_dict()) - - - assert type(e1) == type(e1_r) - assert e1.epsilon==e1_r.epsilon - assert e1.eta==e1_r.eta - assert e1.delta==e1_r.delta - assert e1.always_reset==e1_r.always_reset - assert e1.max_iters==e1_r.max_iters - assert e1.ep_mode==e1_r.ep_mode - assert e1.parallel_updates==e1_r.parallel_updates - - np.testing.assert_array_equal(e1.ga_approx_old.tau[:], e1_r.ga_approx_old.tau[:]) - np.testing.assert_array_equal(e1.ga_approx_old.v[:], e1_r.ga_approx_old.v[:]) - np.testing.assert_array_equal(e1._ep_approximation[0].mu[:], e1_r._ep_approximation[0].mu[:]) - np.testing.assert_array_equal(e1._ep_approximation[0].Sigma_diag[:], e1_r._ep_approximation[0].Sigma_diag[:]) - np.testing.assert_array_equal(e1._ep_approximation[1].tau[:], e1_r._ep_approximation[1].tau[:]) - np.testing.assert_array_equal(e1._ep_approximation[1].v[:], e1_r._ep_approximation[1].v[:]) - np.testing.assert_array_equal(e1._ep_approximation[2].tau[:], e1_r._ep_approximation[2].tau[:]) - np.testing.assert_array_equal(e1._ep_approximation[2].v[:], e1_r._ep_approximation[2].v[:]) - np.testing.assert_array_equal(e1._ep_approximation[3][:], e1_r._ep_approximation[3][:]) + assert type(e2) == type(e2_r) + assert e2.epsilon==e2_r.epsilon + assert e2.eta==e2_r.eta + assert e2.delta==e2_r.delta + assert e2.always_reset==e2_r.always_reset + assert e2.max_iters==e2_r.max_iters + assert e2.ep_mode==e2_r.ep_mode + assert e2.parallel_updates==e2_r.parallel_updates + np.testing.assert_array_equal(e2.ga_approx_old.tau[:], e2_r.ga_approx_old.tau[:]) + np.testing.assert_array_equal(e2.ga_approx_old.v[:], e2_r.ga_approx_old.v[:]) + np.testing.assert_array_equal(e2._ep_approximation[0].mu[:], e2_r._ep_approximation[0].mu[:]) + np.testing.assert_array_equal(e2._ep_approximation[0].Sigma_diag[:], e2_r._ep_approximation[0].Sigma_diag[:]) + np.testing.assert_array_equal(e2._ep_approximation[1].tau[:], e2_r._ep_approximation[1].tau[:]) + np.testing.assert_array_equal(e2._ep_approximation[1].v[:], e2_r._ep_approximation[1].v[:]) + assert(e2._ep_approximation[2] == e2_r._ep_approximation[2]) - e2 = GPy.inference.latent_function_inference.exact_gaussian_inference.ExactGaussianInference() - e2_r = GPy.inference.latent_function_inference.LatentFunctionInference.from_dict(e2.to_dict()) + e3 = GPy.inference.latent_function_inference.exact_gaussian_inference.ExactGaussianInference() + e3_r = GPy.inference.latent_function_inference.LatentFunctionInference.from_dict(e3.to_dict()) - assert type(e2) == type(e2_r) + assert type(e3) == type(e3_r) - def test_serialize_deserialize_model(self): + def test_serialize_deserialize_GP(self): np.random.seed(fixed_seed) N = 20 Nhalf = int(N/2) @@ -165,13 +158,13 @@ def test_serialize_deserialize_model(self): likelihood = GPy.likelihoods.Bernoulli() inference_method=GPy.inference.latent_function_inference.expectation_propagation.EP(ep_mode="nested") mean_function=None + m = GPy.core.GP(X=X, Y=Y, kernel=kernel, likelihood=likelihood, inference_method=inference_method, mean_function=mean_function, normalizer=True, name='gp_classification') m.optimize() m.save_model("temp_test_gp_with_data.json", compress=True, save_data=True) m.save_model("temp_test_gp_without_data.json", compress=True, save_data=False) m1_r = GPy.core.GP.load_model("temp_test_gp_with_data.json.zip") m2_r = GPy.core.GP.load_model("temp_test_gp_without_data.json.zip", (X,Y)) - import os os.remove("temp_test_gp_with_data.json.zip") os.remove("temp_test_gp_without_data.json.zip") var = m.predict(X)[0] @@ -180,7 +173,32 @@ def test_serialize_deserialize_model(self): np.testing.assert_array_equal(np.array(var).flatten(), np.array(var1_r).flatten()) np.testing.assert_array_equal(np.array(var).flatten(), np.array(var2_r).flatten()) - def test_serialize_deserialize_inference_GPRegressor(self): + def test_serialize_deserialize_SparseGP(self): + np.random.seed(fixed_seed) + N = 20 + Nhalf = int(N/2) + X = np.hstack([np.random.normal(5, 2, Nhalf), np.random.normal(10, 2, Nhalf)])[:, None] + Y = np.hstack([np.ones(Nhalf), np.zeros(Nhalf)])[:, None] + kernel = GPy.kern.RBF(1) + likelihood = GPy.likelihoods.Bernoulli() + inference_method=GPy.inference.latent_function_inference.expectation_propagation.EPDTC(ep_mode="nested") + mean_function=None + + sm = GPy.core.SparseGP(X=X, Y=Y, Z=X[0:20,:], kernel=kernel, likelihood=likelihood, inference_method=inference_method, mean_function=mean_function, normalizer=True, name='sparse_gp_classification') + sm.optimize() + sm.save_model("temp_test_gp_with_data.json", compress=True, save_data=True) + sm.save_model("temp_test_gp_without_data.json", compress=True, save_data=False) + sm1_r = GPy.core.GP.load_model("temp_test_gp_with_data.json.zip") + sm2_r = GPy.core.GP.load_model("temp_test_gp_without_data.json.zip", (X,Y)) + os.remove("temp_test_gp_with_data.json.zip") + os.remove("temp_test_gp_without_data.json.zip") + var = sm.predict(X)[0] + var1_r = sm1_r.predict(X)[0] + var2_r = sm2_r.predict(X)[0] + np.testing.assert_array_equal(np.array(var).flatten(), np.array(var1_r).flatten()) + np.testing.assert_array_equal(np.array(var).flatten(), np.array(var2_r).flatten()) + + def test_serialize_deserialize_GPRegressor(self): np.random.seed(fixed_seed) N = 50 N_new = 50 @@ -195,7 +213,6 @@ def test_serialize_deserialize_inference_GPRegressor(self): m.save_model("temp_test_gp_regressor_without_data.json", compress=True, save_data=False) m1_r = GPy.models.GPRegression.load_model("temp_test_gp_regressor_with_data.json.zip") m2_r = GPy.models.GPRegression.load_model("temp_test_gp_regressor_without_data.json.zip", (X,Y)) - import os os.remove("temp_test_gp_regressor_with_data.json.zip") os.remove("temp_test_gp_regressor_without_data.json.zip") @@ -208,7 +225,7 @@ def test_serialize_deserialize_inference_GPRegressor(self): np.testing.assert_array_equal(var.flatten(), var1_r.flatten()) np.testing.assert_array_equal(var.flatten(), var2_r.flatten()) - def test_serialize_deserialize_inference_GPClassifier(self): + def test_serialize_deserialize_GPClassification(self): np.random.seed(fixed_seed) N = 50 Nhalf = int(N/2) @@ -221,7 +238,6 @@ def test_serialize_deserialize_inference_GPClassifier(self): m.save_model("temp_test_gp_classifier_without_data.json", compress=True, save_data=False) m1_r = GPy.models.GPClassification.load_model("temp_test_gp_classifier_with_data.json.zip") m2_r = GPy.models.GPClassification.load_model("temp_test_gp_classifier_without_data.json.zip", (X,Y)) - import os os.remove("temp_test_gp_classifier_with_data.json.zip") os.remove("temp_test_gp_classifier_without_data.json.zip") @@ -231,6 +247,28 @@ def test_serialize_deserialize_inference_GPClassifier(self): np.testing.assert_array_equal(np.array(var).flatten(), np.array(var1_r).flatten()) np.testing.assert_array_equal(np.array(var).flatten(), np.array(var1_r).flatten()) + def test_serialize_deserialize_SparseGPClassification(self): + np.random.seed(fixed_seed) + N = 50 + Nhalf = int(N/2) + X = np.hstack([np.random.normal(5, 2, Nhalf), np.random.normal(10, 2, Nhalf)])[:, None] + Y = np.hstack([np.ones(Nhalf), np.zeros(Nhalf)])[:, None] + kernel = GPy.kern.RBF(1) + m = GPy.models.SparseGPClassification(X, Y, num_inducing=3, kernel=kernel) + m.optimize() + m.save_model("temp_test_sparse_gp_classifier_with_data.json", compress=True, save_data=True) + m.save_model("temp_test_sparse_gp_classifier_without_data.json", compress=True, save_data=False) + m1_r = GPy.models.SparseGPClassification.load_model("temp_test_sparse_gp_classifier_with_data.json.zip") + m2_r = GPy.models.SparseGPClassification.load_model("temp_test_sparse_gp_classifier_without_data.json.zip", (X,Y)) + os.remove("temp_test_sparse_gp_classifier_with_data.json.zip") + os.remove("temp_test_sparse_gp_classifier_without_data.json.zip") + + var = m.predict(X)[0] + var1_r = m1_r.predict(X)[0] + var2_r = m2_r.predict(X)[0] + np.testing.assert_array_equal(np.array(var).flatten(), np.array(var1_r).flatten()) + np.testing.assert_array_equal(np.array(var).flatten(), np.array(var1_r).flatten()) + if __name__ == "__main__": #import sys;sys.argv = ['', 'Test.test_parameter_index_operations'] unittest.main() From 11aa6ea27b09b4907b82bf87f8ba612162b6d6e8 Mon Sep 17 00:00:00 2001 From: Moreno Date: Thu, 7 Jun 2018 09:52:13 +0100 Subject: [PATCH 24/48] Serialization: Add docstrings --- GPy/core/gp.py | 13 +++- GPy/core/mapping.py | 17 ++++- GPy/core/model.py | 30 ++++++++- GPy/core/sparse_gp.py | 12 +++- .../latent_function_inference/__init__.py | 18 +++++- .../exact_gaussian_inference.py | 10 ++- .../expectation_propagation.py | 60 +++++++++++++++-- GPy/kern/src/add.py | 10 ++- GPy/kern/src/kern.py | 24 +++++-- GPy/kern/src/linear.py | 4 +- GPy/kern/src/prod.py | 10 ++- GPy/kern/src/rbf.py | 10 ++- GPy/kern/src/standard_periodic.py | 10 ++- GPy/kern/src/static.py | 8 +-- GPy/kern/src/stationary.py | 64 +++++++++++++++---- GPy/likelihoods/bernoulli.py | 10 ++- GPy/likelihoods/gaussian.py | 10 ++- GPy/likelihoods/likelihood.py | 18 +++++- GPy/likelihoods/link_functions.py | 38 +++++++++-- GPy/mappings/constant.py | 9 ++- GPy/mappings/identity.py | 9 ++- GPy/mappings/linear.py | 12 +++- GPy/models/sparse_gp_classification.py | 26 +++++++- GPy/util/normalizer.py | 30 +++++++-- 24 files changed, 393 insertions(+), 69 deletions(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 453de4078..ab7e8f9dd 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -110,7 +110,14 @@ def __init__(self, X, Y, kernel, likelihood, mean_function=None, inference_metho self.posterior = None def to_dict(self, save_data=True): - input_dict = super(GP, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + Note: It uses the private method _save_to_input_dict of the parent. + + :param boolean save_data: if true, it adds the training data self.X and self.Y to the dictionary + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + input_dict = super(GP, self)._save_to_input_dict() input_dict["class"] = "GPy.core.GP" if not save_data: input_dict["X"] = None @@ -137,7 +144,7 @@ def to_dict(self, save_data=True): return input_dict @staticmethod - def _from_dict(input_dict, data=None): + def _build_from_input_dict(input_dict, data=None): import GPy import numpy as np if (input_dict['X'] is None) or (input_dict['Y'] is None): @@ -282,7 +289,7 @@ def _raw_predict(self, Xnew, full_cov=False, kern=None): mu += self.mean_function.f(Xnew) return mu, var - def predict(self, Xnew, full_cov=False, Y_metadata=None, kern=None, + def predict(self, Xnew, full_cov=False, Y_metadata=None, kern=None, likelihood=None, include_likelihood=True): """ Predict the function(s) at the new point(s) Xnew. This includes the diff --git a/GPy/core/mapping.py b/GPy/core/mapping.py index d8032c541..31e4d8bb6 100644 --- a/GPy/core/mapping.py +++ b/GPy/core/mapping.py @@ -28,7 +28,7 @@ def update_gradients(self, dL_dF, X): def to_dict(self): raise NotImplementedError - def _to_dict(self): + def _save_to_input_dict(self): input_dict = {} input_dict["input_dim"] = self.input_dim input_dict["output_dim"] = self.output_dim @@ -37,16 +37,27 @@ def _to_dict(self): @staticmethod def from_dict(input_dict): + """ + Instantiate an object of a derived class using the information + in input_dict (built by the to_dict method of the derived class). + More specifically, after reading the derived class from input_dict, + it calls the method _build_from_input_dict of the derived class. + Note: This method should not be overrided in the derived class. In case + it is needed, please override _build_from_input_dict instate. + + :param dict input_dict: Dictionary with all the information needed to + instantiate the object. + """ import copy input_dict = copy.deepcopy(input_dict) mapping_class = input_dict.pop('class') input_dict["name"] = str(input_dict["name"]) import GPy mapping_class = eval(mapping_class) - return mapping_class._from_dict(mapping_class, input_dict) + return mapping_class._build_from_input_dict(mapping_class, input_dict) @staticmethod - def _from_dict(mapping_class, input_dict): + def _build_from_input_dict(mapping_class, input_dict): return mapping_class(**input_dict) diff --git a/GPy/core/model.py b/GPy/core/model.py index 799d42bdf..b57e1a776 100644 --- a/GPy/core/model.py +++ b/GPy/core/model.py @@ -8,7 +8,10 @@ class Model(ParamzModel, Priorizable): def __init__(self, name): super(Model, self).__init__(name) # Parameterized.__init__(self) - def _to_dict(self): + def _save_to_input_dict(self): + """ + It is used by the public method to_dict to create json serializable dictionary. + """ input_dict = {} input_dict["name"] = self.name return input_dict @@ -18,16 +21,37 @@ def to_dict(self): @staticmethod def from_dict(input_dict, data=None): + """ + Instantiate an object of a derived class using the information + in input_dict (built by the to_dict method of the derived class). + More specifically, after reading the derived class from input_dict, + it calls the method _build_from_input_dict of the derived class. + Note: This method should not be overrided in the derived class. In case + it is needed, please override _build_from_input_dict instate. + + :param dict input_dict: Dictionary with all the information needed to + instantiate the object. + """ import copy input_dict = copy.deepcopy(input_dict) model_class = input_dict.pop('class') input_dict["name"] = str(input_dict["name"]) import GPy model_class = eval(model_class) - return model_class._from_dict(input_dict, data) + return model_class._build_from_input_dict(input_dict, data) @staticmethod - def _from_dict(model_class, input_dict, data=None): + def _build_from_input_dict(model_class, input_dict, data=None): + """ + This method is used by the public method from_dict to build an object + of class model_class using the information contained in input_dict. + Note: This method is often overrided in the derived class to deal with + any pre-processing of the parameters in input_dict before calling the + constructor of the object. + + :param str model_class: Class of the object to build. + :param dict input_dict: Extra information needed by the constructor of model_class. + """ return model_class(**input_dict) def save_model(self, output_filename, compress=True, save_data=True): diff --git a/GPy/core/sparse_gp.py b/GPy/core/sparse_gp.py index 820b16e7c..eb3650af5 100644 --- a/GPy/core/sparse_gp.py +++ b/GPy/core/sparse_gp.py @@ -119,16 +119,24 @@ def _update_gradients(self): self._Zgrad = self.Z.gradient.copy() def to_dict(self, save_data=True): + """ + Convert the object into a json serializable dictionary. + + :param boolean save_data: if true, it adds the training data self.X and self.Y to the dictionary + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ input_dict = super(SparseGP, self).to_dict(save_data) input_dict["class"] = "GPy.core.SparseGP" input_dict["Z"] = self.Z.tolist() return input_dict @staticmethod - def _from_dict(input_dict, data=None): + def _build_from_input_dict(input_dict, data=None): + # Called from the from_dict method. import GPy if (input_dict['X'] is None) or (input_dict['Y'] is None): - assert(data is not None) + if data is None: + raise ValueError("The model was serialized whithout the training data. 'data' must be not None!") input_dict["X"], input_dict["Y"] = np.array(data[0]), np.array(data[1]) elif data is not None: print("WARNING: The model has been saved with X,Y! The original values are being overriden!") diff --git a/GPy/inference/latent_function_inference/__init__.py b/GPy/inference/latent_function_inference/__init__.py index 97815a418..23742e6a5 100644 --- a/GPy/inference/latent_function_inference/__init__.py +++ b/GPy/inference/latent_function_inference/__init__.py @@ -41,7 +41,7 @@ def on_optimization_end(self): """ pass - def _to_dict(self): + def _save_to_input_dict(self): input_dict = {} return input_dict @@ -50,15 +50,27 @@ def to_dict(self): @staticmethod def from_dict(input_dict): + """ + Instantiate an object of a derived class using the information + in input_dict (built by the to_dict method of the derived class). + More specifically, after reading the derived class from input_dict, + it calls the method _build_from_input_dict of the derived class. + Note: This method should not be overrided in the derived class. In case + it is needed, please override _build_from_input_dict instate. + + :param dict input_dict: Dictionary with all the information needed to + instantiate the object. + """ + import copy input_dict = copy.deepcopy(input_dict) inference_class = input_dict.pop('class') import GPy inference_class = eval(inference_class) - return inference_class._from_dict(inference_class, input_dict) + return inference_class._build_from_input_dict(inference_class, input_dict) @staticmethod - def _from_dict(inference_class, input_dict): + def _build_from_input_dict(inference_class, input_dict): return inference_class(**input_dict) class InferenceMethodList(LatentFunctionInference, list): diff --git a/GPy/inference/latent_function_inference/exact_gaussian_inference.py b/GPy/inference/latent_function_inference/exact_gaussian_inference.py index a0a35fa54..569dbf3bb 100644 --- a/GPy/inference/latent_function_inference/exact_gaussian_inference.py +++ b/GPy/inference/latent_function_inference/exact_gaussian_inference.py @@ -22,7 +22,15 @@ def __init__(self): pass#self._YYTfactor_cache = caching.cache() def to_dict(self): - input_dict = super(ExactGaussianInference, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(ExactGaussianInference, self)._save_to_input_dict() input_dict["class"] = "GPy.inference.latent_function_inference.exact_gaussian_inference.ExactGaussianInference" return input_dict diff --git a/GPy/inference/latent_function_inference/expectation_propagation.py b/GPy/inference/latent_function_inference/expectation_propagation.py index 635a1bbd8..2a558b5b5 100644 --- a/GPy/inference/latent_function_inference/expectation_propagation.py +++ b/GPy/inference/latent_function_inference/expectation_propagation.py @@ -28,6 +28,14 @@ def _update_i(self, eta, ga_approx, post_params, i): self.tau[i] = 1./post_params.Sigma_diag[i] - eta*ga_approx.tau[i] self.v[i] = post_params.mu[i]/post_params.Sigma_diag[i] - eta*ga_approx.v[i] def to_dict(self): + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + return {"tau": self.tau.tolist(), "v": self.v.tolist()} @staticmethod def from_dict(input_dict): @@ -59,6 +67,14 @@ def _update_i(self, eta, delta, post_params, marg_moments, i): return (delta_tau, delta_v) def to_dict(self): + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + return {"tau": self.tau.tolist(), "v": self.v.tolist()} @staticmethod def from_dict(input_dict): @@ -89,6 +105,14 @@ def _update_rank1(self, delta_tau, delta_v, ga_approx, i): DSYR(self.Sigma, si, -ci) def to_dict(self): + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + #TODO: Implement a more memory efficient variant if self.L is None: return { "mu": self.mu.tolist(), "Sigma": self.Sigma.tolist()} @@ -133,6 +157,14 @@ def _update_rank1(self, LLT, Kmn, delta_v, delta_tau, i): #mu = np.dot(Sigma, v_tilde) def to_dict(self): + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + return { "mu": self.mu.tolist(), "Sigma_diag": self.Sigma_diag.tolist()} @staticmethod @@ -205,8 +237,8 @@ def __setstate__(self, state): def __getstate__(self): return [super(EPBase, self).__getstate__() , [self.epsilon, self.eta, self.delta]] - def _to_dict(self): - input_dict = super(EPBase, self)._to_dict() + def _save_to_input_dict(self): + input_dict = super(EPBase, self)._save_to_input_dict() input_dict["epsilon"]=self.epsilon input_dict["eta"]=self.eta input_dict["delta"]=self.delta @@ -370,7 +402,15 @@ def _inference(self, Y, mean_prior, K, ga_approx, cav_params, likelihood, Z_tild return Posterior(woodbury_inv=Wi, woodbury_vector=alpha, K=K), log_marginal, {'dL_dK':dL_dK, 'dL_dthetaL':dL_dthetaL, 'dL_dm':alpha} def to_dict(self): - input_dict = super(EP, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(EP, self)._save_to_input_dict() input_dict["class"] = "GPy.inference.latent_function_inference.expectation_propagation.EP" if self.ga_approx_old is not None: input_dict["ga_approx_old"] = self.ga_approx_old.to_dict() @@ -384,7 +424,7 @@ def to_dict(self): return input_dict @staticmethod - def _from_dict(inference_class, input_dict): + def _build_from_input_dict(inference_class, input_dict): ga_approx_old = input_dict.pop('ga_approx_old', None) if ga_approx_old is not None: ga_approx_old = gaussianApproximation.from_dict(ga_approx_old) @@ -545,7 +585,15 @@ def _local_updates(self, num_data, LLT0, LLT, Kmn, cav_params, post_params, marg def to_dict(self): - input_dict = super(EPDTC, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(EPDTC, self)._save_to_input_dict() input_dict["class"] = "GPy.inference.latent_function_inference.expectation_propagation.EPDTC" if self.ga_approx_old is not None: input_dict["ga_approx_old"] = self.ga_approx_old.to_dict() @@ -558,7 +606,7 @@ def to_dict(self): return input_dict @staticmethod - def _from_dict(inference_class, input_dict): + def _build_from_input_dict(inference_class, input_dict): ga_approx_old = input_dict.pop('ga_approx_old', None) if ga_approx_old is not None: ga_approx_old = gaussianApproximation.from_dict(ga_approx_old) diff --git a/GPy/kern/src/add.py b/GPy/kern/src/add.py index c1834f760..3fc34883f 100644 --- a/GPy/kern/src/add.py +++ b/GPy/kern/src/add.py @@ -44,7 +44,15 @@ def _check_exact_psicomp(self): return False def to_dict(self): - input_dict = super(Add, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(Add, self)._save_to_input_dict() input_dict["class"] = str("GPy.kern.Add") return input_dict diff --git a/GPy/kern/src/kern.py b/GPy/kern/src/kern.py index c08489e22..8da3fbfb1 100644 --- a/GPy/kern/src/kern.py +++ b/GPy/kern/src/kern.py @@ -60,7 +60,7 @@ def __init__(self, input_dim, active_dims, name, useGPU=False, *a, **kw): from .psi_comp import PSICOMP_GH self.psicomp = PSICOMP_GH() - def _to_dict(self): + def _save_to_input_dict(self): input_dict = {} input_dict["input_dim"] = self.input_dim if isinstance(self.active_dims, np.ndarray): @@ -76,16 +76,28 @@ def to_dict(self): @staticmethod def from_dict(input_dict): + """ + Instantiate an object of a derived class using the information + in input_dict (built by the to_dict method of the derived class). + More specifically, after reading the derived class from input_dict, + it calls the method _build_from_input_dict of the derived class. + Note: This method should not be overrided in the derived class. In case + it is needed, please override _build_from_input_dict instate. + + :param dict input_dict: Dictionary with all the information needed to + instantiate the object. + """ + import copy input_dict = copy.deepcopy(input_dict) kernel_class = input_dict.pop('class') input_dict["name"] = str(input_dict["name"]) import GPy kernel_class = eval(kernel_class) - return kernel_class._from_dict(kernel_class, input_dict) + return kernel_class._build_from_input_dict(kernel_class, input_dict) @staticmethod - def _from_dict(kernel_class, input_dict): + def _build_from_input_dict(kernel_class, input_dict): return kernel_class(**input_dict) @@ -375,15 +387,15 @@ def __init__(self, kernels, name, extra_dims=[], link_parameters=True): if link_parameters: self.link_parameters(*kernels) - def _to_dict(self): - input_dict = super(CombinationKernel, self)._to_dict() + def _save_to_input_dict(self): + input_dict = super(CombinationKernel, self)._save_to_input_dict() input_dict["parts"] = {} for ii in range(len(self.parts)): input_dict["parts"][ii] = self.parts[ii].to_dict() return input_dict @staticmethod - def _from_dict(kernel_class, input_dict): + def _build_from_input_dict(kernel_class, input_dict): parts = input_dict.pop('parts', None) subkerns = [] for pp in parts: diff --git a/GPy/kern/src/linear.py b/GPy/kern/src/linear.py index 10edb4c2a..bf75f2010 100644 --- a/GPy/kern/src/linear.py +++ b/GPy/kern/src/linear.py @@ -52,14 +52,14 @@ def __init__(self, input_dim, variances=None, ARD=False, active_dims=None, name= self.psicomp = PSICOMP_Linear() def to_dict(self): - input_dict = super(Linear, self)._to_dict() + input_dict = super(Linear, self)._save_to_input_dict() input_dict["class"] = "GPy.kern.Linear" input_dict["variances"] = self.variances.values.tolist() input_dict["ARD"] = self.ARD return input_dict @staticmethod - def _from_dict(kernel_class, input_dict): + def _build_from_input_dict(kernel_class, input_dict): useGPU = input_dict.pop('useGPU', None) return Linear(**input_dict) diff --git a/GPy/kern/src/prod.py b/GPy/kern/src/prod.py index 31e62392c..6bf5f9f34 100644 --- a/GPy/kern/src/prod.py +++ b/GPy/kern/src/prod.py @@ -43,7 +43,15 @@ def __init__(self, kernels, name='mul'): super(Prod, self).__init__(_newkerns, name) def to_dict(self): - input_dict = super(Prod, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(Prod, self)._save_to_input_dict() input_dict["class"] = str("GPy.kern.Prod") return input_dict diff --git a/GPy/kern/src/rbf.py b/GPy/kern/src/rbf.py index 0b6730d81..c17345d83 100644 --- a/GPy/kern/src/rbf.py +++ b/GPy/kern/src/rbf.py @@ -32,7 +32,15 @@ def __init__(self, input_dim, variance=1., lengthscale=None, ARD=False, active_d self.link_parameter(self.inv_l) def to_dict(self): - input_dict = super(RBF, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(RBF, self)._save_to_input_dict() input_dict["class"] = "GPy.kern.RBF" input_dict["inv_l"] = self.use_invLengthscale if input_dict["inv_l"] == True: diff --git a/GPy/kern/src/standard_periodic.py b/GPy/kern/src/standard_periodic.py index 201f8d195..e7b672397 100644 --- a/GPy/kern/src/standard_periodic.py +++ b/GPy/kern/src/standard_periodic.py @@ -94,7 +94,15 @@ def __init__(self, input_dim, variance=1., period=None, lengthscale=None, ARD1=F self.link_parameters(self.variance, self.period, self.lengthscale) def to_dict(self): - input_dict = super(StdPeriodic, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(StdPeriodic, self)._save_to_input_dict() input_dict["class"] = "GPy.kern.StdPeriodic" input_dict["variance"] = self.variance.values.tolist() input_dict["period"] = self.period.values.tolist() diff --git a/GPy/kern/src/static.py b/GPy/kern/src/static.py index f7042cc11..a4831107a 100644 --- a/GPy/kern/src/static.py +++ b/GPy/kern/src/static.py @@ -14,8 +14,8 @@ def __init__(self, input_dim, variance, active_dims, name): self.variance = Param('variance', variance, Logexp()) self.link_parameters(self.variance) - def _to_dict(self): - input_dict = super(Static, self)._to_dict() + def _save_to_input_dict(self): + input_dict = super(Static, self)._save_to_input_dict() input_dict["variance"] = self.variance.values.tolist() return input_dict @@ -139,12 +139,12 @@ def __init__(self, input_dim, variance=1., active_dims=None, name='bias'): super(Bias, self).__init__(input_dim, variance, active_dims, name) def to_dict(self): - input_dict = super(Bias, self)._to_dict() + input_dict = super(Bias, self)._save_to_input_dict() input_dict["class"] = "GPy.kern.Bias" return input_dict @staticmethod - def _from_dict(kernel_class, input_dict): + def _build_from_input_dict(kernel_class, input_dict): useGPU = input_dict.pop('useGPU', None) return Bias(**input_dict) diff --git a/GPy/kern/src/stationary.py b/GPy/kern/src/stationary.py index 81129a754..cf3f5dff2 100644 --- a/GPy/kern/src/stationary.py +++ b/GPy/kern/src/stationary.py @@ -79,8 +79,8 @@ def __init__(self, input_dim, variance, lengthscale, ARD, active_dims, name, use assert self.variance.size==1 self.link_parameters(self.variance, self.lengthscale) - def _to_dict(self): - input_dict = super(Stationary, self)._to_dict() + def _save_to_input_dict(self): + input_dict = super(Stationary, self)._save_to_input_dict() input_dict["variance"] = self.variance.values.tolist() input_dict["lengthscale"] = self.lengthscale.values.tolist() input_dict["ARD"] = self.ARD @@ -366,12 +366,20 @@ def dK_dr(self, r): return -self.K_of_r(r) def to_dict(self): - input_dict = super(Exponential, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(Exponential, self)._save_to_input_dict() input_dict["class"] = "GPy.kern.Exponential" return input_dict @staticmethod - def _from_dict(kernel_class, input_dict): + def _build_from_input_dict(kernel_class, input_dict): useGPU = input_dict.pop('useGPU', None) return Exponential(**input_dict) @@ -424,12 +432,20 @@ def __init__(self, input_dim, variance=1., lengthscale=None, ARD=False, active_d super(Matern32, self).__init__(input_dim, variance, lengthscale, ARD, active_dims, name) def to_dict(self): - input_dict = super(Matern32, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(Matern32, self)._save_to_input_dict() input_dict["class"] = "GPy.kern.Matern32" return input_dict @staticmethod - def _from_dict(kernel_class, input_dict): + def _build_from_input_dict(kernel_class, input_dict): useGPU = input_dict.pop('useGPU', None) return Matern32(**input_dict) @@ -513,12 +529,20 @@ def __init__(self, input_dim, variance=1., lengthscale=None, ARD=False, active_d super(Matern52, self).__init__(input_dim, variance, lengthscale, ARD, active_dims, name) def to_dict(self): - input_dict = super(Matern52, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(Matern52, self)._save_to_input_dict() input_dict["class"] = "GPy.kern.Matern52" return input_dict @staticmethod - def _from_dict(kernel_class, input_dict): + def _build_from_input_dict(kernel_class, input_dict): useGPU = input_dict.pop('useGPU', None) return Matern52(**input_dict) @@ -578,12 +602,20 @@ def __init__(self, input_dim, variance=1., lengthscale=None, ARD=False, active_d super(ExpQuad, self).__init__(input_dim, variance, lengthscale, ARD, active_dims, name) def to_dict(self): - input_dict = super(ExpQuad, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(ExpQuad, self)._save_to_input_dict() input_dict["class"] = "GPy.kern.ExpQuad" return input_dict @staticmethod - def _from_dict(kernel_class, input_dict): + def _build_from_input_dict(kernel_class, input_dict): useGPU = input_dict.pop('useGPU', None) return ExpQuad(**input_dict) @@ -621,13 +653,21 @@ def __init__(self, input_dim, variance=1., lengthscale=None, power=2., ARD=False self.link_parameters(self.power) def to_dict(self): - input_dict = super(RatQuad, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(RatQuad, self)._save_to_input_dict() input_dict["class"] = "GPy.kern.RatQuad" input_dict["power"] = self.power.values.tolist() return input_dict @staticmethod - def _from_dict(kernel_class, input_dict): + def _build_from_input_dict(kernel_class, input_dict): useGPU = input_dict.pop('useGPU', None) return RatQuad(**input_dict) diff --git a/GPy/likelihoods/bernoulli.py b/GPy/likelihoods/bernoulli.py index a00798f90..2e745b9b4 100644 --- a/GPy/likelihoods/bernoulli.py +++ b/GPy/likelihoods/bernoulli.py @@ -30,7 +30,15 @@ def __init__(self, gp_link=None): self.log_concave = True def to_dict(self): - input_dict = super(Bernoulli, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(Bernoulli, self)._save_to_input_dict() input_dict["class"] = "GPy.likelihoods.Bernoulli" return input_dict diff --git a/GPy/likelihoods/gaussian.py b/GPy/likelihoods/gaussian.py index 412fe4047..830deb4d1 100644 --- a/GPy/likelihoods/gaussian.py +++ b/GPy/likelihoods/gaussian.py @@ -47,7 +47,15 @@ def __init__(self, gp_link=None, variance=1., name='Gaussian_noise'): self.log_concave = True def to_dict(self): - input_dict = super(Gaussian, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(Gaussian, self)._save_to_input_dict() input_dict["class"] = "GPy.likelihoods.Gaussian" input_dict["variance"] = self.variance.values.tolist() return input_dict diff --git a/GPy/likelihoods/likelihood.py b/GPy/likelihoods/likelihood.py index b28fdef51..b4f727195 100644 --- a/GPy/likelihoods/likelihood.py +++ b/GPy/likelihoods/likelihood.py @@ -49,7 +49,7 @@ def __init__(self, gp_link, name): def to_dict(self): raise NotImplementedError - def _to_dict(self): + def _save_to_input_dict(self): input_dict = {} input_dict["name"] = self.name input_dict["gp_link_dict"] = self.gp_link.to_dict() @@ -57,6 +57,18 @@ def _to_dict(self): @staticmethod def from_dict(input_dict): + """ + Instantiate an object of a derived class using the information + in input_dict (built by the to_dict method of the derived class). + More specifically, after reading the derived class from input_dict, + it calls the method _build_from_input_dict of the derived class. + Note: This method should not be overrided in the derived class. In case + it is needed, please override _build_from_input_dict instate. + + :param dict input_dict: Dictionary with all the information needed to + instantiate the object. + """ + import copy input_dict = copy.deepcopy(input_dict) likelihood_class = input_dict.pop('class') @@ -64,10 +76,10 @@ def from_dict(input_dict): name = input_dict.pop('name') import GPy likelihood_class = eval(likelihood_class) - return likelihood_class._from_dict(likelihood_class, input_dict) + return likelihood_class._build_from_input_dict(likelihood_class, input_dict) @staticmethod - def _from_dict(likelihood_class, input_dict): + def _build_from_input_dict(likelihood_class, input_dict): import copy input_dict = copy.deepcopy(input_dict) gp_link_dict = input_dict.pop('gp_link_dict') diff --git a/GPy/likelihoods/link_functions.py b/GPy/likelihoods/link_functions.py index d5fc785f7..0eb05e744 100644 --- a/GPy/likelihoods/link_functions.py +++ b/GPy/likelihoods/link_functions.py @@ -46,20 +46,32 @@ def d3transf_df3(self,f): def to_dict(self): raise NotImplementedError - def _to_dict(self): + def _save_to_input_dict(self): return {} @staticmethod def from_dict(input_dict): + """ + Instantiate an object of a derived class using the information + in input_dict (built by the to_dict method of the derived class). + More specifically, after reading the derived class from input_dict, + it calls the method _build_from_input_dict of the derived class. + Note: This method should not be overrided in the derived class. In case + it is needed, please override _build_from_input_dict instate. + + :param dict input_dict: Dictionary with all the information needed to + instantiate the object. + """ + import copy input_dict = copy.deepcopy(input_dict) link_class = input_dict.pop('class') import GPy link_class = eval(link_class) - return link_class._from_dict(link_class, input_dict) + return link_class._build_from_input_dict(link_class, input_dict) @staticmethod - def _from_dict(link_class, input_dict): + def _build_from_input_dict(link_class, input_dict): return link_class(**input_dict) class Identity(GPTransformation): @@ -82,7 +94,15 @@ def d3transf_df3(self,f): return np.zeros_like(f) def to_dict(self): - input_dict = super(Identity, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(Identity, self)._save_to_input_dict() input_dict["class"] = "GPy.likelihoods.link_functions.Identity" return input_dict @@ -106,7 +126,15 @@ def d3transf_df3(self,f): return (safe_square(f)-1.)*std_norm_pdf(f) def to_dict(self): - input_dict = super(Probit, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(Probit, self)._save_to_input_dict() input_dict["class"] = "GPy.likelihoods.link_functions.Probit" return input_dict diff --git a/GPy/mappings/constant.py b/GPy/mappings/constant.py index 24c632c9b..315b47b77 100644 --- a/GPy/mappings/constant.py +++ b/GPy/mappings/constant.py @@ -40,7 +40,14 @@ def gradients_X(self, dL_dF, X): return np.zeros_like(X) def to_dict(self): - input_dict = super(Constant, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + input_dict = super(Constant, self)._save_to_input_dict() input_dict["class"] = "GPy.mappings.Constant" input_dict["value"] = self.C.values[0] return input_dict diff --git a/GPy/mappings/identity.py b/GPy/mappings/identity.py index 261d918ff..3567b6949 100644 --- a/GPy/mappings/identity.py +++ b/GPy/mappings/identity.py @@ -20,6 +20,13 @@ def gradients_X(self, dL_dF, X): return dL_dF def to_dict(self): - input_dict = super(Identity, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + input_dict = super(Identity, self)._save_to_input_dict() input_dict["class"] = "GPy.mappings.Identity" return input_dict diff --git a/GPy/mappings/linear.py b/GPy/mappings/linear.py index e348d4581..82b7a0e05 100644 --- a/GPy/mappings/linear.py +++ b/GPy/mappings/linear.py @@ -39,13 +39,21 @@ def gradients_X(self, dL_dF, X): return np.dot(dL_dF, self.A.T) def to_dict(self): - input_dict = super(Linear, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(Linear, self)._save_to_input_dict() input_dict["class"] = "GPy.mappings.Linear" input_dict["A"] = self.A.values.tolist() return input_dict @staticmethod - def _from_dict(mapping_class, input_dict): + def _build_from_input_dict(mapping_class, input_dict): import copy input_dict = copy.deepcopy(input_dict) A = np.array(input_dict.pop('A')) diff --git a/GPy/models/sparse_gp_classification.py b/GPy/models/sparse_gp_classification.py index 7a86e1d5a..0e44966a8 100644 --- a/GPy/models/sparse_gp_classification.py +++ b/GPy/models/sparse_gp_classification.py @@ -48,17 +48,41 @@ def from_sparse_gp(sparse_gp): SparseGPClassification(sparse_gp.X, sparse_gp.Y, sparse_gp.Z, sparse_gp.kern, sparse_gp.likelihood, sparse_gp.inference_method, sparse_gp.mean_function, name='sparse_gp_classification') def to_dict(self, save_data=True): + """ + Store the object into a json serializable dictionary + + :param boolean save_data: if true, it adds the data self.X and self.Y to the dictionary + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ model_dict = super(SparseGPClassification,self).to_dict(save_data) model_dict["class"] = "GPy.models.SparseGPClassification" return model_dict @staticmethod def from_dict(input_dict, data=None): + """ + Instantiate an SparseGPClassification object using the information + in input_dict (built by the to_dict method). + + :param data: It is used to provide X and Y for the case when the model + was saved using save_data=False in to_dict method. + :type data: tuple(:class:`np.ndarray`, :class:`np.ndarray`) + """ import GPy m = GPy.core.model.Model.from_dict(input_dict, data) - return GPClassification.from_sparse_gp(m) + from copy import deepcopy + sparse_gp = deepcopy(m) + return SparseGPClassification(sparse_gp.X, sparse_gp.Y, sparse_gp.Z, sparse_gp.kern, sparse_gp.likelihood, sparse_gp.inference_method, sparse_gp.mean_function, name='sparse_gp_classification') def save_model(self, output_filename, compress=True, save_data=True): + """ + Method to serialize the model. + + :param string output_filename: Output file + :param boolean compress: If true compress the file using zip + :param boolean save_data: if true, it serializes the training data + (self.X and self.Y) + """ self._save_model(output_filename, compress=True, save_data=True) diff --git a/GPy/util/normalizer.py b/GPy/util/normalizer.py index 7a3ee0208..2e6d991ae 100644 --- a/GPy/util/normalizer.py +++ b/GPy/util/normalizer.py @@ -52,21 +52,33 @@ def scaled(self): def to_dict(self): raise NotImplementedError - def _to_dict(self): + def _save_to_input_dict(self): input_dict = {} return input_dict @staticmethod def from_dict(input_dict): + """ + Instantiate an object of a derived class using the information + in input_dict (built by the to_dict method of the derived class). + More specifically, after reading the derived class from input_dict, + it calls the method _build_from_input_dict of the derived class. + Note: This method should not be overrided in the derived class. In case + it is needed, please override _build_from_input_dict instate. + + :param dict input_dict: Dictionary with all the information needed to + instantiate the object. + """ + import copy input_dict = copy.deepcopy(input_dict) normalizer_class = input_dict.pop('class') import GPy normalizer_class = eval(normalizer_class) - return normalizer_class._from_dict(normalizer_class, input_dict) + return normalizer_class._build_from_input_dict(normalizer_class, input_dict) @staticmethod - def _from_dict(normalizer_class, input_dict): + def _build_from_input_dict(normalizer_class, input_dict): return normalizer_class(**input_dict) @@ -96,7 +108,15 @@ def scaled(self): return self.mean is not None def to_dict(self): - input_dict = super(Standardize, self)._to_dict() + """ + Convert the object into a json serializable dictionary. + + Note: It uses the private method _save_to_input_dict of the parent. + + :return dict: json serializable dictionary containing the needed information to instantiate the object + """ + + input_dict = super(Standardize, self)._save_to_input_dict() input_dict["class"] = "GPy.util.normalizer.Standardize" if self.mean is not None: input_dict["mean"] = self.mean.tolist() @@ -104,7 +124,7 @@ def to_dict(self): return input_dict @staticmethod - def _from_dict(kernel_class, input_dict): + def _build_from_input_dict(kernel_class, input_dict): s = Standardize() if "mean" in input_dict: s.mean = np.array(input_dict["mean"]) From 292e69ee0d06cba865deaaf7742b13e6c2d88808 Mon Sep 17 00:00:00 2001 From: Eero Siivola Date: Sun, 24 Jun 2018 12:41:00 +0300 Subject: [PATCH 25/48] Added a notice of the correspondence of the likelihood structure to the one of GPstuff due to their request --- GPy/likelihoods/multioutput_likelihood.py | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/GPy/likelihoods/multioutput_likelihood.py b/GPy/likelihoods/multioutput_likelihood.py index 7b201d600..2b4075719 100644 --- a/GPy/likelihoods/multioutput_likelihood.py +++ b/GPy/likelihoods/multioutput_likelihood.py @@ -1,5 +1,9 @@ # Copyright (c) 2012-2014 The GPy authors (see AUTHORS.txt) # Licensed under the BSD 3-clause license (see LICENSE.txt) +# Multioutput likelihood structure is similar to the +# corresponding structure in GPstuff. If building complex +# multioutput models on top of this class and need a reference, +# check GPstuff project. import numpy as np from scipy import stats, special From 8e69db51a290eb0335dd433f639ebbd557b44a71 Mon Sep 17 00:00:00 2001 From: Eero Siivola Date: Sun, 24 Jun 2018 12:41:36 +0300 Subject: [PATCH 26/48] Modified likelihoods test to better test multioutput likelihood --- GPy/testing/likelihood_tests.py | 17 +++++++++++++---- 1 file changed, 13 insertions(+), 4 deletions(-) diff --git a/GPy/testing/likelihood_tests.py b/GPy/testing/likelihood_tests.py index 2c1a6e245..c665d6ab2 100644 --- a/GPy/testing/likelihood_tests.py +++ b/GPy/testing/likelihood_tests.py @@ -129,6 +129,15 @@ def setUp(self): self.Y_metadata = dict() self.Y_metadata['censored'] = censored self.Y_metadata['output_index'] = np.zeros((self.N,1), dtype=int) + self.Y_metadata2 = dict() + self.Y_metadata2['censored'] = censored + inds = np.zeros((self.N,1), dtype=int) + inds[5:10] = 1 + inds[10:] = 2 + self.Y_metadata2['output_index'] = inds + self.combY = self.Y + self.combY[10:] = np.where(self.binary_Y[10:] >0, self.binary_Y[10:], 0) + print(self.combY) #Make a bigger step as lower bound can be quite curved self.step = 1e-4 @@ -294,11 +303,11 @@ def setUp(self): "laplace": True }, "multioutput_default": { - "model": GPy.likelihoods.MultioutputLikelihood([GPy.likelihoods.Bernoulli()]), + "model": GPy.likelihoods.MultioutputLikelihood([GPy.likelihoods.Gaussian(), GPy.likelihoods.Poisson(), GPy.likelihoods.Bernoulli()]), "link_f_constraints": [partial(self.constrain_bounded, lower=0, upper=1)], "laplace": True, - "Y": self.binary_Y, - "Y_metadata": self.Y_metadata, + "Y": self.combY, + "Y_metadata": self.Y_metadata2, "ep": True, "variational_expectations": True, } @@ -627,7 +636,7 @@ def t_ep_fit_rbf_white(self, model, X, Y, f, Y_metadata, step, param_vals, param # Y = Y/Y.max() white_var = 1e-4 kernel = GPy.kern.RBF(X.shape[1]) + GPy.kern.White(X.shape[1]) - ep_inf = GPy.inference.latent_function_inference.EP() + ep_inf = GPy.inference.latent_function_inference.EP(always_reset=True) m = GPy.core.GP(X.copy(), Y.copy(), kernel=kernel, likelihood=model, Y_metadata=Y_metadata, inference_method=ep_inf) m['.*white'].constrain_fixed(white_var) From 8ef7706fe557924c721c572b1f766530b7fbf10b Mon Sep 17 00:00:00 2001 From: Mark Pullin Date: Mon, 2 Jul 2018 15:23:58 +0100 Subject: [PATCH 27/48] Add symmetric kernel --- GPy/kern/__init__.py | 1 + GPy/kern/src/symmetric.py | 137 ++++++++++++++++++++++++++++++++++++ GPy/testing/kernel_tests.py | 14 +++- 3 files changed, 151 insertions(+), 1 deletion(-) create mode 100644 GPy/kern/src/symmetric.py diff --git a/GPy/kern/__init__.py b/GPy/kern/__init__.py index 96abab394..1fedb3141 100644 --- a/GPy/kern/__init__.py +++ b/GPy/kern/__init__.py @@ -34,6 +34,7 @@ from .src.spline import Spline from .src.basis_funcs import LogisticBasisFuncKernel, LinearSlopeBasisFuncKernel, BasisFuncKernel, ChangePointBasisFuncKernel, DomainKernel, PolynomialBasisFuncKernel from .src.grid_kerns import GridRBF +from .src.symmetric import Symmetric from .src.sde_matern import sde_Matern32 from .src.sde_matern import sde_Matern52 diff --git a/GPy/kern/src/symmetric.py b/GPy/kern/src/symmetric.py new file mode 100644 index 000000000..3072b38c2 --- /dev/null +++ b/GPy/kern/src/symmetric.py @@ -0,0 +1,137 @@ +import numpy as np + +from .kern import Kern + + +class Symmetric(Kern): + """ + Symmetric kernel that models a function with even or odd symmetry: + + .. math:: + + f(x) = f(Ax) + + or + + .. math:: + + f(x) = -f(Ax) + + it does this by modelling: + + .. math:: + + f(x) = g(x) \pm g(Ax) + + with kernel + + .. math:: + + k(x, x') \pm k(Ax, x') \pm k(x, Ax') + k(Ax, Ax') + + where k(x, x') is the kernel of g(x) + """ + + def __init__(self, base_kernel, transform, symmetry_type): + + super().__init__(1, [0], name='symmetric_kernel') + if symmetry_type is 'odd': + self.symmetry_sign = -1. + elif symmetry_type is 'even': + self.symmetry_sign = 1. + else: + raise ValueError('symmetry_type input must be ''odd'' or ''even''') + self.transform = transform + self.base_kernel = base_kernel + self.param_names = base_kernel.parameter_names() + self.link_parameters(self.base_kernel) + + def K(self, X, X2): + X_sym = X.dot(self.transform) + + if X2 is None: + X2 = X + X2_sym = X_sym + else: + X2_sym = X2.dot(self.transform) + + cross_term_x_ax = self.symmetry_sign * self.base_kernel.K(X, X2_sym) + + if X2 is None: + cross_term_ax_x = cross_term_x_ax.T + else: + cross_term_ax_x = self.symmetry_sign * \ + self.base_kernel.K(X_sym, X2) + + return (self.base_kernel.K(X, X2) + cross_term_x_ax + cross_term_ax_x + + self.base_kernel.K(X_sym, X2_sym)) + + def Kdiag(self, X): + n_points = X.shape[0] + X_sym = X.dot(self.transform) + + # Evaluate cross terms in batches, taking the diag of a larger matrix + # is wasteful, but is more efficient than calling kernel.K for each data point + batch_size = 100 + n_batches = int(np.ceil(n_points / batch_size)) + cross_term = np.zeros(X.shape[0]) + for i in range(n_batches): + i_start = i * batch_size + i_end = np.min([(i + 1) * batch_size, n_points]) + cross_term[i_start:i_end] = np.diag(self.base_kernel.K( + X_sym[i_start:i_end, :], X[i_start:i_end, :])) + + return self.base_kernel.Kdiag(X) + 2 * self.symmetry_sign * cross_term + self.base_kernel.Kdiag(X_sym) + + def update_gradients_full(self, dL_dK, X, X2): + X_sym = X.dot(self.transform) + if X2 is None: + X2 = X + X2_sym = X2.dot(self.transform) + + # Get gradients from base kernel one term at a time + self.base_kernel.update_gradients_full(dL_dK, X_sym, X2) + gradient = self.symmetry_sign * self.base_kernel.gradient.copy() + + self.base_kernel.update_gradients_full(dL_dK, X, X2_sym) + gradient += self.symmetry_sign * self.base_kernel.gradient.copy() + + self.base_kernel.update_gradients_full(dL_dK, X_sym, X2_sym) + gradient += self.base_kernel.gradient.copy() + + self.base_kernel.update_gradients_full(dL_dK, X, X2) + gradient += self.base_kernel.gradient.copy() + + # Set gradients + self.base_kernel.gradient = gradient + + def update_gradients_diag(self, dL_dK, X): + + dL_dK_full = np.diag(dL_dK) + X_sym = X.dot(self.transform) + + self.base_kernel.update_gradients_diag(dL_dK, X_sym) + gradient = self.base_kernel.gradient.copy() + + self.base_kernel.update_gradients_diag(dL_dK, X) + gradient += self.base_kernel.gradient.copy() + + # The contribution from both cross terms is the same + self.base_kernel.update_gradients_full(dL_dK_full, X, X_sym) + gradient += 2 * self.symmetry_sign * self.base_kernel.gradient.copy() + + self.base_kernel.gradient = gradient + + def gradients_X(self, dL_dK, X, X2): + X_sym = X.dot(self.transform) + if X2 is None: + X2 = X + X2_sym = X.dot(self.transform) + dL_dK = dL_dK + dL_dK.T + else: + X2_sym = X2.dot(self.transform) + + return (self.base_kernel.gradients_X(dL_dK, X, X2) + + self.base_kernel.gradients_X(dL_dK, X_sym, X2_sym).dot(self.transform.T) + + self.symmetry_sign * self.base_kernel.gradients_X(dL_dK, X, X2_sym) + + self.symmetry_sign * self.base_kernel.gradients_X(dL_dK, X_sym, X2).dot(self.transform.T)) diff --git a/GPy/testing/kernel_tests.py b/GPy/testing/kernel_tests.py index e1c9d934f..02186c629 100644 --- a/GPy/testing/kernel_tests.py +++ b/GPy/testing/kernel_tests.py @@ -482,7 +482,19 @@ def test_standard_periodic(self): k = GPy.kern.StdPeriodic(self.D) k.randomize() self.assertTrue(check_kernel_gradient_functions(k, X=self.X, X2=self.X2, verbose=verbose)) - + + def test_symmetric_even(self): + k_base = GPy.kern.Linear(1) + GPy.kern.RBF(1) + transform = -np.array([[1.0]]) + k = GPy.kern.Symmetric(k_base, transform, 'even') + self.assertTrue(check_kernel_gradient_functions(k)) + + def test_symmetric_odd(self): + k_base = GPy.kern.Linear(1) + GPy.kern.RBF(1) + transform = -np.array([[1.0]]) + k = GPy.kern.Symmetric(k_base, transform, 'odd') + self.assertTrue(check_kernel_gradient_functions(k)) + def test_MultioutputKern(self): k1 = GPy.kern.RBF(self.D, ARD=True) k1.randomize() From 1a42cbd3426cebfac67935202621021c48b747b3 Mon Sep 17 00:00:00 2001 From: Mark Pullin Date: Mon, 2 Jul 2018 16:41:50 +0100 Subject: [PATCH 28/48] Add param descriptions --- GPy/kern/src/symmetric.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/GPy/kern/src/symmetric.py b/GPy/kern/src/symmetric.py index 3072b38c2..1577d6bd8 100644 --- a/GPy/kern/src/symmetric.py +++ b/GPy/kern/src/symmetric.py @@ -30,9 +30,13 @@ class Symmetric(Kern): k(x, x') \pm k(Ax, x') \pm k(x, Ax') + k(Ax, Ax') where k(x, x') is the kernel of g(x) + + :param base_kernel: kernel to make symmetric + :param transform: transformation matrix describing symmetry plane, A in equations above + :param symmetry_type: 'odd' or 'even' depending on the symmetry needed """ - def __init__(self, base_kernel, transform, symmetry_type): + def __init__(self, base_kernel, transform, symmetry_type='even'): super().__init__(1, [0], name='symmetric_kernel') if symmetry_type is 'odd': From 09c72eeec56e1cfd51c277050b7241fc757ef643 Mon Sep 17 00:00:00 2001 From: Mark Pullin Date: Mon, 2 Jul 2018 21:03:18 +0100 Subject: [PATCH 29/48] Make symmetric kernel work with python 2.7 --- GPy/kern/src/symmetric.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/GPy/kern/src/symmetric.py b/GPy/kern/src/symmetric.py index 1577d6bd8..85c0bc61b 100644 --- a/GPy/kern/src/symmetric.py +++ b/GPy/kern/src/symmetric.py @@ -38,7 +38,7 @@ class Symmetric(Kern): def __init__(self, base_kernel, transform, symmetry_type='even'): - super().__init__(1, [0], name='symmetric_kernel') + super(Symmetric, self).__init__(1, [0], name='symmetric_kernel') if symmetry_type is 'odd': self.symmetry_sign = -1. elif symmetry_type is 'even': @@ -77,7 +77,7 @@ def Kdiag(self, X): # Evaluate cross terms in batches, taking the diag of a larger matrix # is wasteful, but is more efficient than calling kernel.K for each data point batch_size = 100 - n_batches = int(np.ceil(n_points / batch_size)) + n_batches = int(np.ceil(n_points / float(batch_size))) cross_term = np.zeros(X.shape[0]) for i in range(n_batches): i_start = i * batch_size From 1cd860645131b52c86c7e61de78864213ebec7ae Mon Sep 17 00:00:00 2001 From: Mark Pullin Date: Thu, 19 Jul 2018 10:17:49 +0100 Subject: [PATCH 30/48] Expand class description and some speed improvements --- GPy/kern/src/symmetric.py | 45 ++++++++++++++++++++++++++++++++------- 1 file changed, 37 insertions(+), 8 deletions(-) diff --git a/GPy/kern/src/symmetric.py b/GPy/kern/src/symmetric.py index 85c0bc61b..c7207023e 100644 --- a/GPy/kern/src/symmetric.py +++ b/GPy/kern/src/symmetric.py @@ -7,11 +7,25 @@ class Symmetric(Kern): """ Symmetric kernel that models a function with even or odd symmetry: + For even symmetry we have: + .. math:: f(x) = f(Ax) - or + we then model the function as: + + .. math:: + + f(x) = g(x) + g(Ax) + + the corresponding kernel is: + + .. math:: + + k(x, x') + k(Ax, x') + k(x, Ax') + k(Ax, Ax') + + For odd symmetry we have: .. math:: @@ -21,13 +35,13 @@ class Symmetric(Kern): .. math:: - f(x) = g(x) \pm g(Ax) + f(x) = g(x) - g(Ax) with kernel .. math:: - k(x, x') \pm k(Ax, x') \pm k(x, Ax') + k(Ax, Ax') + k(x, x') - k(Ax, x') - k(x, Ax') + k(Ax, Ax') where k(x, x') is the kernel of g(x) @@ -37,8 +51,8 @@ class Symmetric(Kern): """ def __init__(self, base_kernel, transform, symmetry_type='even'): - - super(Symmetric, self).__init__(1, [0], name='symmetric_kernel') + n_dims = max(base_kernel.active_dims) + 1 + super(Symmetric, self).__init__(n_dims, list(range(n_dims)), name='symmetric_kernel') if symmetry_type is 'odd': self.symmetry_sign = -1. elif symmetry_type is 'even': @@ -114,15 +128,30 @@ def update_gradients_diag(self, dL_dK, X): dL_dK_full = np.diag(dL_dK) X_sym = X.dot(self.transform) + # Calculate gradient for k(Ax, Ax') self.base_kernel.update_gradients_diag(dL_dK, X_sym) gradient = self.base_kernel.gradient.copy() + # Calculate gradient for k(x, x') self.base_kernel.update_gradients_diag(dL_dK, X) gradient += self.base_kernel.gradient.copy() - # The contribution from both cross terms is the same - self.base_kernel.update_gradients_full(dL_dK_full, X, X_sym) - gradient += 2 * self.symmetry_sign * self.base_kernel.gradient.copy() + # Batch process cross term for speed + batch_size = 100 + n_points = dL_dK.shape[0] + n_batches = int(np.ceil(n_points / float(batch_size))) + gradient_part = np.zeros(gradient.shape) + for i in range(n_batches): + i_start = i * batch_size + i_end = np.min([(i + 1) * batch_size, n_points]) + dL_dK_part = dL_dK_full[i_start:i_end, i_start:i_end] + X_part = X[i_start:i_end, :] + X_sym_part = X_sym[i_start:i_end, :] + self.base_kernel.update_gradients_full( + dL_dK_part, X_part, X_sym_part) + gradient_part += self.base_kernel.gradient.copy() + + gradient += 2 * self.symmetry_sign * gradient_part self.base_kernel.gradient = gradient From eca580651864cd185cb72a68dec363e2514c0036 Mon Sep 17 00:00:00 2001 From: Keerthana Elango Date: Tue, 24 Jul 2018 10:46:33 +0100 Subject: [PATCH 31/48] Return deserialized models with actual type instead of base type --- GPy/core/gp.py | 9 ++++-- GPy/core/sparse_gp.py | 38 +++++--------------------- GPy/models/gp_classification.py | 21 ++++++++++++-- GPy/models/sparse_gp_classification.py | 22 ++++++++++++--- GPy/testing/serialization_tests.py | 4 +++ 5 files changed, 54 insertions(+), 40 deletions(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index ab7e8f9dd..ff3a22fae 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -144,14 +144,14 @@ def to_dict(self, save_data=True): return input_dict @staticmethod - def _build_from_input_dict(input_dict, data=None): + def _format_input_dict(input_dict, data=None): import GPy import numpy as np if (input_dict['X'] is None) or (input_dict['Y'] is None): assert(data is not None) input_dict["X"], input_dict["Y"] = np.array(data[0]), np.array(data[1]) elif data is not None: - print("WARNING: The model has been saved with X,Y! The original values are being overriden!") + warnings.warn("WARNING: The model has been saved with X,Y! The original values are being overridden!") input_dict["X"], input_dict["Y"] = np.array(data[0]), np.array(data[1]) else: input_dict["X"], input_dict["Y"] = np.array(input_dict['X']), np.array(input_dict['Y']) @@ -173,6 +173,11 @@ def _build_from_input_dict(input_dict, data=None): input_dict["normalizer"] = GPy.util.normalizer._Norm.from_dict(normalizer) else: input_dict["normalizer"] = normalizer + return input_dict + + @staticmethod + def _build_from_input_dict(input_dict, data=None): + input_dict = GP._format_input_dict(input_dict, data) return GP(**input_dict) def save_model(self, output_filename, compress=True, save_data=True): diff --git a/GPy/core/sparse_gp.py b/GPy/core/sparse_gp.py index eb3650af5..d9439d286 100644 --- a/GPy/core/sparse_gp.py +++ b/GPy/core/sparse_gp.py @@ -131,36 +131,12 @@ def to_dict(self, save_data=True): return input_dict @staticmethod - def _build_from_input_dict(input_dict, data=None): - # Called from the from_dict method. - import GPy - if (input_dict['X'] is None) or (input_dict['Y'] is None): - if data is None: - raise ValueError("The model was serialized whithout the training data. 'data' must be not None!") - input_dict["X"], input_dict["Y"] = np.array(data[0]), np.array(data[1]) - elif data is not None: - print("WARNING: The model has been saved with X,Y! The original values are being overriden!") - input_dict["X"], input_dict["Y"] = np.array(data[0]), np.array(data[1]) - else: - input_dict["X"], input_dict["Y"] = np.array(input_dict['X']), np.array(input_dict['Y']) - - input_dict["Z"] = np.array(input_dict['Z']) - input_dict["kernel"] = GPy.kern.Kern.from_dict(input_dict["kernel"]) - input_dict["likelihood"] = GPy.likelihoods.likelihood.Likelihood.from_dict(input_dict["likelihood"]) - mean_function = input_dict.get("mean_function") - if mean_function is not None: - input_dict["mean_function"] = GPy.core.mapping.Mapping.from_dict(mean_function) - else: - input_dict["mean_function"] = mean_function - input_dict["inference_method"] = GPy.inference.latent_function_inference.LatentFunctionInference.from_dict(input_dict["inference_method"]) - - #FIXME: Assumes the Y_metadata is serializable. We should create a Metadata class - Y_metadata = input_dict.get("Y_metadata") - input_dict["Y_metadata"] = Y_metadata + def _format_input_dict(input_dict, data=None): + input_dict = GP._format_input_dict(input_dict, data) + input_dict["Z"] = np.array(input_dict["Z"]) + return input_dict - normalizer = input_dict.get("normalizer") - if normalizer is not None: - input_dict["normalizer"] = GPy.util.normalizer._Norm.from_dict(normalizer) - else: - input_dict["normalizer"] = normalizer + @staticmethod + def _build_from_input_dict(input_dict, data=None): + input_dict = SparseGP._format_input_dict(input_dict, data) return SparseGP(**input_dict) diff --git a/GPy/models/gp_classification.py b/GPy/models/gp_classification.py index 702d2105f..8a68e74de 100644 --- a/GPy/models/gp_classification.py +++ b/GPy/models/gp_classification.py @@ -16,18 +16,27 @@ class GPClassification(GP): :param X: input observations :param Y: observed values, can be None if likelihood is not None :param kernel: a GPy kernel, defaults to rbf + :param likelihood: a GPy likelihood, defaults to Bernoulli + :param inference_method: Latent function inference to use, defaults to EP + :type inference_method: :class:`GPy.inference.latent_function_inference.LatentFunctionInference` .. Note:: Multiple independent outputs are allowed using columns of Y """ - def __init__(self, X, Y, kernel=None,Y_metadata=None, mean_function=None): + def __init__(self, X, Y, kernel=None,Y_metadata=None, mean_function=None, inference_method=None, + likelihood=None, normalizer=False): if kernel is None: kernel = kern.RBF(X.shape[1]) - likelihood = likelihoods.Bernoulli() + if likelihood is None: + likelihood = likelihoods.Bernoulli() - GP.__init__(self, X=X, Y=Y, kernel=kernel, likelihood=likelihood, inference_method=EP(), mean_function=mean_function, name='gp_classification') + if inference_method is None: + inference_method = EP() + + GP.__init__(self, X=X, Y=Y, kernel=kernel, likelihood=likelihood, inference_method=inference_method, + mean_function=mean_function, name='gp_classification', normalizer=normalizer) @staticmethod def from_gp(gp): @@ -48,3 +57,9 @@ def from_dict(input_dict, data=None): def save_model(self, output_filename, compress=True, save_data=True): self._save_model(output_filename, compress=True, save_data=True) + + @staticmethod + def _build_from_input_dict(input_dict, data=None): + input_dict = GPClassification._format_input_dict(input_dict, data) + input_dict.pop('name', None) # Name parameter not required by GPClassification + return GPClassification(**input_dict) diff --git a/GPy/models/sparse_gp_classification.py b/GPy/models/sparse_gp_classification.py index 0e44966a8..296b70f41 100644 --- a/GPy/models/sparse_gp_classification.py +++ b/GPy/models/sparse_gp_classification.py @@ -17,8 +17,10 @@ class SparseGPClassification(SparseGP): :param X: input observations :param Y: observed values - :param likelihood: a GPy likelihood, defaults to Binomial with probit link_function + :param likelihood: a GPy likelihood, defaults to Bernoulli :param kernel: a GPy kernel, defaults to rbf+white + :param inference_method: Latent function inference to use, defaults to EPDTC + :type inference_method: :class:`GPy.inference.latent_function_inference.LatentFunctionInference` :param normalize_X: whether to normalize the input data before computing (predictions will be in original scales) :type normalize_X: False|True :param normalize_Y: whether to normalize the input data before computing (predictions will be in original scales) @@ -27,11 +29,13 @@ class SparseGPClassification(SparseGP): """ - def __init__(self, X, Y=None, likelihood=None, kernel=None, Z=None, num_inducing=10, Y_metadata=None): + def __init__(self, X, Y=None, likelihood=None, kernel=None, Z=None, num_inducing=10, Y_metadata=None, + mean_function=None, inference_method=None, normalizer=False): if kernel is None: kernel = kern.RBF(X.shape[1]) - likelihood = likelihoods.Bernoulli() + if likelihood is None: + likelihood = likelihoods.Bernoulli() if Z is None: i = np.random.permutation(X.shape[0])[:num_inducing] @@ -39,7 +43,11 @@ def __init__(self, X, Y=None, likelihood=None, kernel=None, Z=None, num_inducing else: assert Z.shape[1] == X.shape[1] - SparseGP.__init__(self, X, Y, Z, kernel, likelihood, inference_method=EPDTC(), name='SparseGPClassification',Y_metadata=Y_metadata) + if inference_method is None: + inference_method = EPDTC() + + SparseGP.__init__(self, X, Y, Z, kernel, likelihood, mean_function=mean_function, inference_method=inference_method, + normalizer=normalizer, name='SparseGPClassification', Y_metadata=Y_metadata) @staticmethod def from_sparse_gp(sparse_gp): @@ -58,6 +66,12 @@ def to_dict(self, save_data=True): model_dict["class"] = "GPy.models.SparseGPClassification" return model_dict + @staticmethod + def _build_from_input_dict(input_dict, data=None): + input_dict = SparseGPClassification._format_input_dict(input_dict, data) + input_dict.pop('name', None) # Name parameter not required by SparseGPClassification + return SparseGPClassification(**input_dict) + @staticmethod def from_dict(input_dict, data=None): """ diff --git a/GPy/testing/serialization_tests.py b/GPy/testing/serialization_tests.py index 57781bf32..d147d59c7 100644 --- a/GPy/testing/serialization_tests.py +++ b/GPy/testing/serialization_tests.py @@ -237,7 +237,9 @@ def test_serialize_deserialize_GPClassification(self): m.save_model("temp_test_gp_classifier_with_data.json", compress=True, save_data=True) m.save_model("temp_test_gp_classifier_without_data.json", compress=True, save_data=False) m1_r = GPy.models.GPClassification.load_model("temp_test_gp_classifier_with_data.json.zip") + self.assertTrue(type(m) == type(m1_r), "Incorrect model type. Expected: {} Actual: {}".format(type(m), type(m1_r))) m2_r = GPy.models.GPClassification.load_model("temp_test_gp_classifier_without_data.json.zip", (X,Y)) + self.assertTrue(type(m) == type(m2_r), "Incorrect model type. Expected: {} Actual: {}".format(type(m), type(m2_r))) os.remove("temp_test_gp_classifier_with_data.json.zip") os.remove("temp_test_gp_classifier_without_data.json.zip") @@ -259,7 +261,9 @@ def test_serialize_deserialize_SparseGPClassification(self): m.save_model("temp_test_sparse_gp_classifier_with_data.json", compress=True, save_data=True) m.save_model("temp_test_sparse_gp_classifier_without_data.json", compress=True, save_data=False) m1_r = GPy.models.SparseGPClassification.load_model("temp_test_sparse_gp_classifier_with_data.json.zip") + self.assertTrue(type(m) == type(m1_r), "Incorrect model type. Expected: {} Actual: {}".format(type(m), type(m1_r))) m2_r = GPy.models.SparseGPClassification.load_model("temp_test_sparse_gp_classifier_without_data.json.zip", (X,Y)) + self.assertTrue(type(m) == type(m2_r), "Incorrect model type. Expected: {} Actual: {}".format(type(m), type(m2_r))) os.remove("temp_test_sparse_gp_classifier_with_data.json.zip") os.remove("temp_test_sparse_gp_classifier_without_data.json.zip") From 2ca138ea68f160db5fc9a8687a08df03ad5dd74c Mon Sep 17 00:00:00 2001 From: David Sheldon Date: Tue, 24 Jul 2018 15:43:29 +0100 Subject: [PATCH 32/48] Allow setup.py to be parsed without numpy If numpy isn't available, don't define ext_mods, pip will then determine numpy is required, install it, then call us again. Fixes #653 --- setup.py | 60 +++++++++++++++++++++++++++++++------------------------- 1 file changed, 33 insertions(+), 27 deletions(-) diff --git a/setup.py b/setup.py index 5e4357b51..ab7e85a0b 100644 --- a/setup.py +++ b/setup.py @@ -38,7 +38,6 @@ import os import sys from setuptools import setup, Extension -import numpy as np import codecs def read(fname): @@ -80,32 +79,39 @@ def ismac(): compile_flags = [ '-fopenmp', '-O3'] link_args = ['-lgomp' ] -ext_mods = [Extension(name='GPy.kern.src.stationary_cython', - sources=['GPy/kern/src/stationary_cython.c', - 'GPy/kern/src/stationary_utils.c'], - include_dirs=[np.get_include(),'.'], - extra_compile_args=compile_flags, - extra_link_args = link_args), - Extension(name='GPy.util.choleskies_cython', - sources=['GPy/util/choleskies_cython.c'], - include_dirs=[np.get_include(),'.'], - extra_link_args = link_args, - extra_compile_args=compile_flags), - Extension(name='GPy.util.linalg_cython', - sources=['GPy/util/linalg_cython.c'], - include_dirs=[np.get_include(),'.'], - extra_compile_args=compile_flags, - extra_link_args = link_args), - Extension(name='GPy.kern.src.coregionalize_cython', - sources=['GPy/kern/src/coregionalize_cython.c'], - include_dirs=[np.get_include(),'.'], - extra_compile_args=compile_flags, - extra_link_args = link_args), - Extension(name='GPy.models.state_space_cython', - sources=['GPy/models/state_space_cython.c'], - include_dirs=[np.get_include(),'.'], - extra_compile_args=compile_flags, - extra_link_args = link_args)] +try: + # So that we don't need numpy installed to determine it's a dependency. + import numpy as np + + ext_mods = [Extension(name='GPy.kern.src.stationary_cython', + sources=['GPy/kern/src/stationary_cython.c', + 'GPy/kern/src/stationary_utils.c'], + include_dirs=[np.get_include(), '.'], + extra_compile_args=compile_flags, + extra_link_args=link_args), + Extension(name='GPy.util.choleskies_cython', + sources=['GPy/util/choleskies_cython.c'], + include_dirs=[np.get_include(), '.'], + extra_link_args=link_args, + extra_compile_args=compile_flags), + Extension(name='GPy.util.linalg_cython', + sources=['GPy/util/linalg_cython.c'], + include_dirs=[np.get_include(), '.'], + extra_compile_args=compile_flags, + extra_link_args=link_args), + Extension(name='GPy.kern.src.coregionalize_cython', + sources=['GPy/kern/src/coregionalize_cython.c'], + include_dirs=[np.get_include(), '.'], + extra_compile_args=compile_flags, + extra_link_args=link_args), + Extension(name='GPy.models.state_space_cython', + sources=['GPy/models/state_space_cython.c'], + include_dirs=[np.get_include(), '.'], + extra_compile_args=compile_flags, + extra_link_args=link_args)] +except ModuleNotFoundError: + ext_mods = [] + setup(name = 'GPy', version = __version__, From fc6bf2b9f4015bb08537e5233e724055fc0f02a9 Mon Sep 17 00:00:00 2001 From: mzwiessele Date: Fri, 27 Jul 2018 14:48:52 +0200 Subject: [PATCH 33/48] fix: python=3.7 --- .travis.yml | 1 + appveyor.yml | 2 ++ 2 files changed, 3 insertions(+) diff --git a/.travis.yml b/.travis.yml index f526bd130..c40d73cb9 100644 --- a/.travis.yml +++ b/.travis.yml @@ -19,6 +19,7 @@ env: #- PYTHON_VERSION=3.4 - PYTHON_VERSION=3.5 - PYTHON_VERSION=3.6 + - PYTHON_VERSION=3.7 before_install: - wget https://github.com/mzwiessele/travis_scripts/raw/master/download_miniconda.sh diff --git a/appveyor.yml b/appveyor.yml index b736d6b46..bc002b55f 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -11,6 +11,8 @@ environment: MINICONDA: C:\Miniconda35-x64 - PYTHON_VERSION: 3.6 MINICONDA: C:\Miniconda36-x64 + - PYTHON_VERSION: 3.7 + MINICONDA: C:\Miniconda37-x64 #configuration: # - Debug From a190c3320b7fefd037b8af1d93ff02392f395126 Mon Sep 17 00:00:00 2001 From: mzwiessele Date: Fri, 27 Jul 2018 14:48:57 +0200 Subject: [PATCH 34/48] =?UTF-8?q?Bump=20version:=201.9.2=20=E2=86=92=201.9?= =?UTF-8?q?.3?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- GPy/__version__.py | 2 +- appveyor.yml | 2 +- setup.cfg | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/GPy/__version__.py b/GPy/__version__.py index 2cbc28c30..bdc0f1626 100644 --- a/GPy/__version__.py +++ b/GPy/__version__.py @@ -1 +1 @@ -__version__ = "1.9.2" +__version__ = "1.9.3" diff --git a/appveyor.yml b/appveyor.yml index bc002b55f..16b649c91 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -3,7 +3,7 @@ environment: secure: 8/ZjXFwtd1S7ixd7PJOpptupKKEDhm2da/q3unabJ00= COVERALLS_REPO_TOKEN: secure: d3Luic/ESkGaWnZrvWZTKrzO+xaVwJWaRCEP0F+K/9DQGPSRZsJ/Du5g3s4XF+tS - gpy_version: 1.9.2 + gpy_version: 1.9.3 matrix: - PYTHON_VERSION: 2.7 MINICONDA: C:\Miniconda-x64 diff --git a/setup.cfg b/setup.cfg index 0f1d4075a..47e46dcf2 100644 --- a/setup.cfg +++ b/setup.cfg @@ -1,5 +1,5 @@ [bumpversion] -current_version = 1.9.2 +current_version = 1.9.3 tag = True commit = True From ba7b5fb11a30d616ed210fab017541ff2c85edd6 Mon Sep 17 00:00:00 2001 From: mzwiessele Date: Fri, 27 Jul 2018 14:49:25 +0200 Subject: [PATCH 35/48] pkg: CHANGELOG --- CHANGELOG.md | 57 ++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 57 insertions(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index 46cb6f690..2815ae3cf 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,62 @@ # Changelog +## v1.9.3 (2018-07-27) + +### Fix + +* Python=3.7. [mzwiessele] + +### Other + +* Bump version: 1.9.2 → 1.9.3. [mzwiessele] + +* Merge pull request #655 from davidsmf/patch-2. [Zhenwen Dai] + + Allow setup.py to be parsed without numpy + +* Allow setup.py to be parsed without numpy. [David Sheldon] + + If numpy isn't available, don't define ext_mods, pip will then determine numpy is required, install it, then call us again. + + Fixes #653 + +* Merge pull request #640 from pgmoren/devel. [Zhenwen Dai] + + Sparse GP serialization + +* Serialization: Add docstrings. [Moreno] + +* Sparse GP serialization. [Moreno] + +* Merge pull request #613 from dtorrejo/Multi_sample_bug. [Max Zwiessele] + + Fixes the dimensions of the samples output + +* Maintains consistency with numpy arrays. [Diego Torrejon] + +* Fixes the dimensions of the samples output. [Diego Torrejon] + +* Merge pull request #607 from pgmoren/devel. [Zhenwen Dai] + + Add serialization functions for EPDTC + +* Add serialization functions for EPDTC. [Moreno] + +* Merge pull request #604 from SheffieldML/deploy. [Max Zwiessele] + + Deploy + +* Use old deploy pypi behavior. [Max Zwiessele] + + Until skip_existing option exists, use the old travis dpl behaviour to not fail on existing files. + +* Don’t build docs anymore in travis. [Max Zwiessele] + +* Merge pull request #603 from SheffieldML/devel. [Max Zwiessele] + + 1.9.* + + ## v1.9.2 (2018-02-22) ### Fix From d8db1b684743b3b7fc7860ec23881fa0042a3574 Mon Sep 17 00:00:00 2001 From: mzwiessele Date: Fri, 27 Jul 2018 15:30:33 +0200 Subject: [PATCH 36/48] fix: py37 cython not compatible --- .travis.yml | 2 +- appveyor.yml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/.travis.yml b/.travis.yml index c40d73cb9..3e8b9be50 100644 --- a/.travis.yml +++ b/.travis.yml @@ -19,7 +19,7 @@ env: #- PYTHON_VERSION=3.4 - PYTHON_VERSION=3.5 - PYTHON_VERSION=3.6 - - PYTHON_VERSION=3.7 + #- PYTHON_VERSION=3.7 before_install: - wget https://github.com/mzwiessele/travis_scripts/raw/master/download_miniconda.sh diff --git a/appveyor.yml b/appveyor.yml index 16b649c91..2d1aca22d 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -12,7 +12,7 @@ environment: - PYTHON_VERSION: 3.6 MINICONDA: C:\Miniconda36-x64 - PYTHON_VERSION: 3.7 - MINICONDA: C:\Miniconda37-x64 + MINICONDA: C:\Miniconda36-x64 #configuration: # - Debug From 4b998da73a009c04820430b0aef13ef3d39800aa Mon Sep 17 00:00:00 2001 From: robromijnders Date: Wed, 29 Aug 2018 18:30:42 +0200 Subject: [PATCH 37/48] fix typo in docstring for GP.opimize() --- GPy/core/gp.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index ff3a22fae..0cc01026f 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -655,7 +655,7 @@ def optimize(self, optimizer=None, start=None, messages=False, max_iters=1000, i :param max_iters: maximum number of function evaluations :type max_iters: int - :messages: whether to display during optimisation + :param messages: whether to display during optimisation :type messages: bool :param optimizer: which optimizer to use (defaults to self.preferred optimizer), a range of optimisers can be found in :module:`~GPy.inference.optimization`, they include 'scg', 'lbfgs', 'tnc'. :type optimizer: string From 8446da628b39ee952bf3ef3815feda387a40d947 Mon Sep 17 00:00:00 2001 From: mzwiessele Date: Sun, 2 Sep 2018 19:07:23 +0100 Subject: [PATCH 38/48] fix: samples tests and plotting, multioutput --- GPy/core/gp.py | 5 +++-- GPy/plotting/gpy_plot/gp_plots.py | 4 ++-- GPy/plotting/gpy_plot/plot_util.py | 11 ++++------- .../baseline/bayesian_gplvm_gradient.npz | Bin 7364 -> 10155 bytes .../baseline/bayesian_gplvm_inducing.npz | Bin 1318 -> 2233 bytes .../baseline/bayesian_gplvm_inducing_3d.npz | Bin 2944 -> 2693 bytes .../baseline/bayesian_gplvm_latent.npz | Bin 33041 -> 35834 bytes .../baseline/bayesian_gplvm_latent_3d.npz | Bin 10788 -> 10562 bytes .../baseline/bayesian_gplvm_magnification.npz | Bin 33854 -> 36631 bytes GPy/testing/baseline/coverage_3d_plot.npz | Bin 434 -> 4599 bytes .../baseline/coverage_annotation_interact.npz | Bin 26140 -> 434 bytes GPy/testing/baseline/coverage_gradient.npz | Bin 228 -> 7183 bytes .../baseline/coverage_imshow_interact.npz | Bin 26134 -> 228 bytes GPy/testing/baseline/gp_2d_data.npz | Bin 2727 -> 3031 bytes GPy/testing/baseline/gp_2d_in_error.npz | Bin 44226 -> 45614 bytes GPy/testing/baseline/gp_2d_inducing.npz | Bin 1319 -> 2233 bytes GPy/testing/baseline/gp_2d_mean.npz | Bin 74257 -> 84189 bytes GPy/testing/baseline/gp_3d_data.npz | Bin 5135 -> 4257 bytes GPy/testing/baseline/gp_3d_inducing.npz | Bin 3275 -> 2702 bytes GPy/testing/baseline/gp_3d_mean.npz | Bin 44684 -> 6672 bytes GPy/testing/baseline/gp_class_likelihood.npz | Bin 39919 -> 60052 bytes GPy/testing/baseline/gp_class_raw.npz | Bin 45084 -> 77997 bytes GPy/testing/baseline/gp_class_raw_link.npz | Bin 46053 -> 79655 bytes GPy/testing/baseline/gp_conf.npz | Bin 12472 -> 13172 bytes GPy/testing/baseline/gp_data.npz | Bin 1572 -> 2489 bytes GPy/testing/baseline/gp_density.npz | Bin 761022 -> 761982 bytes GPy/testing/baseline/gp_in_error.npz | Bin 22116 -> 22813 bytes GPy/testing/baseline/gp_mean.npz | Bin 10462 -> 10477 bytes GPy/testing/baseline/gp_out_error.npz | Bin 22160 -> 22855 bytes GPy/testing/baseline/gp_samples.npz | Bin 31437 -> 31471 bytes GPy/testing/baseline/gplvm_gradient.npz | Bin 7354 -> 10143 bytes GPy/testing/baseline/gplvm_latent.npz | Bin 33458 -> 36261 bytes GPy/testing/baseline/gplvm_latent_3d.npz | Bin 10793 -> 10562 bytes GPy/testing/baseline/gplvm_magnification.npz | Bin 33484 -> 36284 bytes GPy/testing/baseline/kern_ARD.npz | Bin 15212 -> 15212 bytes GPy/testing/baseline/kern_cov_1d.npz | Bin 8030 -> 8035 bytes GPy/testing/baseline/kern_cov_2d.npz | Bin 41779 -> 51553 bytes GPy/testing/baseline/kern_cov_3d.npz | Bin 43566 -> 5662 bytes GPy/testing/baseline/kern_cov_no_lim.npz | Bin 38473 -> 48223 bytes .../baseline/sparse_gp_class_likelihood.npz | Bin 19577 -> 22078 bytes GPy/testing/baseline/sparse_gp_class_raw.npz | Bin 55427 -> 55898 bytes .../baseline/sparse_gp_class_raw_link.npz | Bin 56242 -> 58743 bytes GPy/testing/baseline/sparse_gp_data_error.npz | Bin 23674 -> 25292 bytes GPy/testing/plotting_tests.py | 8 ++++---- appveyor.yml | 4 ++-- 45 files changed, 15 insertions(+), 17 deletions(-) diff --git a/GPy/core/gp.py b/GPy/core/gp.py index 977882ac7..1e2e36117 100644 --- a/GPy/core/gp.py +++ b/GPy/core/gp.py @@ -578,7 +578,7 @@ def predict_magnification(self, Xnew, kern=None, mean=True, covariance=True, dim mag[n] = np.sqrt(np.linalg.det(G[n, :, :])) return mag - def posterior_samples_f(self,X, size=10, **predict_kwargs): + def posterior_samples_f(self,X, size=10, **predict_kwargs): """ Samples the posterior GP at the points X. @@ -589,7 +589,8 @@ def posterior_samples_f(self,X, size=10, **predict_kwargs): :returns: set of simulations :rtype: np.ndarray (Nnew x D x samples) """ - m, v = self._raw_predict(X, full_cov=True, **predict_kwargs) + predict_kwargs["full_cov"] = True # Always use the full covariance for posterior samples. + m, v = self._raw_predict(X, **predict_kwargs) if self.normalizer is not None: m, v = self.normalizer.inverse_mean(m), self.normalizer.inverse_variance(v) diff --git a/GPy/plotting/gpy_plot/gp_plots.py b/GPy/plotting/gpy_plot/gp_plots.py index a12fc8583..202ccfe7e 100644 --- a/GPy/plotting/gpy_plot/gp_plots.py +++ b/GPy/plotting/gpy_plot/gp_plots.py @@ -208,10 +208,10 @@ def _plot_samples(self, canvas, helper_data, helper_prediction, projection, if len(free_dims)==1: # 1D plotting: update_not_existing_kwargs(kwargs, pl().defaults.samples_1d) # @UndefinedVariable - plots = [pl().plot(canvas, Xgrid[:, free_dims], samples[:, s], label=label if s==0 else None, **kwargs) for s in range(samples.shape[-1])] + plots = [pl().plot(canvas, Xgrid[:, free_dims], samples[:, :, s], label=label if s==0 else None, **kwargs) for s in range(samples.shape[-1])] elif len(free_dims)==2 and projection=='3d': update_not_existing_kwargs(kwargs, pl().defaults.samples_3d) # @UndefinedVariable - plots = [pl().surface(canvas, x, y, samples[:, s].reshape(resolution, resolution), **kwargs) for s in range(samples.shape[-1])] + plots = [pl().surface(canvas, x, y, samples[:, :, s].reshape(resolution, resolution), **kwargs) for s in range(samples.shape[-1])] else: pass # Nothing to plot! return dict(gpmean=plots) diff --git a/GPy/plotting/gpy_plot/plot_util.py b/GPy/plotting/gpy_plot/plot_util.py index 7bd1723ff..96a1db424 100644 --- a/GPy/plotting/gpy_plot/plot_util.py +++ b/GPy/plotting/gpy_plot/plot_util.py @@ -81,8 +81,8 @@ def helper_predict_with_model(self, Xgrid, plot_raw, apply_link, percentiles, wh else: percentiles = [] if samples > 0: - fsamples = self.posterior_samples(Xgrid, full_cov=True, size=samples, **predict_kw) - fsamples = fsamples[which_data_ycols] if fsamples.ndim == 3 else fsamples + fsamples = self.posterior_samples(Xgrid, size=samples, **predict_kw) + fsamples = fsamples[:, which_data_ycols, :] else: fsamples = None @@ -95,12 +95,9 @@ def helper_predict_with_model(self, Xgrid, plot_raw, apply_link, percentiles, wh retmu[:, [i]] = self.likelihood.gp_link.transf(mu[:, [i]]) for perc in percs: perc[:, [i]] = self.likelihood.gp_link.transf(perc[:, [i]]) - if fsamples is not None and fsamples.ndim == 3: + if fsamples is not None: for s in range(fsamples.shape[-1]): - fsamples[i, :, s] = self.likelihood.gp_link.transf(fsamples[i, :, s]) - elif fsamples is not None: - for s in range(fsamples.shape[-1]): - fsamples[:, s] = self.likelihood.gp_link.transf(fsamples[:, s]) + fsamples[:, i, s] = self.likelihood.gp_link.transf(fsamples[:, i, s]) return retmu, percs, fsamples def helper_for_plot_data(self, X, plot_limits, visible_dims, fixed_inputs, resolution): diff --git a/GPy/testing/baseline/bayesian_gplvm_gradient.npz b/GPy/testing/baseline/bayesian_gplvm_gradient.npz index 37c46b7a8d5eba83765407a6de948929ac8711d6..1aca64d4689b632977da19c35d320597301cd2b6 100644 GIT binary patch literal 10155 zcmd6sc|6qX+s7@LjD24+b|KlbWr>hvUqWaw7(0_CWXn$WJ!RjOrLxB%``*Z!$Szw5 zW#69B@7GcD9L{+<&pEHg>wYo+eCF+Yf9ASA_kF3zqn{x`K|#SpEP9kmK2G~X;vvn zj?ziIooSPmsuyjXTbPlW9H)O%Ehe5kML#AAi^xg7^MVpa5VoS9lokjOT*^^G^k^RHm|w#0@Q-EIr_o!&i6X!oev@<%K*h 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z);m}RW+5IIX34$|3{Ljp9VG|vj}n7@;C>`tSb9HFnOF44a~WV67OoIRAb) zvWyi`6dc^!f|VH69|w+ZbfVZ`^a^9&z+$7RB8m+z8qp44{)yWhJOIZVV;o>V3D#SG zAP$1)F{h{=2M(QU(1f ztb^xJ993%^S9C3`hpU!04jicwqrAZ`3C#N<7Miisg@S`i7BIN44vsgya-r}5!MY<1 zuJbP(IAdoDWsWX2^(dZ=1!t@{q2OSb8aC^|VL0aK3@(Zd){0RQbe#spM)zHMEaiSL*t8!}5Ria% zRQLqTN8`xSRaJ$T27JX}CH_|r2aeA9qe_5}FO2Ol28T^+qUf1H2j_cKuIUAvMpT?7 zfm1lJ&>Qt}d>OOws2E_?364a@8Q{Q?nJ*L?>}bNgA7P;xqvj|$IQ$78V%#S<-e@BV z#Rj{ZFmX#m95x>p<$x2mFnB2z+#1Im?8LyTd~bwfj?PJ=s(|HG7+YYB#YSo^C^jex zj9re$Mw(wJHfSlZh5ulJO(1{_*OE8+fZ=O24V1IEI4Br4Fv~dD_9jz>PHN7%xQw* z4~(rv{W~z&m^2=&_`}#4SZs7M3)KW{>BHE*Ryf|cBp$r<@L}p$NB{qGZfXHkmM)_p)YSeD7=FBe diff --git a/GPy/testing/plotting_tests.py b/GPy/testing/plotting_tests.py index a80ccf48a..b5ae00371 100644 --- a/GPy/testing/plotting_tests.py +++ b/GPy/testing/plotting_tests.py @@ -38,7 +38,7 @@ try: import matplotlib - matplotlib.use('agg') + # matplotlib.use('agg') except ImportError: # matplotlib not installed from nose import SkipTest @@ -367,13 +367,13 @@ def test_classification(): m = GPy.models.GPClassification(X, Y>Y.mean()) #m.optimize() _, ax = plt.subplots() - m.plot(plot_raw=False, apply_link=False, ax=ax) + m.plot(plot_raw=False, apply_link=False, ax=ax, samples=3) m.plot_errorbars_trainset(plot_raw=False, apply_link=False, ax=ax) _, ax = plt.subplots() - m.plot(plot_raw=True, apply_link=False, ax=ax) + m.plot(plot_raw=True, apply_link=False, ax=ax, samples=3) m.plot_errorbars_trainset(plot_raw=True, apply_link=False, ax=ax) _, ax = plt.subplots() - m.plot(plot_raw=True, apply_link=True, ax=ax) + m.plot(plot_raw=True, apply_link=True, ax=ax, samples=3) m.plot_errorbars_trainset(plot_raw=True, apply_link=True, ax=ax) for do_test in _image_comparison(baseline_images=['gp_class_{}'.format(sub) for sub in ["likelihood", "raw", 'raw_link']], extensions=extensions): yield (do_test, ) diff --git a/appveyor.yml b/appveyor.yml index 2d1aca22d..5a51d7825 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -11,8 +11,8 @@ environment: MINICONDA: C:\Miniconda35-x64 - PYTHON_VERSION: 3.6 MINICONDA: C:\Miniconda36-x64 - - PYTHON_VERSION: 3.7 - MINICONDA: C:\Miniconda36-x64 +# - PYTHON_VERSION: 3.7 +# MINICONDA: C:\Miniconda36-x64 #configuration: # - Debug From 36efd2dc0e9c10cb5cac9b5d684ff129274f1078 Mon Sep 17 00:00:00 2001 From: mzwiessele Date: Sun, 2 Sep 2018 19:11:18 +0100 Subject: [PATCH 39/48] add py37 --- .travis.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.travis.yml b/.travis.yml index 3e8b9be50..c40d73cb9 100644 --- a/.travis.yml +++ b/.travis.yml @@ -19,7 +19,7 @@ env: #- PYTHON_VERSION=3.4 - PYTHON_VERSION=3.5 - PYTHON_VERSION=3.6 - #- PYTHON_VERSION=3.7 + - PYTHON_VERSION=3.7 before_install: - wget https://github.com/mzwiessele/travis_scripts/raw/master/download_miniconda.sh From 9dbb1a945ab65102f40ae2b889bfb593c56900dd Mon Sep 17 00:00:00 2001 From: mzwiessele Date: Sun, 2 Sep 2018 19:17:52 +0100 Subject: [PATCH 40/48] add py37 --- appveyor.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/appveyor.yml b/appveyor.yml index 5a51d7825..2d1aca22d 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -11,8 +11,8 @@ environment: MINICONDA: C:\Miniconda35-x64 - PYTHON_VERSION: 3.6 MINICONDA: C:\Miniconda36-x64 -# - PYTHON_VERSION: 3.7 -# MINICONDA: C:\Miniconda36-x64 + - PYTHON_VERSION: 3.7 + MINICONDA: C:\Miniconda36-x64 #configuration: # - Debug From bf102e47e7a04fbd3f2cd5c05fed8f78cb363214 Mon Sep 17 00:00:00 2001 From: mzwiessele Date: Sun, 2 Sep 2018 19:34:21 +0100 Subject: [PATCH 41/48] fix: bdist_dumb and bdist_rpm --- .travis.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.travis.yml b/.travis.yml index c40d73cb9..038bab01b 100644 --- a/.travis.yml +++ b/.travis.yml @@ -52,7 +52,7 @@ after_success: before_deploy: - if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then - export DIST='sdist'; + export DIST='sdist bdist_rpm bdist_dumb'; elif [[ "$TRAVIS_OS_NAME" == "osx" ]]; then export DIST='bdist_wheel'; From 613265beb8271ee10c5e214bb0d53c8cc74e08cb Mon Sep 17 00:00:00 2001 From: mzwiessele Date: Sun, 2 Sep 2018 19:45:08 +0100 Subject: [PATCH 42/48] pkg: no py37 still does not work --- .travis.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.travis.yml b/.travis.yml index 038bab01b..c6d0a24c2 100644 --- a/.travis.yml +++ b/.travis.yml @@ -19,7 +19,7 @@ env: #- PYTHON_VERSION=3.4 - PYTHON_VERSION=3.5 - PYTHON_VERSION=3.6 - - PYTHON_VERSION=3.7 + #- PYTHON_VERSION=3.7 before_install: - wget https://github.com/mzwiessele/travis_scripts/raw/master/download_miniconda.sh From 141ceeb7fb4391b587db164641f134eb359c5da9 Mon Sep 17 00:00:00 2001 From: mzwiessele Date: Sun, 2 Sep 2018 21:15:10 +0100 Subject: [PATCH 43/48] pkg: merged and tested, no py37 --- appveyor.yml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/appveyor.yml b/appveyor.yml index 2d1aca22d..5a51d7825 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -11,8 +11,8 @@ environment: MINICONDA: C:\Miniconda35-x64 - PYTHON_VERSION: 3.6 MINICONDA: C:\Miniconda36-x64 - - PYTHON_VERSION: 3.7 - MINICONDA: C:\Miniconda36-x64 +# - PYTHON_VERSION: 3.7 +# MINICONDA: C:\Miniconda36-x64 #configuration: # - Debug From 1c101c9c36cabf92c6c4e892c4fd9a06a3cbbd8d Mon Sep 17 00:00:00 2001 From: mzwiessele Date: Sun, 2 Sep 2018 21:15:17 +0100 Subject: [PATCH 44/48] =?UTF-8?q?Bump=20version:=201.9.3=20=E2=86=92=201.9?= =?UTF-8?q?.4?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- GPy/__version__.py | 2 +- appveyor.yml | 2 +- setup.cfg | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/GPy/__version__.py b/GPy/__version__.py index bdc0f1626..844520399 100644 --- a/GPy/__version__.py +++ b/GPy/__version__.py @@ -1 +1 @@ -__version__ = "1.9.3" +__version__ = "1.9.4" diff --git a/appveyor.yml b/appveyor.yml index 5a51d7825..cf4f70968 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -3,7 +3,7 @@ environment: secure: 8/ZjXFwtd1S7ixd7PJOpptupKKEDhm2da/q3unabJ00= COVERALLS_REPO_TOKEN: secure: d3Luic/ESkGaWnZrvWZTKrzO+xaVwJWaRCEP0F+K/9DQGPSRZsJ/Du5g3s4XF+tS - gpy_version: 1.9.3 + gpy_version: 1.9.4 matrix: - PYTHON_VERSION: 2.7 MINICONDA: C:\Miniconda-x64 diff --git a/setup.cfg b/setup.cfg index 47e46dcf2..76f82425d 100644 --- a/setup.cfg +++ b/setup.cfg @@ -1,5 +1,5 @@ [bumpversion] -current_version = 1.9.3 +current_version = 1.9.4 tag = True commit = True From ed060a3c1afba749fed4c6b60d990348d5eb51dd Mon Sep 17 00:00:00 2001 From: mzwiessele Date: Sun, 2 Sep 2018 21:16:30 +0100 Subject: [PATCH 45/48] pkg: changelog --- CHANGELOG.md | 2036 ++++++++++++++++++++++++++------------------------ 1 file changed, 1061 insertions(+), 975 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 2815ae3cf..2428ddb12 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,5 +1,91 @@ # Changelog + +## v1.9.4 (2018-09-02) + +### Fix + +* Bdist_dumb and bdist_rpm. [mzwiessele] + +* Samples tests and plotting, multioutput. [mzwiessele] + +* Py37 cython not compatible. [mzwiessele] + +### Other + +* Bump version: 1.9.3 → 1.9.4. [mzwiessele] + +* Pkg: merged and tested, no py37. [mzwiessele] + +* Pkg: no py37 still does not work. [mzwiessele] + +* Add py37. [mzwiessele] + +* Add py37. [mzwiessele] + +* Merge branch 'cython-fix' of git://github.com/jayanthkoushik/GPy into jayanthkoushik-cython-fix. [mzwiessele] + +* Ensure numpy version is used in coregionalize cython test. [Jayanth Koushik] + +* Use explicity cython/numpy variants in coregionalize test. [Jayanth Koushik] + +* Fix cython check in linalg. [Jayanth Koushik] + +* Don't override global cython config in tests. [Jayanth Koushik] + +* Refactor checking for cython availability. [Jayanth Koushik] + +* Use correct cython check in kernel_tests.py. [Jayanth Koushik] + +* Merge branch 'devel' into esiivola-feature-multioutput. [mzwiessele] + +* Merge branch 'devel' into devel. [Neil Lawrence] + +* Rewrite poster_samples_f to return NxDxsize. [Neil Lawrence] + +* Testing for dims should be checking whether 2nd dim is greater than 1. [Neil Lawrence] + +* Update gp.py. [Neil Lawrence] + + Sample return seemed to have been based on number of training data, not number of posterior samples requested. + +* Merge pull request #668 from RobRomijnders/devel. [Zhenwen Dai] + + fix typo in docstring for GP.opimize() + +* Fix typo in docstring for GP.opimize() [robromijnders] + +* Merge pull request #648 from marpulli/symmetric_kernel. [Zhenwen Dai] + + Add Symmetric kernel + +* Expand class description and some speed improvements. [Mark Pullin] + +* Make symmetric kernel work with python 2.7. [Mark Pullin] + +* Add param descriptions. [Mark Pullin] + +* Add symmetric kernel. [Mark Pullin] + +* Merge pull request #654 from palindromik/devel. [Zhenwen Dai] + + Return deserialized models with actual type instead of base type + +* Return deserialized models with actual type instead of base type. [Keerthana Elango] + +* Merge branch 'feature-multioutput' of https://github.com/esiivola/GPy into esiivola-feature-multioutput. [mzwiessele] + +* Merge remote-tracking branch 'origin/devel' into feature-multioutput. [Eero Siivola] + +* Modified likelihoods test to better test multioutput likelihood. [Eero Siivola] + +* Added a notice of the correspondence of the likelihood structure to the one of GPstuff due to their request. [Eero Siivola] + +* Added a new class that enables using multiple likelihoods for multioutput case (previously, Mixed noise only allowed use of multiple gaussians) [Siivola Eero] + +* Pkg: CHANGELOG. [mzwiessele] + + ## v1.9.3 (2018-07-27) ### Fix @@ -16,7 +102,7 @@ * Allow setup.py to be parsed without numpy. [David Sheldon] - If numpy isn't available, don't define ext_mods, pip will then determine numpy is required, install it, then call us again. + If numpy isn't available, don't define ext_mods, pip will then determine numpy is required, install it, then call us again. Fixes #653 @@ -178,7 +264,7 @@ * update changelog for 1.8.5 - * bump the version: 1.8.4 -> 1.8.5 + * bump the version: 1.8.4 -> 1.8.5 ## v1.8.6 (2018-02-22) @@ -223,7 +309,7 @@ * Changed two function names so that they follow the python naming convention. [Siivola Eero] -* Merge remote-tracking branch 'origin' into feature-multioutput. [Eero Siivola] +* Merge remote-tracking branch 'origin' into feature-multioutput. [Eero Siivola] * Merge pull request #592 from SheffieldML/sparsegp-normalization. [Zhenwen Dai] @@ -237,9 +323,9 @@ * Implemented utility function to compute covariance between points in GP Model. [Andrei Paleyes] -* Changed the structure of multioutput kernel so that it doesn't change the API of Kernels + documented the class. [Eero Siivola] +* Changed the structure of multioutput kernel so that it doesn't change the API of Kernels + documented the class. [Eero Siivola] -* Merge remote-tracking branch 'origin/devel' into feature-multioutput. [Eero Siivola] +* Merge remote-tracking branch 'origin/devel' into feature-multioutput. [Eero Siivola] * Merge pull request #585 from YoshikawaMasashi/devel. [Zhenwen Dai] @@ -255,7 +341,7 @@ * Change dtype for Python 3 in robot_wirelss. [Neil Lawrence] -* Bump the version: 1.8.4 -> 1.8.5. [Zhenwen Dai] +* Bump the version: 1.8.4 -> 1.8.5. [Zhenwen Dai] * Update changelog for 1.8.5. [Zhenwen Dai] @@ -265,7 +351,7 @@ * Add type into docstring. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into multi_out_doc. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into multi_out_doc. [Zhenwen Dai] * Remove non-ascii characters. [Zhenwen Dai] @@ -351,7 +437,7 @@ appveyor twine upload error fix -* Merge branch 'deploy' into devel. [Max Zwiessele] +* Merge branch 'deploy' into devel. [Max Zwiessele] * Merge pull request #558 from SheffieldML/devel. [Max Zwiessele] @@ -372,9 +458,9 @@ * Update appveyor.yml. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] -* Merge branch 'deploy' into devel. [Max Zwiessele] +* Merge branch 'deploy' into devel. [Max Zwiessele] * Merge pull request #557 from SheffieldML/devel. [Max Zwiessele] @@ -451,13 +537,13 @@ * Input warping using Kumar warping. [Shen] -* Merge branch 'deploy' into devel. [Max Zwiessele] +* Merge branch 'deploy' into devel. [Max Zwiessele] -* Merge branch 'devel' into deploy. [mzwiessele] +* Merge branch 'devel' into deploy. [mzwiessele] -* Merge branch 'devel' into deploy. [mzwiessele] +* Merge branch 'devel' into deploy. [mzwiessele] -* Merge branch 'deploy' of github.com:SheffieldML/GPy into deploy. [mzwiessele] +* Merge branch 'deploy' of github.com:SheffieldML/GPy into deploy. [mzwiessele] * Merge pull request #497 from SheffieldML/devel. [Max Zwiessele] @@ -739,7 +825,7 @@ * Merge pull request #492 from pgmoren/devel. [Zhenwen Dai] - We did some benchmarking on classification. These changes should be fine. Let's merge it in. + We did some benchmarking on classification. These changes should be fine. Let's merge it in. * Changes in EP/EPDTC to fix numerical issues and increase the flexibility of the inference. [Moreno] @@ -802,11 +888,11 @@ * Bump version: 1.5.9 → 1.6.0. [mzwiessele] -* Merge branch 'devel' into alexfeld-offline_plotly. [mzwiessele] +* Merge branch 'devel' into alexfeld-offline_plotly. [mzwiessele] -* Merge branch 'devel' into alexfeld-offline_plotly. [mzwiessele] +* Merge branch 'devel' into alexfeld-offline_plotly. [mzwiessele] -* Merge branch 'offline_plotly' of git://github.com/alexfeld/GPy into alexfeld-offline_plotly. [mzwiessele] +* Merge branch 'offline_plotly' of git://github.com/alexfeld/GPy into alexfeld-offline_plotly. [mzwiessele] * Provide two classes for plotly plots to remove global variable. [Alex Feldstein] @@ -819,7 +905,7 @@ * Bump version: 1.5.8 → 1.5.9. [mzwiessele] -* Merge remote-tracking branch 'origin/deploy' into devel. [mzwiessele] +* Merge remote-tracking branch 'origin/deploy' into devel. [mzwiessele] * Merge pull request #455 from SheffieldML/devel. [Max Zwiessele] @@ -909,7 +995,7 @@ * Added pep.py -- Sparse Gaussian processes using Power Expectation Propagation. [Thang Bui] - This allows interpolation between FITC (EP or alpha = 1), and Titsias's variational (VarDTC, VFE when alpha = 0). + This allows interpolation between FITC (EP or alpha = 1), and Titsias's variational (VarDTC, VFE when alpha = 0). * Merge pull request #452 from SheffieldML/setupreq. [Max Zwiessele] @@ -919,7 +1005,7 @@ Polynomial -* Merge branch 'devel' into polinomial. [mzwiessele] +* Merge branch 'devel' into polinomial. [mzwiessele] * Merge pull request #449 from SheffieldML/deploy. [Max Zwiessele] @@ -931,9 +1017,9 @@ newest patch fixing some issues -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] -* Merge branch 'deploy' into devel. [Max Zwiessele] +* Merge branch 'deploy' into devel. [Max Zwiessele] * Merge pull request #442 from SheffieldML/devel. [Max Zwiessele] @@ -971,7 +1057,7 @@ fix: Bug in datasets.py -* Merge branch 'kurtCutajar-devel' into devel. [mzwiessele] +* Merge branch 'kurtCutajar-devel' into devel. [mzwiessele] ## v1.5.3 (2016-09-06) @@ -980,7 +1066,7 @@ * Bump version: 1.5.2 → 1.5.3. [mzwiessele] -* Merge branch 'devel' into kurtCutajar-devel. [mzwiessele] +* Merge branch 'devel' into kurtCutajar-devel. [mzwiessele] * [doc] cleanup. [mzwiessele] @@ -1032,7 +1118,7 @@ ### Fix -* What's new update fix #425 in changelog. [mzwiessele] +* What's new update fix #425 in changelog. [mzwiessele] ### Other @@ -1067,7 +1153,7 @@ * Bump version: 1.4.1 → 1.4.2. [mzwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] * [kern] fix #440. [mzwiessele] @@ -1086,17 +1172,17 @@ Binomial laplace #352 -* Merge branch 'devel' into binomial_laplace. [Max Zwiessele] +* Merge branch 'devel' into binomial_laplace. [Max Zwiessele] * Added binomial derivative and test. [Alan Saul] -* Merge branch 'devel' into fixed_inputs. [Alan Saul] +* Merge branch 'devel' into fixed_inputs. [Alan Saul] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Alan Saul] * Update README.md. [Max Zwiessele] -* Merge branch 'bwengals-devel' into devel. [Max Zwiessele] +* Merge branch 'bwengals-devel' into devel. [Max Zwiessele] * [basisfunc] kernel tests and model tests. [Max Zwiessele] @@ -1108,7 +1194,7 @@ * Removed Logsumexp() from LogisticBasisFuncKernel, allowing slope parameter to be negative. Also removed unnecessary scipy import. [Bill] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Merge pull request #433 from SheffieldML/update_initialize_paramz. [Max Zwiessele] @@ -1146,29 +1232,29 @@ * Bump version: 1.2.1 → 1.3.0. [mzwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] * Merge pull request #421 from SheffieldML/beckdaniel-wgps_improvements. [Max Zwiessele] Beckdaniel wgps improvements -* Merge branch 'devel' into beckdaniel-wgps_improvements. [mzwiessele] +* Merge branch 'devel' into beckdaniel-wgps_improvements. [mzwiessele] * [merge] devel. [mzwiessele] -* Revert "Revert "[kern] Add kernel was swallowing parts #fix #412"" [mzwiessele] +* Revert "Revert "[kern] Add kernel was swallowing parts #fix #412"" [mzwiessele] This reverts commit 0abb9b835ffeb020410bdf9a1e0532139ffa5cfc. -* Revert "[kern] Add kernel was swallowing parts #fix #412" [mzwiessele] +* Revert "[kern] Add kernel was swallowing parts #fix #412" [mzwiessele] This reverts commit b8867f1552c05244dcd5ba38a7a57b6f1056312c. * [kern] Add kernel was swallowing parts #fix #412. [mzwiessele] -* Merge branch 'devel' into beckdaniel-wgps_improvements. [mzwiessele] +* Merge branch 'devel' into beckdaniel-wgps_improvements. [mzwiessele] -* Merge branch 'wgps_improvements' of https://github.com/beckdaniel/GPy into beckdaniel-wgps_improvements. [mzwiessele] +* Merge branch 'wgps_improvements' of https://github.com/beckdaniel/GPy into beckdaniel-wgps_improvements. [mzwiessele] * Improving coverage and removing py2 print. [beckdaniel] @@ -1192,7 +1278,7 @@ * Moved cubic sine from tests to examples. [beckdaniel] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into wgps_improvements. [beckdaniel] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into wgps_improvements. [beckdaniel] Merging new devel @@ -1222,7 +1308,7 @@ * Stuff. [beckdaniel] -* Skipping the wgps Snelson's test (comment the skip line to see the plots) [beckdaniel] +* Skipping the wgps Snelson's test (comment the skip line to see the plots) [beckdaniel] * (wpgs) fixing newton-raphson for f_inv and fixing plotting stuff. [beckdaniel] @@ -1242,15 +1328,15 @@ Offset and clustering: Utility to do clustering (greedy, pairs best clusters until likelihood stops increasing). Also includes a model that has an offset parameter to allow aligning of time series. -* Removing 'threaded' version. [Michael T Smith] +* Removing 'threaded' version. [Michael T Smith] * Push just to rerun testing. [Michael T Smith] -* Don't use message added to cluster code. [Michael T Smith] +* Don't use message added to cluster code. [Michael T Smith] -* Added threaded option - but this doesn't work due to the global interpreter lock. [Ubuntu] +* Added threaded option - but this doesn't work due to the global interpreter lock. [Ubuntu] -* Made initial lengthscale!=1 to ensure we're properly testing gradients. [Michael T Smith] +* Made initial lengthscale!=1 to ensure we're properly testing gradients. [Michael T Smith] * Modified set code in test to work with python 2 and python 3. [Michael T Smith] @@ -1292,11 +1378,11 @@ * Coveralls token in appveyor.yml. [mzwiessele] -* Revert "Revert "[coverage reports] change to coveralls as test"" [mzwiessele] +* Revert "Revert "[coverage reports] change to coveralls as test"" [mzwiessele] This reverts commit ee23da6dd9405120bec62402abf7aaa228a87a19. -* Revert "[coverage reports] change to coveralls as test" [mzwiessele] +* Revert "[coverage reports] change to coveralls as test" [mzwiessele] This reverts commit 040ac72b82b6aa39720abe9817619103892b27a1. @@ -1314,7 +1400,7 @@ * [mean_func] added parameters in additive mean func and tests for mean functions. [mzwiessele] -* Merge branch 'devel' into plotting_tests. [mzwiessele] +* Merge branch 'devel' into plotting_tests. [mzwiessele] * [datasets] rnaseq changed up. [Max Zwiessele] @@ -1322,7 +1408,7 @@ * [testsave] saved the testmodel for quicker and more robust plotting. [Max Zwiessele] -* Merge branch 'devel' into plotting_tests. [Max Zwiessele] +* Merge branch 'devel' into plotting_tests. [Max Zwiessele] * [plotting] adjusting tests for quicker plotting. [Max Zwiessele] @@ -1348,9 +1434,9 @@ * Bump version: 1.1.1 → 1.1.2. [mzwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] -* Merge branch 'deploy' into devel. [Max Zwiessele] +* Merge branch 'deploy' into devel. [Max Zwiessele] * Merge pull request #402 from SheffieldML/devel. [Max Zwiessele] @@ -1482,7 +1568,7 @@ * Trying to be more specific. [Ricardo Andrade] -* Merge branch 'deploy' into devel. [Max Zwiessele] +* Merge branch 'deploy' into devel. [Max Zwiessele] * [py3] iterator .next fixes. [Max Zwiessele] @@ -1490,7 +1576,7 @@ * [#403] fix of inconsistent config naming. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Merge pull request #398 from SheffieldML/integral. [lionfish0] @@ -1500,11 +1586,11 @@ * References integral kernel classes. [Michael T Smith] -* Merge remote-tracking branch 'origin/devel' into integral. [Michael T Smith] +* Merge remote-tracking branch 'origin/devel' into integral. [Michael T Smith] * Merge pull request #397 from avehtari/dev-python3. [Alan Saul] - Python2->Python3 + Python2->Python3 * Merge pull request #4 from alansaul/dev-python3. [Aki Vehtari] @@ -1514,7 +1600,7 @@ * More Python 3 compatibility fixes. [Aki Vehtari] -* Python2->Python3. [Aki Vehtari] +* Python2->Python3. [Aki Vehtari] * Removed references to integral kernels from __init__ [Michael T Smith] @@ -1544,7 +1630,7 @@ * [gradsxx] putting tests in, not complete yet! [Max Zwiessele] -* Merge branch 'devel' into gradientsxx. [Max Zwiessele] +* Merge branch 'devel' into gradientsxx. [Max Zwiessele] * Merged __init__ [Michael T Smith] @@ -1552,7 +1638,7 @@ * Add eq_ode1 kern and ibp_lfm model. [cdguarnizo] -* Integral kernels added, these allow 'histogram' or 'binned' data to be modelled. [Michael T Smith] +* Integral kernels added, these allow 'histogram' or 'binned' data to be modelled. [Michael T Smith] * Fixed bug, replaced for loops with einsum. [alessandratosi] @@ -1562,7 +1648,7 @@ * Fixed gradients_XX_diag. [alessandratosi] -* Merge branch 'gradientsxx' of github.com:SheffieldML/GPy into gradientsxx. [Max Zwiessele] +* Merge branch 'gradientsxx' of github.com:SheffieldML/GPy into gradientsxx. [Max Zwiessele] * Fixed covariance computation in predict_jacobian. [alessandratosi] @@ -1576,13 +1662,13 @@ * [slicing] fixed slicing for second order derivatives. [mzwiessele] -* Merge branch 'devel' into gradientsxx. [mzwiessele] +* Merge branch 'devel' into gradientsxx. [mzwiessele] * Bug fix. [alessandratosi] * Syntax fix. [alessandratosi] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into gradientsxx. [alessandratosi] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into gradientsxx. [alessandratosi] * Modified kernel tests for gradients_XX. [alessandratosi] @@ -1612,7 +1698,7 @@ * [fix #380] reloading ep. [mzwiessele] -* Merge branch 'devel' into kenokabe-devel. [mzwiessele] +* Merge branch 'devel' into kenokabe-devel. [mzwiessele] * [statespace] omg. [mzwiessele] @@ -1620,7 +1706,7 @@ * [open] backwards compatibility. [mzwiessele] -* Merge branch 'devel' of git://github.com/kenokabe/GPy into kenokabe-devel. [mzwiessele] +* Merge branch 'devel' of git://github.com/kenokabe/GPy into kenokabe-devel. [mzwiessele] * Suppress UnicodeDecodeError: ascii codec - when import GPy. [kenokabe] @@ -1632,15 +1718,15 @@ * [static] added fixed tests. [Max Zwiessele] -* Merge branch 'devel' of git://github.com/vsaase/GPy into vsaase-devel. [Max Zwiessele] +* Merge branch 'devel' of git://github.com/vsaase/GPy into vsaase-devel. [Max Zwiessele] * Added precomputed kernel class. [vsaase] * [readme] added landscape for code cleanines. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'state_space' into devel. [mzwiessele] +* Merge branch 'state_space' into devel. [mzwiessele] * [setup] pypi restrictions. [mzwiessele] @@ -1669,7 +1755,7 @@ * Bump version: 1.0.6 → 1.0.7. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * [setup] readme in setup. [Max Zwiessele] @@ -1739,13 +1825,13 @@ * [exponential] fixed exponential *2 error. [mzwiessele] -* Merge branch 'AlexGrig-kalman_new' into state_space. [mzwiessele] +* Merge branch 'AlexGrig-kalman_new' into state_space. [mzwiessele] * FIX: Fixing bugs and innacuracies in state-space inference. [Alexander Grigorievskiy] -* Merge branch 'devel' into state_space. [mzwiessele] +* Merge branch 'devel' into state_space. [mzwiessele] -* Merge branch 'devel' into deploy. [Max Zwiessele] +* Merge branch 'devel' into deploy. [Max Zwiessele] * Bump version: 1.0.2 → 1.0.3. [Max Zwiessele] @@ -1803,15 +1889,15 @@ * Bump version: 0.9.8 → 1.0.0. [Max Zwiessele] -* Revert "Bump version: 0.9.8 → 1.0.0" [Max Zwiessele] +* Revert "Bump version: 0.9.8 → 1.0.0" [Max Zwiessele] This reverts commit b63af98f1fe86d9c065227e113c7da7f19163ad5. -* Revert "Revert "[predict] added noiseless convenience function to gp, bc of whining about it..."" [Max Zwiessele] +* Revert "Revert "[predict] added noiseless convenience function to gp, bc of whining about it..."" [Max Zwiessele] This reverts commit 7c95076b9fd8ad327ae46766b30cc9657883941e. -* Revert "[predict] added noiseless convenience function to gp, bc of whining about it..." [Max Zwiessele] +* Revert "[predict] added noiseless convenience function to gp, bc of whining about it..." [Max Zwiessele] This reverts commit 2001cd6dfd77300e1286245cf68897c17d3f0af0. @@ -1825,7 +1911,7 @@ * [release] calling release branch deploy. [Max Zwiessele] -* Merge branch 'jameshensman-master' into gpy_one_fixes. [Max Zwiessele] +* Merge branch 'jameshensman-master' into gpy_one_fixes. [Max Zwiessele] * Independent outputs kernel now works correctly for symmetrical arguments. [James Hensman] @@ -1837,9 +1923,9 @@ * Bump version: 0.9.7 → 0.9.8. [Max Zwiessele] -* Merge branch 'devel' into gpy_one_fixes. [Max Zwiessele] +* Merge branch 'devel' into gpy_one_fixes. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Merge pull request #261 from AlexGrig/kalman_new. [Max Zwiessele] @@ -1853,7 +1939,7 @@ * TEST: Rename parameters is test function. [Alexander Grigorievskiy] -* TEST: Tests use 'lbfgsb' optimization function. Also some syntactic changes. [Alexander Grigorievskiy] +* TEST: Tests use 'lbfgsb' optimization function. Also some syntactic changes. [Alexander Grigorievskiy] * FIX: Some fixes which prevented tests passing on python3.5. [Alexander Grigorievskiy] @@ -1863,7 +1949,7 @@ * FIX: Get rid of unused imports in state_space_model file. [Alexander Grigorievskiy] -* ENH: Copying sde kernels to the '/src' directory. [Alexander Grigorievskiy] +* ENH: Copying sde kernels to the '/src' directory. [Alexander Grigorievskiy] * TEST: Modifying tests so that their ruunig time is shorter. [Alexander Grigorievskiy] @@ -1889,9 +1975,9 @@ * ENH: Added templates for state-space kernels. [Alexander Grigorievskiy] - Those are childs of regular kernels with extra "sde" function. + Those are childs of regular kernels with extra "sde" function. -* FIX: Fixe bug with "expm" function in "state_space_new". Also some minor changes. [Alexander Grigorievskiy] +* FIX: Fixe bug with "expm" function in "state_space_new". Also some minor changes. [Alexander Grigorievskiy] Test function has been modified also. @@ -1974,9 +2060,9 @@ * Merge pull request #324 from AlexGrig/std_periodic_kernel. [Max Zwiessele] - [kern] Standard periodic kernel. Changes parameter name from 'waveleng… + [kern] Standard periodic kernel. Changes parameter name from 'waveleng… -* [kern] Standard periodic kernel. Changes paramter name from 'wavelenght' to 'period'. This seems to be more clear. Also some minor modifications in the same file. [Alexander Grigorievskiy] +* [kern] Standard periodic kernel. Changes paramter name from 'wavelenght' to 'period'. This seems to be more clear. Also some minor modifications in the same file. [Alexander Grigorievskiy] * Merge pull request #326 from SheffieldML/kern. [Max Zwiessele] @@ -2020,7 +2106,7 @@ [sparsegplvm] added sparsegplvm and tests for minibatch sparsegplvm -* Merge branch 'devel' into minibatch. [mzwiessele] +* Merge branch 'devel' into minibatch. [mzwiessele] * Merge pull request #321 from SheffieldML/limit=3. [Max Zwiessele] @@ -2072,13 +2158,13 @@ * Get rid of mpi4py import. [Zhenwen Dai] -* Merge remote-tracking branch 'upstream/devel' into devel. [Zhenwen Dai] +* Merge remote-tracking branch 'upstream/devel' into devel. [Zhenwen Dai] * Fix the issue of negative prediction variance of normal GP. [Zhenwen Dai] * Slvm gamma mean-field. [Zhenwen Dai] -* Merge remote-tracking branch 'upstream/devel' into devel. [Zhenwen Dai] +* Merge remote-tracking branch 'upstream/devel' into devel. [Zhenwen Dai] * Implement slvm. [Zhenwen Dai] @@ -2118,7 +2204,7 @@ * [matplotlib_dep] added the baseplots utility for backcompatibility. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * [plotting] limits added. [Max Zwiessele] @@ -2130,13 +2216,13 @@ * Bump version: 0.9.5 → 0.9.6. [Max Zwiessele] -* [plotting&kern] bugfixes in plotting and kernel size. [Max Zwiessele] +* [plotting&kern] bugfixes in plotting and kernel size. [Max Zwiessele] * Apidoc in conf. [Alan Saul] * Added paramz to requirement file for docs. [Alan Saul] -* [plotly] scatter plotting was defaulting to color='white' [Max Zwiessele] +* [plotly] scatter plotting was defaulting to color='white' [Max Zwiessele] * [vardtc] these two lines are overridden by the next two lines... [Max Zwiessele] @@ -2210,13 +2296,13 @@ * Documentation. [Alan Saul] -* Merge branch 'devel' into fixing_likelihoods. [Alan Saul] +* Merge branch 'devel' into fixing_likelihoods. [Alan Saul] * Bump version: 0.8.30 → 0.8.31. [Max Zwiessele] * [travis] register failes.. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Update .travis.yml. [Max Zwiessele] @@ -2230,7 +2316,7 @@ * Allow EP to have a auto reset option. [Alan Saul] -* Merge branch 'devel' into fixing_likelihoods. [Alan Saul] +* Merge branch 'devel' into fixing_likelihoods. [Alan Saul] * Bump version: 0.8.28 → 0.8.29. [mzwiessele] @@ -2360,7 +2446,7 @@ * [devel] pickling files... [mzwiessele] -* Merge branch 'devel' into paramz. [mzwiessele] +* Merge branch 'devel' into paramz. [mzwiessele] Conflicts: GPy/core/parameterization/parameter_core.py @@ -2368,7 +2454,7 @@ * [paramz] wrapping - todo: deprecation warnings. [mzwiessele] -* Merge branch 'devel' into paramz. [mzwiessele] +* Merge branch 'devel' into paramz. [mzwiessele] * [dir] structure preserved. [mzwiessele] @@ -2420,11 +2506,11 @@ * [pickling] have the pickling test against a model, which is now being shipped with the distro. [Max Zwiessele] -* Revert "[pickling] _src -> src" [Max Zwiessele] +* Revert "[pickling] _src -> src" [Max Zwiessele] This reverts commit 4cd16a86b48b03d4a6edd56a969242296ab66f4d. -* [pickling] _src -> src. [Max Zwiessele] +* [pickling] _src -> src. [Max Zwiessele] * [plotting] got the old way in again. [Max Zwiessele] @@ -2432,11 +2518,11 @@ * [travis] make more builds. [mzwiessele] -* Merge branch 'beckdaniel-warped_gps_fixes' into devel. [mzwiessele] +* Merge branch 'beckdaniel-warped_gps_fixes' into devel. [mzwiessele] * [beckdaniel] merge in warped gp changes. [mzwiessele] -* Merge remote-tracking branch 'ShefML/devel' into warped_gps_fixes. [beckdaniel] +* Merge remote-tracking branch 'ShefML/devel' into warped_gps_fixes. [beckdaniel] * Merged master. [beckdaniel] @@ -2448,7 +2534,7 @@ * Code cleaning on warping_functions. [beckdaniel] -* Added a new test which tries to replicate Snelson's toy 1D but NR seems to diverge... [beckdaniel] +* Added a new test which tries to replicate Snelson's toy 1D but NR seems to diverge... [beckdaniel] * Added initial test for warped gps using identity function. [beckdaniel] @@ -2656,19 +2742,19 @@ * [devel] merged. [mzwiessele] -* Merge branch 'devel' into plot_density. [mzwiessele] +* Merge branch 'devel' into plot_density. [mzwiessele] -* Revert "change the inverse lengthscale of rbf" [Zhenwen Dai] +* Revert "change the inverse lengthscale of rbf" [Zhenwen Dai] This reverts commit 326ed31fbfff2907bc92d2d444c74d5a24b22691. * Change the inverse lengthscale of rbf. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * A more efficient implementation of prediction with uncertain inputs. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Add original bfgs optimizer and add rbf with inverse lengthscale. [Zhenwen Dai] @@ -2778,7 +2864,7 @@ * [plotly] starting plotly. [mzwiessele] -* ['tests'] assert array equal. [mzwiessele] +* ['tests'] assert array equal. [mzwiessele] * [tests] now working? [mzwiessele] @@ -2918,15 +3004,15 @@ * [density] plot added. [mzwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] * Merge pull request #248 from SheffieldML/travis_testing. [Max Zwiessele] - Travis update to test Linux & MacOSX + Travis update to test Linux & MacOSX Python 2.7, 3.5 on Ubuntu and MacOSX -* Merge branch 'devel' into travis_testing. [mzwiessele] +* Merge branch 'devel' into travis_testing. [mzwiessele] * [copyrighting] and testing. [mzwiessele] @@ -2938,7 +3024,7 @@ * [codecov] added, trying to merge in readme from master. [mzwiessele] -* Merge branch 'devel' into travis_testing. [mzwiessele] +* Merge branch 'devel' into travis_testing. [mzwiessele] * [travis] testing codecoverage. [mzwiessele] @@ -3160,19 +3246,19 @@ * Added factorize_space function which returns a segmentation to shared and private dims. [Andreas] -* [plotting] py3 compatibility, is it right, that relative imports always have to be in the format from . import <.> [mzwiessele] +* [plotting] py3 compatibility, is it right, that relative imports always have to be in the format from . import <.> [mzwiessele] -* [plotting] py3 compatibility, is it right, that relative imports always have to be in the format from . import <.> [mzwiessele] +* [plotting] py3 compatibility, is it right, that relative imports always have to be in the format from . import <.> [mzwiessele] -* [plotting] py3 compatibility, is it right, that relative imports always have to be in the format from . import <.> [mzwiessele] +* [plotting] py3 compatibility, is it right, that relative imports always have to be in the format from . import <.> [mzwiessele] -* [plotting] py3 compatibility, is it right, that relative imports always have to be in the format from . import <.> [mzwiessele] +* [plotting] py3 compatibility, is it right, that relative imports always have to be in the format from . import <.> [mzwiessele] -* [plotting] py3 compatibility, is it right, that relative imports always have to be in the format from . import <.> [mzwiessele] +* [plotting] py3 compatibility, is it right, that relative imports always have to be in the format from . import <.> [mzwiessele] * [newest patch updates, cleaned interfaces and mean_function addidtions] [mzwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] * Fix xrange. [Zhenwen Dai] @@ -3180,7 +3266,7 @@ * Fixed bias+linear and bias+rbf with psi statistics. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Implement Gaussian quadrature psi-statistics for additive kernel. [Zhenwen Dai] @@ -3192,9 +3278,9 @@ * Remove the automatic importing mpi4py. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] -* Errobars_trainset -> plot_errorbars_trainset. [Ricardo] +* Errobars_trainset -> plot_errorbars_trainset. [Ricardo] * Bug fix for model_plots when specifying which_data_ycols. [Zhenwen Dai] @@ -3228,7 +3314,7 @@ * [scipy] deleted from mocking. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * More mocking for scipy, impossible to check without committing :( [Alan Saul] @@ -3242,7 +3328,7 @@ * Mocked scipy for docs. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Add adadelta as an optimizer. [Zhenwen Dai] @@ -3254,7 +3340,7 @@ * Merge pull request #246 from SheffieldML/travis2. [Max Zwiessele] - Dapid's travis changes + Dapid's travis changes * Update rv_transformation_tests.py. [Max Zwiessele] @@ -3284,7 +3370,7 @@ * Update .travis.yml. [Max Zwiessele] -* Dapid's travis changes. [Max Zwiessele] +* Dapid's travis changes. [Max Zwiessele] There was a conflict and I only had access to the web interface. @@ -3302,19 +3388,19 @@ * [classification] sparse gp classification and dtc update. [Max Zwiessele] -* Merge branch 'master' into devel. [Max Zwiessele] +* Merge branch 'master' into devel. [Max Zwiessele] -* Merge branch 'master' into devel. [Max Zwiessele] +* Merge branch 'master' into devel. [Max Zwiessele] -* Merge branch 'master' into devel. [Max Zwiessele] +* Merge branch 'master' into devel. [Max Zwiessele] -* Merge branch 'master' into devel. [Max Zwiessele] +* Merge branch 'master' into devel. [Max Zwiessele] -* Merge branch 'master' into devel. [Max Zwiessele] +* Merge branch 'master' into devel. [Max Zwiessele] -* Merge branch 'master' into devel. [Max Zwiessele] +* Merge branch 'master' into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Bug fix for set_XY. [Zhenwen Dai] @@ -3335,7 +3421,7 @@ * Bump version: 0.8.5 → 0.8.6. [Max Zwiessele] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Max Zwiessele] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Max Zwiessele] * Apply bug fix for set_XY. [Zhenwen Dai] @@ -3347,13 +3433,13 @@ Devel -* Merge branch 'master' into devel. [Max Zwiessele] +* Merge branch 'master' into devel. [Max Zwiessele] -* Merge branch 'master' into devel. [Max Zwiessele] +* Merge branch 'master' into devel. [Max Zwiessele] -* Merge branch 'master' into devel. [Max Zwiessele] +* Merge branch 'master' into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * Updated sampling and plots to be correct shape, and changed plotting of sampling to be posterior samples p(f*|f), like it used to be, and samples_y to plot samples of p(y*|y) [Alan Saul] @@ -3373,7 +3459,7 @@ * [plotting] no printing of warning unless you actually use plotting. [Max Zwiessele] -* [matplotlib] pylab -> pyplot. [Max Zwiessele] +* [matplotlib] pylab -> pyplot. [Max Zwiessele] * Bump version: 0.8.3 → 0.8.4. [Max Zwiessele] @@ -3399,7 +3485,7 @@ * Update setup.py. [Max Zwiessele] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Max Zwiessele] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Max Zwiessele] * Added universal wheels. [Mike Croucher] @@ -3429,7 +3515,7 @@ * [linalg] testing suite update. [Max Zwiessele] -* Merge branch 'master' into devel. [Max Zwiessele] +* Merge branch 'master' into devel. [Max Zwiessele] * Update setup.py with new version number. [mikecroucher] @@ -3441,21 +3527,21 @@ * Update AUTHORS.txt. [Neil Lawrence] -* Merge branch 'devel' [Max Zwiessele] +* Merge branch 'devel' [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Bug fix for compilation on Mac. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Removed annoying print. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Allowed gpyified var gauss. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Added full cov prediction. [Alan Saul] @@ -3489,13 +3575,13 @@ * Merge pull request #211 from PredictiveScienceLab/master. [Zhenwen Dai] - Fixes the PDF transformation bug by handpicking James Hensman's code from the devel branch + Fixes the PDF transformation bug by handpicking James Hensman's code from the devel branch * Removed dir ib_tests. [Ilias Bilionis] * PDF Transformation bug patched. [Ilias Bilionis] -* Handpicked James Hensman's code that ensures that fixes the PDF of transformed variables. Fixed minor plotting bug. [Ilias Bilionis] +* Handpicked James Hensman's code that ensures that fixes the PDF of transformed variables. Fixed minor plotting bug. [Ilias Bilionis] * Fixed MCMC sampler. [Ilias Bilionis] @@ -3527,7 +3613,7 @@ * [readthedocs] forcing readthedocs into not failing. [Max Zwiessele] -* Git Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Git Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Update README.md. [Max Zwiessele] @@ -3535,33 +3621,33 @@ * [testing] [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Fixed for Python 3. [Mike Croucher] * [doc] some changes to the doc, using mathjax some additions in math. [Max Zwiessele] -* Git pushMerge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Git pushMerge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * Optimize util for mpi. [Zhenwen Dai] * [licensing] replaced licensing with BSD, and erfcx. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Used scipy.log1p since it gives more consistent results cross-platform. [Mike Croucher] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Mike Croucher] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Mike Croucher] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * Changed gpu interface for mpi. [Zhenwen Dai] * Switched to scipy.special.log1p@ [Mike Croucher] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Mike Croucher] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Mike Croucher] * Used scipy.log1p since it gives more consistent results cross-platform. [Mike Croucher] @@ -3571,11 +3657,11 @@ * Python 3 fixes. [Mike Croucher] -* Git pushMerge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Git pushMerge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Mike Croucher] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Mike Croucher] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * Speed tuning for mlp kernel and gauss qudrature for psi-statistics. [Zhenwen Dai] @@ -3595,7 +3681,7 @@ * New implementation for mlp kernel (speed improvemd) [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * Merge pull request #227 from Dapid/clean_imports. [mikecroucher] @@ -3605,21 +3691,21 @@ * Unify the interface of psicomp, but the psi2n of linear kernel and gaussian qradrature still needs to be done. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * [MRD] fixed mrd for new structure. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * [empty space] literally : ) [Max Zwiessele] * [pickling] pickle error. [Max Zwiessele] -* Revert "[core] visited as propery" [Max Zwiessele] +* Revert "[core] visited as propery" [Max Zwiessele] This reverts commit a4ce1d473c13fa5cb577e4ff3dbdf76aa6a1a57f. -* Revert "[caching] different error" [Max Zwiessele] +* Revert "[caching] different error" [Max Zwiessele] This reverts commit f7087ebc9003a6950b58533e0ce373c03c82a4a2. @@ -3645,7 +3731,7 @@ * [coverage] added normalizer tests. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * [psi2] NxMxM fixes for the add kernel. [Max Zwiessele] @@ -3665,11 +3751,11 @@ * Reindented, did some profiling which looks promising. [Alan Saul] -* Merge branch 'devel' into missing_opt. [Alan Saul] +* Merge branch 'devel' into missing_opt. [Alan Saul] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Alan Saul] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Alan Saul] * Corrected caching for psi derivatives. [Alan Saul] @@ -3689,7 +3775,7 @@ * Optimizing missing data model, needs tidying but now much faster. [Alan Saul] -* Fixed array2string bug for N > 1000 default printing. [Alan Saul] +* Fixed array2string bug for N > 1000 default printing. [Alan Saul] * Merge pull request #224 from Dapid/fix_print. [mikecroucher] @@ -3697,17 +3783,17 @@ * FIX: missing compatibility Py2/3. [David Menéndez Hurtado] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] -* [add] renamed>sum. [Max Zwiessele] +* [add] renamed>sum. [Max Zwiessele] * [magnification] static corrections. [Max Zwiessele] * [magnification] added static kernel support and faster derivative computations. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * [magnification] plot_magnification expanded. [Max Zwiessele] @@ -3719,7 +3805,7 @@ * Shape of heteroscedastic variance corrected. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Merge pull request #219 from Dapid/fix_209. [mikecroucher] @@ -3737,13 +3823,13 @@ * [merge] [Max Zwiessele] -* Merge branch 'updates' into devel. [Max Zwiessele] +* Merge branch 'updates' into devel. [Max Zwiessele] * [core] updating system, security branching. [Max Zwiessele] * New function to plot just the errorbars of the training data. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Ensuring the shape of the mean vector at predict time fixes bug in EP prediction. [James Hensman] @@ -3755,13 +3841,13 @@ * Model uses the new HeteroscedasticGaussian likelihood. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Add MRD for regression benchmark. [Zhenwen Dai] * Remove the old housing benchmark. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * Fixed random seed for kronecker tests. [James Hensman] @@ -3771,7 +3857,7 @@ * Add missing file. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * Gradients w.r.t. kappa corrected. [Ricardo Andrade] @@ -3781,7 +3867,7 @@ * Fixed laplace seed, added debugging for misc tests. [Alan Saul] -* Merge branch 'devel' of github.com:/sheffieldml/gpy into devel. [James Hensman] +* Merge branch 'devel' of github.com:/sheffieldml/gpy into devel. [James Hensman] * Removed installation conflict. [Alan Saul] @@ -3791,7 +3877,7 @@ * Added variational expectation tests updates. [Alan Saul] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Alan Saul] * Adding var_gauss.py. [James Hensman] @@ -3807,7 +3893,7 @@ * Improve the stability of parallel inference code. [Zhenwen Dai] -* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] * Merge pull request #216 from Dapid/devel-cython_update. [James Hensman] @@ -3817,7 +3903,7 @@ * Tidied setup.py. [James Hensman] -* Merge branch 'Dapid-devel-cythonchol' into devel. [James Hensman] +* Merge branch 'Dapid-devel-cythonchol' into devel. [James Hensman] * Running cython. [James Hensman] @@ -3825,17 +3911,17 @@ * Minor corrections :) [James Hensman] -* Merge branch 'devel' into Dapid-devel-cythonchol. [James Hensman] +* Merge branch 'devel' into Dapid-devel-cythonchol. [James Hensman] * Adding new test for cholesky backprop. [James Hensman] -* Merge branch 'devel-cythonchol' of git://github.com/Dapid/GPy into Dapid-devel-cythonchol. [James Hensman] +* Merge branch 'devel-cythonchol' of git://github.com/Dapid/GPy into Dapid-devel-cythonchol. [James Hensman] * FIX: ensuring contiguity of the buffers for BLAS call and returning a Numpy array. [David Menéndez Hurtado] * FIX: transforming the indexing to 2D. [David Menéndez Hurtado] -* ENH: implementing the Cholesky backpropagation through Scipy's BLAS. [David Menéndez Hurtado] +* ENH: implementing the Cholesky backpropagation through Scipy's BLAS. [David Menéndez Hurtado] * ENH: fixed up BCGPLVM to work with new framework. [James Hensman] @@ -3854,7 +3940,7 @@ * Fixing qualtile code for some likelhoods. [James Hensman] -* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] * Change the default name of sparse_gp_mpi class. [Zhenwen Dai] @@ -3870,11 +3956,11 @@ * Fixed conflict in plotting. [James Hensman] -* Merge branch 'tjhgit-devel' into devel. [James Hensman] +* Merge branch 'tjhgit-devel' into devel. [James Hensman] * Merging. conflict in relative import styles. [James Hensman] -* Merge remote-tracking branch 'upstream/devel' into devel. [tjhgit] +* Merge remote-tracking branch 'upstream/devel' into devel. [tjhgit] Conflicts: GPy/kern/__init__.py @@ -3904,7 +3990,7 @@ * The bug fix for the cblas.h problem in Mac os x. [Zhenwen Dai] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mzwiessele] * Merge the changes. [Fariba] @@ -3912,11 +3998,11 @@ * Improve the documentation of infer_newX. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Change crescent data to optimize with .optimize() [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * Commit to pull. [Neil Lawrence] @@ -3926,7 +4012,7 @@ * Passing metadata. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Generalized the variatinoal Gaussian approximatino revisited code for any likelihood. [James Hensman] @@ -3936,11 +4022,11 @@ * [bgplvm] technical new stuff. [mzwiessele] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mzwiessele] * Some correction for ibp ssgplvm. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Python 3 fixes. [Mike Croucher] @@ -3956,15 +4042,15 @@ * Parallelizing backprop of cholesky. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Jacobians should not be computed only for transforms. [James Hensman] * Jacobians should not be computed only for transforms. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Updated plotting. [Alan Saul] @@ -3976,7 +4062,7 @@ * [verbose opt] verbose needed clear after finish push through. [mzwiessele] -* Merge branch 'devel' of github.com:/sheffieldml/gpy into devel. [James Hensman] +* Merge branch 'devel' of github.com:/sheffieldml/gpy into devel. [James Hensman] * Allow to set color for the skeleton visualization. [Zhenwen Dai] @@ -3988,7 +4074,7 @@ * Minor bugfix in raw_predict with full_cov for sparseGP. [James Hensman] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Alan Saul] * [ssmrd] implement with IBP prior. [Zhenwen Dai] @@ -3998,11 +4084,11 @@ * [ssgplvm] implement IBP prior. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * [param] added multilevel indexing note to doc. [Max Zwiessele] -* Merge branch 'devel' of github.com:/sheffieldml/gpy into devel. [James Hensman] +* Merge branch 'devel' of github.com:/sheffieldml/gpy into devel. [James Hensman] * Some cython improvments for stationary kerns. [James Hensman] @@ -4018,13 +4104,13 @@ * Small bug in cython tests. [James Hensman] -* Merge branch 'reorder_choleskies' into devel. [James Hensman] +* Merge branch 'reorder_choleskies' into devel. [James Hensman] * Svgp working with reordered chols. [James Hensman] * Interim svgp commit. [James Hensman] -* Merge branch 'devel' into reorder_choleskies. [James Hensman] +* Merge branch 'devel' into reorder_choleskies. [James Hensman] * Svgp, more c-ordering. [James Hensman] @@ -4032,9 +4118,9 @@ * Preliminary reconfiguring or choleskies ordering. [James Hensman] -* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * Change the behavior the optimize_restarts to keep the original model parameters for the firt run. [Zhenwen Dai] @@ -4062,11 +4148,11 @@ * Addint constant mapping. [James Hensman] -* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] * [changepoint] cp is array. [mzwiessele] @@ -4096,17 +4182,17 @@ * Added backprop of cholesky grads. [James Hensman] -* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] * Update .travis.yml. [James Hensman] * Update MANIFEST.in. [James Hensman] -* Merge branch 'cython2' into devel. [James Hensman] +* Merge branch 'cython2' into devel. [James Hensman] * Changes to comments in compiled cython file. [James Hensman] -* Merge branch 'cython2' into devel. [James Hensman] +* Merge branch 'cython2' into devel. [James Hensman] * All tests passing. [James Hensman] @@ -4132,11 +4218,11 @@ * Initial cython commit. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * [basis funcs] memory efficient posterior inference. [mzwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] * [plotting] added predict_kw to plot function. [mzwiessele] @@ -4148,11 +4234,11 @@ * Added log predictive density, student t degrees of freedom gradients and plotting functionality. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * [basisfunckern] gradients for non ard adjusted. [mzwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] * Merge with commit of dgplvm. [frb-yousefi] @@ -4172,7 +4258,7 @@ * Updated svgp kernel gradients. [Alan Saul] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mzwiessele] * Manual merging with AS. [James Hensman] @@ -4206,7 +4292,7 @@ Python 3 Compatibility -* Merge remote-tracking branch 'upstream/devel' into devel. [Mike Croucher] +* Merge remote-tracking branch 'upstream/devel' into devel. [Mike Croucher] * Fix printing error. [Mike Croucher] @@ -4218,7 +4304,7 @@ * Resolve merge conflicts. [Mike Croucher] -* Used 'six' to support Py3 and Py2 simultaneously. [Mike Croucher] +* Used 'six' to support Py3 and Py2 simultaneously. [Mike Croucher] * Merge from upstream. [Mike Croucher] @@ -4242,9 +4328,9 @@ * Various Python 3 fixes. [Mike Croucher] -* Types.TupleType -> tuple fix for python 3. [Mike Croucher] +* Types.TupleType -> tuple fix for python 3. [Mike Croucher] -* Im_self->__self__ fix for python 3. [Mike Croucher] +* Im_self->__self__ fix for python 3. [Mike Croucher] * Iterkeys fix for Python 3. [Mike Croucher] @@ -4256,7 +4342,7 @@ * Updated README now that dict issues are fixed. [Mike Croucher] -* Fixed 'dict changed size' errors. [Mike Croucher] +* Fixed 'dict changed size' errors. [Mike Croucher] * Import fixes for Py3. [Mike Croucher] @@ -4326,11 +4412,11 @@ * Import fix for Py3. [Mike Croucher] -* Changed <> to != for Py3 compatibility. [Mike Croucher] +* Changed <> to != for Py3 compatibility. [Mike Croucher] * Updated Py3 work. [Mike Croucher] -* Removed import urllib2 since it wasn't being used. [Mike Croucher] +* Removed import urllib2 since it wasn't being used. [Mike Croucher] * Urllib2 fixes for Py3 compatibility. [Mike Croucher] @@ -4340,7 +4426,7 @@ * Put weave import in a try block so it fails gracefullt in Py3. [Mike Croucher] -* Merge remote-tracking branch 'upstream/devel' into devel. [Mike Croucher] +* Merge remote-tracking branch 'upstream/devel' into devel. [Mike Croucher] * Fixed ConfigParser for Python 3 compat. [Mike Croucher] @@ -4370,19 +4456,19 @@ * Convert print to function for Python 3 compatibility. [Mike Croucher] -* Convert print to function for Python 3 compatibility. This breaks compatibility for versions of Python < 2.6. [Mike Croucher] +* Convert print to function for Python 3 compatibility. This breaks compatibility for versions of Python < 2.6. [Mike Croucher] * Convert print to function for Python 3 compatibility. [Mike Croucher] -* Convert print to function for Python 3 compatibility. This breaks compatibility for versions of Python < 2.6. [Mike Croucher] +* Convert print to function for Python 3 compatibility. This breaks compatibility for versions of Python < 2.6. [Mike Croucher] * Convert print to function for Python 3 compatibility. [Mike Croucher] -* Merge remote-tracking branch 'upstream/devel' into devel. [Mike Croucher] +* Merge remote-tracking branch 'upstream/devel' into devel. [Mike Croucher] * Added details of Python 3 work. [Mike Croucher] -* Convert print to function for Python 3 compatibility. This breaks compatibility for versions of Python < 2.6. [Mike Croucher] +* Convert print to function for Python 3 compatibility. This breaks compatibility for versions of Python < 2.6. [Mike Croucher] * More relative import fixes for Python 3 compatibility. [Mike Croucher] @@ -4392,7 +4478,7 @@ * Speed ups for normal cdf. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Added Y_metadata to log_predictive_density. [Alan Saul] @@ -4400,13 +4486,13 @@ * [basis func kernels] added support for simple basis function kernels, can be easily extended by implementing phi function in BasisFuncKern. [mzwiessele] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mzwiessele] * Small bugfix in white kernel. [James Hensman] * Tests to probe the mean-function functionality. [James Hensman] -* Merge branch 'mean_functions' into devel. [James Hensman] +* Merge branch 'mean_functions' into devel. [James Hensman] * Merges. [James Hensman] @@ -4420,9 +4506,9 @@ * Working mean function examples. [James Hensman] -* Merge branch 'devel' of github.com:/sheffieldml/GPy into mean_functions. [James Hensman] +* Merge branch 'devel' of github.com:/sheffieldml/GPy into mean_functions. [James Hensman] -* Merge branch 'devel' of github.com:/sheffieldml/GPy into mean_functions. [James Hensman] +* Merge branch 'devel' of github.com:/sheffieldml/GPy into mean_functions. [James Hensman] * Merged. ish. [James Hensman] @@ -4458,9 +4544,9 @@ * Bug in linalg jitchol!!! [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] -* Merge branch 'devel' [Max Zwiessele] +* Merge branch 'devel' [Max Zwiessele] * Implement update_gradients_diag for MLP kernel. [Zhenwen Dai] @@ -4476,7 +4562,7 @@ * Mean functions in place. [James Hensman] -* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] * Optimize sslinear kernel. [Zhenwen Dai] @@ -4486,13 +4572,13 @@ * More samples for predictive quantile. [Alan Saul] -* Merge branch 'saul_merge' into devel. [Alan Saul] +* Merge branch 'saul_merge' into devel. [Alan Saul] * Added safe_exp and tests. [Alan Saul] * Small tidying up. [Alan Saul] -* Merge branch 'devel' into saul_merge. [Alan Saul] +* Merge branch 'devel' into saul_merge. [Alan Saul] * Merging with private repo, mostly fixed. [Alan Saul] @@ -4500,9 +4586,9 @@ * Adding likelihoods and block matrices. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Relaxed inference test requirement. [Alan Saul] @@ -4522,7 +4608,7 @@ * Stupid bug. [James Hensman] -* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] * Lots of changes to mappings. [James Hensman] @@ -4532,7 +4618,7 @@ * [verbose opt] ipython notebook new version widget changes. [mzwiessele] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mzwiessele] * A little work on mappings. [James Hensman] @@ -4550,9 +4636,9 @@ * Fix the param renaming problem. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] -* [optimize] max_f_eval -> max_iters. [mzwiessele] +* [optimize] max_f_eval -> max_iters. [mzwiessele] * [optimize] added clear functionality for ipython notebook and kern input sensitivity error handling. [mzwiessele] @@ -4569,13 +4655,13 @@ * Messy merge. [James Hensman] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [frb-yousefi] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [frb-yousefi] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mzwiessele] -* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] -* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] * Reconfigured svgp inference a little. [James Hensman] @@ -4607,13 +4693,13 @@ * Minor weave/numpy bug in coregionalize. [James Hensman] -* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] * Added logging for jitter so we know how much has been added and how many tries have been taken. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * [var dtc] added code for additional covariates, not affecting normal procedures. [Max Zwiessele] @@ -4681,7 +4767,7 @@ * [html print] more table based corrections for html printing. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Implement update_gradients_diag for MLP kernel. [Zhenwen Dai] @@ -4709,9 +4795,9 @@ * Huge merge correcting upstream master. [Alan Saul] -* Merge branch 'devel' [Max Zwiessele] +* Merge branch 'devel' [Max Zwiessele] -* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:/sheffieldml/GPy into devel. [James Hensman] * Another attempt by installing a mini version of anaconda, should be easier to maintain. [Alan Saul] @@ -4731,7 +4817,7 @@ Removing set of numpy random seed - Great spot! We're just about to relase the next iteratino of GPy, we'll make sure it happens there too. + Great spot! We're just about to relase the next iteratino of GPy, we'll make sure it happens there too. Thanks. @@ -4765,7 +4851,7 @@ * Bgplvm steepest gradient map update. [mzwiessele] -* Merge branch 'master' of github.com:SheffieldML/GPy. [mzwiessele] +* Merge branch 'master' of github.com:SheffieldML/GPy. [mzwiessele] * Update README.md with funding acknowledgements. [Neil Lawrence] @@ -4785,7 +4871,7 @@ * Version update. [Max Zwiessele] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Max Zwiessele] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Max Zwiessele] * Pickling now allways binary as well as protocol -1. [Max Zwiessele] @@ -4805,7 +4891,7 @@ * Fixed Ctrl-C behaviour on Windows. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] * Fixed come path issues in sympykern. [James Hensman] @@ -4817,9 +4903,9 @@ * Change order of imports for RTD. [Alan Saul] -* Merge branch 'devel' [Alan Saul] +* Merge branch 'devel' [Alan Saul] -* Merge branch 'master' into devel. [Alan Saul] +* Merge branch 'master' into devel. [Alan Saul] * Removed variational.py. [Alan Saul] @@ -4839,9 +4925,9 @@ * Merge completed. [Max Zwiessele] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mu] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mu] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Andreas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Andreas] * Small changes in svigp. [Andreas] @@ -4865,9 +4951,9 @@ * Bug in ODE_UY fix. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] -* Fixed the numerical quadrature, won't work with large f unless normalized. [Alan Saul] +* Fixed the numerical quadrature, won't work with large f unless normalized. [Alan Saul] * Fixed lots of breaking tests, reduced step size for checkgrad to 1e-4 in tests (perhaps this should be global), added some missing attributes to data_resources.json. [Alan Saul] @@ -4887,9 +4973,9 @@ * Removed print statements from config parser, commented out ODE kerns. [Nicolo Fusi] -* Merge branch 'devel' [Nicolo Fusi] +* Merge branch 'devel' [Nicolo Fusi] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mu] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mu] * Ode UY. [mu] @@ -4897,11 +4983,11 @@ * ODE_UY. [mu] -* Merge branch 'devel' [Nicolo Fusi] +* Merge branch 'devel' [Nicolo Fusi] * Added some more error checking for downloading datasets. [Neil Lawrence] -* Fixed some bugs in mocap.py where errors weren't being raised when file format was incorrect and made datasets.py check for 404 errors which previously were occuring silently ... shhhhh. [Neil Lawrence] +* Fixed some bugs in mocap.py where errors weren't being raised when file format was incorrect and made datasets.py check for 404 errors which previously were occuring silently ... shhhhh. [Neil Lawrence] * Fixed bugs in cmu_mocap loader where cmu_url was missing and loading in mocap data twice in same session led to incorrect url through copy error. [Neil Lawrence] @@ -4911,21 +4997,21 @@ * Changed more examples to accept optimize and plot. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Added comments for models module and adjusted setup. [Max Zwiessele] -* Merge branch 'naniny' into devel. [Max Zwiessele] +* Merge branch 'naniny' into devel. [Max Zwiessele] * Rename _models to models_modules to include in doc. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Some tidying in the regression examples. [James Hensman] * Added optimize and plot for classification, non_gaussian and stochastic examples. [Alan Saul] -* Fixed gp_base and svigp for sampling (doesn't use it but needs the arguments) [Alan Saul] +* Fixed gp_base and svigp for sampling (doesn't use it but needs the arguments) [Alan Saul] * Added constant to Z_tilde, now log likelihoods are equal! [Alan Saul] @@ -4933,9 +5019,9 @@ * Dimensionality reduction examples updated with optimize, plot and verbose. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Changing the seed seems to fix Alan's bug. [James Hensman] +* Changing the seed seems to fix Alan's bug. [James Hensman] * Fixed symmetry in checkgrad issue. [James Hensman] @@ -4945,7 +5031,7 @@ * Improved detectino of sympy. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Fixed exception handling bug in GPy/util/linalg.py:29. [Teo de Campos] @@ -4955,19 +5041,19 @@ * Changeing models to _models in setup.py. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Fixed step size for likelihood tests and allowed randomizing of laplace. [Alan Saul] * Fixed student_t approximation demo and changed convergence critera to difference of f. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Added cfg file to manfiest and package_data. [Alan Saul] * Dimensionality reduction example (oil) updated. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Removed ipdb statement from kern, cleaned up some nasty whitespace. [James Hensman] @@ -4977,7 +5063,7 @@ * More readme edits. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Minor edits to the README. [James Hensman] @@ -4985,9 +5071,9 @@ * Gradientchecker added as a model. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Push minor fix to eq_sympy kernel test. [Neil Lawrence] @@ -4999,7 +5085,7 @@ * Modified to improve part of stability, gradient checks still passing. [Neil Lawrence] -* Added gradient of sympy kernel, seems to pass tests, but know it's not numerically stable. Checking in before making numerically stable. [Neil Lawrence] +* Added gradient of sympy kernel, seems to pass tests, but know it's not numerically stable. Checking in before making numerically stable. [Neil Lawrence] * Fixed test in kern.py to request correct output dim for multioutput covariances. [Neil Lawrence] @@ -5021,19 +5107,19 @@ * Fixed bug in sympy kernel and added sympolic.py back into utils __init__.py. [Neil Lawrence] -* Merge with James's changes. [Neil Lawrence] +* Merge with James's changes. [Neil Lawrence] * Merge. [James Hensman] * Removed some sympy stuff. [James Hensman] -* Merge with James's changes. [Neil Lawrence] +* Merge with James's changes. [Neil Lawrence] * Committing change for master check out. [Neil Lawrence] * Skipping crossterm tests instead of expected failure. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Added a path for the data resources. not all users will be working in the GPy directory. [James Hensman] @@ -5041,11 +5127,11 @@ * Bug fix for single output sympy kernel. [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mu] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mu] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] * Fixed problem in warping. [Nicolo Fusi] @@ -5063,11 +5149,11 @@ * Updated crossterms, rbf x any not working yet (derivatives) [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Weird merge. [James Hensman] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * Part implementation of ode_eq functionality. Not yet numerically stable or efficient (some horrible use of cut and paste to get things working ...) [Neil Lawrence] @@ -5085,17 +5171,17 @@ * Changed how we search for config files on windows. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Fixed up symmetric kern. [James Hensman] * Half way through crossterm objective. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Added block matrix utility. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Added **likelihood_params to predictive_values. [Ricardo] @@ -5103,11 +5189,11 @@ * Adding docstring for symmetric kern. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Bug fixed in numerical approx. to the predictive variance. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Numerical predictions fixed, sampling predictions are not working. [Ricardo] @@ -5119,13 +5205,13 @@ * In the middle of crossterms. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * 2D plots fixed. [Ricardo] * Passing **noise_args into predictive_values. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Missing term in the likelihood. [Ricardo] @@ -5135,7 +5221,7 @@ * BGPLVM test for crossterms. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Even more data plotting. [James Hensman] @@ -5149,7 +5235,7 @@ * Sped up sampling a lot for student t, bernoulli and poisson, added sampling for gaussian and exponential (untested) [Alan Saul] -* Merge remote-tracking branch 'gpy_real/devel' [Alan Saul] +* Merge remote-tracking branch 'gpy_real/devel' [Alan Saul] * Ignoring examples tests again. [Alan Saul] @@ -5177,7 +5263,7 @@ * Added log predictive density, ln p(y*|D) [Alan Saul] -* Merge remote-tracking branch 'gpy_real/devel' [Alan Saul] +* Merge remote-tracking branch 'gpy_real/devel' [Alan Saul] * Updated boston tests (more folds, allow a bias as the datasets are not normalized once split) and more folds. Tweaked some laplace line search parameters, added basis tests for ep. [Alan Saul] @@ -5189,7 +5275,7 @@ * Added numerical mean and variance with quadrature, about to clean up. [Alan Saul] -* Merge branch 'master' into merge_branch. [Alan Saul] +* Merge branch 'master' into merge_branch. [Alan Saul] * Changed the gradients (perhaps for the worse) [Alan Saul] @@ -5215,15 +5301,15 @@ * Playing trying to find what makes it want to go so low. [Alan Saul] -* Fixed bug where B wasn't refering to current f location. [Alan Saul] +* Fixed bug where B wasn't refering to current f location. [Alan Saul] * Everything seems to be gradchecking again. [Alan Saul] -* Added minimizer for finding f, doesn't help. [Alan Saul] +* Added minimizer for finding f, doesn't help. [Alan Saul] * Now checkgrads a lot more of the time, but still fails in optimisation, seems also odd that when parameter is fixed kernel parameters go to infinity. [Alan Saul] -* Added another optimisation which doesn't use gradients. Seems like F is almost always found, but Y can be off, suggesting that Wi__Ki_W is wrong, maybe W? [Alan Saul] +* Added another optimisation which doesn't use gradients. Seems like F is almost always found, but Y can be off, suggesting that Wi__Ki_W is wrong, maybe W? [Alan Saul] * Trying to fix optimisation problem, fixed a few bugs but still fails at very low noise. [Alan Saul] @@ -5235,7 +5321,7 @@ * Checkgrads with explicit and implicit components half the time. [Alan Saul] -* About to input new derivations for Z's... [Alan Saul] +* About to input new derivations for Z's... [Alan Saul] * Took out all the asserts and using pure broadcasting method of diagonal now. [Alan Saul] @@ -5285,17 +5371,17 @@ * Adding gradients, shapes starting to make sense. [Alan Saul] -* Attempted to introduce gradient methods, won't work yet I doubt. [Alan Saul] +* Attempted to introduce gradient methods, won't work yet I doubt. [Alan Saul] -* Merge remote-tracking branch 'upstream/devel' [Alan Saul] +* Merge remote-tracking branch 'upstream/devel' [Alan Saul] * Merged likelihood functions. [Alan Saul] * Should be working now, needed to change relative path names. [Alan Saul] -* Merge branch 'merge_trial' [Alan Saul] +* Merge branch 'merge_trial' [Alan Saul] -* Merge branch 'old_repo' into merge_trial. [Alan Saul] +* Merge branch 'old_repo' into merge_trial. [Alan Saul] * Make directory structure match that of GPy. [Alan Saul] @@ -5305,7 +5391,7 @@ * Merged in branch which had old_repo merged in. [Alan Saul] -* Adding weibull likelihood, requires 'extra_data' to be passed to likelihood, i.e. the censoring information. [Alan Saul] +* Adding weibull likelihood, requires 'extra_data' to be passed to likelihood, i.e. the censoring information. [Alan Saul] * Fixed the z scalings. [Alan Saul] @@ -5339,7 +5425,7 @@ * Got an idea of how to implement! written in docs. [Alan Saul] -* Trying to 'debug' [Alan Saul] +* Trying to 'debug' [Alan Saul] * Got most of laplace approximation working. [Alan Saul] @@ -5369,7 +5455,7 @@ * Rename Binomial to Bernoulli (maybe generalise it with the constant later, but tilted distribution may change) [Alan Saul] -* Added pdf_link's for gaussian and student t, added third derivatives for transformations and tests for them. [Alan Saul] +* Added pdf_link's for gaussian and student t, added third derivatives for transformations and tests for them. [Alan Saul] * Renamed laplace_tests to likelihoods_tests. [Alan Saul] @@ -5377,21 +5463,21 @@ * Fixed some bugs, added third derivative for log transformation, and did some doccing. [Alan Saul] -* Merge remote-tracking branch 'gpy_real/devel' into merge_branch. [Alan Saul] +* Merge remote-tracking branch 'gpy_real/devel' into merge_branch. [Alan Saul] * Still tidying up, laplace now working again, gaussian and student_t likelihoods now done. [Alan Saul] * Started on chaining, must remember to chain _laplace_gradients aswell! [Alan Saul] -* Merge remote-tracking branch 'gpy_real/devel' into merge_branch. [Alan Saul] +* Merge remote-tracking branch 'gpy_real/devel' into merge_branch. [Alan Saul] -* Merge remote-tracking branch 'gpy_real/devel' into merge_branch. [Alan Saul] +* Merge remote-tracking branch 'gpy_real/devel' into merge_branch. [Alan Saul] -* Merge remote-tracking branch 'gpy_real/devel' into merge_branch. [Alan Saul] +* Merge remote-tracking branch 'gpy_real/devel' into merge_branch. [Alan Saul] -* Merge remote-tracking branch 'gpy_real/devel' into merge_branch. [Alan Saul] +* Merge remote-tracking branch 'gpy_real/devel' into merge_branch. [Alan Saul] -* Merge remote-tracking branch 'gpy_real/devel' into merge_branch. [Alan Saul] +* Merge remote-tracking branch 'gpy_real/devel' into merge_branch. [Alan Saul] * Finished tearing gaussian noise down, time for student t. [Alan Saul] @@ -5409,7 +5495,7 @@ * Tidied up laplace. [Alan Saul] -* Integrated Laplace and merged Merge remote-tracking branch 'gpy_real/devel' into merge_branch. [Alan Saul] +* Integrated Laplace and merged Merge remote-tracking branch 'gpy_real/devel' into merge_branch. [Alan Saul] Conflicts: GPy/core/gp.py @@ -5435,7 +5521,7 @@ * All gradients now gradcheck. [Alan Saul] -* Merge remote-tracking branch 'gpy_real/devel' into merge_branch. [Alan Saul] +* Merge remote-tracking branch 'gpy_real/devel' into merge_branch. [Alan Saul] * Refactored tests. [Alan Saul] @@ -5443,7 +5529,7 @@ * Added tests and fixed some naming. [Alan Saul] -* Modified gradient_checker to allow for variable 'f' [Alan Saul] +* Modified gradient_checker to allow for variable 'f' [Alan Saul] * Renamed some things, made some small (incorrect) gradient changes, generalised the gp regression for any likelihood, and added a place holder link function waiting for Richardos changes. [Alan Saul] @@ -5479,7 +5565,7 @@ * Turned omp off by default as discussed. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Added configuration file. [Nicolò Fusi] @@ -5490,7 +5576,7 @@ * Added xw_pen data. [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * Basic sim code functional. [Neil Lawrence] @@ -5525,7 +5611,7 @@ * More ]#copyrighting. [James Hensman] -* Branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * [kernel plots] updates on bar plots. [Max Zwiessele] @@ -5537,7 +5623,7 @@ * Working One vs All sparse gp classification wrapper. [Andreas] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Added lengthscales for a standard GPLVM with ARD. [Andreas] @@ -5551,12 +5637,12 @@ * [inferenceX] with missing data. [mzwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] Conflicts: GPy/inference/latent_function_inference/inferenceX.py -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * Bug fix for infer_newX. [Zhenwen Dai] @@ -5568,9 +5654,9 @@ * [priors] pickling priors (not working for Discriminative prior) [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Spike and slab binary variable numerical enhancement. [Zhenwen Dai] @@ -5580,7 +5666,7 @@ * [MRD] updates and nicer plotting. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Rename the save_params_H5 function to be a general function save which can potentially support other file format. [Zhenwen Dai] @@ -5592,23 +5678,23 @@ * New ssrbf implementation. [Zhenwen Dai] -* Mergt push e branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] +* Mergt push e branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] * Fixed or zero size models will now not raise an error when trying to optimize. [James Hensman] * Fixed or zero size models will now not raise an error when trying to optimize. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Fixed lots of examples. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Fixing examples. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Documenting the core GP class. [Alan Saul] @@ -5622,13 +5708,13 @@ * [dim red] cmu_mocap normalize. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Redundant models deleted. [Ricardo] * Update docstring for checkgrad. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * Add test case for mpi. [Zhenwen Dai] @@ -5640,13 +5726,13 @@ * [mpi] deleted import. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] for cleaning up of parallel -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Better handling of missing pods in examples. [James Hensman] @@ -5654,11 +5740,11 @@ * Model checkgrad enhancement. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Updated conf.py to work again rather than cause an infinite loop. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Added verbose checks for likelihood. [Alan Saul] @@ -5668,7 +5754,7 @@ * Work on kernel plotting. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Improved kernel plotting. [James Hensman] @@ -5684,19 +5770,19 @@ * [examples] pods. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * A bug fix for set_XY. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Fixed prior error. [Alan Saul] * Update the set_XY function. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * Added homepage to main GPy project page. [Alan Saul] @@ -5706,15 +5792,15 @@ * [tests] for issue ##146 and #147, fixing parameters inside __init__ [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] -* Minor doc changes, fixed MPI dependency and 'stop' in var_dtc. [Alan Saul] +* Minor doc changes, fixed MPI dependency and 'stop' in var_dtc. [Alan Saul] * Removed ordinal.py (to Symbolic). [Neil Lawrence] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * Add test cases for inference new X for bayesian GPLVM. [Zhenwen Dai] @@ -5726,11 +5812,11 @@ * [MRD] running again, using missing_data classes, more details needed for missing data though. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * Refine the docstring for hmc. [Zhenwen Dai] @@ -5738,15 +5824,15 @@ * Tidied up laplace warnings. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * Add __init__.py to mcmc. [Zhenwen Dai] * Add documentation for hmc. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Changed init for mcmc. [James Hensman] @@ -5762,9 +5848,9 @@ * [VarDTC] reverted SparseGP to previous state, updated BGPLVM accordingly. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] * Omp for dX. [James Hensman] @@ -5794,7 +5880,7 @@ * Indexing bugfix in weave. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * [ObsAr] added .values. [Max Zwiessele] @@ -5814,11 +5900,11 @@ * [classification] sparse gp inference for EPDTC. [Max Zwiessele] -* [pca] pca -> PCA. [Max Zwiessele] +* [pca] pca -> PCA. [Max Zwiessele] * Weave ObsArray bugfix. [James Hensman] -* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] * Merge the discriminative prior to devel. [Fariba] @@ -5830,13 +5916,13 @@ * Changed pylab for pyplot in classification examples. [James Hensman] -* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] * Additions to week2 MLAI. [Neil Lawrence] * Added cloglog link fn. [James Hensman] -* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] * Remove symbolic import. [Neil Lawrence] @@ -5852,15 +5938,15 @@ * More variational quadtrature code. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] * More removal of references to broken files. [James Hensman] * [missingdata] file for missing data was missing O_o. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Fixing more issues cauesd by removal of symbolic.py. [James Hensman] @@ -5872,19 +5958,19 @@ * [vardtc] missing data handling and stochastic update in d. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] * Removed reference to symbolic.py, which NDL deleted. [James Hensman] * Removed reference to symbolic.py, which NDL deleted. [James Hensman] -* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] * Attempt to align numbers to right. [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * Display of models and params for the notebook. [Neil Lawrence] @@ -5892,7 +5978,7 @@ * Weaved some slow functions in the stationary class. We now fall back (and latch) to numpy if weave fails. [James Hensman] -* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:sheffieldml/GPy into devel. [James Hensman] * Stopped rounding to int in priors printing. [Alan Saul] @@ -5914,7 +6000,7 @@ * [pca] missing data is now handled as mean. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * [missing data] general implementation for subsetting data. [Max Zwiessele] @@ -5936,7 +6022,7 @@ * HalfT prior is working. [Ricardo] -* Half_t prior (Martin's contribution) [Ricardo] +* Half_t prior (Martin's contribution) [Ricardo] * Edited coregionalize implementation. [James Hensman] @@ -5948,7 +6034,7 @@ * Add set_X and set_Y interface to gp model. [Zhenwen Dai] -* Merge branch 'devel' for extending prod kernel. [Zhenwen Dai] +* Merge branch 'devel' for extending prod kernel. [Zhenwen Dai] * Added notimplemented error to svigp. [James Hensman] @@ -5990,13 +6076,13 @@ * Bug fix: param object randomize. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Bug fixed in normalization. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Name can be modified. [Ricardo] @@ -6036,7 +6122,7 @@ * [updates] made updates a function, update_model(True|False|None) [mzwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] * Fix psicomp problem. [Zhenwen Dai] @@ -6056,7 +6142,7 @@ * Remove the print message in model.checkgrad. [Zhenwen Dai] -* Allow the default constraint of a Param object to be 'fixed' [Zhenwen Dai] +* Allow the default constraint of a Param object to be 'fixed' [Zhenwen Dai] * More for debug. [Zhenwen Dai] @@ -6064,7 +6150,7 @@ * Some progress for parameter tie. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * [dim red plots] plotting big models. [mzwiessele] @@ -6091,9 +6177,9 @@ * Further bug fix for sparsegp_mpi. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Noise parameters built depending on Y_metadata. [Ricardo] @@ -6101,7 +6187,7 @@ * Recover the ss_gplvm.py. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * [ard] enhanced ard handling and plotting. [mzwiessele] @@ -6127,15 +6213,15 @@ * Minor changes on SSGPLVM. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * [parameterization] Parameter adding more robust and better error handling. [mzwiessele] -* Added kronecker and variational gaussian approximation gp's, vargpapprox needs generalising to any factorizing likelihood. [Alan Saul] +* Added kronecker and variational gaussian approximation gp's, vargpapprox needs generalising to any factorizing likelihood. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Gradients of predictions for Trevor. [James Hensman] @@ -6153,7 +6239,7 @@ * Merge the current devel into psi2. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * [setup] no import of os, nanana alan :) [mzwiessele] @@ -6163,7 +6249,7 @@ * [bgplvm] gradient settings. [mzwiessele] -* Merge branch 'hmc' into devel. [Zhenwen Dai] +* Merge branch 'hmc' into devel. [Zhenwen Dai] A HMC sampler for GP parameters @@ -6181,17 +6267,17 @@ * Initial implementation of hmc. [Niu] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * [minor] minor changes. [mzwiessele] * Coregionalized 2D plotting fixed. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Bug fixed. [Ricardo] @@ -6199,13 +6285,13 @@ * Returned setup.py read to old version. [Alan Saul] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Alan Saul] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * Changes to datasets.py. [Neil Lawrence] -* Added forced extraction of eggs (as we have a fair few non-py files and use the directory structure) added some files to MANIFEST and setup.py's package_data so its included upon distributing. [Alan Saul] +* Added forced extraction of eggs (as we have a fair few non-py files and use the directory structure) added some files to MANIFEST and setup.py's package_data so its included upon distributing. [Alan Saul] * [inference] less constant jitter, and jitter adjustements. [mzwiessele] @@ -6253,7 +6339,7 @@ * [logging] [mzwiessele] -* [gp] memory > only one copy. [mzwiessele] +* [gp] memory > only one copy. [mzwiessele] * [subbarray] logging. [mzwiessele] @@ -6263,7 +6349,7 @@ * [optmimize] bugfix. [mzwiessele] -* [whitespaces] & [opt] minor fix of optimizer, when Optimizer is provided (set model to self) [mzwiessele] +* [whitespaces] & [opt] minor fix of optimizer, when Optimizer is provided (set model to self) [mzwiessele] * [model] optimizer can now be an optimizer instance, instead of a string. [mzwiessele] @@ -6273,31 +6359,31 @@ * [scg] minor adjustements based on original publication. [mzwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * [linalg] fixed scipy 0.14 bugfix. sciy.linalg.lapack.dpotri was fixed to work right with lower=1, thus, the hack is gone now from GPy.util.linalg.dpotri, when using scipy 0.14 and higher. [Max Zwiessele] * Re-doing the lee dataset. [James Hensman] -* Revert "Minor edits to reading Lee data in datasets.py" [James Hensman] +* Revert "Minor edits to reading Lee data in datasets.py" [James Hensman] This reverts commit 730e229238062fa22b726e8c30c891d0819b3c6e. * Fixed unnecessary warnings when using periodic kernels. [durrande] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Datasets.py updates should have been committed before. [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * Reverting Maxs linalg changes. [James Hensman] * Linalg had lowers missing for windows libraries to work correctly. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] -* Merge branc( 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branc( 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Editied whitespace. [James Hensman] @@ -6315,14 +6401,14 @@ * [splitkern] buf fix. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * Merging. [James Hensman] * Reverting the fixing behaviour. [James Hensman] two reasons: 1) the new behaviour is confusing for new users. Either - something is fixed, or it's not. 2) the fixing didn't work! things that + something is fixed, or it's not. 2) the fixing didn't work! things that should have been fixed were passed to the optimizer for optimization. If we really want to save keystrokes, consider this: @@ -6352,7 +6438,7 @@ * Added CIFAR-10 data to data sets. [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * Fixed an assertion, it was checking the dimensionality of the input data matrix, rather than that of the labels. [teodecampos] @@ -6370,7 +6456,7 @@ * [caching] catching key error, when individuum is already gone. [mzwiessele] -* [optimizer&fixing] optimizer has only one optimizer copy and fixing remembers old constraint. [mzwiessele] +* [optimizer&fixing] optimizer has only one optimizer copy and fixing remembers old constraint. [mzwiessele] * [optimizer] one copy for the optimizer in optimizer_array, use this instead of _set|get_params_transformed. [mzwiessele] @@ -6382,7 +6468,7 @@ * [gp] output data is a copy now. [Max Zwiessele] -* [bgplvm&mrd] missing data greatly improved, still not there yet. [Max Zwiessele] +* [bgplvm&mrd] missing data greatly improved, still not there yet. [Max Zwiessele] * New data sets. [Neil Lawrence] @@ -6469,7 +6555,7 @@ * Reverting the fixing behaviour. [James Hensman] two reasons: 1) the new behaviour is confusing for new users. Either - something is fixed, or it's not. 2) the fixing didn't work! things that + something is fixed, or it's not. 2) the fixing didn't work! things that should have been fixed were passed to the optimizer for optimization. If we really want to save keystrokes, consider this: @@ -6493,7 +6579,7 @@ * [fixing] fixing now saves the old constraint. [Max Zwiessele] -* [index operations] added lookup for properties for a given index as dict <properties, subindex> for given index. [Max Zwiessele] +* [index operations] added lookup for properties for a given index as dict for given index. [Max Zwiessele] * [mrd] more control for init, some missing data adjustements, init greatly improved. [Max Zwiessele] @@ -6519,7 +6605,7 @@ * [ploting] dim reduction. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] * [examples] stick demo. [mzwiessele] @@ -6537,13 +6623,13 @@ * Merge chagnes from devel. [Zhenwen Dai] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Zhenwen Dai] * EP is back. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * [latentfunctioninference] superclass LatentFunctionInference added, which contains a call just before and just after optimization. [Max Zwiessele] @@ -6557,21 +6643,21 @@ * [parameterized] restructered a lot and finalized some stuff. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * [caching] renaming of helper methods to make intention clear. [mzwiessele] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [mzwiessele] -* [indexing&memory] in memory view more efficient, catching some indexing errors. [mzwiessele] +* [indexing&memory] in memory view more efficient, catching some indexing errors. [mzwiessele] * Add Drosophila data. [Neil Lawrence] -* Merge mu's changes into devel. [mu] +* Merge mu's changes into devel. [mu] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * [param] hierarchy traversal easier now. [mzwiessele] @@ -6583,13 +6669,13 @@ * Add ordinal and attempt to fix downloads. [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * [paramcore] fix for traversal. [mzwiessele] * [pydot] build pydot with new observer list. [mzwiessele] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * [bgplvm] init lengthscale as 0./var. [mzwiessele] @@ -6597,7 +6683,7 @@ * Add ordinal and attempt to fix downloads. [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * Made openmp switch in only dependent on potion in rbf.py and linear.py. [Neil Lawrence] @@ -6613,7 +6699,7 @@ * [examples] stick man example corrected. [mzwiessele] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * Working with OU kernel. [marahman] @@ -6663,7 +6749,7 @@ * [caching] done right. [Max Zwiessele] -* Merge branch 'devel' of github.com:/SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:/SheffieldML/GPy into devel. [James Hensman] * Added citation to readme. [James Hensman] @@ -6675,7 +6761,7 @@ * [ssgplvm] linear kernel. [Zhenwen Dai] -* Merge branch 'psi2' of github.com:SheffieldML/GPy into psi2. [Zhenwen Dai] +* Merge branch 'psi2' of github.com:SheffieldML/GPy into psi2. [Zhenwen Dai] * Proper whitespace. [James Hensman] @@ -6693,13 +6779,13 @@ * Removed import of non-added file (Mu) [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * St. [mu] -* Merge branch 'params' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into devel. [James Hensman] -* Merge branch 'params' of https://github.com/SheffieldML/GPy into params. [Neil Lawrence] +* Merge branch 'params' of https://github.com/SheffieldML/GPy into params. [Neil Lawrence] * Pre-devel-move check in. [Neil Lawrence] @@ -6711,11 +6797,11 @@ * Bugfix: slicing checks needed to be suspended for combination kernels, checks are done in inner kernels now. [mzwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [mzwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [mzwiessele] * Merged. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] Conflicts: GPy/kern/_src/kern.py @@ -6730,13 +6816,13 @@ * Bugfix: kern input_sens errir. [mzwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [mzwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [mzwiessele] * Merge kernel source. [Neil Lawrence] * Removed imports of files the are not added to the repo. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Removing Neils mid-atlantic commit because he failed to add the relevant files to the repo. [James Hensman] @@ -6750,7 +6836,7 @@ * Added documentation for parameterized objects, needs more detail and fleshing out with proper english. [mzwiessele] -* Part working on symbolics. Replacing data_resources.json with the correct full file (-hapmap). Don't know why we've gone for separate create file ... [Neil Lawrence] +* Part working on symbolics. Replacing data_resources.json with the correct full file (-hapmap). Don't know why we've gone for separate create file ... [Neil Lawrence] * Need to fix missing data in likelihoods. [Neil Lawrence] @@ -6758,13 +6844,13 @@ * New test heteroscedastic noise model. [Ricardo] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] * Bugfix: mixed up global and local index in unfixing. [mzwiessele] * New file, special request. [Ricardo] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] Conflicts: GPy/models/gp_classification.py @@ -6786,9 +6872,9 @@ * Just had to do a check in from midlantic (showing off). [Neil Lawrence] -* Merge branch 'params' of https://github.com/SheffieldML/GPy into params. [Neil Lawrence] +* Merge branch 'params' of https://github.com/SheffieldML/GPy into params. [Neil Lawrence] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * [datasets] merged hapmap dataset into params. [Max Zwiessele] @@ -6800,7 +6886,7 @@ * Bugfix: fixing through regular expression matching. [Max Zwiessele] -* Bugfix: couldn't constrain single parameters, because of indexing of np. [Max Zwiessele] +* Bugfix: couldn't constrain single parameters, because of indexing of np. [Max Zwiessele] * [Kern] added assertion for inputs X being matrix (ndim == 2) [Max Zwiessele] @@ -6924,19 +7010,19 @@ * Gradient can be zero and two parameter cancellation is caught. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Removed some dubuggnin. [James Hensman] * Delete dangling fixed attribute in constraints. [Max Zwiessele] -* Copy had slight bug in id(_parent_index_) > ids for ints are shared globally. [Max Zwiessele] +* Copy had slight bug in id(_parent_index_) > ids for ints are shared globally. [Max Zwiessele] * Student t noise now called t_scale2. [Max Zwiessele] * Added kernel tests again. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Adding of symbolic likelihoods (not yet fully funcitonal). [Neil Lawrence] @@ -6944,15 +7030,15 @@ * Pickling and caching. [Max Zwiessele] -* Exact inference for N>D of Y. [Max Zwiessele] +* Exact inference for N>D of Y. [Max Zwiessele] * Kernel slicer now asserts X dimension on first seeing X. [Max Zwiessele] * Assertion checks for all kernels. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Moved input_sensitivity to the gp class. [James Hensman] @@ -6972,7 +7058,7 @@ * Array list now working with index. [mzwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Full Linear kernel added, inc testing. [James Hensman] @@ -6994,7 +7080,7 @@ * GPclassification has to default inference method to EP. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Whoops! [Alan Saul] @@ -7008,7 +7094,7 @@ * Variational returns now the right raveled indices. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Merge changes. [Zhenwen Dai] @@ -7022,9 +7108,9 @@ * Caching now per instance, not at def time. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] * Added a couple of tests for model predictions. [Alan Saul] @@ -7032,28 +7118,28 @@ * Correct predictions in Gaussian. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * ODE_UY gradient checks now kernel unit. [Max Zwiessele] * Add kernel adding another add kernel. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [mzwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [mzwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] * Missing docstrings. [Ricardo] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] Conflicts: GPy/likelihoods/mixed_noise.py -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] * 1D inducing inputs modified for coregionalized models. [Ricardo] @@ -7095,7 +7181,7 @@ * All the tests pass (though some are marked known-to-fail. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Known fail for EP tests in unit tests. [Max Zwiessele] @@ -7109,7 +7195,7 @@ * Fixes in likelihoods. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Very weird merge conflict, including in files that I did not change. [James Hensman] @@ -7121,9 +7207,9 @@ * All tests are now to check. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Merged. [James Hensman] @@ -7131,14 +7217,14 @@ * Fixes now hierarchical, maybe need to be restructured as lookup from constraints. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] Conflicts: GPy/likelihoods/gaussian.py * Bug fix w.r.t. var_dtc.py. [Zhenwen Dai] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] Conflicts: GPy/inference/latent_function_inference/var_dtc.py @@ -7161,7 +7247,7 @@ * Parameter missin in dL_dthetaL added. [Ricardo] -* ObservableArray -> ObsAr, because of pickling and ndarray printing. [Max Zwiessele] +* ObservableArray -> ObsAr, because of pickling and ndarray printing. [Max Zwiessele] * Merge conflict. [Max Zwiessele] @@ -7169,17 +7255,17 @@ * Fix the bug regarding to the change of the name dL_dthetaL. [Zhenwen Dai] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] * Fixed Y_metadata bug. [Alan Saul] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] * Added jitter to fitc. [James Hensman] * Added a hack fix as suggested by max, zeroing any negative values (should really be numerically negative values on diagonal) [Alan Saul] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] * Stablised other quadrature (should speed things up also), added sampling ability to poisson. [Alan Saul] @@ -7203,11 +7289,11 @@ * Slicing now returns the right shape, when computing derivative wrt X or Z. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Plotting now seems to work for Bernouilli. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Fixes to EP. [James Hensman] @@ -7237,7 +7323,7 @@ * Merge for new kernel slice handling. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Bugfix for grad_dict. [James Hensman] @@ -7249,7 +7335,7 @@ * Manual merge of tests. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] * Plotting fix. [James Hensman] @@ -7259,21 +7345,21 @@ * Active_dims as extra parameter for kernels, it tells which input dimensions to work on. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] -* Merge branch 'params' of https://github.com/SheffieldML/GPy into params. [Neil Lawrence] +* Merge branch 'params' of https://github.com/SheffieldML/GPy into params. [Neil Lawrence] * Testing a bit cleaned periodic is turned off, bc it need different tests, discontinuous still needed. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Coregionalization example. [Ricardo] * Fix needed. [Ricardo] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] * Temporal fix. [Ricardo] @@ -7295,9 +7381,9 @@ * Google trends and football data sets. [Neil Lawrence] -* Merge branch 'params' of https://github.com/SheffieldML/GPy into params. [Neil Lawrence] +* Merge branch 'params' of https://github.com/SheffieldML/GPy into params. [Neil Lawrence] -* Merge branch 'params' of https://github.com/SheffieldML/GPy into params. [Neil Lawrence] +* Merge branch 'params' of https://github.com/SheffieldML/GPy into params. [Neil Lawrence] * Part written addition to datasets for loading in google trends. [Neil Lawrence] @@ -7326,9 +7412,9 @@ * Missing bracket. [Ricardo] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] -* Q Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Q Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Fixing fitc. [James Hensman] @@ -7336,9 +7422,9 @@ * Fixing coreg kernel. [Ricardo] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] Conflicts: GPy/core/gp.py @@ -7372,7 +7458,7 @@ * Kernel slicer. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into input_dims. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into input_dims. [Max Zwiessele] * Bugfix. [James Hensman] @@ -7414,7 +7500,7 @@ * Whitespaces. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * All parameters in memory. [Max Zwiessele] @@ -7432,11 +7518,11 @@ * [SSGPLVM] support linear kernel with ARD off. [Zhenwen Dai] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Zhenwen Dai] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Zhenwen Dai] * Made sampling default for non-gaussian likelihoods as a quick fix to allow plotting again for likelihoods without predictive values. [Alan Saul] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Name added as a parameter of Prod. [Ricardo] @@ -7460,13 +7546,13 @@ * [SSGPLVM] implemented linear kernel. [Zhenwen Dai] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Zhenwen Dai] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Zhenwen Dai] * Changed kernels in tests (lots still failing, but now mostly for good reason rather than silly naming problems) [Alan Saul] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] * Fixed non_gaussian demo. [Alan Saul] @@ -7484,9 +7570,9 @@ * Minor changes to sympy kernel (removing un-needed comments). [Neil Lawrence] -* Merge branch 'params' of https://github.com/SheffieldML/GPy into params. [Neil Lawrence] +* Merge branch 'params' of https://github.com/SheffieldML/GPy into params. [Neil Lawrence] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Sparse gp with uncertain inputs. [Max Zwiessele] @@ -7496,17 +7582,17 @@ * Bit more testing of observable patter. [Max Zwiessele] -* Merge branch 'params' of https://github.com/SheffieldML/GPy into params. [Neil Lawrence] +* Merge branch 'params' of https://github.com/SheffieldML/GPy into params. [Neil Lawrence] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Zhenwen Dai] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Zhenwen Dai] * Weaving a faster rbf. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Stability in stationary) [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Zhenwen Dai] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Zhenwen Dai] * Caching switched on. [Max Zwiessele] @@ -7520,11 +7606,11 @@ * Einsumming in stationary. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Prediction code need updating, started with woodbury vector, but how to predict variance in sparse gp with uncertain inputs? [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Fixed caching bug with args having Nones. [Max Zwiessele] @@ -7536,11 +7622,11 @@ * Plotting with uncertain inputs. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] -* Observer pattern has a handle to trigger only > min_priority observers. [Max Zwiessele] +* Observer pattern has a handle to trigger only > min_priority observers. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Observer pattern now tested and fully operational. needed the good night rest : ) [Max Zwiessele] @@ -7568,15 +7654,15 @@ * Parent observer now static and always last. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Fixes in the plotting and in the dot graphing. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Pydot graphing half done. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Moved plot functionality from add to kern. [James Hensman] @@ -7594,32 +7680,32 @@ * Gradients. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Some work on ep, and some messing with wher ethe derivatives are computed (in the model, not the inference. [Ricardo] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] Conflicts: GPy/kern/_src/constructors.py -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] Conflicts: GPy/kern/kern.py GPy/kern/parts/prod.py -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] Conflicts: GPy/kern/parts/prod.py @@ -7628,7 +7714,7 @@ * Rbf with new parameter structure. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * BayesianGPLVM init with paramschanged. [Max Zwiessele] @@ -7640,7 +7726,7 @@ * Merged variational posterior changes. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Mucho changes to linear.py. [James Hensman] @@ -7662,11 +7748,11 @@ * Merge SSGPLVM into params branch. [Zhenwen Dai] -* Removing testing code from kern.py (it's now in kern_tests.py. [James Hensman] +* Removing testing code from kern.py (it's now in kern_tests.py. [James Hensman] * More efficient computations in stationary. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Minor merges. [Neil Lawrence] @@ -7674,11 +7760,11 @@ * Started sorting out some tests. [James Hensman] -* Renaming: posterior_variationa -> variational_posterior. [James Hensman] +* Renaming: posterior_variationa -> variational_posterior. [James Hensman] * Kernel tests in working order (not all implemented though. [James Hensman] -* Hierarchical kern should be working. I'll let you know then the tests are up... [James Hensman] +* Hierarchical kern should be working. I'll let you know then the tests are up... [James Hensman] * Tidying in kern. [James Hensman] @@ -7688,11 +7774,11 @@ * More bugfixin. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Fixed stationary again. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Added initialization. [Max Zwiessele] @@ -7700,15 +7786,15 @@ * Stuf in rbf might be broken. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Merged static. [Max Zwiessele] * Input_sensitivity and ard plotting. [Max Zwiessele] -* Revert "changed to 'update_gradients_q_variational'" [Max Zwiessele] +* Revert "changed to 'update_gradients_q_variational'" [Max Zwiessele] This reverts commit f311bfdf17c78bc4f56f03514d4e28b26e2e5057. @@ -7720,19 +7806,19 @@ * Fixed likelihood tests. [Alan Saul] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] -* Changed to 'update_gradients_q_variational' [Zhenwen Dai] +* Changed to 'update_gradients_q_variational' [Zhenwen Dai] * 2d plotting. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Variational posterior and prior added, linear updated. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] * Got rid of debugging and failing ep tests. [Alan Saul] @@ -7742,17 +7828,17 @@ * Ratquad working. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Some work pon EP (uninished) [James Hensman] * Unfinished work on ratinoal quadratic kern. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] -* Merge branch 'params' of https://github.com/SheffieldML/GPy into params. [Neil Lawrence] +* Merge branch 'params' of https://github.com/SheffieldML/GPy into params. [Neil Lawrence] * Changes to sympykern.py. [Neil Lawrence] @@ -7764,9 +7850,9 @@ * Minor fixes in kerns. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Zhenwen Dai] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Zhenwen Dai] * Parameterized now supports deleting of parameters. [Max Zwiessele] @@ -7776,7 +7862,7 @@ * Tidying. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Plot merge. [Max Zwiessele] @@ -7798,7 +7884,7 @@ * Linear without caching, derivatives done. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Spellings. [James Hensman] @@ -7810,7 +7896,7 @@ * Empty init file. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Posterior with one covariance per dimension and param gradient fix. [Max Zwiessele] @@ -7844,11 +7930,11 @@ * Bad git merge. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Rbf andl inear fixes. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Missing sys. [James Hensman] @@ -7872,9 +7958,9 @@ * Priors added. [Max Zwiessele] -* Merge branch 'params' into c_oredered. [James Hensman] +* Merge branch 'params' into c_oredered. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Non verbose checkgrad adjusted to new system. [Max Zwiessele] @@ -7894,15 +7980,15 @@ * Variouschanges. [James Hensman] -* An ugly hack to work around the 'stickiness' of ObservableArray. TODO: remove this hack. [James Hensman] +* An ugly hack to work around the 'stickiness' of ObservableArray. TODO: remove this hack. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Fixed some examples and tests, and stated that Y metadata doesnt need to be the same size as Y. [Alan Saul] * Fixed gradchecker and fixes for paramterized. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Fixed bernoulli likelihood divide by 0 and log of 0. [Alan Saul] @@ -7914,13 +8000,13 @@ * Fixed plotting bug. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] -* Here's fitc. [James Hensman] +* Here's fitc. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Derivatives working in DTC. [James Hensman] @@ -7930,7 +8016,7 @@ * Fixed merge conflict. [Alan Saul] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Changes to DTC. [James Hensman] @@ -7938,31 +8024,31 @@ * Renaming dtc. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] * Fixed copy bug of observable array. [Alan Saul] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] * Minor reorganising. [Alan Saul] * Deleted listarray. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * First draft of DTC. [James Hensman] -* Array core and bgplvm working > changes due to __i<op>__ will now be reported. [Max Zwiessele] +* Array core and bgplvm working > changes due to __i__ will now be reported. [Max Zwiessele] * Kernel adding now takes over constraints. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Dumb merge conflict in a comment. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Some messing with fitc. [James Hensman] @@ -7970,7 +8056,7 @@ * Parameter handling with default constraints. [Max Zwiessele] -* Rename dK_dtheta > gradients_X. [Max Zwiessele] +* Rename dK_dtheta > gradients_X. [Max Zwiessele] * Psi stat and kernel tests new parameterization. [Max Zwiessele] @@ -7982,7 +8068,7 @@ * Fixes added for gradchecking. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] Conflicts: GPy/core/parameterization/param.py @@ -7997,30 +8083,30 @@ * Checkgrad now global and callable from any parameter. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] Conflicts: GPy/core/parameterization/param.py GPy/core/parameterization/parameter_core.py GPy/core/parameterization/parameterized.py -* Stupid error, needed to actually USE the gradients in student t... Looks like s2 of rasm's may have an extra -? dW_df == -d2logpdf_df not just d2logpdf_df? [Alan Saul] +* Stupid error, needed to actually USE the gradients in student t... Looks like s2 of rasm's may have an extra -? dW_df == -d2logpdf_df not just d2logpdf_df? [Alan Saul] * Have most of the likelihood testing working, laplace likelihood parameters need fixing, some of the signs are wrong I believe. [Alan Saul] * Have most of the likelihood testing working, laplace likelihood parameters need fixing, some of the signs are wrong I believe. [Alan Saul] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] * Fixed likelihood tests for new parameters structure. [Alan Saul] * Fixed parameter bugs. [Alan Saul] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Alan Saul] * Fixed parameterized oddity where it was updating all constrained parameters as soon as any were constrained rather than after all are constrained@ @ [Alan Saul] -* _highest_parent_ now follows the tree, dK_dX > gradient_X, added update_grads_variational to linear, bgplvm for new framework. [Max Zwiessele] +* _highest_parent_ now follows the tree, dK_dX > gradient_X, added update_grads_variational to linear, bgplvm for new framework. [Max Zwiessele] * Adjusted periodic exponential to the new parameterization. [Max Zwiessele] @@ -8030,7 +8116,7 @@ * Added caching framework. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Highest parent fix. [Max Zwiessele] @@ -8048,9 +8134,9 @@ * Add spike-and-slab gplvm kernel [unfinished].] [Zhenwen Dai] -* Not calling self.parameters_changed explicitly anymore -> not needed. [Max Zwiessele] +* Not calling self.parameters_changed explicitly anymore -> not needed. [Max Zwiessele] -* An afternoon's work on the laplace approximation. [James Hensman] +* An afternoon's work on the laplace approximation. [James Hensman] * More owrk on the Laplace approx. [James Hensman] @@ -8060,7 +8146,7 @@ * Sparse GP now checkgrads, optimises sensibly. Predicitno still not working. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Adapter laplace inference into the param framework. [Zhenwen Dai] @@ -8072,19 +8158,19 @@ * Wrapping docstrings. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] -* "Missing file?" [Ricardo] +* "Missing file?" [Ricardo] * Changed gradient interface to gp and sparse GP. [James Hensman] * Fixed syntax bug in sparse GP. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Pylab library not needed. [Ricardo] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Ricardo] Conflicts: GPy/core/sparse_gp.py @@ -8149,23 +8235,23 @@ * Fixing scg on this branch. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Plot_latent: added param_to_array to model.X and model.Z for matplotlib plotting. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Some gplvm related fixes. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Beginnings of gplvm. [James Hensman] * Changed priority of observable array to 0. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Foo. [James Hensman] @@ -8173,11 +8259,11 @@ * Bug in setting _highest_parent_ fixed. [Max Zwiessele] -* Getstate > _getstate and setstate > _setstate. [Max Zwiessele] +* Getstate > _getstate and setstate > _setstate. [Max Zwiessele] * New gradient handling way nicer. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] * Gradient field added to param. [Max Zwiessele] @@ -8185,9 +8271,9 @@ * Changes to rbf and white to allow new parameter gradient structure. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [James Hensman] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Merged posterior changes. [Max Zwiessele] @@ -8241,7 +8327,7 @@ * Fixed up the Gaussian likelihood a little. [James Hensman] -* All parameterization stuff now in seperate module -> GPy.core.parameterization. [Max Zwiessele] +* All parameterization stuff now in seperate module -> GPy.core.parameterization. [Max Zwiessele] * Fixed unsized param bug. [Max Zwiessele] @@ -8307,7 +8393,7 @@ * Simple tieing now working, still buggy though, progress with care. [Max Zwiessele] -* Biiig changes in tieing, and printing -> hirarchy now always shown. [Max Zwiessele] +* Biiig changes in tieing, and printing -> hirarchy now always shown. [Max Zwiessele] * Minor edits, like spacing, spelling. [James Hensman] @@ -8319,7 +8405,7 @@ * Added gplbm and sparse gp to new parameterized structure. [Max Zwiessele] -* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'params' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Adjusted parameters to report their changes. [Max Zwiessele] @@ -8339,7 +8425,7 @@ * GPRegression working, gradients still todo. [Max Zwiessele] -* First adjustments to the model and gps -> updates and gradient transforms. [Max Zwiessele] +* First adjustments to the model and gps -> updates and gradient transforms. [Max Zwiessele] * Parameters have a update hirarchy, in which updates to parameters are hirarchically pursuit. [Max Zwiessele] @@ -8381,27 +8467,27 @@ * Updated sympy code, multioutput grad checks pass apart from wrt X. Similar problems with prediction as to sinc covariance, needs investigation. [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * Seems to work on windows now. [Nicolò Fusi] - not everything works yet, but I've identified the main issues. Still + not everything works yet, but I've identified the main issues. Still -* Added olivetti faces data set. It required adding netpbmfile.py a bsd licensed pgm file reader from Christoph Gohlke, which doesn't seem to have a spearate installer. Also modified image_show to assume by default that array ordering is python instead of fortran. Modified brendan_faces demo to explicilty force fortran ordering. Notified Teo of change. [Neil Lawrence] +* Added olivetti faces data set. It required adding netpbmfile.py a bsd licensed pgm file reader from Christoph Gohlke, which doesn't seem to have a spearate installer. Also modified image_show to assume by default that array ordering is python instead of fortran. Modified brendan_faces demo to explicilty force fortran ordering. Notified Teo of change. [Neil Lawrence] * Domain and trtansformations namespace prettyfying. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into params. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into params. [Max Zwiessele] * Some fixes and changes to the sympykern. [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * Nparam changes to num_params. [James Hensman] * Changes Nparts for num_parts in kern. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Andreas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Andreas] * Minor changes. [Andreas] @@ -8409,7 +8495,7 @@ * Fixed stick datasets bug ... but sympykern is currently in a rewrite so will be broken. [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * Plots tidied up. [Ricardo] @@ -8423,7 +8509,7 @@ * Tests updated. [Max Zwiessele] -* Dim reduction examples Q= > input_dim= [Max Zwiessele] +* Dim reduction examples Q= > input_dim= [Max Zwiessele] * Numpy non hashable AHHHHHH. [Max Zwiessele] @@ -8431,13 +8517,13 @@ * Parameterized first beta test. [Max Zwiessele] -* Merge branch 'devel' into params. [Max Zwiessele] +* Merge branch 'devel' into params. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mu] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [mu] * Testing ODE. [mu] @@ -8449,22 +8535,22 @@ * Change to criterion on positive definite check (epsilon*10 instead of epsilon). [Neil Lawrence] -* Remove coregionalization test as it's causing a core dump! Need to chase this up. [Neil Lawrence] +* Remove coregionalization test as it's causing a core dump! Need to chase this up. [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * Some tidying in the EP likelihood. [James Hensman] Changes self.N to self.num_data for consistency with everywhere else added the factor of 2pi to Z. -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Allowed passing of factr to bfgs algorithm. [James Hensman] -* Updates to sympykern including bug fixes and ability to name covariance. Include test for rbf_sympy in kernel tests. Remove coregionalization test as it's causing a core dump! Need to chase this up. [Neil Lawrence] +* Updates to sympykern including bug fixes and ability to name covariance. Include test for rbf_sympy in kernel tests. Remove coregionalization test as it's causing a core dump! Need to chase this up. [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * Fixing W_columns and num_outputs nomenclature. [Ricardo] @@ -8476,7 +8562,7 @@ * Merging changed files. [Neil Lawrence] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Merge pull request #82 from jamesmcm/devel. [James McMurray] @@ -8498,20 +8584,20 @@ * Removing unnecessary stuff... [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] Conflicts: GPy/examples/classification.py -* Fixed a bug in Neil's otherwise tidy hetero kernel. [James Hensman] +* Fixed a bug in Neil's otherwise tidy hetero kernel. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Merge pull request #80 from jamesmcm/devel. [James McMurray] Devel -* Merge branch 'devel' of git://github.com/SheffieldML/GPy into devel. [James McMurray] +* Merge branch 'devel' of git://github.com/SheffieldML/GPy into devel. [James McMurray] * Fixed docstring warnings - could still be mistakes. [James McMurray] @@ -8523,7 +8609,7 @@ * Please stop breaking this module. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Do_test_latents appears to be working now. [James Hensman] @@ -8567,7 +8653,7 @@ * Transformations singleton. [Max Zwiessele] -* Merge branch 'devel' into params. [Max Zwiessele] +* Merge branch 'devel' into params. [Max Zwiessele] Conflicts: GPy/core/transformations.py @@ -8577,7 +8663,7 @@ Devel -* Merge branch 'devel' of git://github.com/SheffieldML/GPy into devel. [James McMurray] +* Merge branch 'devel' of git://github.com/SheffieldML/GPy into devel. [James McMurray] * Bug in prod-coreg kernels fixed, not in the most elegant way though. [Ricardo] @@ -8613,9 +8699,9 @@ * Heaviside transformation fixed. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Likelihoods are now Parameterized objects. [Ricardo] @@ -8627,7 +8713,7 @@ * Fixed Zsolts bug in prod.py. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] Conflicts: GPy/examples/regression.py @@ -8655,7 +8741,7 @@ * LinK2_functions2 merged. [Ricardo] -* Merge branch 'linK_functions2' into devel. [Ricardo] +* Merge branch 'linK_functions2' into devel. [Ricardo] Conflicts: GPy/core/gp.py @@ -8672,7 +8758,7 @@ * Moved to (sparse_)gp_multioutput_regression. [Ricardo] -* Doesn't matter I'll erase this file. [Ricardo] +* Doesn't matter I'll erase this file. [Ricardo] * Duplicated line erased. [Ricardo] @@ -8728,7 +8814,7 @@ * Random changes. [Ricardo] -* The next step is to optimize the noise models' parameters. [Ricardo] +* The next step is to optimize the noise models' parameters. [Ricardo] * Files re-organized. [Ricardo] @@ -8750,15 +8836,15 @@ * Some cool stuff for EP. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Fixed args to bfgs. [James Hensman] * Fixed Alans checkgrad bug. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Working on the Poisson likelihood. [Ricardo] @@ -8766,7 +8852,7 @@ * Correcterd minor errors (imports etc) [Max Zwiessele] -* Pep8'ed transformations module. [Max Zwiessele] +* Pep8'ed transformations module. [Max Zwiessele] * Mrd_sim stable and deprecated. [Max Zwiessele] @@ -8774,9 +8860,9 @@ * Only compare Z cache once. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * Added gibbs.py, although test is still failing. [Neil Lawrence] @@ -8790,9 +8876,9 @@ * Added print m and print m.all differentiation. [Max Zwiessele] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] -* Merge branch 'devel' of git@github.com:SheffieldML/GPy.git into devel. [Max Zwiessele] +* Merge branch 'devel' of git@github.com:SheffieldML/GPy.git into devel. [Max Zwiessele] * Merge dim reduction. [Max Zwiessele] @@ -8812,9 +8898,9 @@ * Changed default values of W and kappa for coregionalisation kernel. Changed names of keyword arguments from Nout and R to output_dim and rank. [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Fixed target slicing bug in prod kernel. [James Hensman] @@ -8846,7 +8932,7 @@ * Added mlp covariance (x gradient not working) [Neil Lawrence] -* Modifications to transformations ... not sure which tests to run to make sure I haven't messed things up. New code avoids exponentiating values greater than -log(eps) or less than log(eps). Also changed negative code to call the positive code (I think they should inherit the positive code ... but maybe not. [Neil Lawrence] +* Modifications to transformations ... not sure which tests to run to make sure I haven't messed things up. New code avoids exponentiating values greater than -log(eps) or less than log(eps). Also changed negative code to call the positive code (I think they should inherit the positive code ... but maybe not. [Neil Lawrence] * Mocking matplotlib pyplot as readthedocs is failing to import it (again...) [Alan Saul] @@ -8862,7 +8948,7 @@ * Constant jitter to Kmm, deleted some white kernels in models and examples. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Added connections.txt. [Neil Lawrence] @@ -8872,7 +8958,7 @@ * Added jacobian and magnification factor. [Alessandra Tosi] -* Oops, that was silly bug. Don't code tired, kids. [James Hensman] +* Oops, that was silly bug. Don't code tired, kids. [James Hensman] problem summing psi2 in sparse_GP @@ -8906,11 +8992,11 @@ * Gradient checker implemented. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Andreas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Andreas] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Changes to psi2 in linear. [James Hensman] @@ -8918,7 +9004,7 @@ * Gradient checker implemented. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Fixed asarray in example toy_ARD. [Andreas] @@ -8926,7 +9012,7 @@ * Merge rbf_inv changes. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Small changes to rbf and rbf_inv. [James Hensman] @@ -8944,15 +9030,15 @@ * Input sensitivity for rbf_inv. [Andreas] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Andreas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Andreas] * Plot_ARD greatly improved, crossterm plotting enabled. [Max Zwiessele] * Plot_ARD greatly improved, crossterm plotting enabled. [Max Zwiessele] -* Git pushMerge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Git pushMerge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] * Fast_array_equals now handles 3d matrices. [Nicolo Fusi] @@ -8962,13 +9048,13 @@ * Stick_bgplvm to original version with rbf. [Andreas] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Andreas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Andreas] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] * Fixed logic for fast_array_equal. [Nicolo Fusi] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] * (much) faster comparison between arrays. Useful for kernel caching. [Nicolo Fusi] @@ -8994,7 +9080,7 @@ * Rbf inv now working. [Andreas] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Andreas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Andreas] * Removed abomnibal matrix class. [James Hensman] @@ -9042,7 +9128,7 @@ * Created a hierarchical kernel. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Fixed a bug in constructor of periodic_matern52. [James Hensman] @@ -9064,11 +9150,11 @@ * More robust gradient clippinggit stat. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Fixed bug in constructors. [Nicolas] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] * New constrain_negative negative_logexp (selected by default) [Nicolas] @@ -9090,11 +9176,11 @@ * Pickling unified with __getstate__ and __setstate__ [Max Zwiessele] -* Merge branch 'devel' into pickle. [Max Zwiessele] +* Merge branch 'devel' into pickle. [Max Zwiessele] * Fixed an import. [Teo de Campos] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] * Added anopther simple subplotting function. [James Hensman] @@ -9102,13 +9188,13 @@ * Added missing import in util.linalg. [Nicolo Fusi] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Merge remote-tracking branch 'origin/devel' into devel. [Ricardo] +* Merge remote-tracking branch 'origin/devel' into devel. [Ricardo] * Bug fix in the confusion matrix. [Ricardo] @@ -9118,7 +9204,7 @@ * Removed unnecessary gitignore line. [Nicolo Fusi] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] * Kernels are now consistent with pep8 and common reason. [Nicolo Fusi] @@ -9126,15 +9212,15 @@ * Merging by hand... [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo] * New version number. [Ricardo] * Ensure_default_constraints is on by default. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] * Bug fix in the confusion matrix. [Ricardo] @@ -9144,9 +9230,9 @@ * Changed manifest from docs to doc. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Corrected minor bug in Brownian kernel. [Nicolas] @@ -9162,7 +9248,7 @@ * Pypi release update. [Max Zwiessele] -* Merge branch 'master' into devel. [Max Zwiessele] +* Merge branch 'master' into devel. [Max Zwiessele] * Removed sympy dependency, incremented version. [James Hensman] @@ -9170,9 +9256,9 @@ * Incremented version. [James Hensman] -* Merge branch 'devel' [James Hensman] +* Merge branch 'devel' [James Hensman] -* Merge branch 'devel' [Alan Saul] +* Merge branch 'devel' [Alan Saul] * Changed version. [Alan Saul] @@ -9180,7 +9266,7 @@ * Robust failure handling in model objective and gradient. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Fixed blaslib bug, I hope. [James Hensman] @@ -9198,11 +9284,11 @@ * Commented out a buggy ax.set_aspect line. [Teo de Campos] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Removed the unnecessary test skip. [Nicolas] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Un-commented out visualize.py. [Teo de Campos] @@ -9212,7 +9298,7 @@ * Removed overwriting_b in lapack. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Fixed lapack importing for old scipy version. [James Hensman] @@ -9222,17 +9308,17 @@ * Merged. [Alan Saul] -* Merge branch 'psi1_transpose_fix' into devel. [James Hensman] +* Merge branch 'psi1_transpose_fix' into devel. [James Hensman] * Psi1 is now the right way around. [James Hensman] * Fixing lapacks. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Removing unused link_functions. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] * Modified lengthscale gradients - demo works now. [James Hensman] @@ -9240,7 +9326,7 @@ * Factored out lapack into utils so we can check version and give deprecation warnings. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Making sure GPy imports. [Neil Lawrence] @@ -9248,57 +9334,57 @@ * Placed back in examples for motion capture! Added spheres to visualization of figure. [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * Added visualization for motion capture data using python visual module. [Neil Lawrence] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * _Xmean is now Xoffset and _Xstd is now _Xscale. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Removed examples with non public datasets. [Nicolas] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] * Removed examples with non public datasets. [Nicolas] * FITC example: bound for lengthscale. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] * Fixed tuto example. [Nicolas] * Non_Gaussian exampless deleted. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Fitc and generalized_fitc models deleted. [Ricardo] * Reduced number of iterations for a couple of things. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Poisson likelihood implementations needs to be thought carefully. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Dimensionality reduction mrd example less interations. [Max Zwiessele] * Link_function class renamed as LinkFunction. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Minor changes. [Ricardo] @@ -9314,19 +9400,19 @@ * Refactored example tests. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Kern constructors now have input_dim instead of D. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merged conflict in tutorial's tests (again) [Nicolas] +* Merged conflict in tutorial's tests (again) [Nicolas] -* Merged conflict in tutorial's tests. [Nicolas] +* Merged conflict in tutorial's tests. [Nicolas] -* Bugs fixed in tutorial's tests. [Nicolas] +* Bugs fixed in tutorial's tests. [Nicolas] * Dim reduction adaption. [Max Zwiessele] @@ -9334,9 +9420,9 @@ * Fixed merge conflict in examples_tests. [Alan Saul] -* Git pushMerge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Git pushMerge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] Conflicts: GPy/core/fitc.py @@ -9351,31 +9437,31 @@ * Merge kern conflicts in examples. [Max Zwiessele] -* Kern params adapted: Nparams > num_params and fixes of input_dim. [Max Zwiessele] +* Kern params adapted: Nparams > num_params and fixes of input_dim. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Nparams > num_params and Nparam_tranformed > num_params_transformed. [Max Zwiessele] +* Nparams > num_params and Nparam_tranformed > num_params_transformed. [Max Zwiessele] -* Made examples possible to run all examples and throw out a dictionary of problems at the end (and whilst it's running, tried to ignore deprecation warnings. [Alan Saul] +* Made examples possible to run all examples and throw out a dictionary of problems at the end (and whilst it's running, tried to ignore deprecation warnings. [Alan Saul] * Lots of bugfixes after refactoring. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * New file. [Ricardo] * Fixed merge conflicts, M now num_inducing. [Alan Saul] -* Refactoring: self.D > self.input_dim in kernels. [Max Zwiessele] +* Refactoring: self.D > self.input_dim in kernels. [Max Zwiessele] * Output_dim instead of input_dim. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * An assortment of fixes. [James Hensman] @@ -9387,7 +9473,7 @@ * New file. [Ricardo] -* Changed all M's for num_inducing. [Alan Saul] +* Changed all M's for num_inducing. [Alan Saul] * Fixed naming to standardized PEP8. [Ricardo] @@ -9407,13 +9493,13 @@ * New FITC model and other stuff. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * How did that happen? [James Hensman] * Merged an emty line... [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] * Dim reduc plotting. [Max Zwiessele] @@ -9434,7 +9520,7 @@ We now match against _get_param_names_transformed(). -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] * Replaced Q by input_dim. [Alan Saul] @@ -9450,13 +9536,13 @@ * Correction to some tests. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Plotting in the model behaves better. [James Hensman] @@ -9476,11 +9562,11 @@ * Examples corrected. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Fixed printing, some example. [James Hensman] @@ -9492,42 +9578,42 @@ * Unit_tests corrected. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Re-merged. only RA's errors (probit?) remain. [James Hensman] +* Re-merged. only RA's errors (probit?) remain. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * MERGE. [Max Zwiessele] * Domains added and class names in priors capitalized. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] Conflicts: GPy/models/GPLVM.py * Remove copies (they are now in visualize code ...). [Neil Lawrence] -* Neil's flailing attempts to update the flailing stick man. [Neil Lawrence] +* Neil's flailing attempts to update the flailing stick man. [Neil Lawrence] * Match_moments function passes transformed values. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Added domain matching in set_prior. [Max Zwiessele] * Added domains to priors. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Examples changed to use new link_functions. [Ricardo] -* Merge branch 'devel' into link_functions. [Ricardo] +* Merge branch 'devel' into link_functions. [Ricardo] * Link functions defined. [Ricardo] @@ -9537,17 +9623,17 @@ * Fixing some examples. [James Hensman] -* Fixed Alan's dependency nightmare. [James Hensman] +* Fixed Alan's dependency nightmare. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] * Scg optimizer enhancments and mrd demo fix. [Max Zwiessele] -* Removed NL's notes, they are now integrated in the issue tracker. [Nicolo Fusi] +* Removed NL's notes, they are now integrated in the issue tracker. [Nicolo Fusi] -* Git branchMerge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Git branchMerge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Mrd and bgplvm simulation examples working. [Max Zwiessele] @@ -9565,11 +9651,11 @@ * Cleaning up setup.py. [Alan Saul] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Test fixed. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Alan Saul] * Added oil test and validation. [Neil Lawrence] @@ -9583,15 +9669,15 @@ * Bugfix: sparseGP.likelihood.Z not added to log_ll. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * DeprecationWarning: Substituded all (\!) flapack occ. with lapack (scipy said so) [Max Zwiessele] * Modified EP code, should be more stable I hope. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] -* Fixed symmetrify for when C/F compiler doesn't work. [Andreas] +* Fixed symmetrify for when C/F compiler doesn't work. [Andreas] * Used scipy.weave to improve the speed of rbf grads. [James Hensman] @@ -9600,15 +9686,15 @@ * Sparse_GP now has a separate predict function. [James Hensman] - GP and sparse_GP used t share a predict fumction. Since we'd like to + GP and sparse_GP used t share a predict fumction. Since we'd like to propagate uncertainty in predictions, sparse_GP.predict needs to accept X_new_variance. -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Added max to authors. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Handling printouts without messages. [Max Zwiessele] @@ -9616,15 +9702,15 @@ * Mocap dataset automatic download. [Andreas] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Logexp_clipped adjust & mrd error messages. [Max Zwiessele] +* Logexp_clipped adjust & mrd error messages. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Bug fix (kernel copy) in mrd. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Merged GPLVM, used Andreas changes. [Max Zwiessele] @@ -9634,15 +9720,15 @@ * Changed likelihood and kernel handling. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Fixed bug in BGPLVM plot. [Teo de Campos] * Implemented plot_latents as an external function in util. [Andreas] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Teo de Campos] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Teo de Campos] * Minor changes to make the demo run faster. [Teo de Campos] @@ -9652,7 +9738,7 @@ * Classification added. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] Conflicts: GPy/models/GP.py @@ -9667,21 +9753,21 @@ * Nosetests do not test expextation of psi_statistics. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Removed the useless print y line. [Teo de Campos] * Fixed bug in sparse GP plotting. [Nicolo Fusi] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] * Sgd. [Nicolo Fusi] * Modified mrd with MZ. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Changes to MRD test. [Ricardo] @@ -9689,9 +9775,9 @@ * Bayesian GPLVM can now take either a likelihood or data matrix as first argument. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Allowing EP in BGPLVM and MRD. [Ricardo] @@ -9707,9 +9793,9 @@ * Structural changes for printing. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Andreas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Andreas] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Teo de Campos] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Teo de Campos] * Changed optimization constraints in GPy/examples/dimensionality_reduction.py. [Teo de Campos] @@ -9717,17 +9803,17 @@ * Removed fisrt prints if display is off. [Andreas] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Automatically fetch datasets and first init. attempt for mocap. [Andreas] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Last stability changes. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Some likelihood.flatten somewhere. [Ricardo] @@ -9741,9 +9827,9 @@ i.e. where numpy is compiled without proper blas linkage -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] * Cross-terms. [Nicolo Fusi] @@ -9751,29 +9837,29 @@ * Minor SGD changes. [Nicolo Fusi] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] * Changes in SGD. [Nicolo Fusi] * SCG printing prettyfied. [Max Zwiessele] -* Merge branch 'mrd' into devel. [Max Zwiessele] +* Merge branch 'mrd' into devel. [Max Zwiessele] * Last changes on BGPLVM stable version. [Max Zwiessele] * Newline only on display. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Andreas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Andreas] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Teo de Campos] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Teo de Campos] * Readded float variance. [Max Zwiessele] @@ -9781,7 +9867,7 @@ * Swiss_roll example changes. [Max Zwiessele] -* Catch beta > 0 not needed anymore. [Max Zwiessele] +* Catch beta > 0 not needed anymore. [Max Zwiessele] * Swiss_roll adjustments. [Max Zwiessele] @@ -9791,7 +9877,7 @@ * Added proper linebeak for SCG printing. [Max Zwiessele] -* Merge branch 'mrd' into devel. [Max Zwiessele] +* Merge branch 'mrd' into devel. [Max Zwiessele] * Swiss_roll example added, BGPLVM_oil now working. [Max Zwiessele] @@ -9807,7 +9893,7 @@ * Printing improved. [Max Zwiessele] -* Merge branch 'devel' into mrd. [Max Zwiessele] +* Merge branch 'devel' into mrd. [Max Zwiessele] * Swiss_roll example. [Max Zwiessele] @@ -9815,7 +9901,7 @@ * Making clipping adjustable. [Max Zwiessele] -* Modified: GPy/models/GPLVM.py Using the following kernel by default: kernel = kern.rbf(Q, ARD=Q>1) + kern.bias(Q, np.exp(-2)) + kern.white(Q, np.exp(-2)) [Teo de Campos] +* Modified: GPy/models/GPLVM.py Using the following kernel by default: kernel = kern.rbf(Q, ARD=Q>1) + kern.bias(Q, np.exp(-2)) + kern.white(Q, np.exp(-2)) [Teo de Campos] * Modified: GPy/util/visualize.py Added the functionality of showing a mosaic of NxN reconstructed images when the size of the number of elements in the feature vector greater than dimensions[0]*dimensions[1]. [Teo de Campos] @@ -9823,7 +9909,7 @@ * Need to commit to resolve a conflict ... [Neil Lawrence] -* Overwrite my changes with James's. [Neil Lawrence] +* Overwrite my changes with James's. [Neil Lawrence] * Merge changes. [Neil Lawrence] @@ -9839,11 +9925,11 @@ * Convenient but not important changes. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Changed prod_orthogonal in tests. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Allowed GP models to plot multiple outputs (in 1D at least) [James Hensman] @@ -9857,9 +9943,9 @@ * Some changes. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Teo de Campos] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Teo de Campos] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Speeding up FITC. [Ricardo] @@ -9867,31 +9953,31 @@ * Ricardo told me to do this. [Teo de Campos] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Removed RA's profile deco. [James Hensman] +* Removed RA's profile deco. [James Hensman] * Generalised backsub_both_sides. [James Hensman] * Remove profile. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] * Moved linalg function to GPy.linalg. [Nicolo Fusi] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolò Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolò Fusi] * Trying to follow changes in likelihood. [Nicolò Fusi] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolò Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolò Fusi] * Small changes. [Nicolò Fusi] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolò Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolò Fusi] * Better f_inv. [Nicolò Fusi] @@ -9903,13 +9989,13 @@ * Gradients are working now. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Added DSYR for ricardo. [James Hensman] * Gradietns check :) [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] * Using weaved symmetrify in pdinv now. [James Hensman] @@ -9921,9 +10007,9 @@ * Change in gradients computation. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolas] * Fixed transformations (Sorry Andreas) [James Hensman] @@ -9974,7 +10060,7 @@ * Added logexp_clipped transformation. [Max Zwiessele] -* Merge branch 'devel' into mrd. [Max Zwiessele] +* Merge branch 'devel' into mrd. [Max Zwiessele] * New termination rule for scg. [Max Zwiessele] @@ -9994,7 +10080,7 @@ * Much tidy9ing in sparse_GP. [James Hensman] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] Conflicts: GPy/examples/dimensionality_reduction.py @@ -10005,11 +10091,11 @@ * Reverted EP procedure (removed cholupdate) [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * BGPLVM example MATLAB compare. [Max Zwiessele] -* Merge branch 'devel' into mrd. [Max Zwiessele] +* Merge branch 'devel' into mrd. [Max Zwiessele] * Last opt updates and tests. [Max Zwiessele] @@ -10017,7 +10103,7 @@ * Various stability working on sparse GP (with MZ) [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Added @testing.deepTest property for skipping tests for deep scan only. [Max Zwiessele] @@ -10031,7 +10117,7 @@ * Mu to go. [Max Zwiessele] -* Merge devel into mrd > transformations added. [Max Zwiessele] +* Merge devel into mrd > transformations added. [Max Zwiessele] * Error bars fixed. [Ricardo] @@ -10047,7 +10133,7 @@ * Async optimize working. [Max Zwiessele] -* Merge branch 'devel' into mrd. [Max Zwiessele] +* Merge branch 'devel' into mrd. [Max Zwiessele] * Added conjugate gradient descent asunc. [Max Zwiessele] @@ -10055,7 +10141,7 @@ * Fixed a bug in all_constrained_indices. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * Typo corrected for negative constrains. [Nicolas] @@ -10065,17 +10151,17 @@ * Eigenvalue decomposition of psi2. [James Hensman] -* Merge branch 'devel' into new_constraints. [James Hensman] +* Merge branch 'devel' into new_constraints. [James Hensman] Conflicts: GPy/core/model.py GPy/core/parameterised.py -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * Minor tidy up of names in visualize (replace histogram with bar chart in lvm_dimselect). [Neil Lawrence] -* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] +* Merge branch 'devel' of https://github.com/SheffieldML/GPy into devel. [Neil Lawrence] * Trying to upgrade numpy version to 1.7.1 as there was an error introduced for weave on 1.7.0 causing tests to fail. [Alan Saul] @@ -10087,7 +10173,7 @@ * Whitespace. [James Hensman] -* Fixed bug in constrain_fixed where soem values weren't deleted. [James Hensman] +* Fixed bug in constrain_fixed where soem values weren't deleted. [James Hensman] * Fixed has_uncertain_inputs weirdness. [James Hensman] @@ -10144,9 +10230,9 @@ * BGPLVM updates and debug helper. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into mrd. [Max Zwiessele] +* Merge branch 'devel' of github.com:SheffieldML/GPy into mrd. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * One more instance of dpotrs instead of dot in sparse GP. [James Hensman] @@ -10154,11 +10240,11 @@ * Rewritten dim_reduction demo to match new style of getters and setters. [Max Zwiessele] -* New getters and setters for self.params, added m['var'] getter and setter. [Max Zwiessele] +* New getters and setters for self.params, added m['var'] getter and setter. [Max Zwiessele] * Merge devel into mrd. [Max Zwiessele] -* Pull branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] +* Pull branch 'devel' of github.com:SheffieldML/GPy into devel. [Max Zwiessele] * More re-enstating of some preiov commits. [James Hensman] @@ -10166,7 +10252,7 @@ * Re-added indepenent_output kern. [James Hensman] -* Added m['ard'] gives all parameters matching 'ard', as well as setting m['ard'] = x to set all mrd parameters. [Max Zwiessele] +* Added m['ard'] gives all parameters matching 'ard', as well as setting m['ard'] = x to set all mrd parameters. [Max Zwiessele] * Stupid kern stash merge. [Max Zwiessele] @@ -10176,7 +10262,7 @@ * Psi_stat_test stash. [Max Zwiessele] -* Merge branch 'devel' into mrd. [Max Zwiessele] +* Merge branch 'devel' into mrd. [Max Zwiessele] * Bugfix: cross term psi1 bias + linear. [Max Zwiessele] @@ -10184,11 +10270,11 @@ * Moved *2. of psi2 statistics into kern and corrected bias+linear cross term. [Max Zwiessele] -* Merge branch 'devel' into mrd. [Max Zwiessele] +* Merge branch 'devel' into mrd. [Max Zwiessele] * Psi stat tests done and failing gracefully. [Max Zwiessele] -* Revert "merge devel mrd" [Max Zwiessele] +* Revert "merge devel mrd" [Max Zwiessele] This reverts commit 3f625a9347fde47625f14898c0a3a6ed4f49b55a, reversing changes made to dc6faeb30355bf9c6f0f3694e8546bcdf26372a8. @@ -10214,37 +10300,37 @@ * Made the basic GP class use dtrtrs where possible. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [James Hensman] * A litle more stability in svigp. [James Hensman] Another instance of dpotrs instead of dot -* Merge branch 'mrd' of github.com:SheffieldML/GPy into mrd. [Max Zwiessele] +* Merge branch 'mrd' of github.com:SheffieldML/GPy into mrd. [Max Zwiessele] * Xticklabels improved. [Max Zwiessele] * Psi stat tests. [Max Zwiessele] -* Merge branch 'devel' into mrd. [Max Zwiessele] +* Merge branch 'devel' into mrd. [Max Zwiessele] * Pdinv passes extra args to jitchol. [andreas] * Demo changed, bgplvm still broken. [Max Zwiessele] -* BGPLVM still failing, doesn't seem to be numerical : ( [Max Zwiessele] +* BGPLVM still failing, doesn't seem to be numerical : ( [Max Zwiessele] -* Merge branch 'devel' into mrd. [Max Zwiessele] +* Merge branch 'devel' into mrd. [Max Zwiessele] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] * Small changes. [Nicolo Fusi] -* Merge branch 'mrd' into devel. [Nicolo Fusi] +* Merge branch 'mrd' into devel. [Nicolo Fusi] * Removed useless _set_params() [Nicolo Fusi] -* Merge branch 'mrd' into devel. [Nicolo Fusi] +* Merge branch 'mrd' into devel. [Nicolo Fusi] * Small changes. [Nicolo Fusi] @@ -10252,9 +10338,9 @@ * Added bgplvm_simulation on same simulation. [Max Zwiessele] -* Merge branch 'devel' into mrd. [Max Zwiessele] +* Merge branch 'devel' into mrd. [Max Zwiessele] -* Merge branch 'mrd' into devel. [Max Zwiessele] +* Merge branch 'mrd' into devel. [Max Zwiessele] * Comments only. [James Hensman] @@ -10262,7 +10348,7 @@ Specifically in computing dL_dKmm -* Rbf computation of psi2 now works if there's only one datum. [James Hensman] +* Rbf computation of psi2 now works if there's only one datum. [James Hensman] * Reverting last change. [Ricardo] @@ -10294,7 +10380,7 @@ * New functions mrd init_X update. [Max Zwiessele] -* Merge branch 'devel' into mrd. [Max Zwiessele] +* Merge branch 'devel' into mrd. [Max Zwiessele] * Fixed merge conflict on BPGLVM. [Nicolo Fusi] @@ -10322,9 +10408,9 @@ * Merged master back into devel (to sync bugfixes) [Nicolo Fusi] -* Merge branch 'master' into devel. [Nicolo Fusi] +* Merge branch 'master' into devel. [Nicolo Fusi] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Nicolo Fusi] * Pdinv now uses dpotri instead of dtrtri and dot. [James Hensman] @@ -10342,17 +10428,17 @@ * Merged local branch. [Nicolo Fusi] -* Merge branch 'new_warping' [Nicolo Fusi] +* Merge branch 'new_warping' [Nicolo Fusi] -* Merge branch 'master' into new_warping. [Nicolo Fusi] +* Merge branch 'master' into new_warping. [Nicolo Fusi] * Changed prediction code. [Nicolo Fusi] -* Merge branch 'devel' into new_warping. [Nicolo Fusi] +* Merge branch 'devel' into new_warping. [Nicolo Fusi] -* Merge branch 'devel' into new_warping. [Nicolo Fusi] +* Merge branch 'devel' into new_warping. [Nicolo Fusi] -* Merge branch 'master' into new_warping. [Nicolo Fusi] +* Merge branch 'master' into new_warping. [Nicolo Fusi] * Changed version. [Nicolo Fusi] @@ -10368,7 +10454,7 @@ * Minor. [Nicolo Fusi] -* Merge branch 'master' into new_warping. [Nicolo Fusi] +* Merge branch 'master' into new_warping. [Nicolo Fusi] * Added a term to warping function. [Nicolo Fusi] @@ -10378,9 +10464,9 @@ * Changed version number in setup.py. [James Hensman] -* Merge branch 'devel' [James Hensman] +* Merge branch 'devel' [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] * Added (optional) iter param dump. [Nicolo Fusi] @@ -10396,9 +10482,9 @@ * Mrd touches. [Max Zwiessele] -* Merge remote-tracking branch 'origin' into mrd. [Max Zwiessele] +* Merge remote-tracking branch 'origin' into mrd. [Max Zwiessele] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] * Bug fixed in periodic kernels: Warning were not handled properly. [Nicolas] @@ -10414,7 +10500,7 @@ * Added simple BGPLVM_oil demo. [James Hensman] -* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo Andrade] +* Merge branch 'devel' of github.com:SheffieldML/GPy into devel. [Ricardo Andrade] * Yak shaving. [James Hensman] @@ -10436,19 +10522,19 @@ * Changes in FITC approximation computation. [Ricardo Andrade] -* Merge branch 'fitc' into devel. [Ricardo Andrade] +* Merge branch 'fitc' into devel. [Ricardo Andrade] * Not needed. [Ricardo Andrade] * Small changes. [Ricardo Andrade] -* Merge branch 'em_fix' into fitc. [Ricardo Andrade] +* Merge branch 'em_fix' into fitc. [Ricardo Andrade] * Print iteration number. [Ricardo Andrade] * Minor changes. [Ricardo Andrade] -* Merge branch 'master' into fitc. [Ricardo Andrade] +* Merge branch 'master' into fitc. [Ricardo Andrade] * Generalized fitc + examples. [Ricardo Andrade] @@ -10458,19 +10544,19 @@ * Rbf now works in a more memory friendly fashion. [James Hensman] -* Merge branch 'master' into devel. [James Hensman] +* Merge branch 'master' into devel. [James Hensman] * Insignificant but annoying bug corrected. [Ricardo Andrade] * Pseudo EM algorithm for EP and maybe Laplace. [Ricardo Andrade] -* Merge branch 'master' into devel. [Nicolo Fusi] +* Merge branch 'master' into devel. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] * More fixing of the predictive variance (correct for full_cov now) [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] * Corrected the predictive variance for Gaussian likelihoods. [James Hensman] @@ -10478,17 +10564,17 @@ * Added fixed effect kernel. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] -* Merge branch 'debug' [James Hensman] +* Merge branch 'debug' [James Hensman] * Increased stability of _compuations in sparse_GP. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] * The warnings are now handeled properly in the periodic kernels. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] * Errors handled in Mat32. [Nicolas] @@ -10510,19 +10596,19 @@ * Fixed trace_dot to be a litle faster... [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] * Non working integratino of SCG into GPy. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] * Fixed bug in dK_dX for the quadratic kernel. [Nicolas] * Added SCG code. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] * Updated list of implemented kernels in the documentation. [Nicolas] @@ -10530,25 +10616,25 @@ * Typo in comments. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] * More messing with the linear algebra in sparse_GP. [James Hensman] -* Some messing with the linear algebra in sparse_GP. This should be more efficient... let's hope nothing breaks. [James Hensman] +* Some messing with the linear algebra in sparse_GP. This should be more efficient... let's hope nothing breaks. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] * Added trace_sum for efficiency. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] -* Merge branch 'master' of github.com:SheffieldML/GPy. [andreas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [andreas] * Tie_param changed to tie_params in tutorials. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] * Few bugs fixed in the documentation. [Nicolas] @@ -10558,17 +10644,17 @@ * Deactivated test_models() [Nicolo Fusi] -* T push :qMerge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* T push :qMerge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] * Fixed checkgrad test to randomize before checking. [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] * Got rid of foo. [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] * Trying to shuffle. [Alan Saul] @@ -10578,27 +10664,27 @@ * Added test generator (not quite finished yet) [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] * Changed example tests. [Alan Saul] * Fixed bug in RBF, added inducing inputs to BGPLVM plots. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] * Example fixed. [Ricardo Andrade] * Update in the rational quadratic kernel and new the tutorial on writting kernels. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] * New rational quadratic kernel. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] * Small changes. [Nicolas] @@ -10608,7 +10694,7 @@ * Changes tie_param to tie_params. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] * Setup.py requires nose now. [James Hensman] @@ -10616,11 +10702,11 @@ * Temporarily removed a test (linear X bias) [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] -* Implemented psi2 'cross terms' for rbfXbias. [James Hensman] +* Implemented psi2 'cross terms' for rbfXbias. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] * A small demo for model tutorial. [James Hensman] @@ -10628,7 +10714,7 @@ * Examples working. [Ricardo Andrade] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] Conflicts: GPy/examples/__init__.py @@ -10639,29 +10725,29 @@ * Adding testing file for examples. [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] -* Example files for tutorials are now in Neil's format. [Nicolas] +* Example files for tutorials are now in Neil's format. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] * Added init. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] * Removed unused partial1. [Alan Saul] * Update in the documentation on kernel implementation. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] -* Now running nosetest doesn't run unittests twice. [Nicolo Fusi] +* Now running nosetest doesn't run unittests twice. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] * Added GPy.tests(), removed some useless tests. [Nicolo Fusi] @@ -10671,9 +10757,9 @@ * Fixed merge conflicts. [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] -* Added the outline of a tutorial on 'interacting with models' [James Hensman] +* Added the outline of a tutorial on 'interacting with models' [James Hensman] * Skipping a test known to fail (linear sparse) [James Hensman] @@ -10689,7 +10775,7 @@ * Examples directory organized. [Ricardo Andrade] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] * Draft of documentation for implemented kernels. [Nicolas] @@ -10697,11 +10783,11 @@ * Draft of documentation for implemented kernels. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] * Sometidying of the psi statistic cross terms. [James Hensman] @@ -10711,7 +10797,7 @@ * All the product_orthogonal have been changed to prod_orthogonal for consistency. [Nicolas] -* Merge branch 'fixEP' [Ricardo Andrade] +* Merge branch 'fixEP' [Ricardo Andrade] * Generalized_FITC removed. [Ricardo Andrade] @@ -10727,9 +10813,9 @@ * Some small changes. [Ricardo Andrade] -* Merge branch 'master' of github.com:SheffieldML/GPy into genFITC. [Ricardo Andrade] +* Merge branch 'master' of github.com:SheffieldML/GPy into genFITC. [Ricardo Andrade] -* Merge branch 'master' of github.com:SheffieldML/GPy into genFITC. [Ricardo Andrade] +* Merge branch 'master' of github.com:SheffieldML/GPy into genFITC. [Ricardo Andrade] * Sparse GP with EP is working now. [Ricardo Andrade] @@ -10745,7 +10831,7 @@ * JH bugfix for slices. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] * Using setuptools instead of distutils. [Max Zwiessele] @@ -10761,7 +10847,7 @@ * Added symmtrical covariance functions. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] * Added dKdiag_dtheta for linear. [James Hensman] @@ -10779,7 +10865,7 @@ * Added optional number of contour levels to the 2D plotting in GP.plot. [James Hensman] -* Some commentary on Neil's notes.txt. [James Hensman] +* Some commentary on Neil's notes.txt. [James Hensman] * Effiiency improvements in sparse_GP. [James Hensman] @@ -10798,7 +10884,7 @@ * Some bugfixes that have affected GPLVM/sparseGPLVM since the hetero noise change. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] * Tutorial improved (and finished) [Nicolas] @@ -10826,19 +10912,19 @@ * Small changes to the lengthscales such that the periodic kernels can be called as the non-periodic ones. [Nicolas] -* Fixed the bug where we couldn't tie parameters at the kern level. [James Hensman] +* Fixed the bug where we couldn't tie parameters at the kern level. [James Hensman] * Added target_param option to checkgrad(), removed unused function parameter. [Nicolò Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolò Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolò Fusi] * Made the name of the Gaussian noise variance noise_variance, for consistency. [James Hensman] * Changes to the uncollapsed GP. [James Hensman] -* Bugfixin' [James Hensman] +* Bugfixin' [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] * Added a set_data method to the Gaussian likelihood. [James Hensman] @@ -10846,11 +10932,11 @@ * Added contribution from the prior to marginal LL printed in the model __str__ [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] * Fixed a bug in sparse GP relating to the psi representation. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] * Reinsert the plot function for kernel that diserpered at one point... [Nicolas] @@ -10862,9 +10948,9 @@ * All kernels working fine with the psi statistics now. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] -* Merge branch 'debug_bias' [James Hensman] +* Merge branch 'debug_bias' [James Hensman] * Fixed bug with the bias kernel. [James Hensman] @@ -10904,23 +10990,23 @@ * Try installing with pip? eek... [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] * Few changes to tutorial bis. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] * Few changes to tutorial. [Nicolas] -* New tutorial draft called 'A kernel overview' [Nicolas] +* New tutorial draft called 'A kernel overview' [Nicolas] * Trying to get plotting working. [Alan Saul] * About to exchange sphinxext. [Alan Saul] -* Added matplotlib test, probably won't work. [Alan Saul] +* Added matplotlib test, probably won't work. [Alan Saul] * Fixed typo. [Alan Saul] @@ -10950,7 +11036,7 @@ * With insert. [Alan Saul] -* Changed path back, think we're closer when its in. [Alan Saul] +* Changed path back, think we're closer when its in. [Alan Saul] * Appended path. [Alan Saul] @@ -10972,9 +11058,9 @@ * Again playing with relative to absolute paths, test. [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] * Broken file removed until new notice. [Ricardo Andrade] @@ -10986,11 +11072,11 @@ * Adding more paths...: [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Ricardo Andrade] * Bug found and fixed in plots for normalized X. [Ricardo Andrade] @@ -11068,7 +11154,7 @@ * Various merge conflicts from the newGP branch. [James Hensman] -* Merge branch 'newGP' [James Hensman] +* Merge branch 'newGP' [James Hensman] Conflicts: GPy/models/GP_regression.py @@ -11083,34 +11169,34 @@ * Partial derivatives for the new likelihood framework. [James Hensman] -* Merge branch 'newGP' of github.com:SheffieldML/GPy into newGP. [Ricardo Andrade] +* Merge branch 'newGP' of github.com:SheffieldML/GPy into newGP. [Ricardo Andrade] * Made the BGPLVM work in the new world order. [James Hensman] * Changes in plotting functions. [Ricardo Andrade] -* Merge branch 'newGP' of github.com:SheffieldML/GPy into newGP. [James Hensman] +* Merge branch 'newGP' of github.com:SheffieldML/GPy into newGP. [James Hensman] * Classification examples corrected (2/3) [Ricardo Andrade] -* Merge branch 'newGP' of github.com:SheffieldML/GPy into newGP. [Ricardo Andrade] +* Merge branch 'newGP' of github.com:SheffieldML/GPy into newGP. [Ricardo Andrade] * EPEM is running. [Ricardo Andrade] * Assorted work on combining the EP and sparse methods. [James Hensman] -* Merge branch 'newGP' of github.com:SheffieldML/GPy into newGP. [James Hensman] +* Merge branch 'newGP' of github.com:SheffieldML/GPy into newGP. [James Hensman] Conflicts: GPy/likelihoods/EP.py -* James' debugging of the EP/GP interface. [Ricardo Andrade] +* James' debugging of the EP/GP interface. [Ricardo Andrade] It seems that the GP-EP algorithm works now. * Merged changes in likelihood_functions (James) [Ricardo Andrade] -* Merge branch 'newGP' of github.com:SheffieldML/GPy into newGP. [Ricardo Andrade] +* Merge branch 'newGP' of github.com:SheffieldML/GPy into newGP. [Ricardo Andrade] Conflicts: GPy/likelihoods/EP.py @@ -11118,11 +11204,11 @@ * So many changes. [Ricardo Andrade] -* Merge branch 'newGP' of github.com:SheffieldML/GPy into newGP. [Ricardo Andrade] +* Merge branch 'newGP' of github.com:SheffieldML/GPy into newGP. [Ricardo Andrade] * Predictive_values implemented in EP. [Ricardo Andrade] -* Beginning of work to make sparse GP ork with RA's EP methods. [James Hensman] +* Beginning of work to make sparse GP ork with RA's EP methods. [James Hensman] * Added a likelihood atom class. [James Hensman] @@ -11140,11 +11226,11 @@ * Added a Gaussian likelihood class. [James Hensman] -* Merge branch 'newGP' of github.com:SheffieldML/GPy into newGP. [James Hensman] +* Merge branch 'newGP' of github.com:SheffieldML/GPy into newGP. [James Hensman] * Changed docs back for newGP. [Alan Saul] -* Merge branch 'newGP' of github.com:SheffieldML/GPy into newGP. [Alan Saul] +* Merge branch 'newGP' of github.com:SheffieldML/GPy into newGP. [Alan Saul] * Trying to fix docs, might break them. [Alan Saul] @@ -11154,7 +11240,7 @@ * Merged conflicts after merging in master to newGP branch. [James Hensman] -* Merge remote-tracking branch 'Falkor/newGP' into newGP. [Ricardo Andrade] +* Merge remote-tracking branch 'Falkor/newGP' into newGP. [Ricardo Andrade] * Working for regression, still some bugs for EP. [Ricardo Andrade] @@ -11164,7 +11250,7 @@ * More changes. [Ricardo Andrade] -* Merge remote-tracking branch 'Falkor/newGP' into newGP. [Ricardo Andrade] +* Merge remote-tracking branch 'Falkor/newGP' into newGP. [Ricardo Andrade] * Minor changes. [Ricardo Andrade] @@ -11174,13 +11260,13 @@ * Now it works. [Ricardo Andrade] -* Merge remote-tracking branch 'Falkor/newGP' into newGP. [Ricardo Andrade] +* Merge remote-tracking branch 'Falkor/newGP' into newGP. [Ricardo Andrade] * Minor change in EM explanation. [Ricardo Andrade] -* Merge branch 'newGP' [Ricardo Andrade] +* Merge branch 'newGP' [Ricardo Andrade] -* Merge remote-tracking branch 'Falkor/newGP' into newGP. [Ricardo Andrade] +* Merge remote-tracking branch 'Falkor/newGP' into newGP. [Ricardo Andrade] * Other change. [Ricardo Andrade] @@ -11194,11 +11280,11 @@ * Other changes. [Ricardo Andrade] -* Merge remote-tracking branch 'Falkor/newGP' into newGP. [Ricardo Andrade] +* Merge remote-tracking branch 'Falkor/newGP' into newGP. [Ricardo Andrade] * Sparse EP. [Ricardo] -* Merge branch 'master' into newGP. [Ricardo Andrade] +* Merge branch 'master' into newGP. [Ricardo Andrade] * No more GP_EP stuff. [Ricardo Andrade] @@ -11218,13 +11304,13 @@ * Small fixes in the kernel documentation. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] * Small changes in the way covariance functions handle lengthscale as input. [Nicolas] * Working on linear kernel. [Nicolò Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] * Reverted back to working docs. [Alan Saul] @@ -11258,7 +11344,7 @@ * Added plot_directive and mathmpl extensions. [Alan Saul] -* Got rid of some extensions we're not sure we're using. [Alan Saul] +* Got rid of some extensions we're not sure we're using. [Alan Saul] * Added extensions for inline doc plotting. [Alan Saul] @@ -11282,7 +11368,7 @@ * Changed default ARD setting in linear. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] * Added path higher. [Alan Saul] @@ -11290,19 +11376,19 @@ * Moved mock into docs. [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] * Added mock file. [Alan Saul] * Added mock to dependencies for docs. [Alan Saul] -* "fixed" Tango imports. [Nicolo Fusi] +* "fixed" Tango imports. [Nicolo Fusi] * Changed travis conf. [Nicolo Fusi] * Useless commit to get travis-ci started. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] * More. [Alan Saul] @@ -11344,7 +11430,7 @@ * Removed matplotlib mock. [Alan Saul] -* Adding extra mock... hopefully this won't carry on. [Alan Saul] +* Adding extra mock... hopefully this won't carry on. [Alan Saul] * Forgot exceptions import. [Alan Saul] @@ -11382,21 +11468,21 @@ * Minor changes. [Nicolo Fusi] -* Merge branch 'master' into SGD. [Nicolo Fusi] +* Merge branch 'master' into SGD. [Nicolo Fusi] * Convenience change in linear.py. [Nicolo Fusi] * Made SGD work with new get/set param. [Nicolo Fusi] -* Merge branch 'master' into SGD. [Nicolo Fusi] +* Merge branch 'master' into SGD. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] * Robustified the assertion re lengthscales in rbf. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] * Fixed bug in rbf.py, removed the ARD moniker from the name variable. [James Hensman] @@ -11406,9 +11492,9 @@ * Improved tutorial for GP_regression. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] * Added missing dataset from mlprojects. [James Hensman] @@ -11420,7 +11506,7 @@ ... and removed a nasty hard link in the examples file -* New operator: the kernels can be multiplied directly with the '*' character. [Nicolas] +* New operator: the kernels can be multiplied directly with the '*' character. [Nicolas] * Some more documentation documentation on the index page. [Nicolas] @@ -11456,7 +11542,7 @@ * Untabified priors.py. [Nicolò Fusi] -* Merge branch 'periodic' [Nicolas] +* Merge branch 'periodic' [Nicolas] * Few bugs fixed in periodic kernels. [Nicolas] @@ -11466,7 +11552,7 @@ * Missing scale and location arguments. [Ricardo] -* Golden serach and Simpson's rule explained. [Ricardo] +* Golden serach and Simpson's rule explained. [Ricardo] * Test. [Ricardo Andrade] @@ -11474,7 +11560,7 @@ * TODO added. [Ricardo Andrade] -* Merge remote-tracking branch 'rick70x7/master' [Ricardo Andrade] +* Merge remote-tracking branch 'rick70x7/master' [Ricardo Andrade] * Poisson and Gaussian likelihood. [Ricardo Andrade] @@ -11486,19 +11572,19 @@ * Added some documentation and example files. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] * Added path for RTD. [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] * Updated index.rst. [Alan Saul] * Restored examples folder. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] * Merged trivial conflict. [James Hensman] @@ -11506,13 +11592,13 @@ * Delete unnecessary rbf_ARD.py. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] * Added sympy dependency and scipy version dependency again. [Alan Saul] * Trying to give pylab dependency. [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] * Added unsupervised.py examples file and datasets.py@ [Neil Lawrence] @@ -11522,33 +11608,33 @@ * Tried fixing build call. [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] * Tried changing the location of the apidoc compilation. [Alan Saul] * Bug fixed in example (in regression.py) [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] * Adding old command I read on the internet for own build. [Alan Saul] * Adding fake kernel to test docs. [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] * Testing docs more. [Alan Saul] * More tests in unit_tests. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] * Trying to get ReadTheDocs to recompile for us. [Alan Saul] * Last ARD flag changes to kernels. [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] * Mods to regression.py now that we have get to get parameters. Moved Youter to YYT. [Neil Lawrence] @@ -11564,19 +11650,19 @@ * Fix error introduced into GP_regression when doing name changes. [Neil Lawrence] -* Merge branch 'master' of https://github.com/SheffieldML/GPy. [Neil Lawrence] +* Merge branch 'master' of https://github.com/SheffieldML/GPy. [Neil Lawrence] * Removed version specification of scipy. [Alan Saul] * Removed latent force model fortran code from setup.py from github code. [Alan Saul] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Alan Saul] * Added apt-get scipy installation for travis, need to ensure version. [Alan Saul] * Expand_param and extract_param replaced with set_params_transformed and get_params_transformed. [Neil Lawrence] -* Merge branch 'master' of https://github.com/SheffieldML/GPy. [Neil Lawrence] +* Merge branch 'master' of https://github.com/SheffieldML/GPy. [Neil Lawrence] * Fixed version setting for numpy scipy installatioN. [Alan Saul] @@ -11592,7 +11678,7 @@ * Minor changes. [Nicolo Fusi] -* Merge branch 'bgplvm' into SGD. [Nicolo Fusi] +* Merge branch 'bgplvm' into SGD. [Nicolo Fusi] * Working on cross terms. [Nicolo Fusi] @@ -11632,13 +11718,13 @@ * Some code to debug the sprase GP gradients with. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy into debug. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy into debug. [James Hensman] * Parameters gridding with checkgrad to aid debugging. [James Hensman] * Fixed index. [Nicolo Fusi] -* Merge branch 'master' into SGD. [Nicolo Fusi] +* Merge branch 'master' into SGD. [Nicolo Fusi] * Pretty printing of gradchecks. [Nicolo Fusi] @@ -11646,11 +11732,11 @@ * Removed unused posix import. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] * Fixed a NF induced bug in the guts of GPy. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] * Sphinx configuratino for readthedocs.org. [James Hensman] @@ -11672,19 +11758,19 @@ * Added a constructor for a generic sympy kernel. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] * Made sympykern truly work in place. [James Hensman] * Removed dL_dZ from sympykern. [James Hensman] - (it's not needed, we can always use dK_dX) + (it's not needed, we can always use dK_dX) * Added demo for uncollapsed GP. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] -* Added Alan's bugfix to this version of GPy: [James Hensman] +* Added Alan's bugfix to this version of GPy: [James Hensman] sympykern is now forced to recompile if the function changes. @@ -11694,9 +11780,9 @@ * Tidied upt he kwargs in sympykern. [James Hensman] -* Merge branch 'sympykern' [James Hensman] +* Merge branch 'sympykern' [James Hensman] -* Added sympykern as a 'kernpart' object. [James Hensman] +* Added sympykern as a 'kernpart' object. [James Hensman] now we can add sympykerns to any other kern @@ -11732,11 +11818,11 @@ * Fixed interface change in optimization.py. [Nicolo Fusi] -* Added autodection of Rasmussen's minimize. [Nicolo Fusi] +* Added autodection of Rasmussen's minimize. [Nicolo Fusi] -* Merge branch 'master' into SGD. [Nicolo Fusi] +* Merge branch 'master' into SGD. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] * Added notes on issues found. [Neil Lawrence] @@ -11760,7 +11846,7 @@ * Some tidying in the EP code. [James Hensman] -* Removed uncertain gp regression from the model __init__, since it's now just a switch in the sparse GP. [James Hensman] +* Removed uncertain gp regression from the model __init__, since it's now just a switch in the sparse GP. [James Hensman] * Fixed SGD to work with new interface. [Nicolo Fusi] @@ -11770,7 +11856,7 @@ * Working implementation of SGD. [Nicolo Fusi] -* GPLVM accepts an initial value for X (in case you don't want to use the default random/PCA init) [Nicolo Fusi] +* GPLVM accepts an initial value for X (in case you don't want to use the default random/PCA init) [Nicolo Fusi] * Now passing a reference of the model to the optimizer (used in SGD) [Nicolo Fusi] @@ -11778,7 +11864,7 @@ * Fixed import error for examples and import error for uncertain inputs GP. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] * Merge changes for model.py and optimization.py on comments. [Neil Lawrence] @@ -11790,11 +11876,11 @@ * Made uncertain inputs a simple swith in the sparse GP class. This simplifies the inherritance structure. [James Hensman] -* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] +* Merge branch 'master' of github.com:SheffieldML/GPy. [James Hensman] * Rbf_ARD now in the updated format for the computation of the derivatives (included for the psi-statistics, but not tested) [Nicolas] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolas] * GPy: Some rewriting for the exponential and Matern kernels. They now pass the unit test. [Nicolas] @@ -11815,7 +11901,7 @@ * Fixed bug in GP_regression. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] * Derivatives of the exponential kernel in the right format. [Nicolas] @@ -11823,9 +11909,9 @@ * Fixed bug in linear_ARD. [Nicolo Fusi] -* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] +* Merge branch 'master' of github.com:SheffieldML/GPy. [Nicolo Fusi] -* Added vim's swp files to gitignore. [James Hensman] +* Added vim's swp files to gitignore. [James Hensman] * Demo for GP regressio with uncertain inputs. [James Hensman] From aa0a7bcb414a154a36f39f413ff8c8e197c0a835 Mon Sep 17 00:00:00 2001 From: mzwiessele Date: Sun, 2 Sep 2018 21:29:08 +0100 Subject: [PATCH 46/48] new: Student-t processes #525 --- GPy/models/tp_regression.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GPy/models/tp_regression.py b/GPy/models/tp_regression.py index 3ed102a6c..56ecf4b55 100644 --- a/GPy/models/tp_regression.py +++ b/GPy/models/tp_regression.py @@ -11,7 +11,7 @@ import numpy as np from scipy import stats from paramz import ObsAr -from paramz.transformations import Logistic, Logexp, LogexpClipped +from paramz.transformations import Logexp import warnings From 0da02ff3fe330a549a1ac9b0ae06ac42ee8b1b89 Mon Sep 17 00:00:00 2001 From: mzwiessele Date: Sun, 2 Sep 2018 22:50:17 +0100 Subject: [PATCH 47/48] =?UTF-8?q?Bump=20version:=201.9.4=20=E2=86=92=201.9?= =?UTF-8?q?.5?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- GPy/__version__.py | 2 +- appveyor.yml | 2 +- setup.cfg | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/GPy/__version__.py b/GPy/__version__.py index 844520399..96974ae13 100644 --- a/GPy/__version__.py +++ b/GPy/__version__.py @@ -1 +1 @@ -__version__ = "1.9.4" +__version__ = "1.9.5" diff --git a/appveyor.yml b/appveyor.yml index cf4f70968..9530ebbe1 100644 --- a/appveyor.yml +++ b/appveyor.yml @@ -3,7 +3,7 @@ environment: secure: 8/ZjXFwtd1S7ixd7PJOpptupKKEDhm2da/q3unabJ00= COVERALLS_REPO_TOKEN: secure: d3Luic/ESkGaWnZrvWZTKrzO+xaVwJWaRCEP0F+K/9DQGPSRZsJ/Du5g3s4XF+tS - gpy_version: 1.9.4 + gpy_version: 1.9.5 matrix: - PYTHON_VERSION: 2.7 MINICONDA: C:\Miniconda-x64 diff --git a/setup.cfg b/setup.cfg index 76f82425d..97aa7a389 100644 --- a/setup.cfg +++ b/setup.cfg @@ -1,5 +1,5 @@ [bumpversion] -current_version = 1.9.4 +current_version = 1.9.5 tag = True commit = True From 0c6438608d591c99a51d5097a434db9f1b94253c Mon Sep 17 00:00:00 2001 From: mzwiessele Date: Sun, 2 Sep 2018 22:50:42 +0100 Subject: [PATCH 48/48] pkg: changelog --- CHANGELOG.md | 35 +++++++++++++++++++++++++++++++++++ 1 file changed, 35 insertions(+) diff --git a/CHANGELOG.md b/CHANGELOG.md index 2428ddb12..c18a81d74 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,6 +1,41 @@ # Changelog +## v1.9.5 (2018-09-02) + +### New + +* Student-t processes #525. [mzwiessele] + +### Fix + +* Merge #514. [mzwiessele] + +* Merge. [mzwiessele] + +### Other + +* Bump version: 1.9.4 → 1.9.5. [mzwiessele] + +* SDE: removed some unnecessary comments. [Alex Grigorievskiy] + +* SDE: Remove sde kernels from the _src folder. [Alex Grigorievskiy] + +* STATE-SPACE: Recent modifications to state-space inference, including bug fixes in state-space kernels. [Alex Grigorievskiy] + +* TEST: Correcting message for test skipping. This is normal that this test does not work and hence skipped. [Alex Grigorievskiy] + +* Solved incorrect parameter assignments (causing test faillure) [Joachim van der Herten] + +* Added some shifts to the degrees of freedom parameter. [Joachim van der Herten] + +* Removal of print statements. [Joachim van der Herten] + +* Implementation of student-t processes. [Joachim van der Herten] + +* Pkg: changelog. [mzwiessele] + + ## v1.9.4 (2018-09-02) ### Fix

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